Abstract
Corn or maize (Zea mays L.) is the most significant grain crop worldwide after wheat and rice. It is widely cultivated and consumed as food, feed, and industrial raw material, along with the emission of a large quantity of corn waste. Such abundant, renewable, and cheap wastes with unique chemical compositions can be efficiently converted into adsorbents for the elimination of dye-contaminated water. This article represents an extensive review of the use of corn/maize waste-derived adsorbents for the sequestration of dyes from aqueous media. This study addressed the utilization of corn residues, including cob, stalk, straw, husk, and silk, as precursors for adsorbents. The adsorption behaviour, mechanism, and regeneration of the studied corn adsorbent/dye systems were identified. It was observed that the most common forms of corn/maize-derived adsorbents that have been utilized for the sequestration of dyes include biosorbents, biochars, activated carbons, and composites. The highest adsorption capacity (1,682.7 mg/g) for dye (methylene blue) sequestration was obtained using a corn husk composite-based adsorbent. Important findings and future ideas are finally mentioned for the corn/maize-based materials and their application as adsorbents for dye removal.
HIGHLIGHTS
Use of corn adsorbents strengthens the popular waste-to-wealth management strategy.
The adsorbent groups include biosorbents, activated carbons, biochar, and composites.
Major mechanisms are electrostatic attraction, ion exchange, and hydrogen bonding.
The adsorbents can be recycled and reused several times.
The highest adsorption capacity (1,682.7 mg/g) was obtained using a corn husk-based composite.
INTRODUCTION
The discharge of contaminants from agricultural, industrial, and municipal activities has a significant impact on public health and aquatic environments (Iwuozor et al. 2022a; Omuku et al. 2022). These contaminants include substances such as dyes, heavy metals, pesticides, pharmaceuticals, and phenolic compounds, among others (Zhul-quarnain et al. 2018; Adeniyi et al. 2022). Dyes are widely used in various industries such as textiles, leather, paper, and food, and their use has led to the release of substantial amounts of dye-containing wastewater into the environment (Abubakar & Batagarawa 2017; Abdullah et al. 2019). Dye contamination in the environment has become a significant environmental issue due to its toxicity, carcinogenicity, and mutagenicity (Yaneva & Georgieva 2013). These contaminants can have harmful impacts on the ecosystem, aquatic life, and human health. Dye contamination in the environment can affect water quality, leading to a decrease in oxygen levels and the accumulation of toxic substances that can result in the death of aquatic life (Abubakar & Batagarawa 2017; Ranjbar et al. 2022). Dye-contaminated water can also affect soil quality, leading to soil degradation, reduced crop productivity, and environmental pollution (Abdel-Aal et al. 2006; Zolgharnein et al. 2016; Ali et al. 2017). Conventional treatment methods for removing dyes from wastewater, such as physical, chemical, and biological techniques, have limitations and can be expensive. As a result, researchers have turned to alternative, cost-effective, and eco-friendly methods for the removal of dyes from aqueous media. Numerous methods have been developed to remove dyes from wastewater, such as adsorption, coagulation, and advanced oxidation processes (Balathanigaimani et al. 2009; Chen et al. 2011, 2020; Chang et al. 2021). Among these methods, adsorption has gained considerable attention as a simple, cost-effective, and efficient process (Abubakar & Batagarawa 2017; Ali et al. 2017). The use of adsorbents derived from natural materials, such as maize/corn-based adsorbents, has emerged as a promising approach for dye removal due to their abundance, low cost, and eco-friendly nature.
Corn or maize is a widely cultivated crop, and its by-products, including husks, cobs, stalks, and leaves, generate significant waste (Mu et al. 2020). These wastes are often left in the field, which can result in environmental issues such as soil degradation and pollution of water resources. In addition, the burning of corn waste in some regions can lead to air pollution and contribute to greenhouse gas emissions (Zheng et al. 2010; Zhao et al. 2014). In recent years, there has been a growing interest in utilizing corn waste as a sustainable and cost-effective solution to address these environmental issues. One promising approach is to convert corn waste into valuable products such as biofuels, biogas, and biodegradable plastics (Kamusoko et al. 2021). For instance, the fermentation of corn waste can produce biogas, which can be used as a renewable energy source for electricity generation and heating. Maize/corn-based adsorbents have recently emerged as a promising alternative for the sequestration of dyes from aqueous media due to their abundance, low cost, renewability, and biodegradability (Rehl et al. 2012). These adsorbents have shown high adsorption capacities for various types of dyes, including synthetic and natural dyes, and have the potential to be used in large-scale wastewater treatment systems.
From the literature survey, it was found that there are a number of review articles that studied the application of corn/maize-based adsorbents for the treatment of water, but none of them were specific on the utilization of the adsorbents for the removal of dyes from aqueous media. For instance, the application of corn cob-based adsorbents for the treatment of heavy metals and dyes has been reviewed (Arquilada et al. 2018). Another study discussed the adsorption of specific aquatic pollutants, with a focus on heavy metals, by corn waste-based adsorbents (Sharma et al. 2019). Also, the pesticide adsorption on biochar derived from maize, rice, and wheat residues has been studied (Ogura et al. 2021). However, these reviews were specific and did not address the synthesis, properties, performance, and reusability of corn/maize-based adsorbents for dye sequestration in detail. This critical review aims to analyse the existing literature on the use of maize/corn-based adsorbents for the sequestration of dyes from aqueous media. This discusses the key aspects of adsorption processes, including adsorption mechanisms, adsorbent preparation, and the effect of various parameters such as pH, temperature, and contact time on the adsorption capacity. Furthermore, regeneration and reusability studies and competitive adsorption were discussed. Moreover, this review will also highlight the challenges and limitations of maize/corn-based adsorbents and identify future research directions to improve their efficiency. The review is restricted to only articles published in the literature in the past 10 years, and only articles published in English were considered.
PREPARATION OF MAIZE/CORN-BASED ADSORBENT
UM adsorbent/maize biosorbent
UM adsorbents are usually prepared by washing the as-collected maize matrix with H2O to remove dirt, followed by drying under the shade, in sunlight, in an oven, or air-drying to remove or reduce its moisture and proliferate the active site's numerical strength for the adsorption process (Ponce et al. 2021). According to Petrović et al. (2017), the as-collected corn silk matrix obtained from planted corn was dried at 353 K, pulverized, and sieved to obtain <0.2 mm particle size. This preparation process was similar to the one carried out by Abubakar & Batagarawa (2017), Lima et al. (2018), Paşka et al. (2014), and Fadhil & Eisa (2019). However, Abubakar & Batagarawa (2017) sun dried their own maize organ (stalk) before oven drying at 65 °C for 24 h and then pounding and sieving to a mesh size of 106 μm, and this was somewhat similar to the water boiling of the plant matrix carried out by Dehvari et al. (2013) and Değermenci et al. (2019) before oven drying at 100 oC and 60 °C, respectively. The authors emphasized that the essence of boiling the plant samples mildly before proper drying is to improve adsorption. Conversely, Guyo et al. (2015) and Ibrahim (2013) air dried as-collected maize plant part samples after washing before pulverizing to the required size. Then, the maize plant sample needed to be cleansed using deionized water, dried once more to get rid of some impurities on its surface, and then sieved to obtain a smooth biosorbent with better porosity (Petrović et al. 2017).
Maize-based biochar
Biochar is a permeable pyrogenic carbonaceous material fabricated by thermal putrefaction of agricultural wastes such as maize cob, livestock mucks, and other biomass in an infinitesimal O2 supply condition without any kind of chemical or physicochemical activation (Liu et al. 2018a; Billa et al. 2019; Eltaweil et al. 2020; Iwuozor et al. 2022b). According to Eltaweil et al. (2020), Iwuozor et al. (2022b), Yang et al. (2018), Wan et al. (2018), and Maneechakr & Karnjanakom (2019), this type of adsorbent fabrication approach is a revolutionary methodology that does not only help in reducing global warming that accompany the emission of CO2 during open burning of biomass or biomass wastes but also afford the resulting adsorbent with excellent porous architecture, enhanced immunity to corrosion and degradation, availability of significant oxygen-containing organic architectural functional groups, and inexpensive fabrication budget, all of which render biochar as an eco-benign sorption candidate for the elimination or degradation of dye contaminants.
Accordingly, MBC is the product of maize matrix anoxic pyrolysis. From various reports gathered in Table 1, most of the authors (Ma et al. 2016; Gao et al. 2019; Tsamo et al. 2019; Li et al. 2019a, 2019b; Eltaweil et al. 2020; Mu et al. 2020; Zhang et al. 2020; Gao et al. 2021) prepared the MBC in a pyrolyzer/muffle furnace sustained between 300–800 oC for 120–360 min with a heating rate of 5–20 oC/min. In addition to the aforementioned harsh reactor condition, nitrogen gas is sometimes added to the biomass matrix in an effort to forefend ash formation as well as to maintain the inert environment in the pyrolyzer, owing to the fact that it has been experimentally established that the biochar yield and the explicit surface area profile are reliant on the aforementioned pyrolysis operating parameters (Gao et al. 2019; Ahmad et al. 2020; Zhang et al. 2020; Gao et al. 2021; Iwuozor et al. 2022b).
Plant parts . | Adsorbent class . | Modification/activation . | Carbonization . | Characterization . | BET SSA (m2/g) . | Yield (wt %) . | References . | |||
---|---|---|---|---|---|---|---|---|---|---|
Reagent/material . | Process . | Temp (°C) . | Heating rate (°C/min) . | Time (mins) . | ||||||
Cob | MAC | KOH | Base activation | 800 | – | 1,440 | FT-IR-ATR, SEM, XRD | – | – | Abdullah et al. (2019) |
Cob | MC | Graphene oxide | 60 | – | 120 | FT-IR, SEM | – | – | Qu et al. (2020) | |
Cob | MB | – | – | 60 | – | – | – | – | – | Qu et al. (2020) |
Cob | MAC | H3PO4 | Acid activation | 600 | – | 60 | – | – | – | Ali et al. (2017) |
Cob | MAC | H3PO4 | Acid activation | 600 | – | 60 | – | – | – | Ali et al. (2017) |
Cob | MAC | H2SO4 | Acid activation | 50 | 10 | 120 | FT-IR, SEM | – | – | Aljeboree & Alkaim (2019) |
Cob | MAC | H3PO4 | Acid activation | 5,000 | – | 60 | FT-IR, SEM | – | – | Aljeboree et al. (2019) |
Cob | MB | HCl | Pyrolysis + Acid activation | 350 | – | 180 | FT-IR, SEM, BET | – | – | Assirey & Altamimi (2021) |
Cob | MB | HCl | Pyrolysis + Acid activation | 450 | – | 180 | FT-IR, SEM, BET | 407 | – | Assirey & Altamimi (2021) |
Cob | MAC | H3PO4 | Acid activation | 500 | 0.2 | 60 | FT-IR-ATR | – | – | Campos et al. (2020) |
Stover | MAC | Ethanol-ammonia + aminopropyltriethoxysilane | – | 70 | – | 960 | FT-IR, XRD SEM-EDS, BET | 0.693 | Carijo et al. (2019) | |
Stalk | MAC | Epichlorohydroin and N,N-dimethylformamide and trimethylamine | – | 100 | – | 1,440 | – | – | – | Chen et al. (2012) |
Straw pith | MAC | ZnCl2 | Salt activation | – | – | – | SEM, FT-IR, XRD | – | – | Chen et al. (2020) |
Straw | MAC | KOH and NaOH | Pyrolysis + base activation | 500 | 10 | 60 | SEM, TEM, BET | 1,993 | – | Chen et al. (2019) |
Stem | MAC | H3PO4, KOH, and ZnCl | Pyrolysis + acid, base and salt activation | – | – | – | – | – | 25.8 | Dada et al. (2012) |
Starch | MAC | Hydrogen peroxide | Acid activation | 80 | – | 60 | SEM, FT-IR, XRD | – | – | Dai et al. (2017) |
Silk | MB | – | – | 60 | – | 4,320 | SEM, FT-IR | – | – | Değermenci et al. (2019) |
Tassel powder | MAC | – | – | 102 | – | 144 | UV-visible spectrophotometer | – | – | Dehvari et al. (2013) |
Cob | MAC | ZnCl2 | Salt activation | 500 | – | 60 | BET, XRD, SEM, EDX, FT-IR | 0.431 | – | Dina et al. (2012) |
Seed chaff | MB | – | – | 100 | – | 300 | FT-IR, SEM, EDX | – | – | Duru & Duru (2017) |
Stalk | MB | – | – | 100 | – | 300 | FT-IR, SEM, EDX | – | – | Duru & Duru (2017) |
Cob | MB | – | – | 100 | – | 300 | FT-IR, SEM, EDX | – | – | Duru & Duru (2017) |
Husk | MB | – | – | 100 | – | 300 | FT-IR, SEM, EDX– | – | – | Duru & Duru (2017) |
Husk | MAC | Tartaric acid | Pyrolysis + acid activation | 100 | – | 240 | EDXRF FT-IR | – | – | Duru et al. (2019) |
Husk | MAC | Metanoic acid | Pyrolysis + acid activation | 100 | – | 240 | EDXRF, FT-IR | – | – | Duru et al. (2019) |
Husk | MAC | Phenol | Pyrolysis + acid activation | 100 | – | 240 | EDXRF, FT-IR | – | – | Duru et al. (2019) |
Cob | MAC | NaOH | Pyrolysis + base activation | 500 | – | 120 | XRD, Raman, FT-IR, TEM, EDS, XPS | – | – | Dutta & Nath (2018) |
Cob | MAC | AlCl3 | Pyrolysis + acid activation | 500 | – | 120 | SEM, BET | 146.64 | El-Bendary et al. (2021) | |
Cob | MAC | – | Pyrolysis | 500 | – | 120 | SEM. BET | 118.53 | El-Bendary et al. (2021) | |
Cob | MAC | H3PO4 | Acid activation + pyrolysis | 400 | – | 120 | BET | 700 | El-Sayed et al. (2014) | |
Cob | MAC | H3PO4 | Acid activation + pyrolysis | 500 | – | 120 | BET | 633 | El-Sayed et al. (2014) | |
Cob | MAC | H3PO4 | Acid activation + pyrolysis | 600 | – | 120 | BET | 600 | El-Sayed et al. (2014) | |
Straw | MBC | FeCl3.CH2O | Pyrolysis + acid activation | 500 | – | 180 | XRD, FT-IR, TEM-EDS, VSM, XPS, TGA, BET | 80.1 | – | Eltaweil et al. (2020) |
Leaves | MAC | HCl | Acid activation | – | – | – | FT-IR, SEM | – | – | Fadhil & Eisa (2019) |
Leaves | MAC | – | – | – | – | – | FT-IR, SEM | – | – | Fadhil & Eisa (2019) |
Leaves | MAC | – | – | – | – | – | FT-IR, SEM | – | – | Fadhil et al. (2021) |
Leaves | MAC | – | – | 70 | – | 1,440 | SEM | – | – | Fadhel et al. (2021) |
Cob | MB | – | Pyrolysis | 500 | – | 120 | FT-IR, XRD, SEM | – | – | Farnane et al. (2018) |
Cob | MAC | H3PO4 | Pyrolysis + acid activation | 500 | – | 120 | FT-IR, XRD, SEM | – | – | Farnane et al. (2018) |
Stalk | MAC | – | – | 25 | – | 1,440 | SEM, XRD, FT-IR | – | – | Fathi et al. (2015) |
Cob | MB | – | – | – | – | – | – | – | – | Fatoye & Onigbinde (2020) |
Straw | MBC | – | Pyrolysis | 300 | 10 | 120 | SEM, BET FT-IR | 1.19 | – | Gao et al. (2019) |
Straw | MBC | – | Pyrolysis | 800 | 10 | 120 | SEM, BET FT-IR | 74.33 | – | Gao et al. (2019) |
Straw + waste red mud | MBC | – | Pyrolysis | 700 | 10 | 120 | SEM, EDX, XRD, BET, XPS | 20.34 | – | Gao et al. (2021) |
Hull | MAC | Tartaric acid | Acid activation | – | – | – | – | – | – | Ghasemi et al. (2017) |
Straw | MAC | Succinic anhydride and xylene | Acid activation | – | – | – | FT-IR,SEM-EDX | – | – | Guo et al. (2015a) |
Starch | MB | – | – | – | – | – | SEM, BET, BJH, pore size analyser | – | – | Guo et al. (2015b) |
Porous starch | MAC | Sodium dihydrogen phosphate-citric acid buffer | Acid activation | – | – | – | SEM, BET, BJH, pore size analyser | – | – | Guo et al. (2015b) |
Straw | MAC | Zinc acetate | Salt activation | – | – | – | SEM, XRD, FT-IR | – | – | Guo et al. (2018) |
Straw | MAC | Zinc acetate and manganese acetate | Salt activation | – | – | – | SEM, XRD, FT-IR | – | – | Guo et al. (2018) |
Straw | MB | – | – | – | – | – | SEM, XRD, FT-IR | – | – | Guo et al. (2018) |
Stover | MB | – | – | – | – | – | – | – | – | Guyo et al. (2015) |
Stover | MAC | HNO3 | Acid activation | – | – | – | – | – | – | Guyo et al. (2015) |
Cob | MAC | – | – | – | – | – | – | – | – | Ibrahim (2013) |
Stalk | MAC | HCl | Acid activation | – | – | – | – | – | – | Ismail et al. (2019) |
Husk leaf | MAC | Ca(OH)2 | Salt activation | 550 | – | – | FT-IR, FE-SEM, XRF | – | – | Jalil et al. (2012) |
Cob | MAC | – | – | 100 | – | 1,200 | FT-IR, SEM | – | – | Javed et al. (2021) |
Cob | MAC | H2SO4 | Acid activation | 105 | – | 1,440 | FT-IR, SEM, XRD, BET, CHNS-O | – | – | Jawad et al. (2018) |
Straw | MB | – | – | – | – | – | BET, SEM, FT-IR | 21.0 | – | Jia & Li (2015) |
Pith | MAC | H2SO4 | Acid activation | – | – | – | BET, FT-IR, SEM, TGA, XRD | 0.01 | – | Jothirani et al. (2016) |
Stalk + walnut shell | MAC | – | Pyrolysis | 500 | – | 180 | SEM, FT-IR, BET | 1,187.00 | Kang et al. (2018) | |
Husk | MAC | ZnCl2 | Salt activation | 100 | – | 1,440 | – | – | – | Khodaie et al. (2013) |
Stalk | MAC | – | – | – | – | – | XRD, SEM-EDS, BET | 4.79 | – | Lara-Vásquez et al. (2016) |
Cob | MAC | ZnCl2 | Salt activation | 350 | – | 120 | – | – | – | Leelavathy et al. (2015) |
Cob | MAC | – | – | – | – | – | – | – | – | Leelavathy et al. (2015) |
Stalk | MBC | Urea & NaHCO3 | Base activation + pyrolysis | 700 | 10 | 120 | BET, XRD, XPS | 325.90 | – | Li et al. (2019a) |
Stalk | MAC | Ethyl acetate | Base activation | – | – | – | SEM, BET | 201.0 | – | Li et al. (2019b) |
Straw | MB | – | – | – | – | – | FT-IR, XRD, SEM, BET | 0.85 | – | Lima et al. (2017) |
Straw | MB | – | – | – | – | – | FT-IR, XRD, SEM, BET | 0.85 | – | Lima et al. (2018) |
Bract | MAC | 2-Aminothiazole | Base activation | – | – | – | FT-IR, SEM, XPS | – | – | Lin et al. (2018) |
Husk leaves | MAC | N,N-dimethylformamide and chloroacetyl chloride | – | 100 | – | 720 | FT-IR, XPS | – | – | Lin et al. (2019) |
Stalk | MBC | – | – | 500 | – | – | Pore analyser, FT-IR, SEM, XRD | – | – | Liu et al. (2019) |
Stalk | MBC | KOH | Base activation | – | – | – | Pore analyser, FT-IR, SEM, XRD | – | – | Liu et al. (2019) |
Stalk | MBC | H3PO4 | Acid activation | – | – | – | Pore analyser, FT-IR, SEM, XRD | – | – | Liu et al. (2019) |
Cob | MAC | KOH | Base activation + pyrolysis | 800 | 10 | 60 | SEM, BET, Raman, FT-IR, XPS | 1,054.20 | – | Liu et al. (2020a) |
Stalk | MAC | Citric acid | Acid activation | – | – | – | FT-IR, BET | 45.30 | – | Soldatkina & Yanar (2021) |
Pericarp | MAC | KOH | Base activation + pyrolysis | 627 | 6 | 93 | BET, SEM, EDS | 23.31 | – | Loya-González et al. (2019) |
Stalk | MBC | – | Pyrolysis | 300 | 20 | 360 | SEM, EDS, XPS, FT-IR | – | – | Ma et al. (2016) |
Stalk | MAC | NaOH | Base activation | – | – | – | FT-IR, FE-SEM | – | – | Ma et al. (2017) |
Straw | MAC | KOH | Base activation + Pyrolysis | 800 | 5 | 60 | FT-IR, EDS, XPS, BET | 213.18 | – | Ma et al. (2019) |
Stalk | MB | – | – | – | – | – | – | – | – | Maghri et al. (2012) |
Husk | MB | – | – | 105 | – | 1,440 | – | – | – | Malik et al. (2016) |
Fibre | MAC | Isopropyl alcohol | – | – | – | – | EDS, SEM, FT-IR | – | – | Mallampati et al. (2015) |
Cob | MAC | CaCl2 | Base activation | – | – | – | SEM, EDX | – | – | Manzoor et al. (2019) |
Stigmata | MB | – | – | – | – | – | FT-IR, SEM | – | – | Mbarki et al. (2018) |
Silk | MB | – | – | 100 | – | 360 | SEM, FT-IR | – | – | Miraboutalebi et al. (2017) |
Cob | MAC | – | – | 300 | – | 120 | SEM, EDS, FT-IR | – | – | Miyah et al. (2016) |
Cob | MBC | – | Pyrolysis | 900 | – | 180 | FT-IR, Raman, XRD, SEM | – | – | Mohanraj et al. (2020) |
Stalk | MAC | – | Pyrolysis | 500 | – | 240 | SEM, FT-IR, BET | – | – | Mousavi et al. (2020) |
Stalk | MAC | – | Pyrolysis | 500 | – | 30 | SEM, FT-IR | – | – | Mousavi et al. (2021) |
Tassel | MAC | H2SO4 | Acid activation | – | – | – | XRD, FT-IR | 250.0 | – | Moyo et al. (2013) |
Cob | MB | – | – | – | – | – | – | – | – | Ibrahim (2013) |
Stalk | MB | – | – | – | – | – | – | – | – | Muhammad et al. (2019) |
Cob | MB | – | – | 100 | – | 1,440 | SEM, XRD, FT-IR | – | – | Muthusamy & Murugan (2016) |
Silk | MC | – | – | – | – | – | SEM, XRD, FT-IR | – | – | Nadaroğlu et al. (2018) |
Cob | MAC | – | Pyrolysis | 500 | 20 | 120 | SEM, TEM, XRD, VSM | – | – | Nethaji et al. (2013) |
Cob | MAC | H3PO4 | Acid activation | 105 | – | 300 | SEM, FT-IR | – | – | Ojediran et al. (2021) |
Cob | MAC | H3PO4 | Acid activation | 105 | – | 300 | FT-IR, SEM, EDX | – | – | Ojedokun & Bello (2017) |
Cob | MAC | H3PO4 and ZnCl2 | Acid Pyrolysis + pyrolysis + salt activation | 500 | – | 60 | – | 1,195.12 | – | Okafor et al. (2015) |
Tassel | MAC | – | Pyrolysis | 500 | – | 60 | FT-IR, SEM | – | – | Olorundare et al. (2014) |
Cob | MC | – | – | – | – | – | FT-IR, SEM, EDX | – | – | Ong et al. (2017) |
Husk | MB | – | – | – | – | – | FT-IR, | – | – | Paşka et al. (2014) |
Husk | MC | – | – | – | – | – | FT-IR, XRD, SEM | – | – | Guin et al. (2018) |
Stalk pith | MAC | Malic acid | Acid activation | – | – | – | SEM, EDS, XRD, FT-IR, XPS | – | – | Peng et al. (2021) |
Silk | MB | – | – | – | – | – | SEM-EDX, ATR-FT-IR, BET | 1.36 | – | Petrović et al. (2016) |
Silk | MB | – | – | – | – | – | SEM-EDX, ATR-FT-IR | 1.36 | – | Petrović et al. (2017) |
Husk | MAC | NaOH | Base activation | – | – | – | SEM, ATR-FT-IR, BET, XRD | 3.01 | – | Ponce et al. (2021) |
Cob | MAC | H3PO4 | Acid activation | 110 | – | 1,440 | XRD, XPS, UV-DRS, PL, FT-IR, FE-SEM, BET, TEM | 293.12 | – | Ramamoorthy et al. (2020) |
Cob | MAC | – | Pyrolysis | 900 | – | 360 | BET, TPD, TGA | – | – | Reddy et al. (2016) |
Straw | MAC | Zncl2 | Salt activation | – | – | – | SEM, BET | 937.0 | Ren et al. (2020) | |
Pericarp | MB | – | – | – | – | – | SEM, ATR-FT-IR, BET | 1.53 | – | Rosas-Castor et al. (2014) |
Cob | MB | – | – | – | – | – | FT-IR | – | – | Abubakar & Ibrahim (2018) |
Cob | MB | – | – | – | – | – | FT-IR, BET, SEM | – | – | Pezhhanfar & Zarei (2021) |
Husk | MB | – | – | – | – | – | FT-IR, BET, SEM | – | – | Pezhhanfar & Zarei (2021) |
Cob | MB | – | – | 120 | – | 1,440 | – | – | – | Sallau et al. (2012) |
Cob | MB | – | – | – | – | – | XRD, TDS, TSS | – | – | Saroj et al. (2015) |
Cob leaves | MB | – | – | – | – | – | FT-IR | – | – | Sepúlveda et al. (2015) |
Stalk | MAC | Cetylpyridinium bromide | Salt activation | – | – | – | FT-IR | 42.6 | – | Soldatkina & Zavrichko (2018) |
Cob | MC | – | – | – | – | – | XRD, SEM, TEM, FT-IR, BET, VSM, XPS | 23.10 | – | Song et al. (2015) |
Cob | MAC | Sulphuric acid | Acid activation | 150 | – | 1,440 | – | – | – | Ismail et al. (2018) |
Stalk | MB | – | – | – | – | – | – | – | – | Taha et al. (2021) |
Stalk | MAC | Sulphuric acid | Acid activation | – | – | – | – | – | – | Taha et al. (2021) |
Stalk | MAC | Magnetic particles FeSO4.7H2O and FeCl3.6H2O | – | – | – | – | – | – | – | Taha et al. (2021) |
Cob | MAC | – | – | – | – | – | – | – | – | Tan et al. (2012) |
Stalk | MAC | H3PO4 | Acid activation | – | – | – | XPS, FT-IR | – | – | Tang et al. (2019) |
Stalk | MAC | Maleic anhydride | Acid activation | – | – | – | XPS, FT-IR | – | – | Tang et al. (2021) |
Cob | MB | – | – | – | – | – | FT-IR, SEM | – | – | Tejada-Tovar et al. (2021) |
Cob | MBC | – | Pyrolysis | 400 | – | 20 | – | – | – | Tsamo et al. (2019) |
Straw | MAC | Tetradecyltrimethyl ammonium bromide | Salt activation | – | – | – | FT-IR, BET, SEM | 4.21 | – | Umpuch & Jutarat (2013) |
Cob | MAC | NaOH | Base activation | – | – | – | FT-IR | – | – | Velmurugan et al. (2016) |
Stem tissue | MB | – | – | – | – | – | BET, FT-IR, SEM | 7.23 | – | Vučurović et al. (2014) |
Cob | MAC | HCl | Acid activation + pyrolysis | 700 | – | 60 | FT-IR, SEM, BET | 784.76 | 56.60 | Wang et al. (2018) |
Straw | MAC | C17H38NBr | Salt activation | – | – | – | – | – | – | Umpuch (2015) |
Stalk | MAC | Triethylenetetramine | – | – | – | – | SEM, TEM | – | – | Wang et al. (2016) |
Leaf | MBC | – | Pyrolysis | 500 | 5.0 | 360 | BET | 2.72 | – | Mu et al. (2020) |
Tassel | MBC | – | Pyrolysis | 500 | 5.0 | 360 | BET | 2.72 | – | Mu et al. (2020) |
Stalk | MBC | – | Pyrolysis | 500 | 5.0 | 360 | BET | 2.72 | – | Mu et al. (2020) |
Root | MBC | – | Pyrolysis | 500 | 5.0 | 360 | BET | 2.72 | – | Mu et al. (2020) |
Silk | MBC | – | Pyrolysis | 500 | 5.0 | 360 | BET | 2.72 | – | Mu et al. (2020) |
Ear | MBC | – | pyrolysis | 500 | 5.0 | 360 | BET | 2.72 | – | Mu et al. (2020) |
Cob | MBC | – | Pyrolysis | 500 | 5.0 | 360 | BET | 2.72 | – | Mu et al. (2020) |
Stalk | MAC | Polyarcrylic acid | Acid activation | – | – | – | FE-SEM, FT-IR | – | – | Wen et al. (2018) |
Cob | MAC | KOH | Pyrolysis and base activation | 500 | 10.0 | 60 | SEM, FT-IR, EDS, BET, thermal analyser | 591.0 | – | Wu et al. (2013) |
Stalk | MAC | NaOH | Base activation | – | – | – | FT-IR, XRD, TG, SEM | – | – | Wu et al. (2017) |
Cob | MB | – | – | – | – | – | FT-IR | – | – | Yaneva & Georgieva (2013) |
Cob | MAC | H3PO4 | Acid activation | – | – | – | FT-IR, BET | 809.80 | – | Zhang et al. (2014) |
Stover | MAC | ZrO2 | – | – | – | – | BET | 2.63 | – | Zhang et al. (2016)) |
Cob | MBC | – | Pyrolysis | 600 | 15 | 120 | SEM, XRD, FT-IR, XPS, EPR | 468.59 | 28.34 | Zhang et al. (2020) |
Straw | MAC | Glutamic acid | Acid activation | – | – | – | SEM, FT-IR | – | – | Zhao et al. (2014) |
Cover | MC | – | – | – | – | – | XRD, EDX, SEM, FT-IR | – | – | Zolgharnein et al. (2016) |
Plant parts . | Adsorbent class . | Modification/activation . | Carbonization . | Characterization . | BET SSA (m2/g) . | Yield (wt %) . | References . | |||
---|---|---|---|---|---|---|---|---|---|---|
Reagent/material . | Process . | Temp (°C) . | Heating rate (°C/min) . | Time (mins) . | ||||||
Cob | MAC | KOH | Base activation | 800 | – | 1,440 | FT-IR-ATR, SEM, XRD | – | – | Abdullah et al. (2019) |
Cob | MC | Graphene oxide | 60 | – | 120 | FT-IR, SEM | – | – | Qu et al. (2020) | |
Cob | MB | – | – | 60 | – | – | – | – | – | Qu et al. (2020) |
Cob | MAC | H3PO4 | Acid activation | 600 | – | 60 | – | – | – | Ali et al. (2017) |
Cob | MAC | H3PO4 | Acid activation | 600 | – | 60 | – | – | – | Ali et al. (2017) |
Cob | MAC | H2SO4 | Acid activation | 50 | 10 | 120 | FT-IR, SEM | – | – | Aljeboree & Alkaim (2019) |
Cob | MAC | H3PO4 | Acid activation | 5,000 | – | 60 | FT-IR, SEM | – | – | Aljeboree et al. (2019) |
Cob | MB | HCl | Pyrolysis + Acid activation | 350 | – | 180 | FT-IR, SEM, BET | – | – | Assirey & Altamimi (2021) |
Cob | MB | HCl | Pyrolysis + Acid activation | 450 | – | 180 | FT-IR, SEM, BET | 407 | – | Assirey & Altamimi (2021) |
Cob | MAC | H3PO4 | Acid activation | 500 | 0.2 | 60 | FT-IR-ATR | – | – | Campos et al. (2020) |
Stover | MAC | Ethanol-ammonia + aminopropyltriethoxysilane | – | 70 | – | 960 | FT-IR, XRD SEM-EDS, BET | 0.693 | Carijo et al. (2019) | |
Stalk | MAC | Epichlorohydroin and N,N-dimethylformamide and trimethylamine | – | 100 | – | 1,440 | – | – | – | Chen et al. (2012) |
Straw pith | MAC | ZnCl2 | Salt activation | – | – | – | SEM, FT-IR, XRD | – | – | Chen et al. (2020) |
Straw | MAC | KOH and NaOH | Pyrolysis + base activation | 500 | 10 | 60 | SEM, TEM, BET | 1,993 | – | Chen et al. (2019) |
Stem | MAC | H3PO4, KOH, and ZnCl | Pyrolysis + acid, base and salt activation | – | – | – | – | – | 25.8 | Dada et al. (2012) |
Starch | MAC | Hydrogen peroxide | Acid activation | 80 | – | 60 | SEM, FT-IR, XRD | – | – | Dai et al. (2017) |
Silk | MB | – | – | 60 | – | 4,320 | SEM, FT-IR | – | – | Değermenci et al. (2019) |
Tassel powder | MAC | – | – | 102 | – | 144 | UV-visible spectrophotometer | – | – | Dehvari et al. (2013) |
Cob | MAC | ZnCl2 | Salt activation | 500 | – | 60 | BET, XRD, SEM, EDX, FT-IR | 0.431 | – | Dina et al. (2012) |
Seed chaff | MB | – | – | 100 | – | 300 | FT-IR, SEM, EDX | – | – | Duru & Duru (2017) |
Stalk | MB | – | – | 100 | – | 300 | FT-IR, SEM, EDX | – | – | Duru & Duru (2017) |
Cob | MB | – | – | 100 | – | 300 | FT-IR, SEM, EDX | – | – | Duru & Duru (2017) |
Husk | MB | – | – | 100 | – | 300 | FT-IR, SEM, EDX– | – | – | Duru & Duru (2017) |
Husk | MAC | Tartaric acid | Pyrolysis + acid activation | 100 | – | 240 | EDXRF FT-IR | – | – | Duru et al. (2019) |
Husk | MAC | Metanoic acid | Pyrolysis + acid activation | 100 | – | 240 | EDXRF, FT-IR | – | – | Duru et al. (2019) |
Husk | MAC | Phenol | Pyrolysis + acid activation | 100 | – | 240 | EDXRF, FT-IR | – | – | Duru et al. (2019) |
Cob | MAC | NaOH | Pyrolysis + base activation | 500 | – | 120 | XRD, Raman, FT-IR, TEM, EDS, XPS | – | – | Dutta & Nath (2018) |
Cob | MAC | AlCl3 | Pyrolysis + acid activation | 500 | – | 120 | SEM, BET | 146.64 | El-Bendary et al. (2021) | |
Cob | MAC | – | Pyrolysis | 500 | – | 120 | SEM. BET | 118.53 | El-Bendary et al. (2021) | |
Cob | MAC | H3PO4 | Acid activation + pyrolysis | 400 | – | 120 | BET | 700 | El-Sayed et al. (2014) | |
Cob | MAC | H3PO4 | Acid activation + pyrolysis | 500 | – | 120 | BET | 633 | El-Sayed et al. (2014) | |
Cob | MAC | H3PO4 | Acid activation + pyrolysis | 600 | – | 120 | BET | 600 | El-Sayed et al. (2014) | |
Straw | MBC | FeCl3.CH2O | Pyrolysis + acid activation | 500 | – | 180 | XRD, FT-IR, TEM-EDS, VSM, XPS, TGA, BET | 80.1 | – | Eltaweil et al. (2020) |
Leaves | MAC | HCl | Acid activation | – | – | – | FT-IR, SEM | – | – | Fadhil & Eisa (2019) |
Leaves | MAC | – | – | – | – | – | FT-IR, SEM | – | – | Fadhil & Eisa (2019) |
Leaves | MAC | – | – | – | – | – | FT-IR, SEM | – | – | Fadhil et al. (2021) |
Leaves | MAC | – | – | 70 | – | 1,440 | SEM | – | – | Fadhel et al. (2021) |
Cob | MB | – | Pyrolysis | 500 | – | 120 | FT-IR, XRD, SEM | – | – | Farnane et al. (2018) |
Cob | MAC | H3PO4 | Pyrolysis + acid activation | 500 | – | 120 | FT-IR, XRD, SEM | – | – | Farnane et al. (2018) |
Stalk | MAC | – | – | 25 | – | 1,440 | SEM, XRD, FT-IR | – | – | Fathi et al. (2015) |
Cob | MB | – | – | – | – | – | – | – | – | Fatoye & Onigbinde (2020) |
Straw | MBC | – | Pyrolysis | 300 | 10 | 120 | SEM, BET FT-IR | 1.19 | – | Gao et al. (2019) |
Straw | MBC | – | Pyrolysis | 800 | 10 | 120 | SEM, BET FT-IR | 74.33 | – | Gao et al. (2019) |
Straw + waste red mud | MBC | – | Pyrolysis | 700 | 10 | 120 | SEM, EDX, XRD, BET, XPS | 20.34 | – | Gao et al. (2021) |
Hull | MAC | Tartaric acid | Acid activation | – | – | – | – | – | – | Ghasemi et al. (2017) |
Straw | MAC | Succinic anhydride and xylene | Acid activation | – | – | – | FT-IR,SEM-EDX | – | – | Guo et al. (2015a) |
Starch | MB | – | – | – | – | – | SEM, BET, BJH, pore size analyser | – | – | Guo et al. (2015b) |
Porous starch | MAC | Sodium dihydrogen phosphate-citric acid buffer | Acid activation | – | – | – | SEM, BET, BJH, pore size analyser | – | – | Guo et al. (2015b) |
Straw | MAC | Zinc acetate | Salt activation | – | – | – | SEM, XRD, FT-IR | – | – | Guo et al. (2018) |
Straw | MAC | Zinc acetate and manganese acetate | Salt activation | – | – | – | SEM, XRD, FT-IR | – | – | Guo et al. (2018) |
Straw | MB | – | – | – | – | – | SEM, XRD, FT-IR | – | – | Guo et al. (2018) |
Stover | MB | – | – | – | – | – | – | – | – | Guyo et al. (2015) |
Stover | MAC | HNO3 | Acid activation | – | – | – | – | – | – | Guyo et al. (2015) |
Cob | MAC | – | – | – | – | – | – | – | – | Ibrahim (2013) |
Stalk | MAC | HCl | Acid activation | – | – | – | – | – | – | Ismail et al. (2019) |
Husk leaf | MAC | Ca(OH)2 | Salt activation | 550 | – | – | FT-IR, FE-SEM, XRF | – | – | Jalil et al. (2012) |
Cob | MAC | – | – | 100 | – | 1,200 | FT-IR, SEM | – | – | Javed et al. (2021) |
Cob | MAC | H2SO4 | Acid activation | 105 | – | 1,440 | FT-IR, SEM, XRD, BET, CHNS-O | – | – | Jawad et al. (2018) |
Straw | MB | – | – | – | – | – | BET, SEM, FT-IR | 21.0 | – | Jia & Li (2015) |
Pith | MAC | H2SO4 | Acid activation | – | – | – | BET, FT-IR, SEM, TGA, XRD | 0.01 | – | Jothirani et al. (2016) |
Stalk + walnut shell | MAC | – | Pyrolysis | 500 | – | 180 | SEM, FT-IR, BET | 1,187.00 | Kang et al. (2018) | |
Husk | MAC | ZnCl2 | Salt activation | 100 | – | 1,440 | – | – | – | Khodaie et al. (2013) |
Stalk | MAC | – | – | – | – | – | XRD, SEM-EDS, BET | 4.79 | – | Lara-Vásquez et al. (2016) |
Cob | MAC | ZnCl2 | Salt activation | 350 | – | 120 | – | – | – | Leelavathy et al. (2015) |
Cob | MAC | – | – | – | – | – | – | – | – | Leelavathy et al. (2015) |
Stalk | MBC | Urea & NaHCO3 | Base activation + pyrolysis | 700 | 10 | 120 | BET, XRD, XPS | 325.90 | – | Li et al. (2019a) |
Stalk | MAC | Ethyl acetate | Base activation | – | – | – | SEM, BET | 201.0 | – | Li et al. (2019b) |
Straw | MB | – | – | – | – | – | FT-IR, XRD, SEM, BET | 0.85 | – | Lima et al. (2017) |
Straw | MB | – | – | – | – | – | FT-IR, XRD, SEM, BET | 0.85 | – | Lima et al. (2018) |
Bract | MAC | 2-Aminothiazole | Base activation | – | – | – | FT-IR, SEM, XPS | – | – | Lin et al. (2018) |
Husk leaves | MAC | N,N-dimethylformamide and chloroacetyl chloride | – | 100 | – | 720 | FT-IR, XPS | – | – | Lin et al. (2019) |
Stalk | MBC | – | – | 500 | – | – | Pore analyser, FT-IR, SEM, XRD | – | – | Liu et al. (2019) |
Stalk | MBC | KOH | Base activation | – | – | – | Pore analyser, FT-IR, SEM, XRD | – | – | Liu et al. (2019) |
Stalk | MBC | H3PO4 | Acid activation | – | – | – | Pore analyser, FT-IR, SEM, XRD | – | – | Liu et al. (2019) |
Cob | MAC | KOH | Base activation + pyrolysis | 800 | 10 | 60 | SEM, BET, Raman, FT-IR, XPS | 1,054.20 | – | Liu et al. (2020a) |
Stalk | MAC | Citric acid | Acid activation | – | – | – | FT-IR, BET | 45.30 | – | Soldatkina & Yanar (2021) |
Pericarp | MAC | KOH | Base activation + pyrolysis | 627 | 6 | 93 | BET, SEM, EDS | 23.31 | – | Loya-González et al. (2019) |
Stalk | MBC | – | Pyrolysis | 300 | 20 | 360 | SEM, EDS, XPS, FT-IR | – | – | Ma et al. (2016) |
Stalk | MAC | NaOH | Base activation | – | – | – | FT-IR, FE-SEM | – | – | Ma et al. (2017) |
Straw | MAC | KOH | Base activation + Pyrolysis | 800 | 5 | 60 | FT-IR, EDS, XPS, BET | 213.18 | – | Ma et al. (2019) |
Stalk | MB | – | – | – | – | – | – | – | – | Maghri et al. (2012) |
Husk | MB | – | – | 105 | – | 1,440 | – | – | – | Malik et al. (2016) |
Fibre | MAC | Isopropyl alcohol | – | – | – | – | EDS, SEM, FT-IR | – | – | Mallampati et al. (2015) |
Cob | MAC | CaCl2 | Base activation | – | – | – | SEM, EDX | – | – | Manzoor et al. (2019) |
Stigmata | MB | – | – | – | – | – | FT-IR, SEM | – | – | Mbarki et al. (2018) |
Silk | MB | – | – | 100 | – | 360 | SEM, FT-IR | – | – | Miraboutalebi et al. (2017) |
Cob | MAC | – | – | 300 | – | 120 | SEM, EDS, FT-IR | – | – | Miyah et al. (2016) |
Cob | MBC | – | Pyrolysis | 900 | – | 180 | FT-IR, Raman, XRD, SEM | – | – | Mohanraj et al. (2020) |
Stalk | MAC | – | Pyrolysis | 500 | – | 240 | SEM, FT-IR, BET | – | – | Mousavi et al. (2020) |
Stalk | MAC | – | Pyrolysis | 500 | – | 30 | SEM, FT-IR | – | – | Mousavi et al. (2021) |
Tassel | MAC | H2SO4 | Acid activation | – | – | – | XRD, FT-IR | 250.0 | – | Moyo et al. (2013) |
Cob | MB | – | – | – | – | – | – | – | – | Ibrahim (2013) |
Stalk | MB | – | – | – | – | – | – | – | – | Muhammad et al. (2019) |
Cob | MB | – | – | 100 | – | 1,440 | SEM, XRD, FT-IR | – | – | Muthusamy & Murugan (2016) |
Silk | MC | – | – | – | – | – | SEM, XRD, FT-IR | – | – | Nadaroğlu et al. (2018) |
Cob | MAC | – | Pyrolysis | 500 | 20 | 120 | SEM, TEM, XRD, VSM | – | – | Nethaji et al. (2013) |
Cob | MAC | H3PO4 | Acid activation | 105 | – | 300 | SEM, FT-IR | – | – | Ojediran et al. (2021) |
Cob | MAC | H3PO4 | Acid activation | 105 | – | 300 | FT-IR, SEM, EDX | – | – | Ojedokun & Bello (2017) |
Cob | MAC | H3PO4 and ZnCl2 | Acid Pyrolysis + pyrolysis + salt activation | 500 | – | 60 | – | 1,195.12 | – | Okafor et al. (2015) |
Tassel | MAC | – | Pyrolysis | 500 | – | 60 | FT-IR, SEM | – | – | Olorundare et al. (2014) |
Cob | MC | – | – | – | – | – | FT-IR, SEM, EDX | – | – | Ong et al. (2017) |
Husk | MB | – | – | – | – | – | FT-IR, | – | – | Paşka et al. (2014) |
Husk | MC | – | – | – | – | – | FT-IR, XRD, SEM | – | – | Guin et al. (2018) |
Stalk pith | MAC | Malic acid | Acid activation | – | – | – | SEM, EDS, XRD, FT-IR, XPS | – | – | Peng et al. (2021) |
Silk | MB | – | – | – | – | – | SEM-EDX, ATR-FT-IR, BET | 1.36 | – | Petrović et al. (2016) |
Silk | MB | – | – | – | – | – | SEM-EDX, ATR-FT-IR | 1.36 | – | Petrović et al. (2017) |
Husk | MAC | NaOH | Base activation | – | – | – | SEM, ATR-FT-IR, BET, XRD | 3.01 | – | Ponce et al. (2021) |
Cob | MAC | H3PO4 | Acid activation | 110 | – | 1,440 | XRD, XPS, UV-DRS, PL, FT-IR, FE-SEM, BET, TEM | 293.12 | – | Ramamoorthy et al. (2020) |
Cob | MAC | – | Pyrolysis | 900 | – | 360 | BET, TPD, TGA | – | – | Reddy et al. (2016) |
Straw | MAC | Zncl2 | Salt activation | – | – | – | SEM, BET | 937.0 | Ren et al. (2020) | |
Pericarp | MB | – | – | – | – | – | SEM, ATR-FT-IR, BET | 1.53 | – | Rosas-Castor et al. (2014) |
Cob | MB | – | – | – | – | – | FT-IR | – | – | Abubakar & Ibrahim (2018) |
Cob | MB | – | – | – | – | – | FT-IR, BET, SEM | – | – | Pezhhanfar & Zarei (2021) |
Husk | MB | – | – | – | – | – | FT-IR, BET, SEM | – | – | Pezhhanfar & Zarei (2021) |
Cob | MB | – | – | 120 | – | 1,440 | – | – | – | Sallau et al. (2012) |
Cob | MB | – | – | – | – | – | XRD, TDS, TSS | – | – | Saroj et al. (2015) |
Cob leaves | MB | – | – | – | – | – | FT-IR | – | – | Sepúlveda et al. (2015) |
Stalk | MAC | Cetylpyridinium bromide | Salt activation | – | – | – | FT-IR | 42.6 | – | Soldatkina & Zavrichko (2018) |
Cob | MC | – | – | – | – | – | XRD, SEM, TEM, FT-IR, BET, VSM, XPS | 23.10 | – | Song et al. (2015) |
Cob | MAC | Sulphuric acid | Acid activation | 150 | – | 1,440 | – | – | – | Ismail et al. (2018) |
Stalk | MB | – | – | – | – | – | – | – | – | Taha et al. (2021) |
Stalk | MAC | Sulphuric acid | Acid activation | – | – | – | – | – | – | Taha et al. (2021) |
Stalk | MAC | Magnetic particles FeSO4.7H2O and FeCl3.6H2O | – | – | – | – | – | – | – | Taha et al. (2021) |
Cob | MAC | – | – | – | – | – | – | – | – | Tan et al. (2012) |
Stalk | MAC | H3PO4 | Acid activation | – | – | – | XPS, FT-IR | – | – | Tang et al. (2019) |
Stalk | MAC | Maleic anhydride | Acid activation | – | – | – | XPS, FT-IR | – | – | Tang et al. (2021) |
Cob | MB | – | – | – | – | – | FT-IR, SEM | – | – | Tejada-Tovar et al. (2021) |
Cob | MBC | – | Pyrolysis | 400 | – | 20 | – | – | – | Tsamo et al. (2019) |
Straw | MAC | Tetradecyltrimethyl ammonium bromide | Salt activation | – | – | – | FT-IR, BET, SEM | 4.21 | – | Umpuch & Jutarat (2013) |
Cob | MAC | NaOH | Base activation | – | – | – | FT-IR | – | – | Velmurugan et al. (2016) |
Stem tissue | MB | – | – | – | – | – | BET, FT-IR, SEM | 7.23 | – | Vučurović et al. (2014) |
Cob | MAC | HCl | Acid activation + pyrolysis | 700 | – | 60 | FT-IR, SEM, BET | 784.76 | 56.60 | Wang et al. (2018) |
Straw | MAC | C17H38NBr | Salt activation | – | – | – | – | – | – | Umpuch (2015) |
Stalk | MAC | Triethylenetetramine | – | – | – | – | SEM, TEM | – | – | Wang et al. (2016) |
Leaf | MBC | – | Pyrolysis | 500 | 5.0 | 360 | BET | 2.72 | – | Mu et al. (2020) |
Tassel | MBC | – | Pyrolysis | 500 | 5.0 | 360 | BET | 2.72 | – | Mu et al. (2020) |
Stalk | MBC | – | Pyrolysis | 500 | 5.0 | 360 | BET | 2.72 | – | Mu et al. (2020) |
Root | MBC | – | Pyrolysis | 500 | 5.0 | 360 | BET | 2.72 | – | Mu et al. (2020) |
Silk | MBC | – | Pyrolysis | 500 | 5.0 | 360 | BET | 2.72 | – | Mu et al. (2020) |
Ear | MBC | – | pyrolysis | 500 | 5.0 | 360 | BET | 2.72 | – | Mu et al. (2020) |
Cob | MBC | – | Pyrolysis | 500 | 5.0 | 360 | BET | 2.72 | – | Mu et al. (2020) |
Stalk | MAC | Polyarcrylic acid | Acid activation | – | – | – | FE-SEM, FT-IR | – | – | Wen et al. (2018) |
Cob | MAC | KOH | Pyrolysis and base activation | 500 | 10.0 | 60 | SEM, FT-IR, EDS, BET, thermal analyser | 591.0 | – | Wu et al. (2013) |
Stalk | MAC | NaOH | Base activation | – | – | – | FT-IR, XRD, TG, SEM | – | – | Wu et al. (2017) |
Cob | MB | – | – | – | – | – | FT-IR | – | – | Yaneva & Georgieva (2013) |
Cob | MAC | H3PO4 | Acid activation | – | – | – | FT-IR, BET | 809.80 | – | Zhang et al. (2014) |
Stover | MAC | ZrO2 | – | – | – | – | BET | 2.63 | – | Zhang et al. (2016)) |
Cob | MBC | – | Pyrolysis | 600 | 15 | 120 | SEM, XRD, FT-IR, XPS, EPR | 468.59 | 28.34 | Zhang et al. (2020) |
Straw | MAC | Glutamic acid | Acid activation | – | – | – | SEM, FT-IR | – | – | Zhao et al. (2014) |
Cover | MC | – | – | – | – | – | XRD, EDX, SEM, FT-IR | – | – | Zolgharnein et al. (2016) |
ATR (Attenuated total reflection), BET (Brunauer–Emmett–Teller), BJH (Barrett–Joyner–Halenda), UV-DRS (Ultraviolet–Visible Diffuse Reflectance Spectroscopy), EDS or EDX (Energy-dispersive X-ray spectroscopy), EDXRF (Energy Dispersive X-ray Fluorescence), EPR (Electron paramagnetic resonance), FT-IR-ATR (Fourier Transform Infrared Attenuated total reflection), PL (Photoluminescence emission spectra), PSO (Pseudo-second order), RE (Removal efficiency), SSA (specific surface area), SEM (Scanning Electron Microscopy, TDS (Total Dissolved Solids), TEM (Transmission electron microscopy), TG or TGA (Thermogravimetric analysis), TPD (Temperature programmed decomposition), TSS (Total Suspended Solids), VSM (vibrating sample magnetometer), XRD (X-ray Diffraction), XPS (X-ray photoelectron spectroscopy), XRF (X-ray photoelectron spectroscopy).
For instance, to prepare corn cob biochar, Zhang et al. (2020) first washed the collected cob with water and absolute EtOH. The biomass was then dried for 24 h in a vacuum chamber at 90°C, followed by pulverizing and sieving to create fine char. The cob fine char was added to a corundum crucible, pyrolyzed under a nitrogen atmosphere for 2 h at a constant temperature of 600 °C (15 °C/min), and then chilled to ambient temperature while maintaining a nitrogen condition. The finished char was then grounded, neutralized with water and EtOH, and dried for 12 h at 90 °C. This similar method was adopted for the fabrication of nZVI/corn straw and functional corn straw biochar composites by Eltaweil et al. (2020) and Gao et al. (2021). Although, according to Eltaweil et al. (2020), the nZVI/corn straw composite was fabricated via a reduction process after the corn straw biochar had been successfully achieved, Gao et al. (2021) achieved the biochar composite in a single pyrolysis step. Shortly, as reported by Eltaweil et al. (2020), ethanol–water (EtOH-H2O) (8:2 ml) was mixed with 50 mg of corn straw biochar and 180 mg of FeCl3.6H2O, and then the mixture was sonicated for 30 min. To convert Fe3+ ions into Fe0, freshly made aqueous NaBH4 was added in drops to the Fe3+/corn straw composite blends. Following the complete addition of NaBH4, the magnetic nZVI/corn straw composite that emerged was detached with an external magnet, repeatedly rinsed with water and EtOH, and then dried overnight in an oven at 50 °C.
Maize activated carbon
MAC can be prepared by chemically activating UM or further activating the MBC analogue, as it has been established in a cow dung-based adsorbent review performed by Iwuozor et al. (2022b) that activation of biochar and its advanced treatment are essential for better adsorptive achievement. Empirically speaking, the MAC and MBC have parallel functional features except for a minor architectural disparity that is primarily linked to permeability. It is assumed that advanced activation of MBC enriches the biochar functional groups and also improves its porosity, which in turn affords extra binding sites for pollutant elimination as a result of increased surface area (Dehkhoda et al. 2016; Tan et al. 2017; Liu et al. 2018a; Li et al. 2019a). Holistically, according to literature, there are two distinct practices (physical and chemical) for producing MAC (Jun et al. 2010; Al-Swaidan & Ahmad 2011; Danish et al. 2011; Ekpete & Horsfall 2011; Yahya et al. 2015). In physical treatment, the matrix will first undergo carbonization and then be activated with steam or CO2. Contrarily, in chemical treatment, the matrix is impregnated with an activating reagent and then carbonizes (pyrolytic decomposition of the biomass matrix) in a hypoxic atmosphere afterward (Solar et al. 2008; Yagmur et al. 2008; Giraldo & Moreno-Piraján 2012; Vicinisvarri et al. 2014). Notably, from several reports gathered in Table 1, during the preparation, most authors used a pre-carbonization activation tactic where the maize plant matrix was chemically activated using acid, base, or salt prior to actual carbonization. Meanwhile, the author provided no pragmatic explanation for the pre-carbonization activation practice selection. Nevertheless, it might be because pre-carbonization activation practice requires lower temperatures, gives a higher yield, produces a high surface area, requires a single step, creates fully grown micro-porousness, and reduces inorganic material composition, as expounded in some other reports (Budinova et al. 2006; Zhu et al. 2008; Hirunpraditkoon et al. 2011; Cruz et al. 2012; Yahya et al. 2015). Going forward, on a general note, the standard procedure before activation includes drying, pulverizing, and sieving to the desired particle size of the as-collected maize precursor. Furthermore, as shown in Table 1, most authors used H3PO4 for acid activation, KOH for base activation, and ZnCl2 for salt activation. Basically, the role of the activating reagent is to function as a dehydrator and oxidant, avert the materialization of the ash or tar, and dissolve the cellulosic constituents of the matrix while introducing the interfacial organic oxygen moiety to the carbon of the matrix, stimulating the development of cross-links and carbon yield (Noor & Nawi 2008; Wang et al. 2010; Bello & Ahmad 2011; Campbell et al. 2012; Jassim et al. 2012; Mahapatra et al. 2012; Örkün et al. 2012; Yahya et al. 2015).
Ali et al. (2017), Zhang et al. (2014), and Aljeboree et al. (2019) used phosphoric acid as an activating agent, while Loya-González et al. (2019) and Liu et al. (2020a) used KOH as an activating agent. Briefly, during the chemical activation procedure, an amount of the activating reagent sufficient to create slurry was added to a weighed amount of the dried and size-reduced maize matrix. The slurry was agitated for a few seconds (usually >60 s) and then left to stand still for some time (usually a few hours). After that, the mixture's filtration residue is used to extract the activated maize matrix, which is then dried in an oven for some hours. To create the preferred MAC, the saturated and withered maize matrix was pyrolyzed in a furnace at various temperatures and times as reported in Table 1, followed by washing (usually with water) to obtain a benign sorbent product without impurity (Aljeboree et al. 2019; Loya-González et al. 2019; Campos et al. 2020). This MAC preparation methodology is consistent with the one adopted by Aljeboree & Alkaim (2019), Assirey & Altamimi (2021), Duru et al. (2019), Dutta & Nath (2018), and Peng et al. (2021) using H2SO4, HCl, tartaric acid, NaOH, and maleic acid, respectively.
Maize-based composite
ADSORBENT PERFORMANCE OF MAIZE/CORN-BASED ADSORBENTS
An adsorbent's adsorptive ability is a crucial determinant of its application assessment. In Table 2, the ability of various corn-based adsorbents to remove contaminants from aqueous solutions is shown. The effectiveness of an adsorbent in removing a given pollutant is typically determined by two factors: adsorption capacity and removal efficiency. While pollutant removal efficiency depends on the pollutant concentration, adsorbent dosage, and competing ions in the system, adsorption capacity is an inherent property of an adsorbent towards the pollutant (Emenike et al. 2021, 2022a). The adsorption capacity is ascertained either experimentally or using isothermal parameters (Emenike et al. 2022b). As illustrated in Table 2, additional variables that influence an adsorbent's ability include the solution pH, temperature, and amount of the adsorbent. The surface area, which reveals the porosity and degree of active sites on the adsorbent, is another important contributing component.
Plant parts . | Adsorbent class . | Adsorbate dye . | RE% . | (mg/g) . | Dosage (g/L) . | pH . | Temp (°C) . | SSA (m2/g) . | Method of determination . | References . |
---|---|---|---|---|---|---|---|---|---|---|
Cob | MAC | Gentian violet | – | 700.0 | – | 3.0 | – | – | Dubinin-Radushkevich | Javed et al. (2021) |
Cob | MAC | Methyl orange | – | 555.56 | – | 6.5 | 25 | 784.76 | Langmuir | Wang et al. (2018) |
Cob | MAC | Malachite green | 94.48 | 313.63 | 1.0 | 12.0 | 25 | – | Langmuir | Farnane et al. (2018) |
Cob | MAC | Methylene blue | 99.98 | 271.19 | 1.0 | 12.0 | 25 | – | Langmuir | Farnane et al. (2018) |
Cob | MAC | Methylene blue | – | 216.60 | 0.1 | 5.6 | 30 | – | Langmuir | Jawad et al. (2018) |
Cob | MAC | Indigo carmine | 90.13 | 118.48 | – | – | 25 | 809.80 | Langmuir | Zhang et al. (2014) |
Cob | MAC | Methylene blue | – | 100.0 | 0.02 | 7.0 | – | 650.0 | Langmuir | Reddy et al. (2016) |
Cob | MAC | Congo red | – | 98.72 | 1.0 | 7.0 | 35 | – | Langmuir | Velmurugan et al. (2016) |
Cob | MAC | Maxilone | – | 86.89 | 0.1 | 10.0 | 45 | – | Langmuir | Aljeboree & Alkaim (2019) |
Cob | MBC | Methyl orange | – | 86.38 | – | – | – | 468.59 | Langmuir | Zhang et al. (2020) |
Cob | MB | Malachite green | 92.11 | 76.42 | 4.0 | 12.0 | 25 | – | Langmuir | Farnane et al. (2018) |
Cob | MB | Methylene blue | 94.41 | 75.27 | 4.0 | 12.0 | 25 | – | Langmuir | Farnane et al. (2018) |
Cob | MAC | Tartrazine | 76.90 | 68.78 | – | – | 25 | 809.80 | Langmuir | Zhang et al. (2014) |
Cob | MAC | Malachite green | 99.3 | 66.52 | – | 6.0 | – | 13.29 | Langmuir | Ojediran et al. (2021) |
Cob | MAC | Congo red | – | 50.0 | – | – | 30 | – | Langmuir | Ojedokun & Bello (2017) |
Cob | MAC | Methylene blue | 96.0 | 46.28 | 2.0 | 12.0 | 20 | – | Experiments | Miyah et al. (2016) |
Cob | MAC | Methylene blue | – | 41.94 | 0.1 | 10.0 | 45 | – | Langmuir | Aljeboree & Alkaim (2019) |
Cob | MAC | Methylene blue | – | 37.45 | 0.5 | 6.0 | 50 | – | Langmuir | Aljeboree et al. (2019) |
Cob | MC | Malachite green | – | 35.34 | – | 4.0 | – | – | Langmuir | Ong et al. (2017) |
Cob | MAC | Crystal violet | – | 33.86 | 0.1 | 10.0 | 45 | – | Langmuir | Aljeboree & Alkaim (2019) |
Cob | MAC | Methylene blue | 99.40 | 28.65 | 2.0 | 8.0 | 25 | 700.00 | Langmuir | El-Sayed et al. (2014) |
Cob | MAC | Sulfur dioxide | – | 19.8 | – | – | – | 591.0 | Experiments | Wu et al. (2013) |
Cob | MAC | Methylene blue | 44.60 | 17.75 | 2.0 | 8.0 | 25 | 633.00 | Langmuir | El-Sayed et al. (2014) |
Cob | MB | Methylene blue | – | 16.08 | – | 6.5 | – | 0.40 | Langmuir | Pezhhanfar & Zarei (2021) |
Cob | MB | Congo red | – | 4.83 | – | 7.0 | – | – | Experiments | Yaneva & Georgieva (2013) |
Cob | MAC | Methylene blue | 92.20 | 0.81 | 2.0 | 8.0 | 25 | 600.00 | Langmuir | El-Sayed et al. (2014) |
Cob | MC | Acid yellow | – | 0.24 | – | 4.0 | – | – | Langmuir | Ong et al. (2017) |
Cob | MAC | Methylene blue | 99.90 | – | 5.0 | – | – | – | Experiments | Ali et al. (2017) |
Cob | MAC | Methylene blue | 99.89 | – | 10.0 | 6.0 | 27 | – | Experiments | Tan et al. (2012) |
Cob | MAC | Brilliant green | 99.60 | – | 5.0 | – | – | – | Experiments | Ali et al. (2017) |
Cob | MAC | Malachite green | 99.39 | – | 10.0 | 7.0 | 29 | – | Experiments | Ismail et al. (2018) |
Cob | MAC | Congo red | 98.10 | – | 0.3 | 6.8 | 27 | – | Experiments | Leelavathy et al. (2015) |
Cob | MAC | Congo red | 97.80 | – | 1.2 | 6.8 | 27 | – | Experiments | Leelavathy et al. (2015) |
Cob | MB | Methylene blue | 96.94 | – | 0.4 | 5.0 | – | – | Langmuir | Fatoye & Onigbinde (2020) |
Cob | MB | Bromophenol blue | 96.53 | – | 4.0 | 2.0 | – | – | Experiments | Abubakar & Ibrahim (2018) |
Cob | MB | Bromothymol blue | 94.39 | – | 0.5 | 2.0 | – | – | Experiments | Abubakar & Ibrahim (2018) |
Cob | MC | Congo red | 91.28 | – | 1.2 | 3.0 | 30 | – | Experiments | Qu et al. (2020) |
Cob | MAC | Methylene blue | 90.86 | – | 0.2 | 7.0 | – | 293.12 | Experiments | Ramamoorthy et al. (2020) |
Cob | MB | Direct blue 199 | 90.0 | – | 8.0 | 7.6 | 28 | – | Experiments | Saroj et al. (2015) |
Cob | MBC | Methylene blue | 82.0 | – | – | – | – | – | Experiments | Mohanraj et al. (2020) |
Cob | MAC | Methyl orange | 80.36 | – | 5.0 | – | 25 | – | Experiments | Abdullah et al. (2019) |
Cob | MB | Congo red | 80.21 | – | 1.2 | 3.0 | 30 | – | Experiments | Qu et al. (2020) |
Cob | MBC | Rhodamine B | 80.0 | – | – | – | – | – | Experiments | Mohanraj et al. (2020) |
Cob | MBC | Methylene blue | 64.0 | – | – | 8.0 | 25 | – | Experiments | Tsamo et al. (2019) |
Cob | MBC | Methylene blue | 33.38 | – | – | – | 25 | 2.72 | Experiments | Mu et al. (2020) |
Cob leaves | MB | Basic violet 4 | 98.4 | 89.0 | 2.0 | 5.4 | 57 | – | Langmuir | Sepúlveda et al. (2015) |
Cover | MC | Alizarin red S | – | 10.5 | 0.2 | 2.0 | – | – | Langmuir | Zolgharnein et al. (2016) |
Ear | MBC | Methylene blue | 44.13 | – | – | – | 25 | 2.72 | Experiments | Mu et al. (2020) |
Fibre | MAC | Alcian blue | 159.0 | – | 7.0 | – | – | Experiments | Mallampati et al. (2015) | |
Fibre | MAC | Methylene blue | – | 70.0 | – | 7.0 | – | – | Experiments | Mallampati et al. (2015) |
Fibre | MAC | Neutral red | – | 50.0 | – | 7.0 | – | – | Experiments | Mallampati et al. (2015) |
Fibre | MAC | Coomaise brilliant blue | – | 35.0 | – | 7.0 | – | – | Experiments | Mallampati et al. (2015) |
Husk | MC | Methylene blue | – | 1,682.7 | – | 9.0 | 47 | – | Langmuir | Guin et al. (2018) |
Husk | MAC | Methylene blue | – | 662.25 | 0.3 | 4.0 | 45 | – | Langmuir | Khodaie et al. (2013) |
Husk | MB | Methylene blue | – | 50.69 | 2.0 | 6.0 | 25 | – | Langmuir | Paşka et al. (2014) |
Husk | MB | Methylene blue | 90.0 | 30.30 | – | 6.2 | 28 | – | Langmuir | Malik et al. (2016) |
Husk | MB | Methylene blue | – | 20.66 | – | 6.5 | – | 2.49 | Langmuir | Pezhhanfar & Zarei (2021) |
Husk | MAC | Methylene blue | 98.50 | – | 5.0 | 10.3 | 25 | 3.01 | Experiments | Ponce et al. (2021) |
Husk leaf | MAC | Malachite green | – | 81.50 | 2.5 | 6.0 | 50 | – | Langmuir | Jalil et al. (2012) |
Leaf | MBC | Methylene blue | 89.32 | – | – | – | 25 | 2.72 | Experiments | Mu et al. (2020) |
Leaves | MAC | Methyl orange | 93.00 | 13.85 | – | 9.0 | 30 | – | Langmuir | Fadhil & Eisa (2019) |
Leaves | MAC | Methyl orange | 71.00 | 4.93 | – | 9.0 | 30 | – | Langmuir | Fadhil & Eisa (2019) |
Leaves | MAC | Malachite green | 91.5 | – | 2.5 | 5.8 | 3.0 | – | Langmuir | Fadhel et al. (2021) |
Leaves | MAC | Indigo carmen | 91.0 | – | 0.3 | 12.0 | 30 | – | Langmuir | Fadhil et al. (2021) |
Pericarp | MAC | Methyl orange | 50.0 | 141.13 | – | – | – | 23.31 | Experiments | Loya-González et al. (2019) |
Pericarp | MB | Methylene blue | – | 110.90 | 1.0 | 8.0 | 35 | 1.53 | Langmuir | Rosas-Castor et al. (2014) |
Pith | MAC | Malachite green | – | 488.3 | 1.6 | 7.0 | 30 | 0.01 | Langmuir | Jothirani et al. (2016) |
Porous starch | MAC | Neutral red | – | 13.05 | – | – | – | 196.88 | Experiments | Guo et al. (2015b) |
Porous starch | MAC | Methylene blue | – | 12.94 | – | – | – | 196.88 | Experiments | Guo et al. (2015b) |
Root | MBC | Methylene blue | 41.12 | – | – | – | 25 | 2.72 | Experiments | Mu et al. (2020) |
Silk | MB | Methylene blue | – | 234.10 | – | 12.0 | – | – | Langmuir | Miraboutalebi et al. (2017) |
Silk | MB | Reactive blue 19 | 99.00 | 71.60 | 5.0 | 2.0 | 25 | – | Langmuir | Değermenci et al. (2019) |
Silk | MB | Reactive red 218 | 99.00 | 63.30 | 5.0 | 2.0 | 25 | – | Langmuir | Değermenci et al. (2019) |
Silk | MC | Direct blue 15 | 99.76 | – | – | 3.0 | 25 | – | Experiments | Nadaroğlu et al. (2018) |
Silk | MBC | Methylene blue | 20.94 | – | – | – | 25 | 2.72 | Experiments | Mu et al. (2020) |
Stalk | MAC | Methylene blue | 94.0 | 870.0 | 0.1 | 7.0 | – | – | Langmuir | Tang et al. (2021) |
Stalk | MAC | Congo red | – | 549.0 | – | – | – | 201.0 | Experiments | Li et al. (2019b) |
Stalk | MB | Methylene blue | – | 500.0 | 4.0 | 6.8 | – | – | Langmuir | Maghri et al. (2012) |
Stalk | MBC | Methylene blue | 100.0 | 406.43 | – | 11.0 | – | – | Langmuir | Liu et al. (2019) |
Stalk | MAC | Methylene blue | – | 370.0 | – | 11.0 | – | – | Langmuir | Wen et al. (2018) |
Stalk | MAC | Coomaise brilliant blue | – | 302.0 | – | – | – | 201.0 | Experiments | Li et al. (2019)b |
Stalk | MBC | Methylene blue | 86.0 | 230.39 | – | 11.0 | – | – | Langmuir | Liu et al. (2019) |
Stalk | MAC | Methylene blue | 97.0 | 129.0 | 2.0 | 9.0 | 35 | – | Langmuir | Tang et al. (2019) |
Stalk | MB | Crystal violet | 82.0 | 120 | 0.1 | 10.0 | – | – | Experiments | Muhammad et al. (2019) |
Stalk | MAC | Methylene blue | 99.70 | 49.01 | 0.2 | – | 50 | – | Experiments | Ma et al. (2017) |
Stalk | MBC | Methylene blue | 41.0 | 43.14 | – | 11.0 | – | – | Langmuir | Liu et al. (2019) |
Stalk | MAC | Acid orange | – | 31.06 | – | 3.0 | 30 | 42.60 | Langmuir | Soldatkina & Zavrichko (2018) |
Stalk | MAC | Acid red | – | 30.77 | – | 3.0 | 30 | 42.60 | Langmuir | Soldatkina & Zavrichko (2018) |
Stalk | MAC | Malachite green | – | 27.55 | – | 6.0 | 60 | 45.3 | Langmuir | Soldatkina & Yanar (2021) |
Stalk | MAC | Direct red 23 | 99.00 | 27.11 | 0.2 | 3.0 | 25 | – | Langmuir | Fathi et al. (2015) |
Stalk | MAC | Methylene blue | – | 26.60 | – | 6.0 | 60 | 45.3 | Langmuir | Soldatkina & Yanar (2021) |
Stalk | MB | Malachite green | – | 11.77 | – | 6.0 | – | 4.79 | Langmuir | Lara-Vásquez et al. (2016) |
Stalk | MAC | Methylene blue | – | 8.75 | – | – | – | – | Langmuir | Wu et al. (2017) |
Stalk | MAC | Rhodamine B | 89.60 | 5.60 | 2.5 | 3.0 | – | – | Langmuir | Mousavi et al. (2021) |
Stalk | MAC | Methylene blue | 99.50 | 2.34 | 1.4 | 11.0 | – | – | Langmuir | Mousavi et al. (2020) |
Stalk | MBC | Phenol | 95.88 | – | – | – | 25 | 325.90 | Experiments | Li et al. (2019a) |
Stalk | MB | Malachite green | 90.00 | – | – | 7.0 | – | – | Experiments | Abubakar & Batagarawa (2017) |
Stalk | UM | Coomaise brilliant blue | 85.0 | – | 2.0 | 3.0 | 25 | – | Experiments | Taha et al. (2021) |
Stalk | MB | Congo red | 84.70 | – | – | – | – | – | Experiments | Abubakar & Batagarawa (2017) |
Stalk | MAC | Coomaise brilliant blue | 80.0 | – | 2.0 | 3.0 | 25 | – | Experiments | Taha et al. (2021) |
Stalk | MAC | Alizarin yellow | 75.85 | – | 0.6 | – | 30 | – | Langmuir | Ismail et al. (2019) |
Stalk | MAC | Coomaise brilliant blue | 50.0 | – | 4.0 | 3.0 | 25 | – | Experiments | Taha et al. (2021) |
Stalk | MBC | Methylene blue | 23.32 | – | – | – | 25 | 2.72 | Experiments | Mu et al. (2020) |
Stalk + walnut shell | MAC | Malachite green | – | 450.78 | – | – | 20 | 1,187.00 | Langmuir | Kang et al. (2018) |
Stalk pith | MAC | Crystal violet | – | 566.27 | 0.25 | 10 | 45 | – | Experiments | Peng et al. (2021) |
Stalk pith | MAC | Methylene blue | – | 422.13 | 0.25 | 10 | 25 | – | Experiments | Peng et al. (2021) |
Starch | MAC | Tartrazine | – | 293.0 | – | 2.5 | 35 | – | Langmuir | Dai et al. (2017) |
Starch | MB | Methylene blue | – | 6.40 | – | – | – | 0.42 | Experiments | Guo et al. (2015b) |
Starch | MB | Neutral red | – | 5.87 | – | – | – | 0.42 | Experiments | Guo et al. (2015b) |
Stem | MAC | Bromophenol blue | – | – | – | – | – | – | Experiments | Dada et al. (2012) |
Stem | MAC | Methyl orange solution | – | – | – | – | – | – | Experiments | Dada et al. (2012) |
Stem tissue | MB | Eriochrome black T | 66.80 | 167.01 | 1.0 | 2.0 | 25 | 7.23 | Langmuir | Vučurović et al. (2014) |
Stem tissue | MB | Methylene blue | 99.90 | 160.84 | 1.0 | 6.0 | 25 | 7.23 | Langmuir | Vučurović et al. (2014) |
Stigmata | MB | Methylene blue | 33.90 | 106.30 | – | 7.0 | – | – | Experiments | Mbarki et al. (2018) |
Stigmata | MB | Indigo carmine | 69.68 | 63.70 | – | 2.0 | – | – | Experiments | Mbarki et al. (2018) |
Stover | MAC | Reactive red 141 | – | 15.65 | 3.0 | 3.0 | – | 0.69 | Langmuir | Carijo et al. (2019) |
Straw | MAC | Rhodamine B | – | 1,578.0 | – | 7.0 | – | 1,993.00 | Langmuir | Chen et al. (2019) |
Straw | MB | Malachite green | – | 524.25 | – | 6.0 | 55 | 0.85 | Experiments | Lima et al. (2018) |
Straw | MBC | Malachite green | 99.00 | 515.77 | 0.3 | 6.0 | 25 | 80.10 | Langmuir | Eltaweil et al. (2020) |
Straw | MB | Malachite green | 77.0 | 200.0 | 0.5 | 6.0 | 55 | 0.85 | Experiments | Lima et al. (2017) |
Straw | MAC | Methylene blue | – | 196.46 | – | 6.0 | 60 | – | Experiments | Zhao et al. (2014) |
Straw | MAC | Reactive brilliant red K-2BP | 83.40 | 178.75 | 2.0 | 3.0 | 45 | 937.0 | Langmuir | Ren et al. (2020) |
Straw | MAC | Green 40 | – | 152.75 | – | 2.0 | – | – | Langmuir | Umpuch (2015) |
Straw | MAC | Reactive brilliant yellow K-6G | 79.30 | 140.84 | 2.0 | 3.0 | 45 | 937.0 | Langmuir | Ren et al. (2020) |
Straw | MAC | Yellow 20 | 95.67 | – | – | 2.0 | – | 4.21 | Experiments | Umpuch & Jutarat (2013) |
Straw | MAC | Blue 21 | 94.70 | – | – | 2.0 | – | 4.21 | Experiments | Umpuch & Jutarat (2013) |
Straw + waste red mud | MBC | Acidic black | – | 70.90 | – | 1.0 | – | 20.34 | Experiments | Gao et al. (2021) |
Straw pith | MAC | Malachite green | – | 242.13 | – | 12.0 | 25 | – | Langmuir | Chen et al. (2020) |
Straw pith | MAC | Methylene blue | – | 215.05 | – | 12.0 | 25 | – | Langmuir | Chen et al. (2020) |
Straw pith | MAC | Rhodamine B | – | 213.68 | – | 12.0 | 25 | – | Langmuir | Chen et al. (2020) |
Tassel | MAC | Methylene blue | – | 200.0 | – | 10.0 | 30 | – | Langmuir | Olorundare et al. (2014) |
Tassel | MBC | Methylene blue | 59.08 | – | – | – | 25 | 2.72 | Experiments | Mu et al. (2020) |
Tassel powder | MAC | Reactive red 198 | 97.00 | 16.95 | 2.0 | 3.0 | – | – | Langmuir | Dehvari et al. (2013) |
Plant parts . | Adsorbent class . | Adsorbate dye . | RE% . | (mg/g) . | Dosage (g/L) . | pH . | Temp (°C) . | SSA (m2/g) . | Method of determination . | References . |
---|---|---|---|---|---|---|---|---|---|---|
Cob | MAC | Gentian violet | – | 700.0 | – | 3.0 | – | – | Dubinin-Radushkevich | Javed et al. (2021) |
Cob | MAC | Methyl orange | – | 555.56 | – | 6.5 | 25 | 784.76 | Langmuir | Wang et al. (2018) |
Cob | MAC | Malachite green | 94.48 | 313.63 | 1.0 | 12.0 | 25 | – | Langmuir | Farnane et al. (2018) |
Cob | MAC | Methylene blue | 99.98 | 271.19 | 1.0 | 12.0 | 25 | – | Langmuir | Farnane et al. (2018) |
Cob | MAC | Methylene blue | – | 216.60 | 0.1 | 5.6 | 30 | – | Langmuir | Jawad et al. (2018) |
Cob | MAC | Indigo carmine | 90.13 | 118.48 | – | – | 25 | 809.80 | Langmuir | Zhang et al. (2014) |
Cob | MAC | Methylene blue | – | 100.0 | 0.02 | 7.0 | – | 650.0 | Langmuir | Reddy et al. (2016) |
Cob | MAC | Congo red | – | 98.72 | 1.0 | 7.0 | 35 | – | Langmuir | Velmurugan et al. (2016) |
Cob | MAC | Maxilone | – | 86.89 | 0.1 | 10.0 | 45 | – | Langmuir | Aljeboree & Alkaim (2019) |
Cob | MBC | Methyl orange | – | 86.38 | – | – | – | 468.59 | Langmuir | Zhang et al. (2020) |
Cob | MB | Malachite green | 92.11 | 76.42 | 4.0 | 12.0 | 25 | – | Langmuir | Farnane et al. (2018) |
Cob | MB | Methylene blue | 94.41 | 75.27 | 4.0 | 12.0 | 25 | – | Langmuir | Farnane et al. (2018) |
Cob | MAC | Tartrazine | 76.90 | 68.78 | – | – | 25 | 809.80 | Langmuir | Zhang et al. (2014) |
Cob | MAC | Malachite green | 99.3 | 66.52 | – | 6.0 | – | 13.29 | Langmuir | Ojediran et al. (2021) |
Cob | MAC | Congo red | – | 50.0 | – | – | 30 | – | Langmuir | Ojedokun & Bello (2017) |
Cob | MAC | Methylene blue | 96.0 | 46.28 | 2.0 | 12.0 | 20 | – | Experiments | Miyah et al. (2016) |
Cob | MAC | Methylene blue | – | 41.94 | 0.1 | 10.0 | 45 | – | Langmuir | Aljeboree & Alkaim (2019) |
Cob | MAC | Methylene blue | – | 37.45 | 0.5 | 6.0 | 50 | – | Langmuir | Aljeboree et al. (2019) |
Cob | MC | Malachite green | – | 35.34 | – | 4.0 | – | – | Langmuir | Ong et al. (2017) |
Cob | MAC | Crystal violet | – | 33.86 | 0.1 | 10.0 | 45 | – | Langmuir | Aljeboree & Alkaim (2019) |
Cob | MAC | Methylene blue | 99.40 | 28.65 | 2.0 | 8.0 | 25 | 700.00 | Langmuir | El-Sayed et al. (2014) |
Cob | MAC | Sulfur dioxide | – | 19.8 | – | – | – | 591.0 | Experiments | Wu et al. (2013) |
Cob | MAC | Methylene blue | 44.60 | 17.75 | 2.0 | 8.0 | 25 | 633.00 | Langmuir | El-Sayed et al. (2014) |
Cob | MB | Methylene blue | – | 16.08 | – | 6.5 | – | 0.40 | Langmuir | Pezhhanfar & Zarei (2021) |
Cob | MB | Congo red | – | 4.83 | – | 7.0 | – | – | Experiments | Yaneva & Georgieva (2013) |
Cob | MAC | Methylene blue | 92.20 | 0.81 | 2.0 | 8.0 | 25 | 600.00 | Langmuir | El-Sayed et al. (2014) |
Cob | MC | Acid yellow | – | 0.24 | – | 4.0 | – | – | Langmuir | Ong et al. (2017) |
Cob | MAC | Methylene blue | 99.90 | – | 5.0 | – | – | – | Experiments | Ali et al. (2017) |
Cob | MAC | Methylene blue | 99.89 | – | 10.0 | 6.0 | 27 | – | Experiments | Tan et al. (2012) |
Cob | MAC | Brilliant green | 99.60 | – | 5.0 | – | – | – | Experiments | Ali et al. (2017) |
Cob | MAC | Malachite green | 99.39 | – | 10.0 | 7.0 | 29 | – | Experiments | Ismail et al. (2018) |
Cob | MAC | Congo red | 98.10 | – | 0.3 | 6.8 | 27 | – | Experiments | Leelavathy et al. (2015) |
Cob | MAC | Congo red | 97.80 | – | 1.2 | 6.8 | 27 | – | Experiments | Leelavathy et al. (2015) |
Cob | MB | Methylene blue | 96.94 | – | 0.4 | 5.0 | – | – | Langmuir | Fatoye & Onigbinde (2020) |
Cob | MB | Bromophenol blue | 96.53 | – | 4.0 | 2.0 | – | – | Experiments | Abubakar & Ibrahim (2018) |
Cob | MB | Bromothymol blue | 94.39 | – | 0.5 | 2.0 | – | – | Experiments | Abubakar & Ibrahim (2018) |
Cob | MC | Congo red | 91.28 | – | 1.2 | 3.0 | 30 | – | Experiments | Qu et al. (2020) |
Cob | MAC | Methylene blue | 90.86 | – | 0.2 | 7.0 | – | 293.12 | Experiments | Ramamoorthy et al. (2020) |
Cob | MB | Direct blue 199 | 90.0 | – | 8.0 | 7.6 | 28 | – | Experiments | Saroj et al. (2015) |
Cob | MBC | Methylene blue | 82.0 | – | – | – | – | – | Experiments | Mohanraj et al. (2020) |
Cob | MAC | Methyl orange | 80.36 | – | 5.0 | – | 25 | – | Experiments | Abdullah et al. (2019) |
Cob | MB | Congo red | 80.21 | – | 1.2 | 3.0 | 30 | – | Experiments | Qu et al. (2020) |
Cob | MBC | Rhodamine B | 80.0 | – | – | – | – | – | Experiments | Mohanraj et al. (2020) |
Cob | MBC | Methylene blue | 64.0 | – | – | 8.0 | 25 | – | Experiments | Tsamo et al. (2019) |
Cob | MBC | Methylene blue | 33.38 | – | – | – | 25 | 2.72 | Experiments | Mu et al. (2020) |
Cob leaves | MB | Basic violet 4 | 98.4 | 89.0 | 2.0 | 5.4 | 57 | – | Langmuir | Sepúlveda et al. (2015) |
Cover | MC | Alizarin red S | – | 10.5 | 0.2 | 2.0 | – | – | Langmuir | Zolgharnein et al. (2016) |
Ear | MBC | Methylene blue | 44.13 | – | – | – | 25 | 2.72 | Experiments | Mu et al. (2020) |
Fibre | MAC | Alcian blue | 159.0 | – | 7.0 | – | – | Experiments | Mallampati et al. (2015) | |
Fibre | MAC | Methylene blue | – | 70.0 | – | 7.0 | – | – | Experiments | Mallampati et al. (2015) |
Fibre | MAC | Neutral red | – | 50.0 | – | 7.0 | – | – | Experiments | Mallampati et al. (2015) |
Fibre | MAC | Coomaise brilliant blue | – | 35.0 | – | 7.0 | – | – | Experiments | Mallampati et al. (2015) |
Husk | MC | Methylene blue | – | 1,682.7 | – | 9.0 | 47 | – | Langmuir | Guin et al. (2018) |
Husk | MAC | Methylene blue | – | 662.25 | 0.3 | 4.0 | 45 | – | Langmuir | Khodaie et al. (2013) |
Husk | MB | Methylene blue | – | 50.69 | 2.0 | 6.0 | 25 | – | Langmuir | Paşka et al. (2014) |
Husk | MB | Methylene blue | 90.0 | 30.30 | – | 6.2 | 28 | – | Langmuir | Malik et al. (2016) |
Husk | MB | Methylene blue | – | 20.66 | – | 6.5 | – | 2.49 | Langmuir | Pezhhanfar & Zarei (2021) |
Husk | MAC | Methylene blue | 98.50 | – | 5.0 | 10.3 | 25 | 3.01 | Experiments | Ponce et al. (2021) |
Husk leaf | MAC | Malachite green | – | 81.50 | 2.5 | 6.0 | 50 | – | Langmuir | Jalil et al. (2012) |
Leaf | MBC | Methylene blue | 89.32 | – | – | – | 25 | 2.72 | Experiments | Mu et al. (2020) |
Leaves | MAC | Methyl orange | 93.00 | 13.85 | – | 9.0 | 30 | – | Langmuir | Fadhil & Eisa (2019) |
Leaves | MAC | Methyl orange | 71.00 | 4.93 | – | 9.0 | 30 | – | Langmuir | Fadhil & Eisa (2019) |
Leaves | MAC | Malachite green | 91.5 | – | 2.5 | 5.8 | 3.0 | – | Langmuir | Fadhel et al. (2021) |
Leaves | MAC | Indigo carmen | 91.0 | – | 0.3 | 12.0 | 30 | – | Langmuir | Fadhil et al. (2021) |
Pericarp | MAC | Methyl orange | 50.0 | 141.13 | – | – | – | 23.31 | Experiments | Loya-González et al. (2019) |
Pericarp | MB | Methylene blue | – | 110.90 | 1.0 | 8.0 | 35 | 1.53 | Langmuir | Rosas-Castor et al. (2014) |
Pith | MAC | Malachite green | – | 488.3 | 1.6 | 7.0 | 30 | 0.01 | Langmuir | Jothirani et al. (2016) |
Porous starch | MAC | Neutral red | – | 13.05 | – | – | – | 196.88 | Experiments | Guo et al. (2015b) |
Porous starch | MAC | Methylene blue | – | 12.94 | – | – | – | 196.88 | Experiments | Guo et al. (2015b) |
Root | MBC | Methylene blue | 41.12 | – | – | – | 25 | 2.72 | Experiments | Mu et al. (2020) |
Silk | MB | Methylene blue | – | 234.10 | – | 12.0 | – | – | Langmuir | Miraboutalebi et al. (2017) |
Silk | MB | Reactive blue 19 | 99.00 | 71.60 | 5.0 | 2.0 | 25 | – | Langmuir | Değermenci et al. (2019) |
Silk | MB | Reactive red 218 | 99.00 | 63.30 | 5.0 | 2.0 | 25 | – | Langmuir | Değermenci et al. (2019) |
Silk | MC | Direct blue 15 | 99.76 | – | – | 3.0 | 25 | – | Experiments | Nadaroğlu et al. (2018) |
Silk | MBC | Methylene blue | 20.94 | – | – | – | 25 | 2.72 | Experiments | Mu et al. (2020) |
Stalk | MAC | Methylene blue | 94.0 | 870.0 | 0.1 | 7.0 | – | – | Langmuir | Tang et al. (2021) |
Stalk | MAC | Congo red | – | 549.0 | – | – | – | 201.0 | Experiments | Li et al. (2019b) |
Stalk | MB | Methylene blue | – | 500.0 | 4.0 | 6.8 | – | – | Langmuir | Maghri et al. (2012) |
Stalk | MBC | Methylene blue | 100.0 | 406.43 | – | 11.0 | – | – | Langmuir | Liu et al. (2019) |
Stalk | MAC | Methylene blue | – | 370.0 | – | 11.0 | – | – | Langmuir | Wen et al. (2018) |
Stalk | MAC | Coomaise brilliant blue | – | 302.0 | – | – | – | 201.0 | Experiments | Li et al. (2019)b |
Stalk | MBC | Methylene blue | 86.0 | 230.39 | – | 11.0 | – | – | Langmuir | Liu et al. (2019) |
Stalk | MAC | Methylene blue | 97.0 | 129.0 | 2.0 | 9.0 | 35 | – | Langmuir | Tang et al. (2019) |
Stalk | MB | Crystal violet | 82.0 | 120 | 0.1 | 10.0 | – | – | Experiments | Muhammad et al. (2019) |
Stalk | MAC | Methylene blue | 99.70 | 49.01 | 0.2 | – | 50 | – | Experiments | Ma et al. (2017) |
Stalk | MBC | Methylene blue | 41.0 | 43.14 | – | 11.0 | – | – | Langmuir | Liu et al. (2019) |
Stalk | MAC | Acid orange | – | 31.06 | – | 3.0 | 30 | 42.60 | Langmuir | Soldatkina & Zavrichko (2018) |
Stalk | MAC | Acid red | – | 30.77 | – | 3.0 | 30 | 42.60 | Langmuir | Soldatkina & Zavrichko (2018) |
Stalk | MAC | Malachite green | – | 27.55 | – | 6.0 | 60 | 45.3 | Langmuir | Soldatkina & Yanar (2021) |
Stalk | MAC | Direct red 23 | 99.00 | 27.11 | 0.2 | 3.0 | 25 | – | Langmuir | Fathi et al. (2015) |
Stalk | MAC | Methylene blue | – | 26.60 | – | 6.0 | 60 | 45.3 | Langmuir | Soldatkina & Yanar (2021) |
Stalk | MB | Malachite green | – | 11.77 | – | 6.0 | – | 4.79 | Langmuir | Lara-Vásquez et al. (2016) |
Stalk | MAC | Methylene blue | – | 8.75 | – | – | – | – | Langmuir | Wu et al. (2017) |
Stalk | MAC | Rhodamine B | 89.60 | 5.60 | 2.5 | 3.0 | – | – | Langmuir | Mousavi et al. (2021) |
Stalk | MAC | Methylene blue | 99.50 | 2.34 | 1.4 | 11.0 | – | – | Langmuir | Mousavi et al. (2020) |
Stalk | MBC | Phenol | 95.88 | – | – | – | 25 | 325.90 | Experiments | Li et al. (2019a) |
Stalk | MB | Malachite green | 90.00 | – | – | 7.0 | – | – | Experiments | Abubakar & Batagarawa (2017) |
Stalk | UM | Coomaise brilliant blue | 85.0 | – | 2.0 | 3.0 | 25 | – | Experiments | Taha et al. (2021) |
Stalk | MB | Congo red | 84.70 | – | – | – | – | – | Experiments | Abubakar & Batagarawa (2017) |
Stalk | MAC | Coomaise brilliant blue | 80.0 | – | 2.0 | 3.0 | 25 | – | Experiments | Taha et al. (2021) |
Stalk | MAC | Alizarin yellow | 75.85 | – | 0.6 | – | 30 | – | Langmuir | Ismail et al. (2019) |
Stalk | MAC | Coomaise brilliant blue | 50.0 | – | 4.0 | 3.0 | 25 | – | Experiments | Taha et al. (2021) |
Stalk | MBC | Methylene blue | 23.32 | – | – | – | 25 | 2.72 | Experiments | Mu et al. (2020) |
Stalk + walnut shell | MAC | Malachite green | – | 450.78 | – | – | 20 | 1,187.00 | Langmuir | Kang et al. (2018) |
Stalk pith | MAC | Crystal violet | – | 566.27 | 0.25 | 10 | 45 | – | Experiments | Peng et al. (2021) |
Stalk pith | MAC | Methylene blue | – | 422.13 | 0.25 | 10 | 25 | – | Experiments | Peng et al. (2021) |
Starch | MAC | Tartrazine | – | 293.0 | – | 2.5 | 35 | – | Langmuir | Dai et al. (2017) |
Starch | MB | Methylene blue | – | 6.40 | – | – | – | 0.42 | Experiments | Guo et al. (2015b) |
Starch | MB | Neutral red | – | 5.87 | – | – | – | 0.42 | Experiments | Guo et al. (2015b) |
Stem | MAC | Bromophenol blue | – | – | – | – | – | – | Experiments | Dada et al. (2012) |
Stem | MAC | Methyl orange solution | – | – | – | – | – | – | Experiments | Dada et al. (2012) |
Stem tissue | MB | Eriochrome black T | 66.80 | 167.01 | 1.0 | 2.0 | 25 | 7.23 | Langmuir | Vučurović et al. (2014) |
Stem tissue | MB | Methylene blue | 99.90 | 160.84 | 1.0 | 6.0 | 25 | 7.23 | Langmuir | Vučurović et al. (2014) |
Stigmata | MB | Methylene blue | 33.90 | 106.30 | – | 7.0 | – | – | Experiments | Mbarki et al. (2018) |
Stigmata | MB | Indigo carmine | 69.68 | 63.70 | – | 2.0 | – | – | Experiments | Mbarki et al. (2018) |
Stover | MAC | Reactive red 141 | – | 15.65 | 3.0 | 3.0 | – | 0.69 | Langmuir | Carijo et al. (2019) |
Straw | MAC | Rhodamine B | – | 1,578.0 | – | 7.0 | – | 1,993.00 | Langmuir | Chen et al. (2019) |
Straw | MB | Malachite green | – | 524.25 | – | 6.0 | 55 | 0.85 | Experiments | Lima et al. (2018) |
Straw | MBC | Malachite green | 99.00 | 515.77 | 0.3 | 6.0 | 25 | 80.10 | Langmuir | Eltaweil et al. (2020) |
Straw | MB | Malachite green | 77.0 | 200.0 | 0.5 | 6.0 | 55 | 0.85 | Experiments | Lima et al. (2017) |
Straw | MAC | Methylene blue | – | 196.46 | – | 6.0 | 60 | – | Experiments | Zhao et al. (2014) |
Straw | MAC | Reactive brilliant red K-2BP | 83.40 | 178.75 | 2.0 | 3.0 | 45 | 937.0 | Langmuir | Ren et al. (2020) |
Straw | MAC | Green 40 | – | 152.75 | – | 2.0 | – | – | Langmuir | Umpuch (2015) |
Straw | MAC | Reactive brilliant yellow K-6G | 79.30 | 140.84 | 2.0 | 3.0 | 45 | 937.0 | Langmuir | Ren et al. (2020) |
Straw | MAC | Yellow 20 | 95.67 | – | – | 2.0 | – | 4.21 | Experiments | Umpuch & Jutarat (2013) |
Straw | MAC | Blue 21 | 94.70 | – | – | 2.0 | – | 4.21 | Experiments | Umpuch & Jutarat (2013) |
Straw + waste red mud | MBC | Acidic black | – | 70.90 | – | 1.0 | – | 20.34 | Experiments | Gao et al. (2021) |
Straw pith | MAC | Malachite green | – | 242.13 | – | 12.0 | 25 | – | Langmuir | Chen et al. (2020) |
Straw pith | MAC | Methylene blue | – | 215.05 | – | 12.0 | 25 | – | Langmuir | Chen et al. (2020) |
Straw pith | MAC | Rhodamine B | – | 213.68 | – | 12.0 | 25 | – | Langmuir | Chen et al. (2020) |
Tassel | MAC | Methylene blue | – | 200.0 | – | 10.0 | 30 | – | Langmuir | Olorundare et al. (2014) |
Tassel | MBC | Methylene blue | 59.08 | – | – | – | 25 | 2.72 | Experiments | Mu et al. (2020) |
Tassel powder | MAC | Reactive red 198 | 97.00 | 16.95 | 2.0 | 3.0 | – | – | Langmuir | Dehvari et al. (2013) |
Corn husks have been studied by Ponce et al. (2021) for their potential to remove methylene blue from liquids. The polymeric component of the fibre was removed from the biowaste using a 0.10 mol/L NaOH solution, which also helped to increase dye's adsorption. Characterization revealed that the main components of the corn husk adsorbent, which has a BET surface area of 3.01 m2/g, are cellulose, hemicellulose, and lignin. More than 90% of the dye was removed in 2 h, according to the adsorption analysis, which demonstrated that the alkali treatment boosted adsorbent's attractiveness towards the adsorbate. A composite made of corncob and GO was created by Qu et al. (2020), and its efficacy in the adsorptive removal of Congo red from wastewater was investigated. The outcome demonstrated the presence of many functional groups in the composite, including hydroxyl, carboxyl, phenol, and alcohol groups, which provided enough binding sites and facilitated dye adsorption. The amount of dye removed rose in response to an increase in adsorbent dosage and reached 80% in 60 min. The process was endothermic and involved chemical adsorption mechanisms. Similar to this, Zolgharnein et al. (2016) evaluated the efficacy of a composite sorbent for the removal of Alizarin red S dye from liquids by impregnating Fe3O4 nanoparticles onto corn cover in a ratio of 1:10. At ideal pH of 2, an adsorbent dosage of 0.2 g, and dye concentration of 10 mg/L, a maximum adsorption capacity of 11.35 mg/g, and a removal efficiency of 80.1% were achieved. The adsorption results were well fitted by pseudo-second-order kinetic, Langmuir, Freudlich, and Dubinin–Radushkevich isotherm models, whereas thermodynamic investigations suggested a spontaneous and exothermic process.
Li et al. (2019b) synthesized a cellulose-rich aerogel in a single step by using a linked solvent system to separate lignin from other corn stalk constituents. The aerogel has a huge surface area (201 m2/g), a porous, three-dimensional structure, and good thermal stability. Congo red and Coomassie brilliant blue had maximum adsorption capacities of 549 and 302 mg/g, respectively, according to a simulation of the aerogel adsorbent in dye-contaminated water. The study offers a practical, eco-friendly method for producing corn stalk material with good water treatment capabilities. Furthermore, Eltaweil et al. (2020) investigated the potential of a composite prepared from corn stalk biochar (CSB) and zero-valent iron nanoparticles (nZVI) to adsorb malachite green dye from solution. The results of the various techniques used to analyse the composite adsorbent, including FT-IR, XRD, SEM, and TGA, showed that it was a magnetic composite with a mesoporous structure, several functional groups, and a large surface area (80.1 m2/g). The adsorption data involved both adsorption and oxidation mechanisms, with a removal efficiency of up to 99.9% attained in 20 min. They also fit well with second-order reaction kinetics and the Langmuir isotherm. Comparing the adsorbent to the individual components (CSB and nZVI), it also demonstrated a higher adsorption capacity (515.77 mg/g), and its magnetic property makes separation easier. The summary of the findings is presented in Table 2.
MECHANISM OF DYE ADSORPTION BY MAIZE-BASED ADSORBENTS
Plant parts . | Adsorbent class . | Dye . | Optimum pH . | pHzc . | Adsorption mechanism . | References . |
---|---|---|---|---|---|---|
Cob | MB | Methylene blue | 6.5 | – | interaction, hydrogen bonds | Pezhhanfar & Zarei (2021) |
Husk | MB | Methylene blue | 6.5 | – | interaction, hydrogen bonds | Pezhhanfar & Zarei (2021) |
Stalk | MBC | Phenol | – | – | Pore-filling, electrostatic attraction, interaction | Li et al. (2019)a |
Stalk | MAC | Acid red | 3.0 | 5.1 | Ion exchange, chemisorption | Soldatkina & Zavrichko (2018) |
Stalk | MAC | Acid orange | 3.0 | 5.1 | Ion exchange, chemisorption | Soldatkina & Zavrichko (2018) |
Stalk | MAC | Congo red | – | – | Hydrogen bonding, interaction | Li et al. (2019b) |
Stalk | MAC | Coomaise brilliant blue | – | – | Hydrogen bonding, interaction | Li et al. (2019b) |
Pericarp | MB | Methylene blue | 8.0 | 3.6 | Electrostatic repulsion | Rosas-Castor et al. (2014) |
Cob | MB | Congo red | 7.0 | 7.2 | Electrostatic interactions, H-bonding, hydrophobic–hydrophobic interactions | Yaneva & Georgieva (2013) |
Cob | MBC | Methyl orange | – | – | Electrostatic interactions, electron sharing, electron exchange | Zhang et al. (2020) |
Silk | MB | Reactive blue 19 | 12.0 | – | Electrostatic interactions | Değermenci et al. (2019) |
Silk | MB | Reactive red 218 | 12.0 | – | Electrostatic interactions | Değermenci et al. (2019) |
Stalk | MAC | Methylene blue | 11.0 | – | Electrostatic interactions | Wen et al. (2018) |
Stem tissue | MB | Methylene blue | 6.0 | 2.4 | Electrostatic interactions | Vučurović et al. (2014) |
Stem tissue | MB | Eriochrome black T | 2.0 | 2.4 | Electrostatic interactions | Vučurović et al. (2014) |
Straw | MAC | Green 40 | 2.0 | – | Electrostatic interactions | Umpuch (2015) |
Stalk | MBC | Methylene blue | 11.0 | – | Electrostatic interaction, hydrogen bonding, stacking, physical interaction | Liu et al. (2019) |
Straw | MAC | Tylosin | 12.0 | – | Electrostatic interaction, H-bonding and hydrophobic interactions | Guo et al. (2018) |
Straw | MAC | Tylosin | 12.0 | – | Electrostatic interaction, H-bonding and hydrophobic interactions | Guo et al. (2018) |
Straw | MB | Tylosin | 12.0 | – | Electrostatic interaction, H-bonding and hydrophobic interactions | Guo et al. (2018) |
Stalk | MAC | Direct red 23 | 12.0 | – | Electrostatic interaction, chemical reaction | Fathi et al. (2015) |
Cob | MB | Congo red | 3.0 | – | Electrostatic interaction | Qu et al. (2020) |
Cob | MC | Congo red | 3.0 | – | Electrostatic interaction | Qu et al. (2020) |
Cob leaves | MB | Basic violet 4 | 5.4 | 4.1 | Electrostatic interaction | Sepúlveda et al. (2015) |
Pith | MAC | Malachite green | 7.0 | – | Electrostatic interaction | Jothirani et al. (2016) |
Stalk | MAC | Rhodamine B | 3.0 | – | Electrostatic interaction | Mousavi et al. (2021) |
Stigmata | MB | Methylene blue | 7.0 | – | Electrostatic interaction | Mbarki et al. (2018) |
Cob | MAC | Gentian violet | 3.0 | 3.15 | Electrostatic attraction | Javed et al. (2021) |
Cob | MAC | Congo red | 7.0 | – | Electrostatic attraction | Velmurugan et al. (2016) |
Cob | MB | Bromophenol blue | 2.0 | 5.0 | Electrostatic attraction | Abubakar & Ibrahim (2018) |
Cob | MB | Bromothymol blue | 2.0 | 5.0 | Electrostatic attraction | Abubakar & Ibrahim (2018) |
Husk | MB | Methylene blue | 6.2 | – | Electrostatic attraction | Malik et al. (2016) |
Stalk | MAC | Methylene blue | 11.0 | 5.0 | Electrostatic attraction | Mousavi et al. (2020) |
Stalk | MAC | Methylene blue | 9.0 | 5.7 | Electrostatic attraction | Tang et al. (2019) |
Stalk | MAC | Methylene blue | 7.0 | 4.8 | Electrostatic attraction | Tang et al. (2021) |
Stigmata | MB | Indigo carmine | 2.0 | – | Electrostatic attraction | Mbarki et al. (2018) |
Straw | MAC | Reactive brilliant yellow K-6G | 3.0 | – | Electrostatic attraction | Ren et al. (2020) |
Straw | MAC | Reactive brilliant red K-2BP | 3.0 | – | Electrostatic attraction | Ren et al. (2020) |
Straw | MAC | Methylene blue | 6.0 | – | Electrostatic attraction | Zhao et al. (2014) |
Tassel | MAC | Methylene blue | 10.0 | – | Electrostatic attraction | Olorundare et al. (2014) |
Stalk | MB | Crystal violet | 10.0 | – | Chemisorption | Muhammad et al. (2019) |
Cob | MAC | Methylene blue | 11.0 | – | – | Ali et al. (2017) |
Cob | MAC | Brilliant green | 11.0 | – | – | Ali et al. (2017) |
Cob | MAC | Methylene blue | 10.0 | – | – | Aljeboree & Alkaim (2019) |
Cob | MAC | Crystal violet | 10.0 | – | – | Aljeboree & Alkaim (2019) |
Cob | MAC | Maxilone | 10.0 | – | – | Aljeboree & Alkaim (2019) |
Cob | MAC | Methylene blue | 6.0 | – | – | Aljeboree et al. (2019) |
Cob | MAC | Acetic acid | 5.6 | – | – | Dina et al. (2012) |
Cob | MAC | Methylene blue | 8.0 | – | – | El-Sayed et al. (2014) |
Cob | MAC | Methylene blue | 12.0 | – | – | Farnane et al. (2018) |
Cob | MAC | Methylene blue | 5.6 | 4.0 | – | Jawad et al. (2018) |
Cob | MAC | Congo red | 6.8 | – | – | Leelavathy et al. (2015) |
Cob | MAC | Methylene blue | 12.0 | – | – | Miyah et al. (2016) |
Cob | MAC | Malachite green | 6.0 | – | – | Ojediran et al. (2021) |
Cob | MAC | Methylene blue | 7.0 | – | – | Ramamoorthy et al. (2020) |
Cob | MAC | Methylene blue | 7.0 | – | – | Reddy et al. (2016) |
Cob | MAC | Malachite green | 7.0 | – | – | Ismail et al. (2018) |
Cob | MAC | Methylene blue | 6.0 | – | – | Tan et al. (2012) |
Cob | MAC | Methyl orange | 6.5 | – | – | Wang et al. (2018) |
Cob | MB | Methylene blue | 12.0 | – | – | Farnane et al. (2018) |
Cob | MB | Malachite green | 12.0 | – | – | Farnane et al. (2018) |
Cob | MB | Methylene blue | 5.0 | – | – | Fatoye & Onigbinde (2020) |
Cob | MB | Direct blue 199 | 7.6 | – | – | Saroj et al. (2015) |
Cob | MBC | Methylene blue | 8.0 | – | – | Tsamo et al. (2019) |
Cob | MC | Malachite green | 4.0 | – | – | Ong et al. (2017) |
Cob | MC | Acid yellow | 4.0 | – | – | Ong et al. (2017) |
Cover | MC | Alizarin red S | 2.0 | – | – | Zolgharnein et al. (2016) |
Fibre | MAC | Alcian blue | 7.0 | – | – | Mallampati et al. (2015) |
Fibre | MAC | Methylene blue | 7.0 | – | – | Mallampati et al. (2015) |
Fibre | MAC | Neutral red | 7.0 | – | – | Mallampati et al. (2015) |
Fibre | MAC | Coomaise brilliant blue | 7.0 | – | – | Mallampati et al. (2015) |
Husk | MAC | Methylene blue | 4.0 | – | – | Khodaie et al. (2013) |
Husk | MAC | Methylene blue | 10.3 | 3.8 | – | Ponce et al. (2021) |
Husk | MB | Methylene blue | 6.0 | – | – | Paşka et al. (2014) |
Husk | MC | Methylene blue | 9.0 | – | – | Guin et al. (2018) |
Husk leaf | MAC | Malachite green | 8.0 | – | – | Jalil et al. (2012) |
Leaves | MAC | Methyl orange | 9.0 | – | – | Fadhil & Eisa (2019) |
Leaves | MAC | Methyl orange | 9.0 | – | – | Fadhil & Eisa (2019) |
Leaves | MAC | Indigo carmen | 12.0 | – | – | Fadhil et al. (2021) |
Leaves | MAC | Malachite green | 10.0 | – | – | Fadhel et al. (2021) |
Pericarp | MAC | Methyl orange | – | 11.2 | – | Loya-González et al. (2019) |
Silk | MB | Methylene blue | 12.0 | – | – | Miraboutalebi et al. (2017) |
Silk | MC | Direct blue 15 | 3.0 | – | – | Nadaroğlu et al. (2018) |
Stalk | MAC | Methylene blue | 6.0 | – | – | Soldatkina & Yanar (2021) |
Stalk | MAC | Malachite green | 6.0 | – | – | Soldatkina & Yanar (2021) |
Stalk | MAC | Coomaise brilliant blue | 3.0 | – | – | Taha et al. (2021) |
Stalk | MB | Malachite green | 5.0 | – | – | Abubakar & Batagarawa (2017) |
Stalk | MB | Congo red | 5.0 | – | – | Abubakar & Batagarawa (2017) |
Stalk | MB | Malachite green | 6.0 | 6.8 | – | Lara-Vásquez et al. (2016) |
Stalk | MB | Methylene blue | 6.8 | – | – | Maghri et al. (2012) |
Stalk | MB | Coomaise brilliant blue | 3.0 | – | – | Taha et al. (2021) |
Stalk + walnut shell | MAC | Malachite green | 6.5 | – | – | Kang et al. (2018) |
Stalk pith | MAC | Methylene blue | 10.0 | – | – | Peng et al. (2021) |
Stalk pith | MAC | Crystal violet | 10.0 | – | – | Peng et al. (2021) |
Starch | MAC | Tartrazine | 2.5 | – | – | Dai et al. (2017) |
Stover | MAC | Reactive red 141 | 3.0 | – | – | Carijo et al. (2019) |
Straw | MAC | Blue 21 | 2.0 | – | – | Umpuch & Jutarat (2013) |
Straw | MAC | Yellow 20 | 2.0 | – | – | Umpuch & Jutarat (2013) |
Straw | MB | Malachite green | 6.0 | 2.3 | – | Lima et al. (2017) |
Straw | MB | Malachite green | 6.0 | – | – | Lima et al. (2018) |
Straw | MBC | Malachite green | 9.0 | – | – | Eltaweil et al. (2020) |
Straw + waste red mud | MBC | Acidic black | 4.0 | – | Gao et al. (2021) | |
Straw pith | MAC | Malachite green | 12.0 | – | – | Chen et al. (2020) |
Straw pith | MAC | Methylene blue | 12.0 | – | – | Chen et al. (2020) |
Straw pith | MAC | Rhodamine B | 12.0 | – | – | Chen et al. (2020) |
Tassel powder | MAC | Reactive red 198 | 9.0 | – | – | Dehvari et al. (2013) |
Cob | MAC | Malachite green | 12.0 | Farnane et al. (2018) |
Plant parts . | Adsorbent class . | Dye . | Optimum pH . | pHzc . | Adsorption mechanism . | References . |
---|---|---|---|---|---|---|
Cob | MB | Methylene blue | 6.5 | – | interaction, hydrogen bonds | Pezhhanfar & Zarei (2021) |
Husk | MB | Methylene blue | 6.5 | – | interaction, hydrogen bonds | Pezhhanfar & Zarei (2021) |
Stalk | MBC | Phenol | – | – | Pore-filling, electrostatic attraction, interaction | Li et al. (2019)a |
Stalk | MAC | Acid red | 3.0 | 5.1 | Ion exchange, chemisorption | Soldatkina & Zavrichko (2018) |
Stalk | MAC | Acid orange | 3.0 | 5.1 | Ion exchange, chemisorption | Soldatkina & Zavrichko (2018) |
Stalk | MAC | Congo red | – | – | Hydrogen bonding, interaction | Li et al. (2019b) |
Stalk | MAC | Coomaise brilliant blue | – | – | Hydrogen bonding, interaction | Li et al. (2019b) |
Pericarp | MB | Methylene blue | 8.0 | 3.6 | Electrostatic repulsion | Rosas-Castor et al. (2014) |
Cob | MB | Congo red | 7.0 | 7.2 | Electrostatic interactions, H-bonding, hydrophobic–hydrophobic interactions | Yaneva & Georgieva (2013) |
Cob | MBC | Methyl orange | – | – | Electrostatic interactions, electron sharing, electron exchange | Zhang et al. (2020) |
Silk | MB | Reactive blue 19 | 12.0 | – | Electrostatic interactions | Değermenci et al. (2019) |
Silk | MB | Reactive red 218 | 12.0 | – | Electrostatic interactions | Değermenci et al. (2019) |
Stalk | MAC | Methylene blue | 11.0 | – | Electrostatic interactions | Wen et al. (2018) |
Stem tissue | MB | Methylene blue | 6.0 | 2.4 | Electrostatic interactions | Vučurović et al. (2014) |
Stem tissue | MB | Eriochrome black T | 2.0 | 2.4 | Electrostatic interactions | Vučurović et al. (2014) |
Straw | MAC | Green 40 | 2.0 | – | Electrostatic interactions | Umpuch (2015) |
Stalk | MBC | Methylene blue | 11.0 | – | Electrostatic interaction, hydrogen bonding, stacking, physical interaction | Liu et al. (2019) |
Straw | MAC | Tylosin | 12.0 | – | Electrostatic interaction, H-bonding and hydrophobic interactions | Guo et al. (2018) |
Straw | MAC | Tylosin | 12.0 | – | Electrostatic interaction, H-bonding and hydrophobic interactions | Guo et al. (2018) |
Straw | MB | Tylosin | 12.0 | – | Electrostatic interaction, H-bonding and hydrophobic interactions | Guo et al. (2018) |
Stalk | MAC | Direct red 23 | 12.0 | – | Electrostatic interaction, chemical reaction | Fathi et al. (2015) |
Cob | MB | Congo red | 3.0 | – | Electrostatic interaction | Qu et al. (2020) |
Cob | MC | Congo red | 3.0 | – | Electrostatic interaction | Qu et al. (2020) |
Cob leaves | MB | Basic violet 4 | 5.4 | 4.1 | Electrostatic interaction | Sepúlveda et al. (2015) |
Pith | MAC | Malachite green | 7.0 | – | Electrostatic interaction | Jothirani et al. (2016) |
Stalk | MAC | Rhodamine B | 3.0 | – | Electrostatic interaction | Mousavi et al. (2021) |
Stigmata | MB | Methylene blue | 7.0 | – | Electrostatic interaction | Mbarki et al. (2018) |
Cob | MAC | Gentian violet | 3.0 | 3.15 | Electrostatic attraction | Javed et al. (2021) |
Cob | MAC | Congo red | 7.0 | – | Electrostatic attraction | Velmurugan et al. (2016) |
Cob | MB | Bromophenol blue | 2.0 | 5.0 | Electrostatic attraction | Abubakar & Ibrahim (2018) |
Cob | MB | Bromothymol blue | 2.0 | 5.0 | Electrostatic attraction | Abubakar & Ibrahim (2018) |
Husk | MB | Methylene blue | 6.2 | – | Electrostatic attraction | Malik et al. (2016) |
Stalk | MAC | Methylene blue | 11.0 | 5.0 | Electrostatic attraction | Mousavi et al. (2020) |
Stalk | MAC | Methylene blue | 9.0 | 5.7 | Electrostatic attraction | Tang et al. (2019) |
Stalk | MAC | Methylene blue | 7.0 | 4.8 | Electrostatic attraction | Tang et al. (2021) |
Stigmata | MB | Indigo carmine | 2.0 | – | Electrostatic attraction | Mbarki et al. (2018) |
Straw | MAC | Reactive brilliant yellow K-6G | 3.0 | – | Electrostatic attraction | Ren et al. (2020) |
Straw | MAC | Reactive brilliant red K-2BP | 3.0 | – | Electrostatic attraction | Ren et al. (2020) |
Straw | MAC | Methylene blue | 6.0 | – | Electrostatic attraction | Zhao et al. (2014) |
Tassel | MAC | Methylene blue | 10.0 | – | Electrostatic attraction | Olorundare et al. (2014) |
Stalk | MB | Crystal violet | 10.0 | – | Chemisorption | Muhammad et al. (2019) |
Cob | MAC | Methylene blue | 11.0 | – | – | Ali et al. (2017) |
Cob | MAC | Brilliant green | 11.0 | – | – | Ali et al. (2017) |
Cob | MAC | Methylene blue | 10.0 | – | – | Aljeboree & Alkaim (2019) |
Cob | MAC | Crystal violet | 10.0 | – | – | Aljeboree & Alkaim (2019) |
Cob | MAC | Maxilone | 10.0 | – | – | Aljeboree & Alkaim (2019) |
Cob | MAC | Methylene blue | 6.0 | – | – | Aljeboree et al. (2019) |
Cob | MAC | Acetic acid | 5.6 | – | – | Dina et al. (2012) |
Cob | MAC | Methylene blue | 8.0 | – | – | El-Sayed et al. (2014) |
Cob | MAC | Methylene blue | 12.0 | – | – | Farnane et al. (2018) |
Cob | MAC | Methylene blue | 5.6 | 4.0 | – | Jawad et al. (2018) |
Cob | MAC | Congo red | 6.8 | – | – | Leelavathy et al. (2015) |
Cob | MAC | Methylene blue | 12.0 | – | – | Miyah et al. (2016) |
Cob | MAC | Malachite green | 6.0 | – | – | Ojediran et al. (2021) |
Cob | MAC | Methylene blue | 7.0 | – | – | Ramamoorthy et al. (2020) |
Cob | MAC | Methylene blue | 7.0 | – | – | Reddy et al. (2016) |
Cob | MAC | Malachite green | 7.0 | – | – | Ismail et al. (2018) |
Cob | MAC | Methylene blue | 6.0 | – | – | Tan et al. (2012) |
Cob | MAC | Methyl orange | 6.5 | – | – | Wang et al. (2018) |
Cob | MB | Methylene blue | 12.0 | – | – | Farnane et al. (2018) |
Cob | MB | Malachite green | 12.0 | – | – | Farnane et al. (2018) |
Cob | MB | Methylene blue | 5.0 | – | – | Fatoye & Onigbinde (2020) |
Cob | MB | Direct blue 199 | 7.6 | – | – | Saroj et al. (2015) |
Cob | MBC | Methylene blue | 8.0 | – | – | Tsamo et al. (2019) |
Cob | MC | Malachite green | 4.0 | – | – | Ong et al. (2017) |
Cob | MC | Acid yellow | 4.0 | – | – | Ong et al. (2017) |
Cover | MC | Alizarin red S | 2.0 | – | – | Zolgharnein et al. (2016) |
Fibre | MAC | Alcian blue | 7.0 | – | – | Mallampati et al. (2015) |
Fibre | MAC | Methylene blue | 7.0 | – | – | Mallampati et al. (2015) |
Fibre | MAC | Neutral red | 7.0 | – | – | Mallampati et al. (2015) |
Fibre | MAC | Coomaise brilliant blue | 7.0 | – | – | Mallampati et al. (2015) |
Husk | MAC | Methylene blue | 4.0 | – | – | Khodaie et al. (2013) |
Husk | MAC | Methylene blue | 10.3 | 3.8 | – | Ponce et al. (2021) |
Husk | MB | Methylene blue | 6.0 | – | – | Paşka et al. (2014) |
Husk | MC | Methylene blue | 9.0 | – | – | Guin et al. (2018) |
Husk leaf | MAC | Malachite green | 8.0 | – | – | Jalil et al. (2012) |
Leaves | MAC | Methyl orange | 9.0 | – | – | Fadhil & Eisa (2019) |
Leaves | MAC | Methyl orange | 9.0 | – | – | Fadhil & Eisa (2019) |
Leaves | MAC | Indigo carmen | 12.0 | – | – | Fadhil et al. (2021) |
Leaves | MAC | Malachite green | 10.0 | – | – | Fadhel et al. (2021) |
Pericarp | MAC | Methyl orange | – | 11.2 | – | Loya-González et al. (2019) |
Silk | MB | Methylene blue | 12.0 | – | – | Miraboutalebi et al. (2017) |
Silk | MC | Direct blue 15 | 3.0 | – | – | Nadaroğlu et al. (2018) |
Stalk | MAC | Methylene blue | 6.0 | – | – | Soldatkina & Yanar (2021) |
Stalk | MAC | Malachite green | 6.0 | – | – | Soldatkina & Yanar (2021) |
Stalk | MAC | Coomaise brilliant blue | 3.0 | – | – | Taha et al. (2021) |
Stalk | MB | Malachite green | 5.0 | – | – | Abubakar & Batagarawa (2017) |
Stalk | MB | Congo red | 5.0 | – | – | Abubakar & Batagarawa (2017) |
Stalk | MB | Malachite green | 6.0 | 6.8 | – | Lara-Vásquez et al. (2016) |
Stalk | MB | Methylene blue | 6.8 | – | – | Maghri et al. (2012) |
Stalk | MB | Coomaise brilliant blue | 3.0 | – | – | Taha et al. (2021) |
Stalk + walnut shell | MAC | Malachite green | 6.5 | – | – | Kang et al. (2018) |
Stalk pith | MAC | Methylene blue | 10.0 | – | – | Peng et al. (2021) |
Stalk pith | MAC | Crystal violet | 10.0 | – | – | Peng et al. (2021) |
Starch | MAC | Tartrazine | 2.5 | – | – | Dai et al. (2017) |
Stover | MAC | Reactive red 141 | 3.0 | – | – | Carijo et al. (2019) |
Straw | MAC | Blue 21 | 2.0 | – | – | Umpuch & Jutarat (2013) |
Straw | MAC | Yellow 20 | 2.0 | – | – | Umpuch & Jutarat (2013) |
Straw | MB | Malachite green | 6.0 | 2.3 | – | Lima et al. (2017) |
Straw | MB | Malachite green | 6.0 | – | – | Lima et al. (2018) |
Straw | MBC | Malachite green | 9.0 | – | – | Eltaweil et al. (2020) |
Straw + waste red mud | MBC | Acidic black | 4.0 | – | Gao et al. (2021) | |
Straw pith | MAC | Malachite green | 12.0 | – | – | Chen et al. (2020) |
Straw pith | MAC | Methylene blue | 12.0 | – | – | Chen et al. (2020) |
Straw pith | MAC | Rhodamine B | 12.0 | – | – | Chen et al. (2020) |
Tassel powder | MAC | Reactive red 198 | 9.0 | – | – | Dehvari et al. (2013) |
Cob | MAC | Malachite green | 12.0 | Farnane et al. (2018) |
Furthermore, it is interesting to say that since the adsorption phenomenon is invariably influenced by the aforementioned experimental conditions, isotherm and kinetics models of best-fit hypotheses as well as thermodynamic parameters can be used in some cases to open up adsorbent–adsorbate interaction mysteries and identify the most plausible adsorption mechanism (Abdelwahab 2008; Danish et al. 2011; Iwuozor et al. 2022b). For instance, Guo et al. (2018) established in their study that the adsorption mechanism of tylosin onto maize straw adsorbent and its composite follow the pseudo-second-order kinetics that reflect chemisorption, and this conforms with most studies (Table 3) except for Muhammad et al. (2019), who differed in their claim and noted that chemisorption occurs through allocation electrons between cornstalk sorbent and crystal violet. Guo et al. (2018) further explained that based on the characterization result, the adsorbent contains numerous oxygen-containing moieties, such as OH, and hence H-bonding may participate in the adsorption course under acidic conditions, and tylosin adsorption on the adsorbents may be ascribed to hydrophobic interactions. Fathi et al. (2015) in their own study thermodynamically established that the negative value of ΔSo implies that the adsorption process occurs via electrostatic interaction between the adsorbent surface and adsorbate molecules in the solution. Both Guo et al. (2018) and Fathi et al. (2015) also pointed out that the negative value of ΔGo with the decreasing temperature makes the adsorption easier.
In addition, most reports in Table 3 empirically confirm that the amount of electrostatic charges that the dye pollutant contributes throughout the adsorption process is strongly governed by pH, and this can be easily explained using pHzc (when the adsorbent's surface is uncharged and in other words, when there is no net charge associated with the functional group charge). For example, as the pH of the solution rises, the surface potential becomes highly negative (when pH is > pHzc), intensifying the electrostatic impact. When the pH falls below pHzc, the surface charge turns positive, making it challenging to adsorb negatively charged dye molecules (Wang & Wang 2008; Rosas-Castor et al. 2014; Kamarehie et al. 2019; Mousavi et al. 2021). This practical explanation is in good agreement with the one reported by Yaneva & Georgieva (2013) and Velmurugan et al. (2016) for the adsorption of Congo red dye, where they observed that at pH < pHzc, the surface of the unmodified and modified corn cob adsorbent was positively charged, and this was advantageous for electrostatic interactions between dye anions (negatively charged dye SO3− groups) and the adsorbent surface. Conversely, Yaneva & Georgieva (2013) noticed that the adsorption of the anionic dye diminished with an uptick in pH (pH 8–9), and this occurrence was linked to both the overabundance of OH ions in the solution that contend for the adsorption sites on corn cob as well as the negative charge on the surface of the adsorbent. The forgoing account is consistent with the one established by Ren et al. (2020), and they also added that in an acidic condition, the protonation influence of a functional group such as SO3− improves the electrostatic attraction between the dye and adsorbents, and as a result, the upsurge in the concentration of H+ was advantageous for the adsorption of reactive brilliant dyes yellow and red. In another study conducted by Zhang et al. (2020) using corn cob biochar for the degradation of Methyl Orange (MO), it was discovered that the foundation of the oxidizing capacity of the corn cob biochar for the degradation of MO dye was taking into account the OH radical present at the biochar adsorbent surface, which vehemently struck and destroyed the N = N bond of the dye, followed by a ring-opening reaction to produce giant CnH2n+2, and final mineralization into CO2 and H2O molecules. It was further affirmed that electrostatic interactions, electron sharing, and electron transfer worked in concert with the radical attack to produce the MO's adsorption process (Zhang et al. 2020). Rosas-Castor et al. (2014) did not differ in their own mechanistic line of thought as well, as they suggest from their experimental findings that maize biosorbent (MB) is adsorbed predominantly on the biosorbent surface by electrostatic attraction and complexation mechanisms. Notably, as established by Barquilha & Braga (2021) and as shown in Table 3, H-bond, π–π interaction, hydrophobic interaction, and electrostatic interaction are predominant for dye adsorption. Also, as expounded by Moradi & Sharma (2021), the numerous active sites on the surface of adsorbents may be related to the charge of the dye ions as well as the active sites. The amount of adsorbed dye reduces as pH values drop because the surface charge virtually becomes positively charged, which makes cationic dye molecules more competitive with H+. Meanwhile, for anionic dye, which can quickly bind to the adsorbent, this condition is more preferable. However, as the pH level in the system rises, a significant volume of OH ions will be released, increasing the number of negatively charged sites. A negatively charged surface affects cationic dyes in a variety of ways, but it has no effect on the adsorption of anionic dyes.
ADSORPTION KINETIC AND ISOTHERM MODELLING
Adsorption isotherms are generally used for describing the adsorption behaviour and evaluating the adsorption capacity of materials used for environmental remediation (Emenike et al. 2023; Ohale et al. 2023). Different adsorption models have been described in the literature to particularly monitor the uptake capacity of maize/corn adsorbents in the removal of dyes. A summary of these isotherm models and associated parameters is presented in Table 4. The practical operation of an adsorption system requires that the equilibrium data be correlated either by an empirical or theoretical equation (Iwuozor et al. 2022c). Many such equations abound in the open literature. However, the foregoing analysis of adsorption isotherms used to model the uptake capacity of maize/corn adsorbents showed that Freundlich and Langmuir isotherms were the most popular and frequently used isotherms used to describe the fit of the equilibrium data.
Plant parts . | Adsorbent class . | Dye . | Isotherm models . | Kinetic models . | References . | ||||
---|---|---|---|---|---|---|---|---|---|
Best fit . | Model type . | R2 . | Best fit . | Model type . | R2 . | ||||
Corn cob | MAC | Methylene blue | Freundlich | Linear | 0.938 | – | – | – | Aljeboree et al. (2019) |
Corn stalk | MB | Malachite green | Freundlich | Linear | 0.998 | PSO | Linear | 0.999 | Abubakar & Batagarawa (2017) |
Corn stalk | MB | Congo red | Langmuir | Linear | 0.991 | PSO | Linear | 0.999 | Abubakar & Batagarawa (2017) |
Corn stover | MAC | Reactive red 141 | Langmuir | Nonlinear | 0.997 | PSO | Nonlinear | 0.995 | Carijo et al. (2019) |
Corn cob | MAC | Methyl violet | Freundlich | Linear | 0.994 | – | – | – | Aljeboree et al. (2021) |
Corn cob | MAC | Methylene blue | Temkin | Linear | 0.996 | – | – | – | Aljeboree & Alkaim (2019) |
Corn cob | MAC | Crystal violet | Freundlich | Linear | 0.995 | – | – | – | Aljeboree & Alkaim (2019) |
Corn cob | MAC | Maxilone blue | Temkin | Linear | 0.997 | – | – | – | Aljeboree & Alkaim (2019) |
Corn cob | MAC | Methylene blue | Freundlich | Linear | 0.994 | – | – | – | Ali et al. (2017) |
Corn cob | MAC | Brilliant green | Freundlich | Linear | 0.994 | – | – | – | Ali et al. (2017) |
Corn straw | MAC | Rhodamine B | Freundlich | Linear | 0.998 | PSO | Linear | 0.999 | Chen et al. (2019) |
Corn cob | MB | Methylene blue | Freundlich | Linear | 0.902 | – | – | – | Fatoye & Onigbinde (2020) |
Corn cob | MB | Methylene blue | Freundlich | Linear | 0.999 | PSO | Linear | 0.989 | Dutta & Nath (2018) |
Corn cob | MAC | Methylene blue | Freundlich | Linear | 0.999 | PSO | Linear | 0.999 | Dutta & Nath (2018) |
Corn cob | MAC | Methylene blue | Langmuir | Linear | 0.986 | – | – | – | El-Sayed et al. (2014) |
Corn leaves | MB | Malachite green | Freundlich | Linear | 0.924 | PFO | Linear | 0.930 | Fadhel et al. (2021) |
Corn leaves | MB | Indigo carmen | Freundlich | Linear | 0.926 | PSO | Linear | 0.993 | Fadhil et al. (2021) |
Corn straw | MAC | Methylene blue | Temkin | Linear | 0.977 | PSO | Linear | 0.995 | Ge et al. (2016) |
Corn stalks | MB | Direct red 23 | Freundlich | Linear | 0.993 | PSO | Linear | 0.999 | Fathi et al. (2015) |
Corn leaves | MB | Methyl orange | Freundlich | Linear | 0.964 | PFO | Linear | 0.908 | Fadhil & Eisa (2019) |
Corn leaves | MAC | Methyl orange | Langmuir | Linear | 0.915 | PSO | Linear | 0.990 | Fadhil & Eisa (2019) |
Corn straw | MBC | Acid black | Diffusion chemisorption model | Linear | 0.972 | Elovich | Linear | 0.990 | Gao et al. (2021) |
Corn straw | MBC | Amino black | Diffusion chemisorption model | Linear | 0.999 | Elovich | Linear | 0.999 | Gao et al. (2021) |
Corn cob | MB | Methylene blue | Langmuir | Linear | 0.978 | PSO | Linear | 0.992 | Farnane et al. (2018) |
Corn cob | MB | Malachite green | Langmuir | Linear | 0.941 | PSO | Linear | 0.983 | Farnane et al. (2018) |
Corn cob | MAC | Methylene blue | Langmuir | Linear | 0.955 | PSO | Linear | 0.960 | Farnane et al. (2018) |
Corn cob | MAC | Malachite green | Langmuir | Linear | 0.937 | PSO | Linear | 0.997 | Farnane et al. (2018) |
Corn stalks | MAC | Malachite green | Langmuir | Linear | 0.998 | PSO | Linear | 0.998 | Kang et al. (2018) |
Corn cob | MB | Gentian violet | Freundlich | Linear | 0.995 | PSO | Linear | 1.000 | Javed et al. (2021) |
Corn cob | MAC | Methylene blue | Freundlich | Linear | 0.944 | PFO | Linear | 0.998 | Jawad et al. (2018) |
Corn pith | MAC | Malachite green | Freundlich | Linear | 0.996 | PFO | Linear | 0.988 | Jothirani et al. (2016) |
Corn straw | MB | Malachite green | Freundlich | Linear | 0.99 | Elovich | Linear | 0.99 | Lima et al. (2017) |
Corn straw | MAC | Malachite green | Freundlich | Linear | 0.99 | Elovich | Linear | 0.99 | Lima et al. (2017) |
Corn cob | MAC | Methylene blue | Langmuir | Linear | 0.99 | PSO | Linear | 1.00 | Medhat et al. (2021) |
Corn straw | MC | Green 40 | Langmuir | Linear | 0.994 | PSO | Linear | 0.999 | Umpuch (2015) |
Plant parts . | Adsorbent class . | Dye . | Isotherm models . | Kinetic models . | References . | ||||
---|---|---|---|---|---|---|---|---|---|
Best fit . | Model type . | R2 . | Best fit . | Model type . | R2 . | ||||
Corn cob | MAC | Methylene blue | Freundlich | Linear | 0.938 | – | – | – | Aljeboree et al. (2019) |
Corn stalk | MB | Malachite green | Freundlich | Linear | 0.998 | PSO | Linear | 0.999 | Abubakar & Batagarawa (2017) |
Corn stalk | MB | Congo red | Langmuir | Linear | 0.991 | PSO | Linear | 0.999 | Abubakar & Batagarawa (2017) |
Corn stover | MAC | Reactive red 141 | Langmuir | Nonlinear | 0.997 | PSO | Nonlinear | 0.995 | Carijo et al. (2019) |
Corn cob | MAC | Methyl violet | Freundlich | Linear | 0.994 | – | – | – | Aljeboree et al. (2021) |
Corn cob | MAC | Methylene blue | Temkin | Linear | 0.996 | – | – | – | Aljeboree & Alkaim (2019) |
Corn cob | MAC | Crystal violet | Freundlich | Linear | 0.995 | – | – | – | Aljeboree & Alkaim (2019) |
Corn cob | MAC | Maxilone blue | Temkin | Linear | 0.997 | – | – | – | Aljeboree & Alkaim (2019) |
Corn cob | MAC | Methylene blue | Freundlich | Linear | 0.994 | – | – | – | Ali et al. (2017) |
Corn cob | MAC | Brilliant green | Freundlich | Linear | 0.994 | – | – | – | Ali et al. (2017) |
Corn straw | MAC | Rhodamine B | Freundlich | Linear | 0.998 | PSO | Linear | 0.999 | Chen et al. (2019) |
Corn cob | MB | Methylene blue | Freundlich | Linear | 0.902 | – | – | – | Fatoye & Onigbinde (2020) |
Corn cob | MB | Methylene blue | Freundlich | Linear | 0.999 | PSO | Linear | 0.989 | Dutta & Nath (2018) |
Corn cob | MAC | Methylene blue | Freundlich | Linear | 0.999 | PSO | Linear | 0.999 | Dutta & Nath (2018) |
Corn cob | MAC | Methylene blue | Langmuir | Linear | 0.986 | – | – | – | El-Sayed et al. (2014) |
Corn leaves | MB | Malachite green | Freundlich | Linear | 0.924 | PFO | Linear | 0.930 | Fadhel et al. (2021) |
Corn leaves | MB | Indigo carmen | Freundlich | Linear | 0.926 | PSO | Linear | 0.993 | Fadhil et al. (2021) |
Corn straw | MAC | Methylene blue | Temkin | Linear | 0.977 | PSO | Linear | 0.995 | Ge et al. (2016) |
Corn stalks | MB | Direct red 23 | Freundlich | Linear | 0.993 | PSO | Linear | 0.999 | Fathi et al. (2015) |
Corn leaves | MB | Methyl orange | Freundlich | Linear | 0.964 | PFO | Linear | 0.908 | Fadhil & Eisa (2019) |
Corn leaves | MAC | Methyl orange | Langmuir | Linear | 0.915 | PSO | Linear | 0.990 | Fadhil & Eisa (2019) |
Corn straw | MBC | Acid black | Diffusion chemisorption model | Linear | 0.972 | Elovich | Linear | 0.990 | Gao et al. (2021) |
Corn straw | MBC | Amino black | Diffusion chemisorption model | Linear | 0.999 | Elovich | Linear | 0.999 | Gao et al. (2021) |
Corn cob | MB | Methylene blue | Langmuir | Linear | 0.978 | PSO | Linear | 0.992 | Farnane et al. (2018) |
Corn cob | MB | Malachite green | Langmuir | Linear | 0.941 | PSO | Linear | 0.983 | Farnane et al. (2018) |
Corn cob | MAC | Methylene blue | Langmuir | Linear | 0.955 | PSO | Linear | 0.960 | Farnane et al. (2018) |
Corn cob | MAC | Malachite green | Langmuir | Linear | 0.937 | PSO | Linear | 0.997 | Farnane et al. (2018) |
Corn stalks | MAC | Malachite green | Langmuir | Linear | 0.998 | PSO | Linear | 0.998 | Kang et al. (2018) |
Corn cob | MB | Gentian violet | Freundlich | Linear | 0.995 | PSO | Linear | 1.000 | Javed et al. (2021) |
Corn cob | MAC | Methylene blue | Freundlich | Linear | 0.944 | PFO | Linear | 0.998 | Jawad et al. (2018) |
Corn pith | MAC | Malachite green | Freundlich | Linear | 0.996 | PFO | Linear | 0.988 | Jothirani et al. (2016) |
Corn straw | MB | Malachite green | Freundlich | Linear | 0.99 | Elovich | Linear | 0.99 | Lima et al. (2017) |
Corn straw | MAC | Malachite green | Freundlich | Linear | 0.99 | Elovich | Linear | 0.99 | Lima et al. (2017) |
Corn cob | MAC | Methylene blue | Langmuir | Linear | 0.99 | PSO | Linear | 1.00 | Medhat et al. (2021) |
Corn straw | MC | Green 40 | Langmuir | Linear | 0.994 | PSO | Linear | 0.999 | Umpuch (2015) |
The reviewed studies in Table 4 showed that most of the studies, regardless of adsorbent type, were better fitted to the Freundlich isotherm. The Freundlich isotherm gave a better description of the experimental data, and this was reflected in the relatively high correlation coefficients observed in the studies. However, there were cases where a particular adsorbent type was better fitted to more than one isotherm model. For instance, activated carbon of different plant parts was shown to be predominantly fitted to Freundlich and Langmuir isotherms, and sometimes to Temkin isotherm. There is another instance where the unmodified form of a plant part is fitted to Freundlich isotherm, and at other times to Langmuir isotherm. The variations exhibited by this adsorbent class could be due to variations in the adsorbate.
Based on the studies reviewed, the pseudo-second-order model exhibited the best fit predominantly. However, there were cases in which the pseudo-first-order and Elovich models exhibited best fit although they had minimal frequency. It is then important to estimate the basic assumption of the pseudo-second-order model. The pseudo-second-order model assumes that the rate-limiting step of the adsorption process is chemisorption. This means that the rate of adsorption is not dependent on adsorbate concentration but on adsorption capacity (Sahoo & Prelot 2020).
ADSORPTION THERMODYNAMICS
The mechanism of adsorption can be further investigated by a thermodynamic process to ascertain the level of electrostatic interaction between the adsorbent and adsorbing species at a given temperature. The nature of adsorption from temperature effect variations is elucidated on the basis of adsorption enthalpy (ΔHo), entropy (ΔSo), and Gibbs free energy (ΔGo). Table 5 lists the values of thermodynamic parameters that were ascertained at various temperatures from certain publications.
Plant parts . | Adsorbent class . | Dye . | Thermodynamics . | References . | |||
---|---|---|---|---|---|---|---|
Temp (K) . | (kJ/mol) . | (kJ/mol) . | (J/mol.K) . | ||||
Corn silk | MB | Reactive blue (RB19) | 298 | 0.4765 | 7.70 | 24.22 | Değermenci et al. (2019) |
308 | 0.2343 | ||||||
318 | −0.0079 | ||||||
328 | −0.2502 | ||||||
Corn silk | MB | Reactive red (RR218) | 298 | 1.8232 | 26.44 | 82.57 | Değermenci et al. (2019) |
308 | 0.9975 | ||||||
318 | 0.1717 | ||||||
328 | −0.6540 | ||||||
Corn straw composite | MC | Malachite green | 298 | −8.89 | 40.90 | 167.08 | Eltaweil et al. (2020) |
303 | −9.72 | ||||||
308 | −10.56 | ||||||
313 | −11.39 | ||||||
Corn stalk | MB | Direct red (DR23) | 283.15 | −4.793 | 57.481 | 228.29 | Fathi et al. (2015) |
288.15 | −5.285 | ||||||
298.15 | −6.336 | ||||||
308.15 | −7.394 | ||||||
318.15 | −8.120 | ||||||
Corn straw | MC | Methylene blue | 298 | −9.25 | −42.66 | −111.37 | Ge et al. (2016) |
318 | −7.75 | ||||||
338 | −4.74 | ||||||
Maize stover | MC | Methyl red | 293 | −5.00 | 7.865 | 0.0439 | Guyo et al. (2017) |
303 | −5.44 | ||||||
313 | −5.88 | ||||||
323 | −46.32 | ||||||
Maize husk leaf | MC | Malachite green | 303 | −5.93 | 32.4 | 127 | Jalil et al. (2012) |
313 | −7.19 | ||||||
323 | −8.46 | ||||||
Corn cob | MBC | Methylene blue | 313 | −67.80 | 25.5 | 139.6 | Jawad et al. (2018) |
323 | −69.20 | ||||||
333 | −70.50 | ||||||
Corn straw | MB | Malachite green | 298 | −22.4 | 54.4 | 0.03 | Lima et al. (2017) |
308 | −25.5 | ||||||
318 | −26.9 | ||||||
328 | −30.6 | ||||||
Corn straw | MB | Malachite green | 298 | −22.4 | 63.8 | 0.03 | Lima et al. (2017) |
308 | −26.3 | ||||||
318 | −28.5 | ||||||
328 | −31.3 | ||||||
Corn straw core | MB | Methylene blue | 298 | −1.67 | −29.95 | −87.56 | Liu et al. (2018b) |
318 | −0.55 | ||||||
338 | 1.88 | ||||||
Corn stalk | MB | Methylene blue | 293 | −26.8 | 9.5 | 124 | Soldatkina & Yanar (2021) |
313 | −28.9 | ||||||
333 | −31.8 | ||||||
Corn stalk | MB | Malachite green | 293 | −26.3 | 11.8 | 130 | Soldatkina & Yanar (2021) |
313 | −28.6 | ||||||
333 | −31.5 | ||||||
Corn starch | MBC | Methylene violet | 298.15 | −16.549 | 1.50 | 0.15 | Mittal et al. (2018) |
308.15 | −17.873 | ||||||
318.15 | −19.558 | ||||||
Corn cob | MAC | Methylene blue | 293 | −7.616 | 37.442 | 153.783 | Miyah et al. (2016) |
303 | −9.154 | ||||||
313 | −10.692 | ||||||
323 | −12.221 | ||||||
Corn cob | MAC | Congo red | 303 | −32.27 | −20.91 | 0.064 | Ojedokun & Bello (2017) |
313 | −34.46 | ||||||
323 | −35.76 | ||||||
Corn husk | MC | Methylene blue | 300 | −1.16 | 18.1 | 64 | Guin et al. (2018) |
310 | −1.74 | ||||||
320 | −2.38 | ||||||
Corn husk | MB | Methylene blue | 298 | −6.5651 | −4.3792 | 15.9408 | Paşka et al. (2014) |
313 | −6.5755 | ||||||
333 | −5.6497 | ||||||
Corn straw | MAC | Reactive brilliant yellow | 298 | −7.05 | 1.61 | 29.05 | Ren et al. (2020) |
308 | −7.34 | ||||||
318 | −7.63 | ||||||
Corn straw | MAC | Reactive brilliant red | 298 | −7.08 | 1.41 | 28.47 | Ren et al. (2020) |
308 | −7.36 | ||||||
318 | −7.65 | ||||||
Maize cob | MB | Bromophenol blue | 298 | −5.039 | −4.226 | 0.003 | Abubakar & Ibrahim (2018) |
303 | −5.052 | ||||||
308 | −5.066 | ||||||
313 | −5.079 | ||||||
318 | −5.093 | ||||||
Maize cob | MB | Bromothymol blue | 298 | −1.528 | 6.871 | 0.028 | Abubakar & Ibrahim (2018) |
303 | −1.669 | ||||||
308 | −1.810 | ||||||
313 | −1.951 | ||||||
318 | −2.092 | ||||||
Corn cob leaves | MB | Basic violet 4 | 303 | −12.57 | −14.43 | −0.0061 | Sepúlveda et al. (2015) |
318 | −12.47 | ||||||
333 | −12.38 | ||||||
Corn stalk | MB | Acidic red | 303 | −30.2 | −9.0 | 70 | Soldatkina & Zavrichko (2018) |
318 | −31.3 | ||||||
328 | −31.9 | ||||||
Corn stalk | MB | Acidic orange | 303 | −30.0 | −14.0 | 53 | Soldatkina & Zavrichko (2018) |
318 | −31.2 | ||||||
328 | −31.3 | ||||||
Maize cob | MBC | Methylene blue | 298 | −1.44 | −11.908 | −0.037 | Tsamo et al. (2019) |
303 | 0.23 | ||||||
318 | −0.36 | ||||||
333 | 0.41 | ||||||
Corn stalk | MC | Methylene blue | 303.15 | −4.956 | −21.471 | −0.054 | Wen et al. (2018) |
313.15 | −4.454 | ||||||
323.15 | −3.817 | ||||||
333.15 | −3.353 | ||||||
Corn cover | MC | Alizarin red S | 298 | −1.51 | −2.81 | −4.6 | Zolgharnein et al. (2016) |
Corn stover | MC | Indigo carmine | 288 | −23,485 | 2.914 | 491.4 | Ahmad et al. (2021) |
298 | −26,770 | ||||||
308 | −28,478 | ||||||
318 | −29,572 |
Plant parts . | Adsorbent class . | Dye . | Thermodynamics . | References . | |||
---|---|---|---|---|---|---|---|
Temp (K) . | (kJ/mol) . | (kJ/mol) . | (J/mol.K) . | ||||
Corn silk | MB | Reactive blue (RB19) | 298 | 0.4765 | 7.70 | 24.22 | Değermenci et al. (2019) |
308 | 0.2343 | ||||||
318 | −0.0079 | ||||||
328 | −0.2502 | ||||||
Corn silk | MB | Reactive red (RR218) | 298 | 1.8232 | 26.44 | 82.57 | Değermenci et al. (2019) |
308 | 0.9975 | ||||||
318 | 0.1717 | ||||||
328 | −0.6540 | ||||||
Corn straw composite | MC | Malachite green | 298 | −8.89 | 40.90 | 167.08 | Eltaweil et al. (2020) |
303 | −9.72 | ||||||
308 | −10.56 | ||||||
313 | −11.39 | ||||||
Corn stalk | MB | Direct red (DR23) | 283.15 | −4.793 | 57.481 | 228.29 | Fathi et al. (2015) |
288.15 | −5.285 | ||||||
298.15 | −6.336 | ||||||
308.15 | −7.394 | ||||||
318.15 | −8.120 | ||||||
Corn straw | MC | Methylene blue | 298 | −9.25 | −42.66 | −111.37 | Ge et al. (2016) |
318 | −7.75 | ||||||
338 | −4.74 | ||||||
Maize stover | MC | Methyl red | 293 | −5.00 | 7.865 | 0.0439 | Guyo et al. (2017) |
303 | −5.44 | ||||||
313 | −5.88 | ||||||
323 | −46.32 | ||||||
Maize husk leaf | MC | Malachite green | 303 | −5.93 | 32.4 | 127 | Jalil et al. (2012) |
313 | −7.19 | ||||||
323 | −8.46 | ||||||
Corn cob | MBC | Methylene blue | 313 | −67.80 | 25.5 | 139.6 | Jawad et al. (2018) |
323 | −69.20 | ||||||
333 | −70.50 | ||||||
Corn straw | MB | Malachite green | 298 | −22.4 | 54.4 | 0.03 | Lima et al. (2017) |
308 | −25.5 | ||||||
318 | −26.9 | ||||||
328 | −30.6 | ||||||
Corn straw | MB | Malachite green | 298 | −22.4 | 63.8 | 0.03 | Lima et al. (2017) |
308 | −26.3 | ||||||
318 | −28.5 | ||||||
328 | −31.3 | ||||||
Corn straw core | MB | Methylene blue | 298 | −1.67 | −29.95 | −87.56 | Liu et al. (2018b) |
318 | −0.55 | ||||||
338 | 1.88 | ||||||
Corn stalk | MB | Methylene blue | 293 | −26.8 | 9.5 | 124 | Soldatkina & Yanar (2021) |
313 | −28.9 | ||||||
333 | −31.8 | ||||||
Corn stalk | MB | Malachite green | 293 | −26.3 | 11.8 | 130 | Soldatkina & Yanar (2021) |
313 | −28.6 | ||||||
333 | −31.5 | ||||||
Corn starch | MBC | Methylene violet | 298.15 | −16.549 | 1.50 | 0.15 | Mittal et al. (2018) |
308.15 | −17.873 | ||||||
318.15 | −19.558 | ||||||
Corn cob | MAC | Methylene blue | 293 | −7.616 | 37.442 | 153.783 | Miyah et al. (2016) |
303 | −9.154 | ||||||
313 | −10.692 | ||||||
323 | −12.221 | ||||||
Corn cob | MAC | Congo red | 303 | −32.27 | −20.91 | 0.064 | Ojedokun & Bello (2017) |
313 | −34.46 | ||||||
323 | −35.76 | ||||||
Corn husk | MC | Methylene blue | 300 | −1.16 | 18.1 | 64 | Guin et al. (2018) |
310 | −1.74 | ||||||
320 | −2.38 | ||||||
Corn husk | MB | Methylene blue | 298 | −6.5651 | −4.3792 | 15.9408 | Paşka et al. (2014) |
313 | −6.5755 | ||||||
333 | −5.6497 | ||||||
Corn straw | MAC | Reactive brilliant yellow | 298 | −7.05 | 1.61 | 29.05 | Ren et al. (2020) |
308 | −7.34 | ||||||
318 | −7.63 | ||||||
Corn straw | MAC | Reactive brilliant red | 298 | −7.08 | 1.41 | 28.47 | Ren et al. (2020) |
308 | −7.36 | ||||||
318 | −7.65 | ||||||
Maize cob | MB | Bromophenol blue | 298 | −5.039 | −4.226 | 0.003 | Abubakar & Ibrahim (2018) |
303 | −5.052 | ||||||
308 | −5.066 | ||||||
313 | −5.079 | ||||||
318 | −5.093 | ||||||
Maize cob | MB | Bromothymol blue | 298 | −1.528 | 6.871 | 0.028 | Abubakar & Ibrahim (2018) |
303 | −1.669 | ||||||
308 | −1.810 | ||||||
313 | −1.951 | ||||||
318 | −2.092 | ||||||
Corn cob leaves | MB | Basic violet 4 | 303 | −12.57 | −14.43 | −0.0061 | Sepúlveda et al. (2015) |
318 | −12.47 | ||||||
333 | −12.38 | ||||||
Corn stalk | MB | Acidic red | 303 | −30.2 | −9.0 | 70 | Soldatkina & Zavrichko (2018) |
318 | −31.3 | ||||||
328 | −31.9 | ||||||
Corn stalk | MB | Acidic orange | 303 | −30.0 | −14.0 | 53 | Soldatkina & Zavrichko (2018) |
318 | −31.2 | ||||||
328 | −31.3 | ||||||
Maize cob | MBC | Methylene blue | 298 | −1.44 | −11.908 | −0.037 | Tsamo et al. (2019) |
303 | 0.23 | ||||||
318 | −0.36 | ||||||
333 | 0.41 | ||||||
Corn stalk | MC | Methylene blue | 303.15 | −4.956 | −21.471 | −0.054 | Wen et al. (2018) |
313.15 | −4.454 | ||||||
323.15 | −3.817 | ||||||
333.15 | −3.353 | ||||||
Corn cover | MC | Alizarin red S | 298 | −1.51 | −2.81 | −4.6 | Zolgharnein et al. (2016) |
Corn stover | MC | Indigo carmine | 288 | −23,485 | 2.914 | 491.4 | Ahmad et al. (2021) |
298 | −26,770 | ||||||
308 | −28,478 | ||||||
318 | −29,572 |
The physical adsorption compelled by the mode of energy interactive process, e.g., hydrogen bonding, van der Waals, and ℼ–ℼ interface between the adsorbent and dye pollutant, is dependent on the Gibbs free energy (ΔGo) (Chang et al. 2021). A combination of negative values (ΔGo < 0) and positive values (ΔGo > 0) of Gibbs free energy at stated temperatures depicting spontaneity and non-spontaneity of chemical reactions was reported in Table 5 for several grades of adsorbent class and dye adsorbate species. The reduction in ΔGo values with increasing temperatures of solution confirms the feasibility of thermodynamics, and the adsorption of anionic and cationic dyes is favourable at high temperatures (Chang et al. 2021). According to Ahmad et al. (2021), at increased temperature, the adsorbent pores get enlarged, subsequently initiating further activation of surface sites, leading to a decrease in ΔGo. On the contrary, Wen et al. (2018) reported a rise in negative values of ΔGo at decreased temperatures that recorded advantageous adsorption processes, and this could be enhanced mobility of the cationic dye at higher temperatures, thereby producing lower adsorption capacity. The positive and negative values of ΔHo observed in Table 5 show that the sorption mechanism is either endothermic or exothermic in nature, in corroboration with the effect of temperature. The exothermic reaction from dye biosorption onto the maize biomass surface site also indicates the existence of a chemical interaction between the adsorbing species and the adsorbate, whereas in the case of the endothermic process, the biosorption is physisorption, indicating a weak interaction between the maize biomass and dye types (Mbarki et al. 2018). The positive values of ΔHo observed in the reviewed literature could be due to probable structural deformation and inducement of a photocatalytic effect by specific functional groups of the maize biomass adsorbent in the adsorption system (Chang et al. 2021).
Entropy change (ΔSo) is a parameter for evaluating the magnitude of irregularity between the adsorbate molecules and the adsorbent. The positive value of ΔSo for the adsorption dyes on different active sites of the adsorbent class designates a rise in sorption randomness, and the attraction of the adsorbent for the dye molecules was high (Soldatkina & Zavrichko 2018). The increase in randomness at the solid–solution interface throughout the adsorption process is indicated by the positive change in entropy values in several prior studies (Table 5). The kinetic energy of the adsorbate molecules rises as a result of the mobility of dye molecules on the sorbent surface site increasing with the temperature increase at positive values of entropy change. On the other hand, the negative values of ΔSo in dye adsorption on composite and improved corn straw elucidate a decrease in the degree of disorderliness between the dye molecules and corn adsorbent class (Ge et al. 2016; Liu et al. 2018b). Similar inferences were observed in the adsorption of dye species on UM cob (Sepúlveda et al. 2015), maize cob biochar (Tsamo et al. 2019), composite corn stalk (Wen et al. 2018), and composite corn cover (Zolgharnein et al. 2016), as shown in Table 5, which could be attributed to the loss of at least a degree of freedom by dye molecules when adsorbed and no occurrence of a notable change in entropy (Wen et al. 2018).
REGENERATION AND REUSABILITY STUDIES
The practical utilization of any adsorbent is predicated upon its potential for use multiple times (Emenike et al. 2022c). However, not many studies have attempted to investigate the possibility of regenerating and reusing maize/corn adsorbents in the adsorption of dyes. Nevertheless, an overview of the studies that carried out this is presented in Table 6. There were significant variations in desorption of the dyes. There were cases where the regeneration efficiencies were higher than 100% after two desorptions, even when the use of two different eluents (NaCl and HCl) was employed. In the study, this observation was attributed to a possible reaction between the lone pair of electrons on the adsorbent and the H+ on the HCl eluent, thus leading to the availability of more reaction sites for the removal of dyes (Song et al. 2016). In some instances, the use of the same eluent exhibited varying regeneration efficiencies, although they were used in the removal of different dyes. Similarly, while some adsorbents performed over long, repeated cycles, others could only be reused once. Hence, it suffices to say that the regenerative efficiency of an adsorbent would depend on the adsorbent type (unmodified or modified), the eluent used, and the pollutant to be removed from the environmental matrix.
Plant parts . | Adsorbent class . | Dye . | Eluent . | Number of cycles (n) . | % desorbed (n = 1) . | % qm retained after n cycles . | References . |
---|---|---|---|---|---|---|---|
Corn stalk | MAC | Methylene blue | Deionized water | 1 | 75 | – | Mousavi et al. (2020) |
Corn stalk | MAC | Malachite green | – | 5 | 90.2 | 33.65 | Kang et al. (2018) |
Corn starch | MAC | Methylene blue | Acetone | 20 | 100 | – | Mittal et al. (2020) |
Corn stalk | MC | Methyl orange | NaCl | 3 | – | – | Song et al. (2016) |
Corn cob | MBC | Methyl orange | – | 3 | > 99 | – | Zhang et al. (2020) |
Corn starch | MC | Golden yellow X-GL | Ethanol | 4 | ≤ 85 | – | Guo et al. (2019) |
Corn straw | MC | Methylene blue | Hydrochloric acid | 5 | 80.6 | – | Liu et al. (2020b) |
Corn fibers | MB | Alcian blue | Acid and alkali solutions | 5 | 96 | – | Mallampati et al. (2015) |
Corn fibers | MB | Methylene blue | Acid and alkali solutions | 5 | 96 | – | Mallampati et al. (2015) |
Corn fibers | MB | Coomassie brilliant blue | Acid and alkali solutions | 5 | 96 | – | Mallampati et al. (2015) |
Corn fibers | MB | Neutral red | Acid and alkali solutions | 5 | 96 | – | Mallampati et al. (2015) |
Corn stover | MC | Reactive red 141 | NaOH | – | < 12 | – | Carijo et al. (2019) |
Corn stover | MC | Reactive red 141 | NaCl | – | < 12 | – | Carijo et al. (2019) |
Corn stover | MC | Reactive red 141 | KOH | – | < 12 | – | Carijo et al. (2019) |
Corn stover | MC | Reactive red 141 | Ethanol | – | < 12 | – | Carijo et al. (2019) |
Corn stover | MC | Reactive red 141 | hexane | – | < 12 | – | Carijo et al. (2019) |
Corn pericarp | MB | Methylene blue | Deionized water | 7 | ≤ 5 | – | Rosas-Castor et al. (2014) |
Corn pericarp | MB | Methylene blue | Hydrochloric acid | 7 | ≤ 70 | – | Rosas-Castor et al. (2014) |
Corn pericarp | MB | Methylene blue | Ethanol | 7 | ≤ 30 | – | Rosas-Castor et al. (2014) |
Corn pericarp | MB | Methylene blue | NaOH | 7 | ≤ 5 | – | Rosas-Castor et al. (2014) |
Corn straw | MC | Methylene blue | Ethanol | 4 | 70–90 | – | Zhao et al. (2014) |
Corn cob | MB | Gentian violet | KOH | – | 92.5 | – | Javed et al. (2021) |
Plant parts . | Adsorbent class . | Dye . | Eluent . | Number of cycles (n) . | % desorbed (n = 1) . | % qm retained after n cycles . | References . |
---|---|---|---|---|---|---|---|
Corn stalk | MAC | Methylene blue | Deionized water | 1 | 75 | – | Mousavi et al. (2020) |
Corn stalk | MAC | Malachite green | – | 5 | 90.2 | 33.65 | Kang et al. (2018) |
Corn starch | MAC | Methylene blue | Acetone | 20 | 100 | – | Mittal et al. (2020) |
Corn stalk | MC | Methyl orange | NaCl | 3 | – | – | Song et al. (2016) |
Corn cob | MBC | Methyl orange | – | 3 | > 99 | – | Zhang et al. (2020) |
Corn starch | MC | Golden yellow X-GL | Ethanol | 4 | ≤ 85 | – | Guo et al. (2019) |
Corn straw | MC | Methylene blue | Hydrochloric acid | 5 | 80.6 | – | Liu et al. (2020b) |
Corn fibers | MB | Alcian blue | Acid and alkali solutions | 5 | 96 | – | Mallampati et al. (2015) |
Corn fibers | MB | Methylene blue | Acid and alkali solutions | 5 | 96 | – | Mallampati et al. (2015) |
Corn fibers | MB | Coomassie brilliant blue | Acid and alkali solutions | 5 | 96 | – | Mallampati et al. (2015) |
Corn fibers | MB | Neutral red | Acid and alkali solutions | 5 | 96 | – | Mallampati et al. (2015) |
Corn stover | MC | Reactive red 141 | NaOH | – | < 12 | – | Carijo et al. (2019) |
Corn stover | MC | Reactive red 141 | NaCl | – | < 12 | – | Carijo et al. (2019) |
Corn stover | MC | Reactive red 141 | KOH | – | < 12 | – | Carijo et al. (2019) |
Corn stover | MC | Reactive red 141 | Ethanol | – | < 12 | – | Carijo et al. (2019) |
Corn stover | MC | Reactive red 141 | hexane | – | < 12 | – | Carijo et al. (2019) |
Corn pericarp | MB | Methylene blue | Deionized water | 7 | ≤ 5 | – | Rosas-Castor et al. (2014) |
Corn pericarp | MB | Methylene blue | Hydrochloric acid | 7 | ≤ 70 | – | Rosas-Castor et al. (2014) |
Corn pericarp | MB | Methylene blue | Ethanol | 7 | ≤ 30 | – | Rosas-Castor et al. (2014) |
Corn pericarp | MB | Methylene blue | NaOH | 7 | ≤ 5 | – | Rosas-Castor et al. (2014) |
Corn straw | MC | Methylene blue | Ethanol | 4 | 70–90 | – | Zhao et al. (2014) |
Corn cob | MB | Gentian violet | KOH | – | 92.5 | – | Javed et al. (2021) |
Plant parts . | Adsorbent class . | Dye . | Competing species . | Concentration of competing species . | Maximum change with competing species . | References . |
---|---|---|---|---|---|---|
Corn stigmata | MB | Methylene blue | NaCl | 1,000 mM | 27.76% decrease | Mbarki et al. (2018) |
Corn stigmata | MB | Indigo carmine | NaCl | 1,000 mM | 83.74% decrease | Mbarki et al. (2018) |
Corn starch | MBC | Methylene violet | CaCl | 0.6 M | 23% decrease | Mittal et al. (2018) |
Corn starch | MBC | Methylene violet | NaCl | 0.6 M | 20.5% decrease | Mittal et al. (2018) |
Corn stalk | MB | Methylene blue | H+ | 0.02 mol/L | 71% decrease | Tang et al. (2019) |
Corn stalk | MB | Methylene blue | K+ | 0.04 mol/L | 16% decrease | Tang et al. (2019) |
Corn stalk | MB | Methylene blue | K+ | 0.030 mol/L | 35.71% decrease | Tang et al. (2021) |
Corn stalk | MB | Methylene blue | Ca2+ | 0.030 mol/L | 85.71% decrease | Tang et al. (2021) |
Corn stalk pith | MB | Crystal violet | NaCl | 0.02 mol/L | 30.65% decrease | Peng et al. (2021) |
Corn stalk pith | MB | Methylene blue | NaCl | 0.02 mol/L | 57.58% decrease | Tang et al. (2019) |
Plant parts . | Adsorbent class . | Dye . | Competing species . | Concentration of competing species . | Maximum change with competing species . | References . |
---|---|---|---|---|---|---|
Corn stigmata | MB | Methylene blue | NaCl | 1,000 mM | 27.76% decrease | Mbarki et al. (2018) |
Corn stigmata | MB | Indigo carmine | NaCl | 1,000 mM | 83.74% decrease | Mbarki et al. (2018) |
Corn starch | MBC | Methylene violet | CaCl | 0.6 M | 23% decrease | Mittal et al. (2018) |
Corn starch | MBC | Methylene violet | NaCl | 0.6 M | 20.5% decrease | Mittal et al. (2018) |
Corn stalk | MB | Methylene blue | H+ | 0.02 mol/L | 71% decrease | Tang et al. (2019) |
Corn stalk | MB | Methylene blue | K+ | 0.04 mol/L | 16% decrease | Tang et al. (2019) |
Corn stalk | MB | Methylene blue | K+ | 0.030 mol/L | 35.71% decrease | Tang et al. (2021) |
Corn stalk | MB | Methylene blue | Ca2+ | 0.030 mol/L | 85.71% decrease | Tang et al. (2021) |
Corn stalk pith | MB | Crystal violet | NaCl | 0.02 mol/L | 30.65% decrease | Peng et al. (2021) |
Corn stalk pith | MB | Methylene blue | NaCl | 0.02 mol/L | 57.58% decrease | Tang et al. (2019) |
COMPETITIVE ADSORPTION
Competitive adsorption explains the level of adsorbent attraction to the dye adsorbate ions in the presence of other existing competing chemical ions in aqueous media. In some textile industries, several electrolytes are added to the dye solution to increase the dye's fastness on the fabrics, thereby accumulating inorganic salts in the effluents that may disrupt the adsorption performance at given concentrations (Peng et al. 2021). Again, the nature of modified or activated biosorbent can introduce coexisting ions during the sorption process, which can compete with dye contaminants for the sorption sites, which may either increase or decrease the ionic strength. The effect of ionic strength on the adsorption tendency of corn stigmata biomass for cationic (methylene blue) and anionic (indigo carmine) dyes was analysed using NaCl solution at varying concentrations of 10, 100, and 1,000 mM (Mbarki et al. 2018). It was observed that the adsorption capacity of methylene blue decreased from 8.267 to 5.972 mg/g and from 8.036 to 1.307 mg/g for indigo carmine at increased concentrations. The positive effect of the salt on the decreased biosorption capacity of methylene blue dye could be due to the competitive interaction between Na+ and cationic dye on the biomass negative surface sites. In addition, the impact of Cl− of salt on the adsorption of indigo carmine follows similar competition between the chloride ion and anionic dye, SO3−, on the modified sorbent attracting sites.
The adsorption behaviour of a magnetic carbonaceous-prepared adsorbent from corn starch in dye aqueous solutions comprising NaCl and CaCl2 was investigated to evaluate the binding interaction between the carbonized adsorbent and methylene violet dye (Mittal et al. 2018). A decrease in efficiency of adsorption was observed with increasing concentrations of cations (0.1, 0.2, 0.3, 0.4, 0.5, and 0.6 M) in the dye solution, which depicts possible competitive electrostatic contacts between the cationic dye molecules and cations (Na+ and Ca2+) on the negatively charged binding sites of the carbonaceous adsorbent material. The existence of Ca2+ in the organic dye solution reduces the adsorption capacity more effectively than Na+ as a result of the smaller hydrated radius of the calcium ion, which aids its mobility in an aqueous solution and has a stronger competing tendency than monovalent ions. Furthermore, the result of coexisting cations (H+ and K+) on the sorption performance of H3PO4-modified corn stalk for methylene blue dye was reported by Tang et al. (2019). The uptake efficiency of methylene blue by the modified adsorbent decreased in the presence of increasing H+ and K+ ion concentrations, which showed that partial displacement and ion exchange were involved during the adsorption mechanism. H+ displayed lower adsorption capacity owing to higher attraction to adsorption sites with a reduced hydrated radius (2.83 Å) than K+, and hence, the driving force for the uptake was highly involved. Tang et al. (2021) reported on the competing effect of varying concentrations of K+ and Ca2+ on the adsorption capacity of carboxylate-modified corn stalk for methylene blue dye. The adsorption capacity values of methylene blue were reduced in the presence of K+ and Ca2+ ions with concentrations ranging from 0 to 0.03 mol/L, (Table 7) thus indicating competition with the organic dye-attracting active site on the treated adsorbent. The competing behaviour of Ca2+ decreased the removal efficiency of dye pollutants compared to K+ as a result of the smaller ionic radius of Ca2+, which constitutes a driving force for easier attraction of the sorption sites. The study further stated that the cations competed with the dye at lower coexisting concentrations, generating a highly decreased range of adsorption capacity, whereas at increasing concentrations, the electrostatic connections between the dye molecule and the surface sites are being inhibited by K+ and Ca2+. The effect of inorganic anions (Cl−, NO2−, NO3−, SO42−, and HPO42−) on the removal performance of cationic dyes (methylene blue and crystal violet) on corn pith biosorbent at concentrations of 0.05 M was evaluated (Peng et al. 2021). It was noted that the sorption efficiency for single and binary cationic dye molecule solutions was somewhat reduced in the presence of varied sodium salts. The status of adsorption inhibition by the anions in a single methylene blue dye aqueous solution follows this order: SO42− > HPO42− > Cl− > NO2− > NO3−, showing stronger competition of divalent electrolytes (Na2SO4 and Na2HPO4) with the dye molecules for limited adsorption sites than monovalent anions. The adsorption capacity of corn pith biosorbent decreased considerably for both sole and binary dye solutions, with a reduction in ionic strength at increased salt concentrations. This is due to the incessant competing electrostatic interaction that existed between Na+ and dye molecules for activated active sites, leading to an increased inhibitory effect on dye removal. In general, the reduction in sorption efficiency of maize biomass for organic dyes is a result of the compressibility of the adsorbent double layer caused by increased ionic strength, thus reducing the electrostatic attraction between the pollutant species and prepared corn biomass.
FINDINGS AND FUTURE PROSPECTS
The adsorption behaviour of a variety of dyes on corn/maize-based materials was reviewed in this study. From the available data, the most utilized corn biomass was cob, stalk, and straw, followed by husk, silk, and leaves. The adsorbents were grouped into four classes, namely, biosorbents, activated carbons, biochar, and composites. All the forms of corn/maize-based adsorbents exhibited high adsorption performance relative to the pre-treated precursor. This was due to the development of porous structure, functionality, and elemental composition in the modified or treated material. In particular, corn/maize-based composites and activated carbon adsorbents showed high surface areas with favourable functionality, which improved adsorbent's efficacy. The maximum uptake of dye was 1,682 mg/g for methylene blue using corn husk-based composite adsorbent, followed by Rhodamine B (using corn/maize-based activated carbon) with an adsorption capacity of 1,578 mg/g. Freundlich and pseudo-second-order models best represented the isotherm and kinetic data of the adsorbents for a variety of dyes. Freundlich and PFO models were also applicable in some studies. The parameters of the Langmuir and Freundlich isotherm models confirm the favourable adsorption nature. The main mechanisms for studied adsorption systems involve electrostatic attraction, ion exchange, and hydrogen bonding, along with complexation, pore filling, and π–π interaction. Thermodynamic results confirm spontaneous, endothermic/exothermic, and feasible adsorption natures.
Corn/maize-based materials were extensively addressed in the literature as highly efficient adsorbents for aquatic contaminants. Nevertheless, some points still need to be considered. Futuristic studies should consider applying two or more corn residues as precursors for adsorbent production. In addition, studies should also include the optimization of preparation variables for the corn/maize materials. There is also a need to test the behaviour of binary or multiple dye adsorbate systems as obtained in industrial wastewaters. Also, identifying the efficiency of corn-based materials for eliminating actual effluents in a continuous adsorption unit could be delved into. Furthermore, there is a need for cost analysis studies. Cost is an important factor in the choice of an adsorbent for industry. Cost analysis studies will not only help industries make informed and feasible decisions but also help futuristic works in this field of study and allow for comparison with commercial adsorbents.
COMPLIANCE WITH ETHICAL STANDARDS
This article does not contain any studies involving human or animal subjects.
FUNDING
There was no external funding for the study.
AUTHORS CONTRIBUTIONS
Kingsley O. Iwuozor: conceptualization, methodology, data curation, writing – original draft, writing – review and editing, validation. Chisom T. Umeh: data curation, writing – original draft, writing – review and editing, validation. Stephen Sunday Emmanuel: data curation, writing – original draft, writing – review and editing, validation. Ebuka Chizitere Emenike: methodology, data curation, writing – original draft, writing – review and editing, validation. Abel U. Egbemhenghe: writing – original draft and writing – review & editing. Odunayo T. Ore: writing – original draft and writing – review and editing. Taiwo Temitayo Micheal: data curation, writing – original draft, writing – review and editing, validation. Fredrick O. Omoarukhe: writing – original draft; writing – review & editing. Patience A. Sagboye; data curation, writing – original draft, writing – review and editing, validation. Victor E. Ojukwu: writing – original draft and writing – review and editing. Adewale George Adeniyi: conceptualization, methodology, writing – original draft; writing – review and editing, validation, supervision, project administration.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.