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In an era marked by rapid industrialization and heightened automobile usage, the demand for crude oil has surged, inducing ecological degradation and resource depletion. Effective management of intricate oily wastewater presents a formidable challenge. While diverse methods like gravity separation, centrifugation, and membrane techniques are employed for oil-water separation, gravity separation is the prevailing choice, yet limited to unstable emulsions. These methods often involve toxic substances harmful to marine life. Our research focuses on separating oil microemulsions in aqueous solutions. This study explores the application of superparamagnetic chitosan coagulants, revealing an optimal 10 ml dosage for peak efficiency. Aiming for rapid oil separation, we achieved a breakthrough with just 30 minutes, establishing a new benchmark. Rigorous VSM testing solidified the particles' magnetic capabilities, augmented through size reduction. Notably, at a 15% oil concentration, a remarkable 99.26% efficiency in oil separation was achieved, offering potential in microbiology, medicine, and drug delivery systems.

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  • Investigation of a superparamagnetic chitosan coagulant.

  • An oil separation time study is performed, and the shortest time recorded for oil separation is investigated.

  • Optimal coagulant dose is determined.

  • Investigation of magnetic properties in superparamagnetic chitosan particles.

  • A study of efficiency and particle size.

chitosan, coagulation, oil–water emulsion, superparamagnetic
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Subscripts

Ci

initial concentration

Cf

final concentration

Acronyms

MNPs

magnetic nanoparticles

XRD

X-ray diffraction

FTIR

Fourier transform infrared spectroscopy

EDS

energy-dispersive spectroscopy

TDS

Total Dissolved Solids

DO

Dissolved Oxygen

EC

Electrical Conductivity

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Oily wastewater from industrial activity and marine oil spills poses serious environmental risks (Hart 1957; Yim et al. 2012). Oil residues, heavy metals, and harmful compounds are released into wastewater by industrial, mining, and petrochemical sectors (Santos et al. 2023). The discharge can pollute waterways and harm aquatic life. For instance, improper refinery discharges can release hydrocarbons and pollutants into rivers, harming downstream ecosystems and water quality (Francis et al. 2023). Oil spills in marine ecosystems, whether caused by unintentional accidents during oil exploration, transportation faults, or natural disasters, can have serious implications (Yim et al. 2012). The 2010 Deepwater Horizon oil spill released a lot of crude petroleum into the Gulf of Mexico. This disaster devastated marine ecosystems, fisheries, and coastal economies (Zengel et al. 2021). In every case, prolonged ecological disruption emphasises the need for appropriate containment, treatment, and preventative methods to reduce these risks (Xiao et al. 2022). Oily effluent from industrial and maritime operations is difficult to manage for environmental protection. Petroleum refining, metallurgy, and food processing produce oily and grease-laden effluents that require particular treatment to minimise environmental damages. Oil spills and ship discharges can pollute marine habitats, requiring fast response techniques like containment booms and skimmers (Pete et al. 2021; Motorin et al. 2022). Sustainable practices such as bioremediation, which uses natural bacteria or coagulants, can also reduce environmental impacts (Wang et al. 2023).

Various techniques are employed to address this significant issue, including gravity separation, chemical coagulation and flocculation, centrifugation, membrane filtration, electro coalescence, absorbent materials, flotation, biological treatment, and a range of coagulants and flocculants such as aluminium sulphate (alum), ferric chloride, polyaluminium chloride (PAC), ferrous sulphate, polyacrylamide (PAM), cationic polyelectrolytes, anionic polyelectrolytes, chitosan, and starch-based flocculants (Meese et al. 2022). Due to their environmental sustainability and potential advantages over synthetic coagulants, natural organic coagulants are being used in wastewater treatment (Rius-Ayra et al. 2020). Using natural organic coagulants to remove oil from oily wastewater has many benefits. First, these coagulants are derived from renewable sources, making them more environmental friendly than synthetic counterparts, which often need extensive processing. For coagulation, tannins from chitosan, Moringa oleifera, horseradish vine, tamarind seeds, and tree barks can replace petroleum-based compounds (Khattabi Rifi et al. 2023). Additionally, natural coagulants are less harmful and pose fewer risks to aquatic species and the ecology. This trait follows green chemistry and environmental conservation principles. Sludge management can be improved by using natural coagulants (Kenea et al. 2023). Sludge formed by natural coagulation is often biodegradable, making it easier to dispose of or treat. This might reduce disposal costs and turn sludge into an agricultural asset, promoting a circular economy. However, natural organic coagulants have considerable downsides. The variation in composition and efficacy of natural coagulants due to seasonal fluctuations, geographic location, and plant development circumstances limits therapeutic efficacy. Synthetic coagulants allow more composition and performance customisation, resulting in more consistent results. Dosage optimisation is another issue. Natural coagulants may require higher dosages than synthetic ones to coagulate. This could affect the cost-effectiveness and practicality of natural coagulants in large-scale wastewater treatment (Okolo et al. 2021).

Chitosan, M. oleifera, and horseradish vine have been widely explored for their adaptability and efficacy. These studies show that these compounds have greater promise than synthetic counterparts. Chitosan reduces chemical oxygen demand (COD), removes suspended particles, sequesters heavy metals, and stabilises nanoparticles. Thus, it is vital to environmental goals. Chitosan, made from crab waste chitin, is deacetylated to provide special properties. This method boosts its positive charge density and water pollution absorption. According to Duran Baron et al. (2017) and Chen et al. (2019), chitin and chitosan are natural biopolymers with biocompatibility, biodegradability, non-toxicity, and adsorption capabilities, making them suitable for many applications. The abundance of chitin in crustacean waste makes it a renewable supply of cellulose (Kostag & El Seoud 2021) Interest in chitosan as a polysaccharide source has lately increased (Subbiahdoss & Reimhult 2020). Compared to alum and PAC, chitosan is a superior and cost-effective therapy. Rapid particle formation and growth make sedimentation easier (Cheng et al. 2023).

Chitin N-deacetylation is a key step in making chitosan, a biopolymer used in pharmaceuticals, agriculture, and water treatment. From crustacean shells, chitin is repeating N-acetylglucosamine units. Chitosan is formed by selectively removing the acetyl groups (CH3CO–) from glucosamine units during N-deacetylation (Tahtat et al. 2007). Chitosan's physical and chemical qualities depend on deacetylation or the elimination of acetyl groups. This parameter greatly affects chitosan's solubility, biocompatibility, and uses. Chitin is an alkaline treated with sodium hydroxide (NaOH) under regulated temperature and time to deacetylate. The deacetylation level of the chitosan product can be adjusted to fulfil industrial and research needs. Thus, optimising the N-deacetylation process of chitin is essential to unlocking the full potential of chitosan-based materials and their oil–water separation applications (Bisht et al. 2021; Vicente et al. 2021; Kou et al. 2023).

The integration of nanotechnology and its inventive implementations has shed light on a trajectory towards revolutionary potentials, by combining Chitin Deacetylation Using Deep Eutectic Solvents: Ab Initio-Supported Process Optimisation (Bisht et al. 2021). This innovative combination not only presents opportunities for improved stabilisation techniques but also signifies advancements in environmental sustainability (Meramo-Hurtado & González-Delgado 2021). The effectiveness and adaptability of natural coagulants, such as chitosan, are supported by empirical evidence. These natural coagulants outperform synthetic alternatives in various areas, including reducing COD, removing suspended particles, binding heavy metals, and stabilising nanoparticles (Siswoyo et al. 2023). Magnetic nanoparticles (MNPs), due to their distinctive size and magnetic characteristics, exhibit a wide range of applications in several sectors. The utilisation of nanoparticles has been increasingly prevalent in several fields such as biotechnology, biomedicine, material science, engineering, and environmental applications, due to their unique physicochemical characteristics (Vo et al. 2015; Hai et al. 2023b). The application of MNPs in addressing wastewater issues has significantly enhanced the preservation of ecosystem integrity. This is primarily attributed to the remarkable magnetic properties of iron oxide (Fe3O4), which make it a highly effective material in this context. The painstaking procedure involves the strategic utilisation of magnetic fields to recover Fe3O4 nanoparticles from reaction media, which is subsequently followed by filtration to achieve a neutral pH using ultrapure water. MNPs have been more valuable in adsorption-based treatment techniques due to their ability to effectively separate pollutants from aqueous solutions (Riofrio et al. 2021). The utility and effectiveness of utilising external magnets for separation surpasses those of conventional filtration or centrifugation techniques. Within the broader context, the chemical co-precipitation method, as exemplified by the studies conducted by several authors (Kumar et al. 2018; Liu et al. 2018; Tu et al. 2020; Liao et al. 2021; Phalake et al. 2022), assumes a crucial role in the synthesis of MNPs. The convergence of these trends holds the potential to significantly alter the course of wastewater management, facilitating the development of sustainable and resilient strategies that contribute to a more environmentally friendly future. Further enhancing the utility of chitosan, the integration of MNPs, particularly superparamagnetic iron oxide (Fe3O4) nanoparticles, introduces a range of compelling advantages. Recent studies showcase the potential of superparamagnetic chitosan hybrid nanoparticles, formed through an innovative one-step co-precipitation strategy involving ferrous ions. These nanoparticles, with defined spherical shapes, display efficient mobility and interaction in aqueous environments, presenting promising applications in various fields (Bahri et al. 2022; Ghattavi et al. 2023).

This study addresses a research gap by investigating the use of superparamagnetic chitosan hybrid nanoparticles for micro-emulsified oil extraction from wastewater. Unlike traditional methods, this unique approach achieves a remarkable oil separation rate with optimal dosage and time, opening new possibilities in magnetic nanoparticle technology across disciplines. The primary focus is on oil-in-water microemulsions, an area with untapped potential in microbiology, medicine, and drug delivery. The research combines chitosan's coagulation ability with ferrous ions using a one-step co-precipitation method, resulting in 99.26% oil separation efficiency.

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In the current study, following materials are used for the synthesis of superparamagnetic chitosan nanoparticles, as shown in Table 1.

Table 1

Chemicals

Sl. no.NameFormulaManufacturer
1. Chitosan C18H35N30 HiMedia Laboratories Pvt. Ltd, Mumbai, India 
2. Ferrous sulphate heptahydrate FeSO4·7H2O Molychem, Mumbai, India 
3. Ferric chloride FeCl3·6H2O Oxford Lab fine Chem LLP, Palghar, Maharashtra, India 
4. Acetic acid glacial CH3COOH Finar Limited, Ahmedabad, Gujarat, India 
5. Sodium hydroxide pellets NaOH Meru Chem PVT.LTD. Mumbai 
6. Ethanol C2H6O India Glycols Ltd 
Sl. no.NameFormulaManufacturer
1. Chitosan C18H35N30 HiMedia Laboratories Pvt. Ltd, Mumbai, India 
2. Ferrous sulphate heptahydrate FeSO4·7H2O Molychem, Mumbai, India 
3. Ferric chloride FeCl3·6H2O Oxford Lab fine Chem LLP, Palghar, Maharashtra, India 
4. Acetic acid glacial CH3COOH Finar Limited, Ahmedabad, Gujarat, India 
5. Sodium hydroxide pellets NaOH Meru Chem PVT.LTD. Mumbai 
6. Ethanol C2H6O India Glycols Ltd 
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Superparamagnetic chitosan nanoparticles are synthesised through the chemical co-precipitation of Fe2+ and Fe3+ ions using NaOH in the presence of chitosan dissolved in acetic acid solution.

The methodology has been modified to reduce the duration of the co-precipitation process. A beaker is utilised to contain an initial volume of 100 mL of a 2% solution of CH3COOH(v/v), followed by the addition of 2 g of chitosan. The beaker is positioned atop a magnetic stirrer (TOP-360HS), whereby the rotational speed is adjusted to 70 rpm. The dissolution kinetics of chitosan particles in the solution typically need duration of around 60 min, as depicted in Figure 1(a). Following this, a combined mass of 1.72 g of FeSO4·7H2O and 4.70 g of FeCl3·6H2O were added to the rotating solution with the molar ratio of chitosan to Fe2+/Fe3+ ions as 1:33. Subsequently, NaOH solution with a concentration of 30% (v/v) was incrementally introduced until the solution's pH reached a neutral state (pH = 7). This process was undertaken to establish the solution's stability, as illustrated in Figure 1(b). The aim of this experimental protocol was to initiate the precipitation of ferric ions onto the chitosan particles. Currently, the rotational velocity remains consistent at 50 rpm while the temperature is gradually increased to 40 °C within a time frame of 10 min. Subsequently, the solution undergoes heat treatment at a temperature of 90 °C for a duration of 1 h, while ensuring consistent agitation at a rate of 50 rpm. The resulting precipitation solution is depicted in Figure 1(c).
Figure 1
Co-precipitation method for the synthesis of magnetic chitosan particles.
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Co-precipitation method for the synthesis of magnetic chitosan particles.

Figure 1
Co-precipitation method for the synthesis of magnetic chitosan particles.
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Co-precipitation method for the synthesis of magnetic chitosan particles.

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Subsequently, the particles undergo separation through the utilisation of vacuum filtration, employing a vacuum pump (Hoxyn Vacuum Pump VE 115N) that is linked to a Büchner funnel. The filtration procedure is iteratively performed using ethanol and distilled water as the filtering agents (Figure 1(d)). The particles resulting from the filtration process exhibit a significant amount of moisture, as depicted in Figure 1(e). Consequently, it is necessary to subject the particles to a drying procedure. Following that, the particles undergo a drying procedure in an oven dryer (S.P. Systems) maintained at a temperature of 70 °C for a period of 1 h, as depicted in Figure 1(f). The ultimate outcome exhibits a black hue and possesses a texture reminiscent to powder as in Figure 1(g). Subsequently, the object is carefully enclosed within an airtight desiccator and preserved in a designated area characterised by low temperature (25–30 °C) and minimal humidity (30 and 50%). The stability of the coagulant is observed to persist for a period of around 3–4 months within the enclosed system. The consistency and dependability in nanoparticle synthesis are achieved through a combination of quality control techniques, such as standardisation of equipment and materials, environmental control, process monitoring, characterisation techniques, documentation, and quality assurance protocols. By implementing these measures, we reduced variability in experimental environments and produced nanoparticles with reliable properties for various applications. The entire process is further explained in the schematic diagram presented in Figure 2.
Figure 2
Schematic diagram showing the synthesis of superparamagnetic chitosan particles.
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Schematic diagram showing the synthesis of superparamagnetic chitosan particles.

Figure 2
Schematic diagram showing the synthesis of superparamagnetic chitosan particles.
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Schematic diagram showing the synthesis of superparamagnetic chitosan particles.

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In the co-precipitation process, initially, Fe2+ and Fe3+ ions obtained from FeSO4 and FeCl3 are introduced into an aqueous solution containing chitosan. Chitosan is a biopolymer derived from chitin, which contains amino groups (NH2) that can serve as binding sites for metal ions such as Fe2+ and Fe3+ ions. In the solution, the amino groups (-NH2) of chitosan form coordination bonds with the Fe2+ and Fe3+ ions. This process involves the donation of lone pairs of electrons from the amino groups to the positively charged ferric ions, resulting in the formation of coordination complexes between chitosan, Fe2+ and Fe3+ ions. As more ions bind to chitosan molecules, the coordination complexes start to aggregate and form nuclei. These nuclei serve as the starting points for precipitation with NaOH. Over time, additional ions continue to join the complexes, causing them to grow in size. As they become larger and heavier, they reach a critical size where they can no longer remain suspended in the solution. At this point, they precipitate out of the solution as solid particles. The inclusion of these connection leads to the generation of superparamagnetic particles, as illustrated in Figure 3.
Figure 3
Chitosan infused with superparamagnetic particles.
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Chitosan infused with superparamagnetic particles.

Figure 3
Chitosan infused with superparamagnetic particles.
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Chitosan infused with superparamagnetic particles.

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Studying lower oil concentrations in oil–water separation is essential for both environmental compliance and resource efficiency. Strict regulations govern oil-in-water levels in industrial and environmental contexts. Removing trace oil efficiently is crucial for eco-compliance and resource recovery. Lower oil concentrations enable cost-effective extraction of valuable components, while also enhancing the efficiency of separation processes with the reduction of time required for the process. Additionally, it prevents contamination and safeguards water resources. Research in this area drives innovation, improving separation technologies, materials, and equipment across various industries. In emergencies, understanding and handling low oil concentrations are vital for effective clean-up and mitigation strategies, given the variable nature of real-world oil–water mixtures. Finally, optimising separation operations, including technique selection and system design, benefits from insights into lower oil concentrations.

Two liquids were mixed together in order to produce an emulsion, which was done so that one liquid would be distributed uniformly throughout the other. An emulsion was created by blending sunflower oil and distilled water at a speed between 2,000 and 2,500 revolutions per minute with a hand blender rated at 750 W of power (Robot Inox 750S). This was done so that the oil would be distributed evenly throughout the water regardless of the water concentration. After the components have been combined, the emulsion is used to study the coagulation of magnetic chitosan, which is necessary for the extraction of oil from water. This process is observed for 15 min after the components have been combined. Samples were taken with oil concentrations of 5, 10, 15, 20, and 50%, with the remaining volume consisting of water (Figures 4 and 5).
Figure 4
Schematic diagram for the synthesis of an oil–water mixture.
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Schematic diagram for the synthesis of an oil–water mixture.

Figure 4
Schematic diagram for the synthesis of an oil–water mixture.
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Schematic diagram for the synthesis of an oil–water mixture.

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Figure 5
50, 20, 15, 10, and 5% of oil content in the water emulsion.
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50, 20, 15, 10, and 5% of oil content in the water emulsion.

Figure 5
50, 20, 15, 10, and 5% of oil content in the water emulsion.
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50, 20, 15, 10, and 5% of oil content in the water emulsion.

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In 1 L of distilled water, 20 mg of superparamagnetic chitosan particles were combined. The pH of the coagulant solution was found to be 8.75. Then, 10 mL of the coagulant was added to each concentration of emulsion while continuously swirling with a magnetic stirrer for 5 min. The coagulant–emulsion mixture was then left alone for 30 min. After 30 min, the efficiency was evaluated using absorbance data from each treated water obtained by a UV–Vis Spectrophotometer (Mortas Scientific MS UV Plus) set to a wavelength of 300–350 nm.

From the absorbance, concentration was calculated by using Beer–Lambert law as follows,
where A indicates the absorbance; ɛ indicates the molar absorptivity; b indicates the length of light path; C indicates the concentration.
Then, oil removal efficiency was calculated by the formula,
where Ci refers to the initial concentration of the oil; Cf refers to the final concentration of the oil.
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When superparamagnetic chitosan coagulant is introduced into an oil–water emulsion, a series of essential mechanisms, including coagulation, flocculation, and buoyancy, contribute to an effective oil–water separation. Micro-emulsified oil particles present in the emulsion are drawn into the porous structure of the superparamagnetic chitosan particles due to the attractive forces at play. This phenomenon can be attributed to the presence of ferrous ions in the superparamagnetic chitosan, which carry a positive charge. Concurrently, the oil particles within the emulsion typically possess negative charges. As a result, the electrostatic interaction between these charged species facilitates the formation of flocs. These flocs, comprised of aggregated oil and chitosan particles, gradually coalesce over time. As depicted in Figure 6, these coagulated flocs ascend towards the surface of the emulsion due to their reduced density compared to the surrounding liquid. This buoyancy-driven migration results in the formation of a distinct layer, effectively separating the treated water from the oil flocs, thereby achieving efficient oil–water separation as shown in Figure 7.
Figure 6
Oil separation mechanism.
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Oil separation mechanism.

Figure 6
Oil separation mechanism.
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Oil separation mechanism.

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Figure 7
Movement of the flocs during oil separation.
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Movement of the flocs during oil separation.

Figure 7
Movement of the flocs during oil separation.
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Movement of the flocs during oil separation.

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We conducted certain studies using the parameters pH, TDS, DO, and EC to determine the internal changes in the oil–water emulsion before and after treatment. Here, we have observed two primary things: first, the characteristics of the oil–water emulsion changed before and after treatment; second, the parameters of the emulsion changed in response to concentration rise. The pH of the oil–water emulsion after the treatment gets lower to the pH of water. As in the oil–water emulsion, the presence of emulsified oil particles in water lowers TDS, DO, and EC values. After treatment, the TDS, DO, and EC values rise to the acceptable limits of water, as shown in Tables 2 and 3.

Table 2

Initial data of oil–water emulsion

Oil concentration (%)pHTDS (mg/L)DO (mg/L)EC (μS/cm)
5 8.07 9 3.9 172 
10 8.31 12 4.2 160 
15 8.47 17 5.1 141 
20 8.52 24 5.8 127 
50 8.63 37 6.3 62 
Oil concentration (%)pHTDS (mg/L)DO (mg/L)EC (μS/cm)
5 8.07 9 3.9 172 
10 8.31 12 4.2 160 
15 8.47 17 5.1 141 
20 8.52 24 5.8 127 
50 8.63 37 6.3 62 
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Table 3

Final data of the treated oil–water emulsion

Oil concentration (%)pHTDS (mg/L)DO (mg/L)EC (μS/cm)
5 7.9 26 7.8 271 
10 7.5 34 7.6 263 
15 7.7 41 7.3 246 
20 7.8 47 7.1 214 
50 7.6 52 6.8 176 
Oil concentration (%)pHTDS (mg/L)DO (mg/L)EC (μS/cm)
5 7.9 26 7.8 271 
10 7.5 34 7.6 263 
15 7.7 41 7.3 246 
20 7.8 47 7.1 214 
50 7.6 52 6.8 176 
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FTIR result

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On investigating the Fourier transform infrared spectroscopy (FTIR) plot from wavenumber of 4,000–500 cm−1, the FTIR analysis of chitosan provides valuable insights into its molecular structure and functional groups. The characteristic peaks of chitosan reveal distinctive vibrational modes that are essential for its identification. Notably, the FTIR spectrum displays prominent peaks at specific wavenumbers: 3,470 cm−1, corresponding to –OH and –NH2 stretching vibrations; 2,890 cm−1, indicative of –CH stretching; 1,560 cm−1, associated with amide I/C = O stretching; 1,400 cm−1, representing amide II/–NH bending; 1,100 cm−1, denoting C–O–C stretching; and 662 cm−1, signifying pyranoside ring stretching vibration (Wang & Li 2023) as shown in Figure 8(a). In case of superparamagnetic chitosan, there are additional prominent peaks at 1,650 cm−1, which corresponds to the presence of conjugated carboxyl groups, highlighting the presence of functional groups crucial for potential applications in drug delivery and biomedical fields. Furthermore, characteristic peaks at 1,390 and 837 cm−1 are observed, which are consistent with the presence of iron(II) oxalate, an integral component of these nanoparticles. The FTIR spectrum also exhibits distinct bands in the range of 1,650–1,615 cm−1; 1,390; 1,160; and 837 cm−1 (Zhong et al. 2022), further confirming the presence of iron sulphate (FeSO4) within the nanoparticle structure as depicted in Figure 8(b). This spectrum ensures that Fe+ ions are infused with chitosan which has increased adsorption capacity compared to untreated chitosan. This is particularly useful in oil–water separation, where the material can efficiently adsorb and remove hydrophobic substances such as oil and grease from water. It can be tailored to selectively adsorb specific contaminants, such as heavy metals, organic pollutants, or oils. This selectivity can be advantageous for treating complex wastewater streams. It can be integrated into existing water treatment processes, such as filtration systems, to enhance oil–water separation efficiency without significant modifications. Iron-infused chitosan can be magnetised, allowing for easy separation of the adsorbent material from the water using magnetic fields. This facilitates the recovery of the adsorbed contaminants.
Figure 8
FTIR of (a) chitosan and (b) chitosan magnetic nanoparticles.
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FTIR of (a) chitosan and (b) chitosan magnetic nanoparticles.

Figure 8
FTIR of (a) chitosan and (b) chitosan magnetic nanoparticles.
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FTIR of (a) chitosan and (b) chitosan magnetic nanoparticles.

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Particle size analysis

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With the application of Zetasizer Nano ZS, the particle size distribution of nanoparticles was determined using Dynamic Light Scattering (DLS) technology (Malvern Instruments, UK). Using the backscattering mode (angle of detection 173°, measurement location 1 mm from the cuvette wall), the device measures changes in intensity over time caused by moving particles in the sample after being irradiated with a He–Ne laser beam (5 mW, 633 nm) in the sample. Particle size distributions are generated by performing an autocorrelation analysis on the data collected, later analysed by statistical data analysis techniques to obtain the particle size distributions. Other sources (Xu, light scattering methods) provide further information on these mathematical ideas. The data presented in this study represent the mean distributions derived from four separate repeats. A temperature of 37 °C was used to conduct the test. From the particle size analysis, it was concluded that in Case I, the average particle size was 1,273 d.nm and in Case II it was 99.43 d.nm. It is further concluded that as we lowered the size of the particles, the efficiency increased from 90.1 to 99.26%, as shown in Figure 9. The particle size of a coagulant is pivotal in oil–water separation. Smaller particles enhance aggregation efficiency by interacting more effectively with oil droplets, ideal for rapid separation. Their even distribution ensures thorough oil droplet interaction, but a balance must be struck to avoid excess usage. Smaller coagulant particles lead to quicker settling of denser flocs or flotation. Filterability depends on particle size, with smaller particles being easier to filter. Smaller coagulant particles may require lower dosages for efficiency, though it varies based on factors. Selection involves considering the mixture, separation efficiency, and cost-effectiveness, often requiring testing. The coagulant's particle size affects collision efficiency, aggregation kinetics, settling speed, contact surface area, energy consumption, process consistency, and effluent quality, making it crucial in oil–water separation processes. Proper selection and control yield efficient, cost-effective separation.
Figure 9
Case I: particles before grinding. Case II: particles after grinding.
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Case I: particles before grinding. Case II: particles after grinding.

Figure 9
Case I: particles before grinding. Case II: particles after grinding.
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Case I: particles before grinding. Case II: particles after grinding.

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SEM and EDS analysis

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Figures 10(a) and 10(b) depict the micrograph of pure chitosan, which was captured using the FlexSEM 1000 II VP-SEM. The micrographs presented in Figure 10(a) and 10(b) depict the fibrous and porous nature of the chitosan structure. The electron micrographs presented in Figure 10(c) and 10(d) illustrate the morphology of superparamagnetic chitosan particles, revealing a porous structure with a chain-like configuration. Based on the findings of the scanning electron microscopy (SEM) study, it can be inferred that the presence of pores inside the particles may serve as a significant factor contributing to the absorption of oil particles by superparamagnetic chitosan particles.
Figure 10
Scanning electron microscopy (SEM) images of (a) and (b) pure chitosan and (c) and (d) superparamagnetic chitosan particles.
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Scanning electron microscopy (SEM) images of (a) and (b) pure chitosan and (c) and (d) superparamagnetic chitosan particles.

Figure 10
Scanning electron microscopy (SEM) images of (a) and (b) pure chitosan and (c) and (d) superparamagnetic chitosan particles.
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Scanning electron microscopy (SEM) images of (a) and (b) pure chitosan and (c) and (d) superparamagnetic chitosan particles.

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Energy-dispersive X-ray spectroscopy (EDS) is a scientific method employed for the purpose of ascertaining the elemental constitution of a given specimen. This is achieved by quantifying the energy and intensity of X-rays discharged during the interaction between a high-energy electron beam and the constituent atoms of the said specimen. EDS serves the purpose of corroborating the elemental stoichiometry, which entails the determination of the relative proportions of distinct elements present within the nanoparticles. Figure 11(a) illustrates the EDS analysis of chitosan in its pure form. The EDS examination reveals the detection of elements such as C, O, and N, as well as impurities like Na and Mg which may be present during the manufacturing process of chitosan.
Figure 11
EDS spectra of (a) pure chitosan and (b) superparamagnetic chitosan particles.
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EDS spectra of (a) pure chitosan and (b) superparamagnetic chitosan particles.

Figure 11
EDS spectra of (a) pure chitosan and (b) superparamagnetic chitosan particles.
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EDS spectra of (a) pure chitosan and (b) superparamagnetic chitosan particles.

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The EDS analysis of magnetic chitosan nanoparticles revealed the presence of four prominent elements: carbon (C), oxygen (O), nitrogen (N), and iron (Fe). These elements are known to be the primary constituents of chitosan and magnetite. The detection of these elements in the EDS spectra provides confirmation of the presence of chitosan and Fe3O4 in the nanoparticles, as depicted in Figure 11(b). Additional impurities, such as sulphur (S), chlorine (Cl), and sodium (Na), are also observed, indicating the presence of by-products resulting from the synthesis procedure.

XRD analysis

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X-ray diffraction (XRD) is used to analyse the phase transition of crystalline materials. A beam of incident X-ray falls on the atoms of a crystal and diffract in different directions. It also contributes to determine the orientation of a single crystal and the average spacing between layers of atoms in a single crystal. Wide-angle X-ray diffraction (WAXRD) was done using BRUKER D8 ADVANCE X-ray diffractometer equipment, in the range of 0°–85° with a scan rate of 2°/min and step size of 0.02°. XRD patterns of superparamagnetic chitosan particles are shown in Figure 12, indicating the existence of iron oxide particles (Fe3O4) and the existence of superparamagnetic chitosan particles. Table 4 shows Miller indices and JCPDS card numbers used the reference with the help of X'pert highscore software.
Table 4

d-spacing of the peaks conforming with the JCPDS database

Compound nameChemical formula2θ (°)d-spacing [Å](h k l)Reference code
Iron pentacyanonitrosoferrate(III) C5Fe2N6O1 34.984 2.562 (004) 98-011-1988 
39.288 2.291 (024) 
50.179 1.816 (044) 
56.87 1.617 (026) 
68.288 1.372 (246) 
Tetramethylammonium hydrogensulfate sulfur dioxide C4H13N1O6S2 25.017 3.556 (202) 98-009-6421 
34.984 2.562 (132) 
38.48 2.337 (313) 
39.288 2.291 (304) 
45.46 1.993 (343) 
50.179 1.86 (272) 
Sucrose C12H22O11 35.99 2.493 (231) 00-024-1977 
38.48 2.337 (231) 
39.288 2.291 (421) 
Magnetite Fe3O4 35.99 2.493 (113) 98-011-1046 
72.24 1.306 (026) 
Thiotrithiazyl nitrate N4O3S4 26.76 3.328 (112) 98-000-7702 
34.984 2.562 (213) 
45.46 1.993 (116) 
50.179 1.816 (153) 
Hematite Fe2O3 26.764 3.328 (200) 98-006-9750 
50.179 1.816 (212) 
55.024 1.667 (400) 
68.288 1.372 (402) 
70.311 1.337 (023) 
Trichlorotrioxotrithiatriazine – Lt Cl3N3O3S3 21.37 4.154 (013) 98-003-2172 
25.017 3.556 (121) 
26.764 3.328 (004) 
45.46 1.993 (153) 
55.024 1.662 (008) 
Compound nameChemical formula2θ (°)d-spacing [Å](h k l)Reference code
Iron pentacyanonitrosoferrate(III) C5Fe2N6O1 34.984 2.562 (004) 98-011-1988 
39.288 2.291 (024) 
50.179 1.816 (044) 
56.87 1.617 (026) 
68.288 1.372 (246) 
Tetramethylammonium hydrogensulfate sulfur dioxide C4H13N1O6S2 25.017 3.556 (202) 98-009-6421 
34.984 2.562 (132) 
38.48 2.337 (313) 
39.288 2.291 (304) 
45.46 1.993 (343) 
50.179 1.86 (272) 
Sucrose C12H22O11 35.99 2.493 (231) 00-024-1977 
38.48 2.337 (231) 
39.288 2.291 (421) 
Magnetite Fe3O4 35.99 2.493 (113) 98-011-1046 
72.24 1.306 (026) 
Thiotrithiazyl nitrate N4O3S4 26.76 3.328 (112) 98-000-7702 
34.984 2.562 (213) 
45.46 1.993 (116) 
50.179 1.816 (153) 
Hematite Fe2O3 26.764 3.328 (200) 98-006-9750 
50.179 1.816 (212) 
55.024 1.667 (400) 
68.288 1.372 (402) 
70.311 1.337 (023) 
Trichlorotrioxotrithiatriazine – Lt Cl3N3O3S3 21.37 4.154 (013) 98-003-2172 
25.017 3.556 (121) 
26.764 3.328 (004) 
45.46 1.993 (153) 
55.024 1.662 (008) 
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Figure 12
XRD analysis of superparamagnetic chitosan particles.
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XRD analysis of superparamagnetic chitosan particles.

Figure 12
XRD analysis of superparamagnetic chitosan particles.
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XRD analysis of superparamagnetic chitosan particles.

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Magnetic properties

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The magnetic performance of the magnetic chitosan particles prepared in this study was determined using VSM. Figure 13 shows the typical magnetisation loop. There was no remanence and coercivity, suggesting that magnetic chitosan particles are superparamagnetic. The saturation magnetisation was calculated to be about 36 emu/g. This value was higher than that of other chitosan-based Fe3O4 beads. They reported the saturation magnetisation was about 17.6 and 16.3 emu/g, respectively. Therefore, the magnetic chitosan particles can be easily separated with the help of the external magnetic field.
Figure 13
Magnetic hysteresis curve of superparamagnetic chitosan particles.
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Magnetic hysteresis curve of superparamagnetic chitosan particles.

Figure 13
Magnetic hysteresis curve of superparamagnetic chitosan particles.
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Magnetic hysteresis curve of superparamagnetic chitosan particles.

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Experimental results

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Oil–water separation time study

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The optimum time at which the coagulant works efficiently is very important in oil–water separation. It is comparatively easy to separate the oil from the emulsion when the oil content in the emulsion is high. So, we prepared an emulsion with less oil content (i.e., 15% oil concentration). This emulsion in the beaker was then placed in a magnetic stirrer. Then, 10 mL of the coagulant was mixed with the emulsion under continuous stirring for 10 min. Then the absorbance of the treated water was determined by an UV spectrophotometer at near to 300 nm wavelength after 10 min. Choosing the 300 nm wavelength in UV spectroscopy is critical for accurate oil concentration measurement in oil–water emulsions because the absorption peak matches with the oil's absorption peak, ensuring exact results. It also improves sensitivity, allowing for more precise oil concentration detection. It is also relatively selective for oil, reducing water interference. This wavelength improves the linear connection between absorbance and concentration as well. Similarly, the absorbance of the same treated water at 15, 20, 25, 30, and 35 min was determined. From the absorbance and by using the Beer–Lambert law, the concentration of the oil was determined. Thus, the efficiency of oil–water separation with respect to time was calculated as 99.26% at 30 min. Only a slight change in the result was observed when the time exceeds 30 min, as shown in Figure 14. So, the optimum separation time examined was 30 min.
Figure 14
Oil removal efficiency of treated water achieved at time (10, 15, 20, 25, 30, and 35 min).
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Oil removal efficiency of treated water achieved at time (10, 15, 20, 25, 30, and 35 min).

Figure 14
Oil removal efficiency of treated water achieved at time (10, 15, 20, 25, 30, and 35 min).
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Oil removal efficiency of treated water achieved at time (10, 15, 20, 25, 30, and 35 min).

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Coagulant dosage study

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The optimum coagulant dosage is always required in coagulation. So, in our case, for determining the coagulant dosage, we have performed some tests on the emulsion similar to the oil separation time study. Here, we prepared five samples of emulsions with 15% oil concentration to study the effect of coagulation dosages on lower concentration of the oil. These five emulsion samples were then placed on a magnetic stirrer. Then, different dosages of coagulants (i.e., 5, 7.5, 10, 12.5, and 15 mL) (Vo et al. 2015; El Rabey et al. 2023; Hai et al. 2023a) were added in each emulsion sample. Then as from the time study, optimum separation time was found to be 30 min. So, absorbance of each treated water was determined by using a UV spectrophotometer. Then, the concentration of oil in treated water was calculated from the absorbance by using the Beer–Lambert law. So, efficiency of oil–water separation with respect to the coagulant dosage was found to be 99.26% at 10 mL of coagulant dosage (Figure 15). So, the optimum dosage examined was 10 mL.
Figure 15
Oil removal efficiency of treated water achieved by different coagulant dosages (5, 7.5, 10, 12.5, and 15 mL) in 15% oil–water emulsions.
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Oil removal efficiency of treated water achieved by different coagulant dosages (5, 7.5, 10, 12.5, and 15 mL) in 15% oil–water emulsions.

Figure 15
Oil removal efficiency of treated water achieved by different coagulant dosages (5, 7.5, 10, 12.5, and 15 mL) in 15% oil–water emulsions.
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Oil removal efficiency of treated water achieved by different coagulant dosages (5, 7.5, 10, 12.5, and 15 mL) in 15% oil–water emulsions.

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Separation efficiency

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Comparative coagulation study on different oil concentrations in the emulsion was required to examine the results at optimum dosage and optimum separation time. For which, we prepared five emulsion samples with different oil concentrations of 5, 10, 15, 20, and 50%. These five emulsions were then treated with 10 mL of coagulant dosage for 30 min. Then, the absorbance of each of the sample was determined and then the concentration of the oil was also obtained as mentioned previously. The separation efficiency of different emulsions having 5, 10, 15, 20, and 50% oil concentration were found to be 81.24, 92.39, 99.26, 99.41, and 99.68% (Figure 16).
Figure 16
Oil removal efficiency from 5, 10, 15, 20, and 50% oil-in-water emulsions.
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Oil removal efficiency from 5, 10, 15, 20, and 50% oil-in-water emulsions.

Figure 16
Oil removal efficiency from 5, 10, 15, 20, and 50% oil-in-water emulsions.
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Oil removal efficiency from 5, 10, 15, 20, and 50% oil-in-water emulsions.

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Then, the oil removal efficiency was calculated by the following formula:
where Ci refers to the initial concentration of oil and Cf refers to the final concentration of oil.
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The optimum time required for efficient coagulation and separation of oil from an emulsion with a lower oil content (15% oil concentration). The procedure involves mixing 10 mL of coagulant with the emulsion and stirring continuously for 10 min. Afterward, the absorbance of the treated water is measured using a UV spectrophotometer at a wavelength near 300 nm. This wavelength is critical because it matches with the absorption peak of oil, ensuring accurate results, improving sensitivity, and reducing water interference. The oil concentration in the treated water is determined using the Beer–Lambert law. The efficiency of oil–water separation with respect to time is calculated and found to be 99.26% at 30 min. The optimum separation time is established as 30 min, with only slight changes in results observed beyond this time. Five samples of emulsion are prepared, and each is treated with a different coagulant dosage (5, 7.5, 10, 12.5, and 15 mL). The samples are stirred for 30 min, similar to the time study. The optimum coagulant dosage is identified as 10 mL. This section explores the separation efficiency of different emulsions with varying oil concentrations (5, 10, 15, 20, and 50%) under the previously established optimum conditions (10 mL coagulant dosage for 30 min). The results demonstrate that the separation efficiency increases with higher oil concentrations in the emulsion, with the highest efficiency achieved for the 50% oil concentration. The same process was repeated 3–4 times in order to verify the reproducibility and reliability of the obtained data. In reality, the composition of emulsions can vary significantly, which may affect the coagulation efficiency. Real-world emulsions might contain various impurities or contaminants not considered in the study.

However, the coagulant used in the study may have a varying effectiveness with different types of oils or contaminants. The study did not explore the coagulant's performance with a wide range of oil types or complex mixtures commonly found in industrial settings. The continuous stirring for 10 min in the time study and 30 min in subsequent tests may not accurately simulate the mixing conditions in real-world applications. The dynamics of mixing, turbulence, and flow rates can significantly impact coagulation efficiency. The study was conducted on a small scale with beakers and a magnetic stirrer. The behaviour of coagulants and separation efficiency may differ when scaling up to industrial-sized equipment, where factors such as residence time and flow patterns are different. While an optimal coagulant dosage was identified, the precision and consistency of dosage delivery can vary in practical applications. Variations in dosage could affect the separation efficiency. The accuracy of oil concentration measurements relies on the sensitivity and calibration of the UV spectrophotometer. Instrumental errors or fluctuations in readings can influence the calculated results. Environmental conditions such as temperature, pH, and salinity can affect the coagulation process. The study may not have accounted for potential variations in these factors. The practicality and cost-effectiveness of using the identified coagulant and optimal conditions in an industrial setting may not have been evaluated. Real-world implementation could face economic and resource challenges.

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Along with the coagulants the fluid properties also play an important role during oil–water separation. If the density and viscosity of oil are significantly lower than water, the separation efficiency is affected due to detrimental effects on coagulation. The density of the oil phase and the difference in the density between oil and water can affect the rate at which oil droplets coagulate and separate from water. Additionally, the viscosity of both the oil and water phases can influence the mobility and collision dynamics of the oil droplets, impacting the coagulation process. Understanding and optimising these factors is crucial in designing effective oil–water separation processes, such as those used in wastewater treatment or oil spill clean-up. The separation efficiency of various type of oil is presented in Table 5. On comparing with the previous literature work, the oil separation efficiency has improved; however, the current oil density and viscosity are much lower than the oil considered in the literature. This observation clearly ensures the suitability of superparamagnetic nanoparticles for various types of oil–water separation process.

Table 5

Comparative study

Sl.No.NameDensity (kg/m3)Viscosity (cP)Separation efficiency (%)
1 Cyclohexane 779 1.0 85.13 
3 Chloroform 498 0.57 84.54 
4 Toluene 869 0.59 83.62 
5 Dichloromethane 1,322 0.44 82.04 
6 Rapeseed oil 914 37 91.19 
7 Lubricating oil 940 52 98.15 
8 Silicone oil 970 20 90.1 
9 Soyabean oil 807 40 97.6 
10 Oil (present work) 798 45 99.26 
Sl.No.NameDensity (kg/m3)Viscosity (cP)Separation efficiency (%)
1 Cyclohexane 779 1.0 85.13 
3 Chloroform 498 0.57 84.54 
4 Toluene 869 0.59 83.62 
5 Dichloromethane 1,322 0.44 82.04 
6 Rapeseed oil 914 37 91.19 
7 Lubricating oil 940 52 98.15 
8 Silicone oil 970 20 90.1 
9 Soyabean oil 807 40 97.6 
10 Oil (present work) 798 45 99.26 
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For the identification of effectiveness of the current process, the achieved removal efficiency of superparamagnetic chitosan has been compared with the removal efficiency that has been reported in the literature for oil–water separation by magnetic and natural coagulants. The comparison reveals that the achieved removal efficiency in the current study by using superparamagnetic chitosan nanoparticles is higher than the data reported in the literature. This could be due to the attainment of large surface area provided by the nanoparticles for the absorption of oil as well (Table 6).

Table 6

Comparison with the literature

Sl.No.Name of the authorAchieved efficiency (%)
1 Radin Mohamed et al. (2014)  75 
2 Pandey et al. (2020)  72 
3 Mishra & Bajpai (2006)  75.71 
4 Kumar & Kumar (2021)  93 
5 Vieira et al. (2010)  98 
6 Shak & Wu (2014)  87 
7 Bhatia et al. (2007)  95 
8 Nascimento et al. (2010)  94.8 
9 Present work 99.26 
Sl.No.Name of the authorAchieved efficiency (%)
1 Radin Mohamed et al. (2014)  75 
2 Pandey et al. (2020)  72 
3 Mishra & Bajpai (2006)  75.71 
4 Kumar & Kumar (2021)  93 
5 Vieira et al. (2010)  98 
6 Shak & Wu (2014)  87 
7 Bhatia et al. (2007)  95 
8 Nascimento et al. (2010)  94.8 
9 Present work 99.26 
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This research has delved into the vital realm of oil–water emulsion separation with the primary objective of optimising the efficiency of this process. Through a systematic exploration of coagulation dynamics, coagulant dosage, and various oil concentrations, we have made significant strides towards a more effective and environmental friendly approach to this critical industrial challenge.

The production and utilisation of superparamagnetic chitosan hybrid nanoparticles have proven to be a promising avenue in overcoming existing limitations within oil–water separation technology. The findings of our study have far-reaching implications, with several key takeaways:

  • Optimal conditions: We have successfully identified optimal conditions for oil–water separation, including a 30-min separation time and a 10 mL of coagulant dosage. These parameters can serve as valuable benchmarks for industrial applications, ensuring efficient and cost-effective separation processes.

  • High separation efficiency: The study has demonstrated that under these optimal conditions, the separation efficiency can exceed 99%, particularly for emulsions with higher oil concentrations. This high efficiency is a testament to the potential of superparamagnetic chitosan hybrid nanoparticles in addressing the challenges of oil–water separation.

  • Broad applicability: While our research focused on specific parameters, the principles underlying the use of superparamagnetic chitosan particles can be applied to a wide range of emulsion compositions as illustrated by the presence of ferrous ions Fe2+ and Fe3+ in the coagulant, examined by XRD analysis and paramagnetic property justified by the VSM test. This adaptability enhances the versatility of our findings in diverse industrial contexts.

  • The study has also revealed a significant trend: as we reduced the size of the particles to an average particle size of 99.43 d.nm, we observed a consistent and notable increase in efficiency. This finding underscores the critical role of particle size in determining the effectiveness of the process under investigation. As we continue to refine our understanding of particle dynamics, we open up exciting possibilities for improving performance and achieving higher levels of efficiency in various applications.

  • Environmental benefits: The use of superparamagnetic chitosan hybrid nanoparticles aligns with environmentally conscious practices. Their efficiency in separating oil from water reduces the environmental impact of industrial processes, contributing to sustainability goals.

  • Future prospects: While our study has made significant strides, there remain avenues for further research. Exploring the behaviour of magnetic coagulants under various environmental conditions, assessing their long-term stability, and evaluating their cost-effectiveness in large-scale applications are areas that warrant continued investigation.

In essence, the development and application of superparamagnetic chitosan hybrid nanoparticles represent a promising advancement in the field of oil–water emulsion separation. By addressing existing challenges and offering efficient, environmental friendly solutions, our research contributes to the enhancement of industrial processes while aligning with sustainability objectives. As we move forward, it is our hope that this work serves as a foundation for further innovation and the development of practical solutions for oil–water separation on a global scale.

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S.S.M. ideologically generated the ideas; A.K.B. and S.C.T. contributed in experimentation, data collection, visualisation, drafting the visualised results, and revising the manuscript. A.S. contributed in proofreading and giving valuable comments. This study was done under the supervision of S.S.M.

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All the authors have checked and agreed to publish this manuscript into Water Practice & Technology.

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The authors are well aware and sure that the used data in this study are not previously published.

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All relevant data are included in the paper or its Supplementary Information.

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The authors declare there is no conflict.

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