Green-Synthesized Iron Oxide-Chitosan Nanocomposite for Chromium and Nanoplastics Remediation

Green-Synthesized Iron Oxide-Chitosan Nanocomposite for Chromium and Nanoplastics Remediation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Green-Synthesized Iron Oxide-Chitosan Nanocomposite for Chromium and Nanoplastics Remediation Shouvik Mahanty, Gopala Krishna Darbha, Richard Paul, Ramin Boroujerdi, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7609084/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract This study presents the eco-friendly synthesis and application of iron oxide nanoparticles (IO-NPs) and a chitosan-based iron oxide nanocomposite (IO-NPs+C) for removing chromium (Cr) ions and nanoplastics (NPs) from contaminated water. For the first time, Aspergillus iranicus, a fungal isolate from the Indian Sundarbans mangrove ecosystem, was employed for the green synthesis of superparamagnetic iron oxide nanoparticles (SPIONs), aligning with sustainable chemistry principles. TEM and XRD analyses confirmed their spherical morphology and size range of 10–50 nm. The nanocomposite exhibited significantly enhanced adsorption efficiency compared to IO-NPs alone, achieving equilibrium capacities of 195.20 mg/g (Cr) and 190.50 mg/g (NPs) under optimal conditions (pH 2, 35°C, 100 mg/L dosage, 120 min contact). Langmuir isotherm fitting suggested monolayer adsorption, with maximum capacities exceeding 500 mg/g (Cr) and 250 mg/g (NPs). Process optimization through Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) revealed a highly efficient removal (92.68% Cr and 97.89% NPs) at optimized conditions of 99.98 mg/L IO-NPs+C, pH 6.8, and 35°C. Field validation using groundwater near a Chromite Ore Processing Residue (COPR) site (Cr: 12.68 ± 1.2 mg/L, spiked NPs: 20 mg/L) showed 93.39% removal of both contaminants with 100 mg/L of IO-NPs+C at pH 7.6 and 313 K within 120 minutes. The IO-NPs+C outperformed IO-NPs alone, establishing its promise as a sustainable and high-performance solution for simultaneous Cr and NP remediation in wastewater treatment. Nanocomposite Adsorption Chromium Nanoplastics Bioremediation Iron oxide Fungi Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Highlights • Fungal-synthesized IO-NPs and IO-NPs + C used for water purification • Nanocomposite showed high adsorption for chromium and nanoplastics • Adsorption followed Langmuir model with Qmax > 500 mg/g for Cr • ANN and RSM models optimized adsorption conditions effectively • Groundwater treatment showed > 93% pollutant removal in real scenario 1.0 Introduction Environmental ecosystems and human health are seriously threatened by the growing problem of plastic waste and the poisonous heavy metals like chromium (Cr) ions that are contaminating water sources. [ 1 , 2 ]. Microplastics (MPs) and nanoplastics (NPs), which are produced when these plastic wastes break down, enter aquatic ecosystems and are easily consumed by marine life [ 3 ]. These particles not only disrupt marine life but also initiates biomagnification, transferring these contaminants through the food web and ultimately affecting humans which leads to reproductive, developmental, and long-term health risks [ 4 ]. Cr ions are released as toxic byproducts of various industrial activities, posing serious health risks that can range from breathing difficulties to cancer with long-term exposure. [ 5 ]. The simultaneous presence of MPs, NPs and Cr ions in water needs urgent, multifaceted strategies to curb their combined threats to both human health and environmental sustainability. Conventional remediation approaches, including filtration, coagulation, and chemical precipitation, frequently prove insufficient, particularly against nanoparticles that evade traditional filtration systems due to their nanoscale dimensions. [ 6 ]. In this context, adsorption has gained prominence as a promising remediation strategy, exploiting the surface characteristics of adsorbent materials to effectively capture and immobilize contaminants.[ 7 ]. Unlike conventional techniques, adsorption demonstrates superior efficiency, particularly for challenging pollutants such as MPs, NPs and Cr ions positioning it at the forefront of advanced water purification technologies [ 6 , 7 ]. Recent studies have highlighted different adsorbing materials e.g activated carbon, biochar, and metal oxides, with iron oxide nanoparticles (IO-NPs) emerging as an effective adsorbing material due to their high surface-to-volume ratio which has enhance reactivity, and strong affinity for both organic and inorganic contaminants. [ 8 ]. IO-NPs hold strong potential to simultaneously capture NPs and Cr ions, underscoring their versatility as a auspicious approach to address complex water pollution challenges [ 9 ]. Building on this potential, the development of IO-NP–chitosan composites (IO-NPs + C) introduce a novel strategy to further enhance adsorption efficiency [ 10 – 12 ]. This approach uses the physicochemical advantages of IO-NPs together with the functionality of chitosan (C), a natural biopolymer widely known for its biocompatibility and abundance. While conventional IO-NP synthesis often relies on chemical reduction or physical deposition, green synthesis methods present a more sustainable alternative. By employing biological agents such as plant extracts, bacteria, or fungi to reduce metal ions under mild conditions, green synthesis not only minimizes environmental impact but also tends to produce nanoparticles with improved stability and biocompatibility [ 13 ]. Fungi, found in the extreme mangrove habitat of Indian Sundarbans can play a significant role in the green synthesis of the nanomaterial [ 14 ]. These mangrove habitats are characterized by high salinity, anoxic conditions, shifting pH, and heavy metal contamination, exerting significant environmental stress of the fungal metabolism. As a result, manglicolous fungi in this region have evolved specialized metabolic pathways that enable them to withstand these harsh conditions [ 15 – 21 ]. The extracellular enzyme secreted from these fungi can catalyse the production of IO-NPs with highly desirable properties, such as optimal size, shape, and surface reactivity, making them especially suited for environmental applications [ 18 – 21 ]. In this approach, the IO-NPs are incorporated with chitosan, also derived from fungi. Compared to traditional chitosan sourced from the shells of the crustacean organism, fungal derived chitosan delivers a sustainable, animal-free alternative with similar pollutant-binding properties [ 22 ]. This fungal-sourced chitosan is rich in amine and hydroxyl groups that can form strong interactions with pollutants such as MPs and Cr ions which significantly enhance the composite's adsorption capacity [ 23 – 25 ]. By employing fungi to produce both IO-NPs and C, this dual-fungal approach creates a composite material with remarkable synergy [ 21 , 22 ]. The IO-NPs offer an extensive surface area that enhances pollutant adsorption [ 19 ], while the chitosan matrix provides structural stability and abundant active sites for binding contaminants [ 24 ]. Furthermore, the magnetic properties of IO-NPs allow the overall composite material to be easily separated from water matrix using a magnetism field, makes it particularly practical for large-scale water treatment applications [ 18 , 19 ]. This project was designed to thoroughly evaluate and optimize a composite material made from IO-NPs and IO-NPs + C for real-world water treatment applications. The IO-NPs were synthesized using fungal extracts, and chitosan obtained from the same fungal source was incorporated to create a fully biogenic composite. Batch adsorption tests were performed to determine how effectively the composite could remove NPs and Cr ions under a range of environmental conditions, including variations in pH, temperature, and competing ions. These experiments provided a realistic assessment of the composite’s performance and helped clarify its behaviour under diverse water contamination scenarios. To fine-tune the adsorption process, advanced optimization methods such as Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) were applied to identify the conditions that maximize pollutant removal. By using the same fungi to produce both the nanoparticles and chitosan, this dual-fungal strategy creates a highly synergistic and sustainable material capable of tackling two major water pollutants simultaneously. The resulting IO-NPs + C composite not only demonstrates significant potential for eco-friendly water purification but also offers a framework for broader environmental remediation applications. The findings of this research provide a pathway toward more effective pollution control strategies, helping to secure cleaner water resources and promote long-term ecosystem health. 2.0 Material & methods 2.1 Reagents For the study analytical-grade iron (III) nitrate [Fe (NO 3 ) 3 ] and ICP-grade chromium standard solution (1000 mg/L) of Cr was procured from Sigma-Aldrich. For fungal isolation, Potato Dextrose Agar (PDA), was obtained from Hi-Media, India. Hydrophilic polystyrene latex beads, surface-coated with an anionic surfactant (FluoSpheres™ Carboxylate-Modified Microspheres 0.1 µm) were considered as model particles to simulate naturally occurring NPs in aquatic environments. This selection is based on the understanding that primary plastics in aquatic systems undergo abiotic degradation, leading to the formation of more hydrophilic secondary forms due to the generation of carbonyl (C = O) functional groups [ 26 ]. The NPs were acquired from Sigma-Aldrich, USA. Other reagents which were used in the study, were of analytical grade, included sodium chloride (NaCl), sodium sulfate (Na 2 SO 4 ), sodium nitrate (NaNO 3 ), sodium hydroxide (NaOH), hydrochloric acid (HCl), sodium bicarbonate (NaHCO 3 ), and Humic acid sodium salt from Sigma-Aldrich. The majority of these chemicals were sourced from Merck, India. All solutions were prepared using deionized water to maintain experimental consistency and purity. 2.2 Sampling location for the sediment samples A sediment from the rhizosphere region was obtained from a depth of 10–15 cm near Nypa fruticans trees lies in the intertidal mangrove zone of Satjelia Island (22° 7'4.05"N, 88°52'23.17"E) in the eastern Indian Sundarbans (Supplementary Fig S1 ) . The sediment collection was performed under sterile conditions to prevent contamination, and the sample was securely sealed in a sterile zip-lock pouch. It was then transported to the laboratory in a temperature-controlled container to maintain sample integrity for subsequent fungal isolation. 2.3 Isolation of manglicolous fungi and green synthesis of IO-NPs and IO-NPs + C Rhizospheric sediments collected from Nypa fruticans in the intertidal mangrove zone were serially diluted up to 10⁻⁴ and inoculated onto modified Potato Dextrose Agar (PDA) plates. To prevent bacterial contamination, chloramphenicol (100 µg/ml) was added, and the pH was adjusted to 5.2 ± 0.02. The plates were incubated at 27°C ± 2°C for 72 hours. Fungal isolates were identified morphologically by applying slide culture techniques and lactophenol cotton blue staining, followed by subculturing for further characterization [ 20 , 21 ]. Fungal cultures were grown in 100 ml Potato Dextrose Broth (PDB) at temperature 27°C ± 2°C for 360 hours. After cultivation, the fungal cell-free filtrate (FCF) was collected using filtration and centrifugation. For nanoparticle synthesis, 9.7 ml of FCF was mixed with 0.3 ml of 3 mM iron (III) nitrate, adjusting the pH to 3.0 ± 0.02. A rapid change in the ocular properties of the mixture signifies nanoparticle formation, which was monitored for 60 minutes using UV-Vis spectroscopy [ 19 ]. Chitosan extraction from fungal mycelia was performed in triplicate, using a method modified from Azeez et al. [ 28 ] and John Kasongo et al. [ 27 ]. Initial deproteinization involved mixing the fungal mycelium with NaOH solution (90°C) at 250 rpm for 2.5 hours using the shaking incubator. The mixture was filtered, washed until neutral in pH, rinsed with acetone, and dried at 105°C to assess biomass yield. Acid extraction followed, where 16 g of deproteinized biomass was incubated in acetic acid at 60°C under reflux for 6 hours. After centrifugation, acid-soluble chitosan was precipitated at pH 8–9 and dried. To deacetylate chitosan, 20 g of the biomass was treated with NaOH at 120°C for 2.5 hours under reflux. The mixture was filtered, washed to neutral pH, rinsed with acetone, and dried. Purification involved dissolving 1 g of chitosan in acetic acid, filtering to remove insoluble particles, neutralizing the solution, precipitating at 4°C, and drying for further analysis. The protocols for preparing the iron-chitosan composite (IO-NPs + C) were adapted from Elnouby et al., [ 35 ] and Zemskova et al., [ 34 ]. In this method, chitosan powder was dissolved in 1–2% acetic acid to form a uniform, viscous solution. The synthesised iron oxide nanoparticles were separately dispersed in distilled water, and ultrasonication was employed to ensure even distribution. The nanoparticle suspension was then gradually added to the chitosan solution under constant stirring to promote interaction between the iron oxide and chitosan. For improved stability, a cross-linking agent such as glutaraldehyde was introduced in minimal amounts. To facilitate the precipitation of the iron-chitosan composite, the pH was adjusted using 0.1 M NaOH. Once precipitated, the composite was filtered, thoroughly washed with distilled water, and dried in a vacuum oven at 50°C. The dried composite was then ground into a fine powder. The nanoparticles were subsequently purified by centrifugation at 14,000 rpm for 10 minutes, re-dispersed in Milli-Q water, and subjected to ultrasonication for 45 minutes. This procedure was repeated three times to ensure the homogeneity of the nanoparticle suspension ( Fig. 1 ) . Control experiments included FCF without iron nitrate (positive control) and iron nitrate without FCF (negative control). Molecular identification of fungal strains confirmed their involvement in iron nanoparticle synthesis and the formation of the iron-chitosan composite. 2.4 Molecular identification of fungal isolates Fungal DNA was extracted and purified using the HiPurATM Plant Genomic Miniprep Kit (HiMedia MB507), and its quality was assessed through 1.2% agarose gel electrophoresis. To amplify ribosomal DNA, primers targeting the internal transcribed spacer (ITS) region were used, based on the method outlined by White et al. [ 29 ], with amplification performed on a VeritiTM thermal cycler (Thermo Fisher Scientific). PCR products were purified and subjected to Sanger sequencing using an ABI 3730xl Genetic Analyzer (Thermo Fisher Scientific). The forward and reverse sequences were aligned using BioEdit v7 to generate a consensus sequence. Fungal species identification was accomplished by submitting the consensus sequence to the NCBI BLAST (Basic Local Alignment Search Tool). The ITS sequence was also deposited into the NCBI GenBank via BankIt for validation and to obtain an accession number. 2.5 Physical and Chemical Characterization of Nanoparticles A range of advanced analytical techniques was employed to comprehensively assess the characteristics of the synthesized nanoparticles (IO-NPs and IO-NPs + C), focusing on their stability in aqueous media, magnetic properties, elemental composition, and crystalline structure ( Fig. 2 , 3 and Supplementary Fig S2) . The synthesised nanoparticles were monitored using a PerkinElmer Lambda 35 UV-Vis spectrophotometer, with measurements taken across wavelengths of 200–700 nm. Following a 30-minute sonication of the nanoparticle suspension (Biobase UC20A sonicator), the zeta potential was measured using a Zetasizer (Zen 1600, Malvern Instruments, USA). For Fourier Transform Infrared Spectroscopy (FTIR) analysis, the nanoparticles were lyophilized (Biobase BK-FD10PT) and combined with potassium bromide (KBr) in a 1:100 ratio. The resulting pellet was then analysed in Attenuated Total Reflection (ATR) mode, with infrared spectra captured in the range of 3500 to 500 cm − 1 at a resolution of 4 cm − 1 using a Jasco FT/IR-6300. Morphological and elemental characterization was performed on 5 mg of lyophilized IO-NPs using Field Emission Scanning Electron Microscopy (FESEM) (JEOL JSM-7600F) at an operating voltage of 15–25 kV, complemented by Energy Dispersive X-ray Spectroscopy (EDX) (Oxford Instruments, INCA PENTA FET X3). Transmission Electron Microscopy (TEM) (JEOL TEM 2100 HR), coupled with EDX for elemental composition analysis, was conducted on a 10 µL sample of the nanoparticle suspension, placed on a carbon-coated copper grid for examination. Crystallographic properties were analyzed through X-ray Powder Diffraction (XRD) using a Philips PW1830 instrument. The diffraction data were collected in 2θ mode, spanning angles from 10° to 80° with a 0.02° step size, using Cu Kα radiation (λ = 1.542 Å) at 40 kV and 30 mA. This analysis provided key insights into the interplanar spacings and intensities, enabling the identification of diffraction peaks for IO-NPs, which were compared against theoretical standards provided by the Joint Committee on Powder Diffraction Standards-International Centre for Diffraction Data (JCPDS-ICDD). Finally, the magnetic properties of the IO-NPs were evaluated using a Superconducting Quantum Interference Device (SQUID) vibrating sample magnetometer (VSM) from Quantum Design. 2.6 Sorption Studies A series of sorption experiments were performed to assess the adsorption efficiency of IO-NPs and IO-NPs + C for nanoparticles (NPs) and chromium (Cr) ions. Stock solutions of 500 mg/L for both NPs and Cr ions were prepared in deionized water (DI). In each experiment, varying concentrations (20–120 mg/L) of IO-NPs and IO-NPs + C were added to 50 mL conical flasks containing 20 mg/L solutions of NPs and Cr ions. The materials were compared to determine their sorption capacities, with initial experiments focused on identifying the optimal adsorbent for subsequent studies. The mixtures were vortexed for 120 minutes to ensure thorough interaction between the adsorbents and pollutants, followed by centrifugation at 2500 rpm for 3 minutes. The supernatant was then carefully extracted, and NPs were quantified using fluorescence spectrometry (Horiba FluoroMax Plus) at an excitation wavelength of 525 nm. Chromium ion concentrations were measured using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). To examine the influence of environmental factors on adsorption performance, various parameters were adjusted, including pH, the presence of competing ions, contact time, initial pollutant concentrations, and varying humic acid concentrations. All experiments were conducted at room temperature (35°C) with consistent pollutant concentrations (20 mg/L), solution volumes (50 mL), and adsorbent masses (100 mg/L). Kinetic studies were carried out by varying the contact times between 0 and 120 minutes, while isotherm experiments evaluated increasing NP and Cr ion concentrations up to 60 mg/L. The adsorption capacity (q) for both NPs and Cr ions was calculated using the equation: q = (C 0 − C e ) ×V/m, % Removal = (C 0 − C e ) / C 0 × 100 where "q" represents the adsorption capacity (mg/g), C 0 and C e are the initial and final concentrations of the pollutants (NPs or Cr ions) in solution (mg/L), "V" is the volume of the solution (mL), and "m" is the mass of the adsorbent (mg). The experimental data were analysed using linear kinetic models, specifically the pseudo-first-order and pseudo-second-order models, to understand the adsorption kinetics. For isotherm analyses, both the Langmuir and Freundlich models were employed to evaluate the adsorption behaviour. The effect of temperature on the sorption process was also examined by conducting experiments at three different temperatures: 15°C (288 K), 25°C (298 K), and 35°C (308 K). Thermodynamic parameters were calculated to provide insights into the adsorption mechanism and its spontaneity. A detailed description of the kinetic, isotherm, and thermodynamic models is presented in Supplementary Table S1 . 2.7 RSM and ANN analysis of the adsorption process The adsorption process was analysed using RSM to model the relationships between four key independent variables: adsorbent dose (mg/L), pH, temperature (°C), and time. A quadratic polynomial equation was used to describe these interactions, with further details provided in the supplementary section (Table I) . Optimal experimental conditions were determined using Derringer’s desirability function and following methods from our previous publications [ 18 , 21 ]. The specific ranges for each variable are detailed in the supplementary section, and the software generated 30 experimental runs, with the actual and predicted outcomes presented in Supplementary Table S2-S4 . Additionally, an ANN model was implemented to predict the percentage removal of heavy metals during the adsorption process. The computational framework for ANN modelling, along with the predicted vs actual graphical plot of the experimental data and R 2 obtained from the algorithmic model are described in supplementary section (Supplementary Table S5) . 2.8 Statistical Analysis of Adsorption Data All experiments were performed in triplicate, with the results reported as the mean ± standard deviation. Data analysis was conducted using Origin software (Version 9.1; OriginLab Corporation) and Microsoft Excel 2022. Statistical significance was evaluated through ANOVA using Design Expert (Version 7.0, Minneapolis, USA) and MATLAB (Version 7.0.1, The MathWorks Inc.). 3.0 Results and discussion 3.1 Mechanism of IO-NPs and IO-NPs + C formation using fungal isolates Fungal strains isolated from the rhizospheric sediment of Nypa fruticans were analyzed for colony morphology, including characteristics such as form, edge and elevation. Identification at the genus level was performed by examining the structures of conidiophores and conidia using taxonomic keys [ 30 ], as demonstrated in Fig. 1 . The fungal cell-free filtrate (FCF) from 15 isolates as screened for its ability to synthesize nanoparticles using a Fe (NO 3 ) 3 solution. Among these, strain STSP9, identified as Aspergillus sp., exhibited rapid nanoparticle synthesis by reducing the iron salt solution within 5 minutes at 30°C ± 2°C. In contrast, the control experiment conducted in the absence of the fungal culture did not show any reduction, confirming the essential role of Aspergillus sp. in the nanoparticle synthesis process. Following nanoparticle formation, chitosan was extracted from STSP9 and integrated with the iron oxide nanoparticles (IO-NPs) to create a composite referred to as IO-NPs + C. The synthesis and assembly of the IO-NPs and the IO-NPs + C composite occurred in multiple stages ( Fig. 1 ) . In step I, NADH reductase initiated the reduction of the iron precursor salt, releasing Fe 3+ and NO 3 − ions [ 31 ]. In step II, Fe 3+ ions interacted with fungal extracellular proteins, leading to the formation of stable organic Fe (III) complexes [ 32 ]. In step III, hydrolysis of these Fe (III) complexes resulted in the formation of Fe(OH) 3 , which nucleated into Fe 2 O 3 nanocrystals that precipitated as iron oxide nanoparticles [ 33 ]. Step IV involved the formation of the IO-NPs + C, where chitosan served as a stabilizing and matrix-forming agent. Chitosan, a natural polysaccharide derived from chitin, was dissolved in 1–2% acetic acid, forming a homogeneous, viscous solution [ 34 , 35 ]. This acidic environment protonated the amine groups of chitosan, causing it to become positively charged and promoting solubility in the aqueous phase. In parallel, the synthesized iron oxide nanoparticles were suspended in distilled water and subjected to ultrasonication to ensure uniform particle distribution, preventing agglomeration. The chitosan solution and the iron oxide nanoparticle suspension were gradually combined under continuous stirring. The strong electrostatic attraction between the negatively charged iron oxide nanoparticles and the positively charged protonated chitosan allowed for efficient interaction and encapsulation of the nanoparticles within the polymer matrix [ 36 ]. This interaction facilitated the uniform dispersion of iron oxide nanoparticles throughout the chitosan matrix, forming a stable composite material [ 37 ]. To further enhance the mechanical strength and stability of the composite glutaraldehyde was introduced in minimal quantities as a cross-linking agent [ 38 ]. Glutaraldehyde forms covalent bonds between the amine groups of chitosan, leading to the formation of a three-dimensional network that reinforces the structural integrity of the composite. This cross-linking process is essential for preventing the premature release of nanoparticles from the chitosan matrix. The pH of the solution was then carefully adjusted using 0.1 M NaOH. This step was critical, as the alkaline conditions promoted the deprotonation of chitosan's amine groups, leading to the precipitation of the iron-chitosan composite [ 24 ]. In this process, the chitosan acts as a scaffold, providing a biocompatible matrix that stabilizes the iron oxide nanoparticles. For spectral analysis, the fungal cell-free filtrate (FCF) served as the positive control, while the iron precursor solution was used as the negative control, showing no significant spectral shift. Strain STSP9 was identified at the species level by sequencing the ITS region, producing a 546 bp sequence with high similarity to Aspergillus iranicus , confirmed via BLAST analysis. This sequence was deposited in the NCBI database under accession number MH824157. 3.2 Physical and chemical characterization of the nanoparticles and the nanocomposite The characterization of IO-NPs and IO-NPs + C employs a suite of advanced analytical techniques to elucidate their structural, chemical, and magnetic properties ( Figs. 2 , 3 and Supplementary Fig S2) . UV-Vis spectroscopy typically shows a distinct absorption peak in the range of 200–400 nm, attributed to surface plasmon resonance (SPR), indicating the formation of nanoparticles and their size-dependent optical characteristics. The IONPs + C emonstrates slight redshifts or variations in peak intensity, suggesting interactions between the chitosan matrix and the nanoparticles that may affect particle size or surface charge [ 39 , 40 , 16 ]. FTIR spectroscopy provides insights into functional groups ( Fig. 3 ) , with the strong Fe-O bond absorption band appearing between 580–630 cm − 1 , indicative of hematite (Fe 3 O 4 ) or maghemite (γ-Fe 2 O 3 ). The composite reveals additional peaks related to chitosan, notably broad bands around 3200–3500 cm − 1 for hydroxyl (–OH) and amino (–NH₂) group vibrations, alongside amide I and II peaks between 1650 − 1560 cm − 1 , confirming chitosan's coordination with iron oxide. Other notable peaks at 830 cm − 1 , 1072–1074 cm − 1 , 1394–1396 cm − 1 , 1510–1512 cm − 1 , and 3119–3144 cm − 1 correspond to C = O, O–H, N–O, and C–H groups, respectively [ 16 , 18 , 19 , 39 – 42 ]. XRD patterns indicate ( Fig. 3 ) the crystalline nature of IONPs, matching the rhombohedral structure of hematite (Fe 2 O 3 ) as per JCPDS No. 24–0072, with characteristic peaks in the regions (012), (104), (110), (113), (024), (116), (122), (214), and (300). Peak broadening signifies the formation of nanoscale crystallites ranging from 2–20 nm, estimated using the Scherrer equation, while the presence of diffuse scattering in the composite reflects the amorphous nature of chitosan, preserving the crystalline structure of iron oxide[ 21 , 43 , 44 ]. Magnetic characterization via SQUID-VSM magnetometry reveals superparamagnetic behaviour of IO-NPs and IO-NPs + C at room temperature, with saturation magnetization (Ms) values between 2–8 emu/g, substantially lower than the bulk magnetite value of ~ 90 emu/g. This decrease is attributed to surface spin disorder from unsaturated surface iron coordination, finite size effects leading to a single magnetic domain structure, and the influence of the chitosan matrix, which spatially separates the nanoparticles, further attenuating their magnetic interactions [ 16 , 20 , 21 , 45 – 47 ]. The M-H curves, measured within a field range of ± 6 T, demonstrate the absence of coercivity (Hc ≈ 0 Oe) and remanence (Mr ≈ 0 emu/g), affirming that the nanoparticles' magnetic moments can swiftly realign with an applied field without residual magnetization. FESEM provides high-resolution imaging of particle morphology (Supplementary Fig S2) , showing pure IO-NPs as spherical or quasi-spherical particles with diameters of 10–30 nm. In the chitosan composite, nanoparticles are uniformly distributed, appearing as discrete, embedded entities within a smooth chitosan matrix. EDX mapping confirms the elemental composition, with prominent signals for Fe and O from IO-NPs and C and N from chitosan, while elemental mapping indicates a homogenous distribution of iron throughout the composite, demonstrating successful integration s[ 16 , 20 , 21 , 48 – 50 ]. TEM reveals uniform particle sizes, typically 5–15 nm ( Figs. 2 a and 2 b (i−iv) ) , with high-resolution images displaying lattice fringes corresponding to specific crystallographic planes, thus affirming the nanoparticles' high crystallinity. In the chitosan composite, TEM indicates encapsulation or coating of IO-NPs by the chitosan, often forming a core-shell structure with the polymer layer manifesting as a thin, amorphous coating around the nanoparticles, confirming effective surface modification and interaction [ 21 , 51 ]. 3.3 Batch adsorption study The batch adsorption study of NPs and Cr ions onto IO-NPs and IO-NPs + C reveals complex adsorption kinetics and thermodynamics, which contribute to improved pollutant removal efficiencies ( Fig. 4 a-d ) . At an initial adsorbate concentration of 20 mg/L and an adsorbent dosage of 100 mg/L, the equilibrium adsorption capacities (q e ) were calculated to be 191 ± 3.11 mg/g for Cr and 177.8 ± 3.6 mg/g for NPs on IO-NPs. Interestingly, the IO-NPs + C demonstrated even greater adsorption capacities, with q e values of 195.20 ± 3.33 mg/g for Cr and 190.50 ± 3.59 mg/g for NPs. Kinetic studies revealed rapid adsorption in the first 30 minutes of the 120-minute process, suggesting that the surface of the adsorbents possessed high affinity and an abundance of active sites in the early stages. As the process advanced, a slower rate of adsorption was observed as these sites became saturated, indicating a transition to a diffusion-controlled mechanism, where intraparticle diffusion becomes the dominant factor. This is particularly noticeable in IO-NPs + C, likely due to the additional binding sites provided by chitosan [ 51 – 53 ]. The study also examined the effect of adsorbent concentration, ranging from 20 to 120 mg/L, and found that optimal adsorption occurred at 100 mg/L (Fig. 4 a, b and c ). This concentration represents the ideal balance between adsorbate molecules and available active sites, preventing oversaturation and maintaining efficient surface interactions. Furthermore, the adsorption process was found to be highly pH-dependent, with maximum efficiency achieved at pH 2. Under acidic conditions, the surfaces of IO-NPs and IO-NPs + C are protonated, which enhances electrostatic attraction between the positively charged surface and the negatively charged Cr ions and NPs. As the pH increased, zeta potential analyses revealed that NPs maintained a stable negative charge (-20 to -64 mV), while the surface charge of IO-NPs and IO-NPs + C shifted from positive to neutral, slightly negative, near neutral pH levels (Fig. 4 d). This behaviour aligns with the point of zero charge (PZC) of the adsorbents, confirming that the adsorption efficiency diminishes as surface charge neutrality is approached, reducing electrostatic interactions [ 54 , 55 ]. Overall, both IO-NPs and IO-NPs + C are highly effective in capturing Cr ions and NPs, with IO-NPs + C exhibiting superior adsorption capacity. The enhanced performance of IO-NPs + C is attributed to the synergistic properties of chitosan, which not only increases surface area but also offers additional binding sites for adsorbates [ 56 , 57 ]. This makes the composite particularly suited for applications in water purification and pollutant removal. 3.4 Effect of common ions and humic acid on adsorption of NPs and Cr on IO-NPs and IO-NPs + C The effect of common ions and humic acid on the adsorption of NPs and Cr ions using IO-NPs and IO-NPs + C was thoroughly investigated at an adsorbent concentration of 100 mg/L, with an initial adsorbate concentration of 20 mg/L, over a contact time of 120 minutes ( Fig. 5 a-d ) . The results indicated that the presence of common ions had varying impacts on the adsorption capacity, with most anions exhibiting negligible effects. Notably, bicarbonate (HCO 3 − ) demonstrated a pronounced influence; at a concentration of 5 mM, the removal efficiency for both NPs and Cr ions decreased by approximately 60%. This significant decline can be attributed to HCO₃⁻ acting as a buffer, which raises the pH from 5.5 to approximately 8.6, enhancing the negative charge on the adsorbent surface and resulting in electrostatic repulsion of negatively charged species like NPs. In contrast, other common ions (such as chloride, nitrate, and sulphate) induced only minor reductions in adsorption capacity, typically around 5–10%. This limited effect can be explained by the relatively weak binding affinity of these ions to the IO-NPs and IO-NPs + C, which does not substantially compete with the adsorption sites available for NPs and Cr ions. The observed minor decrease in removal efficiency suggests that these anions may possess a lower affinity for the IO-NPs and IO-NPs + C. Furthermore, the influence of humic acid concentrations on adsorption was assessed, revealing a significant decrease in removal efficiency. Even at a low concentration of 1 mg/L of humic acid, a reduction in removal percentage of 55–75% was recorded. This decline in adsorption capacity is attributed to the steric hindrances imposed by humic acid, which interferes with the effective aggregation and sedimentation of nanoparticles. The DLVO theory elucidates this phenomenon by suggesting that the presence of humic acid alters the interparticle interactions, increasing repulsive forces between the particles, thereby limiting their co-settling ratios [ 26 ]. Additionally, the stabilizing effect of humic acid on negatively charged IONPs and IO-NPs + C was confirmed by zeta potential measurements. The introduction of 1 mg/L of humic acid caused the zeta potential of IONPs and IO-NPs + C to shift from a neutral value of approximately + 2.85 mV to a significantly negative value of -20 mV. As humic acid concentration increased, the zeta potential became more negative, indicating enhanced stabilization and electrostatic repulsion between nanoparticles, which further inhibited their ability to adsorb NPs and Cr ions effectively. 3.5 Effect of NaOH on desorption of NPs and Cr ions and the reusability study on IO-NPs and IO-NPs + C The desorption behaviour of NPs and Cr ions was investigated using varying concentrations of NaOH, ranging from 0.1 to 0.3 M (Supplementary Fig S3) . The highest desorption efficiency was observed at 0.3 M NaOH, where the strong alkaline environment significantly enhanced the release of both contaminants from the adsorbent surfaces. The increased ionic strength and higher pH levels associated with 0.3 M NaOH facilitate the disruption of electrostatic interactions and hydrogen bonding between the adsorbates and the adsorbent, thus promoting effective desorption [ 19 ]. In a reusability study, both IO-NPs and IO-NPs + C demonstrated substantial stability, retaining their functionality across five adsorption-desorption cycles. However, a gradual decline in adsorption efficiency was noted, with the removal capacity decreasing to below 80% by the fifth cycle. This decrease can be attributed to potential fouling and loss of active sites on the adsorbent materials after multiple cycles, indicating a need for optimization in regeneration protocols to enhance long-term applicability in environmental remediation processes. 3.6 Thermodynamic and kinetic insights into the adsorptive removal of NPs and Cr ions The adsorption behaviour of NPs and Cr onto IO-NPs and IO-NPs + C was systematically investigated through isotherm and kinetic studies at 288, 298, and 308 K. At 308 K, IO-NPs achieved maximum adsorption capacities q e of 526.31 mg/g for Cr ions and 270.27 mg/g for NPs, while IO-NPs + C exhibited even higher adsorption, reaching 625.12 mg/g for Cr ions and 333.31 mg/g for NPs ( Fig. 6 and Supplementary Fig S4) . The adsorption profiles followed the Freundlich isotherm model, indicative of a heterogeneous surface with varied energy sites and a multilayer adsorption mechanism, suggesting that the adsorption sites on both IO-NPs and IO-NPs + C have differential affinities and capacities for Cr ions and NPs. The Freundlich isotherm ( Fig. 6 a and 6 b ) further implies that the adsorption mechanism is influenced by interactions beyond a simple monolayer saturation, accommodating multilayer adsorption on the uneven surface of the iron oxide nanoparticles and chitosan matrix. The enhanced capacity observed for IO-NPs + C at each temperature suggests that the chitosan component introduces additional active sites, potentially through amine and hydroxyl functional groups, thereby increasing surface heterogeneity and complexation potential [ 58 , 59 ]. Kinetic analyses demonstrated a strong fit with the pseudo-second-order model ( Fig. 6 c and 6 d ) across all temperatures, indicating chemisorption as the primary adsorption mechanism. This is characterized by chemical bonds forming between the adsorbate and active sites on the IO-NPs and IO-NPs + C surfaces, likely through electron exchange or covalent interactions, particularly prominent due to the hydroxyl and amine groups present in chitosan. The temperature dependency observed in the pseudo-second-order kinetics also highlights the activation energy required for chemical bonding, suggesting that elevated temperatures enhance reaction rates by increasing the molecular interactions and mobility of Cr ions and NPs [ 60 ]. Thermodynamic parameters, including Gibbs free energy (ΔG), enthalpy (ΔH) and entropy (ΔS), revealed deeper insights into the adsorption mechanism (Supplementary Fig S4 and Table II) . Negative values of ΔG at each temperature confirm the spontaneous nature of adsorption, while the increasingly negative ΔG with rising temperature supports an endothermic process that becomes more favourable at higher temperatures. This temperature-induced enhancement in spontaneity points to activated complex formation on the IO-NPs and IO-NPs + C surface, likely driven by stronger adsorbate-surface interactions at elevated thermal energy levels. The positive values of ΔS suggest an increase in randomness at the solid-liquid interface, which may reflect enhanced structural rearrangements within the adsorbent’s surface layers, optimizing the binding of Cr ions and NPs and thus improving adsorption efficiency[ 61 ]. 7 Utilization of RSM and ANN for the validation of the batch experimental result for the IO-NPs + C for the NPs and Cr ions adsorption In this study, the superior performance of the IO-NPs + C in batch adsorption experiments was evident when compared to IO-NPs alone. The chitosan matrix contributed additional active functional groups, such as amine and hydroxyl, enhancing surface interactions with Cr ions and NPs. This increased adsorption capacity, along with improved stability and stronger pollutant binding, positioned IO-NPs + C as the preferred adsorbent for further optimization. To explore the complex interaction of adsorption parameters, RSM and ANN were employed for multimeric analysis, providing a rigorous framework for process optimization and predictive modelling. RSM was utilized to assess the interaction effects of key variables—adsorbent dosage, temperature, pH, and contact time—on the adsorption efficiency of IO-NPs + C. The quadratic polynomial model generated by RSM allowed for the evaluation of linear, quadratic, and interaction terms in a systematic manner. Statistical significance was confirmed by the high F-values (p 0.99) was in excellent agreement with the adjusted R 2 , suggesting a robust fit that captured the influence of each factor accurately (Supplementary Table S3 and S4) . The model's adequate precision values exceeded 4, a clear indication of its strong signal-to-noise ratio, while the coefficient of variation (% CV) was below 4%, further confirming the model's precision. Key interactions between variables were mapped using 3D response surface plots, which revealed significant effects of IO-NPs + C dosage and temperature on adsorption efficiency, with a positive correlation between increasing dose and temperature and higher removal rates of both Cr ions and NPs. The interaction between dosage and pH was also significant, highlighting the sensitivity of the adsorption process to changes in solution acidity. Optimal conditions for Cr and NP removal were identified as 99.98 mg/L IO-NPs + C, pH 6.8, and 35°C, under which removal efficiencies of 92.68% for Cr and 97.89% for NPs were achieved (Supplementary Fig S5 and S6) . The RSM model provided a detailed understanding of the influence of both linear and interaction terms, confirming the critical role of adsorbent dose and temperature in driving the adsorption process. Additionally, ANN was employed to model the non-linear relationships between variables that RSM might not fully capture. Using a multi-layer perceptron (MLP) architecture and backpropagation algorithms, the ANN model (Supplementary Fig S7 and Table S5) was trained with experimental input-output data, demonstrating high predictive accuracy. The ANN model accurately predicted adsorption efficiencies with over 98% precision, capturing the complex, non-linear interactions between variables. Error analysis showed low mean squared error (MSE) values, indicating minimal differences between predicted and experimental outcomes. 3.8 Application of the IO-NPs + C in real world scenario The application of IO-NPs + C in real-world groundwater remediation was evaluated using a sample collected from a chromite ore processing residue (COPR)-contaminated site in Uttar Pradesh, India. The groundwater exhibited high total dissolved solids (TDS) of 684 mg/L, a pH of 7.6, and an elevated Cr concentration of 12.68 ± 1.2 mg/L with Cr(VI) concentration of 10.96 ± 1.01 mg/L (Supplementary Table S6) . Additionally, to simulate a worst-case contamination scenario, the sample was spiked with 20 mg/L of NPs before treatment. The remediation process involved treating the contaminated water with 100 mg/L of IO-NPs + C under vigorous stirring at 313 K for 120 minutes, leading to an impressive removal efficiency of 95.22% for the total Cr, 93.39% Cr(VI) ions and 92.91% of NPs (Fig. 5 d). The high efficacy of IO-NPs + C can be attributed to a combination of adsorption, surface complexation, and redox transformation processes facilitated by the iron oxide (IO) core and the biopolymeric chitosan (C) coating. The iron oxide nanoparticles provide abundant active sites for Cr(VI) adsorption via electrostatic interactions and ligand exchange, while Fe²⁺/Fe³⁺ redox pairs within the IO structure promote in situ reduction of Cr(VI) to the less toxic Cr(III). Simultaneously, chitosan enhances pollutant removal through its chelating ability, forming stable complexes with Cr species, and its extensive network of hydroxyl (-OH) and amine (-NH₂) functional groups facilitates the adsorption of both metal ions and nanoplastics. The presence of chitosan also imparts additional stability, preventing nanoparticle aggregation and minimizing secondary pollution by reducing material leaching. Furthermore, nanoplastic removal is facilitated by a combination of hydrophobic interactions, electrostatic attraction, and entrapment within the chitosan matrix, preventing further dispersion in the environment. Importantly, the near-neutral pH of the treated water suggests minimal secondary changes to water chemistry, making IO-NPs + C suitable for field-scale applications. These findings underscore IO-NPs + C as a highly efficient and sustainable nanocomposite for the simultaneous removal of heavy metals and emerging contaminants like NPs from polluted water sources. However, further research is needed to evaluate its long-term stability, regeneration potential, and field-scale applicability under varying environmental conditions. 4.0 Conclusion This study offers significant advancements in the field of nanomaterial-based environmental remediation, particularly in the removal of NPs and Cr ions using mycosynthesized IO-NPs and an IO-NPs + C composite. Employing a green synthesis route through the fungal isolate Aspergillus iranicus , we successfully developed an eco-friendly, scalable methodology that eliminates the need for hazardous chemicals and energy-intensive processes typically involved in conventional nanoparticle synthesis. TEM analysis confirmed the spherical morphology of the particles, with sizes ranging from 10 to 50 nm, while crystallographic studies revealed their high crystallinity and FCC structure. Additionally, magnetic characterization demonstrated their superparamagnetic nature, ensuring ease of recovery after adsorption processes. Batch adsorption experiments revealed the IO-NPs and IO-NPs + C to be highly effective in removing Cr ions and NPs, with maximum adsorption capacities (q e ) exceeding 500 mg/g for Cr ions and 250 mg/g for NPs under pH 2, 35°C, and a contact time of 100 min at an adsorbent concentration of 100 mg/L. The superior performance of IO-NPs + C over IO-NPs was attributed to the additional adsorption sites provided by the chitosan matrix, enhancing pollutant binding through electrostatic and chelation interactions. Adsorption isotherms suggested a monolayer adsorption mechanism with maximum adsorption capacities (Q max ) of more than 500 mg/g for Cr ions and 260 mg/g for NPs. The thermodynamic parameters, indicated that the adsorption process was spontaneous and endothermic, further confirming the feasibility of these composites for real-world applications. Reusability studies demonstrated the robustness of the nanomaterials composite, maintaining its efficiency up to five adsorption-desorption cycles with minimal loss in performance. A major innovation of this study was the integration of computational models such as RSM and ANN to optimize the adsorption process. These models were instrumental in identifying the influence of key variables such as adsorbent dose, pH, temperature, and time on adsorption performance. The predicted optimal conditions (99.98 mg/L IO-NPs + C, pH 6.8, and 35°C) were experimentally validated, with pollutant removal rates of 92.68% for Cr and 97.89% for NPs, showcasing minimal deviation from the predicted values and underscoring the precision of the computational approach. The efficacy of IO-NPs + C was validated by treating groundwater contaminated with Cr and spiked with 20 mg/L of NPs, collected near COPR region. Using 100 mg/L of IO-NPs + C at pH 7.6 and 313 K for 120 minutes, 93.39% of Cr and NPs were removed, confirming the composite's effectiveness in real-world conditions. Overall, this research provides a comprehensive framework for developing sustainable, highly efficient nanomaterials for environmental remediation. The study's combination of green synthesis, advanced characterization, robust adsorption performance, and computational optimization marks a significant step toward the large-scale deployment of these composites in water treatment technologies. The integration of bio-based materials such as chitosan further enhances the environmental compatibility and functional versatility of these composites, setting a new benchmark in the development of eco-friendly nanotechnologies for global pollution challenges. Declarations Acknowledgment: The authors are thankful to IISER Kolkata and SINP Kolkata for various research facilities. Author contribution: SM: Writing – original draft, Methodology, Investigation, Software, Formal analysis, Data curation, Conceptualization, Investigation, Formal analysis, Data curation, Fund acquisition; GKD: Writing – review & editing; RP: Writing – review & editing; RB: Writing – review & editing; EVJ: Writing – review & editing; SM(Majumder): Writing – review & editing. Funding: S. Mahanty thanks Science & Engineering Research Board (SERB) for providing the fellowship of National Post Doctoral Fellowship (Sanction Number: PDF/2023/001221) during the tenure of this research and Department of Atomic Energy (DAE) (Letter No. SINP/Estt. /B&SG/Appt./2022) for providing the Research Associate fellowship. Data availability: All the data present in the manuscript and its associated supplementary file. Ethics Approval: Not applicable. Research Involving Humans and Animals Statement: None. Informed Consent: None. Conflict of interest: The authors declare no competing interests. References Adeleye, A. T., Bahar, M. M., Megharaj, M., Fang, C., & Rahman, M. M. (2024). The Unseen Threat of the Synergistic Effects of Microplastics and Heavy Metals in Aquatic Environments: A Critical Review. Current Pollution Reports , 10 (3), 478–497. https://doi.org/10.1007/S40726-024-00298-7/TABLES/3 Ghosh, S., Das, R., Bakshi, M., Mahanty, S., & Chaudhuri, P. (2021). 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Langmuir: the ACS journal of surfaces and colloids , 37 (10), 3189–3201. https://doi.org/10.1021/ACS.LANGMUIR.1C00142 Sahmoune, M. N. (2019). Evaluation of thermodynamic parameters for adsorption of heavy metals by green adsorbents. Environmental Chemistry Letters , 17 (2), 697–704. https://doi.org/10.1007/S10311-018-00819-Z/TABLES/1 Tables Table I: The numeric factors and the values of different points used in the study Variables Symbol Units Factorial points Axial points -1 +1 + a - a Adsorbent Concentration A mg/L 50 100 25 125 Temp B °C 15 35 5 45 pH C 3 8 0.5 10.5 time D min 60 120 30 150 Table II: Comparative analysis of the thermodynamic parameters for the adsorption of NPs and Cr ions by mycosynthesized IO-NPs and IO-NPs+C Adsorbent Heavy metals Temperature (K) Δ G 0 (KJ/mol) ΔH (KJ/mol) ΔS (J/K mol) IO-NPs Cr 288 -1.54565 89.18 316.14 298 -5.7021 308 -7.8231 NPs 288 -1.52446 73.43 255.81 298 -4.31708 308 -8.41853 IO-NPs+C Cr 288 -0.53861 102.37 361.07 298 -2.14662 308 -5.69839 NPs 288 -2.18478 97.53 343.24 298 -3.99941 308 -9.48848 Additional Declarations No competing interests reported. Supplementary Files Supplimentaryfile.docx GA.png Graphical abstract Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 11 Nov, 2025 Reviews received at journal 28 Oct, 2025 Reviewers agreed at journal 18 Oct, 2025 Reviewers agreed at journal 16 Oct, 2025 Reviewers invited by journal 15 Oct, 2025 Editor assigned by journal 22 Sep, 2025 Submission checks completed at journal 22 Sep, 2025 First submitted to journal 13 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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2","display":"","copyAsset":false,"role":"figure","size":3692793,"visible":true,"origin":"","legend":"\u003cp\u003eParticle characterisation of mycosynthesized IO-NPs and IO-NPs+C \u003cstrong\u003ea\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003ei-iv\u003c/strong\u003e\u003c/sub\u003e) TEM images IO-NPs+C its high-resolution images, size analysis and EDX spectrum \u003cstrong\u003eb\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003ei-iv\u003c/strong\u003e\u003c/sub\u003e) TEM images IO-NPs its high-resolution images, size analysis and EDX spectrum \u003cstrong\u003ec) \u003c/strong\u003eUV-Vis spectrum of suspension of Io-NPs and IO-NPs+C \u003cstrong\u003ed) \u003c/strong\u003eGraphical representation of VSM analysis of the IO-NPs and IO-NPs+C in room 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4","display":"","copyAsset":false,"role":"figure","size":1158017,"visible":true,"origin":"","legend":"\u003cp\u003eBatch adsorption of NPs and Cr ions onto IO-NPs and IO-NPs+C in different variation of \u003cstrong\u003ea)\u003c/strong\u003e Time \u003cstrong\u003eb)\u003c/strong\u003e Temperature and \u003cstrong\u003ec)\u003c/strong\u003e pH \u003cstrong\u003ed)\u003c/strong\u003e Zeta potential analysis of NPs, IO-NPs and IO-NPs at different pH\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7609084/v1/2eb0ace3e79660b07e3ab366.png"},{"id":94672528,"identity":"b1e3ba5d-b2c8-4b6d-ac25-a24e90aec4e8","added_by":"auto","created_at":"2025-10-29 13:40:41","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1324470,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of different common ions for the adsorption of NPs and Cr ions by \u003cstrong\u003ea)\u003c/strong\u003eIO-NPs+C and \u003cstrong\u003eb)\u003c/strong\u003e IO-NPs \u003cstrong\u003ec)\u003c/strong\u003e Effect of humic acid for the adsorption of NPs and Cr ions onto IO-NPs and IO-NPs+C \u003cstrong\u003ed)\u003c/strong\u003e Adsorption efficiency of Cr ions from COPR waste water simulated with 20mg/L concentration of NPs by IO-NPs and IO-NPs+C\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7609084/v1/afe0f08f390b0d6d82238144.png"},{"id":94644576,"identity":"cb460e39-9d1f-45ea-b8f9-5bed55eb6d2e","added_by":"auto","created_at":"2025-10-29 08:26:43","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2109006,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical representation of the Freundlich isotherm model and Pseudo 2\u003csup\u003end\u003c/sup\u003e order kinetic model for the adsorption of Cr ions (M) and NPs (P) using IO-NPs and IO-NPs+C\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-7609084/v1/1c0a4d008f3a5465f65e4cb0.png"},{"id":94674059,"identity":"4f92f065-d6c2-4906-977d-b5d298d571de","added_by":"auto","created_at":"2025-10-29 13:42:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":13714692,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7609084/v1/35ddff43-9cf3-48c6-a307-73d13f4e66d0.pdf"},{"id":94672130,"identity":"6939b117-a0f9-449a-81df-652f22bfd059","added_by":"auto","created_at":"2025-10-29 13:39:14","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2987808,"visible":true,"origin":"","legend":"","description":"","filename":"Supplimentaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-7609084/v1/c167d527e98e726da9918024.docx"},{"id":94644566,"identity":"a4d0e866-1008-45d5-8c40-138eeaa499c9","added_by":"auto","created_at":"2025-10-29 08:26:43","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":641023,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraphical abstract\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"GA.png","url":"https://assets-eu.researchsquare.com/files/rs-7609084/v1/43a533cef65b4b24fab80a0e.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Green-Synthesized Iron Oxide-Chitosan Nanocomposite for Chromium and Nanoplastics Remediation","fulltext":[{"header":"Highlights","content":"\u003cp\u003e\u0026bull; Fungal-synthesized IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C used for water purification\u003c/p\u003e\u003cp\u003e\u0026bull; Nanocomposite showed high adsorption for chromium and nanoplastics\u003c/p\u003e\u003cp\u003e\u0026bull; Adsorption followed Langmuir model with Qmax\u0026thinsp;\u0026gt;\u0026thinsp;500 mg/g for Cr\u003c/p\u003e\u003cp\u003e\u0026bull; ANN and RSM models optimized adsorption conditions effectively\u003c/p\u003e\u003cp\u003e\u0026bull; Groundwater treatment showed\u0026thinsp;\u0026gt;\u0026thinsp;93% pollutant removal in real scenario\u003c/p\u003e"},{"header":"1.0 Introduction","content":"\u003cp\u003eEnvironmental ecosystems and human health are seriously threatened by the growing problem of plastic waste and the poisonous heavy metals like chromium (Cr) ions that are contaminating water sources. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Microplastics (MPs) and nanoplastics (NPs), which are produced when these plastic wastes break down, enter aquatic ecosystems and are easily consumed by marine life [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. These particles not only disrupt marine life but also initiates biomagnification, transferring these contaminants through the food web and ultimately affecting humans which leads to reproductive, developmental, and long-term health risks [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Cr ions are released as toxic byproducts of various industrial activities, posing serious health risks that can range from breathing difficulties to cancer with long-term exposure. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The simultaneous presence of MPs, NPs and Cr ions in water needs urgent, multifaceted strategies to curb their combined threats to both human health and environmental sustainability.\u003c/p\u003e\u003cp\u003eConventional remediation approaches, including filtration, coagulation, and chemical precipitation, frequently prove insufficient, particularly against nanoparticles that evade traditional filtration systems due to their nanoscale dimensions. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In this context, adsorption has gained prominence as a promising remediation strategy, exploiting the surface characteristics of adsorbent materials to effectively capture and immobilize contaminants.[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Unlike conventional techniques, adsorption demonstrates superior efficiency, particularly for challenging pollutants such as MPs, NPs and Cr ions positioning it at the forefront of advanced water purification technologies [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRecent studies have highlighted different adsorbing materials e.g activated carbon, biochar, and metal oxides, with iron oxide nanoparticles (IO-NPs) emerging as an effective adsorbing material due to their high surface-to-volume ratio which has enhance reactivity, and strong affinity for both organic and inorganic contaminants. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. IO-NPs hold strong potential to simultaneously capture NPs and Cr ions, underscoring their versatility as a auspicious approach to address complex water pollution challenges [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eBuilding on this potential, the development of IO-NP\u0026ndash;chitosan composites (IO-NPs\u0026thinsp;+\u0026thinsp;C) introduce a novel strategy to further enhance adsorption efficiency [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This approach uses the physicochemical advantages of IO-NPs together with the functionality of chitosan (C), a natural biopolymer widely known for its biocompatibility and abundance. While conventional IO-NP synthesis often relies on chemical reduction or physical deposition, green synthesis methods present a more sustainable alternative. By employing biological agents such as plant extracts, bacteria, or fungi to reduce metal ions under mild conditions, green synthesis not only minimizes environmental impact but also tends to produce nanoparticles with improved stability and biocompatibility [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFungi, found in the extreme mangrove habitat of Indian Sundarbans can play a significant role in the green synthesis of the nanomaterial [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These mangrove habitats are characterized by high salinity, anoxic conditions, shifting pH, and heavy metal contamination, exerting significant environmental stress of the fungal metabolism. As a result, manglicolous fungi in this region have evolved specialized metabolic pathways that enable them to withstand these harsh conditions [\u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19 CR20\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The extracellular enzyme secreted from these fungi can catalyse the production of IO-NPs with highly desirable properties, such as optimal size, shape, and surface reactivity, making them especially suited for environmental applications [\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In this approach, the IO-NPs are incorporated with chitosan, also derived from fungi. Compared to traditional chitosan sourced from the shells of the crustacean organism, fungal derived chitosan delivers a sustainable, animal-free alternative with similar pollutant-binding properties [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This fungal-sourced chitosan is rich in amine and hydroxyl groups that can form strong interactions with pollutants such as MPs and Cr ions which significantly enhance the composite's adsorption capacity [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eBy employing fungi to produce both IO-NPs and C, this dual-fungal approach creates a composite material with remarkable synergy [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The IO-NPs offer an extensive surface area that enhances pollutant adsorption [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], while the chitosan matrix provides structural stability and abundant active sites for binding contaminants [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Furthermore, the magnetic properties of IO-NPs allow the overall composite material to be easily separated from water matrix using a magnetism field, makes it particularly practical for large-scale water treatment applications [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis project was designed to thoroughly evaluate and optimize a composite material made from IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C for real-world water treatment applications. The IO-NPs were synthesized using fungal extracts, and chitosan obtained from the same fungal source was incorporated to create a fully biogenic composite. Batch adsorption tests were performed to determine how effectively the composite could remove NPs and Cr ions under a range of environmental conditions, including variations in pH, temperature, and competing ions. These experiments provided a realistic assessment of the composite\u0026rsquo;s performance and helped clarify its behaviour under diverse water contamination scenarios. To fine-tune the adsorption process, advanced optimization methods such as Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) were applied to identify the conditions that maximize pollutant removal.\u003c/p\u003e\u003cp\u003eBy using the same fungi to produce both the nanoparticles and chitosan, this dual-fungal strategy creates a highly synergistic and sustainable material capable of tackling two major water pollutants simultaneously. The resulting IO-NPs\u0026thinsp;+\u0026thinsp;C composite not only demonstrates significant potential for eco-friendly water purification but also offers a framework for broader environmental remediation applications. The findings of this research provide a pathway toward more effective pollution control strategies, helping to secure cleaner water resources and promote long-term ecosystem health.\u003c/p\u003e"},{"header":"2.0 Material \u0026 methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Reagents\u003c/h2\u003e\u003cp\u003eFor the study analytical-grade iron (III) nitrate [Fe (NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e] and ICP-grade chromium standard solution (1000 mg/L) of Cr was procured from Sigma-Aldrich. For fungal isolation, Potato Dextrose Agar (PDA), was obtained from Hi-Media, India. Hydrophilic polystyrene latex beads, surface-coated with an anionic surfactant (FluoSpheres\u0026trade; Carboxylate-Modified Microspheres 0.1 \u0026micro;m) were considered as model particles to simulate naturally occurring NPs in aquatic environments. This selection is based on the understanding that primary plastics in aquatic systems undergo abiotic degradation, leading to the formation of more hydrophilic secondary forms due to the generation of carbonyl (C\u0026thinsp;=\u0026thinsp;O) functional groups [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The NPs were acquired from Sigma-Aldrich, USA. Other reagents which were used in the study, were of analytical grade, included sodium chloride (NaCl), sodium sulfate (Na\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e), sodium nitrate (NaNO\u003csub\u003e3\u003c/sub\u003e), sodium hydroxide (NaOH), hydrochloric acid (HCl), sodium bicarbonate (NaHCO\u003csub\u003e3\u003c/sub\u003e), and Humic acid sodium salt from Sigma-Aldrich. The majority of these chemicals were sourced from Merck, India. All solutions were prepared using deionized water to maintain experimental consistency and purity.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Sampling location for the sediment samples\u003c/h2\u003e\u003cp\u003eA sediment from the rhizosphere region was obtained from a depth of 10\u0026ndash;15 cm near \u003cem\u003eNypa fruticans\u003c/em\u003e trees lies in the intertidal mangrove zone of Satjelia Island (22\u0026deg; 7'4.05\"N, 88\u0026deg;52'23.17\"E) in the eastern Indian Sundarbans \u003cb\u003e(Supplementary Fig \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e)\u003c/b\u003e. The sediment collection was performed under sterile conditions to prevent contamination, and the sample was securely sealed in a sterile zip-lock pouch. It was then transported to the laboratory in a temperature-controlled container to maintain sample integrity for subsequent fungal isolation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Isolation of manglicolous fungi and green synthesis of IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C\u003c/h2\u003e\u003cp\u003eRhizospheric sediments collected from \u003cem\u003eNypa fruticans\u003c/em\u003e in the intertidal mangrove zone were serially diluted up to 10⁻⁴ and inoculated onto modified Potato Dextrose Agar (PDA) plates. To prevent bacterial contamination, chloramphenicol (100 \u0026micro;g/ml) was added, and the pH was adjusted to 5.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02. The plates were incubated at 27\u0026deg;C\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C for 72 hours. Fungal isolates were identified morphologically by applying slide culture techniques and lactophenol cotton blue staining, followed by subculturing for further characterization [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Fungal cultures were grown in 100 ml Potato Dextrose Broth (PDB) at temperature 27\u0026deg;C\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C for 360 hours. After cultivation, the fungal cell-free filtrate (FCF) was collected using filtration and centrifugation. For nanoparticle synthesis, 9.7 ml of FCF was mixed with 0.3 ml of 3 mM iron (III) nitrate, adjusting the pH to 3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02. A rapid change in the ocular properties of the mixture signifies nanoparticle formation, which was monitored for 60 minutes using UV-Vis spectroscopy [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eChitosan extraction from fungal mycelia was performed in triplicate, using a method modified from Azeez et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] and John Kasongo et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Initial deproteinization involved mixing the fungal mycelium with NaOH solution (90\u0026deg;C) at 250 rpm for 2.5 hours using the shaking incubator. The mixture was filtered, washed until neutral in pH, rinsed with acetone, and dried at 105\u0026deg;C to assess biomass yield. Acid extraction followed, where 16 g of deproteinized biomass was incubated in acetic acid at 60\u0026deg;C under reflux for 6 hours. After centrifugation, acid-soluble chitosan was precipitated at pH 8\u0026ndash;9 and dried. To deacetylate chitosan, 20 g of the biomass was treated with NaOH at 120\u0026deg;C for 2.5 hours under reflux. The mixture was filtered, washed to neutral pH, rinsed with acetone, and dried. Purification involved dissolving 1 g of chitosan in acetic acid, filtering to remove insoluble particles, neutralizing the solution, precipitating at 4\u0026deg;C, and drying for further analysis.\u003c/p\u003e\u003cp\u003eThe protocols for preparing the iron-chitosan composite (IO-NPs\u0026thinsp;+\u0026thinsp;C) were adapted from Elnouby et al., [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and Zemskova et al., [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In this method, chitosan powder was dissolved in 1\u0026ndash;2% acetic acid to form a uniform, viscous solution. The synthesised iron oxide nanoparticles were separately dispersed in distilled water, and ultrasonication was employed to ensure even distribution. The nanoparticle suspension was then gradually added to the chitosan solution under constant stirring to promote interaction between the iron oxide and chitosan. For improved stability, a cross-linking agent such as glutaraldehyde was introduced in minimal amounts. To facilitate the precipitation of the iron-chitosan composite, the pH was adjusted using 0.1 M NaOH. Once precipitated, the composite was filtered, thoroughly washed with distilled water, and dried in a vacuum oven at 50\u0026deg;C. The dried composite was then ground into a fine powder. The nanoparticles were subsequently purified by centrifugation at 14,000 rpm for 10 minutes, re-dispersed in Milli-Q water, and subjected to ultrasonication for 45 minutes. This procedure was repeated three times to ensure the homogeneity of the nanoparticle suspension \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eControl experiments included FCF without iron nitrate (positive control) and iron nitrate without FCF (negative control). Molecular identification of fungal strains confirmed their involvement in iron nanoparticle synthesis and the formation of the iron-chitosan composite.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Molecular identification of fungal isolates\u003c/h2\u003e\u003cp\u003eFungal DNA was extracted and purified using the HiPurATM Plant Genomic Miniprep Kit (HiMedia MB507), and its quality was assessed through 1.2% agarose gel electrophoresis. To amplify ribosomal DNA, primers targeting the internal transcribed spacer (ITS) region were used, based on the method outlined by White et al. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], with amplification performed on a VeritiTM thermal cycler (Thermo Fisher Scientific). PCR products were purified and subjected to Sanger sequencing using an ABI 3730xl Genetic Analyzer (Thermo Fisher Scientific). The forward and reverse sequences were aligned using BioEdit v7 to generate a consensus sequence. Fungal species identification was accomplished by submitting the consensus sequence to the NCBI BLAST (Basic Local Alignment Search Tool). The ITS sequence was also deposited into the NCBI GenBank via BankIt for validation and to obtain an accession number.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Physical and Chemical Characterization of Nanoparticles\u003c/h2\u003e\u003cp\u003eA range of advanced analytical techniques was employed to comprehensively assess the characteristics of the synthesized nanoparticles (IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C), focusing on their stability in aqueous media, magnetic properties, elemental composition, and crystalline structure \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003eand Supplementary Fig S2)\u003c/b\u003e. The synthesised nanoparticles were monitored using a PerkinElmer Lambda 35 UV-Vis spectrophotometer, with measurements taken across wavelengths of 200\u0026ndash;700 nm. Following a 30-minute sonication of the nanoparticle suspension (Biobase UC20A sonicator), the zeta potential was measured using a Zetasizer (Zen 1600, Malvern Instruments, USA). For Fourier Transform Infrared Spectroscopy (FTIR) analysis, the nanoparticles were lyophilized (Biobase BK-FD10PT) and combined with potassium bromide (KBr) in a 1:100 ratio. The resulting pellet was then analysed in Attenuated Total Reflection (ATR) mode, with infrared spectra captured in the range of 3500 to 500 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at a resolution of 4 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e using a Jasco FT/IR-6300. Morphological and elemental characterization was performed on 5 mg of lyophilized IO-NPs using Field Emission Scanning Electron Microscopy (FESEM) (JEOL JSM-7600F) at an operating voltage of 15\u0026ndash;25 kV, complemented by Energy Dispersive X-ray Spectroscopy (EDX) (Oxford Instruments, INCA PENTA FET X3). Transmission Electron Microscopy (TEM) (JEOL TEM 2100 HR), coupled with EDX for elemental composition analysis, was conducted on a 10 \u0026micro;L sample of the nanoparticle suspension, placed on a carbon-coated copper grid for examination. Crystallographic properties were analyzed through X-ray Powder Diffraction (XRD) using a Philips PW1830 instrument. The diffraction data were collected in 2θ mode, spanning angles from 10\u0026deg; to 80\u0026deg; with a 0.02\u0026deg; step size, using Cu Kα radiation (λ\u0026thinsp;=\u0026thinsp;1.542 \u0026Aring;) at 40 kV and 30 mA. This analysis provided key insights into the interplanar spacings and intensities, enabling the identification of diffraction peaks for IO-NPs, which were compared against theoretical standards provided by the Joint Committee on Powder Diffraction Standards-International Centre for Diffraction Data (JCPDS-ICDD). Finally, the magnetic properties of the IO-NPs were evaluated using a Superconducting Quantum Interference Device (SQUID) vibrating sample magnetometer (VSM) from Quantum Design.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Sorption Studies\u003c/h2\u003e\u003cp\u003eA series of sorption experiments were performed to assess the adsorption efficiency of IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C for nanoparticles (NPs) and chromium (Cr) ions. Stock solutions of 500 mg/L for both NPs and Cr ions were prepared in deionized water (DI). In each experiment, varying concentrations (20\u0026ndash;120 mg/L) of IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C were added to 50 mL conical flasks containing 20 mg/L solutions of NPs and Cr ions. The materials were compared to determine their sorption capacities, with initial experiments focused on identifying the optimal adsorbent for subsequent studies. The mixtures were vortexed for 120 minutes to ensure thorough interaction between the adsorbents and pollutants, followed by centrifugation at 2500 rpm for 3 minutes. The supernatant was then carefully extracted, and NPs were quantified using fluorescence spectrometry (Horiba FluoroMax Plus) at an excitation wavelength of 525 nm. Chromium ion concentrations were measured using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES).\u003c/p\u003e\u003cp\u003eTo examine the influence of environmental factors on adsorption performance, various parameters were adjusted, including pH, the presence of competing ions, contact time, initial pollutant concentrations, and varying humic acid concentrations. All experiments were conducted at room temperature (35\u0026deg;C) with consistent pollutant concentrations (20 mg/L), solution volumes (50 mL), and adsorbent masses (100 mg/L). Kinetic studies were carried out by varying the contact times between 0 and 120 minutes, while isotherm experiments evaluated increasing NP and Cr ion concentrations up to 60 mg/L.\u003c/p\u003e\u003cp\u003eThe adsorption capacity (q) for both NPs and Cr ions was calculated using the equation:\u003c/p\u003e\u003cp\u003eq = (C\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;\u0026minus;\u0026thinsp;C\u003csub\u003ee\u003c/sub\u003e) \u0026times;V/m,\u003c/p\u003e\u003cp\u003e% Removal = (C\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;\u0026minus;\u0026thinsp;C\u003csub\u003ee\u003c/sub\u003e) / C\u003csub\u003e0\u003c/sub\u003e\u0026times; 100\u003c/p\u003e\u003cp\u003ewhere \"q\" represents the adsorption capacity (mg/g), C\u003csub\u003e0\u003c/sub\u003e and C\u003csub\u003ee\u003c/sub\u003e are the initial and final concentrations of the pollutants (NPs or Cr ions) in solution (mg/L), \"V\" is the volume of the solution (mL), and \"m\" is the mass of the adsorbent (mg).\u003c/p\u003e\u003cp\u003eThe experimental data were analysed using linear kinetic models, specifically the pseudo-first-order and pseudo-second-order models, to understand the adsorption kinetics. For isotherm analyses, both the Langmuir and Freundlich models were employed to evaluate the adsorption behaviour. The effect of temperature on the sorption process was also examined by conducting experiments at three different temperatures: 15\u0026deg;C (288 K), 25\u0026deg;C (298 K), and 35\u0026deg;C (308 K). Thermodynamic parameters were calculated to provide insights into the adsorption mechanism and its spontaneity. A detailed description of the kinetic, isotherm, and thermodynamic models is presented in \u003cb\u003eSupplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.7 RSM and ANN analysis of the adsorption process\u003c/h2\u003e\u003cp\u003eThe adsorption process was analysed using RSM to model the relationships between four key independent variables: adsorbent dose (mg/L), pH, temperature (\u0026deg;C), and time. A quadratic polynomial equation was used to describe these interactions, with further details provided in the supplementary section \u003cb\u003e(Table I)\u003c/b\u003e. Optimal experimental conditions were determined using Derringer\u0026rsquo;s desirability function and following methods from our previous publications [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The specific ranges for each variable are detailed in the supplementary section, and the software generated 30 experimental runs, with the actual and predicted outcomes presented in \u003cb\u003eSupplementary Table S2-S4\u003c/b\u003e. Additionally, an ANN model was implemented to predict the percentage removal of heavy metals during the adsorption process. The computational framework for ANN modelling, along with the predicted vs actual graphical plot of the experimental data and R\u003csup\u003e2\u003c/sup\u003e obtained from the algorithmic model are described in supplementary section \u003cb\u003e(Supplementary Table S5)\u003c/b\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.8 Statistical Analysis of Adsorption Data\u003c/h2\u003e\u003cp\u003eAll experiments were performed in triplicate, with the results reported as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Data analysis was conducted using Origin software (Version 9.1; OriginLab Corporation) and Microsoft Excel 2022. Statistical significance was evaluated through ANOVA using Design Expert (Version 7.0, Minneapolis, USA) and MATLAB (Version 7.0.1, The MathWorks Inc.).\u003c/p\u003e\u003c/div\u003e"},{"header":"3.0 Results and discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Mechanism of IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C formation using fungal isolates\u003c/h2\u003e\u003cp\u003eFungal strains isolated from the rhizospheric sediment of \u003cem\u003eNypa fruticans\u003c/em\u003e were analyzed for colony morphology, including characteristics such as form, edge and elevation. Identification at the genus level was performed by examining the structures of conidiophores and conidia using taxonomic keys [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], as demonstrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The fungal cell-free filtrate (FCF) from 15 isolates as screened for its ability to synthesize nanoparticles using a Fe (NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e solution. Among these, strain STSP9, identified as \u003cem\u003eAspergillus\u003c/em\u003e sp., exhibited rapid nanoparticle synthesis by reducing the iron salt solution within 5 minutes at 30\u0026deg;C\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C. In contrast, the control experiment conducted in the absence of the fungal culture did not show any reduction, confirming the essential role of \u003cem\u003eAspergillus\u003c/em\u003e sp. in the nanoparticle synthesis process. Following nanoparticle formation, chitosan was extracted from STSP9 and integrated with the iron oxide nanoparticles (IO-NPs) to create a composite referred to as IO-NPs\u0026thinsp;+\u0026thinsp;C. The synthesis and assembly of the IO-NPs and the IO-NPs\u0026thinsp;+\u0026thinsp;C composite occurred in multiple stages \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. In step I, NADH reductase initiated the reduction of the iron precursor salt, releasing Fe\u003csup\u003e3+\u003c/sup\u003e and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e ions [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In step II, Fe\u003csup\u003e3+\u003c/sup\u003e ions interacted with fungal extracellular proteins, leading to the formation of stable organic Fe (III) complexes [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In step III, hydrolysis of these Fe (III) complexes resulted in the formation of Fe(OH)\u003csub\u003e3\u003c/sub\u003e, which nucleated into Fe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e nanocrystals that precipitated as iron oxide nanoparticles [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Step IV involved the formation of the IO-NPs\u0026thinsp;+\u0026thinsp;C, where chitosan served as a stabilizing and matrix-forming agent. Chitosan, a natural polysaccharide derived from chitin, was dissolved in 1\u0026ndash;2% acetic acid, forming a homogeneous, viscous solution [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This acidic environment protonated the amine groups of chitosan, causing it to become positively charged and promoting solubility in the aqueous phase. In parallel, the synthesized iron oxide nanoparticles were suspended in distilled water and subjected to ultrasonication to ensure uniform particle distribution, preventing agglomeration. The chitosan solution and the iron oxide nanoparticle suspension were gradually combined under continuous stirring. The strong electrostatic attraction between the negatively charged iron oxide nanoparticles and the positively charged protonated chitosan allowed for efficient interaction and encapsulation of the nanoparticles within the polymer matrix [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. This interaction facilitated the uniform dispersion of iron oxide nanoparticles throughout the chitosan matrix, forming a stable composite material [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. To further enhance the mechanical strength and stability of the composite glutaraldehyde was introduced in minimal quantities as a cross-linking agent [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Glutaraldehyde forms covalent bonds between the amine groups of chitosan, leading to the formation of a three-dimensional network that reinforces the structural integrity of the composite. This cross-linking process is essential for preventing the premature release of nanoparticles from the chitosan matrix. The pH of the solution was then carefully adjusted using 0.1 M NaOH. This step was critical, as the alkaline conditions promoted the deprotonation of chitosan's amine groups, leading to the precipitation of the iron-chitosan composite [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In this process, the chitosan acts as a scaffold, providing a biocompatible matrix that stabilizes the iron oxide nanoparticles. For spectral analysis, the fungal cell-free filtrate (FCF) served as the positive control, while the iron precursor solution was used as the negative control, showing no significant spectral shift. Strain STSP9 was identified at the species level by sequencing the ITS region, producing a 546 bp sequence with high similarity to \u003cem\u003eAspergillus iranicus\u003c/em\u003e, confirmed via BLAST analysis. This sequence was deposited in the NCBI database under accession number MH824157.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Physical and chemical characterization of the nanoparticles and the nanocomposite\u003c/h2\u003e\u003cp\u003eThe characterization of IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C employs a suite of advanced analytical techniques to elucidate their structural, chemical, and magnetic properties \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003eand Supplementary Fig S2)\u003c/b\u003e. UV-Vis spectroscopy typically shows a distinct absorption peak in the range of 200\u0026ndash;400 nm, attributed to surface plasmon resonance (SPR), indicating the formation of nanoparticles and their size-dependent optical characteristics. The IONPs\u0026thinsp;+\u0026thinsp;C emonstrates slight redshifts or variations in peak intensity, suggesting interactions between the chitosan matrix and the nanoparticles that may affect particle size or surface charge [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. FTIR spectroscopy provides insights into functional groups \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e, with the strong Fe-O bond absorption band appearing between 580\u0026ndash;630 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, indicative of hematite (Fe\u003csub\u003e3\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e) or maghemite (γ-Fe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e). The composite reveals additional peaks related to chitosan, notably broad bands around 3200\u0026ndash;3500 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for hydroxyl (\u0026ndash;OH) and amino (\u0026ndash;NH₂) group vibrations, alongside amide I and II peaks between 1650\u0026thinsp;\u0026minus;\u0026thinsp;1560 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, confirming chitosan's coordination with iron oxide. Other notable peaks at 830 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 1072\u0026ndash;1074 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 1394\u0026ndash;1396 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 1510\u0026ndash;1512 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and 3119\u0026ndash;3144 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e correspond to C\u0026thinsp;=\u0026thinsp;O, O\u0026ndash;H, N\u0026ndash;O, and C\u0026ndash;H groups, respectively [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan additionalcitationids=\"CR40 CR41\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. XRD patterns indicate \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e the crystalline nature of IONPs, matching the rhombohedral structure of hematite (Fe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e) as per JCPDS No. 24\u0026ndash;0072, with characteristic peaks in the regions (012), (104), (110), (113), (024), (116), (122), (214), and (300). Peak broadening signifies the formation of nanoscale crystallites ranging from 2\u0026ndash;20 nm, estimated using the Scherrer equation, while the presence of diffuse scattering in the composite reflects the amorphous nature of chitosan, preserving the crystalline structure of iron oxide[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Magnetic characterization via SQUID-VSM magnetometry reveals superparamagnetic behaviour of IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C at room temperature, with saturation magnetization (Ms) values between 2\u0026ndash;8 emu/g, substantially lower than the bulk magnetite value of ~\u0026thinsp;90 emu/g. This decrease is attributed to surface spin disorder from unsaturated surface iron coordination, finite size effects leading to a single magnetic domain structure, and the influence of the chitosan matrix, which spatially separates the nanoparticles, further attenuating their magnetic interactions [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The M-H curves, measured within a field range of \u0026plusmn;\u0026thinsp;6 T, demonstrate the absence of coercivity (Hc\u0026thinsp;\u0026asymp;\u0026thinsp;0 Oe) and remanence (Mr\u0026thinsp;\u0026asymp;\u0026thinsp;0 emu/g), affirming that the nanoparticles' magnetic moments can swiftly realign with an applied field without residual magnetization. FESEM provides high-resolution imaging of particle morphology \u003cb\u003e(Supplementary Fig S2)\u003c/b\u003e, showing pure IO-NPs as spherical or quasi-spherical particles with diameters of 10\u0026ndash;30 nm. In the chitosan composite, nanoparticles are uniformly distributed, appearing as discrete, embedded entities within a smooth chitosan matrix. EDX mapping confirms the elemental composition, with prominent signals for Fe and O from IO-NPs and C and N from chitosan, while elemental mapping indicates a homogenous distribution of iron throughout the composite, demonstrating successful integration s[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. TEM reveals uniform particle sizes, typically 5\u0026ndash;15 nm \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb\u003csub\u003e\u003cb\u003e(i\u0026minus;iv)\u003c/b\u003e\u003c/sub\u003e\u003cb\u003e)\u003c/b\u003e, with high-resolution images displaying lattice fringes corresponding to specific crystallographic planes, thus affirming the nanoparticles' high crystallinity. In the chitosan composite, TEM indicates encapsulation or coating of IO-NPs by the chitosan, often forming a core-shell structure with the polymer layer manifesting as a thin, amorphous coating around the nanoparticles, confirming effective surface modification and interaction [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Batch adsorption study\u003c/h2\u003e\u003cp\u003eThe batch adsorption study of NPs and Cr ions onto IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C reveals complex adsorption kinetics and thermodynamics, which contribute to improved pollutant removal efficiencies \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea-d\u003cb\u003e)\u003c/b\u003e. At an initial adsorbate concentration of 20 mg/L and an adsorbent dosage of 100 mg/L, the equilibrium adsorption capacities (q\u003csub\u003ee\u003c/sub\u003e) were calculated to be 191\u0026thinsp;\u0026plusmn;\u0026thinsp;3.11 mg/g for Cr and 177.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6 mg/g for NPs on IO-NPs. Interestingly, the IO-NPs\u0026thinsp;+\u0026thinsp;C demonstrated even greater adsorption capacities, with q\u003csub\u003ee\u003c/sub\u003e values of 195.20\u0026thinsp;\u0026plusmn;\u0026thinsp;3.33 mg/g for Cr and 190.50\u0026thinsp;\u0026plusmn;\u0026thinsp;3.59 mg/g for NPs. Kinetic studies revealed rapid adsorption in the first 30 minutes of the 120-minute process, suggesting that the surface of the adsorbents possessed high affinity and an abundance of active sites in the early stages. As the process advanced, a slower rate of adsorption was observed as these sites became saturated, indicating a transition to a diffusion-controlled mechanism, where intraparticle diffusion becomes the dominant factor. This is particularly noticeable in IO-NPs\u0026thinsp;+\u0026thinsp;C, likely due to the additional binding sites provided by chitosan [\u003cspan additionalcitationids=\"CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The study also examined the effect of adsorbent concentration, ranging from 20 to 120 mg/L, and found that optimal adsorption occurred at 100 mg/L (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, b \u003cb\u003eand c\u003c/b\u003e). This concentration represents the ideal balance between adsorbate molecules and available active sites, preventing oversaturation and maintaining efficient surface interactions. Furthermore, the adsorption process was found to be highly pH-dependent, with maximum efficiency achieved at pH 2. Under acidic conditions, the surfaces of IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C are protonated, which enhances electrostatic attraction between the positively charged surface and the negatively charged Cr ions and NPs. As the pH increased, zeta potential analyses revealed that NPs maintained a stable negative charge (-20 to -64 mV), while the surface charge of IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C shifted from positive to neutral, slightly negative, near neutral pH levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). This behaviour aligns with the point of zero charge (PZC) of the adsorbents, confirming that the adsorption efficiency diminishes as surface charge neutrality is approached, reducing electrostatic interactions [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Overall, both IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C are highly effective in capturing Cr ions and NPs, with IO-NPs\u0026thinsp;+\u0026thinsp;C exhibiting superior adsorption capacity. The enhanced performance of IO-NPs\u0026thinsp;+\u0026thinsp;C is attributed to the synergistic properties of chitosan, which not only increases surface area but also offers additional binding sites for adsorbates [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. This makes the composite particularly suited for applications in water purification and pollutant removal.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.4 Effect of common ions and humic acid on adsorption of NPs and Cr on IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe effect of common ions and humic acid on the adsorption of NPs and Cr ions using IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C was thoroughly investigated at an adsorbent concentration of 100 mg/L, with an initial adsorbate concentration of 20 mg/L, over a contact time of 120 minutes \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-d\u003cb\u003e)\u003c/b\u003e. The results indicated that the presence of common ions had varying impacts on the adsorption capacity, with most anions exhibiting negligible effects. Notably, bicarbonate (HCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e) demonstrated a pronounced influence; at a concentration of 5 mM, the removal efficiency for both NPs and Cr ions decreased by approximately 60%. This significant decline can be attributed to HCO₃⁻ acting as a buffer, which raises the pH from 5.5 to approximately 8.6, enhancing the negative charge on the adsorbent surface and resulting in electrostatic repulsion of negatively charged species like NPs. In contrast, other common ions (such as chloride, nitrate, and sulphate) induced only minor reductions in adsorption capacity, typically around 5\u0026ndash;10%. This limited effect can be explained by the relatively weak binding affinity of these ions to the IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C, which does not substantially compete with the adsorption sites available for NPs and Cr ions. The observed minor decrease in removal efficiency suggests that these anions may possess a lower affinity for the IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C. Furthermore, the influence of humic acid concentrations on adsorption was assessed, revealing a significant decrease in removal efficiency. Even at a low concentration of 1 mg/L of humic acid, a reduction in removal percentage of 55\u0026ndash;75% was recorded. This decline in adsorption capacity is attributed to the steric hindrances imposed by humic acid, which interferes with the effective aggregation and sedimentation of nanoparticles. The DLVO theory elucidates this phenomenon by suggesting that the presence of humic acid alters the interparticle interactions, increasing repulsive forces between the particles, thereby limiting their co-settling ratios [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Additionally, the stabilizing effect of humic acid on negatively charged IONPs and IO-NPs\u0026thinsp;+\u0026thinsp;C was confirmed by zeta potential measurements. The introduction of 1 mg/L of humic acid caused the zeta potential of IONPs and IO-NPs\u0026thinsp;+\u0026thinsp;C to shift from a neutral value of approximately\u0026thinsp;+\u0026thinsp;2.85 mV to a significantly negative value of -20 mV. As humic acid concentration increased, the zeta potential became more negative, indicating enhanced stabilization and electrostatic repulsion between nanoparticles, which further inhibited their ability to adsorb NPs and Cr ions effectively.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.5 Effect of NaOH on desorption of NPs and Cr ions and the reusability study on IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe desorption behaviour of NPs and Cr ions was investigated using varying concentrations of NaOH, ranging from 0.1 to 0.3 M \u003cb\u003e(Supplementary Fig S3)\u003c/b\u003e. The highest desorption efficiency was observed at 0.3 M NaOH, where the strong alkaline environment significantly enhanced the release of both contaminants from the adsorbent surfaces. The increased ionic strength and higher pH levels associated with 0.3 M NaOH facilitate the disruption of electrostatic interactions and hydrogen bonding between the adsorbates and the adsorbent, thus promoting effective desorption [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In a reusability study, both IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C demonstrated substantial stability, retaining their functionality across five adsorption-desorption cycles. However, a gradual decline in adsorption efficiency was noted, with the removal capacity decreasing to below 80% by the fifth cycle. This decrease can be attributed to potential fouling and loss of active sites on the adsorbent materials after multiple cycles, indicating a need for optimization in regeneration protocols to enhance long-term applicability in environmental remediation processes.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.6 Thermodynamic and kinetic insights into the adsorptive removal of NPs and Cr ions\u003c/h2\u003e\u003cp\u003eThe adsorption behaviour of NPs and Cr onto IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C was systematically investigated through isotherm and kinetic studies at 288, 298, and 308 K. At 308 K, IO-NPs achieved maximum adsorption capacities q\u003csub\u003ee\u003c/sub\u003e of 526.31 mg/g for Cr ions and 270.27 mg/g for NPs, while IO-NPs\u0026thinsp;+\u0026thinsp;C exhibited even higher adsorption, reaching 625.12 mg/g for Cr ions and 333.31 mg/g for NPs \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e \u003cb\u003eand Supplementary Fig S4)\u003c/b\u003e. The adsorption profiles followed the Freundlich isotherm model, indicative of a heterogeneous surface with varied energy sites and a multilayer adsorption mechanism, suggesting that the adsorption sites on both IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C have differential affinities and capacities for Cr ions and NPs.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe Freundlich isotherm \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb\u003cb\u003e)\u003c/b\u003e further implies that the adsorption mechanism is influenced by interactions beyond a simple monolayer saturation, accommodating multilayer adsorption on the uneven surface of the iron oxide nanoparticles and chitosan matrix. The enhanced capacity observed for IO-NPs\u0026thinsp;+\u0026thinsp;C at each temperature suggests that the chitosan component introduces additional active sites, potentially through amine and hydroxyl functional groups, thereby increasing surface heterogeneity and complexation potential [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eKinetic analyses demonstrated a strong fit with the pseudo-second-order model \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed\u003cb\u003e)\u003c/b\u003e across all temperatures, indicating chemisorption as the primary adsorption mechanism. This is characterized by chemical bonds forming between the adsorbate and active sites on the IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C surfaces, likely through electron exchange or covalent interactions, particularly prominent due to the hydroxyl and amine groups present in chitosan. The temperature dependency observed in the pseudo-second-order kinetics also highlights the activation energy required for chemical bonding, suggesting that elevated temperatures enhance reaction rates by increasing the molecular interactions and mobility of Cr ions and NPs [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThermodynamic parameters, including Gibbs free energy (ΔG), enthalpy (ΔH) and entropy (ΔS), revealed deeper insights into the adsorption mechanism \u003cb\u003e(Supplementary Fig S4 and Table II)\u003c/b\u003e. Negative values of ΔG at each temperature confirm the spontaneous nature of adsorption, while the increasingly negative ΔG with rising temperature supports an endothermic process that becomes more favourable at higher temperatures. This temperature-induced enhancement in spontaneity points to activated complex formation on the IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C surface, likely driven by stronger adsorbate-surface interactions at elevated thermal energy levels. The positive values of ΔS suggest an increase in randomness at the solid-liquid interface, which may reflect enhanced structural rearrangements within the adsorbent\u0026rsquo;s surface layers, optimizing the binding of Cr ions and NPs and thus improving adsorption efficiency[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003e7 Utilization of RSM and ANN for the validation of the batch experimental result for the IO-NPs\u0026thinsp;+\u0026thinsp;C for the NPs and Cr ions adsorption\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn this study, the superior performance of the IO-NPs\u0026thinsp;+\u0026thinsp;C in batch adsorption experiments was evident when compared to IO-NPs alone. The chitosan matrix contributed additional active functional groups, such as amine and hydroxyl, enhancing surface interactions with Cr ions and NPs. This increased adsorption capacity, along with improved stability and stronger pollutant binding, positioned IO-NPs\u0026thinsp;+\u0026thinsp;C as the preferred adsorbent for further optimization. To explore the complex interaction of adsorption parameters, RSM and ANN were employed for multimeric analysis, providing a rigorous framework for process optimization and predictive modelling. RSM was utilized to assess the interaction effects of key variables\u0026mdash;adsorbent dosage, temperature, pH, and contact time\u0026mdash;on the adsorption efficiency of IO-NPs\u0026thinsp;+\u0026thinsp;C. The quadratic polynomial model generated by RSM allowed for the evaluation of linear, quadratic, and interaction terms in a systematic manner. Statistical significance was confirmed by the high F-values (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), demonstrating that the model fit the experimental data well. The predicted coefficient of determination R\u003csup\u003e2\u003c/sup\u003e (\u0026gt;\u0026thinsp;0.99) was in excellent agreement with the adjusted R\u003csup\u003e2\u003c/sup\u003e, suggesting a robust fit that captured the influence of each factor accurately \u003cb\u003e(Supplementary Table S3 and S4)\u003c/b\u003e. The model's adequate precision values exceeded 4, a clear indication of its strong signal-to-noise ratio, while the coefficient of variation (% CV) was below 4%, further confirming the model's precision.\u003c/p\u003e\u003cp\u003eKey interactions between variables were mapped using 3D response surface plots, which revealed significant effects of IO-NPs\u0026thinsp;+\u0026thinsp;C dosage and temperature on adsorption efficiency, with a positive correlation between increasing dose and temperature and higher removal rates of both Cr ions and NPs. The interaction between dosage and pH was also significant, highlighting the sensitivity of the adsorption process to changes in solution acidity. Optimal conditions for Cr and NP removal were identified as 99.98 mg/L IO-NPs\u0026thinsp;+\u0026thinsp;C, pH 6.8, and 35\u0026deg;C, under which removal efficiencies of 92.68% for Cr and 97.89% for NPs were achieved \u003cb\u003e(Supplementary Fig S5 and S6)\u003c/b\u003e. The RSM model provided a detailed understanding of the influence of both linear and interaction terms, confirming the critical role of adsorbent dose and temperature in driving the adsorption process. Additionally, ANN was employed to model the non-linear relationships between variables that RSM might not fully capture. Using a multi-layer perceptron (MLP) architecture and backpropagation algorithms, the ANN model \u003cb\u003e(Supplementary Fig S7 and Table S5)\u003c/b\u003e was trained with experimental input-output data, demonstrating high predictive accuracy. The ANN model accurately predicted adsorption efficiencies with over 98% precision, capturing the complex, non-linear interactions between variables. Error analysis showed low mean squared error (MSE) values, indicating minimal differences between predicted and experimental outcomes.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.8 Application of the IO-NPs\u0026thinsp;+\u0026thinsp;C in real world scenario\u003c/h2\u003e\u003cp\u003eThe application of IO-NPs\u0026thinsp;+\u0026thinsp;C in real-world groundwater remediation was evaluated using a sample collected from a chromite ore processing residue (COPR)-contaminated site in Uttar Pradesh, India. The groundwater exhibited high total dissolved solids (TDS) of 684 mg/L, a pH of 7.6, and an elevated Cr concentration of 12.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2 mg/L with Cr(VI) concentration of 10.96\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01 mg/L \u003cb\u003e(Supplementary Table S6)\u003c/b\u003e. Additionally, to simulate a worst-case contamination scenario, the sample was spiked with 20 mg/L of NPs before treatment. The remediation process involved treating the contaminated water with 100 mg/L of IO-NPs\u0026thinsp;+\u0026thinsp;C under vigorous stirring at 313 K for 120 minutes, leading to an impressive removal efficiency of 95.22% for the total Cr, 93.39% Cr(VI) ions and 92.91% of NPs (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed).\u003c/p\u003e\u003cp\u003eThe high efficacy of IO-NPs\u0026thinsp;+\u0026thinsp;C can be attributed to a combination of adsorption, surface complexation, and redox transformation processes facilitated by the iron oxide (IO) core and the biopolymeric chitosan (C) coating. The iron oxide nanoparticles provide abundant active sites for Cr(VI) adsorption via electrostatic interactions and ligand exchange, while Fe\u0026sup2;⁺/Fe\u0026sup3;⁺ redox pairs within the IO structure promote in situ reduction of Cr(VI) to the less toxic Cr(III). Simultaneously, chitosan enhances pollutant removal through its chelating ability, forming stable complexes with Cr species, and its extensive network of hydroxyl (-OH) and amine (-NH₂) functional groups facilitates the adsorption of both metal ions and nanoplastics. The presence of chitosan also imparts additional stability, preventing nanoparticle aggregation and minimizing secondary pollution by reducing material leaching. Furthermore, nanoplastic removal is facilitated by a combination of hydrophobic interactions, electrostatic attraction, and entrapment within the chitosan matrix, preventing further dispersion in the environment. Importantly, the near-neutral pH of the treated water suggests minimal secondary changes to water chemistry, making IO-NPs\u0026thinsp;+\u0026thinsp;C suitable for field-scale applications. These findings underscore IO-NPs\u0026thinsp;+\u0026thinsp;C as a highly efficient and sustainable nanocomposite for the simultaneous removal of heavy metals and emerging contaminants like NPs from polluted water sources. However, further research is needed to evaluate its long-term stability, regeneration potential, and field-scale applicability under varying environmental conditions.\u003c/p\u003e\u003c/div\u003e"},{"header":"4.0 Conclusion","content":"\u003cp\u003eThis study offers significant advancements in the field of nanomaterial-based environmental remediation, particularly in the removal of NPs and Cr ions using mycosynthesized IO-NPs and an IO-NPs\u0026thinsp;+\u0026thinsp;C composite. Employing a green synthesis route through the fungal isolate \u003cem\u003eAspergillus iranicus\u003c/em\u003e, we successfully developed an eco-friendly, scalable methodology that eliminates the need for hazardous chemicals and energy-intensive processes typically involved in conventional nanoparticle synthesis. TEM analysis confirmed the spherical morphology of the particles, with sizes ranging from 10 to 50 nm, while crystallographic studies revealed their high crystallinity and FCC structure. Additionally, magnetic characterization demonstrated their superparamagnetic nature, ensuring ease of recovery after adsorption processes. Batch adsorption experiments revealed the IO-NPs and IO-NPs\u0026thinsp;+\u0026thinsp;C to be highly effective in removing Cr ions and NPs, with maximum adsorption capacities (q\u003csub\u003ee\u003c/sub\u003e) exceeding 500 mg/g for Cr ions and 250 mg/g for NPs under pH 2, 35\u0026deg;C, and a contact time of 100 min at an adsorbent concentration of 100 mg/L. The superior performance of IO-NPs\u0026thinsp;+\u0026thinsp;C over IO-NPs was attributed to the additional adsorption sites provided by the chitosan matrix, enhancing pollutant binding through electrostatic and chelation interactions. Adsorption isotherms suggested a monolayer adsorption mechanism with maximum adsorption capacities (Q\u003csub\u003emax\u003c/sub\u003e) of more than 500 mg/g for Cr ions and 260 mg/g for NPs. The thermodynamic parameters, indicated that the adsorption process was spontaneous and endothermic, further confirming the feasibility of these composites for real-world applications. Reusability studies demonstrated the robustness of the nanomaterials composite, maintaining its efficiency up to five adsorption-desorption cycles with minimal loss in performance. A major innovation of this study was the integration of computational models such as RSM and ANN to optimize the adsorption process. These models were instrumental in identifying the influence of key variables such as adsorbent dose, pH, temperature, and time on adsorption performance. The predicted optimal conditions (99.98 mg/L IO-NPs\u0026thinsp;+\u0026thinsp;C, pH 6.8, and 35\u0026deg;C) were experimentally validated, with pollutant removal rates of 92.68% for Cr and 97.89% for NPs, showcasing minimal deviation from the predicted values and underscoring the precision of the computational approach. The efficacy of IO-NPs\u0026thinsp;+\u0026thinsp;C was validated by treating groundwater contaminated with Cr and spiked with 20 mg/L of NPs, collected near COPR region. Using 100 mg/L of IO-NPs\u0026thinsp;+\u0026thinsp;C at pH 7.6 and 313 K for 120 minutes, 93.39% of Cr and NPs were removed, confirming the composite's effectiveness in real-world conditions. Overall, this research provides a comprehensive framework for developing sustainable, highly efficient nanomaterials for environmental remediation. The study's combination of green synthesis, advanced characterization, robust adsorption performance, and computational optimization marks a significant step toward the large-scale deployment of these composites in water treatment technologies. The integration of bio-based materials such as chitosan further enhances the environmental compatibility and functional versatility of these composites, setting a new benchmark in the development of eco-friendly nanotechnologies for global pollution challenges.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are thankful to IISER Kolkata and SINP Kolkata for various research facilities.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSM:\u003c/strong\u003e Writing \u0026ndash; original draft, Methodology, Investigation, Software, Formal analysis, Data curation, Conceptualization, Investigation, Formal analysis, Data curation, Fund acquisition; \u003cstrong\u003eGKD:\u003c/strong\u003e Writing \u0026ndash; review \u0026amp; editing; \u003cstrong\u003eRP:\u003c/strong\u003e Writing \u0026ndash; review \u0026amp; editing; \u003cstrong\u003eRB:\u003c/strong\u003e Writing \u0026ndash; review \u0026amp; editing; \u003cstrong\u003eEVJ:\u003c/strong\u003e Writing \u0026ndash; review \u0026amp; editing; \u003cstrong\u003eSM(Majumder):\u003c/strong\u003e Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eS. Mahanty thanks Science \u0026amp; Engineering Research Board (SERB) for providing the fellowship of National Post Doctoral Fellowship (Sanction Number: PDF/2023/001221) during the tenure of this research and Department of Atomic Energy (DAE) (Letter No. SINP/Estt. /B\u0026amp;SG/Appt./2022) for providing the Research Associate fellowship.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the data present in the manuscript and its associated supplementary file.\u003c/p\u003e\n\u003cp\u003eEthics Approval: Not applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResearch Involving Humans and Animals Statement: None.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInformed Consent: None.\u003c/p\u003e\n\u003cp\u003eConflict of interest: The authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdeleye, A. T., Bahar, M. 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Evaluation of thermodynamic parameters for adsorption of heavy metals by green adsorbents. \u003cem\u003eEnvironmental Chemistry Letters\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(2), 697\u0026ndash;704. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/S10311-018-00819-Z/TABLES/1\u003c/span\u003e\u003cspan address=\"10.1007/S10311-018-00819-Z/TABLES/1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable I:\u003c/strong\u003eThe numeric factors and the values of different points used in the study\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymbol\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnits\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactorial points\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAxial points\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e-1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e+1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAdsorbent Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emg/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTemp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026deg;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e10.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003etime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable II:\u003c/strong\u003e Comparative analysis of the thermodynamic parameters for the adsorption of NPs and Cr ions by mycosynthesized IO-NPs and IO-NPs+C\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdsorbent\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeavy metals\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTemperature (K)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;\u003cem\u003eG\u003c/em\u003e\u003csup\u003e0\u003c/sup\u003e (KJ/mol)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;H (KJ/mol)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;S (J/K mol)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 141px;\"\u003e\n \u003cp\u003eIO-NPs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 133px;\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 158px;\"\u003e\n \u003cp\u003e-1.54565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 158px;\"\u003e\n \u003cp\u003e89.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 155px;\"\u003e\n \u003cp\u003e316.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 158px;\"\u003e\n \u003cp\u003e-5.7021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 158px;\"\u003e\n \u003cp\u003e-7.8231\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 133px;\"\u003e\n \u003cp\u003eNPs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 158px;\"\u003e\n \u003cp\u003e-1.52446\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 158px;\"\u003e\n \u003cp\u003e73.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 155px;\"\u003e\n \u003cp\u003e255.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 158px;\"\u003e\n \u003cp\u003e-4.31708\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 158px;\"\u003e\n \u003cp\u003e-8.41853\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 141px;\"\u003e\n \u003cp\u003eIO-NPs+C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 133px;\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 158px;\"\u003e\n \u003cp\u003e-0.53861\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 158px;\"\u003e\n \u003cp\u003e102.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 155px;\"\u003e\n \u003cp\u003e361.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 158px;\"\u003e\n \u003cp\u003e-2.14662\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 158px;\"\u003e\n \u003cp\u003e-5.69839\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 133px;\"\u003e\n \u003cp\u003eNPs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 158px;\"\u003e\n \u003cp\u003e-2.18478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 158px;\"\u003e\n \u003cp\u003e97.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 155px;\"\u003e\n \u003cp\u003e343.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 158px;\"\u003e\n \u003cp\u003e-3.99941\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 158px;\"\u003e\n \u003cp\u003e-9.48848\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003c/table\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bionanoscience","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnsc","sideBox":"Learn more about [BioNanoScience](http://link.springer.com/journal/12668)","snPcode":"12668","submissionUrl":"https://submission.nature.com/new-submission/12668/3","title":"BioNanoScience","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Nanocomposite, Adsorption, Chromium, Nanoplastics, Bioremediation, Iron oxide, Fungi","lastPublishedDoi":"10.21203/rs.3.rs-7609084/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7609084/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This study presents the eco-friendly synthesis and application of iron oxide nanoparticles (IO-NPs) and a chitosan-based iron oxide nanocomposite (IO-NPs+C) for removing chromium (Cr) ions and nanoplastics (NPs) from contaminated water. For the first time, Aspergillus iranicus, a fungal isolate from the Indian Sundarbans mangrove ecosystem, was employed for the green synthesis of superparamagnetic iron oxide nanoparticles (SPIONs), aligning with sustainable chemistry principles. TEM and XRD analyses confirmed their spherical morphology and size range of 10–50 nm. The nanocomposite exhibited significantly enhanced adsorption efficiency compared to IO-NPs alone, achieving equilibrium capacities of 195.20 mg/g (Cr) and 190.50 mg/g (NPs) under optimal conditions (pH 2, 35°C, 100 mg/L dosage, 120 min contact). Langmuir isotherm fitting suggested monolayer adsorption, with maximum capacities exceeding 500 mg/g (Cr) and 250 mg/g (NPs). Process optimization through Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) revealed a highly efficient removal (92.68% Cr and 97.89% NPs) at optimized conditions of 99.98 mg/L IO-NPs+C, pH 6.8, and 35°C. Field validation using groundwater near a Chromite Ore Processing Residue (COPR) site (Cr: 12.68 ± 1.2 mg/L, spiked NPs: 20 mg/L) showed 93.39% removal of both contaminants with 100 mg/L of IO-NPs+C at pH 7.6 and 313 K within 120 minutes. The IO-NPs+C outperformed IO-NPs alone, establishing its promise as a sustainable and high-performance solution for simultaneous Cr and NP remediation in wastewater treatment.","manuscriptTitle":"Green-Synthesized Iron Oxide-Chitosan Nanocomposite for Chromium and Nanoplastics Remediation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-29 08:26:38","doi":"10.21203/rs.3.rs-7609084/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-11T07:16:55+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-28T07:07:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"152449466861547702579781643802683991059","date":"2025-10-18T11:28:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"184354153661826529514888084020204683734","date":"2025-10-16T07:13:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-16T00:50:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-22T14:20:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-22T11:47:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"BioNanoScience","date":"2025-09-13T18:40:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bionanoscience","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnsc","sideBox":"Learn more about [BioNanoScience](http://link.springer.com/journal/12668)","snPcode":"12668","submissionUrl":"https://submission.nature.com/new-submission/12668/3","title":"BioNanoScience","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"49f651be-0987-4117-8c7d-e791b34d2fcc","owner":[],"postedDate":"October 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-30T10:23:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-29 08:26:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7609084","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7609084","identity":"rs-7609084","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}