Chitosan Eco-Friendly Approach to Oil Spill Cleanup: A Combined 2D TD-NMR Relaxation and Computational Modeling Study

Chitosan Eco-Friendly Approach to Oil Spill Cleanup: A Combined 2D TD-NMR Relaxation and Computational Modeling Study | 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 Chitosan Eco-Friendly Approach to Oil Spill Cleanup: A Combined 2D TD-NMR Relaxation and Computational Modeling Study Flavio Kock, Jesus Valdiviezo, Erick Cirilo, Jorge Sifuentes, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7622729/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Jan, 2026 Read the published version in Journal of Polymers and the Environment → Version 1 posted 19 You are reading this latest preprint version Abstract This study elucidates the molecular interactions governing the destabilization of petroleum emulsions by chitosan, using 2D Time-Domain Nuclear Magnetic Resonance (TD-NMR) relaxometry and molecular docking simulations. To that end, we applied a commercial medium molecular weight chitosan (75.50% deacetylated, 7.25 x 10⁴ g/mol) to a series of six petroleum emulsions, which exhibited viscosities ranging from 32.52 to 103.95 mm²/s at 20°C. Our findings demonstrate chitosan's ability to flocculate petroleum emulsions by primarily interacting with water molecules, subsequently affecting the oil phase. Molecular docking simulations confirmed that chitosan binds most strongly to water molecules (via hydrogen bonds) and exhibits only minor interactions with naphthalenes and paraffins (via London dispersion forces). This observation suggests that chitosan's preferential water binding disrupts the oil-water interface and destabilizes the surfactant layer, thereby promoting emulsion breakdown. Marked shifts in T₂ relaxation times that correlate with water content evidence chitosan’s water-centric binding mechanism. Our analysis highlights chitosan’s role as an effective adsorbent for petroleum pollutants, advancing polymer science for addressing crucial environmental remediation challenges. Graphical Abstract Chitosan Petroleum Emulsions TD-NMR Relaxometry Molecular Docking Emulsion Destabilization Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Highlights 2D TD-NMR relaxometry was used to investigate the molecular interactions between chitosan and petroleum emulsions. Chitosan effectively flocculated petroleum emulsions from seawater by interacting with both water molecules and the oil phase. 2D D-T2 maps revealed significant alterations in the molecular environments of both water and oil phases upon chitosan addition. Chitosan's interaction with the oil-water interface disrupted the surfactant layer, destabilizing the emulsion. Molecular docking simulations confirmed strong interactions between chitosan and key petroleum components, as paraffins via London dispersion forces and naphthalenes through polar hydrogen-π (Hp-π) and hydrogen bonds with water molecules. 1. Introduction Chitosan is a versatile biopolymer derived from chitin, the second most abundant natural polysaccharide. It is composed of a linear chain of repeating units of glucosamine and N-acetyl glucosamine, linked together by β(1,4) glycosidic bonds [ 1 , 2 ]. This structure gives chitosan unique properties, including biocompatibility, biodegradability, and antimicrobial activity[ 3 ]. The production of chitosan involves the alkaline deacetylation of chitin, a process characterized by the removal of acetyl groups [ 4 ]. This process alters the chemical properties of chitin, making it more soluble and reactive, and opening up a wide range of potential applications in various fields, such as medicine, agriculture, and environmental science [ 5 – 7 ]. Into the environmental science scope, wastewater contaminated with oil poses a significant threat to aquatic ecosystems, soil health, and human well-being [ 8 ]. Oil spills, industrial effluents, and accidental releases can introduce harmful hydrocarbons into water bodies, disrupting ecosystems, harming wildlife, and compromising water quality [ 9 , 10 ]. Therefore, to address this pressing issue, researchers have turned their attention to exploring innovative solutions, such as the use of biopolymers like chitosan [ 11 ]. Hence, by understanding the interactions between chitosan and oil, scientists aim to develop effective strategies for removing and degrading oil pollutants, thereby mitigating the environmental impact of wastewater contamination. This is particularly relevant given that chitosan's oil adsorption mechanism involves a combination of physical and chemical interactions. Physically, the large surface area of chitosan, replete with pores and functional groups, could facilitate van der Waals forces with oil molecules [ 12 , 13 ]. Chemically, the amino and hydroxyl groups in chitosan engage in hydrogen bonding with polar components present in oil. Additionally, hydrophobic regions within chitosan can promote partitioning of oil molecules into complex matrices, as petroleum-water emulsions [ 2 , 14 ]. Accordingly, to gain a deeper understanding of the mechanisms underlying chitosan's oil adsorption capabilities, various spectroscopic techniques can be employed. These techniques offer valuable insights into the structural changes and interactions occurring at the molecular level. Key techniques include Fourier Transform Infrared (FTIR) spectroscopy, Nuclear Magnetic Resonance (NMR) spectroscopy, X-ray Photoelectron Spectroscopy (XPS), and Raman spectroscopy. Specifically, FTIR can identify functional groups involved in adsorption and detect intermolecular interactions through spectral changes [ 15 ]. Similarly, NMR provides detailed molecular structure information and reveals intermolecular interactions [ 16 ]. Furthermore, XPS analyzes surface composition and identifies specific functional groups involved in adsorption [ 17 ]. Finally, Raman spectroscopy provides information about molecular vibrations and detects intermolecular interactions through changes in vibrational modes [ 18 ]. Therefore, with the combination of these techniques, researchers can gain a comprehensive understanding of the intricate intermolecular interactions between chitosan and oil molecules, driving the development of more efficient and effective oil adsorbents. Building upon this comprehensive analytical framework, and to further elucidate the molecular interactions, flexible docking simulations using DOCKER [ 19 ] and the GFN2-xTB [ 20 ] semiempirical quantum mechanical method were employed. These simulations investigated the interaction between chitosan and the predominant components in light (paraffins) and heavy (naphthalenes) petroleum fractions, as well as with water molecules. Concurrently, in conjunction with the two-dimensional relaxometric approach, this study provided an insight into the complex interactions between chitosan and real-world petroleum emulsions, that ultimately elucidated the physicochemical mechanisms governing emulsion stability and demulsification efficiency, offering potential avenues for optimizing biopolymer-based emulsion breaking technologies through a comprehensive understanding of interfacial dynamics and molecular mobility within these multiphase systems. Herein, we demonstrate that the interactions between chitosan and petroleum emulsions during the flocculation process can be investigated using pulse sequences that simultaneously acquire transverse relaxation times (T 2 ) and self-diffusion coefficients (D) in a benchtop NMR spectrometer. This dual-pronged approach, particularly when coupled with molecular docking tools, offers significant advantages, including the non requirement of cryogenics, deuterated solvents and reduced analysis time [ 21 ]. Our results show that chitosan’s flocculation of petroleum emulsions stems from its strong affinity for water molecules. A robust hydrogen-bond network between the biopolymer’s amino and hydroxyl groups and water dictates chitosan’s conformation in solution and drives its flocculation activity. Although chitosan can also form secondary polar hydrogen-π interactions with naphthalenes and weaker van der Waals contacts with paraffins, these hydrocarbon interactions merely support the dominant water-binding mechanism that enables efficient oil–water separation. 2. Materials and Methods 2.1. Chitosan Sample A commercial medium-weight chitosan (CAS Number: 9012-76-4) powder (75.50% deacetylated, 7.25×10 4 g/mol) was obtained from Sigma-Aldrich, Brazil. Its molecular weight and degree of deacetylation were subsequently determined via 1 H-NMR and viscosimetric measurements, respectively, as per the methodologies outlined by Kassai in 2007 and 2008. [ 22 , 23 ] 2.2. Petroleum emulsions samples For the petroleum emulsion adsorption experiments, 0.25 g of chitosan was utilized. The study employed 25 g of six distinct petroleum emulsions derived from Brazilian crude oils. The fundamental characterization of these emulsions was conducted by the Laboratory for Petroleum Research at the Federal University of Espírito Santo (LabPetro), Brazil. Initially, any free water present in the original samples was removed via a simple decantation process. Subsequently, the samples underwent analysis for bottom sediments and water content (BS&W), adhering to the ASTM D4007 standard [ 24 ]. The results of these analyses were expressed as a percentage (v/v). The API gravity of the samples was calculated according to the ASTM D4052 standard [ 25 ]. This index provides insights into the nature of petroleum emulsions. API gravity values lower than 22.3 indicate a high proportion of heavy fractions, such as naphthenes, in the oil matrix. Conversely, higher API gravity values (> 22.3) suggest a higher concentration of lighter fractions, such as paraffins. The viscosity and density measurements were conducted at 20°C at LabPetro, adhering to the ASTM D-445-06 standard [ 26 ]. Furthermore, Table 1 provides a comprehensive overview of the physicochemical properties of the petroleum samples analyzed in this investigation. Kinematic viscosity measurements (ASTM D445) ranged from 32.521 mm 2 /s to 182.07 mm 2 /s. Concurrently, the API gravity (ASTM D287) of the samples varied between 22.3 º and 29.2 º . Furthermore, basic sediment and water (BS&W) content (ASTM D4007) ranged from 0.20% (v/v) to 20.00% (v/v). Finally, density(ASTM D5002) measurements were observed to range from 0.8770 g⋅cm − 3 to 0.9164 g⋅cm − 3 . Table 1 Physical-chemical properties of petroleum emulsions. Sample ºAPI BSW (v/v) Density (g.cm − 3 ) Viscosity (mm 2 .s − 1 ) 1 29.2 3.60 0.8770 32.829 2 28.0 20.00 0.8832 79.215 3 28.8 3.40 0.8789 32.521 4 27.5 4.40 0.8859 103.95 5 22.3 0.20 0.9164 182.07 6 28.1 18.00 0.8828 69.115 2.3. Time Domain NMR Measurements The NMR measurements were performed in a Maran Ultra-2 NMR spectrometer, Oxford Instruments Ltd. (Abingdon, Oxfordshire, England), operating at a Larmor frequency of 2.2 MHz for hydrogen nuclei ( 1 H) in a 52 mT magnetic field. Two-dimensional diffusion- transverse relaxation (D-T 2 ) experiments were performed at 28°C using pulsed-field gradient Stimulated Echo (PFG-STE) technique. The acquisition parameters included a pre-gradient duration (D1) of 20.0 ms, a pulse interval (τ) of 11.0 ms, a gradient pulse duration (δ) of 10.0 ms, a gradient interval (Δ) of 22.0 ms, and 32,768 echoes (NECH). Eight scans (NS) were acquired, and nine gradient intensity (G) values were applied linearly from 0 to 32 G/cm. The D values were calculated using MATLAB® 7.0 software. All analyses were performed in triplicate, and the mean values were reported. Petroleum emulsion samples were analyzed using two-dimensional NMR pulse sequences. The first dimension employed the Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence to determine T 2 relaxation times, while the second dimension utilized the Pulsed Field Gradient Stimulated Echo (PFG-STE) sequence [ 27 , 28 ], for the determination of the diffusion coefficient (D). The sequence depicted in Fig. 1 involves the application of a π/2 pulse to transfer magnetization to the transverse plane. Following a delay time (D1), a gradient pulse with intensity G and duration δ is applied to the sample. A subsequent π/2 pulse is applied, transferring the magnetization to the z-axis, thereby minimizing the influence of transverse magnetization on the measurements. A time τ is allowed to elapse, followed by the application of another π/2 pulse and a gradient (G) pulse of the same intensity and duration. This sequence results in the formation of an echo. Subsequently, a train of 180° pulses is applied n times along the y-axis, with a time interval of 2τ between each pulse, to obtain a T 2 decay [ 27 ]. Therefore, several experiments were conducted by varying the gradient (G) intensity. The magnetization as a function of time follows the Eq. (1) [ 29 , 30 ]. \(\:M\left(t\right)=\:{\int\:}_{{T}_{2min}}^{{T}_{2max}}.{\int\:}_{{D}_{min}}^{{D}_{max}}{e}^{{-\gamma\:}^{2}.{g}^{2}.{\delta\:}^{2}.D.\left(\varDelta\:-\frac{\delta\:}{3}\right)}{e}^{-\frac{t}{{T}_{2}}}\) F(D,T 2 )dDdT 2 + ε(t) (1) where ε(t) is the experimental noise, the function F(D,T 2 ) correspond to diffusion coefficients and transverse relaxation times (T 2 ) distribution (these values will be determined in the experiment) and the terms \(\:{e}^{{-\gamma\:}^{2}.{g}^{2}.{\delta\:}^{2}.D.\left(\varDelta\:-\frac{\delta\:}{3}\right)}\) and \(\:{e}^{-\frac{t}{{T}_{2}}}\) are denominated Kernel for diffusion and T 2 , respectively. To obtain the two-dimensional maps, the experimental data were processed using the SDR methodology developed by Schlumberger-Doll Research Center, implemented in MATLAB®. The processing method is based on the general Eq. (2): \(\:M\left(t\right)=\:{\iint\:}_{}^{}{K}_{1}\left(x,{\tau\:}_{1}\right){K}_{2}\left(y,{\tau\:}_{2}\right)F\left(x,y\right)dx\) dy + ε (t) (2) This equation can be simplified into matrix form, as represented by Eq. ( 3 ): $$\:M=\:{K}_{1}F{K}_{2}^{{\prime\:}}+E$$ 3 Where the matrices K1, K2, and F are the discretized versions of k1, k2, and F(x,y), respectively. The inversion of Eq. 3 is an ill-posed mathematical problem, meaning that small fluctuations in the experimental data (M) can lead to significant errors in F(x,y). To address this issue, various approaches have been explored. One common approach involves fitting the data to a simplified equation, such as Eq. ( 4 ): $$\:\left|\left|M-{K}_{1}F{K}_{2}^{{\prime\:}}\right|{|}^{2}+\:\alpha\:\right|\left|F\right|{|}^{2\:}$$ 4 where the second term corresponds to Tikhonov regularization, with its amplitude controlled by the α parameter. The choice of α significantly influences the resulting distribution curves and should be carefully selected to avoid introducing bias. The SDR algorithm also employs singular value decomposition (SVD) to extract the principal components K1 and K2, reducing computational costs. 2.4. Molecular docking simulations Flexible docking simulations used a 4-mer chitosan as the receptor constructed from a figshare PDB structure[ 31 ]. We selected naphthalene, a 12-carbon aliphatic chain representing paraffin and water as ligands. Chitosan was modelled in its deprotonated form because seawater pH is closer to 8.1[ 32 ], which lies above chitosan’s pKa of 6.3[ 33 ]. DOCKER from ORCA 6.0.1 [ 19 ] employing the GFN2-xTB semi-empirical quantum chemistry method [ 20 ], was used to evaluate binding geometries and interaction energies. We applied the ddCOSMO solvation model[ 34 ] to account for the dielectric effect of seawater. Ligand efficiency was computed by dividing the DOCKER interaction energy by the number of heavy atoms[ 35 , 36 ]. 2.5. Molecular dynamics simulations The system composed of chitosan, naphthalene, and paraffin was parameterized using GAFF2 with Antechamber [ 37 ] and Parmchk2 (AmberTools25). In LEaP, chitosan was placed at the center of the structure, and the surrounding organic molecules were positioned to avoid overlaps. The system was solvated in a truncated octahedral TIP3P water box [ 38 ], adjusting the ionic strength to 0.15 M. The geometry was relaxed through three consecutive energy minimization steps with decreasing restraints on chitosan, allowing the solvent and ions to accommodate and prevent strains [ 39 , 40 ]. Subsequently, the system underwent heating, followed by NVT and NPT equilibration with progressively decreasing restraints on chitosan, aimed at stabilizing pressure and density. Finally, a production molecular dynamics simulation was performed using OpenMM for 50 ns at 300 K and 1 atm with a 2 fs timestep [ 40 ]. 3. Results and Discussions Chitosan, a biodegradable and renewable polymer derived from chitin, has emerged as a promising adsorbent for removing petroleum pollutants from seawater [ 41 ]. Its unique properties, including high adsorption capacity, biodegradability, and non-toxicity, make it an attractive alternative to traditional methods [ 13 , 17 , 18 ]. The separation of petroleum from seawater driven by chitosan, as depicted in Fig. 2 , is highly efficient through a water-selective mechanism. Chitosan's porous structure and high surface area, abundant with amino and hydroxyl groups, create multiple binding sites that demonstrate strong preferential affinity for water molecules over petroleum components [ 18 , 31 ]. This water-selective binding drives oil-water phase separation by forming a hydrated chitosan network that excludes petroleum droplets from the aqueous environment. Additionally, chitosan simultaneously purifies the seawater by complexing with dissolved metal ions, such as heavy metal ions (Pb 2+ , Cd 2+ , Hg 2+ ) and transition metals ions (Fe 3+ , Cu 2+ , Ni 2+ ), thereby enhancing both the separation efficiency and water quality improvement[ 41 , 42 ]. To elucidate the influence of chitosan on the molecular dynamics of seawater, two-dimensional nuclear magnetic resonance (NMR)self-diffusion coefficient (D) and transverse relaxation times (T 2 ), was employed. Figure 3 a presents the D-T 2 contour plot for the untreated seawater sample (blank sample), which exhibits a strong signal at approximately 1 s (T2) and 10 − 9 mm 2 /s (D) This T2 and D values align with the expected values of molecular mobility of free water molecules at room temperature [ 27 ]. Figure 3 b displays the D-T 2 contour plot for the chitosan-treated seawater sample. This figure shows that the addition of chitosan to a seawater sample significantly alters the T 2 relaxation times, causing a pronounced shift from 10 0 s down to as low as 10 − 3 s. This change, clearly visible in the contour plot, indicates a major modification of the system's molecular dynamics compared to the blank seawater. The observed shift likely results from a combination of factors, including reduction in molecular tumbling, increased local viscosity, and the formation of supramolecular structures or interactions between the chitosan and the components of the seawater [ 27 , 43 ]. Additionally, the analysis of the seawater without chitosan ( Fig. 3 a ) revealed a higher degree of molecular mobility, as evidenced by demonstrably lower molecular correlation times (τ c ). This finding is consistent with established literature regarding the dynamics of small molecules in aqueous solutions [ 28 ]. Such heightened mobility is anticipated in systems characterized by smaller molecular constituents and lower bulk viscosity, which facilitate more rapid molecular tumbling rates and consequently lead to elevated transversal relaxation (T 2 ) times (10 0 s) and diffusion (D) coefficients (10 − 9 mm 2 .s − 1 ). Moreover, interestingly, the measured T 2 values for seawater (T 2 ≈ 1.0 s) were observed to be notably lower than those obtained for distilled water (T 2 = 2.7 s)[ 21 ]. This observed reduction in T 2 relaxation time can be primarily associated with the presence of dissolved inorganic salts within the seawater matrix [ 44 ]. The free electrons of the paramagnetic ions, present in seawater salts, are relaxing agents reducing the water T 2 [ 45 – 47 ]. This phenomenon is in agreement with numerous prior investigations that have unequivocally demonstrated the impact of paramagnetic ions on proton relaxation mechanisms in low-field NMR experiments [ 44 – 46 ]. Furthermore, the analysis of Fig. 3 b reveals a significant perturbation of the aqueous chemical microenvironment upon the introduction of chitosan. Specifically, the observed reduction in the transverse (T 2 ) relaxation time of water, reaching a minimum value of approximately 10 − 3 s, is indicative of the formation of chitosan-water complexes. These complexes give rise to distinct microscopic domains wherein the molecular dynamics of water molecules are substantially restricted. However, despite localized molecular immobilization, the self-diffusion coefficient (D) of water molecules remains largely unaltered (10 − 9 mm 2 .s − 1 ). This suggests that the macroscopic, long-range diffusional behavior of water within the bulk solution is not significantly impeded. Consequently, while the local environment of water molecules within the chitosan polymeric network is demonstrably modified, their overall translational mobility across greater distances remains relatively unaffected. Overall, these results suggest that chitosan selectively interacts with a specific subset of water molecules, forming hydrogen bonds with their hydroxyl groups. This interaction restricts the rotational and translational motion of these bound water molecules, leading to a significant decrease in their T 2 relaxation time. However, a considerable portion of water molecules remain unaffected by the presence of chitosan, as indicated by the persistence of a spin population with T 2 ​values approaching 1.00 s and D values of 10 − 9 mm²/s. These results are consistent with the literature, which indicates that hydrogen bonding interactions between chitosan's hydroxyl groups and water molecules contribute to reduced T 2 ​relaxation times in similar systems [ 48 ]. Figure 4 . 2D D-T 2 correlation maps illustrating the effect of adding 0.25 g of chitosan to various 25 g petroleum emulsion samples. For each emulsion type, the figures [(a), (c), (e), (g), (i), (k)] show the sample before chitosan addition, while the corresponding figures [(b), (d), (f), (h), (j), (l)] display the sample after chitosan addition. Figure 4 a shows the initial D − T 2 map of sample 1 before chitosan addition, revealing a single chemical environment. This environment is characterized by T 2 values spanning 10 − 1 to 10 0 s and a self-diffusion coefficient (D) of approximately 10 − 10 mm²/s². These parameters are characteristic of an oil-dominated phase. The absence of a discernible distinct water phase in Fig. 1 a is consistent with its low basic sediment and water (BSW) content of 3.60%. Upon the incorporation of chitosan (Fig. 4 b), a novel chemical environment becomes apparent in the D − T 2 ​ map of sample 1(a). This newly formed environment exhibits T 2​ values exceeding 10 − 1 s and D values approximating 10 − 9 mm²/s². The emergence of this distinct phase, with relaxation and diffusion characteristics more akin to those of water, suggests a significant interaction between chitosan and the oil phase. This interaction may involve mechanisms such as adsorption of chitosan onto oil droplets or complexation with oil components [ 17 , 41 , 49 , 50 ], thereby altering the interfacial properties and creating a new microenvironment with an increased effective water-like mobility. This finding aligns with established literature that reports chitosan's capacity to interact with hydrocarbons and modify their physical properties within emulsion systems [ 41 , 49 ]. For sample 2 (Fig. 4 c), the initial D − T 2​ map reveals the presence of two distinct water environments. One of these environments is located in closer proximity to the oil phase and is characterized by a relatively higher T 2 ​ value, indicating a greater degree of molecular mobility and larger effective domain size. The second water environment exhibits both higher D and T 2​ values, signifying an increased diffusion coefficient and relaxation time, and is spatially separated from the oil phase. Interestingly, upon the introduction of chitosan, the impact on sample 2 (Fig. 4 d) is less pronounced compared to sample 1 (Fig. 4 a). The primary effect observed is an increase in both the intensity and spatial extent of the water-rich environment. This suggests that chitosan may be promoting the aggregation or coalescence of water domains within the emulsion. Furthermore, a slight coalescence between the water and oil phases is noted (Fig. 4 d), indicating a potential alteration of the interfacial tension or stabilization characteristics of the emulsion. Therefore, these D − T 2 ​ relaxation data indicate that chitosan primarily interacts with the aqueous phase of the emulsion. This interaction is plausibly mediated by hydrogen bonding between the hydroxyl and amine functionalities of chitosan and water molecules. Such interactions typically lead to a reduction in the translational and rotational mobility of associated water molecules, which would be evidenced by a decrease in their T 2 ​ relaxation times [ 46 , 48 ]. Concurrently, the observed augmentation in the signal intensity and/or population of the less-restricted aqueous component (characterized by comparatively longer T 2 ​ values) can be further elucidated by considering the metal complexation capabilities of chitosan [ 46 ]. Specifically, at pH values exceeding its pKa of approximately 6.3, chitosan's amine groups become deprotonated, enabling them to act as effective chelating agents [ 12 , 46 ]. This allows chitosan to bind to and sequester various metal ions (e.g., paramagnetic metal ions) that may be present in the aqueous phase of the petroleum emulsion. The removal or inactivation of these paramagnetic species from the bulk water effectively mitigates their contribution to proton relaxation enhancement, thereby resulting in an apparent increase in the T 2 ​ relaxation times of the water environment from which they were removed. This dual mechanism—direct interaction leading to some water restriction and metal chelation reducing paramagnetic relaxation—contributes to the complex changes observed in the D − T 2 ​​ maps of the aqueous phases. Furthermore, samples 3 (Figs. 4 e, f ) , 4 (Figs. 4 g, h), and 5 (Figs. 4 i, j) consistently exhibit analogous trends in their physicochemical response to chitosan introduction. Specifically, for sample 4 (Fig. 4 g), characterized by a comparatively elevated water content, the addition of chitosan notably induces the formation of a novel, water-like chemical environment as delineated by D − T 2 ​ relaxation mapping (Fig. 4 (h)). This observation strongly suggests a high interaction of chitosan with the aqueous phase within the emulsion system. Further substantiating this affinity for water-rich environments is the attenuated impact of chitosan on sample 5 (Figs. 4 i, j). This sample exhibits a significantly diminished water content, with a basic sediment and water (BSW) value of merely 0.20%. The minimal perturbation observed in sample 5's D − T 2 ​​ signature following chitosan addition underscores the critical role of water content as a determinant in modulating the extent of chitosan's influence on the rheological and interfacial properties of petroleum emulsions. These findings collectively emphasize that the efficacy of chitosan as an emulsion modifier is highly dependent on the initial aqueous phase volume fraction. Additionally, sample 6 (Figs. 4 k, l) exhibits a chitosan-induced behavioral pattern analogous to that observed in sample 2. In both instances, the primary influence of chitosan is localized within the aqueous phase. This interaction is hypothesized to occur predominantly via hydrogen bonding between the hydroxyl (-OH) and amine (-NH 2 ) functional groups of chitosan and water molecules [ 48 ]. Additionally, the potential for metal complexation within the aqueous phase, facilitated by chitosan's chelating capabilities, may contribute to the observed effects. Therefore, these findings strengthen the conclusion that chitosan's efficacy in modifying petroleum emulsions is highly contingent upon the water content and the specific physicochemical properties of both the oil and aqueous phases. Notably, chitosan appears to exhibit a high affinity for water-rich environments. Its ability to effectively interact with water molecules, attributed to the abundance of -OH and -NH 2 moieties on its polymeric backbone, underscores its role in altering the characteristics of the dispersed aqueous phase within these complex systems. Complementing the experimental observations, molecular docking simulations (Fig. 5 ) provide atomistic insights into the intermolecular interactions between chitosan and key components of petroleum emulsions. While raw interaction energies show that chitosan can form strong interactions with hydrocarbon components, the ligand efficiency analysis reveals that chitosan exhibits significantly higher binding efficiency per atom with water molecules (-9.32 kcal/mol) compared to naphthalenes (-1.12 kcal/mol) and paraffins (-1.03 kcal/mol), indicating that water interactions are more energetically favorable on a per-atom basis and establish the hierarchy of these molecular associations. Specifically, the simulations demonstrated that chitosan exhibits its strongest affinity for water molecules through the formation of multiple hydrogen bonds, highlighting chitosan's inherently hydrophilic nature and its primary capacity to interact with the aqueous phase of emulsions. Additionally, chitosan can form secondary interactions with naphthalene derivatives, which are characteristic components of the higher density fractions within petroleum emulsions. These interactions can present polar hydrogen-π (Hp − π) interactions between chitosan’s polar functional groups and naphthalene’s aromatic rings[ 51 ], indicating stable but less favorable complex formation compared to water binding. Finally, interactions with paraffin hydrocarbons, typically enriched in the lower density fractions of petroleum emulsions, are primarily mediated by weak dispersive forces, such as London dispersion forces. These non-covalent forces contribute minimally to the overall binding affinity, representing the weakest interactions among all three molecular systems studied. These computational findings align strongly with experimental observations from chitosan-oil systems, where Payet and Terentjev demonstrated that chitosan exhibits minimal surface activity at paraffin-water interfaces, achieving only modest reductions in interfacial tension compared to conventional surfactants[ 52 ]. Moreover, Abdulhamid et al. indicated that only hydrophobically modified chitosan-based polymers, and not unfunctionalized chitosan, act as surfactants with oil samples[ 53 ]. These experimental studies corroborate our molecular docking results showing chitosan's preferential binding efficiency for water molecules over hydrocarbon components. The weak binding affinity observed for paraffins in our simulations is further supported by molecular dynamics studies demonstrating that chitosan exhibits no measurable interactions with 1-octanol across different temperatures[ 54 ]. Regarding chitosan's interaction with aromatic compounds like naphthalene, experimental studies consistently demonstrate that chitosan requires functionalization with other groups or elements to achieve efficient removal of aromatic compounds. Studies using chitosan modified with iron oxide (FeO) and titanium dioxide (TiO₂) nanoparticles or graphene oxide have shown naphthalene adsorption capacities[ 55 , 56 ]. These enhanced performances occur primarily through interactions facilitated by the added functional groups rather than direct chitosan-naphthalene interactions. The experimental evidence supports our computational finding that while Hp-π interactions between chitosan and naphthalenes are more favorable than paraffin interactions, they remain significantly weaker than chitosan's primary affinity for water molecules, explaining why functionalization is necessary to achieve practical adsorption efficiencies for aromatic pollutants. Figure 6 a shows the snapshot corresponding to the beginning of the trajectory of the molecular dynamics simulation box. The structure of chitosan surrounded by water molecules, as well as naphthalene and paraffin molecules, can be observed. In addition, Na⁺ and Cl⁻ ions were included to maintain the ionic strength of the system. In the final snapshot (Fig. 6 b), it can be observed that both naphthalene and paraffin molecules aggregate near the chitosan chain, reinforcing that chitosan significantly alters the distribution of these molecules, as previously indicated by TD-NMR measurements. This observation is consistent with the radial distribution function (RDF) profiles shown in Fig. 7 . Water molecules display the first peaks at shorter distances from chitosan, highlighting their primary role in solvation. In contrast, naphthalene and paraffin exhibit peaks at longer distances, reflecting their aggregation close to the polymer rather than direct solvation. The sharper peak of naphthalene suggests more specific and localized interactions, which could be attributed to Hp–π interactions, as also implied by the molecular docking analysis. On the other hand, the broader peak of paraffin is consistent with weaker and nonspecific van der Waals interactions, leading to a more diffuse distribution around chitosan. Our computational findings offer a molecular-level understanding of chitosan's diverse interactions within complex petroleum systems, suggesting water affinity as the dominant driving force. This indicates how chitosan's specific attraction to aqueous environments could be key to controlling emulsion destabilization and influencing phase separation through precise intermolecular forces. The insights from this study are vital for grasping the fundamental water-binding mechanisms underlying chitosan's effectiveness in petroleum-water separation. A detailed understanding of these water-selective forces will enable the rational design of enhanced chitosan-based materials with optimized features, such as increased hydrophilic surface area for stronger water binding, enhanced porosity to accommodate larger water networks, and improved selectivity for water over hydrocarbon components, maximizing its water-selective separation capacity and environmental remediation efficiency. 4. Conclusions This study conclusively demonstrates the efficacy of chitosan in destabilizing petroleum emulsions through a multifaceted interaction mechanism elucidated by a combination of 2D (D-T 2 ) Time-Domain Nuclear Magnetic Resonance (TD-NMR) measurements and molecular docking simulations. Our findings reveal that chitosan effectively flocculates petroleum emulsions from seawater by establishing stronger interactions with aqueous phases than with oil phases. Specifically, D-T 2 maps provided compelling evidence of significant alterations in the molecular environments of both water and oil phases following chitosan addition, signifying a direct influence on the emulsion's structural integrity. This observation is attributed to chitosan's disruptive interaction with the oil-water interfacial surfactant layer, which leads to emulsion destabilization. Complementary molecular docking simulations further corroborated these experimental insights, confirming that chitosan's primary affinity lies with water molecules through strong hydrogen bonding interactions. Chitosan can also establish secondary interactions with petroleum components, including weaker (Hp-π interactions with naphthalenes and even weaker London dispersion forces with paraffins. However, these hydrocarbon interactions are significantly less favorable than the dominant water-binding mechanism. Overall, these results provide a molecular-level understanding of chitosan's ability to destabilize petroleum emulsions, underscoring its significant potential as an effective agent for environmental remediation applications. The molecular dynamics simulations reveal a clear organization of the system, where water molecules form solvation shells around chitosan, while naphthalene and paraffin preferentially aggregate at longer distances. The narrow peak of naphthalene indicates specific interactions, which could be attributed to hydrogen–π contacts, whereas the broad peak of paraffin reflects diffuse van der Waals interactions. These findings highlight the role of chitosan in governing the distribution and interactions of both polar and nonpolar species in solution, consistent with experimental observations. Declarations The authors declare no conflicts of interest. Funding This research was funded by the Pontifical Catholic University (Concurso Anual de Proyectos de Investigación PUCP 2025 - CAP 2025, projects numbers PI1287 and PI1290) and Sao Paulo Foundation Research Agency (2025/00509-8). Author Contribution F.K. and J.V. contributed equally to the conceptualization of the study and served as lead contributors for the formal analysis, investigation, and validation. F.K. led the writing of the original draft and contributed equally to its review and editing, while J.V. was the lead on the review and editing. E.C. contributed equally to the study's conceptualization, formal analysis, and validation. J.S. and A.S. provided equal contributions to the formal analysis and validation. L.B. was a lead contributor to the formal analysis and validation, and an equal contributor to the writing of the original draft. J.N. was the lead for validation and provided an equal contribution to both the writing–review and editing and supervision of the project. Finally, L.C. led the formal analysis, validation, and writing–review and editing the final version of this manuscript. Acknowledgement The authors express their gratitude to PETROBRAS for generously providing the real petroleum emulsion samples. Additionally, Dr. Valdiviezo wishes to acknowledge the DataCore facility at the Department of Engineering, PUCP, for providing the infrastructure necessary to conduct molecular simulations for this study. 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09:29:50","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":59090,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7622729/v1/6270ab10f0c70d44c2d5dc98.png"},{"id":92581852,"identity":"7de7dc2c-83a1-46c2-b87d-9f942c46d09a","added_by":"auto","created_at":"2025-10-01 09:37:51","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":473468,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7622729/v1/c71af19283c5e2b077f4989d.png"},{"id":92581853,"identity":"5b3b7ead-7474-4541-b2dd-167600c60abd","added_by":"auto","created_at":"2025-10-01 09:37:51","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":38966,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7622729/v1/8e42e7df5586455f53b2467c.png"},{"id":92581496,"identity":"7b19ca0a-996f-4165-9611-98216cfa37ad","added_by":"auto","created_at":"2025-10-01 09:29:51","extension":"xml","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":137282,"visible":true,"origin":"","legend":"","description":"","filename":"94c58fcf4ac04c10a89f42c7acd665311structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7622729/v1/1c59e8c9e0f4a4e5bdac1dc0.xml"},{"id":92581494,"identity":"93fb145e-d1bb-47e3-95c0-819ffff1711a","added_by":"auto","created_at":"2025-10-01 09:29:51","extension":"html","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":149397,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7622729/v1/2cf480e7871fa1c59ddb4d17.html"},{"id":92581469,"identity":"2ff23a61-9351-412d-ae75-2eebede94d34","added_by":"auto","created_at":"2025-10-01 09:29:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":5862,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation of the Pulsed Field Gradient Stimulated Echo (PFG-STE) pulse sequence employed for bidimensional relaxation-diffusion experiments.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7622729/v1/cbaaf1a24ff71d1de682fba1.png"},{"id":92581470,"identity":"96979a2f-07f8-4dd8-9343-6a867f09b172","added_by":"auto","created_at":"2025-10-01 09:29:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":216383,"visible":true,"origin":"","legend":"\u003cp\u003ePicture of a Petri dish containing a simulated petroleum spill in seawater (left) and the same sample after the addition of chitosan (right) demonstrating the efficiency of chitosan to accelerate oil flocculation in marine environments.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7622729/v1/92a776347edeb4a2d4299227.png"},{"id":92581848,"identity":"009c4224-da16-45c9-aaa1-8ae3fc824ac6","added_by":"auto","created_at":"2025-10-01 09:37:50","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":22800,"visible":true,"origin":"","legend":"\u003cp\u003e(a)\u003cstrong\u003e \u003c/strong\u003e2D D-T\u003csub\u003e2\u003c/sub\u003e correlation maps of a seawater sample and the same sample after the\u0026nbsp; addition (b) 0.25 g of chitosan 25 ml of seawater.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7622729/v1/7aa2793bc3527be3cfe6b856.jpg"},{"id":92581471,"identity":"b4ade118-ff7e-46f9-9b05-1c20f0910d9b","added_by":"auto","created_at":"2025-10-01 09:29:50","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":47460,"visible":true,"origin":"","legend":"\u003cp\u003e2D D-T\u003csub\u003e2\u003c/sub\u003e correlation maps illustrating the effect of adding 0.25 g of chitosan to various 25 g petroleum emulsion samples. For each emulsion type, the figures [(a), (c), (e), (g), (i), (k)] show the sample before chitosan addition, while the corresponding figures [(b), (d), (f), (h), (j), (l)] display the sample after chitosan addition.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7622729/v1/b1299b88ab1ccbecd21b8c74.jpg"},{"id":92581849,"identity":"1c1afe3d-5de2-4e01-99ca-f99243c100f1","added_by":"auto","created_at":"2025-10-01 09:37:50","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":158687,"visible":true,"origin":"","legend":"\u003cp\u003eTop-ranked interaction energies (E\u003csub\u003eint\u003c/sub\u003e) and geometries between chitosan and water, naphthalene and paraffin, predicted using DOCKER and GFN2-xTB with water as the implicit solvent via ddCOSMO. The value in parenthesis corresponds to the ligand efficiency (LE) parameter (interaction energy divided by heavy atoms).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7622729/v1/d90c52475958a83c0f4f8114.png"},{"id":92581476,"identity":"59e2494a-b11d-4843-a474-67c359a93ac1","added_by":"auto","created_at":"2025-10-01 09:29:50","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1480687,"visible":true,"origin":"","legend":"\u003cp\u003eSnapshots of simulation box highlighting chitosan in presence of water, naphtalene, paraffin and counterions (a) at the beginning and (b) after molecular dynamics.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7622729/v1/dc95e57c31b2910c1c226aad.png"},{"id":92581472,"identity":"560c71bd-c6f3-4e2f-ab03-12f337c53321","added_by":"auto","created_at":"2025-10-01 09:29:50","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":50513,"visible":true,"origin":"","legend":"\u003cp\u003eRadial distribution function (RDF) of water, naphthalene, and paraffin relative to chitosan.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7622729/v1/d3315605caad6bc5dde504f2.png"},{"id":99545445,"identity":"ad95897d-59da-4b6f-9cff-f4fdc4de0e89","added_by":"auto","created_at":"2026-01-05 16:07:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2588831,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7622729/v1/903af893-1ec0-400b-8810-be84197fd455.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Chitosan Eco-Friendly Approach to Oil Spill Cleanup: A Combined 2D TD-NMR Relaxation and Computational Modeling Study","fulltext":[{"header":"Highlights","content":"\u003col\u003e\n \u003cli\u003e2D TD-NMR relaxometry was used to investigate the molecular interactions between chitosan and petroleum emulsions.\u003c/li\u003e\n \u003cli\u003eChitosan effectively flocculated petroleum emulsions from seawater by interacting with both water molecules and the oil phase. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003e2D D-T2 maps revealed significant alterations in the molecular environments of both water and oil phases upon chitosan addition.\u003c/li\u003e\n \u003cli\u003eChitosan\u0026apos;s interaction with the oil-water interface disrupted the surfactant layer, destabilizing the emulsion.\u003c/li\u003e\n \u003cli\u003eMolecular docking simulations confirmed strong interactions between chitosan and key petroleum components, as paraffins via London dispersion forces and naphthalenes through polar hydrogen-\u0026pi; (Hp-\u0026pi;) and hydrogen bonds with water molecules.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eChitosan is a versatile biopolymer derived from chitin, the second most abundant natural polysaccharide. It is composed of a linear chain of repeating units of glucosamine and N-acetyl glucosamine, linked together by β(1,4) glycosidic bonds [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This structure gives chitosan unique properties, including biocompatibility, biodegradability, and antimicrobial activity[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The production of chitosan involves the alkaline deacetylation of chitin, a process characterized by the removal of acetyl groups [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This process alters the chemical properties of chitin, making it more soluble and reactive, and opening up a wide range of potential applications in various fields, such as medicine, agriculture, and environmental science [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eInto the environmental science scope, wastewater contaminated with oil poses a significant threat to aquatic ecosystems, soil health, and human well-being [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Oil spills, industrial effluents, and accidental releases can introduce harmful hydrocarbons into water bodies, disrupting ecosystems, harming wildlife, and compromising water quality [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Therefore, to address this pressing issue, researchers have turned their attention to exploring innovative solutions, such as the use of biopolymers like chitosan [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Hence, by understanding the interactions between chitosan and oil, scientists aim to develop effective strategies for removing and degrading oil pollutants, thereby mitigating the environmental impact of wastewater contamination.\u003c/p\u003e\u003cp\u003eThis is particularly relevant given that chitosan's oil adsorption mechanism involves a combination of physical and chemical interactions. Physically, the large surface area of chitosan, replete with pores and functional groups, could facilitate van der Waals forces with oil molecules [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Chemically, the amino and hydroxyl groups in chitosan engage in hydrogen bonding with polar components present in oil. Additionally, hydrophobic regions within chitosan can promote partitioning of oil molecules into complex matrices, as petroleum-water emulsions [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAccordingly, to gain a deeper understanding of the mechanisms underlying chitosan's oil adsorption capabilities, various spectroscopic techniques can be employed. These techniques offer valuable insights into the structural changes and interactions occurring at the molecular level. Key techniques include Fourier Transform Infrared (FTIR) spectroscopy, Nuclear Magnetic Resonance (NMR) spectroscopy, X-ray Photoelectron Spectroscopy (XPS), and Raman spectroscopy. Specifically, FTIR can identify functional groups involved in adsorption and detect intermolecular interactions through spectral changes [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Similarly, NMR provides detailed molecular structure information and reveals intermolecular interactions [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Furthermore, XPS analyzes surface composition and identifies specific functional groups involved in adsorption [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Finally, Raman spectroscopy provides information about molecular vibrations and detects intermolecular interactions through changes in vibrational modes [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Therefore, with the combination of these techniques, researchers can gain a comprehensive understanding of the intricate intermolecular interactions between chitosan and oil molecules, driving the development of more efficient and effective oil adsorbents.\u003c/p\u003e\u003cp\u003eBuilding upon this comprehensive analytical framework, and to further elucidate the molecular interactions, flexible docking simulations using DOCKER [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and the GFN2-xTB [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] semiempirical quantum mechanical method were employed. These simulations investigated the interaction between chitosan and the predominant components in light (paraffins) and heavy (naphthalenes) petroleum fractions, as well as with water molecules. Concurrently, in conjunction with the two-dimensional relaxometric approach, this study provided an insight into the complex interactions between chitosan and real-world petroleum emulsions, that ultimately elucidated the physicochemical mechanisms governing emulsion stability and demulsification efficiency, offering potential avenues for optimizing biopolymer-based emulsion breaking technologies through a comprehensive understanding of interfacial dynamics and molecular mobility within these multiphase systems.\u003c/p\u003e\u003cp\u003eHerein, we demonstrate that the interactions between chitosan and petroleum emulsions during the flocculation process can be investigated using pulse sequences that simultaneously acquire transverse relaxation times (T\u003csub\u003e2\u003c/sub\u003e) and self-diffusion coefficients (D) in a benchtop NMR spectrometer. This dual-pronged approach, particularly when coupled with molecular docking tools, offers significant advantages, including the non requirement of cryogenics, deuterated solvents and reduced analysis time [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Our results show that chitosan\u0026rsquo;s flocculation of petroleum emulsions stems from its strong affinity for water molecules. A robust hydrogen-bond network between the biopolymer\u0026rsquo;s amino and hydroxyl groups and water dictates chitosan\u0026rsquo;s conformation in solution and drives its flocculation activity. Although chitosan can also form secondary polar hydrogen-π interactions with naphthalenes and weaker van der Waals contacts with paraffins, these hydrocarbon interactions merely support the dominant water-binding mechanism that enables efficient oil\u0026ndash;water separation.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Chitosan Sample\u003c/h2\u003e\u003cp\u003eA commercial medium-weight chitosan (CAS Number: 9012-76-4) powder (75.50% deacetylated, 7.25\u0026times;10\u003csup\u003e4\u003c/sup\u003e g/mol) was obtained from Sigma-Aldrich, Brazil. Its molecular weight and degree of deacetylation were subsequently determined via \u003csup\u003e1\u003c/sup\u003eH-NMR and viscosimetric measurements, respectively, as per the methodologies outlined by Kassai in 2007 and 2008. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Petroleum emulsions samples\u003c/h2\u003e\u003cp\u003eFor the petroleum emulsion adsorption experiments, 0.25 g of chitosan was utilized. The study employed 25 g of six distinct petroleum emulsions derived from Brazilian crude oils. The fundamental characterization of these emulsions was conducted by the Laboratory for Petroleum Research at the Federal University of Esp\u0026iacute;rito Santo (LabPetro), Brazil. Initially, any free water present in the original samples was removed via a simple decantation process. Subsequently, the samples underwent analysis for bottom sediments and water content (BS\u0026amp;W), adhering to the ASTM D4007 standard [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The results of these analyses were expressed as a percentage (v/v).\u003c/p\u003e\u003cp\u003eThe API gravity of the samples was calculated according to the ASTM D4052 standard [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This index provides insights into the nature of petroleum emulsions. API gravity values lower than 22.3 indicate a high proportion of heavy fractions, such as naphthenes, in the oil matrix. Conversely, higher API gravity values (\u0026gt;\u0026thinsp;22.3) suggest a higher concentration of lighter fractions, such as paraffins. The viscosity and density measurements were conducted at 20\u0026deg;C at LabPetro, adhering to the ASTM D-445-06 standard [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFurthermore, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides a comprehensive overview of the physicochemical properties of the petroleum samples analyzed in this investigation. Kinematic viscosity measurements (ASTM D445) ranged from 32.521 mm\u003csup\u003e2\u003c/sup\u003e/s to 182.07 mm\u003csup\u003e2\u003c/sup\u003e/s. Concurrently, the API gravity (ASTM D287) of the samples varied between 22.3\u003cb\u003e\u0026ordm;\u003c/b\u003e and 29.2\u003cb\u003e\u0026ordm;\u003c/b\u003e. Furthermore, basic sediment and water (BS\u0026amp;W) content (ASTM D4007) ranged from 0.20% (v/v) to 20.00% (v/v). Finally, density(ASTM D5002) measurements were observed to range from 0.8770 g\u0026sdot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e to 0.9164 g\u0026sdot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhysical-chemical properties of petroleum emulsions.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ordm;API\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBSW (v/v)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDensity (g.cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eViscosity (mm\u003csup\u003e2\u003c/sup\u003e.s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8770\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e32.829\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8832\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e79.215\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8789\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e32.521\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e27.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8859\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e103.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9164\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e182.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8828\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e69.115\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Time Domain NMR Measurements\u003c/h2\u003e\u003cp\u003eThe NMR measurements were performed in a Maran Ultra-2 NMR spectrometer, Oxford Instruments Ltd. (Abingdon, Oxfordshire, England), operating at a Larmor frequency of 2.2 MHz for hydrogen nuclei (\u003csup\u003e1\u003c/sup\u003eH) in a 52 mT magnetic field. Two-dimensional diffusion- transverse relaxation (D-T\u003csub\u003e2\u003c/sub\u003e) experiments were performed at 28\u0026deg;C using pulsed-field gradient Stimulated Echo (PFG-STE) technique. The acquisition parameters included a pre-gradient duration (D1) of 20.0 ms, a pulse interval (τ) of 11.0 ms, a gradient pulse duration (δ) of 10.0 ms, a gradient interval (Δ) of 22.0 ms, and 32,768 echoes (NECH). Eight scans (NS) were acquired, and nine gradient intensity (G) values were applied linearly from 0 to 32 G/cm. The D values were calculated using MATLAB\u0026reg; 7.0 software. All analyses were performed in triplicate, and the mean values were reported.\u003c/p\u003e\u003cp\u003ePetroleum emulsion samples were analyzed using two-dimensional NMR pulse sequences. The first dimension employed the Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence to determine T\u003csub\u003e2\u003c/sub\u003e relaxation times, while the second dimension utilized the Pulsed Field Gradient Stimulated Echo (PFG-STE) sequence [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], for the determination of the diffusion coefficient (D). The sequence depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e involves the application of a π/2 pulse to transfer magnetization to the transverse plane. Following a delay time (D1), a gradient pulse with intensity G and duration δ is applied to the sample. A subsequent π/2 pulse is applied, transferring the magnetization to the z-axis, thereby minimizing the influence of transverse magnetization on the measurements. A time τ is allowed to elapse, followed by the application of another π/2 pulse and a gradient (G) pulse of the same intensity and duration. This sequence results in the formation of an echo. Subsequently, a train of 180\u0026deg; pulses is applied n times along the y-axis, with a time interval of 2τ between each pulse, to obtain a T\u003csub\u003e2\u003c/sub\u003e decay [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTherefore, several experiments were conducted by varying the gradient (G) intensity. The magnetization as a function of time follows the Eq.\u0026nbsp;(1) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:M\\left(t\\right)=\\:{\\int\\:}_{{T}_{2min}}^{{T}_{2max}}.{\\int\\:}_{{D}_{min}}^{{D}_{max}}{e}^{{-\\gamma\\:}^{2}.{g}^{2}.{\\delta\\:}^{2}.D.\\left(\\varDelta\\:-\\frac{\\delta\\:}{3}\\right)}{e}^{-\\frac{t}{{T}_{2}}}\\)\u003c/span\u003e\u003c/span\u003e F(D,T\u003csub\u003e2\u003c/sub\u003e)dDdT\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;ε(t) (1)\u003c/p\u003e\u003cp\u003ewhere ε(t) is the experimental noise, the function F(D,T\u003csub\u003e2\u003c/sub\u003e) correspond to diffusion coefficients and transverse relaxation times (T\u003csub\u003e2\u003c/sub\u003e) distribution (these values will be determined in the experiment) and the terms \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{e}^{{-\\gamma\\:}^{2}.{g}^{2}.{\\delta\\:}^{2}.D.\\left(\\varDelta\\:-\\frac{\\delta\\:}{3}\\right)}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{e}^{-\\frac{t}{{T}_{2}}}\\)\u003c/span\u003e\u003c/span\u003e are denominated \u003cem\u003eKernel\u003c/em\u003e for diffusion and T\u003csub\u003e2\u003c/sub\u003e, respectively.\u003c/p\u003e\u003cp\u003eTo obtain the two-dimensional maps, the experimental data were processed using the SDR methodology developed by Schlumberger-Doll Research Center, implemented in MATLAB\u0026reg;. The processing method is based on the general Eq.\u0026nbsp;(2):\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:M\\left(t\\right)=\\:{\\iint\\:}_{}^{}{K}_{1}\\left(x,{\\tau\\:}_{1}\\right){K}_{2}\\left(y,{\\tau\\:}_{2}\\right)F\\left(x,y\\right)dx\\)\u003c/span\u003e\u003c/span\u003edy\u0026thinsp;+\u0026thinsp;ε (t) (2)\u003c/p\u003e\u003cp\u003eThis equation can be simplified into matrix form, as represented by Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e3\u003c/span\u003e):\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:M=\\:{K}_{1}F{K}_{2}^{{\\prime\\:}}+E$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhere the matrices K1, K2, and F are the discretized versions of k1, k2, and F(x,y), respectively. The inversion of Eq.\u0026nbsp;\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e3\u003c/span\u003e is an ill-posed mathematical problem, meaning that small fluctuations in the experimental data (M) can lead to significant errors in F(x,y). To address this issue, various approaches have been explored. One common approach involves fitting the data to a simplified equation, such as Eq.\u0026nbsp;(\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e4\u003c/span\u003e):\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:\\left|\\left|M-{K}_{1}F{K}_{2}^{{\\prime\\:}}\\right|{|}^{2}+\\:\\alpha\\:\\right|\\left|F\\right|{|}^{2\\:}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere the second term corresponds to Tikhonov regularization, with its amplitude controlled by the α parameter. The choice of α significantly influences the resulting distribution curves and should be carefully selected to avoid introducing bias. The SDR algorithm also employs singular value decomposition (SVD) to extract the principal components K1 and K2, reducing computational costs.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Molecular docking simulations\u003c/h2\u003e\u003cp\u003eFlexible docking simulations used a 4-mer chitosan as the receptor constructed from a figshare PDB structure[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. We selected naphthalene, a 12-carbon aliphatic chain representing paraffin and water as ligands. Chitosan was modelled in its deprotonated form because seawater pH is closer to 8.1[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], which lies above chitosan\u0026rsquo;s pKa of 6.3[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. DOCKER from ORCA 6.0.1 [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] employing the GFN2-xTB semi-empirical quantum chemistry method [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], was used to evaluate binding geometries and interaction energies. We applied the ddCOSMO solvation model[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] to account for the dielectric effect of seawater. Ligand efficiency was computed by dividing the DOCKER interaction energy by the number of heavy atoms[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Molecular dynamics simulations\u003c/h2\u003e\u003cp\u003eThe system composed of chitosan, naphthalene, and paraffin was parameterized using GAFF2 with Antechamber [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and Parmchk2 (AmberTools25). In LEaP, chitosan was placed at the center of the structure, and the surrounding organic molecules were positioned to avoid overlaps. The system was solvated in a truncated octahedral TIP3P water box [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], adjusting the ionic strength to 0.15 M.\u003c/p\u003e\u003cp\u003eThe geometry was relaxed through three consecutive energy minimization steps with decreasing restraints on chitosan, allowing the solvent and ions to accommodate and prevent strains [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Subsequently, the system underwent heating, followed by NVT and NPT equilibration with progressively decreasing restraints on chitosan, aimed at stabilizing pressure and density. Finally, a production molecular dynamics simulation was performed using OpenMM for 50 ns at 300 K and 1 atm with a 2 fs timestep [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results and Discussions","content":"\u003cp\u003eChitosan, a biodegradable and renewable polymer derived from chitin, has emerged as a promising adsorbent for removing petroleum pollutants from seawater [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Its unique properties, including high adsorption capacity, biodegradability, and non-toxicity, make it an attractive alternative to traditional methods [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The separation of petroleum from seawater driven by chitosan, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, is highly efficient through a water-selective mechanism. Chitosan's porous structure and high surface area, abundant with amino and hydroxyl groups, create multiple binding sites that demonstrate strong preferential affinity for water molecules over petroleum components [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This water-selective binding drives oil-water phase separation by forming a hydrated chitosan network that excludes petroleum droplets from the aqueous environment. Additionally, chitosan simultaneously purifies the seawater by complexing with dissolved metal ions, such as heavy metal ions (Pb\u003csup\u003e2+\u003c/sup\u003e, Cd\u003csup\u003e2+\u003c/sup\u003e, Hg\u003csup\u003e2+\u003c/sup\u003e) and transition metals ions (Fe\u003csup\u003e3+\u003c/sup\u003e, Cu\u003csup\u003e2+\u003c/sup\u003e, Ni\u003csup\u003e2+\u003c/sup\u003e), thereby enhancing both the separation efficiency and water quality improvement[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo elucidate the influence of chitosan on the molecular dynamics of seawater, two-dimensional nuclear magnetic resonance (NMR)self-diffusion coefficient (D) and transverse relaxation times (T\u003csub\u003e2\u003c/sub\u003e), was employed. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea presents the D-T\u003csub\u003e2\u003c/sub\u003e contour plot for the untreated seawater sample (blank sample), which exhibits a strong signal at approximately 1 s (T2) and 10\u003csup\u003e\u0026minus;\u0026thinsp;9\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e/s (D) This T2 and D values align with the expected values of molecular mobility of free water molecules at room temperature [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb displays the D-T\u003csub\u003e2\u003c/sub\u003e contour plot for the chitosan-treated seawater sample. This figure shows that the addition of chitosan to a seawater sample significantly alters the T\u003csub\u003e2\u003c/sub\u003e relaxation times, causing a pronounced shift from 10\u003csup\u003e0\u003c/sup\u003e s down to as low as 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e s. This change, clearly visible in the contour plot, indicates a major modification of the system's molecular dynamics compared to the blank seawater. The observed shift likely results from a combination of factors, including reduction in molecular tumbling, increased local viscosity, and the formation of supramolecular structures or interactions between the chitosan and the components of the seawater [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAdditionally, the analysis of the seawater without chitosan \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea\u003cb\u003e)\u003c/b\u003e revealed a higher degree of molecular mobility, as evidenced by demonstrably lower molecular correlation times (τ\u003csub\u003ec\u003c/sub\u003e). This finding is consistent with established literature regarding the dynamics of small molecules in aqueous solutions [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Such heightened mobility is anticipated in systems characterized by smaller molecular constituents and lower bulk viscosity, which facilitate more rapid molecular tumbling rates and consequently lead to elevated transversal relaxation (T\u003csub\u003e2\u003c/sub\u003e) times (10\u003csup\u003e0\u003c/sup\u003e s) and diffusion (D) coefficients (10\u003csup\u003e\u0026minus;\u0026thinsp;9\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e.s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e\u003cp\u003eMoreover, interestingly, the measured T\u003csub\u003e2\u003c/sub\u003e values for seawater (T\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;\u0026asymp;\u0026thinsp;1.0 s) were observed to be notably lower than those obtained for distilled water (T\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;2.7 s)[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This observed reduction in T\u003csub\u003e2\u003c/sub\u003e relaxation time can be primarily associated with the presence of dissolved inorganic salts within the seawater matrix [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The free electrons of the paramagnetic ions, present in seawater salts, are relaxing agents reducing the water T\u003csub\u003e2\u003c/sub\u003e [\u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. This phenomenon is in agreement with numerous prior investigations that have unequivocally demonstrated the impact of paramagnetic ions on proton relaxation mechanisms in low-field NMR experiments [\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFurthermore, the analysis of Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb reveals a significant perturbation of the aqueous chemical microenvironment upon the introduction of chitosan. Specifically, the observed reduction in the transverse (T\u003csub\u003e2\u003c/sub\u003e) relaxation time of water, reaching a minimum value of approximately 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003es, is indicative of the formation of chitosan-water complexes. These complexes give rise to distinct microscopic domains wherein the molecular dynamics of water molecules are substantially restricted.\u003c/p\u003e\u003cp\u003eHowever, despite localized molecular immobilization, the self-diffusion coefficient (D) of water molecules remains largely unaltered (10\u003csup\u003e\u0026minus;\u0026thinsp;9\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e.s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). This suggests that the macroscopic, long-range diffusional behavior of water within the bulk solution is not significantly impeded. Consequently, while the local environment of water molecules within the chitosan polymeric network is demonstrably modified, their overall translational mobility across greater distances remains relatively unaffected.\u003c/p\u003e\u003cp\u003eOverall, these results suggest that chitosan selectively interacts with a specific subset of water molecules, forming hydrogen bonds with their hydroxyl groups. This interaction restricts the rotational and translational motion of these bound water molecules, leading to a significant decrease in their T\u003csub\u003e2\u003c/sub\u003e relaxation time. However, a considerable portion of water molecules remain unaffected by the presence of chitosan, as indicated by the persistence of a spin population with T\u003csub\u003e2\u003c/sub\u003e ​values approaching 1.00 s and D values of 10\u003csup\u003e\u0026minus;\u0026thinsp;9\u003c/sup\u003e mm\u0026sup2;/s. These results are consistent with the literature, which indicates that hydrogen bonding interactions between chitosan's hydroxyl groups and water molecules contribute to reduced T\u003csub\u003e2\u003c/sub\u003e ​relaxation times in similar systems [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. 2D D-T\u003csub\u003e2\u003c/sub\u003e correlation maps illustrating the effect of adding 0.25 g of chitosan to various 25 g petroleum emulsion samples. For each emulsion type, the figures [(a), (c), (e), (g), (i), (k)] show the sample before chitosan addition, while the corresponding figures [(b), (d), (f), (h), (j), (l)] display the sample after chitosan addition.\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea shows the initial D\u0026thinsp;\u0026minus;\u0026thinsp;T\u003csub\u003e2\u003c/sub\u003e map of sample 1 before chitosan addition, revealing a single chemical environment. This environment is characterized by T\u003csub\u003e2\u003c/sub\u003e values spanning 10\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to 10\u003csup\u003e0\u003c/sup\u003e s and a self-diffusion coefficient (D) of approximately 10\u003csup\u003e\u0026minus;\u0026thinsp;10\u003c/sup\u003e mm\u0026sup2;/s\u0026sup2;. These parameters are characteristic of an oil-dominated phase. The absence of a discernible distinct water phase in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea is consistent with its low basic sediment and water (BSW) content of 3.60%.\u003c/p\u003e\u003cp\u003eUpon the incorporation of chitosan (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb), a novel chemical environment becomes apparent in the D\u0026thinsp;\u0026minus;\u0026thinsp;T\u003csub\u003e2\u003c/sub\u003e​ map of sample 1(a). This newly formed environment exhibits T\u003csub\u003e2​\u003c/sub\u003e values exceeding 10\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e s and D values approximating 10\u003csup\u003e\u0026minus;\u0026thinsp;9\u003c/sup\u003e mm\u0026sup2;/s\u0026sup2;. The emergence of this distinct phase, with relaxation and diffusion characteristics more akin to those of water, suggests a significant interaction between chitosan and the oil phase. This interaction may involve mechanisms such as adsorption of chitosan onto oil droplets or complexation with oil components [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], thereby altering the interfacial properties and creating a new microenvironment with an increased effective water-like mobility. This finding aligns with established literature that reports chitosan's capacity to interact with hydrocarbons and modify their physical properties within emulsion systems [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFor sample 2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec), the initial D\u0026thinsp;\u0026minus;\u0026thinsp;T\u003csub\u003e2​\u003c/sub\u003e map reveals the presence of two distinct water environments. One of these environments is located in closer proximity to the oil phase and is characterized by a relatively higher T\u003csub\u003e2\u003c/sub\u003e​ value, indicating a greater degree of molecular mobility and larger effective domain size. The second water environment exhibits both higher D and T\u003csub\u003e2​\u003c/sub\u003e values, signifying an increased diffusion coefficient and relaxation time, and is spatially separated from the oil phase.\u003c/p\u003e\u003cp\u003eInterestingly, upon the introduction of chitosan, the impact on sample 2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed) is less pronounced compared to sample 1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). The primary effect observed is an increase in both the intensity and spatial extent of the water-rich environment. This suggests that chitosan may be promoting the aggregation or coalescence of water domains within the emulsion. Furthermore, a slight coalescence between the water and oil phases is noted (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed), indicating a potential alteration of the interfacial tension or stabilization characteristics of the emulsion.\u003c/p\u003e\u003cp\u003eTherefore, these D\u0026thinsp;\u0026minus;\u0026thinsp;T\u003csub\u003e2\u003c/sub\u003e​ relaxation data indicate that chitosan primarily interacts with the aqueous phase of the emulsion. This interaction is plausibly mediated by hydrogen bonding between the hydroxyl and amine functionalities of chitosan and water molecules. Such interactions typically lead to a reduction in the translational and rotational mobility of associated water molecules, which would be evidenced by a decrease in their T\u003csub\u003e2\u003c/sub\u003e​ relaxation times [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConcurrently, the observed augmentation in the signal intensity and/or population of the less-restricted aqueous component (characterized by comparatively longer T\u003csub\u003e2\u003c/sub\u003e​ values) can be further elucidated by considering the metal complexation capabilities of chitosan [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Specifically, at pH values exceeding its pKa of approximately 6.3, chitosan's amine groups become deprotonated, enabling them to act as effective chelating agents [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. This allows chitosan to bind to and sequester various metal ions (e.g., paramagnetic metal ions) that may be present in the aqueous phase of the petroleum emulsion. The removal or inactivation of these paramagnetic species from the bulk water effectively mitigates their contribution to proton relaxation enhancement, thereby resulting in an apparent increase in the T\u003csub\u003e2\u003c/sub\u003e​ relaxation times of the water environment from which they were removed. This dual mechanism\u0026mdash;direct interaction leading to some water restriction and metal chelation reducing paramagnetic relaxation\u0026mdash;contributes to the complex changes observed in the D\u0026thinsp;\u0026minus;\u0026thinsp;T\u003csub\u003e2\u003c/sub\u003e​​ maps of the aqueous phases.\u003c/p\u003e\u003cp\u003eFurthermore, samples 3 (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee, f\u003cb\u003e)\u003c/b\u003e, 4 (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eg, h), and 5 (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ei, j) consistently exhibit analogous trends in their physicochemical response to chitosan introduction. Specifically, for sample 4 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eg), characterized by a comparatively elevated water content, the addition of chitosan notably induces the formation of a novel, water-like chemical environment as delineated by D\u0026thinsp;\u0026minus;\u0026thinsp;T\u003csub\u003e2\u003c/sub\u003e​ relaxation mapping (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (h)). This observation strongly suggests a high interaction of chitosan with the aqueous phase within the emulsion system.\u003c/p\u003e\u003cp\u003eFurther substantiating this affinity for water-rich environments is the attenuated impact of chitosan on sample 5 (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ei, j). This sample exhibits a significantly diminished water content, with a basic sediment and water (BSW) value of merely 0.20%. The minimal perturbation observed in sample 5's D\u0026thinsp;\u0026minus;\u0026thinsp;T\u003csub\u003e2\u003c/sub\u003e​​ signature following chitosan addition underscores the critical role of water content as a determinant in modulating the extent of chitosan's influence on the rheological and interfacial properties of petroleum emulsions. These findings collectively emphasize that the efficacy of chitosan as an emulsion modifier is highly dependent on the initial aqueous phase volume fraction.\u003c/p\u003e\u003cp\u003eAdditionally, sample 6 (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ek, l) exhibits a chitosan-induced behavioral pattern analogous to that observed in sample 2. In both instances, the primary influence of chitosan is localized within the aqueous phase. This interaction is hypothesized to occur predominantly via hydrogen bonding between the hydroxyl (-OH) and amine (-NH\u003csub\u003e2\u003c/sub\u003e) functional groups of chitosan and water molecules [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Additionally, the potential for metal complexation within the aqueous phase, facilitated by chitosan's chelating capabilities, may contribute to the observed effects.\u003c/p\u003e\u003cp\u003eTherefore, these findings strengthen the conclusion that chitosan's efficacy in modifying petroleum emulsions is highly contingent upon the water content and the specific physicochemical properties of both the oil and aqueous phases. Notably, chitosan appears to exhibit a high affinity for water-rich environments. Its ability to effectively interact with water molecules, attributed to the abundance of -OH and -NH\u003csub\u003e2\u003c/sub\u003e moieties on its polymeric backbone, underscores its role in altering the characteristics of the dispersed aqueous phase within these complex systems.\u003c/p\u003e\u003cp\u003eComplementing the experimental observations, molecular docking simulations (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) provide atomistic insights into the intermolecular interactions between chitosan and key components of petroleum emulsions. While raw interaction energies show that chitosan can form strong interactions with hydrocarbon components, the ligand efficiency analysis reveals that chitosan exhibits significantly higher binding efficiency per atom with water molecules (-9.32 kcal/mol) compared to naphthalenes (-1.12 kcal/mol) and paraffins (-1.03 kcal/mol), indicating that water interactions are more energetically favorable on a per-atom basis and establish the hierarchy of these molecular associations.\u003c/p\u003e\u003cp\u003eSpecifically, the simulations demonstrated that chitosan exhibits its strongest affinity for water molecules through the formation of multiple hydrogen bonds, highlighting chitosan's inherently hydrophilic nature and its primary capacity to interact with the aqueous phase of emulsions. Additionally, chitosan can form secondary interactions with naphthalene derivatives, which are characteristic components of the higher density fractions within petroleum emulsions. These interactions can present polar hydrogen-π (Hp\u0026thinsp;\u0026minus;\u0026thinsp;π) interactions between chitosan\u0026rsquo;s polar functional groups and naphthalene\u0026rsquo;s aromatic rings[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], indicating stable but less favorable complex formation compared to water binding. Finally, interactions with paraffin hydrocarbons, typically enriched in the lower density fractions of petroleum emulsions, are primarily mediated by weak dispersive forces, such as London dispersion forces. These non-covalent forces contribute minimally to the overall binding affinity, representing the weakest interactions among all three molecular systems studied.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThese computational findings align strongly with experimental observations from chitosan-oil systems, where Payet and Terentjev demonstrated that chitosan exhibits minimal surface activity at paraffin-water interfaces, achieving only modest reductions in interfacial tension compared to conventional surfactants[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Moreover, Abdulhamid et al. indicated that only hydrophobically modified chitosan-based polymers, and not unfunctionalized chitosan, act as surfactants with oil samples[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. These experimental studies corroborate our molecular docking results showing chitosan's preferential binding efficiency for water molecules over hydrocarbon components. The weak binding affinity observed for paraffins in our simulations is further supported by molecular dynamics studies demonstrating that chitosan exhibits no measurable interactions with 1-octanol across different temperatures[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRegarding chitosan's interaction with aromatic compounds like naphthalene, experimental studies consistently demonstrate that chitosan requires functionalization with other groups or elements to achieve efficient removal of aromatic compounds. Studies using chitosan modified with iron oxide (FeO) and titanium dioxide (TiO₂) nanoparticles or graphene oxide have shown naphthalene adsorption capacities[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. These enhanced performances occur primarily through interactions facilitated by the added functional groups rather than direct chitosan-naphthalene interactions. The experimental evidence supports our computational finding that while Hp-π interactions between chitosan and naphthalenes are more favorable than paraffin interactions, they remain significantly weaker than chitosan's primary affinity for water molecules, explaining why functionalization is necessary to achieve practical adsorption efficiencies for aromatic pollutants.\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea shows the snapshot corresponding to the beginning of the trajectory of the molecular dynamics simulation box. The structure of chitosan surrounded by water molecules, as well as naphthalene and paraffin molecules, can be observed. In addition, Na⁺ and Cl⁻ ions were included to maintain the ionic strength of the system.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn the final snapshot (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb), it can be observed that both naphthalene and paraffin molecules aggregate near the chitosan chain, reinforcing that chitosan significantly alters the distribution of these molecules, as previously indicated by TD-NMR measurements. This observation is consistent with the radial distribution function (RDF) profiles shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. Water molecules display the first peaks at shorter distances from chitosan, highlighting their primary role in solvation. In contrast, naphthalene and paraffin exhibit peaks at longer distances, reflecting their aggregation close to the polymer rather than direct solvation. The sharper peak of naphthalene suggests more specific and localized interactions, which could be attributed to Hp\u0026ndash;π interactions, as also implied by the molecular docking analysis. On the other hand, the broader peak of paraffin is consistent with weaker and nonspecific van der Waals interactions, leading to a more diffuse distribution around chitosan.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eOur computational findings offer a molecular-level understanding of chitosan's diverse interactions within complex petroleum systems, suggesting water affinity as the dominant driving force. This indicates how chitosan's specific attraction to aqueous environments could be key to controlling emulsion destabilization and influencing phase separation through precise intermolecular forces. The insights from this study are vital for grasping the fundamental water-binding mechanisms underlying chitosan's effectiveness in petroleum-water separation. A detailed understanding of these water-selective forces will enable the rational design of enhanced chitosan-based materials with optimized features, such as increased hydrophilic surface area for stronger water binding, enhanced porosity to accommodate larger water networks, and improved selectivity for water over hydrocarbon components, maximizing its water-selective separation capacity and environmental remediation efficiency.\u003c/p\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eThis study conclusively demonstrates the efficacy of chitosan in destabilizing petroleum emulsions through a multifaceted interaction mechanism elucidated by a combination of 2D (D-T\u003csub\u003e2\u003c/sub\u003e) Time-Domain Nuclear Magnetic Resonance (TD-NMR) measurements and molecular docking simulations. Our findings reveal that chitosan effectively flocculates petroleum emulsions from seawater by establishing stronger interactions with aqueous phases than with oil phases.\u003c/p\u003e\u003cp\u003eSpecifically, D-T\u003csub\u003e2\u003c/sub\u003e maps provided compelling evidence of significant alterations in the molecular environments of both water and oil phases following chitosan addition, signifying a direct influence on the emulsion's structural integrity. This observation is attributed to chitosan's disruptive interaction with the oil-water interfacial surfactant layer, which leads to emulsion destabilization. Complementary molecular docking simulations further corroborated these experimental insights, confirming that chitosan's primary affinity lies with water molecules through strong hydrogen bonding interactions. Chitosan can also establish secondary interactions with petroleum components, including weaker (Hp-π interactions with naphthalenes and even weaker London dispersion forces with paraffins. However, these hydrocarbon interactions are significantly less favorable than the dominant water-binding mechanism. Overall, these results provide a molecular-level understanding of chitosan's ability to destabilize petroleum emulsions, underscoring its significant potential as an effective agent for environmental remediation applications.\u003c/p\u003e\u003cp\u003eThe molecular dynamics simulations reveal a clear organization of the system, where water molecules form solvation shells around chitosan, while naphthalene and paraffin preferentially aggregate at longer distances. The narrow peak of naphthalene indicates specific interactions, which could be attributed to hydrogen\u0026ndash;π contacts, whereas the broad peak of paraffin reflects diffuse van der Waals interactions. These findings highlight the role of chitosan in governing the distribution and interactions of both polar and nonpolar species in solution, consistent with experimental observations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis research was funded by the Pontifical Catholic University (Concurso Anual de Proyectos de Investigaci\u0026oacute;n PUCP 2025 - CAP 2025, projects numbers PI1287 and PI1290) and Sao Paulo Foundation Research Agency (2025/00509-8).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eF.K. and J.V. contributed equally to the conceptualization of the study and served as lead contributors for the formal analysis, investigation, and validation. F.K. led the writing of the original draft and contributed equally to its review and editing, while J.V. was the lead on the review and editing. E.C. contributed equally to the study's conceptualization, formal analysis, and validation. J.S. and A.S. provided equal contributions to the formal analysis and validation. L.B. was a lead contributor to the formal analysis and validation, and an equal contributor to the writing of the original draft. J.N. was the lead for validation and provided an equal contribution to both the writing\u0026ndash;review and editing and supervision of the project. Finally, L.C. led the formal analysis, validation, and writing\u0026ndash;review and editing the final version of this manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors express their gratitude to PETROBRAS for generously providing the real petroleum emulsion samples. Additionally, Dr. Valdiviezo wishes to acknowledge the DataCore facility at the Department of Engineering, PUCP, for providing the infrastructure necessary to conduct molecular simulations for this study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHisham F, Maziati Akmal MH, Ahmad F et al (2024) Biopolymer chitosan: Potential sources, extraction methods, and emerging applications. 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Environ Sci Pollut Res 30:27603\u0026ndash;27621. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11356-022-24198\u0026ndash;9\u003c/span\u003e\u003cspan address=\"10.1007/s11356-022-24198\u0026ndash;9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-polymers-and-the-environment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jooe","sideBox":"Learn more about [Journal of Polymers and the Environment](https://www.springer.com/journal/10924)","snPcode":"10924","submissionUrl":"https://submission.nature.com/new-submission/10924/3","title":"Journal of Polymers and the Environment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Chitosan, Petroleum Emulsions, TD-NMR Relaxometry, Molecular Docking, Emulsion Destabilization","lastPublishedDoi":"10.21203/rs.3.rs-7622729/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7622729/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study elucidates the molecular interactions governing the destabilization of petroleum emulsions by chitosan, using 2D Time-Domain Nuclear Magnetic Resonance (TD-NMR) relaxometry and molecular docking simulations. To that end, we applied a commercial medium molecular weight chitosan (75.50% deacetylated, 7.25 x 10⁴ g/mol) to a series of six petroleum emulsions, which exhibited viscosities ranging from 32.52 to 103.95 mm\u0026sup2;/s at 20\u0026deg;C. Our findings demonstrate chitosan's ability to flocculate petroleum emulsions by primarily interacting with water molecules, subsequently affecting the oil phase. Molecular docking simulations confirmed that chitosan binds most strongly to water molecules (via hydrogen bonds) and exhibits only minor interactions with naphthalenes and paraffins (via London dispersion forces). This observation suggests that chitosan's preferential water binding disrupts the oil-water interface and destabilizes the surfactant layer, thereby promoting emulsion breakdown. Marked shifts in T₂ relaxation times that correlate with water content evidence chitosan\u0026rsquo;s water-centric binding mechanism. Our analysis highlights chitosan\u0026rsquo;s role as an effective adsorbent for petroleum pollutants, advancing polymer science for addressing crucial environmental remediation challenges.\u003c/p\u003e\u003cdiv id=\"ASec1\" class=\"AbstractSection\"\u003e\u003cdiv class=\"Heading\"\u003eGraphical Abstract\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e","manuscriptTitle":"Chitosan Eco-Friendly Approach to Oil Spill Cleanup: A Combined 2D TD-NMR Relaxation and Computational Modeling Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-01 09:29:45","doi":"10.21203/rs.3.rs-7622729/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-15T16:31:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-30T10:08:02+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-30T05:06:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-30T04:04:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-29T13:24:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-28T12:35:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-23T08:45:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-23T05:45:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"43770188644978643376702717504001954030","date":"2025-09-22T12:59:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"112200316742324836817559553437134017207","date":"2025-09-22T04:38:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"288590754195312276414194308945997822198","date":"2025-09-21T20:04:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"227909184270164106539624140194089072042","date":"2025-09-21T15:43:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"240701110815753924504538088056410993540","date":"2025-09-21T02:36:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"205474028342643434918746915458599771878","date":"2025-09-20T13:42:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269011756617009145084726450677498866255","date":"2025-09-20T12:13:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-20T12:01:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-15T19:16:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-15T19:16:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Polymers and the Environment","date":"2025-09-15T16:18:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-polymers-and-the-environment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jooe","sideBox":"Learn more about [Journal of Polymers and the Environment](https://www.springer.com/journal/10924)","snPcode":"10924","submissionUrl":"https://submission.nature.com/new-submission/10924/3","title":"Journal of Polymers and the Environment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6625b001-fd99-451e-a280-6e1f3c88a6ce","owner":[],"postedDate":"October 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-05T16:04:20+00:00","versionOfRecord":{"articleIdentity":"rs-7622729","link":"https://doi.org/10.1007/s10924-025-03722-1","journal":{"identity":"journal-of-polymers-and-the-environment","isVorOnly":false,"title":"Journal of Polymers and the Environment"},"publishedOn":"2026-01-04 15:58:28","publishedOnDateReadable":"January 4th, 2026"},"versionCreatedAt":"2025-10-01 09:29:45","video":"","vorDoi":"10.1007/s10924-025-03722-1","vorDoiUrl":"https://doi.org/10.1007/s10924-025-03722-1","workflowStages":[]},"version":"v1","identity":"rs-7622729","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7622729","identity":"rs-7622729","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}