Molecular modeling investigation on mechanism of cationic dyes removal from aqueous solutions by mesoporous materials

Tackling antibiotic contaminations in wastewater with novel Modified-MOF nanostructures: A study of molecular simulations and DFT calculations

The contamination of wastewater with antibiotics has emerged as a critical global challenge, with profound implications for environmental integrity and human well-being. Adsorption techniques have been meticulously investigated and developed to mitigate and alleviate their effects. In this study, we have investigated the adsorption behaviour of Erythromycin (ERY), Gentamicin (GEN), Levofloxacin (LEVO), and Metronidazole (MET) antibiotics as pharmaceutical contaminants (PHCs) on amide-functionalized (RC (=O)NH2)/MIL-53 (Al) (AMD/ML53A), using molecular simulations and density functional theory (DFT) calculations. Based on our DFT calculations, it becomes apparent that the adsorption tendencies of antibiotics are predominantly governed by the presence of AMD functional groups on the adsorbent surface. Specifically, hydrogen bonding (HB) and van der Waals (vdW) interactions between antibiotics and AMD groups serve as the primary mechanisms facilitating adsorption. Furthermore, we have observed that the adsorption behaviors of these antibiotics are influenced by their respective functional groups, molecular shapes, and sizes. Our molecular simulations delved into how the AMD/ML53A surfaces interact with antibiotics as PHCs. Moreover, various chemical quantum descriptors based on Frontier Molecular Orbitals (FMO) were explored to elucidate the extent of AMD/ML53A adsorption and to assess potential alterations in their electronic properties throughout the adsorption process. Monte Carlo simulation showed that ERY molecules adsorb stronger to the adsorbent in acidic and basic conditions than other contaminants, with high energies: -404.47 kcal/mol in acidic and -6375.26 kcal/mol in basic environments. Molecular dynamics (MD) simulations revealed parallel orientation for the ERY molecule's adsorption on AMD/ML53A with 80% rejection rate. In conclusion, our study highlighted the importance of modeling in developing practical solutions for removing antibiotics as PHCs from wastewater. The insights gained from our calculations can facilitate the design of more effective adsorption materials, ultimately leading to a more hygienic and sustainable ecosystem.

Glutaraldehyde and terephthaldehyde-crosslinked chitosan for cationic and anionic dyes removal from aqueous solutions: Experimental, DFT, kinetic and thermodynamic studies

Novel chitosan polymers were synthesized using two cross-linkers, Glutaraldehyde and Terephthaldehyde, to enhance stability and efficiency. Characterization techniques (XRD, FTIR, FE-SEM, TGA, DTG, BJH, and BET) confirmed successful synthesis. These polymers were employed as adsorbents for removing Malachite Green (MG) and Congo Red (CR) dyes from water. Batch experiments and DFT calculations investigated the adsorption process, thermodynamics, and kinetics. Results showed the CSGT-III polymer achieved the highest removal efficiency. For initial dye concentrations ([CR]o = 50 mg/L, [MG]o = 20 mg/L) and adsorbent doses (0.8 g/L for CR, 0.4 g/L for MG), removal efficiencies were 96.99 % for CR and 99.07 % for MG. Thermodynamic analysis confirmed the spontaneous nature of adsorption, and the process was endothermic for both dyes. The Langmuir model fitted adsorption isotherms well, indicating a homogeneous surface. Kinetic analysis revealed a pseudo-second-order model for both dyes.

Combining computational tools and experimental studies towards endocrine disruptors mitigation: A review of biocatalytic and adsorptive processes

The endocrine disruptors (EDCs) are an important group of emerging contaminants, and their mitigation has been a huge challenge due to their chemistry complexity and variety of these compounds. The traditional treatments are inefficient to completely remove EDCs, and adsorptive processes are the major alternative investigated on their removal. Also, the use of EDCs degrading enzymes has been encouraged due to ecofriendly approach of biocatalytic processes. This paper highlights the occurrence, classification, and toxicity of EDCs with special focus in the use of enzyme-based and adsorptive technologies in the elimination of EDCs from ambiental matrices. Numerous prior reviews have focused on the discussions toward these technologies. However, the literature lacks theoretical discussions about important aspects of these methods such as the mechanisms of EDCs adsorption on the adsorbent surface or the interactions between degrading enzymes - EDCs. In this sense, theoretical calculations combined to experimental studies may help in the development of more efficient technologies to EDCs mitigation. In this review, we point out how computational tools such as molecular docking and molecular dynamics have to contribute to the design of new adsorbents and efficient catalytic processes towards endocrine disruptors mitigation.

Adsorption properties of metal functionalized fullerene (C59Au, C59Hf, C59Ag, and C59Ir) nanoclusters for application as a biosensor for hydroxyurea (HXU): insight from theoretical computation

This theoretical study was conducted to evaluate the efficiency of fullerene C60 and its metal functionalized nano clusters (C59Au, C59Hf, C59Ag and C59Ir) as a sensor for hydroxyurea (HXU). The various conclusions concerning the adsorption and sensing properties of the studied nano surfaces were achieved using density functional theory (DFT) at the M062X-D3/gen/LanL2DZ/def2svp level of theory. Among the nano clusters studied for this interaction, analysis of the HOMO–LUMO energy differences (E g) showed that HXU@C59Hg (H2) reflects the least energy gap of 3.042 eV, indicating its greater reactivity, sensitivity and conductivity. Also, the adsorption phenomenon in this current study is best described as chemisorptions owing to the negative adsorption enthalpies observed. Thus, the adsorption energy (E Ad) follows an increasing pattern of: HXU@C60 (C1) (−0.218 eV) < HXU@C59Ir (I1) (−1.361 eV) < HXU@C59Au (A1) (−1.986 eV) < HXU@C59Hf (H1) (−2.640 eV) < HXU@C59Hg (H2) (−3.347 eV). Least E g, highest E Ad and non-covalent nature of interaction attributed to C59Hg surface are sufficient to show that, among all studied surfaces, C59Hg surface emerged as the most suitable adsorbent for the adsorption of HXU. Hence, it can be used in modeling future adsorbent material for hydroxyurea.

Garlic peel based mesoporous carbon nanospheres for an effective removal of malachite green dye from aqueous solutions: Detailed isotherms and kinetics

Biowaste based nanoadsorbents have gained much attention in the recent times for wastewater decolourization owing to their low cost, high surface area and high adsorption capacities. In the present research, garlic peel based nanoparticles (GCNP) were synthesized at different temperatures by a one step pyrolytic green approach for the effective removal of cationic dye, malachite green from the aqueous medium. The surface properties of Garlic nanoparticles were elucidated by N₂ adsorption- desorption and all the GCNP samples were found to exhibit Type IV(a) isotherm indicating the presence of mesopores in carbon matrix. Using BET calculations, highest surface area (380 m²/g) was obtained for GCNP synthesized at 1000 ^◦C. Characterization of nanoparticles was done by XRD, EDAX, SEM and FTIR studies before and after the dye treatment. Adsorption studies conducted using different parameters like contact time, concentration and pH and dosage of adsorbent showed removal efficiency above 90% for the contact time of 70 min. Best adsorption experimental results were obtained for GCNP synthesized at 1000 °C ascribable to its high surface area, higher total pore volume (0.26 cm²/g) and higher carbon content. Four adsorption isotherm models were used to validate batch equillibrium studies and the results showed data in good agreement with Langmuir and Freundlich isotherms with maximum Langmuir adsorbtion capactiy to be 373.7 mg/g. Kinetic modelling of the data showed best fit with the Pseudo second order model with rate constant value of 48.726 g mg^-1 min^-1. Regenerative studies were conducted conducted upto 6 cycles. Also the GC nanoparticles were tested for their compatibility in membrane form wherein, removal efficiency results were obtained for GCNP anchored in polyvinyl difluoride (PVDF) and polysulfone (PSF) membrane matrix for dye adsorption.

Theoretical and experimental study of the photodegradation of methyl orange in the presence of different morphologies of Au-ZnO using Monte Carlo dynamic simulation

Herein, a simple approach was formed based on synthesizing different morphologies of ZnO and Au-ZnO as photocatalyst. In this study, ZnO and Au-ZnO were synthesized via a co-precipitation method and fully characterized via scanning electron microscopy (SEM), X-ray diffraction (XRD), and energy-dispersive X-ray spectroscopy (EDX). Three different ratios of Zn2+:OH- (1:2, 1:3, and 1:5) controlled the morphology of samples, which were made into spindle, star, and flower structures, respectively. Then, the photocatalytic activity was studied and compared. Their comparison showed that the flower morphology for ZnO and Au-ZnO was more effective in photocatalytic degradation and decolorization of methyl orange dye. Also, quantum and Monte Carlo (MC) calculations were carried out to investigate the adsorption of methyl orange (MO) molecules on ZnO(111) surface in the presence of Au or without Au in aqueous conditions by Monte Carlo adsorption locator simulations in the Materials Studio 2017 software. Au created a tendency to form a relatively strong interaction of MO with the ZnO(111) surface. The adsorption of MO on Au-ZnO(111) in the presence of Au was more significant than that of MO on ZnO(111), suggesting Au could significantly improve the reactivity of the methyl orange toward the ZnO(111).

Adsorptive removal of methylene blue dye from aqueous streams using photocatalytic CuBTC/ZnO chitosan composites

In this study, a CuBTC/ZnO chitosan composite was synthesized for the adsorptive removal of methylene blue dye from aqueous streams. Characterization techniques, namely, scanning electron microscopy, Brunauer-Emmett-Teller, Fourier transform infrared, X-ray diffraction, and thermogravimetric techniques, were used to characterize CuBTC, ZnO, and CuBTC/ZnO chitosan composites. The scanning electron microscopy images revealed the rough and porous structures of the CuBTC/ZnO chitosan composite. The composites were tested for the adsorption capacity and removal efficiency towards the methylene blue dye by varying adsorbent dosage, adsorbate concentration, pH, and contact time. The pseudo-second-order and Langmuir models were the best fit for the adsorption of methylene blue on CuBTC/ZnO chitosan composite beads, indicating that the adsorption was monolayer and chemical in nature. The equilibrium dose of the composites was 1.6 g L^-1, and the contact time was 90 min with a removal efficiency of 98.75%. The maximum adsorption capacity was 50.07 mg g^-1. Regeneration of the composites was performed to check the reusability of the synthesized CuBTC/ZnO chitosan composite beads. The active oxygenated species generated by the photocatalytic action of ZnO on the contaminated water was responsible for the degradation of methylene blue. The reported composite beads can be used for up to 5 cycles to remove methylene blue.

Neural-based modeling adsorption capacity of metal organic framework materials with application in wastewater treatment

We developed a computational-based model for simulating adsorption capacity of a novel layered double hydroxide (LDH) and metal organic framework (MOF) nanocomposite in separation of ions including Pb(II) and Cd(II) from aqueous solutions. The simulated adsorbent was a composite of UiO-66-(Zr)-(COOH)2 MOF grown onto the surface of functionalized Ni50-Co50-LDH sheets. This novel adsorbent showed high surface area for adsorption capacity, and was chosen to develop the model for study of ions removal using this adsorbent. A number of measured data was collected and used in the simulations via the artificial intelligence technique. Artificial neural network (ANN) technique was used for simulation of the data in which ion type and initial concentration of the ions in the feed was selected as the input variables to the neural network. The neural network was trained using the input data for simulation of the adsorption capacity. Two hidden layers with activation functions in form of linear and non-linear were designed for the construction of artificial neural network. The model's training and validation revealed high accuracy with statistical parameters of R2 equal to 0.99 for the fitting data. The trained ANN modeling showed that increasing the initial content of Pb(II) and Cd(II) ions led to a significant increment in the adsorption capacity (Qe) and Cd(II) had higher adsorption due to its strong interaction with the adsorbent surface. The neural model indicated superior predictive capability in simulation of the obtained data for removal of Pb(II) and Cd(II) from an aqueous solution.

Epichlorohydrin and tripolyphosphate-crosslinked chitosan-kaolin composite for Auramine O dye removal from aqueous solutions: Experimental study and DFT calculations

Chitosan (Ch, a natural polymer) and kaolin (K, a natural mineral) composite (Ch-K) was produced with the help of two crosslinkers, epichlorohydrin and tripolyphosphate, and then moulded into uniform beads in tripolyphosphate solution. The synthesis was proved by the analyses involving FT-IR and SEM-EDX. The beads were then used as the natural adsorbent for removal of the auramine O (AO), a frequently-used industrial dye, in aqueous solutions. Adsorbent performance of the Ch-K composite for AO dye molecules was optimized: 500 mg L^-1 at pH 7.5 at 25 °C. The Langmuir model found 0.118 mol kg^-1 for the maximum adsorption capacity of the Ch-K and the D-R isotherm model showed that the nature of the adsorption process was physical. Kinetics of the adsorption could be explained by using both IPD (intraparticle diffusion) and PSO (pseudo second order) models. Thermodynamic parameters demonstrated that the behaviour of the adsorption was an endothermic and spontaneous. The activity of the composite adsorbent was recovered (88%) after the five sequential adsorption/desorption cycles. Supported by experimental findings, the results obtained from in silico modeling at M06-2X/6-31+G (d,p) level helped hypothesise a mechanism for the formation of the Ch-K composite, and shed some light onto the adsorption behaviour of AO dye by assuming several favourable intermolecular interactions.

Molecular separation of ions from aqueous solutions using modified nanocomposites

Herein, two novel porous polymer matrix nanocomposites were synthesized and used as adsorbents for heavy metal uptake. Methacrylate-modified large mesoporous silica FDU-12 was incorporated in poly(methyl methacrylate) matrix through an in-situ polymerization approach. For another, amine-modified FDU-12 was composited with Nylon 6,6 via a facile solution blending protocol. Various characterization techniques including small-angle X-ray scattering, FTIR spectroscopy, field emission-scanning electron microscopy, transmission electron microscopy, porosimetry, and thermogravimetric analysis have been applied to investigate the physical and chemical properties of the prepared materials. The adsorption of Pb(II) onto the synthesized nanocomposites was studied in a batch system. After study the effect of solution pH, adsorbent amount, contact time, and initial concentration of metal ion on the adsorption process, kinetic studies were also conducted. For both adsorbents, the Langmuir and pseudo-second-order models were found to be the best fit to predict isotherm and kinetics of adsorption. Based on the Langmuir model, maximum adsorption capacities of 105.3 and 109.9 mg g-1 were obtained for methacrylate-modified FDU-12/poly(methyl methacrylate) and amine-modified FDU-12/Nylon 6,6, respectively.