Density functional theory study of π-aromatic interaction of benzene, phenol, catechol, dopamine isolated dimers and adsorbed on graphene surface

In-silico mechanistic analysis of adsorption of Iodinated Contrast Media agents on graphene surface

The study aims at assessing the potential of graphene-based adsorbents to reduce environmental impacts of Iodinated Contrast Media Agents (ICMs). We analyze an extensive collection of ICMs. A modeling approach resting on molecular docking and Density Functional Theory simulations is employed to examine the adsorption process at the molecular level. The study also relies on a Quantitative Structure-Activity Relationship (QSAR) modeling framework to correlate molecular properties with the adsorption energy (Ead) of ICMs, thus enabling identification of the key mechanisms underpinning adsorption and of the key factors contributing to it. A collection of distinct QSAR-based models is developed upon relying on Multiple Linear Regression and a standard genetic algorithm method. Having at our disposal multiple models enables us to take into account the uncertainty associated with model formulation. Maximum Likelihood and formal model identification/discrimination criteria (such as Bayesian and/or information theoretic criteria) are then employed to complement the traditional QSAR modeling phase. This has the advantage of (a) providing a rigorous ranking of the alternative models included in the selected set and (b) quantifying the relative degree of likelihood of each of these models through a weight or posterior probability. The resulting workflow of analysis enables one to seamlessly embed DFT and QSAR studies within a theoretical framework of analysis that explicitly takes into account model and parameter uncertainty. Our results suggest that graphene-based surfaces constitute a promising adsorbent for ICMs removal, π-π stacking being the primary mechanism behind ICM adsorption. Furthermore, our findings offer valuable insights into the potential of graphene-based adsorbent materials for effectively removing ICMs from water systems. They contribute to ascertain the significance of various factors (such as, e.g., the distribution of atomic van der Waals volumes, overall molecular complexity, the presence and arrangement of Iodine atoms, and the presence of polar functional groups) on the adsorption process.

Adsorption Behaviors and Mechanism of Phenol and Catechol in Wastewater by Magnetic Graphene Oxides: A Comprehensive Study Based on Adsorption Experiments, Mathematical Models, and Molecular Simulations

This study provides a comprehensive analysis of the adsorption behaviors and mechanisms of phenol and catechol on magnetic graphene oxide (MGO) nanocomposites based on adsorption experiments, mathematical models, and molecular simulations. Through systematic experiments, the influence of various parameters, including contact time, pH conditions, and ionic strength, on the adsorption efficacy was comprehensively evaluated. The optimal contact time for adsorption was identified as 60 min, with the observation that an increase in inorganic salt concentration adversely affected the MGOs' adsorption capacity for both phenol and catechol. Specifically, MGOs exhibited a superior adsorption performance under mildly acidic conditions. The adsorption isotherm was well represented by the Langmuir model, suggesting monolayer coverage and finite adsorption sites for both pollutants. In terms of adsorption kinetics, a pseudo-first-order kinetic model was the most suitable for describing phenol adsorption, while catechol adsorption conformed more closely to a pseudo-second-order model, indicating distinct adsorption processes for these two similar compounds. Furthermore, this research utilized quantum chemical calculations to decipher the interaction mechanisms at the molecular level. Such calculations provided both a visual representation and a quantitative analysis of the interactions, elucidating the underlying physical and chemical forces governing the adsorption phenomena. The findings could not only offer crucial insights for the treatment of coal industrial wastewater containing phenolic compounds with bridging macroscopic observations with microscopic theoretical explanations but also advance the understanding of material-pollutant interactions in aqueous environments.

Effect of electronegative atoms on π - π stacking and hydrogen bonding behavior in simple aromatic molecules - An Ab initio MD study

Ab initio molecular dynamics studies have been performed on fluorobenzene, phenol, and aniline, which have the three most electronegative atoms, fluorine, oxygen, and nitrogen, respectively. Radial distribution functions show strong hydrogen bonding in the phenolic -OH group, whereas it is less prominent in the -NH2 group of aniline. Fluorobenzene does not show strong hydrogen bonds as no solvation shell is found between the fluorine atom and different aromatic hydrogens of the molecule. Spatial distribution functions show that the nitrogen atom of aniline interacts with the aromatic plane, the oxygen atom of phenol is concentrated near the -OH group and fluorobenzene's fluorine atom interacts with the para hydrogen. Liquid phase dimer structures of these systems reveal that perpendicular orientation (Y-shaped) is preferred over parallel ones. Almost half of the total dimer population tends to prefer 90∘±30° angle. H-bond analyses show that fluorobenzene has the longest mean H-bond lifetime for the H-bond between the aromatic hydrogens and the fluorine atoms, whereas the aniline has the least. The mean lifetime between aromatic hydrogens and electronegative atoms increases steadily from aniline to fluorobenzene. Phenolic -OH and amino -NH2 groups show considerably longer mean H-bond lifetime than the aromatic hydrogens. Gas-phase binding energies obtained from quantum chemical calculations show that aniline and phenol dimers have higher binding energy values than the fluorobenzene dimer. Only the phenol dimer shows a perpendicular structure as a stable one, while aniline and fluorobenzene prefer the parallel orientation.

Graphene as a rational interface for enhanced adsorption of microcystin-LR from water

Cyanotoxins such as microcystin-LR (MC-LR) represent a global environmental threat to ecosystems and drinking water supplies. The study investigated the direct use of graphene as a rational interface for removal of MC-LR via interactions with the aromatic ring of the ADDA1 chain of MC-LR and the sp2 hybridized carbon network of graphene. Intra-particle diffusion model fit indicated the high mesoporosity of graphene provided significant enhancements to both adsorption capacities and kinetics when benchmarked against microporous granular activated carbon (GAC). Graphene showed superior MC-LR adsorption capacity of 75.4 mg/g (Freundlich model) compared to 0.982 mg/g (Langmuir model) for GAC. Sorption kinetic studies showed graphene adsorbs 99% of MC-LR in 30 min, compared to zero removal for GAC after 24 hr using the same MC-LR concentration. Density functional theory (DFT), calculations showed that postulated π-based interactions align well with the NMR-based experimental work used to probe primary interactions between graphene and MC-LR adduct. This study proved that π-interactions between the aromatic ring on MC-LR and graphene sp2 orbitals are a dominant interaction. With rapid kinetics and adsorption capacities much higher than GAC, it is anticipated that graphene will offer a novel molecular approach for removal of toxins and emerging contaminants with aromatic systems.

Evaluation interaction of graphene oxide with heparin for antiviral blockade: a study of ab initio simulations, molecular docking, and experimental analysis

CONTEXT

Heparin, one of the drugs reused in studies with antiviral activity, was chosen to investigate a possible blockade of the SARS-CoV-2 spike protein for viral entry through computational simulations and experimental analysis. Heparin was associated to graphene oxide to increase in the binding affinity in biological system. First, the electronic and chemical interaction between the molecules was analyzed through ab initio simulations. Later, we evaluate the biological compatibility of the nanosystems, in the target of the spike protein, through molecular docking. The results show that graphene oxide interacts with the heparin with an increase in the affinity energy with the spike protein, indicating a possible increment in the antiviral activity. Experimental analysis of synthesis and morphology of the nanostructures were carried out, indicating heparin absorption by graphene oxide, confirming the results of the first principle simulations. Experimental tests were conducted on the structure and surface of the nanomaterial, confirming the heparin aggregation on the synthesis with a size between the GO layers of 7.44 Å, indicating a C-O type bond, and exhibiting a hydrophilic surface characteristic (36.2°).

METHODS

Computational simulations of the ab initio with SIESTA code, LDA approximations, and an energy shift of 0.05 eV. Molecular docking simulations were performed in the AutoDock Vina software integrated with the AMDock Tools Software using the AMBER force field. GO, GO@2.5Heparin, and GO@5Heparin were synthesized by Hummers and impregnation methods, respectively, and characterized by X-ray diffraction and surface contact angle.

Ab initio study of water anchored in graphene pristine and vacancy-type defects

CONTEXT

In this paper, we have addressed two issues that are relevant to the interaction of water in pristine and vacant graphene through first-principles calculations based on the Density Functional Theory (DFT). The results showed that for the interaction of pristine graphene with water, the DOWN configuration (with the hydrogen atoms facing downwards) was the most stable, presenting binding energies in the order of -13.62 kJ/mol at a distance of 2.375 Å in the TOP position. We also evaluated the interaction of water with two vacancy models, removing one carbon atom (Vac-1C) and four atoms (Vac-4C). In the Vac-1C system, the most favourable system was the DOWN configuration, with binding energies ranging from -20.60 kJ/mol to -18.41 kJ/mol in the TOP and UP positions, respectively. A different behaviour was observed for the interaction of water with Vac-4C; regardless of the configuration of the water, it is always more favourable for the interaction to occur through the vacancy centre, with binding energies ​​between -13.28 kJ/mol and -20.49 kJ/mol. Thus, the results presented open perspectives for the technological development of nanomembranes as well as providing a better understanding of the wettability effects of graphene sheets, whether pristine or with defects.

METHOD

We evaluated the interaction of pristine and vacant graphene with the water molecule, through calculations based on Density Functional Theory (DFT); implemented by the SIESTA program. The electronic, energetic, and structural properties were analyzed by solving self-consistent Kohn-Sham equations. In all calculations, a double ζ plus a polarized function (DZP) was used for the numerical baise set. Local Density Approximation (LDA) with the Perdew and Zunger (PZ) parameterisation along with a basis set superposition error (BSSE) correction were used to describe the exchange and correlation potential (Vxc). The water and isolated graphene structures were relaxed until the residual forces were less than 0.05 eV/Å^-1 in all atomic coordinates.

Effects of film thickness on electrochemical properties of nanoscale polyethylenedioxythiophene (PEDOT) thin films grown by oxidative molecular layer deposition (oMLD)

Poly(3,4-ethylene dioxythiophene) (PEDOT) has a high theoretical charge storage capacity, making it of interest for electrochemical applications including energy storage and water desalination. Nanoscale thin films of PEDOT are particularly attractive for these applications to enable faster charging. Recent work has demonstrated that nanoscale thin films of PEDOT can be formed using sequential gas-phase exposures via oxidative molecular layer deposition, or oMLD, which provides advantages in conformality and uniformity on high aspect ratio substrates over other deposition techniques. But to date, the electrochemical properties of these oMLD PEDOT thin films have not been well-characterized. In this work, we examine the electrochemical properties of 5-100 nm thick PEDOT films formed using 20-175 oMLD deposition cycles. We find that film thickness of oMLD PEDOT films affects the orientation of ordered domains leading to a substantial change in charge storage capacity. Interestingly, we observe a minimum in charge storage capacity for an oMLD PEDOT film thickness of ∼30 nm (60 oMLD cycles at 150 °C), coinciding with the highest degree of face-on oriented PEDOT domains as measured using grazing incidence wide angle X-ray scattering (GIWAXS). Thinner and thicker oMLD PEDOT films exhibit higher fractions of oblique (off-angle) orientations and corresponding increases in charge capacity of up to 120 mA h g^-1. Electrochemical measurements suggest that higher charge capacity in films with mixed domain orientation arise from the facile transport of ions from the liquid electrolyte into the PEDOT layer. Greater exposure of the electrolyte to PEDOT domain edges is posited to facilitate faster ion transport in these mixed domain films. These insights will inform future design of PEDOT coated high-aspect ratio structures for electrochemical energy storage and water treatment.

Comparison of three cyclodextrins to optimize bisphenol A extraction from source water: Computational, spectroscopic, and analytical studies

Computationally and spectroscopically assisted analytical comparative investigation into the extraction of bisphenol A using three cyclodextrins, that is, α, β, and γ respectively, were performed. A simple, self-tailored μ-solid-phase extraction podium was used to extract bisphenol A from water samples, and high-performance liquid chromatography-ultraviolet was used for the qualitative and quantitative analysis of bisphenol A. Density functional theory first principle calculations, attenuated total reflectance Fourier-transform infrared spectroscopy and Fourier-transform Raman spectroscopy data supports the analytical selection of β-cyclodextrin as the adsorbent for bisphenol A extraction. Analytical optimization of various parameters including sample volume, sample pH, eluting solvent and its volume was performed to discover the most proper conditions for maximum extraction. Under the optimized conditions, a limit of detection value of 0.70 ng/ml and a limit of quantification value of 2.31 ng/ml was achieved with β-cyclodextrin, with recovery (%) values over 98.40-102.50 in real source water samples. Overall, well assisted by comprehensive computational and spectroscopic studies, a novel, simple, sensitive and economic analytical method was developed for the extraction of bisphenol A from source water using cyclodextrin.

Graphene oxide and flavonoids as potential inhibitors of the spike protein of SARS-CoV-2 variants and interaction between ligands: a parallel study of molecular docking and DFT

Nanocarriers allow the connection between biomolecules and other structures to enhance the treatment efficacy, through the biomolecule's properties to an existing drug, or to allow a better and specific delivery. Apigenin and orientin are biomolecules with excellent therapeutic properties that are proposed in the fight against COVID-19. Besides that, graphene oxide is a nanomaterial that exhibits antiviral activity and is used as a nanocarrier of several drugs. We evaluated in this work, through molecular docking, the binding affinity between these structures to the receptor-binding domain of spike protein of two coronavirus variants, Delta and Omicron. The results indicate that all the structures exhibit affinity with the two protein targets, with binding affinity values of -11.88 to -6.65 kcal/mol for the Delta variant and values of -9.58 to -13.20 kcal/mol for the Omicron variant, which is a successful value as found in the literature as a potential inhibitor of SARS-CoV-2 infection. Also, through first-principles calculations based on Density Functional Theory, the interaction of graphene oxide with the biomolecules apigenin and orientin occurred. The results exhibit weak binding energy, which indicates that physical adsorption occurs, with better results when the biomolecule is set in parallel to the nanomaterial due to attractive π-π staking. These results are conducive to the development of a nanocarrier.

Graphene-Mediated removal of Microcystin-LR in chitosan/graphene composites for treatment of harmful algal blooms

Water quality can be severely impacted by algal blooms alone, yet cyanotoxins, such as microcystin (MC), are potent underlying hazards produced by various species of cyanobacteria. Currently there is a need for environmentally compatible and economically viable media to address large scale application for HAB impacted waters. This study evaluated the interactions of chitosan/graphene (CSG) composites with three different species of cyanobacteria: Anabaena sp, Synechocystis sp, and Microcystis aeruginosa for both removal of algal optical density and toxins. Although results suggest that CSG has an algae dependent removal of density with a range of 40-90% removal, graphene/CSG is highly effective at MC toxin removal, removing >94% of MC-LR produced by Microcystis aeruginosa. Characterization by SEM and XRD revealed that 750 m²/g surface area graphene, imparts graphene morphology and functionality into the chitosan matrix surface, potentially enabling π-π interactions between graphene and the aromatic ring of microcystin. This proposed π-π removal mechanism of microcystin via the CSG chitosan biopolymer substrate offers a promising sustainable and selective media suitable for deployable treatment of HAB impacted waters.

BIGDML-Towards accurate quantum machine learning force fields for materials

Machine-learning force fields (MLFF) should be accurate, computationally and data efficient, and applicable to molecules, materials, and interfaces thereof. Currently, MLFFs often introduce tradeoffs that restrict their practical applicability to small subsets of chemical space or require exhaustive datasets for training. Here, we introduce the Bravais-Inspired Gradient-Domain Machine Learning (BIGDML) approach and demonstrate its ability to construct reliable force fields using a training set with just 10-200 geometries for materials including pristine and defect-containing 2D and 3D semiconductors and metals, as well as chemisorbed and physisorbed atomic and molecular adsorbates on surfaces. The BIGDML model employs the full relevant symmetry group for a given material, does not assume artificial atom types or localization of atomic interactions and exhibits high data efficiency and state-of-the-art energy accuracies (errors substantially below 1 meV per atom) for an extended set of materials. Extensive path-integral molecular dynamics carried out with BIGDML models demonstrate the counterintuitive localization of benzene-graphene dynamics induced by nuclear quantum effects and their strong contributions to the hydrogen diffusion coefficient in a Pd crystal for a wide range of temperatures.

Structures, binding energies and non-covalent interactions of furan clusters

Understanding of the furan solvent is subjected to the knowledge of the structures of the furan clusters and interactions taking place therein. Although, furan clusters can be very important to determine the dynamics and the properties of the furan solvent, there has been only a few investigations reported on furan dimer. In this work, we have explored the potential energy surfaces (PESs) of the furan clusters using two incremental levels of theory. Structures have been initially generated using classical molecular dynamics followed by full optimization at the MP2/aug-cc-pVDZ level of theory. The results show that the most stable structure of the furan dimer has a stacking configuration while that of the trimer has a cyclic configuration. We have noted that the structures of the furan tetramer have no definite configurations. In addition, we have performed a quantum theory of atoms in molecule (QTAIM) analysis to identify all possible non-covalent interactions of the furan clusters. The results show that six different types of non-covalent interactions can be identified in furan clusters. We have noted that the CH⋯C and CH⋯O hydrogen bondings are the strongest non-covalent interactions while the H⋯H bonding interaction is found to be the weakest. Furthermore, we have assessed the performance of ten DFT functionals in calculating the binding energies of the furan clusters. The ten DFT functionals (M05, M05-2X, M06, M06-2X, M08HX, PBE0, ωB97XD, PW6B95D3, APFD and MN15) have been benchmarked to DLPNO-CCSD(T)/CBS. The functionals M05-2X and M06 are recommended for further affordable investigations of the furan clusters.

Theoretical study of small aromatic molecules adsorbed in pristine and functionalised graphene

Small aromatic molecules are precursors for several biological systems such as DNA, proteins, drugs, and are also present in several pollutants. The understanding of the interaction of these small aromatic molecules with pristine and functionalised graphene (fGr) can generate different applications. We performed ab initio simulations based on the density functional theory to evaluate the interaction between the aromatic compounds, benzene, benzoic acid, aniline and phenol, with pristine and fGr. The results show that the binding energy for all cases is less than 103.24 kJ/mol (1.07 eV) without substantial modification of the electronic properties, indicating that the interaction occurs through a physical adsorption regime. The results are promising because they suggest that pristine graphene and functionalised graphene are suitable for removing these pollutants, or for carrying molecules for biological applications influenced by π-π and H-bonds interaction.

A density functional theory study on the underwater adhesion of catechol onto a graphite surface

Mussel foot proteins (MFPs) strongly adhere to both hydrophilic and hydrophobic surfaces under wet conditions. This water-resistant adhesion of MFP is ascribed to catechol (1,2-dihydroxybenzene) which is highly contained in the MFP. Currently, little is known about the molecular details of the underwater adhesion of catechol onto a nonpolar hydrophobic surface. By using the density functional theory, we investigate the adhesion of catechol onto a wet graphite surface. We unveil the molecular geometry and energy in the course of the wet adhesion of catechol. Catechol adheres through π-π stacking with the underlying graphite. The surrounding water molecules further strengthen the adhesion by forming hydrogen bonds with catechol. In addition, a significant charge transfer has been observed from wet graphite to the catechol. Consequently, catechol adheres onto the present hydrophobic surface as strongly as onto a hydrophilic silica surface.

Molecular Interpretation of Pharmaceuticals’ Adsorption on Carbon Nanomaterials: Theory Meets Experiments

The ability of carbon-based nanomaterials (CNM) to interact with a variety of pharmaceutical drugs can be exploited in many applications. In particular, they have been studied both as carriers for in vivo drug delivery and as sorbents for the treatment of water polluted by pharmaceuticals. In recent years, the large number of experimental studies was also assisted by computational work as a tool to provide understanding at molecular level of structural and thermodynamic aspects of adsorption processes. Quantum mechanical methods, especially based on density functional theory (DFT) and classical molecular dynamics (MD) simulations were mainly applied to study adsorption/release of various drugs. This review aims to compare results obtained by theory and experiments, focusing on the adsorption of three classes of compounds: (i) simple organic model molecules; (ii) antimicrobials; (iii) cytostatics. Generally, a good agreement between experimental data (e.g. energies of adsorption, spectroscopic properties, adsorption isotherms, type of interactions, emerged from this review) and theoretical results can be reached, provided that a selection of the correct level of theory is performed. Computational studies are shown to be a valuable tool for investigating such systems and ultimately provide useful insights to guide CNMs materials development and design.