The Liquid Water−Benzene System

DeepCV: A Deep Learning Framework for Blind Search of Collective Variables in Expanded Configurational Space

We present Deep learning for Collective Variables (DeepCV), a computer code that provides an efficient and customizable implementation of the deep autoencoder neural network (DAENN) algorithm that has been developed in our group for computing collective variables (CVs) and can be used with enhanced sampling methods to reconstruct free energy surfaces of chemical reactions. DeepCV can be used to conveniently calculate molecular features, train models, generate CVs, validate rare events from sampling, and analyze a trajectory for chemical reactions of interest. We use DeepCV in an example study of the conformational transition of cyclohexene, where metadynamics simulations are performed using DAENN-generated CVs. The results show that the adopted CVs give free energies in line with those obtained by previously developed CVs and experimental results. DeepCV is open-source software written in Python/C++ object-oriented languages, based on the TensorFlow framework and distributed free of charge for noncommercial purposes, which can be incorporated into general molecular dynamics software. DeepCV also comes with several additional tools, i.e., an application program interface (API), documentation, and tutorials.

Ground and excited states of naphthalene–water (naphtha–W6) clusters: a computational study

An MP2 and DFT study of the structures of naphthalene–water hexamer clusters has been performed for both the prism and cage forms of the cluster.

The structure and UV spectroscopy of benzene–water (Bz–W6) clusters using time-dependent density functional theory

MP2, DFT and TD-DFT applied to benzene–(water)₆ clusters show how both perturb the electronic spectra of each other and give rise to new charge transfer features from the benzene to the water cluster.

Noncovalent Interaction Analysis in Fluctuating Environments

Noncovalent interactions play a central role in many chemical and biological systems. In a previous study, Johnson et al developed a NonCovalent Interaction (NCI) index to characterize and visualize different types of weak interactions. To apply the NCI analysis to fluctuating environments as in solution phase, we here develop a new Averaged NonCovalent Interaction (i.e., aNCI) index along with a fluctuation index to characterize magnitude of interactions and fluctuations. We applied aNCI for various systems including solute-solvent and ligand-protein noncovalent interactions. For water and benzene molecules in aqueous solution, solvation structures and the specific hydrogen bond patterns were visualized clearly. For the Cl^-+CH₃Cl S_N2 reaction in aqueous solution, charge reorganization influences over solvation structure along S_N2 reaction were revealed. For ligand-protein systems, aNCI can recover several key fluctuating hydrogen bond patterns that have potential applications for drug design. Therefore, aNCI, as a complementary approach to the original NCI method, can extract and visualize noncovalent interactions from thermal noise in fluctuating environments.

Methane from benzene in argon dielectric barrier discharge

A first-time account of direct, on-line, instantaneous and efficient chemical conversion of gas phase benzene to methane in argon Dielectric Barrier Discharge (DBD) is presented. In the absence of another overt hydrogen-donating source, potency of analogous parents toward methane generation is found to follow the order: benzene>toluene>p-xylene. Simultaneous production of trace amounts of phenolic surface deposits suggest (a) prompt decomposition of the parent molecules, including a large fraction yielding atomic transients (H-atom), (b) continuous and appropriate recombination of such parts, and (c) trace moisture in parent contributing OH radicals and additional H-atoms, which suitably react with the unreacted fraction of the parent, and also other intermediates. Results highlight Ar DBD to be a simple and exploitable technology for transforming undesirable hazardous aromatics to usable/useful low molecular weight open-chain products following the principles of green chemistry and engineering.

Influence of the water content on the diffusion coefficients of Li+ and water across naphthalenic based copolyimide cation-exchange membranes

The transport of lithium ions in cation-exchange membranes based on sulfonated copolyimide membranes is reported. Diffusion coefficients of lithium are estimated as a function of the water content in membranes by using pulsed field gradient (PFG) NMR and electrical conductivity techniques. It is found that the lithium transport slightly decreases with the diminution of water for membranes with water content lying in the range 14 < λ < 26.5, where λ is the number of molecules of water per fixed sulfonate group. For λ < 14, the value of the diffusion coefficient of lithium experiences a sharp decay with the reduction of water in the membranes. The dependence of the diffusion of lithium on the humidity of the membranes calculated from conductivity data using Nernst-Planck type equations follows a trend similar to that observed by NMR. The possible explanation of the fact that the Haven ratio is higher than the unit is discussed. The diffusion of water estimated by (1)H PFG-NMR in membranes neutralized with lithium decreases as λ decreases, but the drop is sharper in the region where the decrease of the diffusion of protons of water also undergoes considerable reduction. The diffusion of lithium ions computed by full molecular dynamics is similar to that estimated by NMR. However, for membranes with medium and low concentration of water, steady state conditions are not reached in the computations and the diffusion coefficients obtained by MD simulation techniques are overestimated. The curves depicting the variation of the diffusion coefficient of water estimated by NMR and full dynamics follow parallel trends, though the values of the diffusion coefficient in the latter case are somewhat higher. The WAXS diffractograms of fully hydrated membranes exhibit the ionomer peak at q = 2.8 nm(-1), the peak being shifted to higher q as the water content of the membranes decreases. The diffractograms present additional peaks at higher q, common to wet and dry membranes, but the peaks are better resolved in the wet membranes. The ionomer peak is not detected in the diffractograms of dry membranes.

Formation of supramolecular structures in organic solvents

The unusual interactions in organic liquids such as methane derivatives, arenes, and alkanes by the infrared (IR) method were revealed. The transformations of molecular shapes, arising from nonclassical hydrogen and dihydrogen bonds, as well as water factor provide the existence of supramolecular structures in organic fluids. The interpretation of the obtained results in terms of the quantum-chemical calculations has been suggested.

Water-benzene interactions: an effective fragment potential and correlated quantum chemistry study

Structures and binding in small water-benzene complexes (1-8 water molecules and 1-2 benzene molecules) are studied using the general effective fragment potential (EFP) method. The lowest energy conformers of the clusters were found using a Monte Carlo technique. The binding energies in the smallest clusters (dimers, trimers, and tetramers) were also evaluated with second order perturbation theory (MP2) and coupled cluster theory (CCSD(T)). The EFP method accurately predicts structures and binding energies in the water-benzene complexes. Benzene is polarizable and consequently participates in hydrogen bond networking of water. Since the water-benzene interactions are only slightly weaker than water-water interactions, structures with different numbers of water-water, benzene-water, and benzene-benzene bonds often have very similar binding energies. This is a challenge for computational methods.