Multilayer Two-Dimensional Water Structure Confined in MoS_2

The conflicting interpretations (square vs rhomboidal) of the recent experimental visualization of the two-dimensional (2D) water confined in between two graphene sheets by transmission electron microscopy measurements, make it important to clarify how the structure of two-dimensional water depends on the constraining medium. Toward this end, we report here molecular dynamics (MD) simulations to characterize the structure of water confined in between two MoS_2 sheets. Unlike graphene, water spontaneously fills the region sandwiched by two MoS_2 sheets in ambient conditions to form planar multilayered water structures with up to four layer. These 2D water molecules form a specific pattern in which the square ring structure is formed by four diamonds via H-bonds, while each diamond shares a corner in a perpendicular manner, yielding an intriguing isogonal tiling structure. Comparison of the water structure confined in graphene (flat uncharged surface) vs MoS_2 (ratchet-profiled charged surface) demonstrates that the polarity (charges) of the surface can tailor the density of confined water, which in turn can directly determine the planar ordering of the multilayered water molecules in graphene or MoS_2. On the other hand, the intrinsic surface profile (flat vs ratchet-profiled) plays a minor role in determining the 2D water configuration

Vibrational Spectroscopic Map, Vibrational Spectroscopy, and Intermolecular Interaction

© 2020 American Chemical Society. Vibrational spectroscopy is an essential tool in chemical analyses, biological assays, and studies of functional materials. Over the past decade, various coherent nonlinear vibrational spectroscopic techniques have been developed and enabled researchers to study time-correlations of the fluctuating frequencies that are directly related to solute-solvent dynamics, dynamical changes in molecular conformations and local electrostatic environments, chemical and biochemical reactions, protein structural dynamics and functions, characteristic processes of functional materials, and so on. In order to gain incisive and quantitative information on the local electrostatic environment, molecular conformation, protein structure and interprotein contacts, ligand binding kinetics, and electric and optical properties of functional materials, a variety of vibrational probes have been developed and site-specifically incorporated into molecular, biological, and material systems for time-resolved vibrational spectroscopic investigation. However, still, an all-encompassing theory that describes the vibrational solvatochromism, electrochromism, and dynamic fluctuation of vibrational frequencies has not been completely established mainly due to the intrinsic complexity of intermolecular interactions in condensed phases. In particular, the amount of data obtained from the linear and nonlinear vibrational spectroscopic experiments has been rapidly increasing, but the lack of a quantitative method to interpret these measurements has been one major obstacle in broadening the applications of these methods. Among various theoretical models, one of the most successful approaches is a semiempirical model generally referred to as the vibrational spectroscopic map that is based on a rigorous theory of intermolecular interactions. Recently, genetic algorithm, neural network, and machine learning approaches have been applied to the development of vibrational solvatochromism theory. In this review, we provide comprehensive descriptions of the theoretical foundation and various examples showing its extraordinary successes in the interpretations of experimental observations. In addition, a brief introduction to a newly created repository Web site (http://frequencymap.org) for vibrational spectroscopic maps is presented. We anticipate that a combination of the vibrational frequency map approach and state-of-the-art multidimensional vibrational spectroscopy will be one of the most fruitful ways to study the structure and dynamics of chemical, biological, and functional molecular systems in the future

Machine learning approach for describing vibrational solvatochromism

© 2020 Author(s). Machine learning is becoming a more and more versatile tool describing condensed matter systems. Here, we employ the feed-forward and the convolutional neural networks to describe the frequency shifts of the amide I mode vibration of N-methylacetamide (NMA) in water. For a given dataset of configurations of an NMA molecule solvated by water, we obtained comparable or improved results for describing vibrational solvatochromic frequency shift with the neural network approach, compared to the previously developed differential evolution algorithm approach. We compared the performance of the atom centered symmetry functions (ACSFs) and simple polynomial functions as descriptors for the solvated system and found that the polynomial function performs better than the ACSFs employed in the description of the amide I vibrational solvatochromism11Nsciescopu

Machine Learning Approach for Describing Water OH Stretch Vibrations

© 2021 American Chemical Society.A machine learning approach employing neural networks is developed to calculate the vibrational frequency shifts and transition dipole moments of the symmetric and antisymmetric OH stretch vibrations of a water molecule surrounded by water molecules. We employed the atom-centered symmetry functions (ACSFs), polynomial functions, and Gaussian-type orbital-based density vectors as descriptor functions and compared their performances in predicting vibrational frequency shifts using the trained neural networks. The ACSFs perform best in modeling the frequency shifts of the OH stretch vibration of water among the types of descriptor functions considered in this paper. However, the differences in performance among these three descriptors are not significant. We also tried a feature selection method called CUR matrix decomposition to assess the importance and leverage of the individual functions in the set of selected descriptor functions. We found that a significant number of those functions included in the set of descriptor functions give redundant information in describing the configuration of the water system. We here show that the predicted vibrational frequency shifts by trained neural networks successfully describe the solvent-solute interaction-induced fluctuations of OH stretch frequencies.11Nsciescopu

Molecular dynamics simulation study of water structure and dynamics on the gold electrode surface with adsorbed 4-mercaptobenzonitrile

Understanding water dynamics at charged interfaces is of great importance in various fields, such as catalysis, biomedical processes, and solar cell materials. In this study, we implemented molecular dynamics simulations of a system of pure water interfaced with Au electrodes, on one side of which 4-mercaptobenzonitrile (4-MBN) molecules are adsorbed. We calculated time correlation functions of various dynamic quantities such as the hydrogen bond status of the N atom of the adsorbed 4-MBN molecules, the rotational motion of the water OH bond, hydrogen bonds between 4-MBN and water, and hydrogen bonds between water molecules in the interface region. Using the Luzar-Chandler model, we analyzed the hydrogen bond dynamics between a 4-MBN and a water molecule. The dynamic quantities we calculated can be divided into two categories: those related to the collective behavior of interfacial water molecules and the H-bond interaction between a water molecule and the CN group of 4-MBN. We found that these two categories of dynamic quantities exhibit opposite trends in response to applied potentials on the Au electrode. We anticipate the present work will help improve our understanding of the interfacial dynamics of water in various electrolyte systems

Computational analysis of pressure-dependent optimal pore size for CO2 capture with graphitic surfaces

There are a growing number of reports suggesting that the specific surface area in graphitic materials is not a critical parameter to determine the CO, capture capacity, but rather the pore size and its geometry are more relevant, yet a detailed theoretical and quantitative understanding that could facilitate further developments for the pore size effects is presently lacking. Using the thermodynamic continuum model combined with electronic structure calculations, we identify the critical size of pores in graphitic materials for enhanced carbon dioxide (CO2) uptake as well as its selectivity relative to N-2. We find that there exists a value of pore size which is most optimal in the CO, capture capacity as well as CO2/N-2 selectivity at a given pressure and temperature, supporting the previous experimental observations regarding critical parameters determining the CO2 adsorption capacity of porous carbon materials. The calculated results emphasize the importance of graphitic pore size from 8 to10 angstrom in CO, capture and selectivity against N-2.

Stability, Molecular Sieving, and Ion Diffusion Selectivity of a Lamellar Membrane from Two-Dimensional Molybdenum Disulfide

Two-dimensional (2D) subnanometer channels allow unique mass transport promising for molecular sieving. New 2D channels of MoS2 nanosheets allow one to understand molecular transmission and separation, unlike the graphene oxide counterpart containing various defects and cationic metal contaminants. Membranes from layered MoS2 platelets show extraordinary stability in an aqueous environment and compatibility with polymer filters, both beneficial to efficient manufacturing. Sharing gas-tightness and unimpeded water vapor permeation with a graphene oxide membrane, our lamellar MoS2 membrane demonstrates a molecular sieving property for organic vapor for the first time. The MoS2 membrane also reveals diffusion selectivity of aqueous ions, attributable to the energy penalty in bulk-to-2D dimensional transition. These newly revealed properties of the lamellar membrane full of angstrom-sized 2D channels point to membrane technology applications for energy and environment.11Nsciescopu

Multilayer Two-Dimensional Water Structure Confined in MoS2,

The conflicting interpretations (square vs rhomboidal) of the recent experimental visualization of the two-dimensional (2D) water confined in between two graphene sheets by transmission electron microscopy measurements, make it important to clarify how the structure of two-dimensional water depends on the constraining medium. Toward this end, we report here molecular dynamics (MD) simulations to characterize the structure of water confined in between two MoS2 sheets. Unlike graphene, Water spontaneously fills the region sandwiched by two MoS2 sheets in ambient conditions to form planar multilayered water structures with up to four layer. These 2D water molecules form a specific pattern in which the square ring structure is formed by four, diamonds, via H-bonds, while each diamond shares a corner in a perpendicular manner, yielding an intriguing isogonal tiling structure. Comparison of the water structure confined in graphene (flat uncharged surface) vs MoS2 (ratchet-profiled charged surface), demonstrates that the polarity (charges),of the surface can tailor the density of:confined water, which in turn can directly determine the planar ordering of the multilayered water molecules in graphene or MoS2. On the other hand, the intrinsic surface profile (flat vs ratchet-profiled) plays a minor role in determining the 2D water configuration.11Nsciescopu