Interaction between water and carbon nanostructures: How good are current density functional approximations?

Studying the adsorption of emerging organic contaminants in zeolites with dispersion-corrected density functional theory calculations: From numbers to recommendations

Adsorption energies obtained from dispersion-corrected density functional theory (DFT) calculations show a considerable dependence on the choice of exchange-correlation functional and dispersion correction. A number of investigations have employed different approaches to compute adsorption energies of small molecules in zeolites, using reference values from high-level calculations and/or experiments. Such comparative studies are lacking for larger functional organic molecules such as pharmaceuticals or personal care products, despite their potential relevance for applications, e. g., in contaminant removal or drug delivery. The present study aims to fill this gap by comparing adsorption energies and, for selected cases, equilibrium structures of emerging organic contaminants adsorbed in MOR- and FAU-type all-silica zeolites. A total of 13 dispersion-corrected DFT approaches are compared, including methods using a pairwise dispersion correction as well as non-local van der Waals density functionals. While absolute values of adsorption energies vary widely, qualitative trends across the set of zeolite-guest combinations are not strongly dependent on the choice of functional. For selected cluster models, DFT adsorption energies are compared to reference values from coupled cluster (DLPNO-CCSD(T)) calculations. Although all DFT approaches deliver systematically more negative adsorption energies than the coupled cluster reference, this tendency is least pronounced for the rev-vdW-DF2 functional.

Origin of dielectric polarization suppression in confined water from first principles

It has long been known that the dielectric constant of confined water should be different from that in bulk. Recent experiments have shown that it is vanishingly small, however the origin of the phenomenon remains unclear. Here we used ab initio molecular dynamics simulations (AIMD) and AIMD-trained machine-learning potentials to understand water's structure and electronic properties underpinning this effect. For the graphene and hexagonal boron-nitride substrates considered, we find that it originates in the spontaneous anti-parallel alignment of the water dipoles in the first two water layers near the solid interface. The interfacial layers exhibit net ferroelectric ordering, resulting in an overall anti-ferroelectric arrangement of confined water. Together with constrained hydrogen-bonding orientations, this leads to much reduced out-of-plane polarization. Furthermore, we directly contrast AIMD and simple classical force-field simulations, revealing important differences. This work offers insight into a property of water that is critical in modulating surface forces, the electric-double-layer formation and molecular solvation, and shows a way to compute it.

DFT study of water on graphene: Synergistic effect of multilayer p-doping

Recent experiments related to a study concerning the adsorption of water on graphene have demonstrated the p-doping of graphene, although most of the ab initio calculations predict nearly zero doping. To shed more light on this problem, we have carried out van der Waals density functional theory calculations of water on graphene for both individual water molecules and continuous water layers with coverage ranging from one to eight monolayers. Furthermore, we have paid attention to the influence of the water molecule orientation toward graphene on its doping properties. In this article, we present the results of the band structure and the Bader charge analysis, showing the p-doping of graphene can be synergistically enhanced by putting 4-8 layers of an ice-like water structure on graphene having the water molecules oriented with oxygen atoms toward graphene.

Ab Initio Molecular Dynamics Investigation of the Solvation States of Hydrated Ions in Confined Water

Ionic transport in nanoscale channels with a critical size comparable to that of ions and solutes exhibits exceptional performance in water desalination, ion separation, electrocatalysts, and supercapacitors. However, the solvation states (SSs), i.e., the hydration structures and probability distribution, of hydrated ions in nanochannels differ from those in the bulk and the perspective of continuum theory. In this work, we conduct ab initio enhanced-sampling atomistic simulations to investigate the ion-specific SSs of monovalent ions (including Li+, Na+, K+, F-, Cl-, and I-) in the graphene channel with a width of 1 nm. Our findings highlight that the SSs of those ions are primarily determined by ion-water hydration, where ion-wall interactions play a minor role. The distribution of ions in layered confined water is a result of ion-specific hydration, which arises from the synergy of entropy and enthalpy. The free energy barriers for transitions between SSs are on the order of 1kBT, allowing for modulation through applying external fields or modifying surface properties. As the ion-wall interaction strengthens, as observed in vermiculite and carbides and nitrides of transition metal channels, the probability of near-wall SSs increases. These results help to improve the performance of nanofluidic devices and provide crucial insights for developing accurate force fields of molecular simulations or advanced theoretical approaches for ion dynamics in confined channels.

Formation of Eigen or Zundel Features at Protonated Water Cluster-Aromatic Interfaces

Interfacial interactions of protonated water clusters adsorbed at aromatic surfaces play an important role in biology, and in atmospheric, chemical and materials sciences. Here, we investigate the interaction of protonated water clusters ((H+ H2 O)n (where n=1-3)) with benzene (Bz), coronene (Cor) and dodecabenzocoronene (Dbc)). To study the structure, stability and spectral features of these complexes, computations are done using DFT-PBE0(+D3) and SAPT0 methods. These interactions are probed by AIM electron density topography and non-covalent interactions index (NCI) analyses. We suggest that the excess proton plays a crucial role in the stability of these model interfaces through strong inductive effects and the formation of Eigen or Zundel features. Also, computations reveal that the extension of the π-aromatic system and the increase of the number of water molecules in the H-bounded water network led to a strengthening of the interactions between the corresponding aromatic compound and protonated water molecules, except when a Zundel ion is formed. The present findings may serve to understand in-depth the role of proton localized at aqueous medium interacting with large aromatic surfaces such as graphene interacting with acidic liquid water. Besides, we give the IR and UV-Vis spectra of these complexes, which may help for their identification in laboratory.

Temperature-pressure phase diagram of confined monolayer water/ice at first-principles accuracy with a machine-learning force field

Understanding the phase behaviour of nanoconfined water films is of fundamental importance in broad fields of science and engineering. However, the phase behaviour of the thinnest water film - monolayer water - is still incompletely known. Here, we developed a machine-learning force field (MLFF) at first-principles accuracy to determine the phase diagram of monolayer water/ice in nanoconfinement with hydrophobic walls. We observed the spontaneous formation of two previously unreported high-density ices, namely, zigzag quasi-bilayer ice (ZZ-qBI) and branched-zigzag quasi-bilayer ice (bZZ-qBI). Unlike conventional bilayer ices, few inter-layer hydrogen bonds were observed in both quasi-bilayer ices. Notably, the bZZ-qBI entails a unique hydrogen-bonding network that consists of two distinctive types of hydrogen bonds. Moreover, we identified, for the first time, the stable region for the lowest-density [Formula: see text] monolayer ice (LD-48MI) at negative pressures (<-0.3 GPa). Overall, the MLFF enables large-scale first-principle-level molecular dynamics (MD) simulations of the spontaneous transition from the liquid water to a plethora of monolayer ices, including hexagonal, pentagonal, square, zigzag (ZZMI), and hexatic monolayer ices. These findings will enrich our understanding of the phase behaviour of the nanoconfined water/ices and provide a guide for future experimental realization of the 2D ices.

Towards the ground state of molecules via diffusion Monte Carlo on neural networks

Diffusion Monte Carlo (DMC) based on fixed-node approximation has enjoyed significant developments in the past decades and become one of the go-to methods when accurate ground state energy of molecules and materials is needed. However, the inaccurate nodal structure hinders the application of DMC for more challenging electronic correlation problems. In this work, we apply the neural-network based trial wavefunction in fixed-node DMC, which allows accurate calculations of a broad range of atomic and molecular systems of different electronic characteristics. Our method is superior in both accuracy and efficiency compared to state-of-the-art neural network methods using variational Monte Carlo (VMC). We also introduce an extrapolation scheme based on the empirical linearity between VMC and DMC energies, and significantly improve our binding energy calculation. Overall, this computational framework provides a benchmark for accurate solutions of correlated electronic wavefunction and also sheds light on the chemical understanding of molecules.

Interfacial Liquid Water on Graphite, Graphene, and 2D Materials

The optical, electronic, and mechanical properties of graphite, few-layer, and two-dimensional (2D) materials have prompted a considerable number of applications. Biosensing, energy storage, and water desalination illustrate applications that require a molecular-scale understanding of the interfacial water structure on 2D materials. This review introduces the most recent experimental and theoretical advances on the structure of interfacial liquid water on graphite-like and 2D materials surfaces. On pristine conditions, atomic-scale resolution experiments revealed the existence of 1-3 hydration layers. Those layers were separated by ∼0.3 nm. The experimental data were supported by molecular dynamics simulations. However, under standard working conditions, atomic-scale resolution experiments revealed the presence of 2-3 hydrocarbon layers. Those layers were separated by ∼0.5 nm. Linear alkanes were the dominant molecular specie within the hydrocarbon layers. Paradoxically, the interface of an aged 2D material surface immersed in water does not have water molecules on its vicinity. Free-energy considerations favored the replacement of water by alkanes.

Water Flow in Single-Wall Nanotubes: Oxygen Makes It Slip, Hydrogen Makes It Stick

Experimental measurements have reported ultrafast and radius-dependent water transport in carbon nanotubes which are absent in boron nitride nanotubes. Despite considerable effort, the origin of this contrasting (and fascinating) behavior is not understood. Here, with the aid of machine learning-based molecular dynamics simulations that deliver first-principles accuracy, we investigate water transport in single-wall carbon and boron nitride nanotubes. Our simulations reveal a large, radius-dependent hydrodynamic slippage on both materials, with water experiencing indeed a ≈5 times lower friction on carbon surfaces compared to boron nitride. Analysis of the diffusion mechanisms across the two materials reveals that the fast water transport on carbon is governed by facile oxygen motion, whereas the higher friction on boron nitride arises from specific hydrogen-nitrogen interactions. This work not only delivers a clear reference of quantum mechanical accuracy for water flow in single-wall nanotubes but also provides detailed mechanistic insight into its radius and material dependence for future technological application.

Density-functional-theory simulations of the water and ice adhesion on silicene quantum dots

The absorption of water and ice on silicon is important to understand for many applications and safety concerns for electronic devices as most of them are fabricated using silicon. Meanwhile, recently silicene nanostructures have attracted much attention due to their potential applications in electronic devices such as gas or humidity sensors. However, for the moment, the theoretical study of the interaction between water molecules and silicene nanostructures is still rare although there is already theoretical work on the effect of water molecules on the silicene periodic structure. The specific conditions such as the finite size effect, the edge saturation of the silicene nanostructure, and the distance between the water/ice and the silicene at the initial onset of the contact have not been carefully considered before. Here we have modelled the absorption of a water molecule and a square ice on the silicene nanodot by using hybrid-exchange density-functional theory, complemented by the Van der Waals forces correction. Three different sizes of silicene nanodots have been chosen for simulations, namely \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$3\times 3$$\end{document}3×3, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$4\times 4$$\end{document}4×4, and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$5\times 5$$\end{document}5×5, with and without the hydrogen saturation on the edge. Our calculations suggest that the silicene nanodots chosen here are both hydrophilic and ice-philic. The water molecule and the square ice have tilted angles towards the silicene nanodot plane at ~ 70º and ~ 45º, respectively, which could be owing to the zig–zag structure on silicene. The absorption energies are size dependent for unsaturated silicene nanodots, whereas almost size independent for the hydrogen saturated cases. Our work on the single water molecule absorption energy on silicene nanodots is qualitatively in agreement with the previous theoretical and experimental work. However, the ice structure on silicene is yet to be validated by the relevant experiments. Our calculation results not only further complement the current paucity of water-to-silicene-nanostructure contact mechanisms, but also lead to the first study of square-ice contact mechanisms for silicene. Our findings presented here could be useful for the future design of semiconducting devices based on silicene nanostructures, especially in the humid and low-temperature environments.

Microscopic Simulations of Electrochemical Double-Layer Capacitors

Electrochemical double-layer capacitors (EDLCs) are devices allowing the storage or production of electricity. They function through the adsorption of ions from an electrolyte on high-surface-area electrodes and are characterized by short charging/discharging times and long cycle-life compared to batteries. Microscopic simulations are now widely used to characterize the structural, dynamical, and adsorption properties of these devices, complementing electrochemical experiments and in situ spectroscopic analyses. In this review, we discuss the main families of simulation methods that have been developed and their application to the main family of EDLCs, which include nanoporous carbon electrodes. We focus on the adsorption of organic ions for electricity storage applications as well as aqueous systems in the context of blue energy harvesting and desalination. We finally provide perspectives for further improvement of the predictive power of simulations, in particular for future devices with complex electrode compositions.

Controlling Hydronium Diffusivity in Model Proton Exchange Membranes

Fuel-cell-based proton exchange membranes (PEMs) show great potential as cost-effective and clean energy conversion devices. In our recent work, we found that for the low-hydrated model PEMs with a inhomogeneous water distribution and a sulfonate anionic functional end group (SO₃^-), the H₃O⁺ reacts with SO₃^- according to SO₃^- + H₃O⁺ ↔ SO₃H + H₂O, indicating that the anions in PEMs become active participants in the hydronium diffusion. In this work, we use fully atomistic ab initio molecular dynamics simulations to elucidate the optimal conditions that would promote the participation of SO₃^- in the hydronium diffusion mechanism by increasing the H₃O⁺/SO₃^- reactivity, thus increasing the hydronium diffusivity along the cell. The results presented in this work allow us to suggest a set of design rules for creating novel, highly conductive PEMs operating at high temperatures under a nonuniform water distribution using a linker/anion with a relatively high pK_a such as (CH₂)₂SO₃. We expect that the discovery of these key design principles will play an important role in the synthesis of high-performing materials for emerging PEM-based fuel cell technologies.

Multi-scale simulation of the adsorption of lithium ion on graphite surface: From quantum Monte Carlo to molecular density functional theory

The structure of the double-layer formed at the surface of carbon electrodes is governed by the interactions between the electrode and the electrolyte species. However, carbon is notoriously difficult to simulate accurately, even with well-established methods such as electronic density functional theory and molecular dynamics. Here, we focus on the important case of a lithium ion in contact with the surface of graphite, and we perform a series of reference quantum Monte Carlo calculations that allow us to benchmark various electronic density functional theory functionals. We then fit an accurate carbon–lithium pair potential, which is used in molecular density functional theory calculations to determine the free energy of the adsorption of the ion on the surface in the presence of water. The adsorption profile in aqueous solution differs markedly from the gas phase results, which emphasize the role of the solvent on the properties of the double-layer.

Capturing Individual Hydrogen Bond Strengths in Ices via Periodic Local Vibrational Mode Theory: Beyond the Lattice Energy Picture

Local stretching force constants derived from periodic local vibrational modes at the vdW-DF2 density functional level have been employed to quantify the intrinsic hydrogen bond strength of 16 ice polymorphs, ices Ih, II, III, IV, V, VI, VII, VIII, IX, XI, XII, XIII, XIV, XV, XVII, and XIX, that are stable under ambient to elevated pressures. Based on this characterization on 1820 hydrogen bonds, relationships between local stretching force constants and structural parameters such as hydrogen bond length and angle were identified. Moreover, different bond strength distributions, from uniform to inhomogeneous, were observed for the 16 ices and could be explained in relation to different local structural elements within ices, that is, rings, that consist of different hydrogen bond types. In addition, criteria for the classification of hydrogen bonds as strong, intermediate, and weak were introduced. The latter was used to explore a different dimension of the water-ice phase diagram. These findings will provide important guidelines for assessing the credibility of new ice structures.

A Dispersion Corrected DFT Investigation of the Inclusion Complexation of Dexamethasone with β-Cyclodextrin and Molecular Docking Study of Its Potential Activity against COVID-19

The encapsulation mode of dexamethasone (Dex) into the cavity of β-cyclodextrin (β-CD), as well as its potential as an inhibitor of the COVID-19 main protease, were investigated using density functional theory with the recent dispersion corrections D4 and molecular docking calculations. Independent gradient model and natural bond orbital approaches allowed for the characterization of the host–guest interactions in the studied systems. Structural and energetic computation results revealed that hydrogen bonds and van der Waals interactions played significant roles in the stabilization of the formed Dex@β-CD complex. The complexation energy significantly decreased from −179.50 kJ/mol in the gas phase to −74.14 kJ/mol in the aqueous phase. A molecular docking study was performed to investigate the inhibitory activity of dexamethasone against the COVID-19 target protein (PDB ID: 6LU7). The dexamethasone showed potential therapeutic activity as a SARS CoV-2 main protease inhibitor due to its strong binding to the active sites of the protein target, with predicted free energy of binding values of −29.97 and −32.19 kJ/mol as calculated from AutoDock4 and AutoDock Vina, respectively. This study was intended to explore the potential use of the Dex@β-CD complex in drug delivery to enhance dexamethasone dissolution, thus improving its bioavailability and reducing its side effects.

Benchmark test of a dispersion corrected revised Tao-Mo semilocal functional for thermochemistry, kinetics, and noncovalent interactions of molecules and solids

In the density functional theory, dispersion corrected semilocal approximations are often used to benchmark weekly interacting finite and extended systems. Here, the focus is on providing a broad overview of the performance of D3 dispersion corrected revised Tao-Mo (revTM) semilocal functionals [A. Patra et al., J. Chem. Phys. 153, 084 117 (2020)] for thermochemistry and kinetics of molecules, molecular crystals, ice polymorphs, metal-organic systems, atom/molecular adsorption on solids, water interacting with nano-materials, binding energies of layered materials, and properties of weekly and strongly bonded solids. We show that the most suitable "optimized power" function for the revTM functional needs a modification to make it suitable for properties related to the diverse nature of finite and extended systems. The present work is an extension of the previously proposed revTM+D3 method with the motivation to design and benchmark the dispersion corrected cost-effective method based on this semilocal approximation. We show that the revised revTM+D3 functional provides various general purpose molecular and solid properties with the closest to experimental findings than its predecessor. The present assessment and benchmarking can be practically useful for performing cost-effective method based simulations of various molecular and solid-state properties.

Machine learning potentials for complex aqueous systems made simple

Understanding complex materials, in particular those with solid–liquid interfaces, such as water on surfaces or under confinement, is a key challenge for technological and scientific progress. Although established simulation approaches have been able to provide important atomistic insight, ab initio techniques struggle with the required time and length scales, while force field methods can often be limited in terms of their accuracy. Here we show how these limitations can be overcome in a simple and automated machine learning procedure to provide accurate models of interactions at the ab initio level, as illustrated for a variety of complex aqueous systems. These developments open up the prospect of the straightforward exploration of many technologically relevant systems by molecular simulations.

Simulation techniques based on accurate and efficient representations of potential energy surfaces are urgently needed for the understanding of complex systems such as solid–liquid interfaces. Here we present a machine learning framework that enables the efficient development and validation of models for complex aqueous systems. Instead of trying to deliver a globally optimal machine learning potential, we propose to develop models applicable to specific thermodynamic state points in a simple and user-friendly process. After an initial ab initio simulation, a machine learning potential is constructed with minimum human effort through a data-driven active learning protocol. Such models can afterward be applied in exhaustive simulations to provide reliable answers for the scientific question at hand or to systematically explore the thermal performance of ab initio methods. We showcase this methodology on a diverse set of aqueous systems comprising bulk water with different ions in solution, water on a titanium dioxide surface, and water confined in nanotubes and between molybdenum disulfide sheets. Highlighting the accuracy of our approach with respect to the underlying ab initio reference, the resulting models are evaluated in detail with an automated validation protocol that includes structural and dynamical properties and the precision of the force prediction of the models. Finally, we demonstrate the capabilities of our approach for the description of water on the rutile titanium dioxide (110) surface to analyze the structure and mobility of water on this surface. Such machine learning models provide a straightforward and uncomplicated but accurate extension of simulation time and length scales for complex systems.

Adsorption and reaction mechanisms of single and double H2O molecules on graphene surfaces with defects: a density functional theory study

More attention needs to be drawn to the high application value of the gasification reaction between carbonaceous materials and water in industry. In this study, density functional theory is used to investigate the adsorption and reaction mechanism of water molecules on graphene surfaces with various kinds of defects. The desorption mechanism of the reaction product is also analyzed. The optimal and stable physical adsorption configuration of water molecules on the pristine graphene and various defects graphene surface has been determined. Chemisorption configurations of a single water molecule and double water molecules on the graphene surface with single vacancy defects are discussed and used as reaction precursors to explore the reaction path of water molecules in the process of desorbing hydrogen at active sites. The whole process of the reaction is largely exothermic and the thermodynamic advantages of double water molecules participating in the reaction are determined. The two reaction mechanisms of two-steps or co-adsorption and desorption of double water molecules are compared, and the lowest energy barrier advantage of the latter is determined.

Confinement-Controlled Aqueous Chemistry within Nanometric Slit Pores

In this Focus Review, we put the spotlight on very recent insights into the fascinating world of wet chemistry in the realm offered by nanoconfinement of water in mechanically rather rigid and chemically inert planar slit pores wherein only monolayer and bilayer water lamellae can be hosted. We review the effect of confinement on different aspects such as hydrogen bonding, ion diffusion, and charge defect migration of H⁺(aq) and OH^-(aq) in nanoconfined water depending on slit pore width. A particular focus is put on the strongly modulated local dielectric properties as quantified in terms of anisotropic polarization fluctuations across such extremely confined water films and their putative effects on chemical reactions therein. The stunning findings disclosed only recently extend wet chemistry in particular and solvation science in general toward extreme molecular confinement conditions.

First-Principles Molecular Dynamics Simulations of the Spontaneous Freezing Transition of 2D Water in a Nanoslit

As with bulk ices, two-dimensional (2D) ices exhibit diverse crystalline structures, and the majority of these 2D structures have been predicted based on classical molecular dynamics (MD) simulations. Here, the spontaneous freezing transition of 2D liquid water within hydrophobic nanoslits is demonstrated for the first time using first-principles MD simulations. Various 2D ices are observed under different lateral pressure and temperature conditions. Notably, the liquid water confined to a 6.0 Å-wide nanoslit can spontaneously freeze into a monolayer ice consisting of an array of zigzag water chains at 2.5 GPa and 250 K. Moreover, within an 8.0 Å-wide nanoslit and at 4.0 GPa and 300 K, a previously unreported bilayer ice forms spontaneously that has a structure resembling that of the double surface layers of bulk ice-VII. Both 2D crystalline ices do not obey the ice rule, suggesting first-principles simulation can access a certain phase space that is not easily approached using classical simulations.

How do the doping concentrations of N and B in graphene modify the water adsorption?

Understanding the interaction of water and graphene is crucial for various applications such as water purification, desalination, and electrocatalysis. Experimental and theoretical studies have already investigated water adsorption on N- and B-doped graphene. However, there are no reports available that elucidate the influences of the N and B doping content in graphene on the microscopic geometrical structure and the electronic properties of the adsorbed water. Thus, this work is devoted to solving this problem using self-consistent van der Waals density functional theory calculations. The N and B doping contents of 0.0, 3.1, 6.3, and 9.4% were considered. The results showed that the binding energy of water increases almost linearly as a function of doping content at all concentrations for N-doped graphene but below 6.3% for B-doped graphene. In the linear range, the binding energy increases by approximately 30 meV for each increment of the doping ratio. Analyses of the geometric and electronic structures explained the enhancement of the water-graphene interaction with the variation in doping percentage.

Adsorption of toxic gases on borophene: surface deformation links to chemisorptions

β₁₂ borophene has received great attention because of its intriguing mechanical and electronic properties. One of the possible applications of borophene is gas sensing. However, the interaction between common gases and β₁₂ borophene remains to be clarified. In this work, we study the interactions of β₁₂ borophene towards five hazardous gases, namely, CO, NO, NH₃, NO₂, and CO₂ using various non-empirical van der Waals density functionals and provide an insight into the adsorption behavior of borophene. The adsorption mechanism and molecular vibrations are discussed in great detail. Among the gases considered, CO₂ is physisorbed while other gases are chemically bonded to β₁₂ borophene. We also demonstrate that the deformation at the ridge of borophene enables its active p_z orbital to strongly hybridize with frontier orbitals of the studied polar gases. Consequently, borophene is predicted to interact strongly with CO, NO, NH₃, and especially NO₂, making it a sensitive sensing material for toxic gases.

β₁₂ borophene has received great attention because of its intriguing mechanical and electronic properties. One of the possible applications of borophene is gas sensing.

Theoretical Prediction of Two-Dimensional Materials, Behavior, and Properties

Predictive modeling of two-dimensional (2D) materials is at the crossroad of two current rapidly growing interests: 2D materials per se, massively sought after and explored in experimental laboratories, and materials theoretical-computational models in general, flourishing on a fertile mix of condensed-matter physics and chemistry with advancing computational technology. Here the general methods and specific techniques of modeling are briefly overviewed, along with a somewhat philosophical assessment of what "prediction" is, followed by selected practical examples for 2D materials, from structures and properties, to device functionalities and synthetic routes for their making. We conclude with a brief sketch-outlook of future developments.

Solid wetting-layers in inorganic nano-reactors: the water in imogolite nanotube case

By combined use of wide-angle X-ray scattering, thermo-gravimetric analysis, inelastic neutron scattering, density functional theory and density functional theory molecular dynamics simulations, we investigate the structure, dynamics and stability of the water wetting-layer in single-walled aluminogermanate imogolite nanotubes (SW Ge-INTs): an archetypal system for synthetically controllable and monodisperse nano-reactors. We demonstrate that the water wetting-layer is strongly bound and solid-like up to 300 K under atmospheric pressure, with dynamics markedly different from that of bulk water. Atomic-scale characterisation of the wetting-layer reveals organisation of the H₂O molecules in a curved triangular sublattice stabilised by the formation of three H-bonds to the nanotube's inner surface, with covalent interactions sufficiently strong to promote energetically favourable decoupling of the H₂O molecules in the adlayer. The evidenced changes in the local composition, structure, electrostatics and dynamics of the Ge-INT's inner surface upon the formation of the solid wetting-layer demonstrate solvent-mediated functionalisation of the nanotube's cavity at room temperature and pressure, suggesting new strategies for the design of nano-rectors towards potential control of chemical reactivity in nano-confined volumes.

Quantifying anisotropic dielectric response properties of nanoconfined water within graphene slit pores

Water presents puzzling properties once it gets confined, in particular its dielectric response becomes highly anisotropic. Here, we analyze the dielectric response of water within graphene slit pores based on molecular dynamics simulations.

Vibrational mode frequency correction of liquid water in density functional theory molecular dynamics simulations with van der Waals correction

We develop a frequency correction scheme for the stretch and bending modes of liquid water, which substantially improves the prediction of the vibrational spectra.