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The van der Waals (vdWs) forces between monolayers has been a unique distinguishing feature of exfoliable materials since the first isolation of graphene. However, the vdWs interaction of exfoliable materials with their substrates and how this interface force influences their interaction with the environment is yet to be well understood.Here, we experimentally and theoretically unravel the role of vdWs forces between the recently rediscovered wide band gap p-type vdW semiconductor violet phosphorus (VP), with various substrates (including, SiO$_2$, mica, Si, Au) and quantify how VP stability in air and its interaction with its surroundings is influenced by the interface force.Using a combination of infrared nanoimaging and theoretical modeling we find the vdWs force at the interface to be a main factor that influences how VP interacts with its surroundings.In addition, the hydrophobicity of the substrate and the substrate surface roughness modify the vdWs force there by influencing VP stability. Our results could guide in the selection of substrates when vdW materials are prepared and more generally highlight the key role of interface force effects that could significantly alter physical properties of vdWs materials.

We provide a new variational definition for the spread of an orbital under periodic boundary conditions (PBCs) that is continuous with respect to the gauge, consistent in the thermodynamic limit, well-suited to diffuse orbitals, and systematically adaptable to schemes computing localized Wannier functions. Existing definitions do not satisfy all these desiderata, partly because they depend on an "orbital center"-an ill-defined concept under PBCs. Based on this theoretical development, we showcase a robust and efficient (10x-70x fewer iterations) localization scheme across a range of materials., Comment: 11 pages, 6 figures

Consistency between the exchange-correlation (xc) functional used during pseudopotential construction and planewave-based electronic structure calculations is important for an accurate and reliable description of the structure and properties of condensed-phase systems. In this work, we present a general scheme for constructing pseudopotentials with range-separated hybrid (RSH) xc functionals based on the solution of the all-electron radial integro-differential equation for a spherical atomic configuration. As proof-of-principle, we demonstrate pseudopotential construction with the PBE, PBE0, HSE, and sRSH (based on LC-$\omega$PBE0) xc functionals for a select set of atoms, and then investigate the importance of pseudopotential consistency when computing band gaps, equilibrium lattice parameters, bulk moduli, and atomization energies of several solid-state systems. In doing so, we find that pseudopotential consistency errors (PSCE) tend to be systematic and can be as large as $1.4\%$ when computing these properties.

High-throughput DFT calculations are key to screening existing/novel materials, sampling potential energy surfaces, and generating quantum mechanical data for machine learning. By including a fraction of exact exchange (EXX), hybrid functionals reduce the self-interaction error in semi-local DFT and furnish a more accurate description of the underlying electronic structure, albeit at a high computational cost that often prohibits such high-throughput applications. To address this challenge, we have constructed SeA (SeA=SCDM+exx+ACE), a robust, accurate, and efficient framework for high-throughput condensed-phase hybrid DFT in the PWSCF module of Quantum ESPRESSO (QE) by combining: (1) the non-iterative selected columns of the density matrix (SCDM) orbital localization scheme, (2) a black-box and linear-scaling EXX algorithm (exx), and (3) adaptively compressed exchange (ACE). Across a diverse set of non-equilibrium (H$_2$O)$_{64}$ configurations (with densities spanning 0.4 g/cm$^3$$-$1.7 g/cm$^3$), SeA yields a one$-$two order-of-magnitude speedup (~8X$-$26X) in the overall time-to-solution compared to PWSCF(ACE) in QE (~78X$-$247X speedup compared to the conventional EXX implementation) and yields energies, ionic forces, and other properties with high fidelity. As a proof-of-principle high-throughput application, we trained a deep neural network (DNN) potential for ambient liquid water at the hybrid DFT level using SeA via an actively learned data set with ~8,700 (H$_2$O)$_{64}$ configurations. Using an out-of-sample set of (H$_2$O)$_{512}$ configurations (at non-ambient conditions), we confirmed the accuracy of this SeA-trained potential and showcased the capabilities of SeA by computing the ground-truth ionic forces in this challenging system containing > 1,500 atoms., Comment: 23 pages, 5 figures, 3 tables

In this work, we present a general framework that unites the two primary strategies for constructing density functional approximations (DFAs): non-empirical (NE) constraint satisfaction and semi-empirical (SE) data-driven optimization. The proposed method employs B-splines -- bell-shaped spline functions with compact support -- to construct each inhomogeneity correction factor (ICF). This choice offers several distinct advantages over a polynomial basis by enabling explicit enforcement of linear and non-linear constraints as well as ICF smoothness using Tikhonov regularization and penalized B-splines (P-splines). As proof of concept, we use this approach to construct CASE21 -- a Constrained And Smoothed semi-Empirical hybrid generalized gradient approximation that completely satisfies all but one constraint (and partially satisfies the remaining one) met by the PBE0 NE-DFA and exhibits enhanced performance across a diverse set of chemical properties. As such, we argue that the paradigm presented herein maintains the physical rigor and transferability of NE-DFAs while leveraging high-quality quantum-mechanical data to improve performance., Comment: 8 pages, 3 figures, 1 scheme

We extend the selected columns of the density matrix (SCDM) methodology [J. Chem. Theory Comput. 2015, 11, 1463--1469]---a non-iterative procedure for generating localized occupied orbitals for condensed-phase systems---to the construction of local molecular orbitals (LMOs) in systems described using non-orthogonal atomic orbital (AO) basis sets. In particular, we introduce three different variants of SCDM (referred to as SCDM-M, SCDM-L, and SCDM-G) that can be used in conjunction with the standard AO basis sets. The SCDM-M and SCDM-L variants are based on the Mulliken and L{\"o}wdin representations of the density matrix, and are tantamount to selecting a well-conditioned set of projected atomic orbitals (PAOs) and projected (symmetrically-) orthogonalized atomic orbitals (POAOs), respectively, as proto-LMOs. The SCDM-G variant leverages a real-space (grid) representation of the wavefunction to select a set of well-conditioned proto-LMOs. A detailed comparative analysis reveals that the LMOs generated by these three SCDM variants are robust, comparable in orbital locality to those produced with the iterative Boys or Pipek-Mezey (PM) localization schemes, and are agnostic towards any single orbital locality metric. Although all three SCDM variants are based on the density matrix, we find that the character of the generated LMOs can differ significantly between SCDM-M, SCDM-L, and SCDM-G. In this regard, only the grid-based SCDM-G procedure (like PM) generates LMOs that qualitatively preserve $\sigma\text{-}\pi$ symmetry and are well-aligned with chemical intuition. While the direct and standalone use of SCDM-generated LMOs should suffice for most applications, our findings also suggest that the use of these orbitals as an unbiased and cost-effective (initial) guess also has the potential to improve the convergence of iterative orbital localization schemes., Comment: 21 pages; 12 figures

In this work, we present NENCI-2021, a benchmark database of approximately $8,000$ non-equilibrium non-covalent interaction energies for a large and diverse selection of intermolecular complexes of biological and chemical relevance. To meet the growing demand for large and high-quality quantum mechanical data in the chemical sciences, NENCI-2021 starts with the $101$ molecular dimers in the widely used S66 and S101 databases, and extends the scope of these works by: (i) including $40$ cation- and anion-$\pi$ complexes, a fundamentally important class of non-covalent interactions (NCIs) that are found throughout nature and pose a substantial challenge to theory, and (ii) systematically sampling all $141$ intermolecular potential energy surfaces (PES) by simultaneously varying the intermolecular distance and intermolecular angle in each dimer. Designed with an emphasis on close contacts, the complexes in NENCI-2021 were generated by sampling seven intermolecular distances along each PES (ranging from $0.7\times\mathrm{-}1.1\times$ the equilibrium separation) as well as nine intermolecular angles per distance (five for each ion-$\pi$ complex), yielding an extensive database of $7,763$ benchmark intermolecular interaction energies ($E_{\rm int}$) obtained at the CCSD(T)/CBS level of theory. In addition, a wide range of intermolecular atom-pair distances are also present in NENCI-2021, where close intermolecular contacts involving atoms that are located within the so-called van der Waals envelope are prevalent -- these interactions in particular pose an enormous challenge for molecular modeling and are observed in many important chemical and biological systems. A detailed SAPT-based energy decomposition analysis also confirms the diverse and comprehensive nature of the intermolecular binding motifs present in NENCI-2021., Comment: 20 pages, 6 figures

In the previous paper of this series [JCTC 2020, 16, 3757], we presented a theoretical and algorithmic framework based on a localized representation of the occupied space that exploits the inherent sparsity in the real-space evaluation of the EXX interaction in finite-gap systems. This was accompanied by a detailed description of exx, a massively parallel hybrid MPI/OpenMP implementation of this approach in Quantum ESPRESSO that enables linear-scaling hybrid DFT based AIMD in the NVE/NVT ensembles of condensed-phase systems containing 500--1000 atoms (in fixed orthorhombic cells) with a wall time cost comparable to semi-local DFT. In this work, we extend exx to enable hybrid DFT based AIMD of large-scale condensed-phase systems with general and fluctuating cells in the NpH/NpT ensembles. Our theoretical extension includes an analytical derivation of the EXX contribution to the stress tensor for systems in general cells with a computational complexity that scales linearly with system size. The corresponding algorithmic extensions to exx include optimized routines that: (i) handle static/fluctuating cells with non-orthogonal lattice symmetries, (ii) solve Poisson's equation in general cells via an automated selection of the auxiliary grid directions in the Natan-Kronik representation of the discrete Laplacian operator, and (iii) evaluate the EXX contribution to the stress tensor. We also critically assess the computational performance of the extended exx module across several different HPC architectures via case studies on ice Ih, II, and III as well as ambient liquid water. We find that the extended exx can evaluate the EXX contribution to the stress tensor with negligible cost (< 1%) and remains highly scalable, thereby bringing us another step closer to routinely performing hybrid DFT based AIMD for large-scale condensed-phase systems across a wide range of thermodynamic conditions., Comment: 30 pages and 5 figures

We introduce QM7-X, a comprehensive dataset of 42 physicochemical properties for $\approx$ 4.2 M equilibrium and non-equilibrium structures of small organic molecules with up to seven non-hydrogen (C, N, O, S, Cl) atoms. To span this fundamentally important region of chemical compound space (CCS), QM7-X includes an exhaustive sampling of (meta-)stable equilibrium structures - comprised of constitutional/structural isomers and stereoisomers, e.g., enantiomers and diastereomers (including cis-/trans- and conformational isomers) - as well as 100 non-equilibrium structural variations thereof to reach a total of $\approx$ 4.2 M molecular structures. Computed at the tightly converged quantum-mechanical PBE0+MBD level of theory, QM7-X contains global (molecular) and local (atom-in-a-molecule) properties ranging from ground state quantities (such as atomization energies and dipole moments) to response quantities (such as polarizability tensors and dispersion coefficients). By providing a systematic, extensive, and tightly-converged dataset of quantum-mechanically computed physicochemical properties, we expect that QM7-X will play a critical role in the development of next-generation machine-learning based models for exploring greater swaths of CCS and performing in silico design of molecules with targeted properties.

The molecular dipole moment ($\boldsymbol{\mu}$) is a central quantity in chemistry. It is essential in predicting infrared and sum-frequency generation spectra, as well as induction and long-range electrostatic interactions. Furthermore, it can be extracted directly from high-level quantum mechanical calculations, making it an ideal target for machine learning (ML). In this work, we choose to represent this quantity with a physically inspired ML model that captures two distinct physical effects: local atomic polarization is captured within the symmetry-adapted Gaussian process regression (SA-GPR) framework, which assigns a (vector) dipole moment to each atom, while movement of charge across the entire molecule is captured by assigning a partial (scalar) charge to each atom. The resulting "MuML" models are fitted together to reproduce molecular $\boldsymbol{\mu}$ computed using high-level coupled-cluster theory (CCSD) and density functional theory (DFT) on the QM7b dataset. The combined model shows excellent transferability when applied to a showcase dataset of larger and more complex molecules, approaching the accuracy of DFT at a small fraction of the computational cost. We also demonstrate that the uncertainty in the predictions can be estimated reliably using a calibrated committee model. The ultimate performance of the models depends, however, on the details of the system at hand, with the scalar model being clearly superior when describing large molecules whose dipole is almost entirely generated by charge separation. These observations point to the importance of simultaneously accounting for the local and non-local effects that contribute to $\boldsymbol{\mu}$; further, they define a challenging task to benchmark future models, particularly those aimed at the description of condensed phases., Comment: 16 pages, 7 figures, plus supplementary information; added Materials Cloud link and corrected values in Table I. To be published in the Journal of Chemical Physics

By including a fraction of exact exchange (EXX), hybrid functionals reduce the self-interaction error in semi-local density functional theory (DFT), and thereby furnish a more accurate and reliable description of the electronic structure in systems throughout biology, chemistry, physics, and materials science. However, the high computational cost associated with the evaluation of all required EXX quantities has limited the applicability of hybrid DFT in the treatment of large molecules and complex condensed-phase materials. To overcome this limitation, we have devised a linear-scaling yet formally exact approach that utilizes a local representation of the occupied orbitals (e.g., maximally localized Wannier functions, MLWFs) to exploit the sparsity in the real-space evaluation of the quantum mechanical exchange interaction in finite-gap systems. In this work, we present a detailed description of the theoretical and algorithmic advances required to perform MLWF-based ab initio molecular dynamics (AIMD) simulations of large-scale condensed-phase systems at the hybrid DFT level. We provide a comprehensive description of the exx algorithm, which is currently implemented in the Quantum ESPRESSO program and employs a hybrid MPI/OpenMP parallelization scheme to efficiently utilize high-performance computing (HPC) resources. This is followed by a critical assessment of the accuracy and parallel performance of this approach when performing AIMD simulations of liquid water in the canonical ensemble. With access to HPC resources, we demonstrate that exx enables hybrid DFT based AIMD simulations of condensed-phase systems containing 500-1000 atoms with a walltime cost that is comparable to semi-local DFT. In doing so, exx takes us closer to routinely performing AIMD simulations of large-scale condensed-phase systems for sufficiently long timescales at the hybrid DFT level of theory., Comment: 34 pages and 10 figures

A comprehensive microscopic understanding of ambient liquid water is a major challenge for $ab$ $initio$ simulations as it simultaneously requires an accurate quantum mechanical description of the underlying potential energy surface (PES) as well as extensive sampling of configuration space. Due to the presence of light atoms (e.g., H or D), nuclear quantum fluctuations lead to observable changes in the structural properties of liquid water (e.g., isotope effects), and therefore provide yet another challenge for $ab$ $initio$ approaches. In this work, we demonstrate that the combination of dispersion-inclusive hybrid density functional theory (DFT), the Feynman discretized path-integral (PI) approach, and machine learning (ML) constitutes a versatile $ab$ $initio$ based framework that enables extensive sampling of both thermal and nuclear quantum fluctuations on a quite accurate underlying PES. In particular, we employ the recently developed deep potential molecular dynamics (DPMD) model---a neural-network representation of the $ab$ $initio$ PES---in conjunction with a PI approach based on the generalized Langevin equation (PIGLET) to investigate how isotope effects influence the structural properties of ambient liquid H$_2$O and D$_2$O. Through a detailed analysis of the interference differential cross sections as well as several radial and angular distribution functions, we demonstrate that this approach can furnish a semi-quantitative prediction of these subtle isotope effects., Comment: 19 pages, 5 figures, and 1 table

The molecular polarizability describes the tendency of a molecule to deform or polarize in response to an applied electric field. As such, this quantity governs key intra- and inter-molecular interactions such as induction and dispersion, plays a key role in determining the spectroscopic signatures of molecules, and is an essential ingredient in polarizable force fields and other empirical models for collective interactions. Compared to other ground-state properties, an accurate and reliable prediction of the molecular polarizability is considerably more difficult as this response quantity is quite sensitive to the description of the underlying molecular electronic structure. In this work, we present state-of-the-art quantum mechanical calculations of the static dipole polarizability tensors of 7,211 small organic molecules computed using linear-response coupled-cluster singles and doubles theory (LR-CCSD). Using a symmetry-adapted machine-learning based approach, we demonstrate that it is possible to predict the molecular polarizability with LR-CCSD accuracy at a negligible computational cost. The employed model is quite robust and transferable, yielding molecular polarizabilities for a diverse set of 52 larger molecules (which includes challenging conjugated systems, carbohydrates, small drugs, amino acids, nucleobases, and hydrocarbon isomers) at an accuracy that exceeds that of hybrid density functional theory (DFT). The atom-centered decomposition implicit in our machine-learning approach offers some insight into the shortcomings of DFT in the prediction of this fundamental quantity of interest.

The ability to reliably predict the structures and stabilities of a molecular crystal and its polymorphs without any prior experimental information would be an invaluable tool for a number of fields, with specific and immediate applications in the design and formulation of pharmaceuticals. In this case, detailed knowledge of the polymorphic energy landscape for an active pharmaceutical ingredient yields profound insight regarding the existence and likelihood of late-appearing polymorphs. However, the computational prediction of the structures and stabilities of molecular crystal polymorphs is particularly challenging due to the high dimensionality of conformational and crystallographic space accompanied by the need for relative (free) energies to within $\approx$ 1 kJ/mol per molecule. In this work, we combine the most successful crystal structure sampling strategy with the most accurate energy ranking strategy of the latest blind test of organic crystal structure prediction (CSP), organized by the Cambridge Crystallographic Data Centre (CCDC). Our final energy ranking is based on first-principles density functional theory (DFT) calculations that include three key physical contributions: (i) a sophisticated treatment of Pauli exchange-repulsion and electron correlation effects with hybrid functionals, (ii) inclusion of many-body van der Waals dispersion interactions, and (iii) account of vibrational free energies. In doing so, this combined approach has an optimal success rate in producing the crystal structures corresponding to the five blind-test molecules. With this practical approach, we demonstrate the feasibility of obtaining reliable structures and stabilities for molecular crystals of pharmaceutical importance, paving the way towards an enhanced fundamental understanding of polymorphic energy landscapes and routine industrial application of molecular CSP methods.

We explore how anharmonicity, nuclear quantum effects (NQE), many-body dispersion interactions, and Pauli repulsion influence thermal properties of dispersion-bound molecular crystals. Accounting for anharmonicity with $ab$ $initio$ molecular dynamics yields cell parameters accurate to within 2% of experiment for a set of pyridine-like molecular crystals at finite temperatures and pressures. From the experimental thermal expansion curve, we find that pyridine-I has a Debye temperature just above its melting point, indicating sizable NQE across the entire crystalline range of stability. We find that NQE lead to a substantial volume increase in pyridine-I ($\approx 40$% more than classical thermal expansion at $153$ K) and attribute this to intermolecular Pauli repulsion promoted by intramolecular quantum fluctuations. When predicting delicate properties such as the thermal expansivity, we show that many-body dispersion interactions and sophisticated treatments of Pauli repulsion are needed in dispersion-bound molecular crystals.

Proton transfer via hydronium and hydroxide ions in water is ubiquitous. It underlies acid-base chemistry, certain enzyme reactions, and even infection by the flu. Despite two-centuries of investigation, the mechanism underlying why hydronium diffuses faster than hydroxide in water is still not well understood. Herein, we employ state of the art Density Functional Theory based molecular dynamics, with corrections for nonlocal van der Waals interactions, and self-interaction in the electronic ground state, to model water and the hydrated water ions. At this level of theory, structural diffusion of hydronium preserves the previously recognized concerted behavior. However, by contrast, proton transfer via hydroxide is dominated by stepwise events, arising from a stabilized hyper-coordination solvation structure that discourages proton transfer. Specifically, the latter exhibits non-planar geometry, which agrees with neutron scattering results. Asymmetry in the temporal correlation of proton transfer enables hydronium to diffuse faster than hydroxide., Comment: accepted by Nature Chemistry, more information will be updated once published

Classical intermolecular potentials typically require an extensive parametrization procedure for any new compound considered. To do away with prior parametrization, we propose a combination of physics-based potentials with machine learning (ML), coined IPML, which is transferable across small neutral organic and biologically-relevant molecules. ML models provide on-the-fly predictions for environment-dependent local atomic properties: electrostatic multipole coefficients (significant error reduction compared to previously reported), the population and decay rate of valence atomic densities, and polarizabilities across conformations and chemical compositions of H, C, N, and O atoms. These parameters enable accurate calculations of intermolecular contributions---electrostatics, charge penetration, repulsion, induction/polarization, and many-body dispersion. Unlike other potentials, this model is transferable in its ability to handle new molecules and conformations without explicit prior parametrization: All local atomic properties are predicted from ML, leaving only eight global parameters---optimized once and for all across compounds. We validate IPML on various gas-phase dimers at and away from equilibrium separation, where we obtain mean absolute errors between 0.4 and 0.7 kcal/mol for several chemically and conformationally diverse datasets representative of non-covalent interactions in biologically-relevant molecules. We further focus on hydrogen-bonded complexes---essential but challenging due to their directional nature---where datasets of DNA base pairs and amino acids yield an extremely encouraging 1.4 kcal/mol error. Finally, and as a first look, we consider IPML in denser systems: water clusters, supramolecular host-guest complexes, and the benzene crystal., Comment: 15 pages, 9 figures

Epitaxy forms the basis of modern electronics and optoelectronics. We report coherent atomically-thin superlattices, in which different transition metal dichalcogenide monolayers--despite large lattice mismatches--are repeated and integrated without dislocations. Grown by a novel omnidirectional epitaxy, these superlattices display fully-matched lattice constants across heterointerfaces while maintaining a surprisingly isotropic lattice structure and triangular symmetry. This strong epitaxial strain is precisely engineered via the nanoscale supercell dimensions, thereby enabling broad tuning of the optical properties and producing photoluminescence peak shifts as large as 250 meV. We present theoretical models to explain this coherent growth as well as the energetic interplay governing the flat-rippled configuration space in these strained monolayers. Such coherent superlattices provide novel building blocks with targeted functionalities at the atomically-thin monolayer limit., Comment: 4 main figures and 11 supplementary figures

Accurate treatment of the long-range electron correlation energy, including van der Waals (vdW) or dispersion interactions, is essential for describing the structure, dynamics, and function of a wide variety of systems. Among the most accurate models for including dispersion into density functional theory (DFT) is the range-separated many-body dispersion (MBD) method [A. Ambrossetti et al., J. Chem. Phys. 140, 18A508 (2014)], in which the correlation energy is modeled at short-range by a semi-local density functional and at long-range by a model system of coupled quantum harmonic oscillators. In this work, we develop analytical gradients of the MBD energy with respect to nuclear coordinates, including all implicit coordinate dependencies arising from the partitioning of the charge density into Hirshfeld effective volumes. To demonstrate the efficiency and accuracy of these MBD gradients for geometry optimizations of systems with intermolecular and intramolecular interactions, we optimized conformers of the benzene dimer and isolated small peptides with aromatic side-chains. We find excellent agreement with the wavefunction theory reference geometries of these systems (at a fraction of the computational cost) and find that MBD consistently outperforms the popular TS and D3(BJ) dispersion corrections. To demonstrate the performance of the MBD model on a larger system with supramolecular interactions, we optimized the C$_{60}$@C$_{60}$H$_{28}$ buckyball catcher host-guest complex. Finally, we find that neglecting the implicit nuclear coordinate dependence arising from the charge density partitioning, as has been done in prior numerical treatments, leads to an unacceptable error in the MBD forces, with relative errors of ~20% (on average) that can extend well beyond 100%., Comment: 18 pages including 5 figures; plus 9 pages supplementary information including 5 additional figures

Positioned between crystalline solids and liquids, disordered many-particle systems which are stealthy and hyperuniform represent new states of matter that are endowed with novel physical and thermodynamic properties. Such stealthy and hyperuniform states are unique in that they are transparent to radiation for a range of wavenumbers around the origin. In this work, we employ recently developed inverse statistical-mechanical methods, which seek to obtain the optimal set of interactions that will spontaneously produce a targeted structure or configuration as a unique ground state, to investigate the spin-spin interaction potentials required to stabilize disordered stealthy hyperuniform one-dimensional (1D) Ising-like spin chains. By performing an exhaustive search over the spin configurations that can be enumerated on periodic 1D integer lattices containing $N=2,3,\ldots,36$ sites, we were able to identify and structurally characterize \textit{all} stealthy hyperuniform spin chains in this range of system sizes. Within this pool of stealthy hyperuniform spin configurations, we then utilized such inverse optimization techniques to demonstrate that stealthy hyperuniform spin chains can be realized as either unique or degenerate disordered ground states of radial long-ranged (relative to the spin chain length) spin-spin interactions. Such exotic ground states are distinctly different from spin glasses in both their inherent structural properties and the nature of the spin-spin interactions required to stabilize them. As such, the implications and significance of the existence of such disordered stealthy hyperuniform ground state spin systems warrants further study, including whether their bulk physical properties and excited states, like their many-particle system counterparts, are singularly remarkable, and can be experimentally realized., Comment: 11 pages, 9 figures

In this work, the solvation and electronic structure of the aqueous chloride ion solution was investigated using Density Functional Theory (DFT) based \textit{ab initio} molecular dynamics (AIMD). From an analysis of radial distribution functions, coordination numbers, and solvation structures, we found that exact exchange ($E_{\rm xx}$) and non-local van der Waals (vdW) interactions effectively \textit{weaken} the interactions between the Cl$^-$ ion and the first solvation shell. With a Cl-O coordination number in excellent agreement with experiment, we found that most configurations generated with vdW-inclusive hybrid DFT exhibit 6-fold coordinated distorted trigonal prism structures, which is indicative of a significantly disordered first solvation shell. By performing a series of band structure calculations on configurations generated from AIMD simulations with varying DFT potentials, we found that the solvated ion orbital energy levels (unlike the band structure of liquid water) strongly depend on the underlying molecular structures. In addition, these orbital energy levels were also significantly affected by the DFT functional employed for the electronic structure; as the fraction of $E_{\rm xx}$ was increased, the gap between the highest occupied molecular orbital of Cl$^-$ and the valence band maximum of liquid water steadily increased towards the experimental value., Comment: 13 pages, 8 figures

Within the framework of density functional theory, the inclusion of exact exchange and non-local van der Waals/dispersion (vdW) interactions is crucial for predicting a microscopic structure of ambient liquid water that quantitatively agrees with experiment. In this work, we have used the local structure index (LSI) order parameter to analyze the local structure in such highly accurate $ab$ $initio$ liquid water. At ambient conditions, the LSI probability distribution, P($I$), was unimodal with most water molecules characterized by more disordered high-density-like local environments. With thermal excitations removed, the resultant bimodal P($I$) in the inherent potential energy surface (IPES) exhibited a 3:1 ratio between high- and low-density-like molecules, with the latter forming small connected clusters amid the predominant population. By considering the spatial correlations and hydrogen bond network topologies $among$ water molecules with the same LSI identities, we demonstrate that the signatures of the experimentally observed low- (LDA) and high-density (HDA) amorphous phases of ice are present in the IPES of ambient liquid water. Analysis of the LSI autocorrelation function uncovered a persistence time of $\sim$ 4 ps---a finding consistent with the fact that natural thermal fluctuations are responsible for transitions between these distinct yet transient local aqueous environments in ambient liquid water., Comment: 12 pages, 6 figures

In this work, we report the results of a series of density functional theory (DFT) based ab initio molecular dynamics (AIMD) simulations of ambient liquid water using a hierarchy of exchange-correlation (XC) functionals to investigate the individual and collective effects of exact exchange (Exx), via the PBE0 hybrid functional, non-local vdW/dispersion interactions, via a fully self-consistent density-dependent dispersion correction, and approximate nuclear quantum effects (aNQE), via a 30 K increase in the simulation temperature, on the microscopic structure of liquid water. Based on these AIMD simulations, we found that the collective inclusion of Exx, vdW, and aNQE as resulting from a large-scale AIMD simulation of (H$_2$O)$_{128}$ at the PBE0+vdW level of theory, significantly softens the structure of ambient liquid water and yields an oxygen-oxygen structure factor, $S_{\rm OO}(Q)$, and corresponding oxygen-oxygen radial distribution function, $g_{\rm OO}(r)$, that are now in quantitative agreement with the best available experimental data. This level of agreement between simulation and experiment as demonstrated herein originates from an increase in the relative population of water molecules in the interstitial region between the first and second coordination shells, a collective reorganization in the liquid phase which is facilitated by a weakening of the hydrogen bond strength by the use of the PBE0 hybrid XC functional, coupled with a relative stabilization of the resultant disordered liquid water configurations by the inclusion of non-local vdW/dispersion interactions.

An accurate determination of the electron correlation energy is essential for describing the structure, stability, and function in a wide variety of systems, ranging from gas-phase molecular assemblies to condensed matter and organic/inorganic interfaces. Even small errors in the correlation energy can have a large impact on the description of chemical and physical properties in the systems of interest. In this context, the development of efficient approaches for the accurate calculation of the long-range correlation energy (and hence dispersion) is the main challenge. In the last years a number of methods have been developed to augment density functional approximations via dispersion energy corrections, but most of these approaches ignore the intrinsic many-body nature of correlation effects, leading to inconsistent and sometimes even qualitatively incorrect predictions. Here we build upon the recent many-body dispersion (MBD) framework, which is intimately linked to the random-phase approximation for the correlation energy. We separate the correlation energy into short-range contributions that are modeled by semi-local functionals and long-range contributions that are calculated by mapping the complex all-electron problem onto a set of atomic response functions coupled in the dipole approximation. We propose an effective range-separation of the coupling between the atomic response functions that extends the already broad applicability of the MBD method to non-metallic materials with highly anisotropic responses, such as layered nanostructures. Application to a variety of high-quality benchmark datasets illustrates the accuracy and applicability of the improved MBD approach, which offers the prospect of first-principles modeling of large structurally complex systems with an accurate description of the long-range correlation energy., Comment: 15 pages, 3 figures

Interatomic pairwise methods are currently among the most popular and accurate ways to include dispersion energy in density functional theory (DFT) calculations. However, when applied to more than two atoms, these methods are still frequently perceived to be based on \textit{ad hoc} assumptions, rather than a rigorous derivation from quantum mechanics. Starting from the adiabatic connection fluctuation-dissipation (ACFD) theorem, an exact expression for the electronic exchange-correlation energy, we demonstrate that the pairwise interatomic dispersion energy for an arbitrary collection of isotropic polarizable dipoles emerges from the second-order expansion of the ACFD formula. Moreover, for a system of quantum harmonic oscillators coupled through a dipole--dipole potential, we prove the equivalence between the full interaction energy obtained from the Hamiltonian diagonalization and the ACFD correlation energy in the random-phase approximation. This property makes the Hamiltonian diagonalization an efficient method for the calculation of the many-body dispersion energy. In addition, we show that the switching function used to damp the dispersion interaction at short distances arises from a short-range screened Coulomb potential, whose role is to account for the spatial spread of the individual atomic dipole moments. By using the ACFD formula we gain a deeper understanding of the approximations made in the interatomic pairwise approaches, providing a powerful formalism for further development of accurate and efficient methods for the calculation of the dispersion energy.

Polymorphs in molecular crystals are often very close in energy, yet they may possess markedly different physical and chemical properties. The understanding and prediction of polymorphism is of paramount importance for a variety of applications, including pharmaceuticals, non-linear optics, and hydrogen storage. Here, we show that the non-additive many-body dispersion (MBD) energy beyond the standard pairwise approximation is crucial for the correct qualitative and quantitative description of polymorphism in molecular crystals. This is rationalized by the sensitive dependence of the MBD energy on the polymorph geometry and the ensuing dynamic electric fields inside molecular crystals. We use the glycine crystal as a fundamental and stringent benchmark case to demonstrate the accuracy of the DFT+MBD method.