Accurate Force Fields for Atomistic Simulations of Oxides, Hydroxides, and Organic Hybrid Materials up to the Micrometer Scale

The simulation of metals, oxides, and hydroxides can accelerate the design of therapeutics, alloys, catalysts, cement-based materials, ceramics, bioinspired composites, and glasses. Here we introduce the INTERFACE force field (IFF) and surface models for α-Al2O3, α-Cr2O3, α-Fe2O3, NiO, CaO, MgO, β-Ca(OH)2, β-Mg(OH)2, and β-Ni(OH)2. The force field parameters are nonbonded, including atomic charges for Coulomb interactions, Lennard-Jones (LJ) potentials for van der Waals interactions with 12-6 and 9-6 options, and harmonic bond stretching for hydroxide ions. The models outperform DFT calculations and earlier atomistic models (Pedone, ReaxFF, UFF, CLAYFF) up to 2 orders of magnitude in reliability, compatibility, and interpretability due to a quantitative representation of chemical bonding consistent with other compounds across the periodic table and curated experimental data for validation. The IFF models exhibit average deviations of 0.2% in lattice parameters, <10% in surface energies (to the extent known), and 6% in bulk moduli relative to experiments. The parameters and models can be used with existing parameters for solvents, inorganic compounds, organic compounds, biomolecules, and polymers in IFF, CHARMM, CVFF, AMBER, OPLS-AA, PCFF, and COMPASS, to simulate bulk oxides, hydroxides, electrolyte interfaces, and multiphase, biological, and organic hybrid materials at length scales from atoms to micrometers. The nonbonded character of the models also enables the analysis of mixed oxides, glasses, and certain chemical reactions, and well-performing nonbonded models for silica phases, SiO2, are introduced. Automated model building is available in the CHARMM-GUI Nanomaterial Modeler. We illustrate applications of the models to predict the structure of mixed oxides, and energy barriers of ion migration, as well as binding energies of water and organic molecules in outstanding agreement with experimental data and calculations at the CCSD(T) level. Examples of model building for hydrated, pH-sensitive oxide surfaces to simulate solid-electrolyte interfaces are discussed.

Many-Body Methods for Surface Chemistry Come of Age: Achieving Consensus with Experiments

The adsorption energy of a molecule onto the surface of a material underpins a wide array of applications, spanning heterogeneous catalysis, gas storage, and many more. It is the key quantity where experimental measurements and theoretical calculations meet, with agreement being necessary for reliable predictions of chemical reaction rates and mechanisms. The prototypical molecule-surface system is CO adsorbed on MgO, but despite intense scrutiny from theory and experiment, there is still no consensus on its adsorption energy. In particular, the large cost of accurate many-body methods makes reaching converged theoretical estimates difficult, generating a wide range of values. In this work, we address this challenge, leveraging the latest advances in diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] to obtain accurate predictions for CO on MgO. These reliable theoretical estimates allow us to evaluate the inconsistencies in published temperature-programed desorption experiments, revealing that they arise from variations in employed pre-exponential factors. Utilizing this insight, we derive new experimental estimates of the (electronic) adsorption energy with a (more) precise pre-exponential factor. As a culmination of all of this effort, we are able to reach a consensus between multiple theoretical calculations and multiple experiments for the first time. In addition, we show that our recently developed cluster-based CCSD(T) approach provides a low-cost route toward achieving accurate adsorption energies. This sets the stage for affordable and reliable theoretical predictions of chemical reactions on surfaces to guide the realization of new catalysts and gas storage materials.

A density functional theory study on the adsorption of different organic sulfides on boron nitride nanosheet

The adsorption of methanethiol (MT), thiophene (T), benzothiophene (BT), dibenzothiophene (DBT) on hexagonal boron nitride (h-BN) has been investigated by the framework of the density functional theory (DFT) calculations in this work. The prefer adsorption sites and interfacial angles of different sulfur compounds on the surface of the h-BN are investigated and analyzed. The adsorption energy results indicated that the adsorption of MT (Ead ≈ -6 kcal mol-1), T (Ead ≈ -10 kcal mol-1), BT (Ead ≈ -15 kcal mol-1), and DBT (Ead ≈ -21 kcal mol-1) on monolayer h-BN is physical interaction, and the value of Ead on bilayer h-BN is more than that on monolayer h-BN 0.05%. Adsorptive conformations show that sulfides prefer to be adsorbed on center B atoms rather than N atoms. Meanwhile, thiophene and its analogues tend to be adsorbed parallel on h-BN plane. Energy decomposition, natural population analysis (NPA), and electrostatic potential (ESP) analysis used to better understand the nature of adsorption on h-BN. van der Waals force plays a dominant role in adsorption process. Due to the π-π interactions, T, BT, and DBT have larger van der Waals forces than MT and the value of adsorption energy is negative correlated to the number of benzene rings. These findings are helpful for deeper understanding the adsorptive desulfurization mechanism and help develop better adsorbents for desulfurization in the future.

Finite-Size Error Cancellation in Diffusion Monte Carlo Calculations of Surface Chemistry

The accurate prediction of reaction mechanisms in heterogeneous (surface) catalysis is one of the central challenges in computational chemistry. Quantum Monte Carlo methods─Diffusion Monte Carlo (DMC) in particular─are being recognized as higher-accuracy, albeit more computationally expensive, alternatives to Density Functional Theory (DFT) for energy predictions of catalytic systems. A major computational bottleneck in the broader adoption of DMC for catalysis is the need to perform finite-size extrapolations by simulating increasingly large periodic cells (supercells) to eliminate many-body finite-size effects and obtain energies in the thermodynamic limit. Here, we show that it is possible to significantly reduce this computational cost by leveraging the cancellation of many-body finite-size errors that accompanies the evaluation of energy differences when calculating quantities like adsorption (binding) energies and mapping potential energy surfaces. We analyze the cancellation and convergence of many-body finite-size errors in two well-known adsorbate/slab systems, H₂O/LiH(001) and CO/Pt(111). Based on this analysis, we identify strategies for obtaining binding energies in the thermodynamic limit that optimally utilize error cancellation to balance accuracy and computational efficiency. Using one such strategy, we then predict the correct order of adsorption site preference on CO/Pt(111), a challenging problem for a wide range of density functionals. Our accurate and inexpensive DMC calculations are found to unambiguously recover the top > bridge > hollow site order, in agreement with experimental observations. We proceed to use this DMC method to map the potential energy surface of CO hopping between Pt(111) adsorption sites. This reveals the existence of an L-shaped top-bridge-hollow diffusion trajectory characterized by energy barriers that provide an additional kinetic justification for experimental observations of CO/Pt(111) adsorption. Overall, this work demonstrates that it is routinely possible to achieve order-of-magnitude speedups and memory savings in DMC calculations by taking advantage of error cancellation in the calculation of energy differences that are ubiquitous in heterogeneous catalysis and surface chemistry more broadly.

The challenge of non-covalent interactions: theory meets experiment for reconciling accuracy and interpretation

In the past decade, many gas-phase spectroscopic investigations have focused on the understanding of the nature of weak interactions in model systems. Despite the fact that non-covalent interactions play a key role in several biological and technological processes, their characterization and interpretation are still far from being satisfactory. In this connection, integrated experimental and computational investigations can play an invaluable role. Indeed, a number of different issues relevant to unraveling the properties of bulk or solvated systems can be addressed from experimental investigations on molecular complexes. Focusing on the interaction of biological model systems with solvent molecules (e.g., water), since the hydration of the biomolecules controls their structure and mechanism of action, the study of the molecular properties of hydrated systems containing a limited number of water molecules (microsolvation) is the basis for understanding the solvation process and how structure and reactivity vary from gas phase to solution. Although hydrogen bonding is probably the most widespread interaction in nature, other emerging classes, such as halogen, chalcogen and pnicogen interactions, have attracted much attention because of the role they play in different fields. Their understanding requires, first of all, the characterization of the directionality, strength, and nature of such interactions as well as a comprehensive analysis of their competition with other non-covalent bonds. In this review, it is shown how state-of-the-art quantum-chemical computations combined with rotational spectroscopy allow for fully characterizing intermolecular interactions taking place in molecular complexes from both structural and energetic points of view. The transition from bi-molecular complex to microsolvation and then to condensed phase is shortly addressed.

A comparison between quantum chemistry and quantum Monte Carlo techniques for the adsorption of water on the (001) LiH surface

We present a comprehensive benchmark study of the adsorption energy of a single water molecule on the (001) LiH surface using periodic coupled cluster and quantum Monte Carlo theories. We benchmark and compare different implementations of quantum chemical wave function based theories in order to verify the reliability of the predicted adsorption energies and the employed approximations. Furthermore we compare the predicted adsorption energies to those obtained employing widely used van der Waals density-functionals. Our findings show that quantum chemical approaches are becoming a robust and reliable tool for condensed phase electronic structure calculations, providing an additional tool that can also help in potentially improving currently available van der Waals density-functionals.

Comparing van der Waals DFT methods for water on NaCl(001) and MgO(001)

In this work, a range of van der Waals type density functionals are applied to the H₂O/NaCl(001) and H₂O/MgO(001) interface systems to explore the effect of an explicit dispersion treatment. The functionals we use are the self-consistent vdW functionals vdW-DF, vdW-DF2, optPBE-vdW, optB88-vdW, optB86b-vdW, and vdW-DF-cx, as well as the dispersion-corrected PBE-TS and PBE-D2 methods; they are all compared with the standard PBE functional. For both NaCl(001) and MgO(001), we find that the dispersion-flavoured functionals stabilize the water-surface interface by approximately 20%-40% compared to the PBE results. For NaCl(001), where the water molecules remain intact for all overlayers, the dominant contribution to the adsorption energy from "density functional theory dispersion" stems from the water-surface interactions rather than the water-water interactions. The optPBE-vdW and vdW-DF-cx functionals yield adsorption energies in good agreement with available experimental values for both NaCl and MgO. To probe the strengths of the perturbations of the adsorbed water molecules, we also calculated water dipole moments and found an increase up to 85% for water at the MgO(001) surface and 70% at the NaCl(001) surface, compared to the gas-phase dipole moment.

Adsorption, Dissociation, and Dehydrogenation of Water Monomer and Water Dimer on the Smallest 3D Aluminum Particle. The O-H Dissociation Barrier Disappears for the Dimer

We present a detailed mechanistic study on the interaction and reaction of water monomer and water dimer with the smallest 3D aluminum particle (Al₆) by employing density functional and explicitly correlated coupled cluster CCSD(T)-F12 theories. Water adsorption, dissociation, and dehydrogenation are considered. For the monomer reaction, where core-valence correlation and an extrapolation to the complete basis set limit is allowed for, our coupled cluster calculations predict the O-H dissociation barrier of about 2 kcal/mol. For the dimer reaction, two distinct reaction paths are identified, initiated by forming separate dimer complexes wherein (H₂O)₂ adsorbs mainly via the oxygen atom of the donor H₂O molecule. The key O-H dissociation transition states of the dimer reaction involve a concerted migration of two H atoms resulting in the dissociation of the donor molecule and formation of the OH-water complex adsorbed on the metal cluster's surface. The most remarkable feature of both dimer reaction energy profiles is the lack of the overall energy barrier for the (rate-determining) O-H dissociation. The hydrogen bond acceptor molecule is suggested to have an extra catalytic effect on the O-H dissociation barrier of the hydrogen bond donor molecule by removing this barrier. A similar effect on the dehydrogenation step is indicated.

Modeling Polymorphic Molecular Crystals with Electronic Structure Theory

Interest in molecular crystals has grown thanks to their relevance to pharmaceuticals, organic semiconductor materials, foods, and many other applications. Electronic structure methods have become an increasingly important tool for modeling molecular crystals and polymorphism. This article reviews electronic structure techniques used to model molecular crystals, including periodic density functional theory, periodic second-order Møller-Plesset perturbation theory, fragment-based electronic structure methods, and diffusion Monte Carlo. It also discusses the use of these models for predicting a variety of crystal properties that are relevant to the study of polymorphism, including lattice energies, structures, crystal structure prediction, polymorphism, phase diagrams, vibrational spectroscopies, and nuclear magnetic resonance spectroscopy. Finally, tools for analyzing crystal structures and intermolecular interactions are briefly discussed.

Accelerating MP2C dispersion corrections for dimers and molecular crystals

The MP2C dispersion correction of Pitonak and Hesselmann [J. Chem. Theory Comput. 6, 168 (2010)] substantially improves the performance of second-order Møller-Plesset perturbation theory for non-covalent interactions, albeit with non-trivial computational cost. Here, the MP2C correction is computed in a monomer-centered basis instead of a dimer-centered one. When applied to a single dimer MP2 calculation, this change accelerates the MP2C dispersion correction several-fold while introducing only trivial new errors. More significantly, in the context of fragment-based molecular crystal studies, combination of the new monomer basis algorithm and the periodic symmetry of the crystal reduces the cost of computing the dispersion correction by two orders of magnitude. This speed-up reduces the MP2C dispersion correction calculation from a significant computational expense to a negligible one in crystals like aspirin or oxalyl dihydrazide, without compromising accuracy.