Machine Learning of Partial Charges Derived from High-Quality Quantum-Mechanical Calculations

Parametrization of small organic molecules for classical molecular dynamics simulations is not trivial. The vastness of the chemical space makes approaches using building blocks challenging. The most common approach is therefore an individual parametrization of each compound by deriving partial charges from semiempirical or ab initio calculations and inheriting the bonded and van der Waals (Lennard-Jones) parameters from a (bio)molecular force field. The quality of the partial charges generated in this fashion depends on the level of the quantum-chemical calculation as well as on the extraction procedure used. Here, we present a machine learning (ML) based approach for predicting partial charges extracted from density functional theory (DFT) electron densities. The training set was chosen with the goal to provide a broad coverage of the known chemical space of druglike molecules. In addition to the speed of the approach, the partial charges predicted by ML are not dependent on the three-dimensional conformation in contrast to the ones obtained by fitting to the electrostatic potential (ESP). To assess the quality and compatibility with standard force fields, we performed benchmark calculations for the free energy of hydration and liquid properties such as density and heat of vaporization.

Rationally designing mixed Cu–(μ-O)–M (M = Cu, Ag, Zn, Au) centers over zeolite materials with high catalytic activity towards methane activation

The direct conversion of methane to methanol on [Cu(μ-O)M]²⁺ (M = Cu, Ag, Zn, Au) bimetal centers in ZSM-5 zeolite is investigated using periodic DFT for the first time.

Tunable electronic and magnetic properties of graphene-like XYBe3 (XY = BN, AlN, SiC, GeC) nanosheets with carrier doping: a first-principles study

Graphyne-like ternary beryllide nanosheets are found to be promising host materials because of their carrier-induced tunable magnetism and half-metallicity.

On the thickness of the double layer in ionic liquids

The Au(111)|BF₄⁻interface model in which BF₄⁻reorients and spontaneously dissociates at surface coverageθ= 1/3.

Introducing DDEC6 atomic population analysis: part 4. Efficient parallel computation of net atomic charges, atomic spin moments, bond orders, and more

The DDEC6 method is one of the most accurate and broadly applicable atomic population analysis methods. It works for a broad range of periodic and non-periodic materials with no magnetism, collinear magnetism, and non-collinear magnetism irrespective of the basis set type. First, we show DDEC6 charge partitioning to assign net atomic charges corresponds to solving a series of 14 Lagrangians in order. Then, we provide flow diagrams for overall DDEC6 analysis, spin partitioning, and bond order calculations. We wrote an OpenMP parallelized Fortran code to provide efficient computations. We show that by storing large arrays as shared variables in cache line friendly order, memory requirements are independent of the number of parallel computing cores and false sharing is minimized. We show that both total memory required and the computational time scale linearly with increasing numbers of atoms in the unit cell. Using the presently chosen uniform grids, computational times of ∼9 to 94 seconds per atom were required to perform DDEC6 analysis on a single computing core in an Intel Xeon E5 multi-processor unit. Parallelization efficiencies were usually >50% for computations performed on 2 to 16 cores of a cache coherent node. As examples we study a B-DNA decamer, nickel metal, supercells of hexagonal ice crystals, six X@C₆₀ endohedral fullerene complexes, a water dimer, a Mn₁₂-acetate single molecule magnet exhibiting collinear magnetism, a Fe₄O₁₂N₄C₄₀H₅₂ single molecule magnet exhibiting non-collinear magnetism, and several spin states of an ozone molecule. Efficient parallel computation was achieved for systems containing as few as one and as many as >8000 atoms in a unit cell. We varied many calculation factors (e.g., grid spacing, code design, thread arrangement, etc.) and report their effects on calculation speed and precision. We make recommendations for excellent performance.

We parallelize the DDEC6 method to efficiently compute net atomic charges, atomic spin moments, and bond orders in diverse materials.

Scaling Relations for Acidity and Reactivity of Zeolites

Zeolites are widely applied as solid acid catalysts in various technological processes. In this work we have computationally investigated how catalytic reactivity scales with acidity for a range of zeolites with different topologies and chemical compositions. We found that straightforward correlations are limited to zeolites with the same topology. The adsorption energies of bases such as carbon monoxide (CO), acetonitrile (CH3CN), ammonia (NH3), trimethylamine (N(CH3)3), and pyridine (C5H5N) give the same trend of acid strength for FAU zeolites with varying composition. Crystal orbital Hamilton populations (COHP) analysis provides a detailed molecular orbital picture of adsorbed base molecules on the Brønsted acid sites (BAS). Bonding is dominated by strong σ donation from guest molecules to the BAS for the adsorbed CO and CH3CN complexes. An electronic descriptor of acid strength is constructed based on the bond order calculations, which is an intrinsic parameter rather than adsorption energy that contains additional contributions due to secondary effects such as van der Waals interactions with the zeolite walls. The bond order parameter derived for the CH3CN adsorption complex represents a useful descriptor for the intrinsic acid strength of FAU zeolites. For FAU zeolites the activation energy for the conversion of π-adsorbed isobutene into alkoxy species correlates well with the acid strength determined by the NH3 adsorption energies. Other zeolites such as MFI and CHA do not follow the scaling relations obtained for FAU; we ascribe this to the different van der Waals interactions and steric effects induced by zeolite framework topology.

Which Oxide for Low-Emissivity Glasses? First-Principles Modeling of Silver Adhesion

Density functional theory (DFT) calculations were performed to assess the work of adhesion of silver layers deposited on metal oxide surfaces differing by their chemical nature (ZnO, TiO₂, SnO₂, and ZrO₂) and their crystallographic face. The calculated work of adhesion values range from ∼0 to 3 J m^-2 and are shown to originate from the interplay between ionic (associated with charge transfer at the interface) and covalent (as probed by atomic bond orders between silver and the metal oxide atoms) interactions. The results are discussed in the context of the design of silver/metal oxide interfaces for low-emissivity glasses.

Facile Anhydrous Proton Transport on Hydroxyl Functionalized Graphane

Graphane functionalized with hydroxyl groups is shown to rapidly conduct protons under anhydrous conditions through a contiguous network of hydrogen bonds. Density functional theory calculations predict remarkably low barriers to diffusion of protons along a 1D chain of surface hydroxyls. Diffusion is controlled by the local rotation of hydroxyl groups, a mechanism that is very different from that found in 1D water wires in confined nanopores or in bulk water. The proton mean square displacement in the 1D chain was observed to follow Fickian diffusion rather than the expected single-file mobility. A charge analysis reveals that the charge on the proton is essentially equally shared by all hydrogens bound to oxygens, effectively delocalizing the proton.

CO2 Capture and Separations Using MOFs: Computational and Experimental Studies

This Review focuses on research oriented toward elucidation of the various aspects that determine adsorption of CO₂ in metal-organic frameworks and its separation from gas mixtures found in industrial processes. It includes theoretical, experimental, and combined approaches able to characterize the materials, investigate the adsorption/desorption/reaction properties of the adsorbates inside such environments, screen and design new materials, and analyze additional factors such as material regenerability, stability, effects of impurities, and cost among several factors that influence the effectiveness of the separations. CO₂ adsorption, separations, and membranes are reviewed followed by an analysis of the effects of stability, impurities, and process operation conditions on practical applications.

Activation of CO2 by supported Cu clusters

CO₂ forms a bent, negative anion upon adsorption near a Cu₃ cluster supported on TiO₂.

Introducing DDEC6 atomic population analysis: part 3. Comprehensive method to compute bond orders

A new method to compute accurate bond orders for metallic, covalent, polar-covalent, ionic, multi-centered, aromatic, dative, dispersion, and hydrogen bonding.

Applications of large-scale density functional theory in biology

Density functional theory (DFT) has become a routine tool for the computation of electronic structure in the physics, materials and chemistry fields. Yet the application of traditional DFT to problems in the biological sciences is hindered, to a large extent, by the unfavourable scaling of the computational effort with system size. Here, we review some of the major software and functionality advances that enable insightful electronic structure calculations to be performed on systems comprising many thousands of atoms. We describe some of the early applications of large-scale DFT to the computation of the electronic properties and structure of biomolecules, as well as to paradigmatic problems in enzymology, metalloproteins, photosynthesis and computer-aided drug design. With this review, we hope to demonstrate that first principles modelling of biological structure-function relationships are approaching a reality.

Reactive wetting properties of TiO2 nanoparticles predicted by ab initio molecular dynamics simulations

Small-sized wet TiO2 nanoparticles have been investigated by ab initio molecular dynamics simulations. Chemical and physical adsorption of water on the TiO2-water interface was studied as a function of water content, ranging from dry nanoparticles to wet nanoparticles with monolayer coverage of water. The surface reactivity was shown to be a concave function of water content and driven by surface defects. The local coordination number at the defect was identified as the key factor to decide whether water adsorption proceeds through dissociation or physisorption on the surface. A consistent picture of TiO2 nanoparticle wetting at the microscopic level emerges, which corroborates existing experimental data and gives further insight into the molecular mechanisms behind nanoparticle wetting. These calculations will facilitate the engineering of metal oxide nanoparticles with a controlled catalytic water activity.

Computationally designed tandem direct selective oxidation using molecular oxygen as oxidant without coreductant

A newly designed two-step selective oxidation process was computationally tested for propene epoxidation using molecular oxygen as oxidant without co-reductant.

A microscopic level insight into Pt doped TiZn (001) surface for hydrogen energy storage usage

H-storage behavior on TiZn and Pt-doped TiZn alloys.

Introducing DDEC6 atomic population analysis: part 1. Charge partitioning theory and methodology

We introduce a new atomic population analysis method that performs exceptionally well across an extremely broad range of periodic and non-periodic material types.

DFT study of Rh-decorated pristine, B-doped and vacancy defected graphene for hydrogen adsorption

Rh adatom stability on graphene, with and without defects has been investigated by density functional theory (DFT). The feasibility to achieve uniform dispersion for the metallic atom and the hydrogen storage capacity for each system were evaluated.