High-Throughput Exploration of Ti-V-Nb-Mo Carbide MXenes Using Neural Network Potentials and Their Evaluation as Catalysts for Hydrogen Evolution Reaction.

Realization of a sustainable hydrogen economy in the future requires the development of efficient and cost-effective catalysts for its production at scale. MXenes (MX) are a class of 2D materials with 'n' layers of carbon or nitrogen (X) interleaved by 'n+1' layers of transition metal (M) and have emerged as promising materials for various applications including catalysts for hydrogen evolution reaction (HER). Their properties are intimately related to both their composition and their atomic structure.

Effects of Segregation on the Catalytic Properties of AgAuCuPdPt High-Entropy Alloy for CO Reduction Reaction.

Multicomponent alloys are promising catalysts for diverse chemical conversions, owing to the ability to tune their vast compositional space to maximize catalytic activity and product selectivity. However, elemental segregation, whereby the surface or grain boundaries of the material are enriched in a few elements, is a physically observed phenomenon in such alloys. Such segregation alters not only the composition but also the kinds of catalytically active sites present at the surface.

Systematic Identification of Atom-Centered Symmetry Functions for the Development of Neural Network Potentials.

Neural network potentials are emerging as promising classical force fields that can enable long-time and large-length scale simulations at close to accuracies. They learn the underlying potential energy surface by mapping the Cartesian coordinates of atoms to system energies using elemental neural networks. To ensure invariance with respect to system translation, rotation, and atom index permutations, in the Behler-Parrinnello type of neural network potential (BP-NNP), the Cartesian coordinates of atoms are transformed into "structural fingerprints" using atom-centered symmetry functions (ACSFs).

Applied machine learning for predicting the lanthanide-ligand binding affinities.

Binding affinities of metal-ligand complexes are central to a multitude of applications like drug design, chelation therapy, designing reagents for solvent extraction etc. While state-of-the-art molecular modelling approaches are usually employed to gather structural and chemical insights about the metal complexation with ligands, their computational cost and the limited ability to predict metal-ligand stability constants with reasonable accuracy, renders them impractical to screen large chemical spaces. In this context, leveraging vast amounts of experimental data to learn the metal-binding affinities of ligands becomes a promising alternative.

Hydration structure and water exchange kinetics at xenotime-water interfaces: implications for rare earth minerals separation.

Hydration of surface ions gives rise to structural heterogeneity and variable exchange kinetics of water at complex mineral-water interfaces. Here, we employ ab initio molecular dynamics (AIMD) simulations and water adsorption calorimetry to examine the aqueous interfaces of xenotime, a phosphate mineral that contains predominantly Y3+ and heavy rare earth elements. Consistent with natural crystal morphology, xenotime is predicted to have a tetragonal prismatic shape, dominated by the {100} surface.

Interfacial structure in the liquid-liquid extraction of rare earth elements by phosphoric acid ligands: a molecular dynamics study.

Solvent extraction (SX), wherein two immiscible liquids, one containing the extractant molecules and the other containing the solute to be extracted are brought in contact to effect the phase transfer of the solute, underpins metal extraction and recovery processes. The interfacial region is of utmost importance in the SX process, since besides thermodynamics, the physical and chemical heterogeneity at the interface governs the kinetics of the process. Yet, a fundamental understanding of this heterogeneity and its implications for the extraction mechanism are currently lacking.

Bulk and surface DFT investigations of inorganic halide perovskites screened using machine learning and materials property databases.

In the recent past, there has been proliferation in high-throughput density functional theory and data-driven explorations of materials motivated by a need to reduce physical testing and costly computations for materials discovery. This has, in conjunction with the development of open-access materials property databases, encouraged accelerated and more streamlined discovery and screening of technologically relevant materials. In this work, we report our results on the screening and DFT studies of one such class of materials, i.

A comparative study of surface energies and water adsorption on Ce-bastnäsite, La-bastnäsite, and calcite via density functional theory and water adsorption calorimetry.

Bastnäsite, a fluoro-carbonate mineral, is the single largest mineral source of light rare earth elements (REE), La, Ce and Nd. Enhancing the efficiency of separation of the mineral from gangue through froth flotation is the first step towards meeting an ever increasing demand for REE. To design and evaluate collector molecules that selectively bind to bastnäsite, a fundamental understanding of the structure and surface properties of bastnäsite is essential.

Thermodynamic, Spectroscopic, and Computational Studies of f-Element Complexation by N-Hydroxyethyl-diethylenetriamine-N,N',N″,N″-tetraacetic Acid.

Potentiometric and spectroscopic techniques were combined with DFT calculations to probe the coordination environment and determine thermodynamic features of trivalent f-element complexation by N-hydroxyethyl-diethylenetriamine-N,N',N″,N″-tetraacetic acid, HEDTTA. Ligand protonation constants and lanthanide stability constants were determined using potentiometry. Five protonation constants were accessible in I = 2.

Development of a ReaxFF potential for carbon condensed phases and its application to the thermal fragmentation of a large fullerene.

In this article, we report the development of a ReaxFF reactive potential that can accurately describe the chemistry and dynamics of carbon condensed phases. Density functional theory (DFT)-based calculations were performed to obtain the equation of state for graphite and diamond and the formation energies of defects in graphene and amorphous phases from fullerenes. The DFT data were used to reparametrize ReaxFFCHO, resulting in a new potential called ReaxFFC-2013.

A density functional tight binding model with an extended basis set and three-body repulsion for hydrogen under extreme thermodynamic conditions.

We present a new DFTB-p3b density functional tight binding model for hydrogen at extremely high pressures and temperatures, which includes a polarizable basis set (p) and a three-body environmentally dependent repulsive potential (3b). We find that use of an extended basis set is necessary under dissociated liquid conditions to account for the substantial p-orbital character of the electronic states around the Fermi energy. The repulsive energy is determined through comparison to cold curve pressures computed from density functional theory (DFT) for the hexagonal close-packed solid, as well as pressures from thermally equilibrated DFT-MD simulations of the liquid phase.

Large scale computational chemistry modeling of the oxidation of highly oriented pyrolytic graphite.

Large scale molecular dynamics (MD) simulations are performed to study the oxidation of highly oriented pyrolytic graphite (HOPG) by hyperthermal atomic oxygen beam (5 eV). Simulations are performed using the ReaxFF classical reactive force field. We present here additional evidence that this method accurately reproduces ab initio derived energies relevant to HOPG oxidation.

Molecular-dynamics-based study of the collisions of hyperthermal atomic oxygen with graphene using the ReaxFF reactive force field.

In this work, we have investigated the hyperthermal collisions of atomic oxygens with graphene through molecular dynamics simulations using the ReaxFF reactive force field. First, following Paci et al. (J.