Benchmarking water adsorption on metal surfaces with ab initio molecular dynamics.

Solid-water interfaces are ubiquitous in nature and technology. In particular, technologies evolving in the green transition, such as electrocatalysis, heavily rely on the junction of an electrolyte and an electrode as a central part of the device. For the understanding of atomic-scale processes taking place at the electrolyte-electrode interface, density functional theory (DFT) has become the de facto standard.

Enriching Surface-Accessible CO in the Zero-Gap Anion-Exchange-Membrane-Based CO Electrolyzer.

Zero-gap anion exchange membrane (AEM)-based CO electrolysis is a promising technology for CO production, however, their performance at elevated current densities still suffers from the low local CO concentration due to heavy CO neutralization. Herein, via modulating the CO feed mode and quantitative analyzing CO utilization with the aid of mass transport modeling, we develop a descriptor denoted as the surface-accessible CO concentration ([CO ] ), which enables us to indicate the transient state of the local [CO ]/[OH ] ratio and helps define the limits of CO -to-CO conversion. To enrich the [CO ] , we developed three general strategies: (1) increasing catalyst layer thickness, (2) elevating CO pressure, and (3) applying a pulsed electrochemical (PE) method.

MCML: Combining physical constraints with experimental data for a multi-purpose meta-generalized gradient approximation.

The predictive power of density functional theory for materials properties can be improved without increasing the overall computational complexity by extending the generalized gradient approximation (GGA) for electronic exchange and correlation to density functionals depending on the electronic kinetic energy density in addition to the charge density and its gradient, resulting in a meta-GGA. Here, we propose an empirical meta-GGA model that is based both on physical constraints and on experimental and quantum chemistry reference data. The resulting optimized meta-GGA MCML yields improved surface and gas phase reaction energetics without sacrificing the accuracy of bulk property predictions of existing meta-GGA approaches.

Autonomous intelligent agents for accelerated materials discovery.

We present an end-to-end computational system for autonomous materials discovery. The system aims for cost-effective optimization in large, high-dimensional search spaces of materials by adopting a sequential, agent-based approach to deciding which experiments to carry out. In choosing next experiments, agents can make use of past knowledge, surrogate models, logic, thermodynamic or other physical constructs, heuristic rules, and different exploration-exploitation strategies.

Machine learning with bond information for local structure optimizations in surface science.

Local optimization of adsorption systems inherently involves different scales: within the substrate, within the molecule, and between the molecule and the substrate. In this work, we show how the explicit modeling of different characteristics of the bonds in these systems improves the performance of machine learning methods for optimization. We introduce an anisotropic kernel in the Gaussian process regression framework that guides the search for the local minimum, and we show its overall good performance across different types of atomic systems.

DFT simulation of the X-ray diffraction pattern of aluminum-ion-intercalated graphite used as the cathode material of the aluminum-ion battery.

Many breakthroughs have been achieved in rechargeable aluminum-ion battery technologies in recent years. Most recently, operando X-ray diffraction (XRD) combined with density functional theory (DFT) calculations was reported to study the chloroaluminate anion (AlCl4-)-intercalated graphite cathode of the battery. However, there are quite a few discrepancies between the measured and simulated XRD patterns.

Catalysis-Hub.org, an open electronic structure database for surface reactions.

We present a new open repository for chemical reactions on catalytic surfaces, available at https://www.catalysis-hub.org .

High-throughput calculations of catalytic properties of bimetallic alloy surfaces.

A comprehensive database of chemical properties on a vast set of transition metal surfaces has the potential to accelerate the discovery of novel catalytic materials for energy and industrial applications. In this data descriptor, we present such an extensive study of chemisorption properties of important adsorbates - e.g.

Graph Theory Approach to High-Throughput Surface Adsorption Structure Generation.

We present a methodology for graph based enumeration of surfaces and unique chemical adsorption structures bonded to those surfaces. Utilizing the graph produced from a bulk structure, we create a unique graph representation for any general slab cleave and further extend that representation to include a large variety of catalytically relevant adsorbed molecules. We also demonstrate simple geometric procedures to generate 3D initial guesses of these enumerated structures.

A Lattice Kinetic Monte Carlo Solver for First-Principles Microkinetic Trend Studies.

Mean-field microkinetic models in combination with Brønsted-Evans-Polanyi like scaling relations have proven highly successful in identifying catalyst materials with good or promising reactivity and selectivity. Analysis of the microkinetic model by means of lattice kinetic Monte Carlo promises a faithful description of a range of atomistic features involving short-range ordering of species in the vicinity of an active site. In this paper, we use the "fruit fly" example reaction of CO oxidation on fcc(111) transition and coinage metals to motivate and develop a lattice kinetic Monte Carlo solver suitable for the numerically challenging case of vastly disparate rate constants.

Bottom-Up Design of a Copper-Ruthenium Nanoparticulate Catalyst for Low-Temperature Ammonia Oxidation.

A novel nanoparticulate catalyst of copper (Cu) and ruthenium (Ru) was designed for low-temperature ammonia oxidation at near-stoichiometric mixtures using a bottom-up approach. A synergistic effect of the two metals was found. An optimum CuRu catalyst presents a reaction rate threefold higher than that for Ru and forty-fold higher than that for Cu.

To address surface reaction network complexity using scaling relations machine learning and DFT calculations.

Surface reaction networks involving hydrocarbons exhibit enormous complexity with thousands of species and reactions for all but the very simplest of chemistries. We present a framework for optimization under uncertainty for heterogeneous catalysis reaction networks using surrogate models that are trained on the fly. The surrogate model is constructed by teaching a Gaussian process adsorption energies based on group additivity fingerprints, combined with transition-state scaling relations and a simple classifier for determining the rate-limiting step.

Intrinsic Selectivity and Structure Sensitivity of Rhodium Catalysts for C(2+) Oxygenate Production.

Synthesis gas (CO + H2) conversion is a promising route to converting coal, natural gas, or biomass into synthetic liquid fuels. Rhodium has long been studied as it is the only elemental catalyst that has demonstrated selectivity to ethanol and other C2+ oxygenates. However, the fundamentals of syngas conversion over rhodium are still debated.

Nickel-silver alloy electrocatalysts for hydrogen evolution and oxidation in an alkaline electrolyte.

The development of improved catalysts for the hydrogen evolution reaction (HER) and hydrogen oxidation reaction (HOR) in basic electrolytes remains a major technical obstacle to improved fuel cells, water electrolyzers, and other devices for electrochemical energy storage and conversion. Based on the free energy of adsorbed hydrogen intermediates, theory predicts that alloys of nickel and silver are active for these reactions. In this work, we synthesize binary nickel-silver bulk alloys across a range of compositions and show that nickel-silver alloys are indeed more active than pure nickel for hydrogen evolution and, possibly, hydrogen oxidation.

Catalysis. Assessing the reliability of calculated catalytic ammonia synthesis rates.

We introduce a general method for estimating the uncertainty in calculated materials properties based on density functional theory calculations. We illustrate the approach for a calculation of the catalytic rate of ammonia synthesis over a range of transition-metal catalysts. The correlation between errors in density functional theory calculations is shown to play an important role in reducing the predicted error on calculated rates.

mBEEF: an accurate semi-local Bayesian error estimation density functional.

We present a general-purpose meta-generalized gradient approximation (MGGA) exchange-correlation functional generated within the Bayesian error estimation functional framework [J. Wellendorff, K. T.

Platinum redispersion on metal oxides in low temperature fuel cells.

We have analyzed the aptitude of several metal oxide supports (TiO(2), SnO(2), NbO(2), ZrO(2), SiO(2), Ta(2)O(5) and Nb(2)O(5)) to redisperse platinum under electrochemical conditions pertinent to the Proton Exchange Membrane Fuel Cell (PEMFC) cathode. The redispersion on oxide supports in air has been studied in detail; however, due to different operating conditions it is not straightforward to link the chemical and the electrochemical environment. The largest differences reflect in (1) the oxidation state of the surface (the oxygen species coverage), (2) temperature and (3) the possibility of platinum dissolution at high potentials and the interference of redispersion with normal working potential of the PEMFC cathode.

A theoretical evaluation of possible transition metal electro-catalysts for N2 reduction.

Theoretical studies of the possibility of forming ammonia electrochemically at ambient temperature and pressure are presented. Density functional theory calculations were used in combination with the computational standard hydrogen electrode to calculate the free energy profile for the reduction of N(2) admolecules and N adatoms on several close-packed and stepped transition metal surfaces in contact with an acidic electrolyte. Trends in the catalytic activity were calculated for a range of transition metal surfaces and applied potentials under the assumption that the activation energy barrier scales with the free energy difference in each elementary step.

Mechanism of the initial stages of nitrogen-doped single-walled carbon nanotube growth.

We have studied the mechanism of the initial stages of nitrogen-doped single-walled carbon nanotube growth illustrated for the case of a floating catalyst chemical vapor deposition system, which uses carbon monoxide (CO) and ammonia (NH(3)) as precursors and iron as a catalyst. We performed first-principles electronic-structure calculations, fully incorporating the effects of spin polarization and magnetic moments, to investigate the bonding and chemistry of CO, NH(3), and their fragments on a model Fe(55) icosahedral cluster. A possible dissociation path for NH(3) to atomic nitrogen and hydrogen was identified, with a reaction barrier consistent with an experimentally determined value we measured by tandem infrared and mass spectrometry.

Density functional theory in surface chemistry and catalysis.

Recent advances in the understanding of reactivity trends for chemistry at transition-metal surfaces have enabled in silico design of heterogeneous catalysts in a few cases. The current status of the field is discussed with an emphasis on the role of coupling theory and experiment and future challenges.