Microscopic Properties of Na and Li—A First Principle Study of Metal Battery Anode Materials

Using density functional theory, we studied the bulk and surface properties of Li and Na electrodes on an atomistic level. To get a better understanding of the initial stages of surface growth phenomena (and thus dendrite formation), various self-diffusion mechanisms were studied. For this purpose, dedicated diffusion pathways on the surfaces of Na and Li were investigated within the terrace-step-kink (TSK) model utilizing nudged elastic band calculations. We were able to prove that the mere investigation of terrace self-diffusion on the respective low-index surfaces does not provide a possible descriptor for dendritic growth. Finally, we provide an initial view of the surface growth behavior of both alkali metals as well as provide a basis for experimental investigations and theoretical long-scale kinetic Monte Carlo simulations

In silico characterization of nanoparticles

Nanoparticles (NPs) make for intriguing heterogeneous catalysts due to their large active surface area and excellent and often size-dependent catalytic properties that emerge from a multitude of chemically different surface reaction sites. NP catalysts are, in principle, also highly tunable: even small changes to the NP size or surface facet composition, doping with heteroatoms, or changes of the supporting material can significantly alter their physicochemical properties. Because synthesis of size- and shape-controlled NP catalysts is challenging, the ability to computationally predict the most favorable NP structures for a catalytic reaction of interest is an in-demand skill that can help accelerate and streamline the material optimization process. Fundamentally, simulations of NP model systems present unique challenges to computational scientists. Not only must considerable methodological hurdles be overcome in performing calculations with hundreds to thousands of atoms while retaining appropriate accuracy to be able to probe the desired properties. Also, the data generated by simulations of NPs are typically more complex than data from simulations of, for example, single crystal surface models, and therefore often require different data analysis strategies. To this end, the present work aims to review analytical methods and data analysis strategies that have proven useful in extracting thermodynamic trends from NP simulations

Simulations of the Oxidation and Degradation of Platinum Electrocatalysts

Improved understanding of the fundamental processes leading to degradation of platinum nanoparticle electrocatalysts is essential to the continued advancement of their catalytic activity and stability. To this end, the oxidation of platinum nanoparticles is simulated using a ReaxFF reactive force field within a grand‐canonical Monte Carlo scheme. 2–4 nm cuboctahedral particles serve as model systems, for which electrochemical potential‐dependent phase diagrams are constructed from the thermodynamically most stable oxide structures, including solvation and thermochemical contributions. Calculations in this study suggest that surface oxide structures should become thermodynamically stable at voltages around 0.80–0.85 V versus standard hydrogen electrode, which corresponds to typical fuel cell operating conditions. The potential presence of a surface oxide during catalysis is usually not accounted for in theoretical studies of Pt electrocatalysts. Beyond 1.1 V, fragmentation of the catalyst particles into [Pt$_{6}$O$_{8}$]$^{4-}$ clusters is observed. Density functional theory calculations confirm that [Pt$_{6}$O$_{8}$]$^{4-}$ is indeed stable and hydrophilic. These results suggest that the formation of [Pt$_{6}$O$_{8}$]$^{4-}$ may play an important role in platinum catalyst degradation as well as the electromotoric transport of Pt$^{2+/4+Zahl}$ ions in fuel cells

Atomistic Studies on Water-Induced Lithium Corrosion

It is well known that lithium reacts violently with water under the release of molecular hydrogen and the formation of lithium hydroxide. In this work, the initial mechanisms for the surface reactions of metallic lithium with water from the gas phase were investigated by means of periodic density functional theory calculations. For this purpose, adsorption/absorption structures and diffusion and dissociation processes of hydrogen, OH, and H$_{2}$O on low-index metallic lithium surfaces were investigated. Through thermodynamic and kinetic considerations, negatively charged centers on the surface were identified as the origin of hydrogen formation. The strikingly low reaction barriers for the reaction at these centers implied a self-supporting effect of hydrogen evolution and the associated lithium degradation

In-Silico Characterization of Nanoparticle Catalysts

Nanoparticles (NPs) make for intriguing heterogeneous catalysts due to their large active surface area and excellent and often size-dependent catalytic properties that emerge from a multitude of chemically different surface reaction sites. NP catalysts are, in principle, also highly tunable: even small changes to the NP size or surface facet composition, doping with heteroatoms, or changes of the supporting material can significantly alter their physicochemical properties. Because synthesis of size- and shape-controlled NP catalysts is challenging, the ability to computationally predict the most favorable NP structures for a catalytic reaction of interest is an in-demand skill that can help accelerate and streamline the material optimization process. Fundamentally, simulations of NP model systems present unique challenges to computational scientists. Not only must considerable methodological hurdles be overcome in performing calculations with hundreds to thousands of atoms while retaining appropriate accuracy to be able to probe the desired properties. Also, the data generated by simulations of NPs are typically more complex than data from simulations of, for example, single crystal surface models, and therefore often requires different data analysis strategies. To this end, the present work aims to review analytical methods and data analysis strategies that have proven useful in extracting thermodynamic trends from NP simulations.Comment: To be submitted to PCCP as a tutorial revie

Microscopic Properties of Na and Li—A First Principle Study of Metal Battery Anode Materials

Publisher's version (útgefin grein)Using density functional theory, we studied the bulk and surface properties of Li and Na electrodes on an atomistic level. To get a better understanding of the initial stages of surface growth phenomena (and thus dendrite formation), various self-diffusion mechanisms were studied. For this purpose, dedicated diffusion pathways on the surfaces of Na and Li were investigated within the terrace-step-kink (TSK) model utilizing nudged elastic band calculations. We were able to prove that the mere investigation of terrace self-diffusion on the respective low-index surfaces does not provide a possible descriptor for dendritic growth. Finally, we provide an initial view of the surface growth behavior of both alkali metals as well as provide a basis for experimental investigations and theoretical long-scale kinetic Monte Carlo simulations.This work was funded by the German Research Foundation (DFG) under Project ID 390874152 (POLiS Cluster of Excellence). Further, computational resources were provided by the state of Baden‐Württemberg through bwHPC and the German Science Foundation (DFG) under Grant No. INST 40/467‐1 FUGG.Peer Reviewe

Simulations of the Oxidation and Degradation of Platinum Electrocatalysts

Publisher's version (útgefin grein)Improved understanding of the fundamental processes leading to degradation of platinum nanoparticle electrocatalysts is essential to the continued advancement of their catalytic activity and stability. To this end, the oxidation of platinum nanoparticles is simulated using a ReaxFF reactive force field within a grand-canonical Monte Carlo scheme. 2–4 nm cuboctahedral particles serve as model systems, for which electrochemical potential-dependent phase diagrams are constructed from the thermodynamically most stable oxide structures, including solvation and thermochemical contributions. Calculations in this study suggest that surface oxide structures should become thermodynamically stable at voltages around 0.80–0.85 V versus standard hydrogen electrode, which corresponds to typical fuel cell operating conditions. The potential presence of a surface oxide during catalysis is usually not accounted for in theoretical studies of Pt electrocatalysts. Beyond 1.1 V, fragmentation of the catalyst particles into [Pt6O8]4− clusters is observed. Density functional theory calculations confirm that [Pt6O8]4− is indeed stable and hydrophilic. These results suggest that the formation of [Pt6O8]4− may play an important role in platinum catalyst degradation as well as the electromotoric transport of Pt2+/4+ ions in fuel cells.B.K. thanks the University of Iceland Research Fund for support through a PhD fellowship, Dr. Anna Garden for access to nanoparticle DFT structures, and Marcos Tacca for translation help of Spanish primary literature. Andrey Sinyavskiy is acknowledged for implementing the 2PT method. This work was supported by the German Federal Ministry of Education and Research through the BMBF-project ?GEP ? Grundlagen elektrochemischer Phasengrenzen? (Grant No. 13XP5023D), the Deutsche Forschungsgemeinschaft (DFG) through Grant No. SFB-1316 (collaborative research center), as well as through the Icelandic Research Fund under Grant No. 174582-052. Computational resources were provided by the state of Baden?W?rttemberg through bwHPC and the German Science Foundation (DFG) under Grant No. INST 40/467-1 FUGG. The Volkswagen Group, Wolfsburg, Germany is acknowledged for partial funding of this project.Peer Reviewe

Theoretische Untersuchungen zur Sauerstoffreduktion an Übergangsmetall-Elektroden

A ReaxFF reactive interaction potential for Pt/O is developed using a first-principles-based multiscale approach and applied to investigate model-systems relevant to the oxygen reduction reaction (ORR) on platinum. Investigations of Pt(111) surface oxidation under various external conditions (from UHV to near-ambient-pressures) reveal two key mechanistic steps as the surface coverage increases, namely platinum surface buckling and subsequent oxygen absorption into the surface. Thermodynamically stable surface oxides on Pt(111) are predicted for the first time, which may be responsible for the sluggish kinetics of the ORR. Finally, reactive molecular dynamics studies provide new ideas for mechanistic pathways involved in the formation of water from hydrogen and oxygen gas on Pt(111)

KVIK Optimiser - An Enhanced ReaxFF Force Field Training Approach

In this work, we demonstrate the superior exploration capabilities of the population-based methods over the sequential one-parameter parabolic interpolation (SOPPI) approach to optimise ReaxFF force field parameters. Evolutionary algorithms (EAs) are heuristic-based approaches using a population of concurrent models in the search space to evolve towards the global best through stochastic operations. The parallelisation of EAs scales almost linearly, and no differentiable objective function is required. These methods were tested for their search performance and convergence behaviour on different multi-dimensional, multimodal benchmark functions. The developed KVIK (Icelandic for: dynamic, in motion) optimisation framework features an extended training 1routine designed to parameterise solid-state systems efficiently. The optimisation routine was applied to train a reactive force field potential for metallic lithium and sodium and their interaction parameters. The KVIK-optimised ReaxFF potential function parameter set reproduces relative energy results from the density functional theory (DFT) reference data set within the standard deviation range established using the error estimation routine provided by the BEEF-vdW density functional. Finally, thermodynamically and kinetically driven surface growth phenomena on metallic Li- and Na-electrodes were investigated using coupled ReaxFF/Monte Carlo (MC) approaches

Topologically Sensitive Surface Segregations of Au-Pd Alloys in Electrocatalytic Hydrogen Evolution

Density functional calculations along with in situ X-ray absorption spectroscopy data show that AuPd alloys form unique potential-controlled surface structures during the hydrogen evolution. We find evidence for surface segregations preferring a gold surface if the surface is free of chemisorbed species, while hydrogen adsorption triggers palladium segregation into the surface