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Electrochemical processes play a crucial role in energy storage and conversion systems, yet their computational modeling remains a significant challenge. Accurately incorporating the effects of electric potential has been a central focus in…
Accurate prediction of ionic conductivity is critical for the design of high-performance solid-state electrolytes in next-generation batteries. We benchmark molecular dynamics (MD) approaches for computing ionic conductivity in 21 lithium…
The path toward Li-ion batteries with higher energy-densities will likely involve use of thin lithium metal (Li) anode (<50 $\mu$m in thickness), whose cyclability today remains limited by dendrite formation and low Coulombic efficiency.…
Solid-state electrolytes, by enabling lithium metal anodes, may significantly increase the energy density of current lithium-ion batteries. However, similar to their liquid counterparts, these hard and stiff electrolytes can still be…
The recently published DeePMD model (https://github.com/deepmodeling/deepmd-kit), based on a deep neural network architecture, brings the hope of solving the time-scale issue which often prevents the application of first principle molecular…
The structure and growth of the Solid Electrolyte Interphase (SEI) region between an electrolyte and an electrode is one of the most fundamental, yet less-well understood phenomena in solid-state batteries. We present a parameter-free…
Recently some critical problems and challenges have been exposed, hindering the development and practical application of SSLBs, such as the low room temperature ionic conductivity of solid electrolyte, the risk of short circuit caused by…
Lithium (Li) metal anodes are essential for developing next-generation high-energy-density batteries. However, Li dendrite/whisker formation caused short-circuiting issue and short cycle life have prevented lithium metal from being viably…
Li$_6$PS$_5$Cl is a promising candidate for the solid electrolyte in all-solid-state Li-ion batteries. In applications, this material is in a polycrystalline state with grain boundaries (GBs) that can affect ionic conductivity. While…
Battery interfaces critically influence lithium-metal battery performance through their role in ion diffusion and dendrite formation. However, structural characterization of these interfaces has remained challenging due to limitations in…
The decomposition of ethylene carbonate (EC) during the initial growth of solid-electrolyte interphase (SEI) films at the solvent-graphitic anode interface is critical to lithium ion battery operations. Ab initio molecular dynamics…
The sustainable production of many bulk chemicals relies on heterogeneous catalysis. The rational design or improvement of the required catalysts critically depends on insights into the underlying mechanisms at the atomic scale. In recent…
The increasing need for portable and large-scale energy storage systems requires development of new, long lasting and highly efficient battery systems. Solid state NMR spectroscopy has emerged as an excellent method for characterizing…
Machine-learning interatomic potentials (MLIPs) enable large-scale atomistic simulations at moderate computational cost while retaining ab initio accuracy. MLIPs trained on coupled-cluster data, particularly CCSD(T), have emerged as a…
Future lithium-based batteries are expected to use solid electrolytes to achieve higher energy density and fast charge capabilities. The majority of solid electrolytes are thermodynamically unstable against layered oxide cathodes. Here, the…
Metal coordination is ubiquitous in Nature and central in many applications ranging from nanotechnology to catalysis and environmental chemistry. Complex formation results from the subtle interplay between different thermodynamic, kinetic,…
In recent years, significant progress has been made in the development of machine learning potentials (MLPs) for atomistic simulations with applications in many fields from chemistry to materials science. While most current MLPs are based…
We review recent ab initio molecular dynamics studies of electrode/electrolyte interfaces in lithium ion batteries. Our goals are to introduce experimentalists to simulation techniques applicable to models which are arguably most faithful…
With the growing availability of machine-learned interatomic potential (MLIP) models for materials simulations, there is an increasing demand for robust, automated, and chemically insightful benchmarking methodologies. In response, we here…
The design of efficient electrolysis devices for pure metal production requires accurate data on the properties of the melts used in the process. This work focuses on two key systems for calcium production: the molten Ca-Cu alloy and the…