Lithium batteries and the solid electrolyte interphase (SEI)—progress and outlook

H Adenusi, GA Chass, S Passerini… - Advanced Energy …, 2023 - Wiley Online Library
Interfacial dynamics within chemical systems such as electron and ion transport processes
have relevance in the rational optimization of electrochemical energy storage materials and …

Enhancing the Faradaic efficiency of solid oxide electrolysis cells: progress and perspective

PS Gaikwad, K Mondal, YK Shin… - npj Computational …, 2023 - nature.com
To reduce global warming, many countries are shifting to sustainable energy production
systems. Solid oxide electrolysis cells (SOECs) are being considered due to their high …

Boosting rechargeable batteries R&D by multiscale modeling: myth or reality?

AA Franco, A Rucci, D Brandell, C Frayret… - Chemical …, 2019 - ACS Publications
This review addresses concepts, approaches, tools, and outcomes of multiscale modeling
used to design and optimize the current and next generation rechargeable battery cells …

Metal ion modeling using classical mechanics

P Li, KM Merz Jr - Chemical reviews, 2017 - ACS Publications
Metal ions play significant roles in numerous fields including chemistry, geochemistry,
biochemistry, and materials science. With computational tools increasingly becoming …

A comparative study on the oxidation of two-dimensional Ti 3 C 2 MXene structures in different environments

R Lotfi, M Naguib, DE Yilmaz, J Nanda… - Journal of Materials …, 2018 - pubs.rsc.org
The oxidation of two-dimensional Ti3C2 MXene structures has been recognized as a
promising method for the formation of hybrid structures of carbon supported nanotitania …

Review of force fields and intermolecular potentials used in atomistic computational materials research

JA Harrison, JD Schall, S Maskey, PT Mikulski… - Applied Physics …, 2018 - pubs.aip.org
Molecular simulation is a powerful computational tool for a broad range of applications
including the examination of materials properties and accelerating drug discovery. At the …

High-dimensional neural network potential for liquid electrolyte simulations

S Dajnowicz, G Agarwal, JM Stevenson… - The Journal of …, 2022 - ACS Publications
Liquid electrolytes are one of the most important components of Li-ion batteries, which are a
critical technology of the modern world. However, we still lack the computational tools …

Neural network reactive force field for C, H, N, and O systems

P Yoo, M Sakano, S Desai, MM Islam, P Liao… - npj Computational …, 2021 - nature.com
Reactive force fields have enabled an atomic level description of a wide range of
phenomena, from chemistry at extreme conditions to the operation of electrochemical …

Machine learning force field parameters from ab initio data

Y Li, H Li, FC Pickard IV, B Narayanan… - Journal of chemical …, 2017 - ACS Publications
Machine learning (ML) techniques with the genetic algorithm (GA) have been applied to
determine a polarizable force field parameters using only ab initio data from quantum …

Modeling the solid electrolyte interphase: Machine learning as a game changer?

D Diddens, WA Appiah, Y Mabrouk… - Advanced Materials …, 2022 - Wiley Online Library
The solid electrolyte interphase (SEI) is a complex passivation layer that forms in situ on
many battery electrodes such as lithium‐intercalated graphite or lithium metal anodes. Its …