198 citations · 328 across the 4 of their papers we have counts for
4 papers
Wavelet Scattering Networks for Atomistic Systems with Extrapolation of Material Properties
Paul Sinz, Michael W. Swift, Xavier Brumwell +4
The dream of machine learning in materials science is for a model to learn the underlying physics of an atomic system, allowing it to move beyond interpolation of the training set…
First-principles prediction of potentials and space-charge layers in all-solid-state batteries
Michael W. Swift, Yue Qi
As all-solid-state batteries (SSBs) develop as an alternative to traditional cells, a thorough theoretical understanding of driving forces behind battery operation is needed. We pr…
Steerable Wavelet Scattering for 3D Atomic Systems with Application to Li-Si Energy Prediction
Xavier Brumwell, Paul Sinz, Kwang Jin Kim +2
A general machine learning architecture is introduced that uses wavelet scattering coefficients of an inputted three dimensional signal as features. Solid harmonic wavelet scatteri…
Using atomic layer deposition to hinder solvent decomposition in lithium ion batteries: first principles modeling and experimental studies
Kevin Leung, Yue Qi, Kevin R. Zavadil +5
Passivating lithium ion battery electrode surfaces to prevent electrolyte decomposition is critical for battery operations. Recent work on conformal atomic layer deposition (ALD) c…