86 citations · 174 across the 29 of their papers we have counts for
8 papers · 1 filter
SPARC-X-API: Versatile Python Interface for Real-space Density Functional Theory Calculations
Tian Tian, Lucas R Timmerman, Shashikant Kumar +3
Density Functional Theory (DFT) is the de facto workhorse for large-scale electronic structure calculations in chemistry and materials science. While plane-wave DFT implementations…
Kohn-Sham accuracy from orbital-free density functional theory via -machine learning
Shashikant Kumar, Xin Jing, John E. Pask +2
We present a -machine learning model for obtaining Kohn-Sham accuracy from orbital-free density functional theory (DFT) calculations. In particular, we employ a machine learned…
Soft and transferable pseudopotentials from multi-objective optimization
Mostafa Faghih Shojaei, John E. Pask, Andrew J. Medford +1
Ab initio pseudopotentials are a linchpin of modern molecular and condensed matter electronic structure calculations. In this work, we employ multi-objective optimization to maximi…
Robust and scalable uncertainty estimation with conformal prediction for machine-learned interatomic potentials
Yuge Hu, Joseph Musielewicz, Zachary Ulissi +1
Uncertainty quantification (UQ) is important to machine learning (ML) force fields to assess the level of confidence during prediction, as ML models are not inherently physical and…
A Universal Framework for Featurization of Atomistic Systems
Xiangyun Lei, Andrew J. Medford
Molecular dynamics simulations are an invaluable tool in numerous scientific fields. However, the ubiquitous classical force fields cannot describe reactive systems, and quantum mo…
Computational Study of Transition-Metal Substitutions in Rutile TiO (110) for Photoelectrocatalytic Ammonia Synthesis
Benjamin M. Comer, Max H. Lenk, Aradhya P. Rajanala +2
Synthesis of ammonia through photo- and electrocatalysis is a rapidly growing field. Titania-based catalysts are widely reported for photocatalytic ammonia synthesis and have also…
Design and Analysis of Machine Learning Exchange-Correlation Functionals via Rotationally Invariant Convolutional Descriptors
Xiangyun Lei, Andrew J. Medford
In this work we explore the potential of a new data-driven approach to the design of exchange-correlation (XC) functionals. The approach, inspired by convolutional filters in compu…
Analysis of Photocatalytic Nitrogen Fixation on Rutile TiO(110)
Benjamin M. Comer, Andrew J. Medford
Photocatalytic nitrogen fixation provides a promising route to produce reactive nitrogen compounds at benign conditions. Titania has been reported as an active photocatalyst for re…