10 citations · 17 across the 4 of their papers we have counts for
5 papers
Exploring Model Complexity in Machine Learned Potentials for Simulated Properties
Andrew Rohskopf, James Goff, Dionysios Sema +5
Machine learning (ML) enables the development of interatomic potentials that promise the accuracy of first principles methods while retaining the low cost and parallel efficiency o…
Shadow molecular dynamics and atomic cluster expansions for flexible charge models
James Goff, Yu Zhang, Christian F. A. Negre +2
A shadow molecular dynamics scheme for flexible charge models is presented, where the shadow Born-Oppenheimer potential is derived from a coarse-grained approximation of range-sepa…
Permutation-adapted complete and independent basis for atomic cluster expansion descriptors
James M. Goff, Charles Sievers, Mitchell A. Wood +1
Atomic cluster expansion (ACE) methods provide a systematic way to describe particle local environments of arbitrary body order. For practical applications it is often required tha…
Predicting the pseudocapacitive windows for MXene electrodes with voltage-dependent cluster expansion models
James M. Goff, Francisco Marques dos Santos Vieira, Nathan D. Keilbart +2
MXene transition-metal carbides and nitrides are of growing interest for energy storage applications. These compounds are especially promising for use as pseudocapacitive electrode…
Quantifying multi-point ordering in alloys
James M. Goff, Bryant Y. Li, Susan B. Sinnott +1
A central problem in multicomponent lattice systems is to systematically quantify multi-point ordering. Ordering in such systems is often described in terms of pairs, even though t…