10 citations · 17 across the 4 of their papers we have counts for
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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…
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…