25 citations · 39 across the 5 of their papers we have counts for
5 papers
Equivariant Tensor Network Potentials
Max Hodapp, Alexander Shapeev
Machine-learning interatomic potentials (MLIPs) have made a significant contribution to the recent progress in the fields of computational materials and chemistry due to the MLIPs'…
AI-accelerated Materials Informatics Method for the Discovery of Ductile Alloys
Ivan Novikov, Olga Kovalyova, Alexander Shapeev +1
In computational materials science, a common means for predicting macroscopic (e.g., mechanical) properties of an alloy is to define a model using combinations of descriptors that…
Machine-learning potentials enable predictive tractable high-throughput screening of random alloys
Max Hodapp, Alexander Shapeev
We present an automated procedure for computing stacking fault energies in random alloys from large-scale simulations using moment tensor potentials (MTPs) with the accuracy of den…
Efficient flexible boundary conditions for long dislocations
Max Hodapp
We present a novel efficient implementation of the flexible boundary condition (FBC) method, initially proposed by Sinclair et al., for large single-periodic problems. Efficiency i…
Analysis of a Sinclair-type domain decomposition solver for atomistic/continuum coupling
M. Hodapp
The "flexible boundary condition" method, introduced by Sinclair and coworkers in the 1970s, remains among the most popular methods for simulating isolated two-dimensional crystall…