activity
19942024
most citedAutomated discovery of a robust interatomic potential for aluminum

98 citations · 377 across the 17 of their papers we have counts for

collaborators

17 papers

cond-mat.mtrl-sci2024

High Pressure Suppression of Plasticity due to Over-Nucleation of Shear Strain

Brenden W. Hamilton, Timothy C. Germann

High pressure shear band formation is a critical phenomenon in energetic materials due to its influence on both mechanical strength and mechanochemical activation. While shear band…

cond-mat.soft2023

Using Limited Neural Networks to Assess Relative Mechanistic Influence on Shock Heating in Granular Solids

Brenden W Hamilton, Timothy C. Germann

The rapid compaction of granular media results in localized heating that can induce chemical reactions, phase transformations, and melting. However, there are numerous mechanisms i…

cond-mat.mtrl-sci2023★ 1 cited

Interplay of Mechanochemistry and Material Processes in the Graphite to Diamond Phase Transformation

Brenden W. Hamilton, Timothy C. Germann

he manifestation of intra-molecular strains in covalent systems is widely known to accelerate chemical reactions and open alternative reaction paths. This process is moderately und…

cond-mat.mtrl-sci2022★ 21 cited

Energy Localization Efficiency in TATB Pore Collapse Mechanisms

Brenden W. Hamilton, Timothy C. Germann

Atomistic and continuum scale modeling efforts have shown that shock induced collapse of porosity can occur via a wide range of mechanisms dependent on pore morphology, shockwave p…

cs.LG2022★ 9 cited

Predictive Scale-Bridging Simulations through Active Learning

Satish Karra, Mohamed Mehana, Nicholas Lubbers +12

Throughout computational science, there is a growing need to utilize the continual improvements in raw computational horsepower to achieve greater physical fidelity through scale-b…

physics.comp-ph2021★ 32 cited

Machine Learning of consistent thermodynamic models using automatic differentiation

David Rosenberger, Kipton Barros, Timothy C. Germann +1

We propose a data-driven method to describe consistent equations of state (EOS) for arbitrary systems. Complex EOS are traditionally obtained by fitting suitable analytical express…