3 citations · 4 across the 5 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…
High-temperature thermal conductivity measurements of macro-porous graphite
Shomik Verma, Michael Adams, Mary Foxen +3
Graphite is a unique material for high temperature applications and will likely become increasingly important as we attempt to electrify industrial applications. However, high-qual…
Power Availability of PV plus Thermal Batteries in real-world electric power grids
Odin Foldvik Eikeland, Colin C. Kelsall, Kyle Buznitsky +4
As variable renewable energy sources comprise a growing share of total electricity generation, energy storage technologies are becoming increasingly critical for balancing energy g…
Phonon Optimized Potentials
Andrew Rohskopf, Hamid R. Seyf, Kiarash Gordiz +1
Molecular dynamics (MD) simulations have been extensively used to study phonons and gain insight, but direct comparisons to experimental data are often difficult, due to a lack of…
A New Formalism for Calculating Modal Contributions to Thermal Interface Conductance from Molecular Dynamics Simulations
Kiarash Gordiz, Asegun Henry
A new formalism for extracting the modal contributions to thermal interface conductance with full inclusion of anharmonicity is presented. The results indicate that when two materi…