5 papers
Active learning and molecular dynamics simulations to find high melting temperature alloys
David E. Farache, Juan C. Verduzco, Zachary D. McClure +2
Active learning (AL) can drastically accelerate materials discovery; its power has been shown in various classes of materials and target properties. Prior efforts have used machine…
Parsimonious neural networks learn interpretable physical laws
Saaketh Desai, Alejandro Strachan
Machine learning is playing an increasing role in the physical sciences and significant progress has been made towards embedding domain knowledge into models. Less explored is its…
Implementing a neural network interatomic model with performance portability for emerging exascale architectures
Saaketh Desai, Samuel Temple Reeve, James F. Belak
The two main thrusts of computational science are more accurate predictions and faster calculations; to this end, the zeitgeist in molecular dynamics (MD) simulations is pursuing m…
Tuning martensitic transformations via coherent second phases in nanolaminates using free energy landscape engineering
Saaketh Desai, Samuel Temple Reeve, Karthik Guda Vishnu +1
We explore the possibilities and limitations of using a coherent second phase to engineer the thermo-mechanical properties of a martensitic alloy by modifying the underlying free e…
Molecular Modeling of the Microstructure Evolution during the Carbonization of PAN-Based Carbon Fibers
Saaketh Desai, Chunyu Li, Tongtong Shen +1
Development of high strength carbon fibers (CFs) requires an understanding of the relationship between the processing conditions, microstructure and resulting properties. We develo…