90 citations · 348 across the 19 of their papers we have counts for
19 papers
Best Practices for Fitting Machine Learning Interatomic Potentials for Molten Salts: A Case Study Using NaCl-MgCl2
Siamak Attarian, Chen Shen, Dane Morgan +1
In this work, we developed a compositionally transferable machine learning interatomic potential using atomic cluster expansion potential and PBE-D3 method for (NaCl)1-x(MgCl2)x mo…
Multi-principal element alloy discovery using directed energy deposition and machine learning
Phalgun Nelaturu, Jason R. Hattrick-Simpers, Michael Moorehead +4
Multi-principal element alloys open large composition spaces for alloy development. The large compositional space necessitates rapid synthesis and characterization to identify prom…
Amorphous shear bands in crystalline materials as drivers of plasticity
Xuanxin Hu, Nuohao Liu, Vrishank Jambur +7
Traditionally, the formation of amorphous shear bands (SBs) in crystalline materials has been undesirable, because SBs can nucleate voids and act as precursors to fracture. They al…
Machine Learning Prediction of Critical Cooling Rate for Metallic Glasses From Expanded Datasets and Elemental Features
Benjamin T. Afflerbach, Carter Francis, Lane E. Schultz +9
We use a random forest model to predict the critical cooling rate (RC) for glass formation of various alloys from features of their constituent elements. The random forest model wa…
Thermophysical properties of FLiBe using moment tensor potentials
Siamak Attarian, Dane Morgan, Izabela Szlufarska
Fluoride salts are prospective materials for applications in some next generation nuclear reactors and their thermophysical properties at various conditions are of interest. Experi…
Modified Band Alignment Method to Obtain Hybrid Functional Accuracy from Standard DFT: Application to Defects in Highly Mismatched III-V:Bi Alloys
Maciej P. Polak, Robert Kudrawiec, Ryan Jacobs +2
This paper provides an accurate theoretical defect energy database for pure and Bi-containing III-V (III-V:Bi) materials and investigates efficient methods for high-throughput defe…