5 citations · 6 across the 5 of their papers we have counts for
5 papers
High-Throughput Computation of Li-based Battery Material Databases: Chemistry-Processing-Property Relationships
Scott R. Broderick, Kaito Miyamoto, Krishna Rajan
In this paper, we incorporate processing into the data driven property modeling of Li-based spinel battery materials. When considering spinel compounds of the form LiMe2O4 with Me…
New Generalized Informatics Framework for Development of Large Scale Virtual Battery Material Databases
Scott R. Broderick, Kaito Miyamoto, Krishna Rajan
In this paper, we introduce an approach for the prediction of capacity for over 100,000 spinel compounds relevant for battery materials, from which we propose the 20 most promising…
Machine-Learning-Based Intelligent Framework for Discovering Refractory High-Entropy Alloys with Improved High-Temperature Yield Strength
Stephen A. Giles, Debasis Sengupta, Scott R. Broderick +1
Refractory high-entropy alloys (RHEAs) are a promising class of alloys that show elevated-temperature yield strengths and have potential to use as high-performance materials in gas…
Impact of Extreme Electrical Fields on Charge Density Distributions in Alloys
Claudia Loyola, Joaquin Peralta, Scott R. Broderick +1
The purpose of this work is to identify the field evaporation mechanism associated with charge density distribution under extreme fields, linking atom probe tomography (APT) experi…
An Interactive 3D Visualization Tool for Large Scale Data Sets for Quantitative Atom Probe Tomography
Hari Dahal, Michael Stukowski, Matthias J. Graf +2
Several visualization schemes have been developed for imaging materials at the atomic level through atom probe tomography. The main shortcoming of these tools is their inability to…