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1 to 4 of 4 Results

Data for: A Physics-Regularized Machine Learning Approach for Predicting Time–Temperature–Transformation Curves in Alloys: Application to Uranium-Based Alloys Mar 30, 2026 Garg, Sunidhi; Jishnu Bhattacharyya; Vineet V. Joshi; Sean R. Agnew; Prasanna V. Balachandran, 2026, "Data for: A Physics-Regularized Machine Learning Approach for Predicting Time–Temperature–Transformation Curves in Alloys: Application to Uranium-Based Alloys", https://doi.org/10.18130/V3/EXJA3W, University of Virginia Dataverse, V1 The data in each sheet is described below: 1. Data_train: Training dataset used for all the ML models 2. Data_test: Test dataset used for all the ML models 3. Data_virtual: Dataset having the principal component (PC) values of U-Mo-X alloys absent from train and test set and is the input to predict the TTT curves for these U-Mo-X alloys 4. Data_cal...
Data for: An Active Learning Framework for Predicting Misfit Volume in Body-Centered Cubic Refractory High-Entropy Alloys Mar 23, 2026 Liu, Shunshun; Balachandran, Prasanna V., 2026, "Data for: An Active Learning Framework for Predicting Misfit Volume in Body-Centered Cubic Refractory High-Entropy Alloys", https://doi.org/10.18130/V3/AD6H08, University of Virginia Dataverse, V1 Data for: An Active Learning Framework for Predicting Misfit Volume in Body-Centered Cubic Refractory High-Entropy Alloys. This repository contains relaxation trajectories for all BCC HEA crystal structures, and 11 template SQS structures.
Data for: A Computational Dieke Design Map for Near-Infrared Optical Absorption in Transition Metal-Substituted Yttria-Stabilized Zirconia Feb 13, 2026 Liu, Shunshun; Clarke, David R.; Balachandran, Prasanna V., 2026, "Data for: A Computational Dieke Design Map for Near-Infrared Optical Absorption in Transition Metal-Substituted Yttria-Stabilized Zirconia", https://doi.org/10.18130/V3/9DMDUS, University of Virginia Dataverse, V1 Collection of 16 transition metal-substituted YSZ (yttria-stabilized zirconia) structure files and corresponding Yambo GW-BSE output logs, organized by dopant and nominal charge state. The crystal structure file can be used to replicate the GW-BSE calculation discussed in the manuscript, and the GW-BSE output log can be used a reference of GW-BSE c...
Replication Data for: Expert-Grounded Prompt Engineering for Extracting Lattice Constants of High Entropy Alloys from Scientific Publications using Large Language Models Jan 2, 2026 Liu, Shunshun; Booth, Talon R.; Ji, Yangfeng; Reinhart, Wesley; Balachandran, Prasanna V., 2025, "Replication Data for: Expert-Grounded Prompt Engineering for Extracting Lattice Constants of High Entropy Alloys from Scientific Publications using Large Language Models", https://doi.org/10.18130/V3/ABITMJ, University of Virginia Dataverse, V2, UNF:6:paS6QAcYVTvf7GrPXMUGXg== [fileUNF] Raw data and code snapshot for Expert-Grounded Prompt Engineering for Extracting Lattice Constants of High Entropy Alloys from Scientific Publications using Large Language Models.

Data for: A Physics-Regularized Machine Learning Approach for Predicting Time–Temperature–Transformation Curves in Alloys: Application to Uranium-Based Alloys

Mar 30, 2026

Garg, Sunidhi; Jishnu Bhattacharyya; Vineet V. Joshi; Sean R. Agnew; Prasanna V. Balachandran, 2026, "Data for: A Physics-Regularized Machine Learning Approach for Predicting Time–Temperature–Transformation Curves in Alloys: Application to Uranium-Based Alloys", https://doi.org/10.18130/V3/EXJA3W, University of Virginia Dataverse, V1

The data in each sheet is described below: 1. Data_train: Training dataset used for all the ML models 2. Data_test: Test dataset used for all the ML models 3. Data_virtual: Dataset having the principal component (PC) values of U-Mo-X alloys absent from train and test set and is the input to predict the TTT curves for these U-Mo-X alloys 4. Data_cal...

Data for: An Active Learning Framework for Predicting Misfit Volume in Body-Centered Cubic Refractory High-Entropy Alloys

Mar 23, 2026

Liu, Shunshun; Balachandran, Prasanna V., 2026, "Data for: An Active Learning Framework for Predicting Misfit Volume in Body-Centered Cubic Refractory High-Entropy Alloys", https://doi.org/10.18130/V3/AD6H08, University of Virginia Dataverse, V1

Data for: An Active Learning Framework for Predicting Misfit Volume in Body-Centered Cubic Refractory High-Entropy Alloys. This repository contains relaxation trajectories for all BCC HEA crystal structures, and 11 template SQS structures.

Data for: A Computational Dieke Design Map for Near-Infrared Optical Absorption in Transition Metal-Substituted Yttria-Stabilized Zirconia

Feb 13, 2026

Liu, Shunshun; Clarke, David R.; Balachandran, Prasanna V., 2026, "Data for: A Computational Dieke Design Map for Near-Infrared Optical Absorption in Transition Metal-Substituted Yttria-Stabilized Zirconia", https://doi.org/10.18130/V3/9DMDUS, University of Virginia Dataverse, V1

Collection of 16 transition metal-substituted YSZ (yttria-stabilized zirconia) structure files and corresponding Yambo GW-BSE output logs, organized by dopant and nominal charge state. The crystal structure file can be used to replicate the GW-BSE calculation discussed in the manuscript, and the GW-BSE output log can be used a reference of GW-BSE c...

Replication Data for: Expert-Grounded Prompt Engineering for Extracting Lattice Constants of High Entropy Alloys from Scientific Publications using Large Language Models

Jan 2, 2026

Liu, Shunshun; Booth, Talon R.; Ji, Yangfeng; Reinhart, Wesley; Balachandran, Prasanna V., 2025, "Replication Data for: Expert-Grounded Prompt Engineering for Extracting Lattice Constants of High Entropy Alloys from Scientific Publications using Large Language Models", https://doi.org/10.18130/V3/ABITMJ, University of Virginia Dataverse, V2, UNF:6:paS6QAcYVTvf7GrPXMUGXg== [fileUNF]

Raw data and code snapshot for Expert-Grounded Prompt Engineering for Extracting Lattice Constants of High Entropy Alloys from Scientific Publications using Large Language Models.

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