Data for manuscript "Virp: neural network-accelerated prediction of physical properties in site-disordered materials"

Chen, Andy Paul; Hoffmann Petersen, Martin; Hippalgaonkar, Kedar

doi:10.5281/zenodo.16666679

Published August 1, 2025 | Version v1.0.1

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Data for manuscript "Virp: neural network-accelerated prediction of physical properties in site-disordered materials"

1. Nanyang Technological University
2. Technical University of Denmark
3. Institute of Materials Research and Engineering

Data corresponding to each subsection under Section 2: Results of "Virp: neural network-accelerated prediction of physical properties in site-disordered materials"

Please contact Andy Paul Chen (andypaul.chen@ntu.edu.sg) or Kedar Hippalgaonkar (kedar@ntu.edu.sg) for specific details.

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Name	Size
2-1 Determining the sample size (database).tar.gz md5:99b441a5894d9929b9a941332e34bbad	323.2 MB	Download
2-2 Periodic boundary image artifacts.tar.gz md5:c73e5a6734a2680d8821982ac16ecdaf	7.5 MB	Download
2-3 Symmetrical equivalence of virtual cells.tar.gz md5:8a0497b155cfdb1074d08198e7b25286	1.1 MB	Download
2-4 Calculation times.tar.gz md5:484647dba4c4451ee9b8346c2af5027b	253.6 kB	Download
2-5 Comparison with first principles calculations.tar.gz md5:9feab9425d8993c4663187c874f84fa1	7.8 GB	Download

Additional details

Repository URL: https://github.com/andypaulchen/virp
Programming language: Python
Development Status: Active

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Data for manuscript "Virp: neural network-accelerated prediction of physical properties in site-disordered materials"

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