Published October 16, 2026
| Version v1.1.0
Software
Open
Graded revision lets autonomous campaigns update symbolic laws of SiGeC semiconductors from mixed-fidelity evidence
Authors/Creators
- 1. Materials Science & Engineering, The University of Utah
Description
Code, data and figure scripts for the paper "Graded revision lets autonomous campaigns update symbolic laws of SiGeC semiconductors from mixed-fidelity evidence" (Journal of Materials Chemistry A (RSC)). Taylor D. Sparks acknowledges support from the Army Research Office Materials Design, under Contract No. W911NF-23-1-0333.
Notes
Code (Python, shell and SLURM scripts) is released under the MIT License (LICENSE). Data, result files and figures are released under the Creative Commons Attribution 4.0 International licence (LICENSE-CC-BY-4.0.txt). Archived third-party datasets keep their own terms; their sources are cited in the paper.
Files
Sparks-Ackolf-HOLAR-Autonomous-Labs/NablaSDL_Revision-v1.1.0.zip
Additional details
Related works
- Is supplement to
- Software: https://github.com/Sparks-Ackolf-HOLAR-Autonomous-Labs/NablaSDL_Revision/tree/v1.1.0 (URL)