High-throughput study of electrical conductivity in ordered metals
Abstract
We present a computational framework that integrates machine learning with high-throughput ab initio calculations to screen over 2.8 million compounds for metallic transport. We identify several intermetallic candidates with predicted high conductivities comparable to that of aluminum (36.59 x 106 S/m). We perform full electron-phonon coupling calculations for the top-performing materials, yielding results in good agreement with available experimental data. Our analysis reveals that while the noble metals (Ag, Au, Cu) possess a conductivity that remains difficult to surpass due to their unique electronic structure and low scattering, compounds like LiBePt2 can achieve comparable performance by utilizing valence electrons from light elements to shift high-scattering d-states beneath the Fermi level. This study not only identifies novel high-performance conductors but also demonstrates the predictive power of combining statistical learning with detailed ab initio calculations.
Versions
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BibTeX
@misc{silva2026highthroughput,
title = {{High-throughput study of electrical conductivity in ordered metals}},
author = {Thalis H. B. da Silva and Hai-Chen Wang and Tiago F. T. Cerqueira and Simone Di Cataldo and Silvana Botti and Miguel A. L. Marques},
howpublished = {arXiv},
year = {2026},
month = aug,
doi = {10.48550/arxiv.2605.22167},
eprint = {2605.22167},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2605.22167},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - High-throughput study of electrical conductivity in ordered metals
AU - Thalis H. B. da Silva
AU - Hai-Chen Wang
AU - Tiago F. T. Cerqueira
AU - Simone Di Cataldo
AU - Silvana Botti
AU - Miguel A. L. Marques
PY - 2026
DA - 2026/08/15
PB - arXiv
DO - 10.48550/arxiv.2605.22167
UR - https://arxiv.org/abs/2605.22167
AB - We present a computational framework that integrates machine learning with high-throughput ab initio calculations to screen over 2.8 million compounds for metallic transport. We identify several intermetallic candidates with predicted high conductivities comparable to that of aluminum (36.59 x 10^6 S/m). We perform full electron-phonon coupling calculations for the top-performing materials, yielding results in good agreement with available experimental data. Our analysis reveals that while the noble metals (Ag, Au, Cu) possess a conductivity that remains difficult to surpass due to their unique electronic structure and low scattering, compounds like LiBePt2 can achieve comparable performance by utilizing valence electrons from light elements to shift high-scattering d-states beneath the Fermi level. This study not only identifies novel high-performance conductors but also demonstrates the predictive power of combining statistical learning with detailed ab initio calculations.
ER -