4 citations · 7 across the 4 of their papers we have counts for
Showing cond-mat.mtrl-sciShow all
3 papers · 1 filter
cond-mat.mtrl-sci2026
A Generalizable Machine Learning Framework for Half-Heusler Thermoelectrics
Shoeb Athar, Adrien Mecibah, Philippe Jund
Machine learning (ML) has emerged as a powerful approach for accelerating the discovery of thermoelectric (TE) materials, yet many models suffer from limited generalizability. Here…
cond-mat.mtrl-sci2026★ 3 cited
Beyond Predicted ZT: Machine Learning Strategies for the Experimental Discovery of Thermoelectric Materials
Shoeb Athar, Philippe Jund
The discovery of high-performance thermoelectric (TE) materials for advancing green energy harvesting from waste heat is an urgent need in the context of looming energy crisis and…
cond-mat.mtrl-sci2025★ 4 cited
Tackling dataset curation challenges towards reliable machine learning: a case study on thermoelectric materials
Shoeb Athar, Adrien Mecibah, Philippe Jund
Machine Learning (ML) driven discovery of novel and efficient thermoelectric (TE) materials warrants experimental TE datasets of high volume, diversity, and quality. While the larg…