most citedUnlocking Thermoelectric Potential: A Machine Learning Stacking Approach for Half Heusler Alloys

3 citations · 4 across the 3 of their papers we have counts for

collaborators
Showing cond-mat.mtrl-sciShow all

2 papers · 1 filter

cond-mat.mtrl-sci2024★ 3 cited

Unlocking Thermoelectric Potential: A Machine Learning Stacking Approach for Half Heusler Alloys

Vipin K. E, Prahallad Padhan

Thermoelectric properties of Half Heusler alloys are predicted by adopting an ensemble modelling approach, specifically the stacking model integrated using Random Forest and XGBoos…

cond-mat.mtrl-sci2024

Advancements in Tuning Thermoelectric Properties: Insights from Hybrid Functional Studies, Strain Engineering, and Machine Learning Models

Vipin K E, Prahallad Padhan

Thermoelectric properties in topological insulator Bi2Se3 are explored with multifaceted strategies, i.e., hybrid functional with strain and artificial intelligence methodology. Th…