3 citations · 4 across the 3 of their papers we have counts for
3 papers
physics.comp-ph2024★ 1 cited
Data-Driven Catalyst Design: A Machine Learning Approach to Predicting Electrocatalytic Performance in Hydrogen Evolution and Oxygen Evolution Reactions
Vipin K E, Prahallad Padhan
The transition to sustainable green hydrogen production demands innovative electrocatalyst design strategies that can overcome current technological limitations. This study introdu…
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…