High-Performance stacking ensemble learning for thermoelectric figure-of-merit prediction

High-Performance stacking ensemble learning for thermoelectric figure-of-merit prediction

Thermoelectric materials, which convert thermal energy directly into electricity, hold promise for sustainable energy applications. However, accurately predicting their efficiency, quantified by the figure of merit (zT), remains challenging, especially for doped materials. Here we present a machine...

Full description

Saved in:
Bibliographic Details
Main Authors: Yuelin Wang, Chengquan Zhong, Jingzi Zhang, Honghao Yao, Junjie Chen, Xi Lin
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Materials & Design
Subjects:
Thermoelectric materials
zT
Machine Learning
Stacking ensemble model
Online Access:http://www.sciencedirect.com/science/article/pii/S0264127524009274
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items