Reshaping the material research paradigm of electrochemical energy storage and conversion by machine learning

H Yang, Z He, M Zhang, X Tan, K Sun, H Liu, N Wang… - …, 2023 - Wiley Online Library
Abstract For a “Carbon Neutrality” society, electrochemical energy storage and conversion
(EESC) devices are urgently needed to facilitate the smooth utilization of renewable and …

Unveiling thermal stresses in RETaO4 (RE= Nd, Sm, Eu, Gd, Tb, Dy, Ho and Er) by first-principles calculations and finite element simulations

M Gan, X Chong, T Lu, C Yang, W Yu, SL Shang… - Acta Materialia, 2024 - Elsevier
Thermal stress (σ) plays a critical role in regulating the stability and durability of thermal
barrier coatings (TBCs) during service. However, its measurements are limited due to …

Extraordinary thermoelectric performance, thermal stability and mechanical properties of n-type Mg3Sb1. 5Bi0. 5 through multi-dopants at interstitial site

F Jiang, T Feng, Y Zhu, Z Han, R Shu, C Chen… - Materials Today …, 2022 - Elsevier
Mg 3 Sb 2-based thermoelectric materials have attracted much interest since the discovery
of their excellent n-type thermoelectric performance with excess Mg content and proper …

Machine learning in energy storage material discovery and performance prediction

G Huang, F Huang, W Dong - Chemical Engineering Journal, 2024 - Elsevier
Energy storage material is one of the critical materials in modern life. However, due to the
difficulty of material development, the existing mainstream batteries still use the materials …

Observation of ballistic-diffusive thermal transport in GaN transistors using thermoreflectance thermal imaging

ZK Liu, Y Shen, HL Li, BY Cao - Rare Metals, 2024 - Springer
To develop effective thermal management strategies for gallium-nitride (GaN) transistors, it
is essential to accurately predict the device junction temperature. Since the width of the heat …

[PDF][PDF] Structure, magnetic and thermoelectric properties of high entropy selenides Bi0. 6Sb0. 6In0. 4Cr0. 4Se3

F Jiang, T Feng, Y Zhu, C Xia, C Liu, Y Chen… - Mater. Lab, 2022 - matlab.labapress.com
Introducing magnetic elements or nanoparticles into the thermoelectric matrix is of great
importance to regulate the thermoelectric performance and evaluate the magnetic …

First principles calculations of the electronic configuration and photocatalytic performance of GaSe (Ga 2 SSe)/MoS 2 (MoSSe) heterojunctions

L Li, J Ren, J Li, X Guo, M Liu, X Lu - Journal of Materials Chemistry C, 2023 - pubs.rsc.org
The electronic structure and photocatalytic performance of GaSe/MoSSe and Ga2SSe/MoS2
heterojunctions are systematically investigated by means of first-principles calculations. The …

Machine learning guided 3D printing of carbon microlattices with customized performance for supercapacitive energy storage

H Yang, L Fang, Z Yuan, X Teng, H Qin, Z He, Y Wan… - Carbon, 2023 - Elsevier
Abstract Three-dimensional (3D) printing has stood out as a reliable technology to construct
carbon microlattice electrodes for supercapacitors (SCs) in the field of custom areal …

Prediction of sintered density of binary W (Mo) alloys using machine learning

HX Liu, YF Yang, YF Cai, CH Wang, C Lai, YW Hao… - Rare Metals, 2023 - Springer
Powder metallurgy is the optimal method for the consolidation and preparation of W (Mo)
alloys, which exhibit excellent application prospects at high temperatures. The properties of …

Machine Learning Unveils the Physical Properties of Materials Driving Thermoelectric Generator Efficiency: The Case of Half-Heuslers

A Tukmakova, P Graziosi - ACS Applied Energy Materials, 2024 - ACS Publications
We report a machine learning (ML)-based approach allowing thermoelectric generator
(TEG) efficiency evaluation directly from five parameters: two physical properties─ carrier …