Breaking the poisoning paradigm: a high-throughput DFT screening of high-entropy alloys with a focus on phonon-induced uncertainty

Although surface poisoning is typically thought to deactivate electrocatalysis, this work suggests its intentional application in promoting HER via a systematic high-throughput machine learning and DFT exploration of HEAs.

Authors

Institutions

Publication Details

Journal
Journal of Materials Chemistry A
Published
2025-01-01
DOI
https://doi.org/10.1039/d5ta03759j
Citations
2
Primary Topic
High Entropy Alloys Studies
Type
article
Field-Weighted Citation Impact
1.43

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Breaking the poisoning paradigm: a high-throughput DFT screening of high-entropy alloys with a focus on phonon-induced uncertainty

Mohsen Tamtaji, William A. Goddard, GuanHua Chen
2 citations
Journal of Materials Chemistry A
High Entropy Alloys Studies
1.43
article

Breaking the poisoning paradigm: a high-throughput DFT screening of high-entropy alloys with a focus on phonon-induced uncertainty

Mohsen Tamtaji, William A. Goddard, GuanHua Chen
article en
2 citations

Abstract

Although surface poisoning is typically thought to deactivate electrocatalysis, this work suggests its intentional application in promoting HER via a systematic high-throughput machine learning and DFT exploration of HEAs.

Journal of Materials Chemistry AVol. 13(32)
California Institute of Technology (US), QuantumCTek (China) (CN), University of Hong Kong (HK)
National Science Foundation, Hong Kong Government
Openalex Percentile: Top 19%
High Entropy Alloys Studies
1.43
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.