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Accelerated identification of galvanic corrosion-inhibiting intermetallics in Al alloys via high-throughput DFT calculations and machine learning
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DOI:10.1016/j.mtchem.2026.103678.png)
Abstract
En 中文
• A multi-step high-throughput computation and machine learning were conducted to discover binary IMCs inducing inhibitory HER. • Phase stability screening, galvanic corrosion sensitivity assessment, and density functional theory calculations for Esurf and ΔGHad, were carried out to build the ML dataset. • The HER-suppressing capabilities of cathodic binary IMCs were ranked according to their surface stability and predicted ΔGHad via ML.
Keywords:
intermetallic compounds
hydrogen evolution reaction
galvanic corrosion
density functional theory
machine learning
Journal
IF:
6.7
Papers:
3.6K
Citations:
1.4W
