Cu–Ni Oxidation Mechanism Unveiled: A Machine Learning-Accelerated First-Principles and in Situ TEM Study

Wisesa, Pandu; Li, Meng; Curnan, Matthew T.; Gu, Geun Ho; Han, Jeong Woo; Yang, Judith C.; Saidi, Wissam A.

doi:10.1021/acs.nanolett.4c04648

Cu–Ni Oxidation Mechanism Unveiled: A Machine Learning-Accelerated First-Principles and in Situ TEM Study

Journal Article · Tue Jan 14 00:00:00 EST 2025 · Nano Letters

DOI:https://doi.org/10.1021/acs.nanolett.4c04648· OSTI ID:2503927

^[1]; Li, Meng ^[2]; ^[3]; ^[4]; ^[5]; Yang, Judith C. ^[2]; ^[6]

Univ. of Pittsburgh, PA (United States)
Univ. of Pittsburgh, PA (United States); Brookhaven National Laboratory (BNL), Upton, NY (United States). Center for Functional Nanomaterials (CFN)
Univ. of Pittsburgh, PA (United States); Korea Institute of Energy Technology (KENTECH), Naju (Korea, Republic of)
Korea Institute of Energy Technology (KENTECH), Naju (Korea, Republic of)
Seoul National Univ. (Korea, Republic of)
Univ. of Pittsburgh, PA (United States); National Energy Technology Laboratory (NETL), Pittsburgh, PA (United States)

Here, the development of accurate methods for determining how alloy surfaces spontaneously restructure under reactive and corrosive environments is a key, long-standing, grand challenge in materials science. Using machine learning-accelerated density functional theory and rare-event methods, in conjunction with in situ environmental transmission electron microscopy (ETEM), we examine the interplay between surface reconstructions and preferential segregation tendencies of CuNi(100) surfaces under oxidation conditions. Our modeling approach predicts that oxygen-induced Ni segregation in CuNi alloys favors Cu(100)-O c(2 × 2) reconstruction and destabilizes the Cu(100)-O (2√2 × √2)R45° missing row reconstruction (MRR). In situ ETEM experiments validate these predictions and show Ni segregation followed by NiO nucleation and growth in regions without MRR, with secondary nucleation and growth of Cu₂O in MRR regions. Our approach based on combining disparate computational components and in situ ETEM provides a holistic description of the oxidation mechanism in CuNi, which applies to other alloy systems.

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This content will become publicly available on Wed Jan 14 00:00:00 EST 2026

Research Organization:: Brookhaven National Laboratory (BNL), Upton, NY (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); National Science Foundation (NSF); National Research Foundation of Korea (NRF)

Grant/Contract Number:: SC0012704; CSSI-2003808; CBET-2130804; OAC-2117681; CMMI-1905647

OSTI ID:: 2503927

Report Number(s):: BNL-227499-2025-JAAM

Journal Information:: Nano Letters, Journal Name: Nano Letters; ISSN 1530-6984

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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36 MATERIALS SCIENCE
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