Identification of the Intrinsic Ordering Effect of PtCo Intermetallic Catalysts on Fuel Cell Durability

ABSTRACT The dissolution of 3d transition metals is a central bottleneck limiting the practical use of Pt‐alloy cathode catalysts in fuel cells. Although ordered intermetallic compounds (IMCs) have been explored for nearly 4 decades as a route to mitigate this instability, the durability benefit of structural ordering itself remains debated and has rarely been reliably validated under practical membrane electrode assembly (MEA) conditions. Herein, we design a phase‐diagram‐guided sequential annealing protocol that yields an ordered/disordered PtCo catalyst pair with closely matched particle size and composition, enabling the durability effect of structural ordering to be rigorously isolated. In practical MEAs, structural ordering does not translate into a significant H 2 ‐air performance gain but markedly slows catalyst degradation. For example, after 90 000 cycles of accelerated durability test, the ordered catalyst loses only 28 mV at 1.5 A cm −2 , less than half that of its disordered counterpart (65 mV). Correlative in situ MEA diagnostics, electron microscopy, and online inductively coupled plasma mass spectrometry trace this enhanced durability to suppressed Co outward diffusion and dissolution. Machine‐learning‐accelerated theoretical calculations further rationalize this stabilization by revealing a higher thermodynamic penalty for Co surface segregation and a larger kinetic barrier for Co diffusion toward neighboring vacancies in the ordered IMC.

Authors

Institutions

Publication Details

Journal
Angewandte Chemie International Edition
Published
2026-11-11
DOI
https://doi.org/10.1002/anie.6908014
Primary Topic
Electrocatalysts for Energy Conversion
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Identification of the Intrinsic Ordering Effect of PtCo Intermetallic Catalysts on Fuel Cell Durability

Liang Zhang, Jianqiu Li, Hai‐Wei Liang, Lei Tong et al.
Angewandte Chemie International Edition
Electrocatalysts for Energy Conversion
article

Identification of the Intrinsic Ordering Effect of PtCo Intermetallic Catalysts on Fuel Cell Durability

Liang Zhang, Jianqiu Li, Hai‐Wei Liang, Lei Tong, Zhou Chen, Xiangfu Niu, Tian‐Wei Song, Yucheng Wang, Yanxi Lyu, Zi‐rui Li, Shuai Li, Rui Zhang, Cong Xu, Xuan Luo
article en

Abstract

ABSTRACT The dissolution of 3d transition metals is a central bottleneck limiting the practical use of Pt‐alloy cathode catalysts in fuel cells. Although ordered intermetallic compounds (IMCs) have been explored for nearly 4 decades as a route to mitigate this instability, the durability benefit of structural ordering itself remains debated and has rarely been reliably validated under practical membrane electrode assembly (MEA) conditions. Herein, we design a phase‐diagram‐guided sequential annealing protocol that yields an ordered/disordered PtCo catalyst pair with closely matched particle size and composition, enabling the durability effect of structural ordering to be rigorously isolated. In practical MEAs, structural ordering does not translate into a significant H 2 ‐air performance gain but markedly slows catalyst degradation. For example, after 90 000 cycles of accelerated durability test, the ordered catalyst loses only 28 mV at 1.5 A cm −2 , less than half that of its disordered counterpart (65 mV). Correlative in situ MEA diagnostics, electron microscopy, and online inductively coupled plasma mass spectrometry trace this enhanced durability to suppressed Co outward diffusion and dissolution. Machine‐learning‐accelerated theoretical calculations further rationalize this stabilization by revealing a higher thermodynamic penalty for Co surface segregation and a larger kinetic barrier for Co diffusion toward neighboring vacancies in the ordered IMC.

Angewandte Chemie International Edition
University of Science and Technology of China (CN), Xiamen University (CN), Tsinghua University (CN)
Electrocatalysts for Energy Conversion
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.

Laika access coming soon