journal article·2026-04-14Open access

Bifunctional Electrocatalysts with High-Entropy Alloys: Bridging Hydrogen Evolution and Oxygen Reduction

Jialu Li, Jianzhuo Wu, Abdulrahman Allangawi, Yu Li, Honglin Li, Yongfeng Guo, Huabin Zhang, Wan-Lu Li

Chemistry of Materials· Volume 38· Issue 7

Abstract

High-entropy alloys (HEAs) have emerged as a promising class of bifunctional electrocatalysts capable of simultaneously driving the hydrogen evolution reaction (HER) and the oxygen reduction reaction (ORR) with high activity and durability. Their near-equiatomic multicomponent compositions give rise to unique physicochemical characteristics, including lattice distortion, sluggish diffusion, high-entropy stabilization, and pronounced electronic heterogeneity, that collectively generate diverse and synergistic active sites inaccessible in conventional alloys. This review summarizes recent progress in HEA-based bifunctional electrocatalysis, with a focus on the fundamental mechanisms governing HER and ORR activity, stability, and selectivity. We discuss advances in synthesis strategies, ranging from confined growth and step-alloying to scalable continuous-flow methods, that enable precise control over composition, size, and surface structure. Complementary computational and data-driven approaches, including density functional theory, machine-learning-assisted screening, and descriptor development, are highlighted as essential tools for navigating the vast HEA design space and establishing structure-property relationships. Particular attention is paid to adsorption-energy distributions, multisite cooperativity, and environmental effects under realistic electrochemical conditions. Finally, we outline current challenges and future opportunities for integrating mechanistic understanding with AI-guided, closed-loop design frameworks to accelerate the discovery of next-generation HEA bifunctional electrocatalysts for sustainable energy conversion.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Electrocatalysts for Energy Conversion · High Entropy Alloys Studies · Machine Learning in Materials Science

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Program of Materials Science and Engineering

University of California San Diego

Aiiso Yufeng Li Family Department of Chemical and Nano Engineering

Center for Renewable Energy and Storage Technologies (CREST), Physical Science and Engineering Division

King Abdullah University of Science and Technology (KAUST)

Funding

University of California, San Diego · Basic Energy Sciences · Air Force Office of Scientific Research · American Chemical Society Petroleum Research Fund

References (100+)

Show source-provided references
1. 10.1021/acs.chemrev.3c0033210.1021/acs.chemrev.3c00332 ↗
2. 10.1126/sciadv.adn287710.1126/sciadv.adn2877 ↗
3. 10.1016/j.matdes.2025.11463310.1016/j.matdes.2025.114633 ↗
4. 10.1038/nature1147510.1038/nature11475 ↗
5. 10.1016/j.joule.2018.12.01510.1016/j.joule.2018.12.015 ↗
6. 10.1039/c2ra20839c10.1039/c2ra20839c ↗
7. 10.1016/j.rser.2019.10962010.1016/j.rser.2019.109620 ↗
8. 10.1038/s41560-019-0462-710.1038/s41560-019-0462-7 ↗
9. 10.1021/acs.chemrev.5b0046210.1021/acs.chemrev.5b00462 ↗
10. 10.1021/jz501061n10.1021/jz501061n ↗
11. 10.1021/jp047349j10.1021/jp047349j ↗
12. 10.1021/acscatal.1c0485410.1021/acscatal.1c04854 ↗
13. 10.1002/aenm.20160023610.1002/aenm.201600236 ↗
14. 10.1038/nchem.36710.1038/nchem.367 ↗
15. 10.1038/s41578-019-0121-410.1038/s41578-019-0121-4 ↗
16. 10.1002/adfm.20241311510.1002/adfm.202413115 ↗
17. 10.3390/e1609474910.3390/e16094749 ↗
18. 10.1016/j.msea.2003.10.25710.1016/j.msea.2003.10.257 ↗
19. 10.1002/adem.20030056710.1002/adem.200300567 ↗
20. 10.1016/j.actamat.2016.08.08110.1016/j.actamat.2016.08.081 ↗
21. 10.1016/j.jmrt.2024.01.24610.1016/j.jmrt.2024.01.246 ↗
22. 10.1016/j.pmatsci.2013.10.00110.1016/j.pmatsci.2013.10.001 ↗
23. 10.1016/j.coelec.2020.10065110.1016/j.coelec.2020.100651 ↗
24. 10.1002/anie.20242376510.1002/anie.202423765 ↗
25. 10.1038/s41467-025-63527-710.1038/s41467-025-63527-7 ↗
26. 10.1002/adma.20230249910.1002/adma.202302499 ↗
27. 10.1002/adma.20230183610.1002/adma.202301836 ↗
28. 10.1126/sciadv.abg160010.1126/sciadv.abg1600 ↗
29. 10.1063/1.481232310.1063/1.4812323 ↗
30. 10.1080/21663831.2023.222439710.1080/21663831.2023.2224397 ↗
31. 10.1016/j.pmatsci.2022.10101810.1016/j.pmatsci.2022.101018 ↗
32. 10.1016/j.chempr.2019.02.01510.1016/j.chempr.2019.02.015 ↗
33. 10.1021/acscatal.9b0434310.1021/acscatal.9b04343 ↗
34. 10.1080/21663831.2014.91269010.1080/21663831.2014.912690 ↗
35. 10.1038/s41467-020-19277-910.1038/s41467-020-19277-9 ↗
36. Hammer B. · 2000 · 45 · 71
37. 10.1038/nmat331310.1038/nmat3313 ↗
38. 10.1016/j.esci.2025.10050610.1016/j.esci.2025.100506 ↗
39. 10.1103/PhysRevLett.81.281910.1103/PhysRevLett.81.2819 ↗
40. 10.1038/nmat379510.1038/nmat3795 ↗
41. 10.1126/science.121193410.1126/science.1211934 ↗
42. 10.1038/s41560-018-0296-810.1038/s41560-018-0296-8 ↗
43. 10.1021/ja072479210.1021/ja0724792 ↗
44. 10.1149/1.185698810.1149/1.1856988 ↗
45. 10.1002/cctc.20100039710.1002/cctc.201000397 ↗
46. 10.1016/S0022-0728(75)80261-010.1016/S0022-0728(75)80261-0 ↗
47. 10.1021/j100148a03010.1021/j100148a030 ↗
48. 10.1021/j100022a00210.1021/j100022a002 ↗
49. 10.1016/S0167-5729(01)00022-X10.1016/S0167-5729(01)00022-X ↗
50. 10.1021/acs.chemrev.9b0024810.1021/acs.chemrev.9b00248 ↗
51. 10.1039/C3CS60468C10.1039/C3CS60468C ↗
52. 10.1149/1.277969210.1149/1.2779692 ↗
53. 10.1039/tf951470091410.1039/tf9514700914 ↗
54. 10.1016/j.nanoen.2016.04.01710.1016/j.nanoen.2016.04.017 ↗
55. 10.1039/c3ee00045a10.1039/c3ee00045a ↗
56. 10.1016/j.matt.2020.07.02910.1016/j.matt.2020.07.029 ↗
57. 10.1002/anie.20201437410.1002/anie.202014374 ↗
58. 10.1002/anie.20171185810.1002/anie.201711858 ↗
59. 10.1126/science.113594110.1126/science.1135941 ↗
60. 10.1002/aenm.20180226910.1002/aenm.201802269 ↗
61. 10.1021/acs.chemrev.4c0013310.1021/acs.chemrev.4c00133 ↗
62. 10.1016/S1872-2067(24)60067-710.1016/S1872-2067(24)60067-7 ↗
63. 10.1007/s12274-022-4432-110.1007/s12274-022-4432-1 ↗
64. 10.1038/s41524-025-01579-510.1038/s41524-025-01579-5 ↗
65. 10.1016/j.jmst.2021.12.01410.1016/j.jmst.2021.12.014 ↗
66. 10.1016/j.matlet.2021.13109810.1016/j.matlet.2021.131098 ↗
67. 10.1016/j.jmst.2021.09.02510.1016/j.jmst.2021.09.025 ↗
68. 10.1039/C9RA03254A10.1039/C9RA03254A ↗
69. 10.1007/s42864-021-00084-810.1007/s42864-021-00084-8 ↗
70. 10.1002/sstr.20200003310.1002/sstr.202000033 ↗
71. 10.1002/smsc.20220010910.1002/smsc.202200109 ↗
72. 10.1016/j.nanoen.2023.10836210.1016/j.nanoen.2023.108362 ↗
73. 10.1126/science.abn310310.1126/science.abn3103 ↗
74. 10.1002/aenm.20220296210.1002/aenm.202202962 ↗
75. 10.1007/s40820-025-01779-010.1007/s40820-025-01779-0 ↗
76. 10.1088/0957-0233/16/1/00110.1088/0957-0233/16/1/001 ↗
77. 10.1021/co200007w10.1021/co200007w ↗
78. 10.1080/09506608.2016.118002010.1080/09506608.2016.1180020 ↗
79. 10.1038/s41929-018-0142-110.1038/s41929-018-0142-1 ↗
80. 10.1557/jmr.2018.22210.1557/jmr.2018.222 ↗
81. 10.1016/j.matlet.2020.12875410.1016/j.matlet.2020.128754 ↗
82. 10.1103/PhysRevLett.116.10550110.1103/PhysRevLett.116.105501 ↗
83. 10.1143/PTPS.53.110.1143/PTPS.53.1 ↗
84. 10.1557/jmr.2018.23710.1557/jmr.2018.237 ↗
85. 10.1103/PhysRevB.61.787710.1103/PhysRevB.61.7877 ↗
86. 10.1016/j.jallcom.2019.15292810.1016/j.jallcom.2019.152928 ↗
87. 10.1103/PhysRev.156.80910.1103/PhysRev.156.809 ↗
88. 10.1103/PhysRevLett.65.35310.1103/PhysRevLett.65.353 ↗
89. Gao M. C. · 2016 · 33310.1007/978-3-319-27013-5_10 ↗
90. 10.1016/S0364-5916(02)80006-210.1016/S0364-5916(02)80006-2 ↗
91. 10.1007/s11837-015-1594-210.1007/s11837-015-1594-2 ↗
92. 10.1016/j.calphad.2008.12.00510.1016/j.calphad.2008.12.005 ↗
93. 10.1103/PhysRevB.102.17420910.1103/PhysRevB.102.174209 ↗
94. Li, H.; Liu, C.; Guo, Y.; Luo, X.; Chen, Y.; Li, W.L. Conditional Generative Modeling for Amorphous Multi-Element Materials arXiv preprint arXiv:2503.07043 Mar. 10th, 2025.10.21203/rs.3.rs-6364530/v1 ↗
95. 10.20517/jmi.2021.0510.20517/jmi.2021.05 ↗
96. 10.1126/science.abo494010.1126/science.abo4940 ↗
97. 10.1021/jp047349j10.1021/jp047349j ↗
98. 10.1038/376238a010.1038/376238a0 ↗
99. 10.1038/s41578-019-0152-x10.1038/s41578-019-0152-x ↗
100. 10.1002/celc.20180130210.1002/celc.201801302 ↗