Recent progress on multi-scale calculation of perovskite-based proton-conducting electrolytes for proton ceramic fuel cells

Weiwei Zhang, Yong Wang, Wolong Li, Yongcun Li, Lili Sun and Xuyun Zhang

Applied Energy, 2026, vol. 402, issue PC, No S0306261925017490

Abstract: Proton ceramic fuel cells have received much attention as efficient energy conversion technologies due to their relatively mild operating temperature, low cost and excellent performance. Perovskite-type oxides are the core electrolyte materials that affect the efficiency of proton ceramic fuel cells due to the inherent property of allowing proton traversal. In this paper, we provide a systematic review of multi-scale simulations, which can reveal proton absorption and conduction mechanisms from the atomic scale to the macroscopic scale to screen novel electrolyte materials and reveal their constitutive relationships. To accelerate proton conduction, atomic-scale simulations based on first-principles calculations of density-functional theory have provided an important theoretical tool for revealing the proton transport mechanism of perovskite-based proton conductors and optimizing the material design in recent years. The integration of density-functional theory with conventional experiments, molecular dynamics, and machine learning is emphasized, which will accelerate the development process of high-performance electrolytes for proton ceramic fuel cells. Firstly, a major overview of the application of first-principles and molecular dynamics calculations to the study of perovskite-based proton-conducting electrolytes is presented, including the electronic structure and its phase stability, thermodynamic and chemical properties, and the kinetic properties and mechanisms of proton absorption and conduction. The integrated pairing of multi-scale optimization of perovskite-based proton-conducting electrolytes and the use of machine learning and high-throughput screening to optimize the important decisions of candidate materials are also discussed. Some representative examples are given in turn. In particular, the focus is summarized on defect regulation mechanisms, proton migration path resolution, the process of protons crossing grain boundaries, and the prediction of novel materials. The auxiliary relationship between theoretical calculations and experimental characterization is also explored. Finally, from a personal perspective, the current challenges and future directions of computationally driven proton conductor electrolyte materials with multi-scale interconvergence are discussed.

Keywords: PCFCs; Perovskite-based proton-conducting electrolytes; Proton transport mechanism; Machine learning; High-throughput screening (search for similar items in EconPapers)
Date: 2026
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261925017490
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:402:y:2026:i:pc:s0306261925017490

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2025.127019

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().