REFERENCES
1. Park, S.; Vohs, J. M.; Gorte, R. J. Direct oxidation of hydrocarbons in a solid-oxide fuel cell. Nature 2000, 404, 265-7.
2. Duan, C.; Kee, R.; Zhu, H.; et al. Highly efficient reversible protonic ceramic electrochemical cells for power generation and fuel production. Nat. Energy. 2019, 4, 230-40.
3. Wachsman, E. D.; Lee, K. T. Lowering the temperature of solid oxide fuel cells. Science 2011, 334, 935-9.
4. Zakaria, Z.; Awang Mat, Z.; Abu Hassan, S. H.; Boon Kar, Y. A review of solid oxide fuel cell component fabrication methods toward lowering temperature. Int. J. Energy. Res. 2020, 44, 594-611.
5. Vinchhi, P.; Khandla, M.; Chaudhary, K.; Pati, R. Recent advances on electrolyte materials for SOFC: a review. Inorg. Chem. Commun. 2023, 152, 110724.
6. Rafique, M.; Nawaz, H.; Shahid Rafique, M.; Bilal Tahir, M.; Nabi, G.; Khalid, N. Material and method selection for efficient solid oxide fuel cell anode: recent advancements and reviews. Int. J. Energy. Res. 2019, 43, 2423-46.
7. Ahmad, M. Z.; Ahmad, S. H.; Chen, R. S.; Ismail, A. F.; Hazan, R.; Baharuddin, N. A. Review on recent advancement in cathode material for lower and intermediate temperature solid oxide fuel cells application. Int. J. Hydrogen. Energy. 2022, 47, 1103-20.
8. Dhanasekaran, A.; Subramanian, Y.; Omeiza, L. A.; et al. Computational fluid dynamics for protonic ceramic fuel cell stack modeling: a brief review. Energies 2023, 16, 208.
9. Yokokawa, H.; Suzuki, M.; Yoda, M.; et al. Achievements of NEDO Durability Projects on SOFC stacks in the light of physicochemical mechanisms. Fuel. Cells. 2019, 19, 311-39.
10. Xu, Y.; Cai, S.; Chi, B.; Tu, Z. Technological limitations and recent developments in a solid oxide electrolyzer cell: a review. Int. J. Hydrogen. Energy. 2024, 50, 548-91.
11. Irvine, J. T. S.; Neagu, D.; Verbraeken, M. C.; Chatzichristodoulou, C.; Graves, C.; Mogensen, M. B. Evolution of the electrochemical interface in high-temperature fuel cells and electrolysers. Nat. Energy. 2016, 1, 15014.
12. Chen, K.; Jiang, S. P. Surface segregation in solid oxide cell oxygen electrodes: phenomena, mitigation strategies and electrochemical properties. Electrochem. Energ. Rev. 2020, 3, 730-65.
13. Khan, M.; Xu, X.; Knibbe, R.; Zhu, Z. Air electrodes and related degradation mechanisms in solid oxide electrolysis and reversible solid oxide cells. Renew. Sustaina. Energy. Rev. 2021, 143, 110918.
14. Lin, C.; Chen, T.; Chyou, Y.; Chiang, L. Thermal stress analysis of a planar SOFC stack. J. Power. Sources. 2007, 164, 238-51.
15. Brus, G.; Miyawaki, K.; Iwai, H.; Saito, M.; Yoshida, H. Tortuosity of an SOFC anode estimated from saturation currents and a mass transport model in comparison with a real micro-structure. Solid. State. Ionics. 2014, 265, 13-21.
16. Zhang, Y.; Chen, B.; Guan, D.; et al. Thermal-expansion offset for high-performance fuel cell cathodes. Nature 2021, 591, 246-51.
17. Choi, S.; Kucharczyk, C. J.; Liang, Y.; et al. Exceptional power density and stability at intermediate temperatures in protonic ceramic fuel cells. Nat. Energy. 2018, 3, 202-10.
18. Chen, Y.; deGlee, B.; Tang, Y.; et al. A robust fuel cell operated on nearly dry methane at 500 °C enabled by synergistic thermal catalysis and electrocatalysis. Nat. Energy. 2018, 3, 1042-50.
19. Machado, M.; Baiutti, F.; Bernadet, L.; et al. Functional thin films as cathode/electrolyte interlayers: a strategy to enhance the performance and durability of solid oxide fuel cells. J. Mater. Chem. A. 2022, 10, 17317-25.
20. Pirou, S.; Talic, B.; Brodersen, K.; et al. Production of a monolithic fuel cell stack with high power density. Nat. Commun. 2022, 13, 1263.
21. Jeong, H.; Lee, C.; Son, J.; et al. Advancing towards ready-to-use solid oxide fuel cells: 5 minute cold start-up with high-power performance. J. Mater. Chem. A. 2023, 11, 7415-21.
22. Gao, Z.; Mogni, L. V.; Miller, E. C.; Railsback, J. G.; Barnett, S. A. A perspective on low-temperature solid oxide fuel cells. Energy. Environ. Sci. 2016, 9, 1602-44.
23. Qiu, P.; Li, C.; Liu, B.; Yan, D.; Li, J.; Jia, L. Materials of solid oxide electrolysis cells for H2O and CO2 electrolysis: a review. J. Adv. Ceram. 2023, 12, 1463-510.
24. Yang, Y.; Zhang, Y.; Yan, M. A review on the preparation of thin-film YSZ electrolyte of SOFCs by magnetron sputtering technology. Sep. Purif. Technol. 2022, 298, 121627.
25. Hwang, S.; Lee, J.; Kang, G.; et al. A hydrogel-assisted GDC chemical diffusion barrier for durable solid oxide fuel cells. J. Mater. Chem. A. 2021, 9, 11683-90.
26. Menzler, N. H.; Sebold, D.; Sohn, Y. J.; Zischke, S. Post-test characterization of a solid oxide fuel cell after more than 10 years of stack testing. J. Power. Sources. 2020, 478, 228770.
27. Fang, Q.; Blum, L.; Stolten, D. Electrochemical performance and degradation analysis of an SOFC short stack following operation of more than 100,000 hours. J. Electrochem. Soc. 2019, 166, F1320-5.
28. Khan, M. Z.; Mehran, M. T.; Song, R.; Lee, J.; Lee, S.; Lim, T. A simplified approach to predict performance degradation of a solid oxide fuel cell anode. J. Power. Sources. 2018, 391, 94-105.
29. Gallo, M.; Polverino, P.; Mougin, J.; Morel, B.; Pianese, C. Coupling electrochemical impedance spectroscopy and model-based aging estimation for solid oxide fuel cell stacks lifetime prediction. Appl. Energy. 2020, 279, 115718.
30. Wang, Y.; Chen, T. A bi-objective AHP-MINLP-GA approach for flexible alternative supplier selection amid the COVID-19 pandemic. Soft. Comput. Lett. 2021, 3, 100016.
31. Xue, F.; Lei, Y.; Cheng, T.; et al. Phase-field modeling of crack growth and mitigation in solid oxide cells. Int. J. Hydrogen. Energy. 2023, 48, 9845-60.
32. Su, Y.; Zhong, Z.; Jiao, Z. A novel multi-physics coupled heterogeneous single-cell numerical model for solid oxide fuel cell based on 3D microstructure reconstructions. Energy. Environ. Sci. 2022, 15, 2410-24.
33. Monaco, F.; Hubert, M.; Vulliet, J.; et al. Degradation of Ni-YSZ electrodes in solid oxide cells: impact of polarization and initial microstructure on the Ni evolution. J. Electrochem. Soc. 2019, 166, F1229-42.
34. Yuan, B.; Zhang, X.; Tang, C.; Wang, N.; Ye, S. How AI guided the development of green hydrogen production: in the case of solid oxide electrolysis cell? J. Mater. Inf. 2025, 5, 25.
35. Liu, B.; Ding, M.; Shaham, S.; Rahayu, W.; Farokhi, F.; Lin, Z. When machine learning meets privacy: a survey and outlook. ACM. Comput. Surv. 2022, 54, 1-36.
36. Lu, X.; Luo, S.; Li, J.; et al. FIND: a forward–inverse navigation and discovery platform for hydrogen storage alloys powered by data-driven machine learning. J. Mater. Inf. 2025, 5, 48.
37. Di, H.; Liu, Z.; Xiao, M.; et al. Exploring hydration of air electrodes for protonic ceramic cells: a review. Chem. Eng. J. 2025, 507, 160759.
38. Xiong, X.; Liang, K.; Ma, G.; Ba, L. Three-dimensional multi-physics modelling and structural optimization of SOFC large-scale stack and stack tower. Int. J. Hydrogen. Energy. 2023, 48, 2742-61.
39. AK, Pollok, S, Hagen, A. Degradation studies using machine learning on novel solid oxide cell database. Fuel. Cells. 2021, 21, 566-76.
40. Li, H.; Zhu, J.; Lyu, Z.; Han, M.; Sun, K.; Zhong, H. An agile layer-resolved SOFC stack model using physics-informed neural network. Int. J. Hydrogen. Energy. 2024, 54, 586-600.
41. Gong, W.; Cai, Z.; Yang, J.; Li, X.; Jian, L. Parameter identification of an SOFC model with an efficient, adaptive differential evolution algorithm. Int. J. Hydrogen. Energy. 2014, 39, 5083-96.
42. Jacobs, R.; Liu, J.; Abernathy, H.; Morgan, D. Machine learning design of perovskite catalytic properties. Adv. Energy. Mater. 2024, 14, 2303684.
43. Sciazko, A.; Komatsu, Y.; Nakamura, A.; Ouyang, Z.; Hara, T.; Shikazono, N. 3D microstructures of solid oxide fuel cell Ni-YSZ anodes with carbon deposition. Chem. Eng. J. 2023, 460, 141680.
44. Zhang, G.; Zhao, H.; Lin, L.; Huang, P.; Ke, Z.; Wang, Q. Fast ionic conduction and boosted cathode reaction enabled by BSCF–YSZ for LT-SOFC application. J. Mater. Sci. Mater. Electron. 2023, 34, 11355.
45. Zhai, S.; Xie, H.; Cui, P.; et al. A combined ionic Lewis acid descriptor and machine-learning approach to prediction of efficient oxygen reduction electrodes for ceramic fuel cells. Nat. Energy. 2022, 7, 866-75.
46. Wang, N.; Yuan, B.; Tang, C.; et al. Machine-learning-accelerated development of efficient mixed protonic-electronic conducting oxides as the air electrodes for protonic ceramic cells. Adv. Mater. 2022, 34, e2203446.
47. Zhang, Q.; Guo, Y.; Ding, J.; Xia, S. Hole conductivity in the electrolyte of proton-conducting SOFC: mathematical model and experimental investigation. J. Alloys. Compd. 2019, 801, 343-51.
48. Wang, N.; Yuan, B.; Zheng, F.; et al. Machine‐learning assisted screening proton conducting Co/Fe based oxide for the air electrode of protonic solid oxide cell. Adv. Funct. Mater. 2024, 34, 2309855.
49. Tang, C.; Yuan, B.; Zhang, X.; et al. Rationally designed air electrode boosting electrochemical performance of protonic ceramic cells. Adv. Energy. Mater. 2025, 15, 2402654.
50. Niu, Z.; Zhao, W.; Wu, B.; et al. π Learning: a performance‐informed framework for microstructural electrode design. Adv. Energy. Mater. 2023, 13, 2300244.
51. Peng, X.; Xu, B. Unraveling impacts of polycrystalline microstructures on ionic conductivity of ceramic electrolytes by computational homogenization and machine learning. J. Appl. Phys. 2024, 136, 105101.
52. Yang, K.; Liu, J.; Wang, Y.; et al. Machine-learning-assisted prediction of long-term performance degradation on solid oxide fuel cell cathodes induced by chromium poisoning. J. Mater. Chem. A. 2022, 10, 23683-90.
53. Yu, F.; Xiao, J.; Zhang, Y.; et al. New insights into carbon deposition mechanism of nickel/yttrium-stabilized zirconia cermet from methane by in situ investigation. Appl. Energy. 2019, 256, 113910.
54. Lyu, Z.; Liu, Y.; Sciazko, A.; et al. Co‐generation of electricity and chemicals from methane using direct internal reforming solid oxide fuel cells. Adv. Energy. Mater. 2025, 15, 2403869.
55. Holzer, L.; Münch, B.; Iwanschitz, B.; Cantoni, M.; Hocker, T.; Graule, T. Quantitative relationships between composition, particle size, triple phase boundary length and surface area in nickel-cermet anodes for solid oxide fuel cells. J. Power. Sources. 2011, 196, 7076-89.
56. Mogensen, M. B.; Chen, M.; Frandsen, H. L.; et al. Ni migration in solid oxide cell electrodes: review and revised hypothesis. Fuel. Cells. 2021, 21, 415-29.
57. Shimura, T.; Jiao, Z.; Hara, S.; Shikazono, N. Quantitative analysis of solid oxide fuel cell anode microstructure change during redox cycles. J. Power. Sources. 2014, 267, 58-68.
58. Sciazko, A.; Komatsu, Y.; Yokoi, R.; Shimura, T.; Shikazono, N. Effects of mass fraction of La0.9Sr0.1Cr0.5Mn0.5O3-δ and Gd0.1Ce0.9O2-δ composite anodes for nickel free solid oxide fuel cells. J. Eur. Ceram. Soc. 2022, 42, 1556-67.
59. Jeangros, Q.; Aebersold, A.; Hébert, C.; Van Herle, J.; Hessler-Wyser, A. A TEM study of Ni interfaces formed during activation of SOFC anodes in H2: influence of grain boundary symmetry and segregation of impurities. Acta. Mater. 2016, 103, 442-7.
60. Harris, W. M.; Lombardo, J. J.; Nelson, G. J.; et al. Three-dimensional microstructural imaging of sulfur poisoning-induced degradation in a Ni-YSZ anode of solid oxide fuel cells. Sci. Rep. 2014, 4, 5246.
61. Sciazko, A.; Komatsu, Y.; Shimura, T.; Shikazono, N. Prediction of electrode microstructure evolutions with physically constrained unsupervised image-to-image translation networks. npj. Comput. Mater. 2024, 10, 1228.
62. Pawłowski, P.; Buchaniec, S.; Prokop, T.; Iwai, H.; Brus, G. Microstructure evolution of solid oxide fuel cell anodes characterized by persistent homology. Energy. AI. 2023, 14, 100256.
63. Zheng, Y.; Wu, X.; Zhao, D.; et al. Data-driven fault diagnosis method for the safe and stable operation of solid oxide fuel cells system. J. Power. Sources. 2021, 490, 229561.
64. Le, G. T.; Mastropasqua, L.; Brouwer, J.; Adler, S. B. Simulation-informed machine learning diagnostics of solid oxide fuel cell stack with electrochemical impedance spectroscopy. J. Electrochem. Soc. 2022, 169, 034530.
65. Wu, X.; Xu, Y.; Peng, J.; Xia, Z.; Kupecki, J.; Li, X. Novel hybrid modeling and analysis method for steam reforming solid oxide fuel cell system multifault degradation fusion assessment. ACS. Omega. 2023, 8, 36876-92.
66. He, Y.; Wang, R.; Kwong, S.; Wang, X. Bayesian classifiers based on probability density estimation and their applications to simultaneous fault diagnosis. Inform. Sci. 2014, 259, 252-68.
67. Zhang, Z.; Li, S.; Xiao, Y.; Yang, Y. Intelligent simultaneous fault diagnosis for solid oxide fuel cell system based on deep learning. Appl. Energy. 2019, 233-4, 930-42.
68. Liu, Y.; Qie, T.; Yu, Y.; et al. A novel integral reinforcement learning-based control method assisted by twin delayed deep deterministic policy gradient for solid oxide fuel cell in DC microgrid. IEEE. Trans. Sustain. Energy. 2023, 14, 688-703.
69. Mozdzierz, M.; Chalusiak, M.; Kimijima, S.; Szmyd, J. S.; Brus, G. An afterburner-powered methane/steam reformer for a solid oxide fuel cells application. Heat. Mass. Transfer. 2018, 54, 2331-41.
70. Ghorbani, B.; Vijayaraghavan, K. Developing a virtual hydrogen sensor for detecting fuel starvation in solid oxide fuel cells using different machine learning algorithms. Int. J. Hydrogen. Energy. 2020, 45, 27730-44.
71. Ba, L.; Xiong, X.; Yang, Z.; Lei, Z.; Ge, B.; Peng, S. A novel multi-physics and multi-dimensional model for solid oxide fuel cell stacks based on alternative mapping of BP neural networks. J. Power. Sources. 2021, 500, 229784.
72. Lyu, Z.; Wang, Y.; Sciazko, A.; et al. Prediction of fuel cell performance degradation using a combined approach of machine learning and impedance spectroscopy. J. Energy. Chem. 2023, 87, 32-41.
73. Wu, X.; Li, Y.; Cai, S.; et al. Data-driven approaches for predicting performance degradation of solid oxide fuel cells system considering prolonged operation and shutdown accumulation effect. J. Power. Sources. 2024, 598, 234186.
74. Barredo Arrieta, A.; Díaz-Rodríguez, N.; Del Ser, J.; et al. Explainable artificial intelligence (XAI): concepts, taxonomies, opportunities and challenges toward responsible AI. Inf. Fusion. 2020, 58, 82-115.
