Evolution and Reconstruction of Air‐Electrode Surface Composition in Reversible Protonic Ceramic Cells: Mechanisms, Impacts on Catalytic Performance, and Optimization Strategies – A Review

Advanced Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 5, 2025

Abstract Reversible protonic ceramic cells (R‐PCCs) are at the forefront of electrochemical conversion devices, capable reversibly and efficiently converting chemical energy into electricity intermediate temperatures (350–700 °C) with zero carbon emissions. However, slow surface catalytic reactions air‐electrode often hinder their performance durability. The electrode is not merely an extension bulk structure, equilibrium reconstruction can lead to significantly different crystal‐plane terminations morphologies, which influenced by material's intrinsic properties external reaction conditions. Understanding evolution elevated in water‐containing, oxidative atmospheres presents significant importance. In this review, a comprehensive summary recent processes applying advanced characterization techniques for high‐temperature surfaces provided, exploring correlations between fluctuations examining structural various associated degradation activation phenomena, offering insights impact on performance. Furthermore, reported strategies advances enhancing R‐PCCs through engineering discussed. This review offers valuable expected guide future developments catalysis, solid‐state ionics, materials.

Language: Английский

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Exploring hydration of air electrodes for protonic ceramic cells: a review

Chemical Engineering Journal, Journal Year: 2025, Volume and Issue: unknown, P. 160759 - 160759

Published: Feb. 1, 2025

Language: Английский

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Prediction of perovskite oxygen vacancies for oxygen electrocatalysis at different temperatures

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Oct. 29, 2024

Efficient catalysts are imperative to accelerate the slow oxygen reaction kinetics for development of emerging electrochemical energy systems ranging from room-temperature alkaline water electrolysis high-temperature ceramic fuel cells. In this work, we reveal role cationic inductive interactions in predetermining vacancy concentrations 235 cobalt-based and 200 iron-based perovskite at different temperatures, trend can be well predicted machine learning techniques based on lattice environment, requiring no heavy computational experimental inputs. Our results further show that catalytic activity perovskites is strongly correlated with their concentration operating temperatures. We then provide a learning-guided route developing electrocatalysts suitable operation temperatures time efficiency good prediction accuracy. Catalyst screening an important process but it's usually time-consuming labor intensive. Here authors report using develop solid oxide cells reduced

Language: Английский

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Advancements and prospects of perovskite-based fuel electrodes in solid oxide cells for CO₂ electrolysis to CO

Chemical Science, Journal Year: 2024, Volume and Issue: 15(29), P. 11166 - 11187

Published: Jan. 1, 2024

Developments and prospects for solid oxide cells using a perovskite-based fuel electrode CO 2 electrolysis to CO.

Language: Английский

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Specific surface area (SSA) of perovskites with uncertainty estimation approach

Computational Materials Science, Journal Year: 2025, Volume and Issue: 249, P. 113668 - 113668

Published: Jan. 9, 2025

Language: Английский

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Machine learning strategies for small sample size in materials science

Science China Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 2, 2025

Language: Английский

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Recent Progress in Sr₂Fe_1.5Mo_0.5O_6‐δ‐Based Multifunctional Materials for Energy Conversion and Storage

Advanced Functional Materials, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 1, 2024

Abstract Perovskite oxides, particularly double perovskite have drawn significant research interest within the fields of solid‐state chemistry and materials science. As a quintessential oxide, Sr 2 Fe 1.5 Mo 0.5 O 6‐δ (SFM) has unique electronic, magnetic, catalytic properties. These attributes make it promising candidate for energy conversion storage applications. This review offers comprehensive overview advancements using SFM across various applications, including solid oxide cells, protonic ceramic electrocatalysis. Notably, highlights emerging optimization strategies that enhance functionality based on fundamental understanding reaction mechanisms. The concludes by discussing persistent challenges facing SFM‐based functional materials, as well their prospects, considering both industrial

Language: Английский

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Co-based Spinel and Perovskite Oxides in Catalytic Combustion of Volatile Organic Compounds: Recent Advances and Future Prospects

Journal of environmental chemical engineering, Journal Year: 2025, Volume and Issue: 13(1), P. 115359 - 115359

Published: Jan. 7, 2025

Language: Английский

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Impact of Halogen Groups on the Properties of PEA‐Based 2D Pb–Sn Halide Perovskites

Advanced Optical Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 8, 2025

Abstract Tuning broad emission in 2D Pb–Sn halide perovskites (HPs) is essential for advancing optoelectronic applications, particularly color‐tunable and white‐light‐emitting devices. This linked to structural factors, such as defects phase segregation of the Pb component within system, which are strongly influenced by molecular structure chemical properties spacer cations. Atomic tuning spacers via halogenation opens up a new way fine‐tune properties, enabling further augmentations HP functionalities. Nevertheless, distinct emission's sensitivity chemistry remains underexplored. Here, halogenation's influence systematically investigated on characteristics using high‐throughput workflow. These findings reveal that F‐containing phenethylammonium (4F‐PEA) narrows broadband PL, whereas Cl broadens it. Through correlative study, it found 4F‐PEA reduces not only local but also defect levels microstrains HPs. likely attributed manifestation less lattice distortion stronger surface coordination dipole‐augmented 4F‐PEA. results highlight key factor modulating density HPs, offering promising pathway tune enhanced performance.

Language: Английский

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Mechanistically Interpretable AI for Accelerated Energy Materials Design

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: March 21, 2025

Breakthroughs in energy materials stem from a systematic understanding of catalytic activity and stability at the atomic scale. However, growing complexity real-world applications, conflicting material characterization metrics, overwhelming volume experimental data pose significant challenges identifying fundamental structure-property relationships translating them into transformative advancements. While informatics data-driven approaches have accelerated discovery, their effectiveness is often hindered by dataset bias, limited interpretability, poor generalizability. To address these challenges, we developed Two-Stage Material Screening framework, integrating high-throughput computations, standardized experiments, active learning to systematically explore vast chemical space 6,940,032 candidates, 4,287 promising electrocatalysts. By leveraging SHAP-based analysis, revealed pivotal role d-p band hybridization oxygen reduction reaction electrocatalysis, effectively linking theoretical insights with validation. Notably, protonic ceramic electrochemical cells incorporating five most electrocatalysts exhibited record-breaking peak power density 2.68 W cm² 600 °C – 35% higher than previous benchmarks while maintaining exceptional durability over 500 hours. Our AI-driven approach accurately predicts properties, reveals critical insights, accelerates validation, significantly advancing design.

Language: Английский

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