通过机器学习潜力加速PrNixCo1-xO3-δ的热和化学膨胀的原子模拟
Hao Deng1,2, Quanwen Sun1,3, Meng Li1
1Energy & Environmental Science and Technology, Idaho National Laboratory, Idaho Falls, ID, 83401, USA.
Small methods
|July 9, 2025
概括
质子陶电化学电池 (PCEC) 在高蒸汽中面临格子扩张,影响稳定性. 机器学习潜力揭示了Ni/Co占用影响这些扩张,建议减轻策略,以提高PCEC的界面稳定性.
科学领域:
- 材料科学 材料科学 材料科学
- 计算化学的计算化学
- 电化学 电化学 电化学
背景情况:
- 质子陶电化学电池 (PCEC) 在涉及高蒸汽度和高温的操作条件下容易发生显著的晶格扩张.
- 这些扩张,特别是在电极和固态电解质中,可能会损害PCEC的长期稳定性和性能.
- 了解驱动这些体积变化的基本机制对于设计更强大的PCEC材料至关重要.
研究的目的:
- 使用先进的计算方法阐明导质子PrNixCo1-xO3-δ (PNC) 格子的体积膨胀.
- 为了研究氧空缺 (
- 为了将Ni/Co占用与热和化学膨胀贡献及其对界面稳定性的影响相关联.
主要方法:
- 使用新开发的机器学习潜力 (MLP) 进行了Phonon计算.
- 这项研究分析了PrNixCo1-xO3-δ中的晶格扩张,其作用是氧空缺和质子合并的联合作用.
- 系统地调查了不同Ni/Co占用率对热和化学膨胀的影响.
主要成果:
- Ni/Co占用明显影响热和化学膨胀;Co占用与热膨胀有关,而Ni占用与化学膨胀有关.
- 与原始PNC材料相比,氧气空缺和质子吸收都会增加热膨胀.
- 温度升高会对水化诱导的化学扩张产生负面影响,而高Ni占用率会导致严重的化学扩张,可能会损害界面稳定性.
结论:
- 提高PCEC电化学性能的策略可能会对电极-电解质界面稳定性产生负面影响,特别是在高Ni占用时,由于显著的化学扩张.
- 缓解丰富的PNC材料中的化学扩张对于改善PCEC的界面稳定性至关重要.
- 基于机器学习的原子间潜力所采用的计算语音计算方法预计将对未来的PCEC开发做出重大贡献.
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