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A multiscale framework to predict electrochemical characteristics of yttrium doped Barium Zirconate based solid oxide cells

机译:多尺度框架,以预测基于钇掺杂的基于氧化锆的固体氧化物细胞的电化学特性

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摘要

A multiscale model is developed combining physics at atomistic, meso and continuum scales to predict the electrochemical characteristics of Current-Voltage curves in Yttrium doped Barium Zirconate based solid oxide cells. The most probable reaction pathway involving proton transfer from the surface of electrodes to the electrode/air/electrolyte Triple Phase Boundary from where it moves to the electrolyte is proposed, and their reaction barriers have been predicted from Density Functional Theory calculations. The model is validated against experimental observations. The environment, such as the amount of H2 (reducing) and O2 (oxidizing) gases the electrolyte is equilibrated in, affects the type of charge carriers while the temperature affects their rate of transport. Both these factors affect the rate of reactions in the proposed pathway. These effects are well manifested in the predicted electrochemical characteristics. The reducing environments are suitable for fuel cell mode operation and, the oxidizing environments are suitable for electrolyzer cell mode operations. The activation energy for conductivity in oxidizing environments is higher making it less amenable for low-temperature operation than in reducing environments. A data-driven sensitivity analysis is performed from which a non intuitive parameter, permittivity of the electrolyte, is predicted to be important for Solid Oxide Cell performance.commentSuperscript/Subscript Available/comment
机译:多尺度模型是在原子,中索和连续尺度的组合物理学中,以预测钇掺杂钡基锆酸钡基固体氧化物细胞电流电压曲线的电化学特性。提出了涉及从电极表面转移到电极/空气/电解质三相边界的最可能的反应途径,从其移动到电解质的位置,并且已经预测了它们的反应屏障,从密度泛函理论计算中预测。该模型针对实验观察验证。诸如电解质平衡电解质的H 2(还原)和O 2(氧化)气体的环境,影响电荷载体的类型,而温度影响其运输速率。这两种因素都会影响所提出的途径中的反应率。这些效果在预测的电化学特征中表现出很好的表现。还原环境适用于燃料电池模式操作,并且氧化环境适用于电解槽单元模式操作。氧化环境中的电导率的激活能量较高,使其对低温操作的较少可容纳而不是在还原环境中。数据驱动的灵敏度分析是从哪一种非直观参数,电解质的介电常数,预测对固体氧化物细胞性能很重要。<注释>上标/下标的

著录项

  • 来源
    《Journal of power sources》 |2021年第1期|228969.1-228969.13|共13页
  • 作者

    Priya Pikee; Aluru N. R.;

  • 作者单位

    Univ Illinois Beckman Inst Adv Sci & Technol Dept Mech Sci & Engn Urbana IL 61801 USA;

    Univ Illinois Beckman Inst Adv Sci & Technol Dept Mech Sci & Engn Urbana IL 61801 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    BZY; SOFC; SOEC; Current-Voltage; Reducing and oxidizing; Neural networks;

    机译:BZY;SOFC;SOEC;电流电压;减少和氧化;神经网络;
  • 入库时间 2022-08-18 22:24:29

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