Enhancing the Faradaic efficiency of solid oxide electrolysis cells: progress and perspective 

Prashik S. Gaikwad, Kunal Mondal, Yun Kyung Shin, Adri C. T. van Duin & Gorakh Pawar

npj Computational Materials 9: 149 (2023)

doi.org/10.1038/s41524-023-01044-1

Published: 21 August, 2023

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综述：固体氧化物电解池的最新进展与展望

为减少全球变暖，许多国家正在转向可持续的能源生产系统。氢气 (H₂) 作为一种清洁能源载体，是未来低碳能源的重要组成部分。绿色H₂是最清洁的H₂形式，无碳排放，风力或水力发电的电解发电是其生产来源之一。电解可使用三种类型的电解池进行：（1）碱性电解池;（2）质子交换膜电解池；(3) 固体氧化物电解池 (SOECs)。其中SOECs生产H₂的效率最高，但其低法拉第效率和高能源成本限制了H₂作为燃料的大规模采用。在本工作中，来自美国爱达荷国家实验室材料科学与制造工程系的Gorakh Pawar教授团队，对SOECs的关键方面做了最新的综述和展望，包括目前最先进的阳极、阴极和电解质材料，影响法拉第效率的操作和材料参数，以及解决影响SOECs法拉第效率瓶颈的计算模拟技术。在该综述中，作者提出，阴极、阳极和电解质材料的选择都会影响法拉第效率，从而影响电池的性能，只有电池中每个组成部分都100%有效，才能发挥SOECs的优势。工作还提出，电解质材料的主要问题是由于不可忽略的电子传导而导致的电池泄露，从而降低法拉第效率。计算是一种强大的工具，可用于系统研究、分析和理解与电解质内电流泄漏有关的问题。在原子水平上，可以通过密度泛函理论（DFT）研究来了解表面化学性质和电子-空穴迁移率，这与电流泄漏直接相关。通过使用包含电子/空穴对模拟的方法，如从头算分子动力学和eReaxFF。分子动力学 (MD) 研究可用于研究温度对电子/空穴形成以及迁移率和体化学的影响，从而有助于了解影响电池法拉第效率和H₂生成的因素。结合DFT/MD的蒙特卡罗 (MC) 模拟可用于研究更大时间尺度上的缺陷演化和积累。多尺度建模有助于在不同长度尺度解决目前与 SOECs 相关的法拉第效率等问题。最后，将材料基因组计划数据库与机器学习技术和数据分析相结合，将加快研究和探索与 SOECs 相关的新材料的进程，这对科学界大有裨益。

Editorial Summary

Review: Latest progress and perspective of solid oxide electrolysis cells

To reduce global warming, many countries are shifting to sustainable energy production systems. Hydrogen (H₂), as a clean energy carrier, is an important part of the energy mix in a low-carbon energy future. Green H₂ is the cleanest form of H₂, and electrolysis using wind- or hydro-generated electricity is considered to be one of the best green H₂ production sources. Electrolysis can be performed using three types of electrolysis cells: (1) alkaline cells (AECs); (2) proton exchange membrane (PEM) electrolysis cells; (3) solid oxide electrolysis cells (SOECs). SOECs can generate H₂ with the highest efficiency, but its low Faraday efficiency and high energy costs limit the large-scale adoption of H₂ as a fuel. In this work, a group led by Prof. Gorakh Pawar from the Department of Material Science and Manufacturing Engineering, Idaho National Laboratory, outlined the key aspects of SOECs: current state-of-the-art anode, cathode, and electrolyte materials, operational and materials parameters affecting faradaic efficiency, and computational modeling techniques to resolve bottlenecks affecting SOEC faradaic efficiency. In the review, the authors proposed that the selections of materials for the cathode, anode, and electrolyte all affect the Faradaic efficiency, and thus performance of a cell, and each component of the cell need to be 100% effective and efficient to utilize the promising features of SOECs. They also proposed that the main issue with electrolyte materials is current leakage due to a non-negligible electron conduction, which decreases faradaic efficiency. A computational model is a powerful tool that can be used to systematically study, analyze, and understand the problems related to current leakage within electrolytes. On the atomistic level, density functional theory (DFT) studies can be performed to understand the surface chemistries and electron-hole mobility, which is directly related to current leakage. Molecular dynamics (MD) studies can be used to investigate the effect that temperature has on electron/hole formation, as well as mobility and bulk chemistries, by using methods that explicitly include electron/hole pair modeling such as ab initio molecular dynamics (AIMD) and eReaxFF, thereby helping to understand the factors affecting the faradaic efficiency of the cell and H₂ generation. Monte Carlo (MC) simulations in combination with DFT/MD can be used to investigate the defect evolution and accumulation on a larger timescale. Multi-scale modeling is helpful in solving the current problems like faradaic efficiency related to SOECs at different length scales. Lastly, combining the Materials Genome Project database with machine learning techniques and data analytics will accelerate the process of investigating and exploring new materials related to SOECs, which will significantly help the scientific community.