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通过机器学习引导的气体进化电极泡失活的发现

Jack R Lake¹, Simon Rufer¹, Jim James²

¹Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA. varanasi@mit.edu.

|October 8, 2024

概括

电化学气泡降低了气体演变电极的性能. 这项研究表明,使用表面工程和机器学习,无活化更接近直接接触泡区域,而不是整个预测区域.

科学领域:

电化学电化学电化学
表面科学是一门学科.
材料科学材料科学材料科学

背景情况:

电化学气泡会对气体演变电极性能产生不利影响.
关于泡诱导的失活程度及其演变的理解有限.
当前的模型通常基于整个投射的电极面积来估计失活.

研究的目的:

为了研究由氧气演变引起的电极失活.
分析表面工程对气泡形成和电极失活的影响.
开发一种更准确的方法来估计泡诱导的电极失活.

主要方法:

利用表面工程来控制氧气进化过程中的泡形成.
采用基于机器学习的基于图像的泡检测方法.
分析大量的实验数据来量化气泡冲击和电极失活.

主要成果:

电极不活化并不能准确地用整个预测面积来表示.
表面工程电极表现出小气泡冲击,投射面积高,直接气泡接触低.
一种新的方法提供了更准确的估计泡无活化,与直接泡接触面积相关联.

结论:

在整个投射电极区域内假设无活化是一个差的近似.
表面工程策略可以通过控制泡动态来减轻无活化.
准确评估不活化需要考虑直接接触到气泡的区域.

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