Toward the Prediction of Electrochromic Properties of WO3 Films: Combination of Experimental and Machine Learning Approaches,The Journal of Physical Chemistry Letters

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Toward the Prediction of Electrochromic Properties of WO3 Films: Combination of Experimental and Machine Learning Approaches
The Journal of Physical Chemistry Letters ( IF 4.8 ) Pub Date : 2022-08-23 , DOI: 10.1021/acs.jpclett.2c02248
Brandon Faceira ₁ , Lionel Teule-Gay ₁ , Gian-Marco Rignanese ₂ , Aline Rougier ₁

Affiliation

WO₃ is the state of the art of electrochromic oxide materials finding technological application in smart windows. In this work, a set of WO₃ thin films were deposited by magnetron sputtering by varying total pressure, oxygen partial pressure, and power. On each film two properties were measured, the electrochemical reversibility and the blue color persistence of Li_xWO₃ films in simulated ambient conditions. With the help of machine learning, prediction maps for such electrochromic properties, namely, color persistence and reversibility, were designed. High-performance WO₃ films were targeted by a global score which is the product of these two properties. The combined approach of experimental measurements and machine learning led to a complete picture of electrochromic properties depending of sputtering parameters providing an efficient tool in regards to time saving.

中文翻译：

对 WO3 薄膜电致变色性能的预测：实验和机器学习方法的结合

WO ₃是在智能窗户中找到技术应用的电致变色氧化物材料的最新技术。在这项工作中，通过改变总压、氧分压和功率，通过磁控溅射沉积了一组WO _3薄膜。_{在每个薄膜上测量了两种特性，即 Li x} WO ₃薄膜在模拟环境条件下的电化学可逆性和蓝色持久性。在机器学习的帮助下，设计了这种电致变色特性的预测图，即颜色持久性和可逆性。高性能WO ₃电影的目标是全球得分，这是这两个属性的产物。实验测量和机器学习的组合方法导致了取决于溅射参数的电致变色特性的完整图像，提供了一种节省时间的有效工具。

更新日期：2022-08-23

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