Toward the Prediction of Electrochromic Properties of WO<sub>3</sub> Films: Combination of Experimental and Machine Learning Approaches
Brandon Faceira, Lionel Teulé‐Gay, Gian‐Marco Rignanese, Aline Rougier
Abstract
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 LixWO3 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.