[EPp1-3]Research on High-Performance Electrophoretic Display Materials Based on Machine Learning
*Yanjun Zhang1, Yuanhao Feng1, Jian Jin1, Wanlong Guo1, Zihao Wang1, Jujian Fu1, Yuan Ding1, Bojia Lyu1,2(1. Shanghai Tianma Microelectronics Co., Ltd (China), 2. Shanghai Jiao Tong University (China))
Keywords:
machine learning,electrophoretic display,material development,GRU
In order to improve the efficiency and shorten the cycle, this paper proposes a method of developing high-performance electrophoretic display materials based on machine learning. Experimental results indicate that the GRU model can effectively capture the performance variations under different conditions, validating the potential application of machine learning algorithms in the development of electrophoretic display materials.