Chinese Journal of Liquid Crystals and Displays, Volume. 37, Issue 8, 972(2022)
High-throughput blue phase liquid crystal recognition based on convolutional neural network
With the development of liquid crystal display technology, blue phase liquid crystal has entered the researcher’s field of vision due to its advantages and has attracted continuous attention. However, there are many difficulties in its research and practical application. For example, the blue phase only exists in a very narrow temperature range, so the rapid identification of the blue phase liquid crystal and the rapid calculation of blue phase temperature range are extremely important. In this paper, a model trained by a machine learning algorithm combined with Labview software can realize the rapid recognition of the liquid crystal phase state and the rapid reading and calculation of the blue phase temperature range. During the experiment, the overall recognition accuracy of 159 840 sample point phase images was above 93%. The research results of this paper can help to effectively identify the blue phase, quickly obtain the blue phase temperature range, and quickly screen the applicable blue phase liquid crystal formula, so as to improve the research efficiency of blue phase materials and to promote their application in display devices.
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Ya-qian ZHANG, Yong-feng CUI, Hao WANG, Wan-li HE, Lei ZHANG, Zhou YANG, Hui CAO, Dong WANG, Yu-zhan LI. High-throughput blue phase liquid crystal recognition based on convolutional neural network[J]. Chinese Journal of Liquid Crystals and Displays, 2022, 37(8): 972
Category: Research Articles
Received: Dec. 1, 2021
Accepted: --
Published Online: Aug. 15, 2022
The Author Email: Wan-li HE (hewanli@mater.ustb.edu.cn)