Machine learning methods for liquid crystal research: phases, textures, defects and physical properties
Author:
Affiliation:
1. Infochemistry Scientific Center, ITMO University, Saint-Petersburg, Russia
Abstract
Funder
Ministry of Science and Higher Education of the Russian Federation
Publisher
Royal Society of Chemistry (RSC)
Link
http://pubs.rsc.org/en/content/articlepdf/2024/SM/D3SM01634J
Reference107 articles.
1. Liquid Crystals: Versatile Self-Organized Smart Soft Materials
2. Advanced liquid crystal devices for augmented reality and virtual reality displays: principles and applications
3. Functional Liquid Crystals towards the Next Generation of Materials
4. Liquid Crystalline Systems from Nature and Interaction of Living Organisms with Liquid Crystals
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2. Genetic algorithm for the response of arbitrarily twisted nematic liquid crystals to an applied field;Physical Review E;2024-05-23
3. Machine eye for defects: Machine learning-based solution to identify and characterize topological defects in textured images of nematic materials;Physical Review Research;2024-03-08
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