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Liquid Crystals Volume 47, 2020 - Issue 3
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Article

Predicting molecular ordering in a binary liquid crystal using machine learning

Takuya InokuchiAdvanced Analytical Science Laboratories, Research & Development Headquarters, Lion Corporation, Tokyo, JapanCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0003-1872-6734View further author information
ORCID Icon,
Ryosuke OkamotoDepartment of Mechanical Engineering, Kindai University, Osaka, JapanView further author information
&
Noriyoshi AraiDepartment of Mechanical Engineering, Keio University, Yokohama, JapanCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-5254-7329View further author information
ORCID Icon
Pages 438-448 | Received 15 Apr 2019, Accepted 12 Aug 2019, Published online: 27 Aug 2019

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Saeed Akbarishandiz, Soumya Ray, Fei Zhou, Xiao Chen & Joao Maia. (2024) Machine learning of performance space mapping for the DPD simulation of drug delivery to endothelial cells. Molecular Simulation 0:0, pages 1-9.
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Ingo Dierking, Jason Dominguez, James Harbon & Joshua Heaton. (2023) Testing different supervised machine learning architectures for the classification of liquid crystals. Liquid Crystals 50:7-10, pages 1461-1477.
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Ingo Dierking, Jason Dominguez, James Harbon & Joshua Heaton. (2023) Classification of liquid crystal textures using convolutional neural networks. Liquid Crystals 50:7-10, pages 1526-1540.
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Kazutaka Yamada & Noriyoshi Arai. Cholesteric liquid crystal phase variations within nanotubes: an in-depth analysis of the influences of twist radius and molecular pitch. Liquid Crystals 0:0, pages 1-11.
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Piyushkumar Panchal, Bansi Shingala, Sanketsinh Thakor, Prince Jain, Chandan R. Vaja, Anand Joshi, K. N. Shah, V. A. Rana & Jaivik Pathak. XGBoost Regression Analysis of Dielectric Properties of Epoxy Resin with Inorganic Hybrid Nanofillers. Journal of Macromolecular Science, Part B 0:0, pages 1-17.
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Atul D Watpade, Sanketsinh Thakor, Prince Jain, Prajna P. Mohapatra, Chandan R. Vaja, Anand Joshi, Dimple V. Shah & Mohammad Tariqul Islam. (2024) Comparative analysis of machine learning models for predicting dielectric properties in MoS2 nanofiller-reinforced epoxy composites. Ain Shams Engineering Journal 15:6, pages 102754.
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Anastasiia Piven, Darina Darmoroz, Ekaterina Skorb & Tetiana Orlova. (2024) Machine learning methods for liquid crystal research: phases, textures, defects and physical properties. Soft Matter 20:7, pages 1380-1391.
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Kaihua Zhang, Xiangrui Gong & Ying Jiang. (2024) Machine Learning in Soft Matter: From Simulations to Experiments. Advanced Functional Materials.
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Rebecca Betts & Ingo Dierking. (2024) Possibilities and limitations of convolutional neural network machine learning architectures in the characterisation of achiral orthogonal smectic liquid crystals. Soft Matter.
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Rebecca Betts & Ingo Dierking. (2023) Machine learning classification of polar sub-phases in liquid crystal MHPOBC. Soft Matter 19:39, pages 7502-7512.
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Gülnur Önsal, Onur Uğurlu, Ümit H. Kaynar & Deniz Türsel Eliiyi. (2023) Minimization of the threshold voltage parameter of the co-doped ZnO doped liquid crystals by machine learning algorithms. Scientific Reports 13:1.
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Tetiana Orlova, Anastasiia Piven, Darina Darmoroz, Timur Aliev, Tamer Mahmoud Tamer Abdel Razik, Anton Boitsev, Natalia Grafeeva & Ekaterina Skorb. (2023) Machine learning for soft and liquid molecular materials. Digital Discovery 2:2, pages 298-315.
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Pelin Yildirim Taser, Gulnur Onsal & Onur Ugurlu. (2022) Comparison of experimental measurements and machine learning predictions of dielectric constant of liquid crystals. Bulletin of Materials Science 46:1.
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Erika I. Barcelos, Shaghayegh Khani, Mônica F. Naccache & Joao Maia. (2022) Supervised learning for accurate mesoscale simulations of suspension flow in wall-bounded geometries. Physics of Fluids 34:5.
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Hiroaki Tsujinoue, Takuma Nozawa & Noriyoshi Arai. (2020) Cylindrical defect structures formed by chiral nematic liquid crystals in quasi-one-dimensional systems. Physical Chemistry Chemical Physics 22:29, pages 16896-16904.
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