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RESEARCH ARTICLE · Liquid Crystals · 2019

Predicting molecular ordering in a binary liquid crystal using machine learning

Takuya Inokuchi, Ryosuke Okamoto, Noriyoshi Arai

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Predicting molecular ordering in a binary liquid crystal using machine learningOriginalCylindrical defect structures formed by chiral nematic liquid crystals in quasi-one-dimensional systems6COUPLING MACHINE LEARNING AND MESOSCALE MODELING TO STUDY THE FLOW OF SEMI-DENSE AND DENSE SUSPENSIONS0Supervised learning for accurate mesoscale simulations of suspension flow in wall-bounded geometries4Classification of liquid crystal textures using convolutional neural networks18Comparison of experimental measurements and machine learning predictions of dielectric constant of liquid crystals20Machine learning classification of polar sub-phases in liquid crystal MHPOBC19Machine learning for soft and liquid molecular materials21The Applications of Machine Learning in the Study of Liquid Crystals: A Review2Testing different supervised machine learning architectures for the classification of liquid crystals16Minimization of the threshold voltage parameter of the co-doped ZnO doped liquid crystals by machine learning algorithms8Machine learning methods for liquid crystal research: phases, textures, defects and physical properties18Possibilities and limitations of convolutional neural network machine learning architectures in the characterisation of achiral orthogonal smectic liquid crystals11Machine Learning in Soft Matter: From Simulations to Experiments34Comparative analysis of machine learning models for predicting dielectric properties in MoS2 nanofiller-reinforced epoxy composites70Automatic Testing Technology of BTB Liquid Crystal Display Advanced Fault Detection in Smart Meter for Smart Machine1Machine learning of performance space mapping for the DPD simulation of drug delivery to endothelial cells1Cholesteric liquid crystal phase variations within nanotubes: an in-depth analysis of the influences of twist radius and molecular pitch1Texture identification in liquid crystal-protein droplets using evaporative drying, generalized additive modeling, and K-means Clustering13XGBoost Regression Analysis of Dielectric Properties of Epoxy Resin with Inorganic Hybrid Nanofillers21Recent Advances in Ocular Drug Delivery: Insights into Lyotropic Liquid Crystals21Comprehensive study of spinel nanoparticles using experimental, theoretical and machine learning methods25Transformer-Driven Classification of a Nature-Born Complex Dataset Via Reference-Based Data Embedding0Unlocking the potential of liquid crystals as phase change materials for thermal energy storage12Convolutional neural network analysis of optical texture patterns in liquid-crystal skyrmions5Machine Learning in nanoarchitectonics24A Holistic Integration of Machine Learning for Selecting Optimum Ratio of Nanoparticles in Epoxy-Based Nanocomposite Insulators5Machine learning in liquid crystal research: Accelerating discovery, optimization, and applications2Machine Learning-Assisted Prediction of Dielectric Properties of Epoxy Composites with PMMA/MWCNT Hybrid Nano-Fillers0Artificial Intelligence as the Next Visionary in Liquid Crystal Research3Data-Driven Prediction of Epoxy Nanocomposite Insulator Fabrication for Enhanced Breakdown Voltage Performance0

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  1. Cylindrical defect structures formed by chiral nematic liquid crystals in quasi-one-dimensional systems

    Physical Chemistry Chemical Physics · 2020

    Hiroaki Tsujinoue, Takuma Nozawa, Noriyoshi Arai

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  2. COUPLING MACHINE LEARNING AND MESOSCALE MODELING TO STUDY THE FLOW OF SEMI-DENSE AND DENSE SUSPENSIONS

    Venue not supplied by source · 2022

    ERIKA IMADA BARCELOS

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  3. Supervised learning for accurate mesoscale simulations of suspension flow in wall-bounded geometries

    Physics of Fluids · 2022

    Erika I. Barcelos, Shaghayegh Khani, Mônica F. Naccache, João Manuel Maia

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  4. Classification of liquid crystal textures using convolutional neural networks

    Liquid Crystals · 2022

    Ingo Dierking, Jason Dominguez, James Harbon, Joshua Heaton

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  5. Comparison of experimental measurements and machine learning predictions of dielectric constant of liquid crystals

    Bulletin of Materials Science · 2022

    Pelin Yıldırım Taşer, Gülnur Önsal, Onur Uğurlu

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  6. Machine learning classification of polar sub-phases in liquid crystal MHPOBC

    Soft Matter · 2023

    Rebecca Betts, Ingo Dierking

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  7. Machine learning for soft and liquid molecular materials

    Digital Discovery · 2023

    Tetiana Orlova, Anastasiia O. Piven, Darina D. Darmoroz, Timur A. Aliev, Tamer Mahmoud Tamer Abdel Razik, Anton A. Boitsev, Natalia Grafeeva, Екатерина Владимировна Скорб

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  8. The Applications of Machine Learning in the Study of Liquid Crystals: A Review

    Journal of Student Research · 2023

    Dmitri Kalinin, Jason Abercrombie

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  9. Testing different supervised machine learning architectures for the classification of liquid crystals

    Liquid Crystals · 2023

    Ingo Dierking, Jason Dominguez, James Harbon, Joshua Heaton

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  10. Minimization of the threshold voltage parameter of the co-doped ZnO doped liquid crystals by machine learning algorithms

    Scientific Reports · 2023

    Gülnur Önsal, Onur Uğurlu, Ümit H. Kaynar, Deniz Türsel Eliiyi

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  11. Machine learning methods for liquid crystal research: phases, textures, defects and physical properties

    Soft Matter · 2024

    Anastasiia O. Piven, Darina D. Darmoroz, Екатерина Владимировна Скорб, Tetiana Orlova

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  12. Possibilities and limitations of convolutional neural network machine learning architectures in the characterisation of achiral orthogonal smectic liquid crystals

    Soft Matter · 2024

    Rebecca Betts, Ingo Dierking

    Read original paper ↗ ·

  13. Machine Learning in Soft Matter: From Simulations to Experiments

    Advanced Functional Materials · 2024

    Kaihua Zhang, Xiangrui Gong, Ying Lan Jiang

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  14. Comparative analysis of machine learning models for predicting dielectric properties in MoS2 nanofiller-reinforced epoxy composites

    Ain Shams Engineering Journal · 2024

    Atul D. Watpade, Sanketsinh Thakor, Prince Jain, Prajna P. Mohapatra, Chandan R. Vaja, Anand Y. Joshi, Dimple V. Shah, Mohammad Tariqul Islam

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  15. Automatic Testing Technology of BTB Liquid Crystal Display Advanced Fault Detection in Smart Meter for Smart Machine

    Journal of Electrical Systems · 2024

    Xiujun Du

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  16. Machine learning of performance space mapping for the DPD simulation of drug delivery to endothelial cells

    Molecular Simulation · 2024

    Saeed Akbarishandiz, Soumya Ray, Fei Zhou, Xiao Chen, João Manuel Maia

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  17. Cholesteric liquid crystal phase variations within nanotubes: an in-depth analysis of the influences of twist radius and molecular pitch

    Liquid Crystals · 2024

    Kazutaka YAMADA, Noriyoshi Arai

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  18. Texture identification in liquid crystal-protein droplets using evaporative drying, generalized additive modeling, and K-means Clustering

    The European Physical Journal E · 2024

    Anusuya Pal, Amalesh Gope

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  19. XGBoost Regression Analysis of Dielectric Properties of Epoxy Resin with Inorganic Hybrid Nanofillers

    Journal of Macromolecular Science Part B · 2024

    Piyushkumar Panchal, Bansi Shingala, Sanketsinh Thakor, Prince Jain, Chandan R. Vaja, Anand Y. Joshi, Karan Shah, Vipinchandra A. Rana, Jaivik Pathak

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  20. Recent Advances in Ocular Drug Delivery: Insights into Lyotropic Liquid Crystals

    Pharmaceuticals · 2024

    Samer Adwan, Madeiha Qasmieh, Faisal Al‐Akayleh, Ahmed S.A. Ali Agha

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  21. Comprehensive study of spinel nanoparticles using experimental, theoretical and machine learning methods

    Physica B Condensed Matter · 2024

    Poonam Sharma, Mitesh B. Solanki, Sanketsinh Thakor, Prince Jain, Ajay Zapadiya, Dimple V. Shah, Chandan R. Vaja

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  22. Transformer-Driven Classification of a Nature-Born Complex Dataset Via Reference-Based Data Embedding

    SSRN Electronic Journal · 2025

    Kyung Hyun Ahn, Young Jin Lee

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  23. Unlocking the potential of liquid crystals as phase change materials for thermal energy storage

    Energy Materials · 2025

    Rahul Bapusaheb Karyappa, Jiayao Cheng, Charissa Lixuan Ho, Suxi Wang, Warinton Thitsartarn, Junhua Kong, Dan Kai, Beng Hoon Tan, Pei Wang, Zhengyao Qu, Xian Jun Loh, Jianwei Xu, Qiang Zhu

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  24. Convolutional neural network analysis of optical texture patterns in liquid-crystal skyrmions

    Scientific Reports · 2025

    J. Terroa, Mykola Tasinkevych, C. S. Dias

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  25. Machine Learning in nanoarchitectonics

    Advances in Colloid and Interface Science · 2025

    Bogdan V. Parakhonskiy, Junnan Song, André G. Skirtach

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  26. A Holistic Integration of Machine Learning for Selecting Optimum Ratio of Nanoparticles in Epoxy-Based Nanocomposite Insulators

    Processes · 2025

    Abubakar Siddique, Muhammad Usama Shahid, Laraib Akram, Waseem Aslam, Kholod D. Alsufiani

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  27. Machine learning in liquid crystal research: Accelerating discovery, optimization, and applications

    Next research. · 2025

    Raj Kumar Khan, A.K. Verma

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  28. Machine Learning-Assisted Prediction of Dielectric Properties of Epoxy Composites with PMMA/MWCNT Hybrid Nano-Fillers

    Smart innovation, systems and technologies · 2026

    Sanketsinh Thakor, Prince Jain, Payel Deb, Anand Y. Joshi, Unnati Joshi

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  29. Artificial Intelligence as the Next Visionary in Liquid Crystal Research

    Advanced Functional Materials · 2026

    Mert Orhan Astam, Ouassim L'Karkouri, Danqing Liu

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  30. Data-Driven Prediction of Epoxy Nanocomposite Insulator Fabrication for Enhanced Breakdown Voltage Performance

    International Conference on Robotics and Automation in Industry (ICRAI) · 2026

    Abubakar Siddique, Sonia Bibi, Muhammad Abdullah, Umar Fayyaz, Abdullah Abid

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