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RESEARCH PAPER · Advanced Theory and Simulations · 2020

Machine Learning Based Distinguishing between Ferroelectric and Non‐Ferroelectric Polarization–Electric Field Hysteresis Loops

Qicheng Huang, Zhen Hong Fan, Lanqing Hong, Shengliang Cheng, Zhengwei Tan, Guo Tian, Deyang Chen, Zhipeng Hou, Minghui Qin, Min Zeng, Xubing Lu, Guofu Zhou, Xingsen Gao, Jun‐Ming Liu

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Machine Learning Based Distinguishing between Ferroelectric and Non‐Ferroelectric Polarization–Electric Field Hysteresis LoopsOriginalPhysics-based optimization of Landau parameters for ferroelectrics: application to BZT–50BCT4Switching dynamics in organic ferroelectrics1Machine learning assisted prediction of dielectric temperature spectrum of ferroelectrics27Merits and Demerits of Machine Learning of Ferroelectric, Flexoelectric, and Electrolytic Properties of Ceramic Materials10Review of the opportunities and limitations for powder-based high-throughput solid-state processing of advanced functional ceramics36Machine Learning-Guided Cycle Life Prediction for Electrochromic Devices Based on Deuterium and Water Mixing Solvent5Machine learning assisted innovative strategy for experimental validation of functional properties of lead-free ceramics8Intelligent Monitoring Technology of Partial Discharge Based on an Integrated Sensing–Memory–Computation System6LiNbO 3 and ZnO–Ni multilayer thin films as hybrid metamaterials towards tunable properties0Interfacial coupling-driven enhancement of capacitance in MnFe₂O₄/NiO nanocomposites synthesized via sol–gel auto-combustion3Predicting the electric field-driven evolving hysteresis loop of the NBT ferroelectric via hybrid machine learning and mathematical modelling0Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization0

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  1. Physics-based optimization of Landau parameters for ferroelectrics: application to BZT–50BCT

    Modelling and Simulation in Materials Science and Engineering · 2021-08-03

    Oscar A. Torres-Matheus, R. Edwin Garcı́a, Catherine M. Bishop

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  2. Switching dynamics in organic ferroelectrics

    Elsevier eBooks · 2022-01-01

    Tim D. Cornelissen, Martijn Kemerink

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  3. Machine learning assisted prediction of dielectric temperature spectrum of ferroelectrics

    Journal of Advanced Ceramics · 2023-07-18

    Jingjin He, Changxin Wang, Junjie Li, Chuanbao Liu, Dezhen Xue, Jiangli Cao, Yanjing Su, Lijie J. Qiao, Turab Lookman, Yang Bai

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  4. Merits and Demerits of Machine Learning of Ferroelectric, Flexoelectric, and Electrolytic Properties of Ceramic Materials

    Materials · 2024-05-23

    Kyuichi Yasui

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  5. Review of the opportunities and limitations for powder-based high-throughput solid-state processing of advanced functional ceramics

    Journal of the European Ceramic Society · 2024-07-27

    Kyle Grant Webber, Oliver Clemens, Vincenzo Buscaglia, Barbara Malič, Rajendra Kumar Bordia, Tobias Fey, Udo R. Eckstein

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  6. Machine Learning-Guided Cycle Life Prediction for Electrochromic Devices Based on Deuterium and Water Mixing Solvent

    Micromachines · 2024-08-26

    Yitong Wu, Sifan Kong, Qingxin Yao, Muyun Li, Huayi Lai, Duoyu Sun, Qingyue Cai, Zelin Qiu, Honglong Ning, Yong Zhang

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  7. Machine learning assisted innovative strategy for experimental validation of functional properties of lead-free ceramics

    Materials Chemistry and Physics · 2024-10-04

    Srujan Sapkal, Balasubramanian Kandasubramanian, Himanshu Sekhar Panda

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  8. Intelligent Monitoring Technology of Partial Discharge Based on an Integrated Sensing–Memory–Computation System

    Langmuir · 2025-02-22

    Zhao Yú, Jia‐Wei Zhang, Fouad Belhora, Abdеlowahеd Hajjaji, Chen Lu Song

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  9. LiNbO 3 and ZnO–Ni multilayer thin films as hybrid metamaterials towards tunable properties

    RSC Advances · 2026-01-01

    Nirali A. Bhatt, Lizabeth J. Quigley, Juanjuan Lu, Claire A. Mihalko, Aleem M. Siddiqui, Raktim Sarma, Haiyan Wang

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  10. Interfacial coupling-driven enhancement of capacitance in MnFe₂O₄/NiO nanocomposites synthesized via sol–gel auto-combustion

    Journal of Sol-Gel Science and Technology · 2026-02-18

    Muhammad Amjad, Ismat Bibi, Munawar Iqbal, Shagufta Kamal, Ghulam Mustafa, Shazia Nouren, Babar Taj, Nosheen Nazar, Norah Muhammad Alwadai, Arif Nazir

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  11. Predicting the electric field-driven evolving hysteresis loop of the NBT ferroelectric via hybrid machine learning and mathematical modelling

    Physica B Condensed Matter · 2026-06-17

    Abhinav Kumar, Amit Kumar, Sumit Kumar Mev, Amit Kumar, Sumit Kumar Mev, Saket Asthana

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  12. Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

    Advanced Electronic Materials · 2026-07-29

    Faizan Ali, David Lehninger, Florencio Sánchez, Ignasi Fina

    Read original paper ↗ ·
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