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RESEARCH PAPER · Composites Science and Technology · 2023

A predictive model for the relationship between processing conditions and properties of thermoplastic vulcanizates (TPVs) via machine learning

Xinhu Xu, Lifeng Ma, Hui Nan Guo, Chang‐Ping Feng, YanSong Wang, Zhian Mao

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A predictive model for the relationship between processing conditions and properties of thermoplastic vulcanizates (TPVs) via machine learningOriginalConstruct the relationship of the interface structure-properties for TPV via micromechanical method based on cohesive zone model9Design a special micro-perforated plate coupled with the labyrinth metamaterial with improved sound absorption properties at medium and low frequencies3Multidisciplinary design of door inner belt weatherstrip for simultaneous reduction of wind noise and squeaking in electric vehicles5Predicting Natural Rubber Crystallinity by a Novel Machine Learning Algorithm Based on Molecular Dynamics Simulation Data19Self-constructed strategy-based reinforcement LSTM approach for fiber-reinforced polymer non-linear degradation performance analysis12Fabrication of High-Performance Thermoplastic Vulcanizate (Tpv) Composites Filled with Carbon Black Based on Hydrogenated Acrylonitrile Butadiene Rubber and Thermoplastic Polyester Elastomer0Construct of heterogeneous crosslinked networks and the reversible bonds for TPV toward the combination of excellent reinforcement and extensibility9The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing37Dynamic modeling and vibration control optimization of a rotating hollow beam with ESACLD treatment7Prevention of Leakage in Machine Learning Prediction for Polymer Composite Properties16Enhancing Injection Molding Optimization for SFRPs Through Multi‐Fidelity Data‐Driven Approaches Incorporating Prior Information in Limited Data Environments7Water Absorption Behavior of Dual-Sponge Structure Sealing Elastomers Assisted by Machine Learning8Electrical insulation and dielectric properties of aramid fiber reinforced epoxy composites under mechanical stress28Morphology and properties of carbon black‐filled thermoplastic vulcanizate ( TPV ) composites based on hydrogenated acrylonitrile butadiene rubber and thermoplastic polyester elastomer5From processing to properties: Enhancing machine learning models with microstructural information in polymer nanocomposites20A New Strategy for the Preparation of Fully Biobased and Biodegradable Polylactic Acid with Both High Rigidity and Flexibility29Development and optimization of an artificial neural network (ANN) model for predicting the cadmium fixation efficiency of biochar in soil9Micromechanical insights for enhancing the rebound resilience of sealing materials based on TPV8Influence of Rubber Distribution and Shape on Properties of Thermoplastic Vulcanizate: Finite Element Modeling0Machine Learning Approaches in Polymer Science: Progress and Fundamental for a New Paradigm86Microstructure-Driven mechanical behavior and recovery mechanism of thermoplastic vulcanizates: A multi-scale analysis9Machine learning-driven constructing relationship between processing and mechanical properties of TPV: A view of one stacking model4Investigation on selective distribution of carbon nanotubes in thermoplastic vulcanizate (TPV) nanocomposites based on HNBR/TPEE and property optimization: road to functionalized applications4Machine learning in polymer science: A new lens for physical and chemical exploration35Study on stress transfer mechanism of thermoplastic vulcanizate considering nonlinear viscoelastic interphase: A multiscale modeling approach1Adding machine learning to the polymer reaction engineering toolbox13Machine Learning‐Driven Prediction of Polypropylene Alloy Properties: A Bayesian Network– XGBoost Framework Robust to Missing Data0Machine Learning‐Guided Analysis of Rebound Mechanisms in Thermoplastic Vulcanizates via Automated Co‐Simulation0Stimuli-Responsive Smart Polymer: A Precise Era with Artificial Intelligence and Machine Learning8Physics-informed dual neural networks for predicting the complex tensile behavior of rubber composites0Interpretable machine learning for tensile strength prediction and processing optimization of thermoplastic vulcanizates0Two-Stage Machine Learning for Thermo-Mechanical Properties Optimization of Carbon-Filled Polyimide Composites0

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  1. Construct the relationship of the interface structure-properties for TPV via micromechanical method based on cohesive zone model

    Polymer · 2023-09-21

    Lifeng Ma, Chunxiao Li, Congchao Liu

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  2. Design a special micro-perforated plate coupled with the labyrinth metamaterial with improved sound absorption properties at medium and low frequencies

    Modern Physics Letters B · 2023-09-22

    Xiuyu Li, Lifeng Ma, Jiajia Hu, Zhiyuan Zhu

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  3. Multidisciplinary design of door inner belt weatherstrip for simultaneous reduction of wind noise and squeaking in electric vehicles

    Materials Today Communications · 2023-11-10

    Sanghyun Lee, Bumyong Yoon, Seung-Hyun Cho, Sanghyun Lee, Kyoung Min Hong, Jonghwan Suhr

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  4. Predicting Natural Rubber Crystallinity by a Novel Machine Learning Algorithm Based on Molecular Dynamics Simulation Data

    Langmuir · 2023-11-20

    Qionghai Chen, Zhanjie Liu, Yongdi Huang, Anwen Hu, Wanhui Huang, Liqun Zhang, Lihong Cui, Jun Liu

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  5. Self-constructed strategy-based reinforcement LSTM approach for fiber-reinforced polymer non-linear degradation performance analysis

    Composites Science and Technology · 2023-12-31

    Zhicen Song, Yunwen Feng, Cheng Jiang Lu, Jiaqi Liu, Wei-Huang Pan

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  6. Fabrication of High-Performance Thermoplastic Vulcanizate (Tpv) Composites Filled with Carbon Black Based on Hydrogenated Acrylonitrile Butadiene Rubber and Thermoplastic Polyester Elastomer

    SSRN Electronic Journal · 2024-01-01

    Ziwen Cui, Yuanrong Jing, Lianxu Liu, Yingjun Liu, Aihua Du

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  7. Construct of heterogeneous crosslinked networks and the reversible bonds for TPV toward the combination of excellent reinforcement and extensibility

    European Polymer Journal · 2024-01-19

    Longhao Li, Lifeng Ma, Yansong Wang, Chunxiao Li, Chengyuan He, Xiuyu Li

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  8. The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing

    Composites Science and Technology · 2024-02-24

    Paulina Wiśniewska, Elnaz Movahedifar, Krzysztof Formela, Mohannad Zeyad Naser, Henri Vahabi, Mohammad Reza Saeb

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  9. Dynamic modeling and vibration control optimization of a rotating hollow beam with ESACLD treatment

    Thin-Walled Structures · 2024-03-05

    Yongxin Zhang, Liang Li, Dingguo Zhang, Wei‐Hsin Liao

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  10. Prevention of Leakage in Machine Learning Prediction for Polymer Composite Properties

    Journal of Chemical Information and Modeling · 2024-04-20

    Hajime Shimakawa, Akiko Kumada, Masahiro Sato

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  11. Enhancing Injection Molding Optimization for SFRPs Through Multi‐Fidelity Data‐Driven Approaches Incorporating Prior Information in Limited Data Environments

    Advanced Theory and Simulations · 2024-05-25

    Hugon Lee, Mingyu Lee, Jiyoung Jung, Ikjin Lee, Seunghwa Ryu

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  12. Water Absorption Behavior of Dual-Sponge Structure Sealing Elastomers Assisted by Machine Learning

    ACS Applied Polymer Materials · 2024-05-30

    Wentong Lu, Hao Tian, Yan Liu, Yiyao Zhu, Peilong Zhou, Jincheng Wang, Long Li, Jianhua Xiao

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  13. Electrical insulation and dielectric properties of aramid fiber reinforced epoxy composites under mechanical stress

    Composites Science and Technology · 2024-06-28

    Yifang Wang, Boxue X. Du, Yun Chen, Xin Lin, Xiaoxiao Kong

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  14. Morphology and properties of carbon black‐filled thermoplastic vulcanizate ( TPV ) composites based on hydrogenated acrylonitrile butadiene rubber and thermoplastic polyester elastomer

    Journal of Applied Polymer Science · 2024-09-09

    Ziwen Cui, Yuanrong Jing, Lianxu Liu, Yingjun Liu, Aihua Du

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  15. From processing to properties: Enhancing machine learning models with microstructural information in polymer nanocomposites

    Composites Communications · 2024-09-11

    Zi-Long Wan, Siyuan Chen, Xueyang Feng, Zhao‐Yan Sun

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  16. A New Strategy for the Preparation of Fully Biobased and Biodegradable Polylactic Acid with Both High Rigidity and Flexibility

    Macromolecules · 2024-09-26

    Yi Han, Nanying Ning, Zhao Wang, Liqun Zhang

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  17. Development and optimization of an artificial neural network (ANN) model for predicting the cadmium fixation efficiency of biochar in soil

    Journal of environmental chemical engineering · 2024-09-26

    Yifan Wang, Liang Xu, Jianen Li, Yan Li, Yutong Zhou, Wei Liu, Yunhe Ai, Bo Zhang, Bo Zhang, Jianhua Qu, Ying Zhang

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  18. Micromechanical insights for enhancing the rebound resilience of sealing materials based on TPV

    Polymer · 2024-09-30

    Chengyuan He, Lifeng Ma, Xiaolong Xie, Longhao Li, Xi Kang

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  19. Influence of Rubber Distribution and Shape on Properties of Thermoplastic Vulcanizate: Finite Element Modeling

    Current Materials Science · 2024-10-03

    Longhao Li, Lifeng Ma, Congchao Liu, Jingyi Wei

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  20. Machine Learning Approaches in Polymer Science: Progress and Fundamental for a New Paradigm

    SmartMat · 2025-01-09

    Chunhui Xie, Haoke Qiu, Lu Liu, Yang You, Hongfei Li, Yunqi Li, Zhao‐Yan Sun, Jiaping Lin, Lijia An

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  21. Microstructure-Driven mechanical behavior and recovery mechanism of thermoplastic vulcanizates: A multi-scale analysis

    Composites Part A Applied Science and Manufacturing · 2025-02-05

    Chunxiao Li, Lifeng Ma, Zhiyuan Zhu, Longhao Li, Chengyuan He

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  22. Machine learning-driven constructing relationship between processing and mechanical properties of TPV: A view of one stacking model

    Polymer · 2025-04-07

    Zhi Long Zhang, Lifeng Ma, Longhao Li, Chengyuan He, Chunxiao Li

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  23. Investigation on selective distribution of carbon nanotubes in thermoplastic vulcanizate (TPV) nanocomposites based on HNBR/TPEE and property optimization: road to functionalized applications

    Polymer · 2025-04-30

    Ziwen Cui, Yuanrong Jing, Yingjun Liu, Aihua Du

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  24. Machine learning in polymer science: A new lens for physical and chemical exploration

    Progress in Materials Science · 2025-07-29

    Xiao-Qin Cao, Yongqing Zhang, Zhenghua Sun, Hongyao Yin, Yujun Feng

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  25. Study on stress transfer mechanism of thermoplastic vulcanizate considering nonlinear viscoelastic interphase: A multiscale modeling approach

    Composite Structures · 2025-09-08

    Longhao Li, Lifeng Ma, Chunxiao Li, Chengyuan He, Xiuyu Li

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  26. Adding machine learning to the polymer reaction engineering toolbox

    Progress in Polymer Science · 2025-09-25

    Kiarash Farajzadehahary, Shaghayegh Hamzehlou, Nicholas Ballard

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  27. Machine Learning‐Driven Prediction of Polypropylene Alloy Properties: A Bayesian Network– XGBoost Framework Robust to Missing Data

    Journal of Polymer Science · 2025-11-22

    Shaojie Zheng, Jijiang Hu, Zhen Yao

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  28. Machine Learning‐Guided Analysis of Rebound Mechanisms in Thermoplastic Vulcanizates via Automated Co‐Simulation

    Journal of Applied Polymer Science · 2026-03-21

    Yiming Sun, Lifeng Ma, Chengyuan He, Xi Kang, Jufeng Lv

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  29. Stimuli-Responsive Smart Polymer: A Precise Era with Artificial Intelligence and Machine Learning

    Precision Chemistry · 2026-03-27

    Tamanna Pradhan, Subhajit Das, Khokan Mondal, Subrata Dolui

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  30. Physics-informed dual neural networks for predicting the complex tensile behavior of rubber composites

    Polymer · 2026-05-26

    Minhan Song, Wei Wang, Chong Qiang Sun

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  31. Interpretable machine learning for tensile strength prediction and processing optimization of thermoplastic vulcanizates

    European Polymer Journal · 2026-06-29

    Chunxue Li, Meiqing Shi, Feiping Zhao, Yanjie Liang, Liyuan Zhang, Yan Xu, Qingwei Wang, Liyuan Chai

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  32. Two-Stage Machine Learning for Thermo-Mechanical Properties Optimization of Carbon-Filled Polyimide Composites

    Materials · 2026-08-28

    Yu Zhang, Wenting Zhao, Luling He, Qiong Li, MA Wei-bin, Tongle Xu, Peng Ding

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