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RESEARCH PAPER · Composites Science and Technology · 2022

An adaptive framework to accelerate optimization of high flame retardant composites using machine learning

Fengqing Chen, Longjie Weng, Jinhe Wang, Pin Chieh Wu, Dianpu Ma, Fei Pan, Peng Ding

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An adaptive framework to accelerate optimization of high flame retardant composites using machine learningOriginalRationalizing Functionalized MXenes as Effective Anchor Materials for Lithium–Sulfur Batteries via First-Principles Calculations30Material genome approach-based design of multi-functional self-curing epoxy resin with intrinsic flame retardancy and ultra-high modulus25Advancing flame retardant prediction: A self-enforcing machine learning approach for small datasets23Rethinking the pathway to sustainable fire retardants87Recent advancements in fire retardant mechanisms of carbon nanotubes, graphene, and fullerene polymeric nanoarchitectures46Assessment of Nano-Imprinting Process in CuZr Amorphous Films Through Combination of Machine Learning and Molecular Dynamics3Accelerated feasible screening of flame-retardant polymeric composites using data-driven multi-objective optimization13XFEM and machine learning combined approach for failure prediction of microcapsules in cement-based self-healing materials13Accelerating the discovery of N-annulated perylene organic sensitizers via an interpretable machine learning model10Machine learning-enabled rational design of organic flame retardants for enhanced fire safety of epoxy resin composites28Machine learning assisted screening of doped metals phosphides electrocatalyst towards efficient hydrogen evolution reaction19Predicting Natural Rubber Crystallinity by a Novel Machine Learning Algorithm Based on Molecular Dynamics Simulation Data19Novel advancements in flame retardant mechanisms of halloysite nanotubes polymeric nanoarchitectures12Machine learning for expediting next-generation of fire-retardant polymer composites43Nanotechnology in Flame Retardancy of Textile7Peak regulation strategies for ground source heat pump demand response of based on load forecasting: A case study of rural building in China26The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing37Improvement the classification of a nanocomposite using nanoparticules based on a meta-analysis study, Recurrent Neural Network and Recurrent Neural Network Monte-Carlo algorithms1Prevention of Leakage in Machine Learning Prediction for Polymer Composite Properties16Improving the classification of a nanocomposite using nanoparticles based on a meta-analysis study, recurrent neural network and recurrent neural network Monte-Carlo algorithms11Data-driven design and green preparation of bio-based flame retardant polyamide composites4Machine Learning in Polymer Research167Deep learning-aided preparation and mechanism revaluation of waste wood lignocellulose-based flame-retardant composites12Design optimization of hybrid bistable symmetric laminate using machine learning2Machine learning-driven molecular generation for accelerated screening of high-performance flame retardants in epoxy resin composites13A machine learning platform for polymer flammability prediction8Active learning-based generative design of halogen-free flame-retardant polymeric composites6Machine learning in polymer science: A new lens for physical and chemical exploration35Ant colony algorithm guided synthesis of flame retardants for enhanced polylactic acid flame retardancy3Flame-retardant coatings: Recent advances in materials, mechanisms, and multifunctional applications12A Hybrid Experimental–Machine Learning Framework for Designing Fire-Resistant Natural Fiber Composites2Data-efficient Machine Learning for Polymer Informatics12Intelligent prediction of fire retardancy and smoke suppression in waste wood composites with a hybrid deep learning model2Machine Learning-assisted Discovery of Multifunctional Coordination in Multicomponent Composites0Using Machine Learning for Green Substitution of Industrial Chemicals: Integrating Functionality, Hazard, and Life Cycle Impact17The paradigm shift of intelligent material design and development for fire safety: progress, challenges, and machine learning2Designing flame retardants for epoxy resins with generative AI for preventing battery thermal runaway propagation13AI-aided de novo molecular design of phosphamide for fire-retardant polylactide with enhanced integrated properties3Siloxane-bridged phosphaphenanthrene-containing imidazole-cured epoxy thermosets with synchronously improve flame retardancy and toughness0Decoding the limiting oxygen index of rigid polyurethane foams via explainable machine learning: Effects of elements, mechanisms and dosage0A mechanistic study on the concentration-dependent pyrolysis behavior of 3D cross-linked epoxy/TPP networks via ReaxFF-MD0

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  1. Rationalizing Functionalized MXenes as Effective Anchor Materials for Lithium–Sulfur Batteries via First-Principles Calculations

    The Journal of Physical Chemistry Letters · 2023-02-23

    Xiaorong Zhu, Ming Ge, Tongming Sun, Xiaolei Yuan, Yafei Li

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  2. Material genome approach-based design of multi-functional self-curing epoxy resin with intrinsic flame retardancy and ultra-high modulus

    Chemical Engineering Journal · 2023-06-15

    Junliang He, Ji Zhou, Jizhen Tian, Shuai Li, Yunfei Gao, Zhengguang Heng, Yang Chen, Huawei Zou, Mei Liang

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  3. Advancing flame retardant prediction: A self-enforcing machine learning approach for small datasets

    Applied Physics Letters · 2023-06-19

    Cheng Yan, Xiang Hua Lin, Xiaming Feng, Hongyu Yang, Patrick F. Mensah, Guoqiang Li

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  4. Rethinking the pathway to sustainable fire retardants

    Exploration · 2023-07-06

    Jiabing Feng, Lei Liu, Yan Zhang, Qingsheng Wang, Hong Yu Liang, Hao Wang, Pingan Song

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  5. Recent advancements in fire retardant mechanisms of carbon nanotubes, graphene, and fullerene polymeric nanoarchitectures

    Journal of Analytical and Applied Pyrolysis · 2023-08-02

    Christopher Igwe Idumah

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  6. Assessment of Nano-Imprinting Process in CuZr Amorphous Films Through Combination of Machine Learning and Molecular Dynamics

    Journal of Electronic Materials · 2023-08-11

    Biju Theruvil Sayed, Mahmoud M. Al-Sakhnini, Asaad A.H. Alzubaidi, Ahmed Hussien Alawadi, Ahmed Jaber Ibrahim, Shavan K. Askar

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  7. Accelerated feasible screening of flame-retardant polymeric composites using data-driven multi-objective optimization

    Computational Materials Science · 2023-09-03

    Fengqing Chen, Zhen Guo, Jinhe Wang, Runhai Ouyang, Dianpu Ma, Pei Gao, Fei Pan, Peng Ding

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  8. XFEM and machine learning combined approach for failure prediction of microcapsules in cement-based self-healing materials

    Construction and Building Materials · 2023-10-02

    Qiao Song, Xianfeng Wang, Fang Yuan, Feng Xing

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  9. Accelerating the discovery of N-annulated perylene organic sensitizers via an interpretable machine learning model

    Journal of Molecular Structure · 2023-10-14

    Yu Zhang, Zhichun Zheng, Fengqing Chen, Minjie Li, Peng Ding, Wencong Lu

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  10. Machine learning-enabled rational design of organic flame retardants for enhanced fire safety of epoxy resin composites

    Composites Communications · 2023-10-18

    Zhongwei Chen, Boran Yang, Nannan Song, Yufan Liu, Yufan Liu, Rong Feng, Xida Zhang, Tingting Chen, Qingwu Zhang, Juncheng Jiang, Tao Chen, Yuan Yu, Lian X. Liu

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  11. Machine learning assisted screening of doped metals phosphides electrocatalyst towards efficient hydrogen evolution reaction

    Molecular Catalysis · 2023-11-04

    Shuyi Cao, Yuhong Luo, Tianhang Li, Jingde Li, Lanlan Wu, Guihua Liu

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  12. 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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  13. Novel advancements in flame retardant mechanisms of halloysite nanotubes polymeric nanoarchitectures

    Polymer-Plastics Technology and Materials · 2023-12-01

    Raphael Stone Odera, Christopher Igwe Idumah, Emmanuel Obumneme Ezeani, Victor Ugochukwu Okpechi, Izuchukwu Odinakachi Madu, Henry Chukwuka Oyeoka, Shedrack C. Ugwu, James Ekuma Ogbu

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  14. Machine learning for expediting next-generation of fire-retardant polymer composites

    Composites Communications · 2023-12-31

    Pooya Jafari, Ruoran Zhang, Siqi Huo, Qingsheng Wang, Jianming Yong, Min Hong, Ravinesh Chand Deo, Hao Wang, Pingan Song

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  15. Nanotechnology in Flame Retardancy of Textile

    Materials horizons · 2024-01-01

    Sayak Nandi, Ishmam Zahin Chowdhury, Sumit Mandal

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  16. Peak regulation strategies for ground source heat pump demand response of based on load forecasting: A case study of rural building in China

    Renewable Energy · 2024-02-02

    Qinglong Meng, Ying’an Wei, Jingjing Fan, Yanbo Li, Fan Zhao, Lei Yu, Hang Sun, Le Jiang, Lingli Yu

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  17. 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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  18. Improvement the classification of a nanocomposite using nanoparticules based on a meta-analysis study, Recurrent Neural Network and Recurrent Neural Network Monte-Carlo algorithms

    Research Square · 2024-04-14

    Rania Loukil, Wejden Gazehi, Mongi Besbes

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  19. 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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  20. Improving the classification of a nanocomposite using nanoparticles based on a meta-analysis study, recurrent neural network and recurrent neural network Monte-Carlo algorithms

    Nanocomposites · 2024-07-08

    Rania Loukil, Wejden Gazehi, Mongi Besbes

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  21. Data-driven design and green preparation of bio-based flame retardant polyamide composites

    Journal of Materials Chemistry A · 2025-01-01

    Christina Schenk, Jose Hobson, Maciej Harańczyk, De‐Yi Wang

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  22. Machine Learning in Polymer Research

    Advanced Materials · 2025-02-09

    Wei Chun Ge, Ramindu De Silva, Yanan Fan, Scott A. Sisson, Martina H. Stenzel

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  23. Deep learning-aided preparation and mechanism revaluation of waste wood lignocellulose-based flame-retardant composites

    International Journal of Biological Macromolecules · 2025-03-03

    Kongjie Gu, Xingying Zhang, Zhiqiang Dong, Hongyun Chen, Manqi Xu, Zhuolin Sun, Shenjie Han, Jieyu Zhang, Youming Yu, Junfeng Hou

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  24. Design optimization of hybrid bistable symmetric laminate using machine learning

    Mechanics of Advanced Materials and Structures · 2025-04-15

    Paulomi Mukherjee, Banamali Sahu, Arunachalakasi Arockiarajan, Shaikh Faruque Ali

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  25. Machine learning-driven molecular generation for accelerated screening of high-performance flame retardants in epoxy resin composites

    Chemical Engineering Journal · 2025-05-19

    Zhongwei Chen, Chunlei He, Kai Wang, Rong Feng, Long Xiang, Ziwei Zuo, Changliang Wang, Xinyuan Yang, Yong Chang Guo, Juncheng Jiang, Yuan Yu

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  26. A machine learning platform for polymer flammability prediction

    Polymer Degradation and Stability · 2025-05-21

    Duy Nhat Phan, Alexander B. Morgan, Lokendra Poudel, Rahul Bhowmik

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  27. Active learning-based generative design of halogen-free flame-retardant polymeric composites

    Journal of Materials Informatics · 2025-05-21

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

    Progress in Materials Science · 2025-07-29

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  29. Ant colony algorithm guided synthesis of flame retardants for enhanced polylactic acid flame retardancy

    European Polymer Journal · 2025-08-04

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  30. Flame-retardant coatings: Recent advances in materials, mechanisms, and multifunctional applications

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  31. A Hybrid Experimental–Machine Learning Framework for Designing Fire-Resistant Natural Fiber Composites

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  32. Data-efficient Machine Learning for Polymer Informatics

    Chinese Journal of Polymer Science · 2025-09-02

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  33. Intelligent prediction of fire retardancy and smoke suppression in waste wood composites with a hybrid deep learning model

    Sustainable materials and technologies · 2025-12-04

    Manqi Xu, Liwen Zhou, Junjie Xia, Shenjie Han, Xingying Zhang, Kongjie Gu, Zhiqiang Dong, Junfeng Hou

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  34. Machine Learning-assisted Discovery of Multifunctional Coordination in Multicomponent Composites

    Chinese Journal of Polymer Science · 2025-12-18

    Zi-Ran Guo, Sen Xue, Lu He, Zi‐Long Xie, Tian-Hao Yang, Qiang Fu

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  35. Using Machine Learning for Green Substitution of Industrial Chemicals: Integrating Functionality, Hazard, and Life Cycle Impact

    Chemical Reviews · 2026-01-02

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  36. The paradigm shift of intelligent material design and development for fire safety: progress, challenges, and machine learning

    Polymer Degradation and Stability · 2026-01-31

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  37. Designing flame retardants for epoxy resins with generative AI for preventing battery thermal runaway propagation

    Journal of Material Science and Technology · 2026-03-27

    Pooya Jafari, Guofeng Ye, Junling Wang, Tao Chu, Boyou Hou, Di Wu, Siqi Huo, Hao Wang, Ziqi Sun, Pingan Song

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  38. AI-aided de novo molecular design of phosphamide for fire-retardant polylactide with enhanced integrated properties

    Polymer Degradation and Stability · 2026-04-14

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  39. Siloxane-bridged phosphaphenanthrene-containing imidazole-cured epoxy thermosets with synchronously improve flame retardancy and toughness

    European Polymer Journal · 2026-06-15

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  40. Decoding the limiting oxygen index of rigid polyurethane foams via explainable machine learning: Effects of elements, mechanisms and dosage

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  41. A mechanistic study on the concentration-dependent pyrolysis behavior of 3D cross-linked epoxy/TPP networks via ReaxFF-MD

    Chemical Engineering Journal · 2026-08-10

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