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RESEARCH PAPER · Polymer Degradation and Stability · 2024

Deeper insights into flame retardancy of polymers by interpretable, quantifiable, yet accurate machine-learning model

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17 direct citing papers in this saved network. Explore the next layer with second-order citations.

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42 direct citing works

Deeper insights into flame retardancy of polymers by interpretable, quantifiable, yet accurate machine-learning modelOriginalMetal–Organic Frameworks Meet Two‐Dimensional Materials in Polymer Matrices for Flame Retardant and Sensor Applications30Design and Development of Fire-Safety Materials in Artificial Intelligence Era6Augmenting nonlinear shear creep evaluation of adhesive joints with conditional tabular GAN3Machine learning-driven molecular generation for accelerated screening of high-performance flame retardants in epoxy resin composites13Bayesian Optimization of flame-retardant performance in a high-Tg epoxy resin system5Lignin-based flame retardant containing nitrogen and phosphorus coordinated by Fe3+ for TPU7Editorial: Recent advances in flame retardant polymeric materials and composites0The paradigm shift of intelligent material design and development for fire safety: progress, challenges, and machine learning2Accelerating the design of flame-retardant polypropylene composites: An approach driven by explainable ensemble machine learning and Bayesian optimization3High-Performance Poly(aryl ether ketone) Foams with Low Dielectric Constant and Dielectric Loss1Ecological impacts of hydropower projects in the lower reaches of the Yarlung Zangbo River driven by machine learning: Focusing on nitrogen and phosphorus cycle prediction and assessment1Nano Flame Retardants for Polymer Composites: A 20-Year Journey from Fundamental Discoveries to Emerging Frontiers1Data-driven prediction and non-compensatory assessment of flame retardancy in phosphorus-containing flame-retardant epoxy resin1Fire Testing and Hazard Assessment for Flame Retardant Polymer Composites0Decoding the limiting oxygen index of rigid polyurethane foams via explainable machine learning: Effects of elements, mechanisms and dosage0Reaction-to-fire characterization data driving the AI-assisted design of flame-retardant polymeric materials1Sparse data inverse design framework for flame-retardant polymer composites0

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17 direct citing papers saved.

  1. Metal–Organic Frameworks Meet Two‐Dimensional Materials in Polymer Matrices for Flame Retardant and Sensor Applications

    Small Science · 2025-02-21

    Xue Bi, Yanan Hou, Ye‐Tang Pan, Siqi Huo, Congling Shi, Jiyu He, Rongjie Yang

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  2. Design and Development of Fire-Safety Materials in Artificial Intelligence Era

    Accounts of Materials Research · 2025-04-01

    Teng Fu, Yu-Zhong Wang

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  3. Augmenting nonlinear shear creep evaluation of adhesive joints with conditional tabular GAN

    International Journal of Adhesion and Adhesives · 2025-05-17

    Songbo Wang, Sifan Ban, Zhuo Duan, Siyuan Frank Yang, Yang Li

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  4. 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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  5. Bayesian Optimization of flame-retardant performance in a high-Tg epoxy resin system

    Computational Materials Science · 2025-09-16

    Niko Krebs, Martin Demleitner, Rodrigo Queiroz Albuquerque, Bernhard Schartel, Holger Ruckdäschel

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  6. Lignin-based flame retardant containing nitrogen and phosphorus coordinated by Fe3+ for TPU

    International Journal of Biological Macromolecules · 2026-01-01

    Xinrui Meng, Yuhan Liu, Yongqian Fu, Ming Jing, Chunzhu Jiang, Wei Hu

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  7. Editorial: Recent advances in flame retardant polymeric materials and composites

    Frontiers in Materials · 2026-01-26

    Xiaolang Chen, Siqi Huo, Jun Cheng Sun, Jing Zhang

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

    Polymer Degradation and Stability · 2026-01-31

    Yuanchuan Ren, Yuhang Lin, Xuejun Zhu, Shiyong Zhao, Renjie Huang, Tingfeng Su, Cheng Wang, Nanqi Ren

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  9. Accelerating the design of flame-retardant polypropylene composites: An approach driven by explainable ensemble machine learning and Bayesian optimization

    Composites Communications · 2026-02-06

    Weize Lv, Hu Bi, Yong Zheng Fang, Haiyang Lin, Guodong Jiang, Yucai Shen

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  10. High-Performance Poly(aryl ether ketone) Foams with Low Dielectric Constant and Dielectric Loss

    ACS Applied Polymer Materials · 2026-02-12

    Jiyong Zhao, Zhipeng Wang, Heran Nie

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  11. Ecological impacts of hydropower projects in the lower reaches of the Yarlung Zangbo River driven by machine learning: Focusing on nitrogen and phosphorus cycle prediction and assessment

    Results in Engineering · 2026-03-20

    Qingli Han, Yuanchuan Ren

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  12. Nano Flame Retardants for Polymer Composites: A 20-Year Journey from Fundamental Discoveries to Emerging Frontiers

    Accounts of Materials Research · 2026-05-05

    Wei Cai, De‐Yi Wang

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  13. Data-driven prediction and non-compensatory assessment of flame retardancy in phosphorus-containing flame-retardant epoxy resin

    Polymer Degradation and Stability · 2026-05-09

    Qiong Tan, De-Yi Wang

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  14. Fire Testing and Hazard Assessment for Flame Retardant Polymer Composites

    Safety Science and Technology · 2026-06-18

    Shuheng Wang, Min Yue, Junjie Ren, Fei Ren, Bin Zou, Xiaodong Qian, Ye‐Tang Pan, Congling Shi, Sheng Zhang

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

    Composites Part A Applied Science and Manufacturing · 2026-06-21

    Xiaoyan Sun, Ru Zhou, Min Hao, Madeleine Bussemaker, Lian X. Liu

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  16. Reaction-to-fire characterization data driving the AI-assisted design of flame-retardant polymeric materials

    Progress in Polymer Science · 2026-06-26

    Rui-Zhi Wu, Fan Li, Ya-Han Kuang, Ya-Jie Yang, Xiu‐Li Wang, Yu‐Zhong Wang, Teng Fu

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  17. Sparse data inverse design framework for flame-retardant polymer composites

    Composites Part A Applied Science and Manufacturing · 2026-09-25

    Weibin Ma, Ling Li, Yu Zhang, Xinquan Zou, Kai Zhang, Feng Wang, Minjie Li, Peng Ding

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