BetaCitation Atlas

RESEARCH PAPER · ACS Applied Engineering Materials · 2022

Accelerated Design of Flame Retardant Polymeric Nanocomposites via Machine Learning Prediction

Read original paper ↗

See where this research leads.

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

Open in your workspace →Saved 2026-10-14 · complete coverage
Filter Citing Papers
Press Enter or comma to add · × to remove · searches titles and available abstracts
Journals
All journals
Most represented first · select one or more
Explore Terms In These PapersHide SuggestionsShow Suggestions

Original and current center papers stay visible as anchors.
Numbers show citations received
42 direct citing works

Accelerated Design of Flame Retardant Polymeric Nanocomposites via Machine Learning PredictionOriginalAccurate Prediction of Microstructure of Composites using Machine Learning18A Prediction of Corrosion-related Leakage on Distribution Pipelines via Machine Learning Method2Flame retardant properties of metal hydroxide-based polymer composites: A machine learning approach45Flame Retardancy Index (FRI) for Polymer Materials Ranking73Material genome approach-based design of multi-functional self-curing epoxy resin with intrinsic flame retardancy and ultra-high modulus25Rethinking the pathway to sustainable fire retardants87A short review on machine learning for the purpose of optimizing and predicting the properties of polymeric nanocomposites21Computer Modeling and Machine Learning in Chemistry and Materials Science: From Properties and Reactions of Small Organic and Inorganic Molecules to the Smart Design of Polymers and Composites11CO2 pipelines release and dispersion: A review28Machine learning-enabled rational design of organic flame retardants for enhanced fire safety of epoxy resin composites28Recent advances in flame retardant polymers via thiol-ene click chemistry22Machine learning for expediting next-generation of fire-retardant polymer composites43Carbon‐based Flame Retardants for Polymers: A Bottom‐up Review79ROBERT : Bridging the Gap Between Machine Learning and Chemistry49Deeper insights into flame retardancy of polymers by interpretable, quantifiable, yet accurate machine-learning model17Machine‐Learning‐Assisted Process Optimization for High‐Performance Organic Thermoelectrics13AI and ML in Polymer Science: Enhancing Material Informatics Through Predictive Modelling0AI-driven advances in metal–organic frameworks: from data to design and applications47Applications of Predictive Modeling for Polymers0Data-driven design and green preparation of bio-based flame retardant polyamide composites4Process optimization of SiC/(Mo, W)Si2 nanocomposites preparation based on BOA-SSA1State of the art in machine learning for the purpose of optimizing and predicting the properties of polymeric nanocomposites2Practical machine learning model selection and interpretation for organophosphorus flame retardancy in Epoxy resin17Advancing polymer nanocomposites through mechanochemical approaches25Intumescent, catalyzed flame retardant systems for polyamide‐based powder bed fusion6Design and Development of Fire-Safety Materials in Artificial Intelligence Era6Determining the quality of imprinted polymers using diverse feature selections methods, Ada Boost and Gradient boosting algorithms3Flame-retardant coatings: Recent advances in materials, mechanisms, and multifunctional applications12A Hybrid Experimental–Machine Learning Framework for Designing Fire-Resistant Natural Fiber Composites2A parametric study and tailored infill design for enhanced flame-retardant performance of SORPLAS in FFF 3D printing0Bayesian Optimization of flame-retardant performance in a high-Tg epoxy resin system5Aerogel-Based Phase Change Materials Meet Flame Retardancy: From Materials to Properties3Machine learning-guided optimization of flame retardancy in rigid polyurethane foams0Methods for predicting the fire behaviour of fibre reinforced thermoset composites0Enhancing flame retardancy and mechanical performance of epoxy/carbon/ramie hybrid composites: influence of ammonium polyphosphate and artificial neural network predictions2Orchestrating explainable AI, ChatGPT, and human expertise: a framework for extracting polymer design guidelines0Using Machine Learning for Green Substitution of Industrial Chemicals: Integrating Functionality, Hazard, and Life Cycle Impact17Designing 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 properties3Machine learning in aerogels: from performance analytics to design optimization and property prediction4Decoding 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 materials1A Novel Image Analysis Methodology for Data‐Driven Assessment of Polymer Combustion Dynamics in the Vertical Flame Test0MCCX: Combining Monte Carlo, Convolutional Neural Networks and Boosting in Predicting Nanoparticle Viability0Large Language Model-Assisted Development of Reliable Machine Learning Models for Hydrogen Evolution Reaction Catalysts0

Arrows point to the paper being cited. Selecting a paper shows its incoming citations and its known path back to the original paper.

Browse Matching Papers

Papers that cite this work

45 direct citing papers saved.

  1. Accurate Prediction of Microstructure of Composites using Machine Learning

    Advanced Theory and Simulations · 2022-12-22

    Sheng Sang, Chen Xu, Jiadi Fan, Daniel Miao, Conner Side, Ziping Wang

    Read original paper ↗ ·
  2. A Prediction of Corrosion-related Leakage on Distribution Pipelines via Machine Learning Method

    Unknown journal · 2023-03-19

    Zhuoran Zhang, Guanlan Liu

    Read original paper ↗ ·
  3. Flame retardant properties of metal hydroxide-based polymer composites: A machine learning approach

    Composites Communications · 2023-04-16

    Junchen Xiao, Jose Hobson, Arnab Ghosh, Maciej Harańczyk, De‐Yi Wang

    Read original paper ↗ ·
  4. Flame Retardancy Index (FRI) for Polymer Materials Ranking

    Polymers · 2023-05-23

    Henri Vahabi, Elnaz Movahedifar, Baljinder K. Kandola, Mohammad Reza Saeb

    Read original paper ↗ ·
  5. 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

    Read original paper ↗ ·
  6. 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

    Read original paper ↗ ·
  7. A short review on machine learning for the purpose of optimizing and predicting the properties of polymeric nanocomposites

    Materials Today Proceedings · 2023-08-01

    Abhishek Saxena, Amrinder Mehta, Hitesh Vasudev, Gaurav Prashar, Nisreen Yasir Jasim

    Read original paper ↗ ·
  8. Computer Modeling and Machine Learning in Chemistry and Materials Science: From Properties and Reactions of Small Organic and Inorganic Molecules to the Smart Design of Polymers and Composites

    Compounds · 2023-08-24

    Alexander S. Novikov

    Read original paper ↗ ·
  9. CO2 pipelines release and dispersion: A review

    Journal of Loss Prevention in the Process Industries · 2023-09-20

    Chi‐Yang Li, Jazmine Aiya D. Marquez, Pingfan Hu, Qingsheng Wang

    Read original paper ↗ ·
  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

    Read original paper ↗ ·
  11. Recent advances in flame retardant polymers via thiol-ene click chemistry

    Journal of Macromolecular Science Part A · 2023-11-10

    Emrah Çakmakçı

    Read original paper ↗ ·
  12. 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

    Read original paper ↗ ·
  13. Carbon‐based Flame Retardants for Polymers: A Bottom‐up Review

    Advanced Materials · 2024-05-30

    Guan Heng Yeoh, Ivan Miguel De Cachinho Cordeiro, Wei Wang, Cheng Wang, Anthony Chun Yin Yuen, Timothy Bo Yuan Chen, Juan Baena Vargas, Guangzhao Mao, Ulf Garbe, Hui Tong Chua

    Read original paper ↗ ·
  14. ROBERT : Bridging the Gap Between Machine Learning and Chemistry

    Wiley Interdisciplinary Reviews Computational Molecular Science · 2024-09-01

    David Dalmau, Juan V. Alegre‐Requena

    Read original paper ↗ ·
  15. Deeper insights into flame retardancy of polymers by interpretable, quantifiable, yet accurate machine-learning model

    Polymer Degradation and Stability · 2024-09-14

    Ran Wang, Ran Wang, Teng Fu, Xiuli Wang, Yu‐Zhong Wang, Xiuli Wang, Yu‐Zhong Wang

    Read original paper ↗ ·
  16. Machine‐Learning‐Assisted Process Optimization for High‐Performance Organic Thermoelectrics

    Advanced Energy Materials · 2024-11-26

    Jeehyun Jeong, Suyeon Park, Juhyung Park, Jeong Han Song, Jeonghun Kwak

    Read original paper ↗ ·
  17. AI and ML in Polymer Science: Enhancing Material Informatics Through Predictive Modelling

    Studies in computational intelligence · 2025-01-01

    Semmedu Selvaraj Kalaivani, Appusamy Muthukrishnaraj, Ayyar Manikandan, K. P. Soman, Y. Slimani

    Read original paper ↗ ·
  18. AI-driven advances in metal–organic frameworks: from data to design and applications

    Chemical Communications · 2025-01-01

    Yuhang Song, Jiakai Li, Dongzhi Chi, Zhengtao Xu, Jie Liu, Mingxi Chen, Ziyu Wang

    Read original paper ↗ ·
  19. Applications of Predictive Modeling for Polymers

    Challenges and advances in computational chemistry and physics · 2025-01-01

    Fangyou Yan, Jiayi Zhu, Xiaojie Feng, Xiaoying He, Yin‐Ning Zhou

    Read original paper ↗ ·
  20. 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

    Read original paper ↗ ·
  21. Process optimization of SiC/(Mo, W)Si2 nanocomposites preparation based on BOA-SSA

    Manufacturing Review · 2025-01-01

    Tingyu Liu

    Read original paper ↗ ·
  22. State of the art in machine learning for the purpose of optimizing and predicting the properties of polymeric nanocomposites

    Elsevier eBooks · 2025-01-01

    Amrinder Mehta, Hitesh Vasudev, Chander Prakash, Alokesh Pramanik, Animesh Kumar Basak, S. Shankar

    Read original paper ↗ ·
  23. Practical machine learning model selection and interpretation for organophosphorus flame retardancy in Epoxy resin

    Polymer Degradation and Stability · 2025-01-18

    Jiajun Li, Bin Zou, Amirbek Bekeshev, Marzhan K. Akhmetova, Raigul O. Orynbassar, Xin Wang, Yuan Z. Hu

    Read original paper ↗ ·
  24. Advancing polymer nanocomposites through mechanochemical approaches

    Advanced Nanocomposites · 2025-03-12

    Linh Chi Tran, Xiao Su, Huynh H. Nguyen, Ly B.T. La, Philip Adu, Qiong Jia, Ivan Lee, Hsu‐Chiang Kuan, Xianhu Liu, Jun Ma

    Read original paper ↗ ·
  25. Intumescent, catalyzed flame retardant systems for polyamide‐based powder bed fusion

    Journal of Vinyl and Additive Technology · 2025-03-13

    Paul Roumeliotis, Samuel Schlicht, Dietmar Drummer

    Read original paper ↗ ·
  26. Design and Development of Fire-Safety Materials in Artificial Intelligence Era

    Accounts of Materials Research · 2025-04-01

    Teng Fu, Yu-Zhong Wang

    Read original paper ↗ ·
  27. Determining the quality of imprinted polymers using diverse feature selections methods, Ada Boost and Gradient boosting algorithms

    Results in Materials · 2025-05-12

    Bita Yarahmadi, Seyed Majid Hashemianzadeh

    Read original paper ↗ ·
  28. Flame-retardant coatings: Recent advances in materials, mechanisms, and multifunctional applications

    Progress in Organic Coatings · 2025-08-08

    S. Manivannan

    Read original paper ↗ ·
  29. A Hybrid Experimental–Machine Learning Framework for Designing Fire-Resistant Natural Fiber Composites

    Applied Sciences · 2025-08-20

    Cristóbal Galleguillos Ketterer, José Luis Valín Rivera, Maria Elena Fernandez, Nicolás Norambuena, Meylí Valin Fernández

    Read original paper ↗ ·
  30. A parametric study and tailored infill design for enhanced flame-retardant performance of SORPLAS in FFF 3D printing

    The International Journal of Advanced Manufacturing Technology · 2025-08-20

    Yih‐Lin Cheng, Yi‐Wen Chen, Yen-Ting Li

    Read original paper ↗ ·
  31. 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

    Read original paper ↗ ·
  32. Aerogel-Based Phase Change Materials Meet Flame Retardancy: From Materials to Properties

    Gels · 2025-11-19

    Panpan Zhao, Shudi Ying, Riming Hu, Jiachen Ma, Xuchuan Jiang

    Read original paper ↗ ·
  33. Machine learning-guided optimization of flame retardancy in rigid polyurethane foams

    Polymer Degradation and Stability · 2025-12-04

    Xiaoyan Sun, Jiankun Fu, Min Hao, Madeleine Bussemaker, Juncheng Jiang, Ru Zhou, Lian X. Liu

    Read original paper ↗ ·
  34. Methods for predicting the fire behaviour of fibre reinforced thermoset composites

    Polymer Degradation and Stability · 2025-12-15

    Ákos Pomázi, Gergely Magyar, Andrea Toldy

    Read original paper ↗ ·
  35. Enhancing flame retardancy and mechanical performance of epoxy/carbon/ramie hybrid composites: influence of ammonium polyphosphate and artificial neural network predictions

    Journal of Adhesion Science and Technology · 2025-12-18

    S. Senthamizh Selvan, I.S. Rajay Vedaraj

    Read original paper ↗ ·
  36. Orchestrating explainable AI, ChatGPT, and human expertise: a framework for extracting polymer design guidelines

    Journal of Materials Chemistry A · 2026-01-01

    Yin Kan Phua, Nana Terasoba, Manabu Tanaka, Tsuyohiko Fujigaya, Koichiro Kato

    Read original paper ↗ ·
  37. Using Machine Learning for Green Substitution of Industrial Chemicals: Integrating Functionality, Hazard, and Life Cycle Impact

    Chemical Reviews · 2026-01-02

    Haobo Wang, Jingwen Chen, Wenjia Liu, Dailong Wang, Yuhang Song, Huixiao Hong, Tong Wang, Paul T. Anastas, Julie Beth Zimmerman

    Read original paper ↗ ·
  38. 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

    Read original paper ↗ ·
  39. AI-aided de novo molecular design of phosphamide for fire-retardant polylactide with enhanced integrated properties

    Polymer Degradation and Stability · 2026-04-14

    Pooya Jafari, Guoping Zhu, Zongmin Zhu, Mark Lynch, Taotao Cai, Siqi Huo, Jianping Ren, Guobo Huang, Pingan Song

    Read original paper ↗ ·
  40. Machine learning in aerogels: from performance analytics to design optimization and property prediction

    Progress in Materials Science · 2026-04-21

    Zahra Amiri, Omid Aghababaei Tafreshi, Hangyu Song, Zia Saadatnia, Chul B. Park, Hani E. Naguib

    Read original paper ↗ ·
  41. 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

    Read original paper ↗ ·
  42. 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

    Read original paper ↗ ·
  43. A Novel Image Analysis Methodology for Data‐Driven Assessment of Polymer Combustion Dynamics in the Vertical Flame Test

    Journal of Applied Polymer Science · 2026-07-28

    Erika Nakashima, Takashi Fujii, Ryō Tanaka, Yuya Nakanishi, Tomonaga Ueno

    Read original paper ↗ ·
  44. MCCX: Combining Monte Carlo, Convolutional Neural Networks and Boosting in Predicting Nanoparticle Viability

    ACS Applied Engineering Materials · 2026-08-20

    Qiankun Mo, Xingfei Wei, Ravithree D. Senanayake, Amelyn Phang, Rigoberto Hernandez

    Read original paper ↗ ·
  45. Large Language Model-Assisted Development of Reliable Machine Learning Models for Hydrogen Evolution Reaction Catalysts

    ACS Sustainable Chemistry & Engineering · 2026-09-28

    Lanxin Guo, Haoyu Yang, Chi‐Yang Li, Ahmed Badreldin, Shengyao Wang, Rebecca Eason, Ying Li, Qingsheng Wang

    Read original paper ↗ ·