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RESEARCH PAPER · Composites Communications · 2023

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

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42 direct citing works

Machine learning for expediting next-generation of fire-retardant polymer compositesOriginalBismuth trioxide replaced diantimony trioxide to obtain polyvinyl chloride leather with high flame retardancy and low flame propagation rate8Enhancing machining accuracy of banana fiber-reinforced composites with ensemble machine learning58Artificial Neural Network Modeling in the Presence of Uncertainty for Predicting Hydrogenation Degree in Continuous Nitrile Butadiene Rubber Processing10Application of machine learning for composite moulding process modelling74An efficient machine learning-based model for predicting the stress-strain relationships of thermoplastic polymers with limited testing data19Optimized Machine Learning Prediction and RSM Optimization of Mechanical Properties in Boiled Eggshell Filler-Added Biocomposites30Recent advances in graphene allotropes-based fire detection sensors34D printed Electroactive carbon fiber and carbon nanotube synergistically reinforced composites for supporting personalized insole11AI and ML in Polymer Science: Enhancing Material Informatics Through Predictive Modelling0Data-driven design and green preparation of bio-based flame retardant polyamide composites4Recyclable fire-retardant bio-based thermosets: From molecular engineering to performances and applications132Flame-retardant innovations in bio-based treatments for lignocellulosic natural fibers: A review1327Chapter 2 Machine learning applications in material science: unveiling innovative solutions1Ant 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 Composites2Machine learning-assisted dual-objective synergistic optimization for mechanical and electrical properties of CNTs/Cu composites5Phosphorus‐Free Flame‐Retardant Strategies for Epoxy Resins9Bayesian Optimization of flame-retardant performance in a high-Tg epoxy resin system5Application of machine learning in the study of heavy metal remediation in soil using biochar-based nanocomposites6Smart design of thermoplastic vulcanizate products: Linking process to performance via interpretable machine learning1Multi-Objective Optimization and Reliability Assessment of Date Palm Fiber/Sheep Wool Hybrid Polyester Composites Using RSM and Weibull Analysis3Enhancing Flame Retardancy in Polypropylene Composites: A Bayesian Optimization Approach0Research progress on halogen-free flame retardant epoxy resins7Methods 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 predictions2Advancements in Nanotechnology and Nanomaterials for Enhanced Fire Safety0Advancing composites manufacturing through digitalization and AI: Toward composites 4.00Membrane Filtration Techniques: Purifying Wastewater from Emerging Toxicants0Using 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 properties3Sustainable hybrid rubber nanocomposites: a review of green solvents processing and machine learning-driven optimization2Data-driven prediction and non-compensatory assessment of flame retardancy in phosphorus-containing flame-retardant epoxy resin1Siloxane-bridged phosphaphenanthrene-containing imidazole-cured epoxy thermosets with synchronously improve flame retardancy and toughness0Fire 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 materials1A review of the application of machine learning in the field of fire public safety: From risk assessment to emergency decision-making0Machine learning-assisted formulation design of flame-retardant polyoxymethylene composites0EMPIRICAL BENCHMARKING OF GRADIENT BOOSTING FOR THERMAL DEGRADATION PREDICTION IN MINERAL–POLYMER COMPOSITES0Large Language Model-Assisted Development of Reliable Machine Learning Models for Hydrogen Evolution Reaction Catalysts0

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  3. Artificial Neural Network Modeling in the Presence of Uncertainty for Predicting Hydrogenation Degree in Continuous Nitrile Butadiene Rubber Processing

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  8. 4D printed Electroactive carbon fiber and carbon nanotube synergistically reinforced composites for supporting personalized insole

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  11. Recyclable fire-retardant bio-based thermosets: From molecular engineering to performances and applications

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

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

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  22. Multi-Objective Optimization and Reliability Assessment of Date Palm Fiber/Sheep Wool Hybrid Polyester Composites Using RSM and Weibull Analysis

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  23. Enhancing Flame Retardancy in Polypropylene Composites: A Bayesian Optimization Approach

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  24. Research progress on halogen-free flame retardant epoxy resins

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  25. Methods for predicting the fire behaviour of fibre reinforced thermoset composites

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