Accelerated feasible screening of flame-retardant polymeric composites using data-driven multi-objective optimization
Author:
Publisher
Elsevier BV
Subject
Computational Mathematics,General Physics and Astronomy,Mechanics of Materials,General Materials Science,General Chemistry,General Computer Science
Reference39 articles.
1. Towards the Development of Green Flame Retardancy by Polybenzoxazines;Machado;Prog. Polym. Sci.,2021
2. Lignin-derived bio-based flame retardants toward high-performance sustainable polymeric materials;Yang;Green Chem.,2020
3. Flame-retardant-wrapped polyphosphazene nanotubes: A novel strategy for enhancing the flame retardancy and smoke toxicity suppression of epoxy resins;Qiu;J. Hazard. Mater.,2017
4. An Individualized Core-Shell Architecture Derived from Covalent Triazine Frameworks: Toward Enhancing the Flame Retardancy, Smoke Release Suppression, and Toughness of Bismaleimide Resin;Jiang;ACS Mater. Lett.,2023
5. An adaptive framework to accelerate optimization of high flame retardant composites using machine learning;Chen;Compos. Sci. Technol.,2023
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3. Machine learning for expediting next-generation of fire-retardant polymer composites;Composites Communications;2024-01
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