Machine learning-guided design of organic phosphorus-containing flame retardants to improve the limiting oxygen index of epoxy resins

被引:32
作者
Chen, Zhongwei [1 ,2 ]
Yang, Boran [1 ]
Song, Nannan [1 ]
Chen, Tingting [1 ]
Zhang, Qingwu [1 ]
Li, Changxin [1 ]
Jiang, Juncheng [1 ]
Chen, Tao [2 ]
Yu, Yuan [1 ]
Liu, Lian X. [2 ]
机构
[1] Nanjing Tech Univ, Coll Safety Sci & Engn, Nanjing 210009, Peoples R China
[2] Univ Surrey, Dept Chem & Proc Engn, Surrey GU2 7XH, England
基金
中国国家自然科学基金;
关键词
Machine learning; Composites; Fire resistance; Limiting oxygen index; Epoxy resin; MECHANICAL-PROPERTIES; THERMAL-STABILITY; NANOCOMPOSITES; COMPOUND; BEHAVIOR; GRAPHENE;
D O I
10.1016/j.cej.2022.140547
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The addition of organic phosphorus-containing flame retardants (OPFRs) has greatly improved the fire resistance of epoxy resins (EPs). Developing the relationship of the fire resistance with the structure of OPFRs and their addition amount will help discover high-performance EP composites, which was achieved in this work by ma-chine learning (ML). By combining descriptors encoded from OPFR molecules and the addition amount as fea-tures, an ML model with the limiting oxygen index (LOI) as the target was developed with a coefficient of determination (R2) of the ML model on the test set of 0.642. The trained ML model indicated that fire retardants containing conjugated systems with penta-substituted phosphorus containing a P--O bond and the nitrogen element can significantly increase the LOI of EPs, which led to the synthesis of a 9,10-dihydro-9-oxa-10-phospha-phenanthrene-10-oxide derivative (BDOPO) in this work. Furthermore, the accuracy of the ML model was validated through experiments. The predicted LOI values of the EP/BDOPO composites followed the same trend as the experimental values, with an average error of 5.1 %. The model can also illustrate the molecular structure required for synthesizing an OPFR and predict the amount of this OPFR to be added into EPs for enhanced LOI of the EPs.
引用
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页数:10
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