Organic polymer materials,as the most abundantly produced materials,possess a flammable nature,making them potential hazards to human casualties and property losses.Target polymer design is still hindered due to the l...Organic polymer materials,as the most abundantly produced materials,possess a flammable nature,making them potential hazards to human casualties and property losses.Target polymer design is still hindered due to the lack of a scientific foundation.Herein,we present a robust,generalizable,yet intelligent polymer discovery framework,which synergizes diverse capabilities,including the in situ burning analyzer,virtual reaction generator,and material genomic model,to achieve results that surpass the sum of individual parts.Notably,the high-throughput analyzer created for the first time,grounded in multiple spectroscopic principles,enables in situ capturing of massive combustion intermediates;then,the created realistic apparatus transforming to the virtual reaction generator acquires exponentially more intermediate information;further,the proposed feature engineering tool,which embedded both polymer hierarchical structures and massive intermediate data,develops the generalizable genomic model with excellent universality(adapting over 20 kinds of polymers)and high accuracy(88.8%),succeeding discovering series of novel polymers.This emerging approach addresses the target polymer design for flame-retardant application and underscores a pivotal role in accelerating polymeric materials discovery.展开更多
基金supported by the National Natural Science Foundation of China(51991351,51827803,52103122,and 22375138)the Institutional Research Fund from Sichuan University(no.2021SCUNL201)the Fundamental Research Funds for the Central Universities,and the 111 project(B20001).
文摘Organic polymer materials,as the most abundantly produced materials,possess a flammable nature,making them potential hazards to human casualties and property losses.Target polymer design is still hindered due to the lack of a scientific foundation.Herein,we present a robust,generalizable,yet intelligent polymer discovery framework,which synergizes diverse capabilities,including the in situ burning analyzer,virtual reaction generator,and material genomic model,to achieve results that surpass the sum of individual parts.Notably,the high-throughput analyzer created for the first time,grounded in multiple spectroscopic principles,enables in situ capturing of massive combustion intermediates;then,the created realistic apparatus transforming to the virtual reaction generator acquires exponentially more intermediate information;further,the proposed feature engineering tool,which embedded both polymer hierarchical structures and massive intermediate data,develops the generalizable genomic model with excellent universality(adapting over 20 kinds of polymers)and high accuracy(88.8%),succeeding discovering series of novel polymers.This emerging approach addresses the target polymer design for flame-retardant application and underscores a pivotal role in accelerating polymeric materials discovery.
