期刊
ACS MATERIALS LETTERS
卷 5, 期 8, 页码 2174-2188出版社
AMER CHEMICAL SOC
DOI: 10.1021/acsmaterialslett.3c00307
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This study presents a versatile methodology to simulate and forecast the radiochemical damage of polydimethylsiloxane (PDMS) foam. By conducting multiscale simulations with experimental verification, the radiolytic kinetics of PDMS foam in radiation-thermal environments are studied. A radiolytic kinetic model of PDMS is then developed using material informatics gained from experiments, reactive force field simulations, and density functional theory calculations.
The widespread and advanced application of polymers outshinesthecurrent ability to theoretically predict their radiation deteriorationwithout much prior knowledge. This work presents a versatile methodologyto simulate and forecast the radiochemical damage of polydimethylsiloxane(PDMS) foam. The radiolytic kinetics of PDMS foam in radiation-thermalenvironments is first studied by multiscale simulations with experimentalverification. Then the radiolytic kinetic model of PDMS is developedvia material informatics gained from experiments, reactive force fieldsimulations, and density functional theory calculations, involvingthe paramount elementary reactions and other events in the physical,physicochemical, and chemical stages. The model configuration is designedto interactively couple with the service conditions and structuralrelationships, which enables the model to allow for the intricateradiation-thermal coupling effect, dose rate effect, and postradiationeffect. To improve the adaptivity and accuracy of the model and furtherrationalize the radiolytic kinetics frame, the diffusion coefficientsand reaction rate constants with temperature, topology, and morphologydependence are calculated. The developed radiolytic kinetic modelcan precisely predict the deteriorated PDMS system from various aspectssimultaneously, including gas yields, radiation chemical yields, anddamaged molecular structure and cross-linking network. The overallaccuracy in view of the standard deviation calculated from the normalizeddata is less than 0.35. The proposed methodology has a promising futurein nonempirical simulations, multiscale understanding, and goal-orientedharnessing of the structure-property relationships of polymers.
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