Multiscale Modeling of a Mechanophore-embedded Nanocomposite for Damage Initiation Detection

摘要

This paper presents multiscale modeling of a mechanophore-embedded nanocomposite material for detection of damage initiation. Mechanophores are force-responsive functional units which allow for molecular-scale understanding of the local mechanical environment and can transform the material properties in response. Recently, a cyclobutane-based mechanophore embedded in a thermoset polymer matrix has been investigated for detecting damage precursors and tracking propagation in a thermoset polymeric matrix. Tris-(Cinnamoyloxymethyl)-Ethane (TCE) was used as fluorescent crack sensing additives in epoxy network polymer blends. The cyclobutane sensing units were produced by photodimerization of the C=C double bond in the cinnamoyl functional group of TCE. When the blended system undergoes crack formation and propagation, the cyclobutane units are mechanochemically cleaved to afford the monomeric structure. This structure is capable of strong fluorescence emission, indicating the location of the crack in the epoxy. This study aims at developing a mechanochemical reaction-based multiscale modeling framework to simulate the self-sensing phenomenon of TCE-embedded thermoset polymers. The methodology initiates at the atomistic level and connects the relevant length scales; ranging from mechanophore activation at the sub-molecular level to fluorescence intensity at the nano/microscale. A quantum theory-based method is incorporated to quantify the interatomic potential of the mechanophore under external force. Intermolecular force is estimated using molecular dynamics (MD) simulation by analyzing energy distribution in the epoxy/smart material network structure. A bond ordered potential-based MD simulation has been incorporated to simulate mechanophore activation, which is correlated to the fluorescence intensity of the mechanophore. The experimentally observed color change phenomena associated with damage initiation have also been interpreted using this quantum theory-based modeling framework.