Damage Precursor Detection in Polymer Matrix Composites Using Novel Smart Composite Particles

Abstract

Abstract : A novel self-sensing framework, utilizing embedded cyclobutane-based mechanophores, was developed for identifying damage precursors and propagation. The novel 'smart' material was incorporated into a thermoset polymer matrix and the color change phenomenon was observed under compressive loading. The smart material based polymer system was used to construct glass fiver reinforced composites to investigate the performance of the composite under cyclic loading; the correlation between fluorescence intensity and fatigue cycle was investigated. Fourier Transform Infrared Spectroscopy showed the potential of detecting damage in carbon-containing composites by identifying changes in the peak intensity associated with the mechanically responsive cyclobutane ring. An atomistic simulation methodology was developed in conjunction with the experimental work; the Molecular Dynamics (MD) based methodology was capable of emulating the experiments. After simulating the epoxy curing and ultraviolet (UV) dimerization process, mechanophore activation in the thermoset polymer matrix was successfully emulated. A local work analysis method was developed to evaluate the mechanophore sensitivity quantitatively. The simulation method captured the physical entanglement between epoxy and mechanophore network, which affected the mechanical properties of the polymer matrix significantly. Results from the simulations showed increment in the number of activated cyclobutanes during the deformation test. Good agreement was observed with experimental results: the intensity of fluorescence was found to be directly proportional to the deformation.