ABSTRACT
Elastomers embedded with micro- and nanoscale droplets of liquid metal (LM) alloys like eutectic gallium-indium (EGaIn) can exhibit unique combinations of elastic, thermal, and electrical properties that are difficult to achieve using rigid filler. For composites with sufficient concentrations of liquid metal, the LM droplets can form percolating networks that conduct electricity and deform with the surrounding elastomer as the composite is stretched. Surprisingly, experimental measurements performed on LM-embedded elastomers (LMEEs) show that the total electrical resistance of the composite increases only slightly even as the elastomer is stretched to several times its natural length. In contrast, Pouillet's law would predict an exponential increase in resistance (Ω) with stretch (λ) due to the incompressibility of liquid metal and elastomer. In this manuscript, we perform a computational analysis to examine the unique electromechanical properties of conductive LMEE composites. Our analysis suggests that the gauge factor that quantifies electromechanical coupling (i.e. G = {ΔΩ/Ω0}/λ) decreases with increasing tortuosity of the conductive pathways formed by the connected LM droplets. A dimensionless parameter for path tortuosity can be used to estimate G for statistically homogeneous LMEE composites. These results rationalize experimental observations and provide insight into the influence of liquid metal droplet assembly on the functionality of the composite.
ABSTRACT
We present a distributed fiber optic sensing scheme to image 3D strain fields inside concrete blocks during laboratory-scale hydraulic fracturing. Strain fields were measured by optical fibers embedded during casting of the concrete blocks. The axial strain profile along the optical fiber was interrogated by the in-fiber Rayleigh backscattering with 1-cm spatial resolution using optical frequency domain reflectometry (OFDR). The 3D strain fields inside the cubes under various driving pressures and pumping schedules were measured and used to characterize the location, shape, and growth rate of the hydraulic fractures. The fiber optic sensor detection method presented in this paper provides scientists and engineers an unique laboratory tool to understand the hydraulic fracturing processes via internal, 3D strain measurements with the potential to ascertain mechanisms related to crack growth and its associated damage of the surrounding material as well as poromechanically-coupled mechanisms driven by fluid diffusion from the crack into the permeable matrix of concrete specimens.
