MULTISCALE SIMULATION AND MACHINE LEARNING-ASSISTED PERFORMANCE PREDICTION FOR CEMENTITIOUS COMPOSITES

Caroline Willuhn, University of Rhode Island

Abstract

Although advantageous in many regards, solid polymer electrolytes have the major disadvantage of low ionic conductivity, preventing commercial utilization. Amorphous polymers have a higher lithium-ion conductivity than crystalline polymers. This is why many attempts are made to decrease their crystallinity. The integration of nanoparticles has been shown toeffectively reduce a polymer’s degree of crystallinity, thus enabling faster Li-ion transport.This work studies the integration of carboxyl-terminated carbon black (CB) and bariumtitanate nanoparticles into a PEO/LiTFSI polymer electrolyte (PE) with the final goal of enhancing its Li-ion conductivity. Differential Scanning Calorimetry (DSC) was carried out and showed a decrease in glass transition temperature, melting temperature, and degree of crystallinity for the nanoparticle-doped PE. DSC therefore confirmed the increase in amorphousness, which also agrees with findings from X-Ray Diffraction. Impedance measurements show that the ionic conductivity slightly increases with adding either type of nanoparticle but eventually reaches a maximum. At 60∞C and 70∞C the ionic conductivities of the PEO/LiTFSI electrolyte are 3.96 ∑ 10−4 S/cm and 9.46 ∑ 10−4 S/cm, respectively. The addition of 1wt% CB at 60∞C raises the ionic conductivity to 1.14 ∑ 10−3 S/cm. Adding 6wt% of BaTiO3 at 70∞C leads to an ionic conductivity of 1.18 ∑ 10−3 S/cm. With the obtained PE, full cells were built with an LTO anode and LFP cathode, showing that the cells cycle but have very high internal resistances, leading to low capacities.