![]() ![]() The study helps in visualizing the motion of the charged particles in different electrical conditions, which is not possible to probe experimentally. In this manuscript, we simulate this phenomenon using mesoscale simulations, taking into account the important features of spatial–temporal potential mapping based on the time-varying signal, the motion of charged particles in the liquid due to the electric field, and the attachment of particles on the electrode. Since the geometry of these structures determines their electrochemical properties, understanding the mechanisms that regulate polymer assembly under electrically programmed conditions is an important aspect. ![]() The strategy has been recently explored for neuromorphic engineering by establishing link between the electrical signals and the dendrites’ shapes. It resembles synaptogenesis in the brain, in which the electrical stimulation in the brain causes the formation of synapses from the cellular neural composites. However, during “fast” charging, the local Li+ concentrations rapidly decrease leading to mass transport limited conditions which result in dendrite growth and lower battery performance.Electropolymerization is a bottom-up materials engineering process of micro/nano-scale that utilizes electrical signals to deposit conducting dendrites morphologies by a redox reaction in the liquid phase. During standard charging, the Li+ concentrations at the anode create reaction rate limited conditions that lead to more uniform Li+ deposition. The computational studies demonstrate the mechanisms by which these novel techniques improve the performance of lithium metal batteries such as reducing the pore size in carbon nanomembranes reduces dendrite length and increases deposition density ionic liquid crystal supramolecular assemblies oriented perpendicular to the anode increase the uniformity of Li+ deposition at the anode the effects of homogeneity of ionic conductivity of protective coatings on the anode to enable uniform Li+ deposition.Īdditionally, the model is used to explore how the local conditions in the electrolyte change during battery cycling. Building upon these insights and in collaboration with experimental groups, the effect of the structure of novel coatings and electrolytes on the mass transport to the anode and subsequent dendrite morphology are investigated. Additionally, despite the characterization of battery separators using bulk properties, the heterogeneity of the separators lead to vastly different local transport outcomes. The findings from the simulations suggest that the tortuosity of the separator is a key property affecting transport. Using SPH, the geometrical parameters of the separator are characterized based on their effect on mass transport and dendrite growth. The first goal is to understand the effects of local transport through battery separators on dendrite growth by explicitly representing commercial battery separator structures taken from SEM images. Using the SPH model, the effect of various structures in the electrolyte on mass transport and dendrite growth are investigated. The model is implemented in the LAMMPs code base and includes the ability to model charge/discharge cycles. The SPH model simulates the physics at this interface by solving the governing equations for diffusion, migration, and potential distribution in a binary electrolyte and near a reactive, moving interface and dendrite surfaces. In this dissertation, a meso-scale computational model, using the smoothed particle hydrodynamics (SPH) numerical method, is used to simulate the deposition process at the electrolyte/anode interface of a lithium metal battery. ![]()
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