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Computational investigation of dead weight reduction in lithium ion batteries by conductive additive gradients
Thesis   Open access

Computational investigation of dead weight reduction in lithium ion batteries by conductive additive gradients

Cassandra Megan Lees
Master of Science (M.S.), Drexel University
Jun 2020
DOI:
https://doi.org/10.17918/00000174
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Abstract

Storage batteries--Materials Electrolytes--Conductivity Power resources Lithium ion batteries Computer simulation
Industrial-scale lithium ion battery production often involves overengineering conductivity in electrodes via conductive additives in order improve performance. When more additive is present than is needed, the extra mass lowers energy density without improving performance. There are two scales of conductivity that can be investigated; bulk conductivity on millimeter scale and particle conductance on nanometer scale. This work seeks to investigate where particle conductance is important in cathodes, with the goal of reducing dead weight in spaces where nm-scale conductivity is less crucial. This is done by both simulating layered NMC cathodes with different particle conductances in each layer in Python and experimentally fabricating layered NMC cathodes with different amounts of conductive carbon black in each layer in the laboratory and observing the effects on discharge curves of both the simulations and the laboratory experiments. Simulation results indicate that particle conductance is much more important on the separator side of the cathode, so the current collector side can have significantly less conductive additive than the separator side without impeding performance. Laboratory results are pending lab openings post Covid-19. Keywords: Batteries, Conductivity, Energy, Lithium, Modeling, Simulation

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