biostudies-literatureLin HU.S. Department of Energy (DOE)National Science Foundation (NSF)e2203470119https://www.ebi.ac.uk/biostudies/studies/S-EPMC9303984biostudies-literatureUnknown119(29)Electrical transport in semiconducting and metallic particle suspensions is an enabling feature of emerging grid-scale battery technologies. Although the physics of the transport process plays a key role in these technologies, no universal framework has yet emerged. Here, we examine the important contribution of shear flow to the electrical transport of non-Brownian suspensions. We find that these suspensions exhibit a strong dependence of the transport rate on the particle volume fraction and applied shear rate, which enables the conductivity to be dynamically changed by over 10⁷ decades based on the applied shear rate. We combine experiments and simulations to conclude that the transport process relies on a combination of charge and particle diffusion with a rate that can be predicted using a quantitative physical model that incorporates the self-diffusion of the particles.Proceedings of the National Academy of Sciences of the United States of AmericaQuantifying the hydrodynamic contribution to electrical transport in non-Brownian suspensions.PMC9303984DE-SC0022119CBET-2047365Swan JWRichards JJLin HCho NMajji MVZeeman JRfalseQuantifying the hydrodynamic contribution to electrical transport in non-Brownian suspensions.Electrical transport in semiconducting and metallic particle suspensions is an enabling feature of emerging grid-scale battery technologies. Although the physics of the transport process plays a key role in these technologies, no universal framework has yet emerged. Here, we examine the important contribution of shear flow to the electrical transport of non-Brownian suspensions. We find that these suspensions exhibit a strong dependence of the transport rate on the particle volume fraction and applied shear rate, which enables the conductivity to be dynamically changed by over 10⁷ decades based on the applied shear rate. We combine experiments and simulations to conclude that the transport process relies on a combination of charge and particle diffusion with a rate that can be predicted using a quantitative physical model that incorporates the self-diffusion of the particles.2022-01-01T00:00:00Z2022 Jul2025-04-19T23:05:46.26Z2025-04-19T23:05:46.26ZS-EPMC93039843585834610.1073/pnas.2203470119