  The Galvanostatic Intermittent Titration Technique (GITT) is a ubiquitous
method for determining the solid-state diffusivity in lithium-ion battery
materials. However, it is notoriously time-consuming and relies upon
assumptions whose applicability is questionable. We propose a novel methodology
that allows inference of the diffusivity for a more general class of data that
is simpler and faster to harvest. We infer the diffusivity (as a function of
stoichiometry) by minimising the residual sum of squares between data and
solutions to a spherically-symmetric diffusion model in a single representative
active material particle. Using data harvested from the NMC cathode of a
commercial LG M50 cell we first demonstrate that our method is able to
reproduce the diffusivities inferred by the GITT, which requires ten days of
galvanostatic intermittent titration data. We then demonstrate that our method
reliably reconstructs diffusivity using significantly less data. Despite
arising from quick-to-measure data, our method more accurately infers
diffusivities. This work is a contribution towards developing faster and more
reliable techniques in parameter inference for lithium-ion batteries.
