Intercalation Pathway in Many-Particle LiFePO4 Electrode Revealed by Nanoscale State-of-Charge Mapping
Citations Over TimeTop 1% of 2013 papers
Abstract
The intercalation pathway of lithium iron phosphate (LFP) in the positive electrode of a lithium-ion battery was probed at the ∼40 nm length scale using oxidation-state-sensitive X-ray microscopy. Combined with morphological observations of the same exact locations using transmission electron microscopy, we quantified the local state-of-charge of approximately 450 individual LFP particles over nearly the entire thickness of the porous electrode. With the electrode charged to 50% state-of-charge in 0.5 h, we observed that the overwhelming majority of particles were either almost completely delithiated or lithiated. Specifically, only ∼2% of individual particles were at an intermediate state-of-charge. From this small fraction of particles that were actively undergoing delithiation, we conclude that the time needed to charge a particle is ∼1/50 the time needed to charge the entire particle ensemble. Surprisingly, we observed a very weak correlation between the sequence of delithiation and the particle size, contrary to the common expectation that smaller particles delithiate before larger ones. Our quantitative results unambiguously confirm the mosaic (particle-by-particle) pathway of intercalation and suggest that the rate-limiting process of charging is initiating the phase transformation by, for example, a nucleation-like event. Therefore, strategies for further enhancing the performance of LFP electrodes should not focus on increasing the phase-boundary velocity but on the rate of phase-transformation initiation.
Related Papers
- → Prediction of State of Charge (SOC) of Battery Electric Vehicle(2021)3 cited
- → Battery State of Charge Estimation Considering the Battery Aging(2014)2 cited
- An algorithm for predicting state of charge of lithium iron phosphate batteries(2011)
- → Modeling Tool For Determination Of The Available Energy In Battery Storage Systems(2021)2 cited
- → State of charge estimation at battery level from multiple cells management(2015)1 cited