Multiscale dynamics of charging and plating in graphite electrodes coupling operando microscopy and phase-field modelling.

The phase separation dynamics in graphitic anodes significantly affects lithium plating propensity, which is the major degradation mechanism that impairs the safety and fast charge capabilities of automotive lithium-ion batteries. In this study, we present comprehensive investigation employing operando high-resolution optical microscopy combined with non-equilibrium thermodynamics implemented in a multi-dimensional (1D+1D to 3D) phase-field modeling framework to reveal the rate-dependent spatial dynamics of phase separation and plating in graphite electrodes. Here we visualize and provide mechanistic understanding of the multistage phase separation, plating, inter/intra-particle lithium exchange and plated lithium back-intercalation phenomena. A strong dependence of intra-particle lithiation heterogeneity on the particle size, shape, orientation, surface condition and C-rate at the particle level is observed, which leads to early onset of plating spatially resolved by a 3D image-based phase-field model. Moreover, we highlight the distinct relaxation processes at different state-of-charges (SOCs), wherein thermodynamically unstable graphite particles undergo a drastic intra-particle lithium redistribution and inter-particle lithium exchange at intermediate SOCs, whereas the electrode equilibrates much slower at low and high SOCs. These physics-based insights into the distinct SOC-dependent relaxation efficiency provide new perspective towards developing advanced fast charge protocols to suppress plating and shorten the constant voltage regime.

Computer-Vision-Based Approach to Classify and Quantify Flaws in Li-Ion Electrodes.

X-ray computed tomography (X-ray CT) is a non-destructive characterization technique that in recent years has been adopted to study the microstructure of battery electrodes. However, the often manual and laborious data analysis process hinders the extraction of useful metrics that can ultimately inform the mechanisms behind cycle life degradation. This work presents a novel approach that combines two convolutional neural networks to first locate and segment each particle in a nano-CT LiNiMnCoO2 (NMC) electrode dataset, and successively classifies each particle according to the presence of flaws or cracks within its internal structure. Metrics extracted from the computer vision segmentation are validated with respect to traditional threshold-based segmentation, confirming that flawed particles are correctly identified as single entities. Successively, slices from each particle are analyzed by a pre-trained classifier to detect the presence of flaws or cracks. The models are used to quantify microstructural evolution in uncycled and cycled NMC811 electrodes, as well as the number of flawed particles in a NMC622 electrode. As a proof-of-concept, a 3-phase segmentation is also presented, whereby each individual flaw is segmented as a separate pixel label. It is anticipated that this analysis pipeline will be widely used in the field of battery research and beyond.

The effect of wavelength on the variability of the flash visual evoked potential P2: A potential biomarker for mild cognitive impairment and Alzheimer's dementia.

As the number of individuals diagnosed with amnestic mild cognitive impairment (aMCI) and Alzheimer's dementia (AD) increases, a need exists for early detection and treatment of the disorders. A recent review of the literature conducted by Arruda et al. (2020) revealed that the latency of the flash visual-evoked potential-P2 (FVEP-P2) may possess pathognomic information that may assist in the early detection and treatment of each disease. Unfortunately, while group differences in latency are robust, the ability to discriminate between individuals remains difficult due to the natural variability associated with the FVEP-P2 latency. In the current investigation, we examine the role of wavelength of light in the production of the FVEP-P2, with the goal of reducing the variability associated with the FVEP-P2 latency and improving the diagnostic accuracy of the FVEP-P2 evaluation. METHOD: Twenty-four healthy individuals (11 males and 13 females), ages 18 to 36 years (M = 25.00, SD = 5.60), participated in this investigation. Each participant experienced five blocks of 100 strobe flashes (or trials) under two different light conditions (blue filtered light and polychromatic white light) with their eyes closed. The FVEP-P2 associated with each trial was identified and the latency and amplitude of each component was calculated. RESULT: The results of several repeated measures analysis of variance revealed no statistically significant differences in intra- and inter-individual variability associated with the P2 latency or amplitude. However, there was a significant difference in the amplitude of the P2 produced by the two lights, with blue filtered light producing significantly lower amplitudes than the polychromatic white light. CONCLUSION: The results of the present investigation suggest that while imperfect, the current practice of employing polychromatic white light in the production of the FVEP-P2 remains the gold standard and that additional methods of reducing the natural variability of the P2 need to be developed if the FVEP-P2 latency is to be used as a biomarker.

Photomodulated rayleigh scattering of single semiconductor nanowires: probing electronic band structure.

The internal electronic structures of single semiconductor nanowires can be resolved using photomodulated Rayleigh scattering spectroscopy. The Rayleigh scattering from semiconductor nanowires is strongly polarization sensitive which allows a nearly background-free method for detecting only the light that is scattered from a single nanowire. While the Rayleigh scattering efficiency from a semiconductor nanowire depends on the dielectric contrast, it is relatively featureless as a function of energy. However, if the nanowire is photomodulated using a second pump laser beam, the internal electronic structure can be resolved with extremely high signal-to-noise and spectral resolution. The photomodulated Rayleigh scattering spectra can be understood theoretically as a first derivative of the scattering efficiency that results from a modulation of the band gap and depends sensitively on the nanowire diameter. Fits to spectral lineshapes provide both the band structure and the diameter of individual GaAs and InP nanowires under investigation.