Engineering topics

Ayyaswamy, Abhinand

Publications and source records attributed to Ayyaswamy, Abhinand.

3 records

DOE OSTI2026

Crossover as Determinant for Safety and Performance Tradeoffs in Proton Exchange Membrane Water Electrolyzers

Hydrogen (H2) crossover is a pressing challenge constraining safe and efficient operation of proton exchange membrane water electrolyzers (PEMWEs) especially amongst strides to employ thinner membranes, which enables improved energy efficiency, and elevated cathode pressures, that reduces the energy burden on downstream compressors. Here, we develop a microstructure-aware multicomponent reactive-transport framework that resolves dissolved and gaseous H2 transport pathways and mechanistically links electrode architecture to crossover related safety and performance. We show that operability is co-governed by the cathode catalyst layer (CCL) and the anode porous transport layer (APTL) which sets the H2 crossover flux and the egress capacity respectively. Elevated Pt/C ratio in the CCL suppresses crossover flux by up to 23% while a higher APTL porosity lowers H2 in O2 fraction by 0.6% in the anode effluent. We condense the findings into (cathode pressure-current density) maps overlaid with safety limits and performance targets and ultimately define two safety-performance unified metrics to gauge the size and quality of the operating window. Given the push towards higher pressure and deeper turndown for renewable integration, this study provides mechanistic design guidance to prevent crossover-induced safety risks while preserving the desired performance.

Electrolysis↗

DOE OSTI2024

Evaluating Pressure‐dependent Discharge Behavior of Foil Versus In situ Plated Lithium Metal Anodes in Solid‐State Batteries

Abstract Anode‐free manufacturing of solid‐state batteries (SSBs) shows promise to maximize energy density by eliminating excess lithium (Li) and simplifying battery production. However, high reversibility during discharge (stripping of Li) is necessary for long‐lifetime SSBs with a limited Li reservoir. Further, the plastic flow of Li changes depending on the Li thickness, leading to possible differences in discharge performance under stack pressure. This work investigates the pressure‐dependent discharge performance of anode‐free manufactured SSBs with in situ plated Li and compares the performance to that of conventional thick Li foil cells. Distinct stripping behavior is observed at low pressures (0–1 MPa), where Li diffusivity and initial interfacial contact may control accessible capacity, compared to high pressures (3–10 MPa) where mechanical deformation of Li likely governs stripping behavior. Analysis of impedance spectra collected during stripping shows that additional stack pressure delays the formation of deep, as opposed to lateral, voids in the Li anode. These results provide insights to guide the transition from thick Li foil anodes to anode‐free manufactured SSBs.

Haslam, Catherine G.↗

DOE OSTI2024

Uncertainty quantification and propagation in lithium-ion battery electrodes using bayesian convolutional neural networks

The complex nature of manufacturing processes stipulates electrodes to possess high variability with increased heterogeneity during production. X-ray computed tomography imaging has proved to be critical in visualizing the complicated stochastic particle distribution of as-manufactured electrodes in lithium-ion batteries. However, accurate prediction of their electrochemical performance necessitates precise evaluation of kinetic and transport properties from real electrodes. Image segmentation that characterizes voxels to particle/pore phase is often meticulous and fraught with subjectivity owing to a myriad of unconstrained choices and filter algorithms. Here we utilize a Bayesian convolutional neural network to tackle segmentation subjectivity and quantify its pertinent uncertainties. Otsu inter-variance and Blind/Referenceless Imaging Spatial Quality Evaluator are used to assess the relative image quality of grayscale tomograms, thus evaluating the uncertainty in the derived microstructural attributes. We analyze how image uncertainty is correlated with the uncertainties and magnitude of kinetic and transport properties of an electrode, further identifying pathways of uncertainty propagation within microstructural attributes. The coupled effect of spatial heterogeneity and microstructural anisotropy on the uncertainty quantification of transport parameters is also understood. This work demonstrates a novel methodology to extract microstructural descriptors from real electrode images through quantification of associated uncertainties and discerning the relative strength of their propagation, thus facilitating feedback to manufacturing processes from accurate image based electrochemical simulations.

25 ENERGY STORAGE↗