Structure–Property Relationships of Recycled Lithium-Ion Battery Cathodes: Microstructure Optimization Using Virtual Materials Testing
Source abstract
Abstract
The increasing demand for sustainable battery technologies requires effective recycling strategies for end-of-life lithium-ion battery cathodes. In this study, virtual materials testing, a well-established framework for modeling conventionally manufactured NMC-based cathodes, is applied to partially recycled cathodes. To this end, virtual cathodes consisting of mixtures of pristine and recycled NMC particles are utilized to systematically analyze structure–property relationships depending on mixing ratios and different spatial arrangement strategies. For this purpose, a stochastic 3D model is developed that is capable of generating virtual cathodes with arbitrary volume fractions of active materials and mixing ratios of pristine and recycled NMC particles. Particularly, the stochastic 3D model can mimic the different size distributions of pristine and recycled particles that are observed in image data. Additionally, the model allows the structuring of pristine and recycled NMC either uniformly mixed or layer-wise arranged, mimicking single- and dual-layer cathodes. Subsequently, a systematic computational analysis is conducted to assess the influence of increasing active material ratios of recycled particles, ranging from 0 % to 100 %, while maintaining a constant overall active material volume fraction. The impact of particle mixing on cathode performance is evaluated by examining transport-relevant geometrical descriptors and effective properties, such as geodesic tortuosity, specific surface area, and tortuosity factor.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advancements in Battery Materials · Advanced Battery Technologies Research · Recycling and Waste Management Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Stochastics, Ulm University, Helmholtzstraße 18, D-89069 Ulm, Germany
National Laboratory of the Rockies, 15013 Denver West Parkway, Golden, CO 80401, USA
Mines/NLR Advanced Energy Systems Graduate Program, Colorado School of Mines, Golden, CO 80401, USA
SDU Applied AI and Data Science Unit, University of Southern Denmark, Campusvej 55, DK-5230 Odense, Denmark
Funding
DOE’s Vehicle Technologies Office, Extreme Fast Charge, and Cell Evaluation of Lithium-ion Batteries Program
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