Perspectives on manufacturing simulations of Li-S battery cathodes
Lithium-sulfur batteries (LSBs) are one of the main contenders for next generation post lithium-ion batteries (LIBs). As the process of scientific discovery advances, many of the challenges that prevent the commercial deployment of LSBs, especially at the most fundamental materials level, are slowly...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/268734 |
| Acceso en línea: | http://hdl.handle.net/10261/268734 https://api.elsevier.com/content/abstract/scopus_id/85126675198 |
| Access Level: | acceso abierto |
| Palabra clave: | Computational modeling Electrode mesostructure Lithium sulfur batteries Manufacturing |
| Sumario: | Lithium-sulfur batteries (LSBs) are one of the main contenders for next generation post lithium-ion batteries (LIBs). As the process of scientific discovery advances, many of the challenges that prevent the commercial deployment of LSBs, especially at the most fundamental materials level, are slowly being addressed. However, batteries are complex systems that require not only the identifcation of suitable materials, but also require the knowledge of how to assemble and manufacture all the components together in order to obtain an optimally working battery. This is not a simple task, as battery manufacturing is a multi-stepped, multi-parameter, highly correlated process, where many parameters compete, and deep knowledge of the systems is required in order to achieve the optimal manufacturing conditions, which has already been shown in the case of LIBs. In these regards, manufacturing simulations have proven to be invaluable in order to advance in the knowledge of this exciting and technologically relevant field. Thus, in this work, we aim at providing future perspectives and opportunities that we think are interesting in order to create digital twins for the LSB manufacturing process. We also provide comprehensive and realistic ways in which already existing models could be adapted to LSBs in the short-term, and which are the challenges that might be found along the way. |
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