4.6 Editorial Material

Perspectives on manufacturing simulations of Li-S battery cathodes

Journal

JOURNAL OF PHYSICS-ENERGY
Volume 4, Issue 1, Pages -

Publisher

IOP Publishing Ltd
DOI: 10.1088/2515-7655/ac4ac3

Keywords

lithium sulfur batteries; manufacturing; computational modeling; electrode mesostructure

Funding

  1. European Union through the European Research Council [772873]
  2. European Union [957189]
  3. Institut Universitaire de France
  4. Conseil regional des Hauts de France
  5. Universite Picardie Jules Verne under project name (OPERANDO)
  6. BATTERY 2030+ initiative [957213]
  7. European Research Council (ERC) [772873] Funding Source: European Research Council (ERC)

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Lithium-sulfur batteries are potential candidates for the next generation of batteries, and the challenges in their commercial deployment are gradually being addressed. Battery manufacturing is a complex process that requires in-depth knowledge of the system, and manufacturing simulations are invaluable in advancing this field.
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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