materialscloud:2024.73
Published May 14, 2024 | Version v1
Dataset Open

FINALES - Electrolyte optimization for maximum conductivity and for maximum cycle life

Creators

  • 1. Department of Energy Conversion and Storage, Technical University of Denmark (DTU), 2800 Kgs. Lyngby, Denmark
  • 2. Helmholtz-Institut Ulm (HIU), Helmholtzstr. 11, 89081 Ulm
  • 3. Technical University of Munich, Germany; TUM School of Natural Sciences, Department of Chemistry, Chair of Digital Catalysis; Munich Institute of Robotics and Machine Intelligence (MIRMI); Munich Data Science Institute MDSI
  • 4. Theory and Simulation of Materials (THEOS) and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
  • 5. Dassault Systèmes, 51063 Cologne, Germany
  • 6. Present address: Technical University of Munich, Germany; TUM School of Natural Sciences, Department of Chemistry, Chair of Digital Catalysis; Munich Institute of Robotics and Machine Intelligence (MIRMI); Munich Data Science Institute MDSI
  • 7. Laboratory for Materials Simulations (LMS), Paul Scherrer Institut (PSI), CH-5232 Villigen PSI, Switzerland
  • 8. SINTEF Industry, Battery Technology, 7034 Trondheim, Norway
  • 9. Department of Materials Chemistry, National Institute of Chemistry, Hajdrihova 19, 1000, Ljubljana, Slovenia

* Contact person

Description

This study investigates an electrolyte system composed of lithium hexafluorophosphate (LiPF6), ethylene carbonate (EC) and ethyl methyl carbonate (EMC). For the assembly of full cells, electrodes based on graphite and lithium nickel dioxide (LNO) are used. This work provides insight into the similarity of formulations of an electrolyte optimized for maximum conductivity and another one optimized for maximum cycle life are expected to be in this chemical system. The goal is to assess whether it is promising to target research efforts on finding an electrolyte formulation within this chemical space which can fulfill both requirements. A campaign utilizing the latest version of FINALES is designed to determine conductivity values and predict end of life for various electrolyte formulations containing the aforementioned chemicals. The campaigns were able to reproducibly identify regions of high ionic conductivity of the aforementioned chemical composition. The ML methodology applied for the EOL optimisation allowed accelerated early life-time predictions.

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References

Journal reference (Published peer reviewed article producing the data in question)
M. Vogler, S. K. Steensen, F. F. Ramírez, L. Merker, J. Busk, J. M. Carlsson, L. H. Rieger, B. Zhang, F. Liot, G. Pizzi, F. Hanke, E. Flores, H. Hajiyani, S. Fuchs, A. Sanin, M. Gaberšček, I. E. Castelli, S. Clark, T. Vegge, A. Bhowmik, H. S. Stein, Advanced Energy Materials 14, 2403263 (2024), doi: 10.1002/aenm.202403263

Preprint (Preprint describing the optimisations performed and the developed FINALES framework)
Monika Vogler, Simon K. Steensen, Francisco Fernando Ramirez, Leon Merker, Jonas Busk, Johan M. Carlsson, Laura Hannemose Rieger, Bojing Zhang, François Liot, Giovanni Pizzi, Felix Hanke, Eibar Flores, Hamidreza Hajiyan, Stefan Fuchs, Alexey Sanin, Miran Gaberšček, Ivano E. Castelli, Simon Clark, Tejs Vegge, Arghya Bhowmik and Helge S. Stein, 2024 (in preperation), doi: 10.26434/chemrxiv-2024-vfq1n

Software (The source code for the developed optimisation server framework)
https://github.com/BIG-MAP/FINALES2, doi: 10.5281/zenodo.10987727

Software (The source code for the developed optimisation server framework)
https://github.com/BIG-MAP/FINALES2

Software (Please refer to the definitions of the schemas underlying this dataset available at https://doi.org/10.5281/zenodo.11142866 for further information about the content of the fields and its units)
https://github.com/BIG-MAP/FINALES2_schemas/releases/tag/v1.0.1, doi: 10.5281/zenodo.11142866