Simon K. Steensen^1*, Monika Vogler^2,3*, Francisco Fernando Ramirez^4*, Leon Merker^2*, Jonas Busk^1*, Johan M. Carlsson^5*, Laura Hannemose Rieger^1*, Bojing Zhang^2,6*, Francois Liot⁴, Giovanni Pizzi^4,7*, Felix Hanke^5*, Eibar Flores^8*, Hamidreza Hajiyani⁵, Stefan Fuchs², Alexey Sanin^2,6*, Miran Gaberšček^9*, Ivano E. Castelli^1*, Simon Clark^8*, Tejs Vegge^1*, Arghya Bhowmik^1*, Helge S. Stein^3*

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

* Corresponding authors emails: skste@dtu.dk, monika.vogler@kit.edu, ramirezfranciscof@gmail.com, leon.merker@kit.edu, jbusk@dtu.dk, johan.carlsson@3ds.com, lauri@dtu.dk, bojing.zhang@tum.de, giovanni.pizzi@psi.ch, felix.hanke@3ds.com, eibar.flores.cedeno@sintef.no, aleksei.sanin@tum.de, miran.gaberscek@ki.si, ivca@dtu.dk, simon.clark@sintef.no, teve@dtu.dk, arbh@dtu.dk, helge.stein@tum.de

DOI10.24435/materialscloud:qt-1s [version v1]

Publication date: May 14, 2024

How to cite this record

Simon K. Steensen, Monika Vogler, Francisco Fernando Ramirez, Leon Merker, Jonas Busk, Johan M. Carlsson, Laura Hannemose Rieger, Bojing Zhang, Francois Liot, Giovanni Pizzi, Felix Hanke, Eibar Flores, Hamidreza Hajiyani, Stefan Fuchs, Alexey Sanin, Miran Gaberšček, Ivano E. Castelli, Simon Clark, Tejs Vegge, Arghya Bhowmik, Helge S. Stein, FINALES - Electrolyte optimization for maximum conductivity and for maximum cycle life, Materials Cloud Archive 2024.73 (2024), https://doi.org/10.24435/materialscloud:qt-1s

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.

Materials Cloud sections using this data

Files

File name	Size	Description
FINALES (09_2023) Electrolyte Optimization for Maximum Conductivity and for Maximum Cycle Life.zip MD5md5:bc7eb8d7b741f8bba859ff3d280719cd	214.2 KiB	Server data for the singletask phase optimising conductivity
FINALES (11_2023) Electrolyte Optimization for Maximum Conductivity and for Maximum Cycle Life.zip MD5md5:68e6797a70b121baa18380215d55638a	8.8 MiB	Server data for the multitask phase optimising conductivity and EOL
FINALES (09_2023 to 12_2023) Electrolyte Optimization for Maximum Conductivity and for Maximum Cycle Life (Additional Data).zip MD5md5:98259a0defc0c5533e2ab855bee6d0e4	2.1 GiB	Additional data for the two optimisations phases. This addtional data was saved locally by the tenants and not saved/communicated through the FINALES server.
README.md MD5md5:18fd595d99f69720bd110ab83d578af4	5.6 KiB	Extended information for the optimisation campaigns including acknowledgements. Includes descriptions of the data format in the .zip files

License

Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

External references

Keywords

BIG-MAP Battery Electrolyte formulation End-of-lifetime ionic conductivity Material Acceleration Platform MAP electronic structure machine learning Experimental