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Galvanostatic performance of single-particle Li-ion battery materials: a rapid diagram diagnosis assisted by a Python / C++ software

Andrés Ruderman, Edgardo Maximiliano Gavilán-Arriazu, Francisco Fernandez, Yair Ein-Eli, Ezequiel P.M. Leiva

Research output: Contribution to journalArticlepeer-review

Abstract

Herein, a novel open-source software for predicting the performance of single particles of electrode materials under galvanostatic charging conditions is presented. The model improves previous work by incorporating different thermodynamic approaches to describe the interaction between intercalated ions, and the software provides tools for fitting different kinetic parameters and generating potential/capacity profiles or concentration/distance profiles to be analyzed. These features allow for detailed studies of the factors limiting the charging rate of active materials in which ions are intercalated. The diagnostic diagram is constructed through simulations of the capacity reached for a given potential cut-off, represented in the domain of two dimensionless parameters. These parameters represent kinetic and particle-size limitations for Li-ion storage. The present tool aims to facilitate the analysis of single-particle experiments, taking advantage of two different computational languages, popular in scientific computing: Python and C++. The software integrates a Python interface, for user-friendly interaction, with a C++ computational core allowing parallelization via OpenMP, for high computational performance. The software supports different thermodynamic approaches: Langmuir-Frumkin intercalation model and equilibrium potentials derived from experimental data. The inclusion of experimental insertion isotherms allows for the construction of realistic capacity diagrams. The open-source software is available at https://github.com/fernandezfran/galpynostatic/.

Original languageEnglish
Article number015946
JournalPHYSICA SCRIPTA
Volume100
Issue number1
DOIs
StatePublished - 1 Jan 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • lithium-ion batteries
  • materials diagnosis
  • single-particle
  • software

All Science Journal Classification (ASJC) codes

  • Condensed Matter Physics
  • Atomic and Molecular Physics, and Optics
  • Mathematical Physics

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