Machine Learning Benchmarks for Classiﬁcation of Electrochemical Impedance Spectra

doi:doi:10.57702/2ay80nvw

Machine Learning Benchmarks for Classiﬁcation of Electrochemical Impedance Spectra

The EIS data set, Z, associated with this article was created by QS. It comprises approximately 9,300 synthetic impedance spectra, z ∈ Z that are vectors of impedances, z ∈ Cn.

BibTex:

@dataset{Joachim_Schaeffer_and_Paul_Gasper_and_Masaki_Adachi_and_Raymond_Gasper_and_Esteban_Garcia-Tamayo_and_Juan_Pablo_Gaviria-Cardona_and_Simon_Montoya-Bedoya_and_Anoushka_Bhutani_and_Andrew_Schiek_and_Rhys_Goodall_and_Rolf_Findeisen_and_Richard_D_Braatz_and_Simon_Engelke_2024,
    abstract = {The EIS data set, Z, associated with this article was created by QS. It comprises approximately 9,300 synthetic impedance spectra, z ∈ Z that are vectors of impedances, z ∈ Cn.},
    author = {Joachim Schaeffer and Paul Gasper and Masaki Adachi and Raymond Gasper and Esteban Garcia-Tamayo and Juan Pablo Gaviria-Cardona and Simon Montoya-Bedoya and Anoushka Bhutani and Andrew Schiek and Rhys Goodall and Rolf Findeisen and Richard D. Braatz and Simon Engelke},
    doi = {10.57702/2ay80nvw},
    institution = {No Organization},
    keyword = {'classification', 'electrochemical impedance spectroscopy', 'equivalent circuit model', 'machine learning'},
    month = {dec},
    publisher = {TIB},
    title = {Machine Learning Benchmarks for Classiﬁcation of Electrochemical Impedance Spectra},
    url = {https://service.tib.eu/ldmservice/dataset/machine-learning-benchmarks-for-classi-cation-of-electrochemical-impedance-spectra},
    year = {2024}
}