Data of physical and electrochemical characteristics of calendered NMC622 electrodes and lithium-ion cells at pilot-plant battery manufacturing

Mona Faraji-Niri; Marc Fransic V Hidalgo; Geanina Apachitei; Daniela Dogaru; Michael Lain; Mark Copley; James Marco

doi:10.1016/j.dib.2023.109798

Data of physical and electrochemical characteristics of calendered NMC622 electrodes and lithium-ion cells at pilot-plant battery manufacturing

Data Brief. 2023 Nov 10:52:109798. doi: 10.1016/j.dib.2023.109798. eCollection 2024 Feb.

Authors

Mona Faraji-Niri^{1

2}, Marc Fransic V Hidalgo^{1

2}, Geanina Apachitei^{1

2}, Daniela Dogaru^{1

2}, Michael Lain^{1

2}, Mark Copley^{1

2}, James Marco^{1

2}

Affiliations

¹ Warwick Manufacturing Group, University of Warwick, CV4 7AL Coventry, UK.
² The Faraday Institution, Quad One, Harwell Science and Innovation Campus, Didcot, UK.

Abstract

The data reported here was prepared to study the effects of calendering process on NMC622 cathodes using a 3-3-2 full factorial design of experiments. The data set consists of 18 unique combinations of calender roll temperature (85 °C, 120 °C, or 145 °C), electrode porosity (30%, 35%, or 40%), and electrode mass loading (120 g/m² or 180 g/m²). The reported physical characteristics of the electrodes include thickness, coating weight, maximum tensile strength, and density. The electrochemical performances of the electrodes were obtained by testing coin cells. In this context, 54 half-cells were produced, 3 per each calendering experiment to ensure repeatability and reliability of the results. The responses of interest included, charge energy capacity at C/2, C/5, discharge energy capacity at C/20, C/5, C/2, C, 2C, 5C, 10C, gravimetric capacity (charge at C/2, C/5, discharge at C/20, C/5, C/2, C, 2C, 5C, 10C), volumetric capacity (charge at C/2, C/5, discharge at C/20, C/5, C/2, C, 2C, 5C, 10C), rate performance (5C:0.2C), area specific impedance (at 10% to 90% state of charge (SoC) in 10 breakpoints), long-term cycling capacity (charge at C/5 for 50 cycles, discharge at C/2 for 50 cycles), long-term cycling degradation (at C/2 during 50 cycles of charge and discharge), and cycling columbic efficiency (50 cycles of C/2 charge and discharge). The details of the experimental design that has led to this data as well as comprehensive statistical analysis, and machine learning-based models can be found in the recently published manuscripts by Hidalgo et al. and Faraji-Niri et al. [1,2].

Keywords: Battery cycling; Calendering process; Electrochemical characteristics; Electrode manufacturing; Lithium-ion battery; Machine learning; Pilot-plant; SEM/EDS images.