Supercapacitor auto analyser: An automated data analysis software for supercapacitor characterization

Nenhuma Miniatura disponível




Boratto, Miguel H. [UNESP]
Lima, João V.M. [UNESP]
Malliaras, George G.
Graeff, Carlos F.O. [UNESP]

Título da Revista

ISSN da Revista

Título de Volume



High-performance supercapacitors (SCs) with high power, energy, and long-life cycles, are essential for innovating wearable and portable electronics as extensively reported in literature. The Web of Science shows more than 23,000 papers published since 2018 with the topic ‘Supercapacitor’, number that keep growing, from 732 papers per year in 2012 to an average of 4651 papers per year since 2018. However, the establishment of performance metrics on the reported values should be achieved to reduce inconsistencies in their real performances. For that reason, we developed the Supercapacitors Auto Analyser (SCAA) program for SCs data analysis to support the community to establish performance metrics for SC devices, with standard terms, equations, and units. The SCAA generates important graphs with the SCs key properties and electrochemical performance such as capacitance, energy, power, coulombic efficiency (CE), equivalent series resistance (ESR), drop potential (Vdrop), cycling stability, and time constant. These results are calculated from common data generated by potentiostat on SCs characterization such as cyclic voltammetry (CV), galvanostatic charge–discharge (GCD), and electrochemical impedance spectroscopy (EIS). With appropriate inputs, the SCAA provides as many as 50 graphs with accurate normalizations by mass, area, or volume in a few minutes. This automation of data analysis is packed in a software made available to the community in the supplementary materials and website



Data analysis, Key parameters, Metrics, Normalization, Supercapacitors

Como citar

Journal of Energy Storage, v. 63.