A mini-review of artificial intelligence techniques for predicting the performance of supercapacitors. (2022)

• Record Type: Journal Article
• Authors: Adekoya, Gbolahan Joseph; Adekoya, Oluwasegun Chijioke; Ugo, Ugonna Kingsley; Sadiku, Emmanuel Rotimi; Hamam, Yskandar; Ray, Suprakas Sinha
• Is Part Of: Materials today. Volume 62:(2022)Supplement 1
• Page Start: S184
• Page End: S188
• Publication Date: 2022
• Subjects: Artificial intelligence -- Machine learning -- Supercapacitor -- ANN -- Linear regression; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2022.05.079
• Languages: English
• ISSNs: 2214-7853

Abstract

Graphical abstract: Abstract: Supercapacitors are used to store and release electrical charges like batteries and conventional capacitors. Unlike conventional capacitors, they have higher capacitance and power density, and they charge faster than batteries can. Supercapacitors are mainly classified as hybrid supercapacitors, pseudocapacitors, and electrochemical double-layer capacitors. To predict the application behaviour and optimization of supercapacitors, artificial intelligence, specifically machine language is utilized more recently. Models based on artificial intelligence are less complicated and maybe accurate enough. This paper identifies machine language models that have been employed to predict the supercapacitors' performance.