fig2

Machine learning-assisted prediction, screen, and interpretation of porous carbon materials for high-performance supercapacitors

Figure 2. Box-normal plots of the data distributions for each parameter of collected data. (A) SC of PCMs; (B) Current density (CD) tested in a three-electrode system; (C) SSA of PCMs; (D) Total pore volume (Vt) of PCMs; (E and F) Contents of nitrogen (N), oxygen (O) in PCMs; (G-I) Contents of N-containing functional groups [pyridine nitrogen (N-6), pyrrole nitrogen (N-5), and graphitic nitrogen (N-Q)]; (J-L) Contents of O-containing functional groups [carbonyl-O group (C=O, O-I), hydroxyl-O/ether-O group (C-OH/C-O-C, O-II), and carboxyl-O group (-COOH, O-III)]. SC: Specific capacitance; PCMs: porous carbon materials; CD: current density; SSA: specific surface area.

Journal of Materials Informatics
ISSN 2770-372X (Online)
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