2026-10-13T16:40:09Z https://www.scidb.cn/oai

10.57760/sciencedb.j00125.00213 2026-07-08T20:31:09Z

2026-07-08 A dataset ofMicroplastic-Derived Hierarchical Porous Carbon via Dual-Functional ZnO Engineering for High-Performance Supercapacitors with Machine Learning Insights doi:10.57760/sciencedb.j00125.00213 en The dataset presented in this deposit was generated through experiment/simulation/analysis workflow. The raw data were collected using electrochemical workstation, XRD, FTIR, SEM, UV–Vis, Origin, MATLAB, Python, etc., following standard experimental procedures described in the associated study. Microplastic waste; Porous carbon; ZnO nanoparticles; Machine learning; Supercapacitors Jai Kumar Honglei He Siting Wang Fangyuan Bai Xue Wang Zhuanpei Wang Xiaowei Yang RESTRICTED dataset Science Data Bank