A graphical abstract of the technique. Credit: A. Kabiraj, S. Mahapatra /Cell Reports Physical Science 2022
Engineers have developed a computer-based technique that can screen thousands of two-dimensional materials, and identify those with potential for making highly efficient energy-storage devices1.
The approach quickly assesses potential for applications in a lithium-ion battery or a supercapacitor or both — allowing for a hybrid system suitable for powering electric vehicles, say the researchers from the Indian Institute of Science in Bangalore.
Previous experiments and theoretical studies had only tested a small fraction of two-dimensional materials. Despite their tremendous potential, no high throughput studies had attempted to predict the materials’ energy-storage capacity.
The team, which included electronic engineers’, Santanu Mahapatra and Arnab Kabiraj, developed a high-throughput computer code and a machine-learning model to analyse thousands of two-dimensional materials for producing electrodes. Their method revealed several potential electrode materials, such as silicene and vanadium sulfide, for lithium-ion battery and supercapacitor use.
