Machine learning technology was used to design a carbonaceous supercapacitor material that stores four times more energy than the best commercial material available. The modeling system tested by researchers from U.S. Oak Ridge National Laboratory, University of California-Riverside, University of Tennessee and U.S. Ames National Laboratory predicted that the highest capacitance for a carbon electrode would be 570 farads per gram if the carbon was co-doped with oxygen and nitrogen.

Based on this finding, an extremely porous doped carbon was designed that would provide huge surface areas for interfacial electrochemical reactions. The material was synthesized as an oxygen-rich carbon framework for storing and transporting charge. The carbon was activated to generate more pores and add functional chemical groups at sites for oxidation or reduction reactions. The process applied uses sodium amide as the activation agent at about 600° C, creating more active sites than the hotter industrial processes conventionally used.

Analysis of electrolyte transport in the carbon pores by quasielastic neutron scattering revealed the electrolyte moved at different speeds: quickly in the mesopores and slowly in the micropores. Modified step potential electrochemical spectroscopy also demonstrated that mesopores doped with oxygen and nitrogen contribute most to the overall capacitance.

According to the research published in Nature Communications, the synthesized material had a capacitance of 611 farads/gram, four times that of a typical commercial material. The surface area was among the highest recorded for carbonaceous materials, exceeding 4,000 m²/g and is attributed to a combination of mesopores in the 2 nm to 50 nm range and micropores tinier than 2 nm.