alkali-metal intercalation in disordered carbon anode materials JMCA2019

A dataset created as part of a combination DFT-ML approach to study three alkali metals (K, Li, Na) in model carbon systems at a range of densities and degrees of disorder. The purpose of the study was to investigate the properties of alkali metals in hard (non-graphitising) and nanoporous carbons as potential anode materials for battery technology.

本数据集系结合密度泛函理论-机器学习（DFT-ML）方法研制，旨在研究三种碱金属（钾、锂、钠）在模型碳系中，于不同密度和杂乱程度下的性质。该研究旨在探讨碱金属在硬碳（非石墨化碳）和纳米多孔碳中的特性，以评估其作为电池技术潜在阳极材料的可能性。