Fabrication of FeP2/C/CNTs@3D interconnected graphene aerogel composite for lithium-ion battery anodes and the electrochemical performance evaluation using machine learning

Abstract

Featuring low cost and high theoretical capacity, phosphorus-rich iron diphosphides (FeP2) have emerged as excellent anode candidates for lithium-ion batteries. However, the typical chemical synthses involving high temperatures and toxic gases have restricted the mass production of FeP2. We now report a FeP2/C/CNTs@3D interconnected graphene aerogel composite synthesized by ball milling and low temperature heat treatment. Because of the unique microstructure and synergistic effect between well-dispersed FeP2 particles and graphene aerogel, the as-prepared FeP2/C/CNTs@GA-2.5% displays excellent lithium storage performance in terms of reversible capacity (886 mA h g−1 at 0.1 A g−1), cycling stability (476 mA h g−1 at 2 A g−1 even after 1000 cycles), and rate capability (685 mA h g−1 at 5 A g−1). Machine learning methods (decision tree and random forest algorithms) prove effective in evaluating and predicting electrochemical performance of the electrode materials.