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Synthesis of nitrogen, phosphoric‐codoped carbon nanosheets decorated with cobalt phosphide nanoparticles for boosting lithium storage behavior

Liyuan Liu, Hanwen Zhang, Qin Mu, Jianchao He, Shiqiang Li, Huiyu Jiang, Biao He, Xiaoyang Yang, Xueqin Sun, Xiubo Xie, Wei Du, Chuanxin Hou

2025Rare Metals41 citationsDOI

Abstract

Abstract Due to high theoretical specific capacity and excellent thermal stability, transition metal phosphides (TMPs) have emerged as highly promising candidates of anode materials for advancing lithium‐ion batteries. However, it remains confronted with significant challenges, including large volume expansion, low specific surface area and limited electron conductivity, which hinder their practical application in the field of energy storage. Herein, nitrogen, phosphoric‐codoped carbon nanosheets decorated with cobalt phosphide nanoparticles (CoP/N, P–C) are synthesized through a simple and environment‐friendly synthesis method demonstrating their potential as anode materials for lithium‐ion batteries. The element‐doped carbon matrix can enhance electrical conductivity, accelerate ion transport, improve the active sites, and buffer the volume expansion of CoP nanoparticles, collectively leading to significantly improved electrochemical performance. The prepared CoP/N, P–C electrodes present outstanding electrochemical performance, delivering a discharge specific capacity of 920 mAh g −1 after 100 cycles at 0.1 A g −1 and 686 mAh g −1 after 3,000 cycles even at 2.0 A g −1 . The quantitative kinetic analysis result reveals that pseudo‐capacitance dominates total capacity behavior (70.6% at 0.5 mV s −1 ). Furthermore, the galvanostatic intermittent titration technique (GITT) is applied to prove the super‐fast diffusion coefficient of the electrodes. This work provides a simplified and environmentally friendly method for effective modification of the comprehensive properties of transition metal phosphates.

Topics & Concepts

PhosphideMaterials scienceCobaltNanoparticleLithium (medication)Boosting (machine learning)Carbon fibersNanotechnologyChemical engineeringComposite materialMetallurgyComposite numberNickelComputer scienceEndocrinologyEngineeringMedicineMachine learningAdvancements in Battery MaterialsAdvanced Battery Materials and TechnologiesSupercapacitor Materials and Fabrication