Microstructure Evolution and Its Correlation with Performance in Nitrogen-Containing Porous Carbon Prepared by Polypyrrole Carbonization: Insights from Hybrid Calculations

Materials

Lele Sun¹  Shanshan Li²  Xinge Wu²  Xiangying Meng²  Fang Bian³  Gaowu Qin³  Hongwei Yang⁴ 

[1] College of Information Science and Engineering, Northeastern University, Shenyang 110819, China;College of Sciences, Northeastern University, Shenyang 110819, China;Key Laboratory for Anisotropy and Texture of Materials (MoE), School of Materials Science and Engineering, Northeastern University, Shenyang 110819, China;State Key Laboratory of Advanced Technologies for Comprehensive Utilization of Platinum Metals, Kunming Precious Metals New Materials Technology Co., Ltd., Kunming 650106, China;

关键词: nitrogen-containing porous carbon;    carbonization;    polypyrrole;    machine learning;    reactive molecular dynamics;   

DOI  :  10.3390/ma15103705

来源: DOAJ

【 摘 要 】

The preparation of nitrogen-containing porous carbon (NCPC) materials by controlled carbonization is an exciting topic due to their high surface area and good conductivity for use in the fields of electrochemical energy storage and conversion. However, the poor controllability of amorphous porous carbon prepared by carbonization has always been a tough problem due to the unclear carbonation mechanism, which thus makes it hard to reveal the microstructure–performance relationship. To address this, here, we comprehensively employed reactive molecular dynamics (ReaxFF-MD) simulations and first-principles calculations, together with machine learning technologies, to clarify the carbonation process of polypyrrole, including the deprotonation and formation of pore structures with temperature, as well as the relationship between microstructure, conductance, and pore size. This work constructed ring expressions for PPy thermal conversion at the atomic level. It revealed the structural factors that determine the conductivity and pore size of carbonized products. More significantly, physically interpretable machine learning models were determined to quantitatively express structure factors and performance structure–activity relationships. Our study also confirmed that deprotonation preferentially occurred by desorbing the dihydrogen atom on nitrogen atoms during the carbonization of PPy. This theoretical work clearly reproduces the microstructure evolution of polypyrrole on an atomic scale that is hard to do via experimentation, thus paving a new way to the design and development of nitrogen-containing porous carbon materials with controllable morphology and performance.

【 授权许可】

Unknown