Suppr超能文献

来自可回收野葛的杂原子掺杂纳米多孔碳及其对氧还原和析氢反应的双重活性。

Heteroatom-doped nanoporous carbon from recyclable lobata and its dual activities for oxygen reduction and hydrogen evolution reactions.

作者信息

Lu Wen-Chao, Zhu Zi-Chun, Hou Bei-Hua, Zhang Hai-Xia, Liao Min-Ji, Wu Zhen-Yu, Chen Ping

机构信息

School of Chemistry and Chemical Engineering, Anhui University Hefei Anhui 230601 P. R. China

School of Chemistry and Materials Engineering, Chizhou University Chizhou Anhui 247000 P. R. China.

出版信息

RSC Adv. 2018 Jul 5;8(43):24392-24398. doi: 10.1039/c8ra03572e. eCollection 2018 Jul 2.

Abstract

Many efficient and non-precious metal catalysts for oxygen reduction or hydrogen evolution reactions have been developed, but bifunctional catalysts for both oxygen reduction reaction and hydrogen evolution reactions are seldom reported despite their advantages. Herein, we designed the bulk preparation of heteroatom-doped nanoporous carbon catalysts using widely available and recyclable lobata powder as the carbon source. The typical product was N, P and Fe Tri-doped nano-porous carbon (N,P,Fe-NPC) with high surface area (BET surface area of 776.68 m g and electrochemical surface area of 55.0 mF cm). The typical N,P,Fe-NPC sample simultaneously exhibited high activities for oxygen reduction and hydrogen evolution reactions. Because of the high surface area and the tri-doping of N, P and Fe elements, the prepared material may have applications in other fields such as gas uptake, sensors, sewage treatment, and supercapacitors. The suggested approach is low-cost, simple and readily scalable.

摘要

人们已经开发出许多用于氧还原或析氢反应的高效且非贵金属催化剂,然而,尽管具有优势,但用于氧还原反应和析氢反应的双功能催化剂却鲜有报道。在此,我们设计了以广泛可得且可回收的羽扇豆粉为碳源,大量制备杂原子掺杂的纳米多孔碳催化剂。典型产物是具有高表面积(BET表面积为776.68 m²/g,电化学表面积为55.0 mF/cm²)的N、P和Fe三掺杂纳米多孔碳(N,P,Fe-NPC)。典型的N,P,Fe-NPC样品同时展现出对氧还原和析氢反应的高活性。由于高表面积以及N、P和Fe元素的三掺杂,所制备的材料可能在其他领域如气体吸附、传感器、污水处理和超级电容器等方面具有应用前景。所提出的方法成本低、操作简单且易于扩大规模。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e3ef/9082073/c2d731f15f77/c8ra03572e-s1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验