Highly Efficient and Selective CO Electro-Reduction to HCOOH on Sn Particle-Decorated Polymeric Carbon Nitride.

ChemSusChem

State Key Laboratory of High Performance Ceramics and Superfine Microstructure, Shanghai Institute of Ceramics, Chinese Academy of Sciences, 1295 Dingxi Road, Shanghai, 200050, P. R. China.

Published: December 2020

Electrochemical conversion of CO into liquid fuels by efficient and earth-abundant catalysts is of broad interest but remains a great challenge in renewable energy production and environmental remediation. Herein, a Sn particle-decorated polymeric carbon nitride (CN) electrocatalyst was successfully developed for efficient, durable, and highly selective CO reduction to formic acid. High-resolution X-ray photoelectron spectroscopy confirmed that the metallic Sn particles and CN matrix are bound by strong chemical interaction, rendering the composite catalyst a stable structure. More notably, the electronic structure of Sn was well tuned to be highly electron-rich due to the electron transfer from N atoms of CN to Sn atoms via metal-support interactions, which favored the adsorption and activation of CO molecules, promoted charge transport, and thus enhanced the electrochemical conversion of CO . The composite electrocatalyst demonstrated an excellent Faradaic efficiency of formic acid (FE ) up to 96±2 % at the potential of -0.9 V vs. reversible hydrogen electrode, which remained at above 92 % during the electrochemical reaction of 10 h, indicating that the present Sn particle-decorated polymeric carbon nitride electrocatalyst is among the best in comparison with reported Sn-based electrocatalysts.

Download full-text PDF

Source
http://dx.doi.org/10.1002/cssc.202002184DOI Listing

Publication Analysis

Top Keywords

particle-decorated polymeric
12
polymeric carbon
12
carbon nitride
12
electrochemical conversion
8
nitride electrocatalyst
8
formic acid
8
highly efficient
4
efficient selective
4
selective electro-reduction
4
electro-reduction hcooh
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!