WeChat Mini Program
Old Version Features

Engineering Unsymmetrically Coordinated Fe Sites Via Heteroatom Pairs Synergetic Contribution for Efficient Oxygen Reduction.

SMALL(2023)

Univ Sci & Technol China

Cited 12|Views30
Abstract
Single-atom Fe catalysts are considered as the promising catalysts for oxygen reduction reaction (ORR). However, the high electronegativity of the symmetrical coordination N atoms around Fe site generally results in too strong adsorption of *OOH intermediates on the active site, severely limiting the catalytic performance. Herein, a "heteroatom pair synergetic modulation" strategy is proposed to tailor the coordination environment and spin state of Fe sites, enabling breaking the shackles of unsuitable adsorption of intermediate products on the active centers toward a more efficient ORR pathway. The unsymmetrically Co and B heteroatomic coordinated Fe single sites supported on an N-doped carbon (Fe─B─Co/NC) catalyst perform excellent ORR activity with high half-wave potential (E1/2 ) of 0.891 V and a large kinetic current density (Jk ) of 60.6 mA cm-2 , which is several times better than those of commercial Pt/C catalysts. By virtue of in situ electrochemical impedance and synchrotron infrared spectroscopy, it is observed that the optimized Fe sites can effectively accelerate the evolution of O2 into the *O intermediate, overcoming the sluggish O─O bond cleavage of the *OOH intermediate, which is responsible for fast four-electron reaction kinetics.
More
Translated text
Key words
asymmetric coordination,electrocatalysts,in situ electrochemical impedance,in situ synchrotron infrared spectroscopy,ORR
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined