Biological Neural Network-Inspired Micro/Nano-Fibrous Carbon Aerogel for Coupling Fe Atomic Clusters With Fe-N4 Single Atoms to Enhance Oxygen Reduction Reaction

IF 12.1 2区 材料科学 Q1 CHEMISTRY, MULTIDISCIPLINARY Small Pub Date : 2025-03-05 DOI:10.1002/smll.202500419
Jiaojiao Sun, Mengxia Shen, A-jun Chang, Shiqiang Cui, Huijuan Xiu, Pengbo Wang, Xia Li, Yonghao Ni
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Abstract

Nitrogen-coordinated metal single atoms catalysts, especially with M-N4 configuration confined within the carbon matrix, emerge as a frontier of electrocatalytic research for enhancing the sluggish kinetics of oxygen reduction reaction (ORR). Nevertheless, due to the highly planar D4h symmetry configuration in M-N4, their adsorption behavior toward oxygen intermediates is limited, undesirably elevating the energy barriers associated with ORR. Moreover, the structural engineering of the carbon substrate also poses significant challenges. Herein, inspired by the biological neural network (BNN), a reticular nervous system for high-speed signal processing and transmitting, a comprehensive structural biomimetic strategy is proposed for tailoring Fe-N4 single atoms (Fe SAs) coupled with Fe atomic clusters (Fe ACs) active sites, which are anchored onto chitosan microfibers/nanofibers-based carbon aerogel (CMNCA-FeSA+AC) with continuous conductive channels and an oriented porous architecture. Theoretical analysis reveals the synergistic effect of Fe SAs and Fe ACs for optimizing their electronic structures and expediting the ORR. The ingenious biomimetic strategy will shed light on the topology engineering and structural optimization of efficient electrocatalysts for advanced electrochemical energy conversion devices.

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生物神经网络激发的微/纳米纤维碳气凝胶用于Fe原子簇与Fe- n4单原子的耦合以增强氧还原反应
氮配位金属单原子催化剂,特别是M-N4构型限制在碳基体内的金属单原子催化剂,已成为电催化研究的前沿,以提高氧还原反应(ORR)的缓慢动力学。然而,由于M-N4中高度平面的D4h对称构型,它们对氧中间体的吸附行为受到限制,从而不利地提高了与ORR相关的能垒。此外,碳基板的结构工程也提出了重大挑战。本文受生物神经网络(BNN)这一用于高速信号处理和传输的网状神经系统的启发,提出了一种综合结构仿生策略,将Fe- n4单原子(Fe SAs)与Fe原子团簇(Fe ACs)活性位点结合,并将其固定在具有连续导电通道和定向多孔结构的壳聚糖微纤维/纳米纤维基碳气凝胶(CMNCA-FeSA+AC)上。理论分析表明,Fe - sa和Fe - ACs在优化其电子结构和加速ORR方面具有协同作用。这种巧妙的仿生策略将为先进的电化学能量转换装置的高效电催化剂的拓扑工程和结构优化提供启示。
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来源期刊
Small
Small 工程技术-材料科学:综合
CiteScore
17.70
自引率
3.80%
发文量
1830
审稿时长
2.1 months
期刊介绍: Small serves as an exceptional platform for both experimental and theoretical studies in fundamental and applied interdisciplinary research at the nano- and microscale. The journal offers a compelling mix of peer-reviewed Research Articles, Reviews, Perspectives, and Comments. With a remarkable 2022 Journal Impact Factor of 13.3 (Journal Citation Reports from Clarivate Analytics, 2023), Small remains among the top multidisciplinary journals, covering a wide range of topics at the interface of materials science, chemistry, physics, engineering, medicine, and biology. Small's readership includes biochemists, biologists, biomedical scientists, chemists, engineers, information technologists, materials scientists, physicists, and theoreticians alike.
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