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Revealing the operando ORR mechanism of single-atom catalysts anchored in nanobowl structures for advanced hydroxide exchange membrane fuel cells

Chemical Engineering Journal, 528 (2026) 172462 (Elsevier) | DOI: 10.1016/j.cej.2025.172462
Authors:Sun-Tang Chang, Hui-Xin Liu, Yi-Ching Chu, Ying-Rui Lu, Chen-Hao Wang*

📄 Abstract

This study utilizes advanced operando techniques, focusing on wavelet transform (WT), Raman spectroscopy, and electrochemical impedance spectroscopy (EIS), to unravel the atomic-scale mechanism of the oxygen reduction reaction (ORR) in a novel Fe single-atom nanobowl (Fe-SANb) catalyst. By integrating operando X-ray absorption spectroscopy (XAS), WT, Raman, and EIS analyses, this work reveals the dynamic interactions between Fe active sites and oxygen intermediates under realistic operating conditions. The operando Raman spectra clearly display the emergence of the O–Fe–N stretching band, confirming the oxygen bonding process. The Tafel plot demonstrates the excellent catalytic activity of Fe-SANb, showing a low slope of 78.85 mV dec⁻¹. The Fe-SANb catalyst achieves a peak power density of 554.2 mW cm⁻² and retains 95% of its performance after 30,000 cycles, rivaling commercial Pt/C catalysts.

🔬 Five Key Findings

1
3% Fe is optimal: onset potential 0.96 V, Tafel slope 78.85 mV dec⁻¹, n ≈ 3.95 (4-electron pathway).
2
Operando Raman directly observes O–Fe–N stretching at 598 cm⁻¹ at 1.0 V vs. RHE, confirming O bonding on Fe-N active sites.
3
WT-EXAFS captures transient Fe-O-O interaction (~3 Å⁻¹), revealing potential-dependent ORR mechanism.
4
Peak power density 554.2 mW cm⁻²; 95% retained after 30,000 cycles, 2× Pt/C durability.
5
Graphitic-N + thiophene-S synergy optimizes Fe-N electronic structure and O₂ adsorption stability.

📊 Key Figures

Figure 1: Structural and morphological characterization of Fe-SANb catalyst, showing Fe single atoms uniformly dispersed on nitrogen-doped carbon support in nanobowl architecture.
Figure 2: ORR performance and durability of Fe-SANb catalyst: polarization curves, power density curves, and performance comparison before and after 30,000 cycles.