Electrocatalytic reduction of nitrate to ammonia (NORR) is gaining attention for low carbon emissions and environmental protection. However, low ammonia production rate and poor selectivity have remained major challenges in this multi-proton coupling process. Herein, we report a facile strategy toward a novel Fe-based hybrid structure composed of Fe single atoms and FeC atomic clusters that demonstrates outstanding performance for synergistic electrocatalytic NORR. By synchrotron Fourier transform infrared spectroscopy and theoretical computation, we clarify that Fe single atoms serve as the active site for NORR, while FeC clusters facilitate HO dissociation to provide protons (*H) for continued hydrogenation reactions. As a result, the Fe-based electrocatalyst exhibits ammonia Faradaic efficiency of nearly 100%, with a corresponding production rate of 24768 μg h cm at -0.4 V vs RHE, exceeding most reported metal-based catalysts. This research provides valuable guidance toward multi-step reactions.
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http://dx.doi.org/10.1021/acs.nanolett.3c04049 | DOI Listing |
J Am Chem Soc
March 2025
Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-3290, United States.
Semiconductor devices often rely on high-purity materials and interfaces achieved through vapor- and vacuum-based fabrication methods, which can enable precise compositional control down to single atomic layers. Compared to groups IV and III-V semiconductors, hybrid perovskites (HPs) are an emergent class of semiconductor materials with remarkable solution processability and compositional variability that have facilitated rapid experimentation to achieve new properties and progress toward efficient devices, particularly for solar cells. Surprisingly, vapor deposition techniques for HPs are substantially less developed, despite the complementary benefits that have secured vapor methods as workhorse tools for semiconductor fabrication.
View Article and Find Full Text PDFJ Am Chem Soc
March 2025
School of Chemistry, The University of New South Wales, Sydney, New South Wales 2052, Australia.
The presence of defects can significantly improve catalytic activity and stability, as they influence the binding of the reactants, intermediates, and products to the catalyst. Controlling defects in the structures of nanocrystal catalysts is synthetically challenging. In this study, we demonstrate the ability to control the growth of Ir nanocrystals, enabling the tuning of both structural and surface defects.
View Article and Find Full Text PDFAngew Chem Int Ed Engl
March 2025
Center for Advancing Electronics Dresden, TU Dresden, 01062, Dresden, Germany.
N-Heterocyclic carbenes are highly effective ligands for anchoring functional organic molecules to metal surfaces and nanoparticles, facilitating the formation of self-assembled monolayers. However, their adsorption on surface is difficult to predict and control, and there is an ongoing debate on the geometry of NHC derivatives on gold surfaces and on the role of gold adatoms. We present two single molecules based on a benzimidazole NHC, one equipped with a thiophene substituent, and the other ending with a Br atom.
View Article and Find Full Text PDFNanomaterials (Basel)
March 2025
Department of Optical Engineering, School of Opto-Electronic Engineering, Changchun University of Science and Technology, Changchun 130022, China.
Wet etching is the mainstream fabrication method for single-bar quantum cascade lasers (QCLs). Different etching solutions result in varying etching effects on III-V semiconductor materials. In this study, an efficient and nearly ideal etching solution ratio was proposed for simultaneously etching both InP and GaInAs/AlInAs, and the surface chemical reactions induced by each component of the etching solution during the process were investigated.
View Article and Find Full Text PDFJ Chem Inf Model
March 2025
Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.
With the rapid advancements in the field of fluorescent dyes, accurate prediction of optical properties and efficient retrieval of dye-related data are essential for effective dye design. However, there is a lack of tools for comprehensive data integration and convenient data retrieval. Moreover, existing prediction models mainly focus on a single property of fluorescent dyes and fail to account for the diverse fluorophores and solutions in a systematic manner.
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