What is the Real Origin of the Activity of Fe–N–C Electrocatalysts in the O₂ Reduction Reaction? Critical Roles of Coordinating Pyrrolic N and Axially Adsorbing Species

Journal of the American Chemical Society, Journal Year: 2022, Volume and Issue: 144(39), P. 18144 - 18152

Published: Sept. 22, 2022

Fe–N–C electrocatalysts have emerged as promising substitutes for Pt-based catalysts the oxygen reduction reaction (ORR). However, their real catalytic active site is still under debate. The underlying roles of different types coordinating N including pyridinic and pyrrolic in performance require thorough clarification. In addition, how to understand pH-dependent activity another urgent issue. Herein, we comprehensively studied 13 N-coordinated FeNxC configurations corresponding ORR through simulations which mimic realistic electrocatalytic environment on basis constant-potential implicit solvent models. We demonstrate that contributes a higher than N, FeN4C exhibits highest acidic media. Meanwhile, situ transformation *O-FeN4C *OH-FeN4C clarifies origin alkaline These findings can provide indispensable guidelines rational design better durable catalysts.

Language: Английский

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MOF-Derived Co and Fe Species Loaded on N-Doped Carbon Networks as Efficient Oxygen Electrocatalysts for Zn-Air Batteries

Nano-Micro Letters, Journal Year: 2022, Volume and Issue: 14(1)

Published: Aug. 11, 2022

Searching for cheap, efficient, and stable oxygen electrocatalysts is vital to promote the practical performance of Zn-air batteries with high theoretic energy density. Herein, a series Co nanoparticles highly dispersed Fe loaded on N-doped porous carbon substrates are prepared through "double-solvent" method in situ doped metal-organic frameworks as precursors. The optimized catalysts exhibit excellent reduction evolution reaction. Furthermore, rechargeable designed demonstrate higher peak power density better cycling stability than those commercial Pt/C+RuO2. According structure characterizations electrochemical tests, interaction contributes superior electrocatalysis. In addition, large specific surface areas, structures interconnected three-dimensional networks also play important roles improving This work provides inspiration rational design advanced paves way application batteries.

Language: Английский

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Structure-Performance Descriptors and the Role of the Axial Oxygen Atom on M–N₄–C Single-Atom Catalysts for Electrochemical CO₂ Reduction

ACS Catalysis, Journal Year: 2022, Volume and Issue: 12(9), P. 5441 - 5454

Published: April 22, 2022

Revealing and characterizing the catalytic sites, along with elucidating a convenient activity descriptor, can provide essential guidance in determining efficient electrocatalytic catalysts for CO2 reduction reaction (CO2RR). In this work, mechanism of to methane (CH4) on 23 transition metal-coordinated nitrogen-doped carbon M–N4–C single-atom (SACs) was studied by density functional theory calculations, step forward revealing effects axial O atom (M–N4O–C) their activity. The over SACs is strongly dependent outmost d-shell electron numbers electronegativity selected metals. introduction changes coordination structure central metal atoms, which not only improves stability M–N4O–C (especially electrochemical stability) but also affects adsorption strength intermediate species then or reduces activity, depends intrinsic properties atoms. More importantly, considering comprehensive number electrons, electronegativity, coordinate numbers, bonding length nearest neighbor atom, descriptor (φ) based materials developed correlate volcano-shaped relationships between φ limiting potentials were well established. particular, five (Mn–N4–C, Cr–N4–C, Os–N4O–C, Ru–N4O–C, Rh–N4O–C) close summit volcano screened. Based catalyst be predicted directly from characteristics material instead expensive calculation energies. This work great significance understanding CO2RR design stable electrocatalysts.

Language: Английский

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Revealing the role of double-layer microenvironments in pH-dependent oxygen reduction activity over metal-nitrogen-carbon catalysts

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Oct. 31, 2023

A standing puzzle in electrochemistry is that why the metal-nitrogen-carbon catalysts generally exhibit dramatic activity drop for oxygen reduction when traversing from alkaline to acid. Here, taking FeCo-N6-C double-atom catalyst as a model system and combining ab initio molecular dynamics simulation situ surface-enhanced infrared absorption spectroscopy, we show it significantly distinct interfacial double-layer structures, rather than energetics of multiple reaction steps, cause pH-dependent on catalysts. Specifically, greatly disparate charge densities electrode surfaces render different orientations water under acid conditions, thereby affecting formation hydrogen bonds between surface oxygenated intermediates molecules, eventually controlling kinetics proton-coupled electron transfer steps. The present findings may open new feasible avenues design advanced proton exchange membrane fuel cells.

Language: Английский

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Advances on Axial Coordination Design of Single-Atom Catalysts for Energy Electrocatalysis: A Review

Nano-Micro Letters, Journal Year: 2023, Volume and Issue: 15(1)

Published: Oct. 13, 2023

Abstract Single-atom catalysts (SACs) have garnered increasingly growing attention in renewable energy scenarios, especially electrocatalysis due to their unique high efficiency of atom utilization and flexible electronic structure adjustability. The intensive efforts towards the rational design synthesis SACs with versatile local configurations significantly accelerated development efficient sustainable electrocatalysts for a wide range electrochemical applications. As an emergent coordination avenue, intentionally breaking planar symmetry by adding ligands axial direction metal single atoms offers novel approach tuning both geometric structures, thereby enhancing electrocatalytic performance at active sites. In this review, we briefly outline burgeoning research topic axially coordinated provide comprehensive summary recent advances synthetic strategies Besides, challenges outlooks field also been emphasized. present review provides in-depth understanding SACs, which could bring new perspectives solutions fine regulation structures catering high-performing electrocatalysis.

Language: Английский

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Progress and challenges in nitrous oxide decomposition and valorization

Chemical Society Reviews, Journal Year: 2024, Volume and Issue: 53(16), P. 8379 - 8423

Published: Jan. 1, 2024

Nitrous oxide (N

Language: Английский

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Two‐Dimensional Organometallic Frameworks with Pyridinic Single‐Metal‐Atom Sites for Bifunctional ORR/OER

Advanced Functional Materials, Journal Year: 2022, Volume and Issue: 32(44)

Published: Aug. 11, 2022

Abstract Achieving efficient bifunctional oxygen reduction and evolution reactions (ORR/OER) on non‐noble metal catalysts is desirable but remains a significant challenge. Herein, inspired by the experimentally synthesized (phen 2 N )FeCl molecule, stable 2D organometallic framework, namely monolayer, proposed as qualified candidate means of constant‐potential first‐principles computations. Unlike most frameworks that feature pyrrolic coordination, monolayer exhibits pyridinic‐type FeN 4 ligation environment. The unique structure enables high single‐atom Fe loading in heterogeneous system, superior to typical FeNC materials. Constant‐potential energy analysis microkinetic modeling demonstrate holds great potential for facilitating ORR/OER both acidic alkaline conditions, showing theoretical activity higher than materials, Pt/IrO . Moreover, )MCl monolayers (M = Mn, Co, Ni) are explored, )MnCl also identified have excellent activity. This study highlights rational design local coordination environments boosting electrocatalytic performance frameworks.

Language: Английский

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A Universal Machine Learning Framework for Electrocatalyst Innovation: A Case Study of Discovering Alloys for Hydrogen Evolution Reaction

Advanced Functional Materials, Journal Year: 2022, Volume and Issue: 32(47)

Published: Sept. 16, 2022

Abstract Massive efforts have been made to develop efficient electrocatalysts for green hydrogen production. The introduction of machine learning (ML) has brought new opportunities the design electrocatalysts. However, current ML studies shown that efficiency and accuracy this method in electrocatalyst development are severely hindered by two major problems, high computational cost paid electronic or geometrical structures with accuracy, large errors resulted from those easily accessible relatively simple physical chemical properties lower level accuracy. Here, a universal framework is proposed achieves local structure optimization using potential (MLP) efficiently obtain accurate descriptors, combining graph convolutional neural networks, 43 high‐performance alloys successfully screened as evolution reaction 2973 candidates. More importantly, part best candidates identified verified experiments, one them (AgPd) systematically investigated ab initio calculations under realistic electrocatalytic environments further demonstrate significantly, can be compromised MLP optimized structural descriptor input, paradigm could established designing

Language: Английский

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Unraveling the improved CO2 adsorption and COOH* formation over Cu-decorated ZnO nanosheets for CO2 reduction toward CO

Chemical Engineering Journal, Journal Year: 2022, Volume and Issue: 452, P. 139701 - 139701

Published: Oct. 10, 2022

Language: Английский

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Perspective on Theoretical Models for CO₂ Electrochemical Reduction

The Journal of Physical Chemistry C, Journal Year: 2022, Volume and Issue: 126(8), P. 3820 - 3829

Published: Feb. 18, 2022

The electrochemical reduction of CO2 (CO2RR) is a promising alternative to achieve carbon neutrality and the sustainable development human civilization. Rational design electrocatalysts for CO2RR requires thorough understanding catalytically active sites corresponding reaction mechanisms from atomic level, where theoretical computations simulations are indispensable. In this perspective, we summarize recent progress in simulating both thermodynamic kinetic aspects, including different methods describing solvent–ion effects applied potentials. addition, brief overview applications machine learning (ML) catalysts presented, simulation electrocatalytic processes also discussed, considering solvent model under constant potential by ML. Finally, an outlook provided future computational models their CO2RR.

Language: Английский

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