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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Zbořil, Radek
Technical University of Ostrava
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (17/17 displayed)
- 2024Unveiling the potential of covalent organic frameworks for energy storage: Developments, challenges, and future prospectscitations
- 2023TiO2 nanotube arrays decorated with Ir nanoparticles for enhanced hydrogen evolution electrocatalysis
- 2022Intermetallic Copper‐Based Electride Catalyst with High Activity for C–H Oxidation and Cycloaddition of CO<sub>2</sub> into Epoxidescitations
- 2022Band gap and Morphology Engineering of Hematite Nanoflakes from an Ex Situ Sn Doping for Enhanced Photoelectrochemical Water Splittingcitations
- 2022Graphene-Based Metal-Organic Framework Hybrids for Applications in Catalysis, Environmental, and Energy Technologiescitations
- 2021Rational Design of Graphene Derivatives for Electrochemical Reduction of Nitrogen to Ammoniacitations
- 2021Covalent Graphene-MOF Hybrids for High-Performance Asymmetric Supercapacitorscitations
- 2021Emerging MXene@Metal-Organic Framework Hybridscitations
- 2020Controlling phase fraction and crystal orientation via thermal oxidation of iron foils for enhanced photoelectrochemical performancecitations
- 2020Metal Halide Perovskite@Metal-Organic Framework Hybridscitations
- 2020High-performance hydrogen evolution electrocatalysis using proton-intercalated TiO2 nanotube arrays as interactive supports for Ir nanoparticlescitations
- 2019Crystal Structure‐ and Morphology‐Driven Electrochemistry of Iron Oxide Nanoparticles in Hydrogen Peroxide Detectioncitations
- 2019Photocatalysis with Reduced TiO2: From Black TiO2 to Cocatalyst-Free Hydrogen Productioncitations
- 2016Advanced Sensing of Antibiotics with Magnetic Gold Nanocomposite: Electrochemical Detection of Chloramphenicolcitations
- 2015Direct evidence of Fe(v) and Fe(iv) intermediates during reduction of Fe(vi) to Fe(iii): a nuclear forward scattering of synchrotron radiation approachcitations
- 2013Thermal decomposition of [Co(en)3][Fe(CN)6]∙ 2H2O: Topotactic dehydration process, valence and spin exchange mechanism elucidation
- 2006Phase composition of steel–enamel interfaces: Effects of chemical pre-treatmentcitations
Places of action
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article
Rational Design of Graphene Derivatives for Electrochemical Reduction of Nitrogen to Ammonia
Abstract
<p>The conversion of nitrogen to ammonia offers a sustainable and environmentally friendly approach for producing precursors for fertilizers and efficient energy carriers. Owing to the large energy density and significant gravimetric hydrogen content, NH3 is considered an apt next-generation energy carrier and liquid fuel. However, the low conversion efficiency and slow production of ammonia through the nitrogen reduction reaction (NRR) are currently bottlenecks, making it an unviable alternative to the traditional Haber-Bosch process for ammonia production. The rational design and engineering of catalysts (both photo- and electro-) represent a crucial challenge for improving the efficiency and exploiting the full capability of the NRR. In the present review, we highlight recent progress in the development of graphene-based systems and graphene derivatives as catalysts for the NRR. Initially, the history, fundamental mechanism, and importance of the NRR to produce ammonia are briefly discussed. We also outline how surface functionalization, defects, and hybrid structures (single-atom/multiatom as well as composites) affect the N2 conversion efficiency. The potential of graphene and graphene derivatives as NRR catalysts is highlighted using pertinent examples from theoretical simulations as well as machine learning based performance predictive methods. The review is concluded by identifying the crucial advantages, drawbacks, and challenges associated with principal scientific and technological breakthroughs in ambient catalytic NRR. </p>