Recent Progress of Single‐atom Catalysts in the Electrocatalytic Reduction of Oxygen to Hydrogen Peroxide

Zhu, Weiya; Chen, Shaowei

doi:10.1002/elan.202060334

Cited by 28 publications

(32 citation statements)

References 90 publications

(106 reference statements)

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“…However, the volcano plots of the both are overlapped for the same rate-determining step when *OOH binds weakly. [404,405] As the inverse process of ORR reaction, the OER reaction produces the O 2 molecule from H 2 O involving the same electron transfer and intermediates (*OOH, *OH, and *O). Theoretically, the difference in Gibbs free energies between *OOH and *OH (ΔΔG = ΔG *OOH −-ΔG *OH ) is 2.46 eV, and the difference in Gibbs free energies between *O and *OH (ΔG *O −ΔG *OH ) is 1.23 eV for ideal OER catalyst, resulting in the overpotential of 0 V. Actually, due to the limitation of the scaling relation, [382] ΔΔG is typically approximate constant of 3.2 eV for metal oxides, and the η OER is almost solely dependent on (ΔG *O −ΔG *OH ) alone.…”

Section: Oxygen Reduction Reaction (Orr) and Oxygen Evolution Reaction (Oer)mentioning

confidence: 99%

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Density Functional Theory for Electrocatalysis

Liao

Xia

et al. 2021

Energy & Environ Materials

143

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With the increase in energy demand and worldwide natural environment crises, it is imperative to develop green and sustainable energy systems to produce clean fuels and chemicals, which can replace fossil fuels and reduce carbon dioxide emissions. [1][2][3] A promising strategy is to develop advanced electrochemical technologies that can convert some common molecules (e.g., water, carbon dioxide, and nitrogen) into high-value chemical products (e.g., hydrogen, hydrocarbons, oxygenates, ammonia, and carbonates). [4][5][6][7] The important energy-related electrocatalytic reactions, including hydrogen evolution reaction (HER), oxygen evolution reaction (OER), oxygen reduction reaction (ORR), nitrogen reduction reaction (NRR), carbon dioxide reduction reaction (CO 2 RR), are the key conversion routes. In the complex processes for the electrocatalytic reactions, an efficient, highly selective, and stable electrocatalyst plays a pivotal role in speeding up the reaction kinetics and decreasing the overpotential, [5,8,9] which can enhance the sustainable energy conversion efficiency. Over the past few decades, tremendous progresses have been made in the establishment of electrocatalysts preparation and fundamental catalytic mechanisms. [6,7,[9][10][11][12][13][14][15][16][17][18] Nevertheless, those breakthroughs still stay at the stage of experimental synthesis and lack of indepth understanding of fundamental principles of the active site on the catalyst surface and catalytic reactions mechanisms, which seriously limits the development of efficient catalysts. Researchers are full of enthusiasm about preparation of advanced catalysts with ideal properties, expecting to establish the composition-structure-function relationships. Density functional theory (DFT) calculations are based on quantum mechanics, which can calculate the electronic structure of the whole catalytic system. It is probably the most powerful computational approach to investigate the structure-activity relationships of electrocatalysts at atomic level. With the rapid advances of computer technology, DFT calculations have created tremendous opportunities in shedding light on the electrocatalytic mechanisms and predicting promising catalysts. [19,20] Identification of the active sites and understanding of the reaction mechanisms are the two key aspects for the study of electrocatalytic reactions. [21] For the former, the experimental approach for identifying active sites is indirect by prepared specified catalysts and establishing definite correlations between catalytic performances and controllable factors. [22,23] Actually, many intermediate states of electrocatalytic

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Section: Oxygen Reduction Reaction (Orr) and Oxygen Evolution Reaction (Oer)mentioning

confidence: 99%

“…However, the volcano plots of the both are overlapped for the same rate‐determining step when *OOH binds weakly. [ 404,405 ]…”

Section: Electrocatalytic Reactionsmentioning

confidence: 99%

Density Functional Theory for Electrocatalysis

Liao

Xia

et al. 2021

Energy & Environ Materials

143

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“…The electrochemical production of H 2 O 2 mainly relies on the 2e − process of the ORR, with the reaction equations shown in eqn (24) and (25). 219 H 2 O 2 acts as a by-product in the 4e − reaction process of the ORR, and thus during the reaction process, the 4e − process needs to be inhibited. Therefore, it is very important to choose a suitable catalyst.In alkaline medium: O 2 + 2H 2 O + 2e − → H 2 O 2 + 2OH − Acidic medium: O 2 + 2H + + 2e − → H 2 O 2 An ideal electrochemical catalyst should be able to strongly adsorb O 2 to generate the oxygen-containing *OOH intermediate in the electrochemical synthesis of H 2 O 2 , and then the weak adsorption of *OOH on the surface of the catalyst can easily desorb and generate H 2 O 2 .…”

Section: Applications Of Fe-sacsmentioning

confidence: 99%

Emerging single-atom iron catalysts for advanced catalytic systems

Chang

Wang

et al. 2022

Nanoscale Horiz.

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“…When hydrogen peroxide is expected to be produced as a target molecule [34], the catalyst trends to be design following the two‐electron pathway. However, in most cases, the four‐electron mechanism is preferred, for it has higher energy efficiency and H 2 O 2 might be harmful to fuel cells.…”

Section: Machine Learning [13–15]mentioning

confidence: 99%

Accelerating Optimizing the Design of Carbon‐based Electrocatalyst via Machine Learning

Huang

2021

Electroanalysis

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In this era of artificial intelligence, we urgently want to optimize the current material design methods to come up with a more efficient and more accurate closedloop system. The approach requires at least three parts including high-throughput screening, automated synthesis platform, and machine learning algorithms. Fortunately, the techniques mentioned above have been substantial developed. We have introduced the common algorithms of machine learning. Then, several machine learningbased design of carbon-based electrocatalysts are discussed. We tried to illustrate the research norms involving machine learning. Besides, other paper structures and details have been also discussed.

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Recent Progress of Single‐atom Catalysts in the Electrocatalytic Reduction of Oxygen to Hydrogen Peroxide

Cited by 28 publications

References 90 publications

Density Functional Theory for Electrocatalysis

Density Functional Theory for Electrocatalysis

Emerging single-atom iron catalysts for advanced catalytic systems

Accelerating Optimizing the Design of Carbon‐based Electrocatalyst via Machine Learning

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