Non-precious metal activated MoSi2N4 monolayers for high-performance OER and ORR electrocatalysts: A first-principles study DOI Creative Commons
Song Lu, Yang Zhang,

Fengliu Lou

et al.

Applied Surface Science, Journal Year: 2021, Volume and Issue: 579, P. 152234 - 152234

Published: Dec. 17, 2021

Developing high-performance electrocatalysts for oxygen evolution reaction (OER) and reduction (ORR) is crucial energy conversion storage. Recently, a new type of two-dimensional material MoSi2N4 was successfully synthesized received considerable attention because novel properties potential applications. Herein, by means first principles calculation, the OER/ORR activities 3d transition metal (TM) atoms embedded ([email protected]) were investigated. The calculated results indicate that TM on exhibit good electrochemical stability. On sites, [email protected] shows highest OER activity with an overpotential 0.48 V, whereas most active ORR catalyst V. Si site (Si−N1−Cu) follows dual-site mechanism, exhibiting same as N (0.55/0.65 V). Interestingly, outer (Zn−N1) achieves lowest 0.38 better than state-of-the-art RuO2 catalyst. We demonstrate not only serve sites themselves but also activate host to improve performance MoSi2N4. Our work opens windows opportunity developing catalysts beyond precious metal-based efficient

Language: Английский

Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery DOI
Haoxin Mai, Tu C. Le, Dehong Chen

et al.

Chemical Reviews, Journal Year: 2022, Volume and Issue: 122(16), P. 13478 - 13515

Published: July 21, 2022

Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels, reducing the impact of global warming, providing solutions environmental pollution. Improved processes for catalyst design better understanding electro/photocatalytic essential improving effectiveness. Recent advances in data science artificial intelligence have great potential accelerate electrocatalysis photocatalysis research, particularly rapid exploration large materials chemistry spaces through machine learning. Here comprehensive introduction to, critical review of, learning techniques used research provided. Sources electro/photocatalyst current approaches representing these by mathematical features described, most commonly methods summarized, quality utility models evaluated. Illustrations how applied novel discovery elucidate electrocatalytic or photocatalytic reaction mechanisms The offers guide scientists on selection research. application catalysis represents paradigm shift way advanced, next-generation catalysts will be designed synthesized.

Language: Английский

Citations

277

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 DOI
Xu Hu, Suya Chen, Letian Chen

et al.

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

Citations

195

2D Transition Metal Dichalcogenides‐Based Electrocatalysts for Hydrogen Evolution Reaction DOI Creative Commons
Aniruddha Mondal, Alberto Vomiero

Advanced Functional Materials, Journal Year: 2022, Volume and Issue: 32(52)

Published: Oct. 30, 2022

Abstract Hydrogen is an efficient, clean, and economical energy source, owing to its huge density. Electrochemical water splitting a potential candidate for inexpensive eco‐friendly hydrogen production. Recently, the development of 2D transition metal chalcogenides (TMDs) nanomaterials with variety physicochemical properties has shown their as eminent non‐noble metal‐based nanoscale electrocatalysts evolution. Nanostructuring such materials induces deep modification functionalities, compared bulk counterparts. High density different types exposed active sites formed, small diffusion paths, which enhances electron transfer in structures, can successfully aid charge collection process electrocatalytic evolution reactions. In this review, key parameters improve catalyst performance TMDs electrochemical reaction (HER) processes are discussed detail most recent developments field summarized, focusing on improvement activity TMDs. This review delivers insight clear understanding HER, suggesting new type efficient HER well other renewable fields.

Language: Английский

Citations

155

Theoretical Advances in Understanding and Designing the Active Sites for Hydrogen Evolution Reaction DOI
Fang Sun, Qing Tang, De‐en Jiang

et al.

ACS Catalysis, Journal Year: 2022, Volume and Issue: 12(14), P. 8404 - 8433

Published: June 30, 2022

As a fundamental step of water splitting and stepping stone toward exploring other multielectron transfer processes, the electrocatalytic hydrogen evolution reaction (HER) is an ideal model for both understanding electrocatalyst design. Here, we review fundamentals recent developments theoretical insights into HER, covering mechanistic aspects, key activity descriptors, local environment considerations, advances beyond computational electrode. Although it experimentally challenging to explore active sites mechanisms in process, show great potential identifying mechanisms. In this Review, especially focus depth on revealing designing HER. Major challenges ahead will also be discussed at end Review.

Language: Английский

Citations

146

Vacancy-induced 2H@1T MoS2 phase-incorporation on ZnIn2S4 for boosting photocatalytic hydrogen evolution DOI
Yanhua Peng, Mengjie Geng, Jianqiang Yu

et al.

Applied Catalysis B Environment and Energy, Journal Year: 2021, Volume and Issue: 298, P. 120570 - 120570

Published: July 29, 2021

Language: Английский

Citations

127

Nickel single-atom catalysts intrinsically promoted by fast pyrolysis for selective electroreduction of CO2 into CO DOI

Yibo Guo,

Sai Yao,

Yuanyuan Xue

et al.

Applied Catalysis B Environment and Energy, Journal Year: 2021, Volume and Issue: 304, P. 120997 - 120997

Published: Dec. 8, 2021

Language: Английский

Citations

112

Toward Excellence of Electrocatalyst Design by Emerging Descriptor‐Oriented Machine Learning DOI
Jianwen Liu, Wenzhi Luo, Lei Wang

et al.

Advanced Functional Materials, Journal Year: 2022, Volume and Issue: 32(17)

Published: Jan. 15, 2022

Abstract Machine learning (ML) is emerging as a powerful tool for identifying quantitative structure–activity relationships to accelerate electrocatalyst design by from historic data without explicit programming. The algorithms, data/database, and descriptors are usually the decisive factors ML play pivotal role electrocatalysis they contain essence of catalysis physicochemical nature. Despite considerable research efforts regarding with ML, lack universal selection tactics bridging gap between structures activity impedes its wider application. A timely summary application in helps deepen understanding nature improve scope efficiency. This review summarizes geometrical, electronic, used input training predicting reveal general rules their electrocatalysts. In response challenges hydrogen evolution reaction, oxygen reduction CO 2 nitrogen these areas tracked progress prospective changes. Additionally, potential automated discovery discussed other well‐known electrocatalytic processes.

Language: Английский

Citations

79

Machine Learning: A New Paradigm in Computational Electrocatalysis DOI
Xu Zhang, Yun Tian, Letian Chen

et al.

The Journal of Physical Chemistry Letters, Journal Year: 2022, Volume and Issue: 13(34), P. 7920 - 7930

Published: Aug. 18, 2022

Designing and screening novel electrocatalysts, understanding electrocatalytic mechanisms at an atomic level, uncovering scientific insights lie the center of development electrocatalysis. Despite certain success in experiments computations, it is still difficult to achieve above objectives due complexity systems vastness chemical space for candidate electrocatalysts. With advantage machine learning (ML) increasing interest electrocatalysis energy conversion storage, data-driven research motivated by artificial intelligence (AI) has provided new opportunities discover promising investigate dynamic reaction processes, extract knowledge from huge data. In this Perspective, we summarize recent applications ML electrocatalysis, including electrocatalysts simulation processes. Furthermore, interpretable methods are discussed accelerate generation. Finally, blueprint envisaged future

Language: Английский

Citations

76

Engineering 2D Photocatalysts for Solar Hydrogen Peroxide Production DOI
Jindi Yang, Xiangkang Zeng, Mike Tebyetekerwa

et al.

Advanced Energy Materials, Journal Year: 2024, Volume and Issue: 14(23)

Published: April 3, 2024

Abstract Solar energy can be utilized in photocatalysis technology to realize light‐driven hydrogen peroxide (H 2 O ) production, a green chemical synthesis route. Designing high‐performance photocatalysts is critical achieving practical solar H production. During the past decade, significant research progress made photocatalytic materials for Particularly 2D materials‐based stand out due their unique physical and properties. This review highlights intricate relationship between material innovation photochemical It starts with fundamental principles of generation, focusing on crucial steps such as photon absorption, carrier dynamics, surface reactions, challenges that solve at each step. Then, various production are introduced detail. Engineering strategies optimize performance discussed afterward. Finally, future opportunities designing outlined. expected inspire engineering conversion other chemicals.

Language: Английский

Citations

68

MA2Z4 family heterostructures: Promises and prospects DOI Creative Commons
Che Chen Tho, San‐Dong Guo,

Shi‐Jun Liang

et al.

Applied Physics Reviews, Journal Year: 2023, Volume and Issue: 10(4)

Published: Nov. 22, 2023

Recent experimental synthesis of ambient-stable MoSi2N4 monolayer has garnered enormous research interest. The intercalation morphology MoSi2N4—composed a transition metal nitride (Mo-N) inner sub-monolayer sandwiched by two silicon (Si-N) outer sub-monolayers—has motivated the computational discovery an expansive family synthetic MA2Z4 monolayers with no bulk (3D) material counterpart (where M = metals or alkaline earth metals; A Si, Ge; and N N, P, As). exhibit interesting electronic, magnetic, optical, spintronic, valleytronic, topological properties, making them compelling platform for next-generation device technologies. Furthermore, heterostructure engineering enormously expands opportunities MA2Z4. In this review, we summarize recent rapid progress in design MA2Z4-based heterostructures based on first-principle density functional theory (DFT) simulations—a central work horse widely used to understand physics, chemistry, general rules specific targeted functions. We systematically classify their contact types, review physical focus performances electronics, optoelectronics, energy conversion applications. performance promises applications that include electrical contacts, transistors, spintronic devices, photodetectors, solar cells, photocatalytic water splitting. present several prospects heterostructures, which hold potential guide next phase exploration, moving beyond initial “gold rush” research. This unveils vast application paves roadmap future development devices.

Language: Английский

Citations

63