Manipulating the Local Coordination and Electronic Structures for Efficient Electrocatalytic Oxygen Evolution

2021 ◽  
pp. 2103004
Author(s):  
Zhi‐Peng Wu ◽  
Huabin Zhang ◽  
Shouwei Zuo ◽  
Yan Wang ◽  
Song Lin Zhang ◽  
...  
Author(s):  
Hyoi Jo ◽  
Yejin Yang ◽  
Arim Seong ◽  
Donghwi Jeong ◽  
Jeongwon Kim ◽  
...  

Developing a stable and highly efficient electrocatalyst for oxygen evolution reactions (OERs) is critical for renewable, safe, and emission-free energy technologies. Perovskite oxides with flexible and tunable electronic structures as...


2020 ◽  
Vol 8 (19) ◽  
pp. 9638-9645 ◽  
Author(s):  
Tanglue Feng ◽  
Guangtao Yu ◽  
Songyuan Tao ◽  
Shoujun Zhu ◽  
Ruiqi Ku ◽  
...  

Through the modification of the surface and bulk electronic structures of Ru, the developed Ru-based catalyst presents superior electrocatalytic hydrogen and oxygen evolution activities with great durability over a wide pH range.


2020 ◽  
Vol 117 (13) ◽  
pp. 132902
Author(s):  
Mitsutaka Haruta ◽  
Aoi Nii ◽  
Yoshiteru Hosaka ◽  
Noriya Ichikawa ◽  
Takashi Saito ◽  
...  

Author(s):  
Changhai Liu ◽  
Dingwei Ji ◽  
Hong Shi ◽  
Zhenyu Wu ◽  
Hui Huang ◽  
...  

Perovskite oxides (ABO3) as electrocatalysts applied for oxygen evolution reaction (OER) have been studied for decades due to its high flexibility and adjustability for electronic structures. Herein, a series of...


Author(s):  
Dawn A. Bonnell ◽  
Yong Liang

Recent progress in the application of scanning tunneling microscopy (STM) and tunneling spectroscopy (STS) to oxide surfaces has allowed issues of image formation mechanism and spatial resolution limitations to be addressed. As the STM analyses of oxide surfaces continues, it is becoming clear that the geometric and electronic structures of these surfaces are intrinsically complex. Since STM requires conductivity, the oxides in question are transition metal oxides that accommodate aliovalent dopants or nonstoichiometry to produce mobile carriers. To date, considerable effort has been directed toward probing the structures and reactivities of ZnO polar and nonpolar surfaces, TiO2 (110) and (001) surfaces and the SrTiO3 (001) surface, with a view towards integrating these results with the vast amount of previous surface analysis (LEED and photoemission) to build a more complete understanding of these surfaces. However, the spatial localization of the STM/STS provides a level of detail that leads to conclusions somewhat different from those made earlier.


Nanoscale ◽  
2020 ◽  
Vol 12 (39) ◽  
pp. 20413-20424
Author(s):  
Riming Hu ◽  
Yongcheng Li ◽  
Fuhe Wang ◽  
Jiaxiang Shang

Bilayer single atom catalysts can serve as promising multifunctional electrocatalysts for the HER, ORR, and OER.


Author(s):  
Т. М. Мельниченко ◽  
Т. Д. Мельниченко ◽  
Я. Я. Коцак ◽  
Я. П. Куценко ◽  
П. П. Пуга

2019 ◽  
Author(s):  
Seoin Back ◽  
Kevin Tran ◽  
Zachary Ulissi

<div> <div> <div> <div><p>Developing active and stable oxygen evolution catalysts is a key to enabling various future energy technologies and the state-of-the-art catalyst is Ir-containing oxide materials. Understanding oxygen chemistry on oxide materials is significantly more complicated than studying transition metal catalysts for two reasons: the most stable surface coverage under reaction conditions is extremely important but difficult to understand without many detailed calculations, and there are many possible active sites and configurations on O* or OH* covered surfaces. We have developed an automated and high-throughput approach to solve this problem and predict OER overpotentials for arbitrary oxide surfaces. We demonstrate this for a number of previously-unstudied IrO2 and IrO3 polymorphs and their facets. We discovered that low index surfaces of IrO2 other than rutile (110) are more active than the most stable rutile (110), and we identified promising active sites of IrO2 and IrO3 that outperform rutile (110) by 0.2 V in theoretical overpotential. Based on findings from DFT calculations, we pro- vide catalyst design strategies to improve catalytic activity of Ir based catalysts and demonstrate a machine learning model capable of predicting surface coverages and site activity. This work highlights the importance of investigating unexplored chemical space to design promising catalysts.<br></p></div></div></div></div><div><div><div> </div> </div> </div>


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