High-Throughput Screening of a Single-Atom Alloy for Electroreduction of Dinitrogen to Ammonia

Author(s):  
Guokui Zheng ◽  
Yanle Li ◽  
Xu Qian ◽  
Ge Yao ◽  
Ziqi Tian ◽  
...  
Small Methods ◽  
2018 ◽  
Vol 3 (9) ◽  
pp. 1800376 ◽  
Author(s):  
Chongyi Ling ◽  
Yixin Ouyang ◽  
Qiang Li ◽  
Xiaowan Bai ◽  
Xin Mao ◽  
...  

2021 ◽  
Author(s):  
Guokui Zheng ◽  
Ziqi Tian ◽  
Xingwang Zhang ◽  
Liang Chen ◽  
Xu Qian ◽  
...  

<p></p><p>Exploring electrocatalyst with high activity, selectivity and stability is essential for development of applicable electrocatalytic ammonia synthesis technology. By performing density functional theory calculations, we systematically investigated a series of transition-metal doped Au-based single atom alloys (SAAs) as promising electrocatalysts for nitrogen reduction reaction (NRR). For Au-based electrocatalyst, the first hydrogenation step (*N<sub>2</sub>→*NNH) normally determines the limiting potential of the overall reaction process. Compared with pristine Au(111) surface, introducing single atom can significantly enhance the binding strength of N<sub>2</sub>, leading to decreased energy barrier of the key step, i.e., ΔG(*N<sub>2</sub>→*NNH). According to simulation results, three descriptors were proposed to describe ΔG(*N<sub>2</sub>→*NNH), including ΔG(*NNH), <i>d</i>-band center, and . Eight doped elements (Ti, V, Nb, Ru, Ta, Os, W, and Mo) were initially screened out with limiting potential ranging from -0.75V to -0.30 V. Particularly, Mo- and W-doped systems possess the best activity with limiting potentials of -0.30 V, respectively. Then the intrinsic relationship between structure and the potential performance was further analyzed by using machine-learning. The selectivity, feasibility, stability of these candidates were also evaluated, confirming that SAA containing Mo, Ru ,Ta, and W could be outstanding NRR electrocatalysts. This work not only broadens the understating of SAA application in electrocatalysis, but also devotes to the discovery of novel NRR electrocatalysts.</p><br><p></p>


2020 ◽  
Vol 8 (10) ◽  
pp. 5209-5216 ◽  
Author(s):  
Mohammad Zafari ◽  
Deepak Kumar ◽  
Muhammad Umer ◽  
Kwang S. Kim

Machine learning (ML) methods would significantly reduce the computational burden of catalysts screening for nitrogen reduction reaction (NRR).


Nano Energy ◽  
2020 ◽  
Vol 68 ◽  
pp. 104304 ◽  
Author(s):  
Tong Yang ◽  
Ting Ting Song ◽  
Jun Zhou ◽  
Shijie Wang ◽  
Dongzhi Chi ◽  
...  

2020 ◽  
Vol 8 (1) ◽  
pp. 107-123 ◽  
Author(s):  
Shivam Saxena ◽  
Tuhin Suvra Khan ◽  
Fatima Jalid ◽  
Manojkumar Ramteke ◽  
M. Ali Haider

The advent of machine learning (ML) techniques in solving problems related to materials science and chemical engineering is driving expectations to give faster predictions of material properties.


2021 ◽  
Author(s):  
Guokui Zheng ◽  
Ziqi Tian ◽  
Xingwang Zhang ◽  
Liang Chen ◽  
Xu Qian ◽  
...  

<p></p><p>Exploring electrocatalyst with high activity, selectivity and stability is essential for development of applicable electrocatalytic ammonia synthesis technology. By performing density functional theory calculations, we systematically investigated a series of transition-metal doped Au-based single atom alloys (SAAs) as promising electrocatalysts for nitrogen reduction reaction (NRR). For Au-based electrocatalyst, the first hydrogenation step (*N<sub>2</sub>→*NNH) normally determines the limiting potential of the overall reaction process. Compared with pristine Au(111) surface, introducing single atom can significantly enhance the binding strength of N<sub>2</sub>, leading to decreased energy barrier of the key step, i.e., ΔG(*N<sub>2</sub>→*NNH). According to simulation results, three descriptors were proposed to describe ΔG(*N<sub>2</sub>→*NNH), including ΔG(*NNH), <i>d</i>-band center, and . Eight doped elements (Ti, V, Nb, Ru, Ta, Os, W, and Mo) were initially screened out with limiting potential ranging from -0.75V to -0.30 V. Particularly, Mo- and W-doped systems possess the best activity with limiting potentials of -0.30 V, respectively. Then the intrinsic relationship between structure and the potential performance was further analyzed by using machine-learning. The selectivity, feasibility, stability of these candidates were also evaluated, confirming that SAA containing Mo, Ru ,Ta, and W could be outstanding NRR electrocatalysts. This work not only broadens the understating of SAA application in electrocatalysis, but also devotes to the discovery of novel NRR electrocatalysts.</p><br><p></p>


Planta Medica ◽  
2012 ◽  
Vol 78 (11) ◽  
Author(s):  
L Hingorani ◽  
NP Seeram ◽  
B Ebersole

Planta Medica ◽  
2015 ◽  
Vol 81 (16) ◽  
Author(s):  
K Georgousaki ◽  
N DePedro ◽  
AM Chinchilla ◽  
N Aliagiannis ◽  
F Vicente ◽  
...  

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