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

2021 ◽  
Author(s):  
Guokui Zheng ◽  
Yanle Li ◽  
Xu Qian ◽  
Ge Yao ◽  
Ziqi Tian ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Single Atom ◽  
Single Atom Alloy

scholarly journals A General Two‐Step Strategy–Based High‐Throughput Screening of Single Atom Catalysts for Nitrogen Fixation

Small Methods ◽  
2018 ◽  
Vol 3 (9) ◽  
pp. 1800376 ◽  
Author(s):  
Chongyi Ling ◽  
Yixin Ouyang ◽  
Qiang Li ◽  
Xiaowan Bai ◽  
Xin Mao ◽  
...  
Keyword(s):  
Nitrogen Fixation ◽  
High Throughput ◽  
High Throughput Screening ◽  
Single Atom

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

2021 ◽  
Author(s):  
Guokui Zheng ◽  
Ziqi Tian ◽  
Xingwang Zhang ◽  
Liang Chen ◽  
Xu Qian ◽  
...  
Keyword(s):  
High Throughput Screening ◽  
Density Functional ◽  
Ammonia Synthesis ◽  
Density Functional Theory Calculations ◽  
Reduction Reaction ◽  
Single Atom ◽  
Functional Theory ◽  
Metal Doped ◽  
Single Atom Alloy ◽  
Single Atom Alloys

<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>

Machine learning-based high throughput screening for nitrogen fixation on boron-doped single atom catalysts

2020 ◽  
Vol 8 (10) ◽  
pp. 5209-5216 ◽  
Author(s):  
Mohammad Zafari ◽  
Deepak Kumar ◽  
Muhammad Umer ◽  
Kwang S. Kim
Keyword(s):  
Machine Learning ◽  
Nitrogen Fixation ◽  
High Throughput ◽  
High Throughput Screening ◽  
Reduction Reaction ◽  
Single Atom ◽  
Nitrogen Reduction ◽  
Computational Burden ◽  
Boron Doped

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

High-throughput screening of transition metal single atom catalysts anchored on molybdenum disulfide for nitrogen fixation

Nano Energy ◽  
2020 ◽  
Vol 68 ◽  
pp. 104304 ◽  
Author(s):  
Tong Yang ◽  
Ting Ting Song ◽  
Jun Zhou ◽  
Shijie Wang ◽  
Dongzhi Chi ◽  
...  
Keyword(s):  
Nitrogen Fixation ◽  
Transition Metal ◽  
Molybdenum Disulfide ◽  
High Throughput ◽  
High Throughput Screening ◽  
Single Atom

In silico high throughput screening of bimetallic and single atom alloys using machine learning and ab initio microkinetic modelling

2020 ◽  
Vol 8 (1) ◽  
pp. 107-123 ◽  
Author(s):  
Shivam Saxena ◽  
Tuhin Suvra Khan ◽  
Fatima Jalid ◽  
Manojkumar Ramteke ◽  
M. Ali Haider
Keyword(s):  
Machine Learning ◽  
Ab Initio ◽  
High Throughput ◽  
Material Properties ◽  
In Silico ◽  
High Throughput Screening ◽  
Chemical Engineering ◽  
Materials Science ◽  
Single Atom ◽  
Single Atom Alloys

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.

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

2021 ◽  
Author(s):  
Guokui Zheng ◽  
Ziqi Tian ◽  
Xingwang Zhang ◽  
Liang Chen ◽  
Xu Qian ◽  
...  
Keyword(s):  
High Throughput Screening ◽  
Density Functional ◽  
Ammonia Synthesis ◽  
Density Functional Theory Calculations ◽  
Reduction Reaction ◽  
Single Atom ◽  
Functional Theory ◽  
Metal Doped ◽  
Single Atom Alloy ◽  
Single Atom Alloys

<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>

High-throughput screening program for botanical extracts

Planta Medica ◽  
2012 ◽  
Vol 78 (11) ◽  
Author(s):  
L Hingorani ◽  
NP Seeram ◽  
B Ebersole
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Screening Program ◽  
Botanical Extracts

High throughput screening of microbial biodiversity for the discovery of novel cosmeceutical agents

Planta Medica ◽  
2015 ◽  
Vol 81 (16) ◽  
Author(s):  
K Georgousaki ◽  
N DePedro ◽  
AM Chinchilla ◽  
N Aliagiannis ◽  
F Vicente ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Microbial Biodiversity
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