Machine Learning for Transition-Metal-Based Hydrogen Generation Electrocatalysts

ACS Catalysis ◽  
2021 ◽  
pp. 3930-3937
Author(s):  
Min Wang ◽  
Hongwei Zhu
Keyword(s):  
Machine Learning ◽  
Transition Metal ◽  
Hydrogen Generation

Lateral-size control of exfoliated transition-metal–oxide 2D materials by machine learning on small data

Nanoscale ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 3853-3859
Author(s):  
Ryosuke Mizuguchi ◽  
Yasuhiko Igarashi ◽  
Hiroaki Imai ◽  
Yuya Oaki
Keyword(s):  
Machine Learning ◽  
Transition Metal ◽  
Metal Oxide ◽  
2D Materials ◽  
Size Control ◽  
Transition Metal Oxide ◽  
Small Data ◽  
Lateral Size

Lateral sizes of the exfoliated transition-metal–oxide nanosheets were predicted and controlled by the assistance of machine learning. 

A review of transition-metal boride/phosphide-based materials for catalytic hydrogen generation from hydrolysis of boron-hydrides

2018 ◽  
Vol 5 (4) ◽  
pp. 760-772 ◽  
Author(s):  
Hongming Sun ◽  
Jing Meng ◽  
Lifang Jiao ◽  
Fangyi Cheng ◽  
Jun Chen
Keyword(s):  
Transition Metal ◽  
Hydrogen Generation ◽  
Metal Boride ◽  
Hydrogen Economy ◽  
Boron Hydrides ◽  
Catalytic Hydrogen ◽  
And Storage ◽  
Hydrolysis Of ◽  
Essential Prerequisite

Efficient hydrogen generation and storage is an essential prerequisite of a future hydrogen economy.

scholarly journals Transition metal-doped nickel phosphide nanoparticles as electro- and photocatalysts for hydrogen generation reactions

2019 ◽  
Vol 242 ◽  
pp. 186-193 ◽  
Author(s):  
Ho-Wing Man ◽  
Chui-Shan Tsang ◽  
Molly Meng-Jung Li ◽  
Jiaying Mo ◽  
Bolong Huang ◽  
...  
Keyword(s):  
Transition Metal ◽  
Hydrogen Generation ◽  
Nickel Phosphide ◽  
Metal Doped

scholarly journals Formation enthalpies for transition metal alloys using machine learning

2017 ◽  
Vol 95 (21) ◽  
Author(s):  
Shashanka Ubaru ◽  
Agnieszka Międlar ◽  
Yousef Saad ◽  
James R. Chelikowsky
Keyword(s):  
Machine Learning ◽  
Transition Metal ◽  
Metal Alloys ◽  
Transition Metal Alloys ◽  
Formation Enthalpies
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