2011
DOI: 10.1088/1468-6996/12/5/054207
|View full text |Cite
|
Sign up to set email alerts
|

A combinatorial characterization scheme for high-throughput investigations of hydrogen storage materials

Abstract: In order to increase measurement throughput, a characterization scheme has been developed that accurately measures the hydrogen storage properties of materials in quantities ranging from 10 ng to 1 g. Initial identification of promising materials is realized by rapidly screening thin-film composition spread and thickness wedge samples using normalized IR emissivity imaging. The hydrogen storage properties of promising samples are confirmed through measurements on single-composition films with high-sensitivity … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2021
2021
2021
2021

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 12 publications
0
1
0
Order By: Relevance
“…The intelligent strategies play a crucial role in technologies ranging from electronics, energy generation and storage, aerospace, medicine, and defence industry [3][4][5]. To achieve these technologies, attention has been given recently to integrate high-throughput first-principles calculations and combinatorial methods to obtain robust, extrapolative tools for gaining insights into structure-property-composition relationships in order to reduce the experimental efforts, time, and cost in the materials discovery process [6][7][8][9][10][11][12][13].…”
Section: Introductionmentioning
confidence: 99%
“…The intelligent strategies play a crucial role in technologies ranging from electronics, energy generation and storage, aerospace, medicine, and defence industry [3][4][5]. To achieve these technologies, attention has been given recently to integrate high-throughput first-principles calculations and combinatorial methods to obtain robust, extrapolative tools for gaining insights into structure-property-composition relationships in order to reduce the experimental efforts, time, and cost in the materials discovery process [6][7][8][9][10][11][12][13].…”
Section: Introductionmentioning
confidence: 99%