Alloy Search and Predict outputs for 100,000 equimolar four-element combinations with the lowest microscopic thermal neutron absorption cross-section
| Main Author: | King, Daniel |
|---|---|
| Format: | Dataset |
| Terbitan: |
Mendeley
, 2019
|
| Subjects: | |
| Online Access: |
https:/data.mendeley.com/datasets/c74wnj5vv3 |
| ctrlnum |
0.17632-c74wnj5vv3.1 |
|---|---|
| fullrecord |
<?xml version="1.0"?>
<dc><creator>King, Daniel</creator><title>Alloy Search and Predict outputs for 100,000 equimolar four-element combinations with the lowest microscopic thermal neutron absorption cross-section</title><publisher>Mendeley</publisher><description>A rapid high-throughput computational technique, for assessment of alloy formation, implemented into the program "Alloy Search and Predict (ASAP)" (www.alloyasap.com) was used to search for an alloy suitable as a nuclear reactor cladding material for generations III+ and IV reactors. It is advantageous for these materials to have low thermal neutron cross-sections, high melting temperatures and phase stability.
A linear combination of the microscopic thermal neutron absorption cross sections (σ) was performed in combination with ASAP to make an assessment of the stability of the solid solution phase (Φ), mismatch in atomic radii (𝛿) and σ. Over 1 million unique equimolar four-element systems were evaluated were it was deemed that the Nb-Ti-V-Zr warranted further experimental and theoretical investigation.
The full list of systems assessed by ASAP is available in the "Full_ASAP_output.csv" and the ASAP output data corresponding to the 100,000 combinations that have the lowest microscopic thermal neutron absorption cross-section are included in "100000_lowest_ASAP_dataset.xlsx".</description><subject>Alloys</subject><subject>Computational Materials Science</subject><subject>Structural Materials for Nuclear Reactors</subject><type>Other:Dataset</type><identifier>10.17632/c74wnj5vv3.1</identifier><rights>Creative Commons Attribution 4.0 International</rights><rights>http://creativecommons.org/licenses/by/4.0</rights><relation>https:/data.mendeley.com/datasets/c74wnj5vv3</relation><date>2019-01-09T11:57:26Z</date><recordID>0.17632-c74wnj5vv3.1</recordID></dc>
|
| format |
Other:Dataset Other |
| author |
King, Daniel |
| title |
Alloy Search and Predict outputs for 100,000 equimolar four-element combinations with the lowest microscopic thermal neutron absorption cross-section |
| publisher |
Mendeley |
| publishDate |
2019 |
| topic |
Alloys Computational Materials Science Structural Materials for Nuclear Reactors |
| url |
https:/data.mendeley.com/datasets/c74wnj5vv3 |
| contents |
A rapid high-throughput computational technique, for assessment of alloy formation, implemented into the program "Alloy Search and Predict (ASAP)" (www.alloyasap.com) was used to search for an alloy suitable as a nuclear reactor cladding material for generations III+ and IV reactors. It is advantageous for these materials to have low thermal neutron cross-sections, high melting temperatures and phase stability.
A linear combination of the microscopic thermal neutron absorption cross sections (σ) was performed in combination with ASAP to make an assessment of the stability of the solid solution phase (Φ), mismatch in atomic radii (δ) and σ. Over 1 million unique equimolar four-element systems were evaluated were it was deemed that the Nb-Ti-V-Zr warranted further experimental and theoretical investigation.
The full list of systems assessed by ASAP is available in the "Full_ASAP_output.csv" and the ASAP output data corresponding to the 100,000 combinations that have the lowest microscopic thermal neutron absorption cross-section are included in "100000_lowest_ASAP_dataset.xlsx". |
| id |
IOS7969.0.17632-c74wnj5vv3.1 |
| institution |
Universitas Islam Indragiri |
| affiliation |
onesearch.perpusnas.go.id |
| institution_id |
804 |
| institution_type |
library:university library |
| library |
Teknologi Pangan UNISI |
| library_id |
2816 |
| collection |
Artikel mulono |
| repository_id |
7969 |
| city |
INDRAGIRI HILIR |
| province |
RIAU |
| shared_to_ipusnas_str |
1 |
| repoId |
IOS7969 |
| first_indexed |
2020-04-08T08:19:35Z |
| last_indexed |
2020-04-08T08:19:35Z |
| recordtype |
dc |
| _version_ |
1686587544661131264 |
| score |
17.538404 |