| Title |
Machine learning-assisted high-throughput exploration of interface energy space in multi-phase-field model with CALPHAD potential
|
|---|---|
| Published in |
Materials Theory, January 2022
|
| DOI | 10.1186/s41313-021-00038-0 |
| Authors |
Vahid Attari, Raymundo Arroyave |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 41% |
| Student > Master | 3 | 18% |
| Researcher | 1 | 6% |
| Unknown | 6 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Materials Science | 6 | 35% |
| Engineering | 5 | 29% |
| Computer Science | 1 | 6% |
| Unknown | 5 | 29% |