Computational Materials Science
GPTKB entity
Statements (49)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:academic
|
| gptkbp:aimsTo |
predict material properties
understand material behavior |
| gptkbp:appliesTo |
gptkb:ceramics
metals nanomaterials semiconductors polymers composites |
| gptkbp:conference |
ICCMSE
|
| gptkbp:contributedTo |
gptkb:nanotechnology
biomaterials research materials engineering electronic materials research energy materials research |
| gptkbp:enables |
materials design
materials discovery optimization of materials |
| gptkbp:hasApplication |
biomaterials
thin films magnetic materials catalysts coatings optical materials solar cells alloys superconductors fuel cells battery materials nanodevices structural materials thermoelectrics |
| gptkbp:hasJournal |
Computational Materials Science (journal)
|
| https://www.w3.org/2000/01/rdf-schema#label |
Computational Materials Science
|
| gptkbp:relatedTo |
computational chemistry
computational physics materials science |
| gptkbp:studies |
materials
|
| gptkbp:uses |
gptkb:density_functional_theory
gptkb:machine_learning gptkb:Monte_Carlo_methods high-performance computing computer simulations molecular dynamics theoretical models data-driven approaches first-principles calculations |
| gptkbp:bfsParent |
gptkb:Jürgen_Furthmüller
|
| gptkbp:bfsLayer |
7
|