Cargando…
Materials discovery and design: by means of data science and optimal learning
This book addresses the current status, challenges and future directions of data-driven materials discovery and design. It presents the analysis and learning from data as a key theme in many science and cyber related applications. The challenging open questions as well as future directions in the ap...
Autores principales: | Lookman, Turab, Eidenbenz, Stephan, Alexander, Frank, Barnes, Cris |
---|---|
Lenguaje: | eng |
Publicado: |
Springer
2018
|
Materias: | |
Acceso en línea: | https://dx.doi.org/10.1007/978-3-319-99465-9 http://cds.cern.ch/record/2641333 |
Ejemplares similares
-
Frustrated materials and ferroic glasses
por: Lookman, Turab, et al.
Publicado: (2018) -
Multi-objective Optimization for Materials Discovery via Adaptive Design
por: Gopakumar, Abhijith M., et al.
Publicado: (2018) -
Learning from data to design functional materials without inversion symmetry
por: Balachandran, Prasanna V., et al.
Publicado: (2017) -
Materials science and technology for design engineers
por: Javitz, Alex E
Publicado: (1972) -
International Conference on Pattern Formation in Fluids and Materials : Collective Phenomena in Physics '96
por: Lookman, T, et al.
Publicado: (1997)