Cargando…
Inverse Design of Materials by Machine Learning
It is safe to say that every invention that has changed the world has depended on materials. At present, the demand for the development of materials and the invention or design of new materials is becoming more and more urgent since peoples’ current production and lifestyle needs must be changed to...
Autores principales: | Wang, Jia, Wang, Yingxue, Chen, Yanan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8911677/ https://www.ncbi.nlm.nih.gov/pubmed/35269043 http://dx.doi.org/10.3390/ma15051811 |
Ejemplares similares
-
Machine‐Learning Microstructure for Inverse Material Design
por: Pei, Zongrui, et al.
Publicado: (2021) -
Tackling Photonic Inverse Design with Machine Learning
por: Liu, Zhaocheng, et al.
Publicado: (2021) -
Machine Learning
in Interpolation and Extrapolation
for Nanophotonic Inverse Design
por: Acharige, Didulani, et al.
Publicado: (2022) -
Feature Selection in Machine Learning for Perovskite Materials Design and Discovery
por: Wang, Junya, et al.
Publicado: (2023) -
Machine-enabled inverse design of inorganic solid materials: promises and challenges
por: Noh, Juhwan, et al.
Publicado: (2020)