Cargando…
Deep learning-based inverse design of microstructured materials for optical optimization and thermal radiation control
Microstructures with engineered properties are critical to thermal management in aerospace and space applications. Due to the overwhelming number of microstructure design variables, traditional approaches to material optimization can have time-consuming processes and limited use cases. Here, we comb...
Autores principales: | Sullivan, Jonathan, Mirhashemi, Arman, Lee, Jaeho |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10164128/ https://www.ncbi.nlm.nih.gov/pubmed/37149649 http://dx.doi.org/10.1038/s41598-023-34332-3 |
Ejemplares similares
-
Deep learning based analysis of microstructured materials for thermal radiation control
por: Sullivan, Jonathan, et al.
Publicado: (2022) -
Machine‐Learning Microstructure for Inverse Material Design
por: Pei, Zongrui, et al.
Publicado: (2021) -
Microstructured Materials Inverse Problems
por: Janno, Jaan, et al.
Publicado: (2011) -
A predictive machine learning approach for microstructure optimization and materials design
por: Liu, Ruoqian, et al.
Publicado: (2015) -
Inverse Design of Materials by Machine Learning
por: Wang, Jia, et al.
Publicado: (2022)