Cargando…
Deep learning based analysis of microstructured materials for thermal radiation control
Microstructured materials that can selectively control the optical properties are crucial for the development of thermal management systems in aerospace and space applications. However, due to the vast design space available for microstructures with varying material, wavelength, and temperature cond...
Autores principales: | Sullivan, Jonathan, Mirhashemi, Arman, Lee, Jaeho |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9192759/ https://www.ncbi.nlm.nih.gov/pubmed/35697745 http://dx.doi.org/10.1038/s41598-022-13832-8 |
Ejemplares similares
-
Deep learning-based inverse design of microstructured materials for optical optimization and thermal radiation control
por: Sullivan, Jonathan, et al.
Publicado: (2023) -
Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials
por: Chun, Sehyun, et al.
Publicado: (2020) -
Deep learning approach for chemistry and processing history prediction from materials microstructure
por: Farizhandi, Amir Abbas Kazemzadeh, et al.
Publicado: (2022) -
Deep Learning-Based Segmentation of 3D Volumetric Image and Microstructural Analysis
por: Mahmud, Bahar Uddin, et al.
Publicado: (2023) -
Composite Materials for Thermal Energy Storage: Enhancing Performance through Microstructures
por: Ge, Zhiwei, et al.
Publicado: (2014)