Deep learning for non-parameterized MEMS structural design

The geometric designs of MEMS devices can profoundly impact their physical properties and eventual performances. However, it is challenging for researchers to rationally consider a large number of possible designs, as it would be very time- and resource-consuming to study all these cases using numer...

Descripción completa

Detalles Bibliográficos
Autores principales: Guo, Ruiqi, Sui, Fanping, Yue, Wei, Wang, Zekai, Pala, Sedat, Li, Kunying, Xu, Renxiao, Lin, Liwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9424241/
https://www.ncbi.nlm.nih.gov/pubmed/36051747
http://dx.doi.org/10.1038/s41378-022-00432-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9424241/
https://www.ncbi.nlm.nih.gov/pubmed/36051747
http://dx.doi.org/10.1038/s41378-022-00432-9

Ejemplares similares