Tackling Multi-Physics Nano-Scale Phenomena in Capillary Force Lithography with Small Data by Hybrid Intelligence.
Bayesian evolutionary algorithm
hybrid intelligence
nano capillary lithography
nano-grating
transparent machine learning
Journal
Micromachines
ISSN: 2072-666X
Titre abrégé: Micromachines (Basel)
Pays: Switzerland
ID NLM: 101640903
Informations de publication
Date de publication:
26 Oct 2023
26 Oct 2023
Historique:
received:
05
10
2023
revised:
23
10
2023
accepted:
25
10
2023
medline:
25
11
2023
pubmed:
25
11
2023
entrez:
25
11
2023
Statut:
epublish
Résumé
The scientific community has been looking for novel approaches to develop nanostructures inspired by nature. However, due to the complicated processes involved, controlling the height of these nanostructures is challenging. Nanoscale capillary force lithography (CFL) is one way to use a photopolymer and alter its properties by exposing it to ultraviolet radiation. Nonetheless, the working mechanism of CFL is not fully understood due to a lack of enough information and first principles. One of these obscure behaviors is the sudden jump phenomenon-the sudden change in the height of the photopolymer depending on the UV exposure time and height of nano-grating (based on experimental data). This paper uses known physical principles alongside artificial intelligence to uncover the unknown physical principles responsible for the sudden jump phenomenon. The results showed promising results in identifying air diffusivity, dynamic viscosity, surface tension, and electric potential as the previously unknown physical principles that collectively explain the sudden jump phenomenon.
Identifiants
pubmed: 38004841
pii: mi14111984
doi: 10.3390/mi14111984
pmc: PMC10673390
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : National Science Foundation
ID : 1931380
Organisme : National Science Foundation
ID : 2129796
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