Machine learning enables design automation of microfluidic flow-focusing droplet generation
Devices for droplet generation are at the heart of many microfluidic applications but difficult to tailor for specific cases. Lashkaripour et al. show how design customization can greatly be simplified by combining rapid prototyping with data-driven machine learning strategies.
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2021-01-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-020-20284-z |
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doaj-26fb0f19f58d4b0b8fb52cda68311ccb2021-01-10T12:17:44ZengNature Publishing GroupNature Communications2041-17232021-01-0112111410.1038/s41467-020-20284-zMachine learning enables design automation of microfluidic flow-focusing droplet generationAli Lashkaripour0Christopher Rodriguez1Noushin Mehdipour2Rizki Mardian3David McIntyre4Luis Ortiz5Joshua Campbell6Douglas Densmore7Department of Biomedical Engineering, Boston UniversityComputational and Systems Biology, Massachusetts Institute of TechnologyBiological Design CenterBiological Design CenterDepartment of Biomedical Engineering, Boston UniversityBiological Design CenterDepartment of Medicine, Boston UniversityBiological Design CenterDevices for droplet generation are at the heart of many microfluidic applications but difficult to tailor for specific cases. Lashkaripour et al. show how design customization can greatly be simplified by combining rapid prototyping with data-driven machine learning strategies.https://doi.org/10.1038/s41467-020-20284-z |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ali Lashkaripour Christopher Rodriguez Noushin Mehdipour Rizki Mardian David McIntyre Luis Ortiz Joshua Campbell Douglas Densmore |
spellingShingle |
Ali Lashkaripour Christopher Rodriguez Noushin Mehdipour Rizki Mardian David McIntyre Luis Ortiz Joshua Campbell Douglas Densmore Machine learning enables design automation of microfluidic flow-focusing droplet generation Nature Communications |
author_facet |
Ali Lashkaripour Christopher Rodriguez Noushin Mehdipour Rizki Mardian David McIntyre Luis Ortiz Joshua Campbell Douglas Densmore |
author_sort |
Ali Lashkaripour |
title |
Machine learning enables design automation of microfluidic flow-focusing droplet generation |
title_short |
Machine learning enables design automation of microfluidic flow-focusing droplet generation |
title_full |
Machine learning enables design automation of microfluidic flow-focusing droplet generation |
title_fullStr |
Machine learning enables design automation of microfluidic flow-focusing droplet generation |
title_full_unstemmed |
Machine learning enables design automation of microfluidic flow-focusing droplet generation |
title_sort |
machine learning enables design automation of microfluidic flow-focusing droplet generation |
publisher |
Nature Publishing Group |
series |
Nature Communications |
issn |
2041-1723 |
publishDate |
2021-01-01 |
description |
Devices for droplet generation are at the heart of many microfluidic applications but difficult to tailor for specific cases. Lashkaripour et al. show how design customization can greatly be simplified by combining rapid prototyping with data-driven machine learning strategies. |
url |
https://doi.org/10.1038/s41467-020-20284-z |
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