Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Daniel Stoecklein"'
Publikováno v:
Lab on a Chip. 21:3910-3923
Mixing is a basic but challenging step to achieve in high throughput microfluidic applications such as organic synthesis or production of particles. A common approach to improve micromixer performance is to devise a single component that enhances mix
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::33ef99dbf2c17b10cc2fef73ef6822a1
https://doi.org/10.1039/d1lc00483b
https://doi.org/10.1039/d1lc00483b
Autor:
Matteo Antognoli, Laura Donato, Chiara Galletti, Daniel Stoecklein, Dino Di Carlo, Elisabetta Brunazzi
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0408364303fefee69833be9a9bbd913f
https://doi.org/10.2139/ssrn.4292583
https://doi.org/10.2139/ssrn.4292583
Autor:
Daniel Stoecklein, Shreya Udani, Samira Chizari, Amin Farzaneh, Jonathan B. Hopkins, Dino Di Carlo
Publikováno v:
Optics express. 28(26)
In this work, we demonstrate the high-throughput fabrication of 3D microparticles using a scanning two-photon continuous flow lithography (STP-CFL) technique in which microparticles are shaped by scanning the laser beam at the interface of laminar co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea053997a74bd2cf8ead22e27628ffb4
https://pubmed.ncbi.nlm.nih.gov/33379542
https://pubmed.ncbi.nlm.nih.gov/33379542
Autor:
Daniel Stoecklein, Kin Gwn Lore, Baskar Ganapathysubramanian, Soumik Sarkar, Michael A. Davies
Publikováno v:
Neural Networks. 98:305-317
Recurrent neural network (RNN) and Long Short-term Memory (LSTM) networks are the common go-to architecture for exploiting sequential information where the output is dependent on a sequence of inputs. However, in most considered problems, the depende
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::33743b3466b3874b9e16433f6130c603
https://doi.org/10.1016/j.neunet.2017.12.003
https://doi.org/10.1016/j.neunet.2017.12.003
Publikováno v:
Journal of Fluid Mechanics. 886
Design of microparticles which stabilize at the centerline of a channel flow when part of a dilute suspension is examined numerically for moderate Reynolds numbers ($10 \le Re \le 80$). Stability metrics for particles with arbitrary shapes are formul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c3148bf2bec62c2dc3b53a1e905cbdb
https://doi.org/10.1017/jfm.2019.1007
https://doi.org/10.1017/jfm.2019.1007
Publikováno v:
Journal of Mechanical Design. 141
Efficient exploration of design spaces is highly sought after in engineering applications. A spectrum of tools has been proposed to deal with the computational difficulties associated with such problems. In the context of our case study, these tools
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::815c1b14873e8dba67bfb938a73ef698
https://doi.org/10.1115/1.4044397
https://doi.org/10.1115/1.4044397
Autor:
Chueh-Yu Wu, Joseph de Rutte, Michael A. Davies, Baskar Ganapathysubramanian, Dino Di Carlo, Daniel Stoecklein
Publikováno v:
Lab on a chip. 19(19)
Flow sculpting is a powerful method for passive flow control that uses a sequence of bluff-body structures to engineer the structure of inertially flowing microfluidic streams. A variety of cross-sectional flow shapes can be created through this meth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf886fcfd51ada495be233c3c56d7ea4
https://pubmed.ncbi.nlm.nih.gov/31482902
https://pubmed.ncbi.nlm.nih.gov/31482902
Autor:
Daniel Stoecklein, Dino Di Carlo
Publikováno v:
Analytical chemistry. 91(1)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56e55b3dd177ada4d55dafa625b40955
https://pubmed.ncbi.nlm.nih.gov/31503453
https://pubmed.ncbi.nlm.nih.gov/31503453
Publikováno v:
Microfluidics and Nanofluidics. 22
Approaches to abstract and modularize models of fluid flow in microfluidic devices can enable predictive and rational engineering of microfluidic circuits with rapid designer feedback. The shape of co-flowing streams in the inertial flow regime has b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a82a3f8cb0926985c099e4e3004d498
https://doi.org/10.1007/s10404-018-2093-x
https://doi.org/10.1007/s10404-018-2093-x