Reinforcement Learning for Dynamic Microfluidic Control-Reference-Cited by-同舟云学术

Reinforcement Learning for Dynamic Microfluidic Control

Published:2018-08-29 Issue:8 Volume:3 Page:10084-10091
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Dressler Oliver J.¹,Howes Philip D.¹^ORCID,Choo Jaebum²^ORCID,deMello Andrew J.¹^ORCID

Affiliation:

1. Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir Prelog Weg 1, 8093 Zürich, Switzerland

2. Department of Bionano Technology, Hanyang University, Ansan 426-791, South Korea

Funder

Eidgen?ssische Technische Hochschule Z?rich

National Research Foundation of Korea

H2020 Marie Sklodowska-Curie Actions

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

http://pubs.acs.org/doi/pdf/10.1021/acsomega.8b01485

Reference50 articles.

1. Genetic interaction mapping with microfluidic-based single cell sequencing

2. Microfluidics for cell-based high throughput screening platforms—A review

3. Chemical and Biological Dynamics Using Droplet-Based Microfluidics

4. Tuning-free controller to accurately regulate flow rates in a microfluidic network

5. The perceptron: A probabilistic model for information storage and organization in the brain.

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