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Title: Automated control of microfluidic devices based on machine learning

Abstract

A system is provided to automatically monitor and control the operation of a microfluidic device using machine learning technology. The system receives images of a channel of a microfluidic device collected by a camera during operation of the microfluidic device. Upon receiving an image, the system applies a classifier to the image to classify the operation of the microfluidic device as normal, in which no adjustment to the operation is needed, or as abnormal, in which an adjustment to the operation is needed. When an image is classified as normal, the system may make no adjustment to the microfluidic device. If, however, an image is classified as abnormal, the system may output an indication that the operation is abnormal, output an indication of a needed adjustment, or control the microfluidic device to make the needed adjustment.

Inventors:
; ; ; ; ; ;
Issue Date:
Research Org.:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1840253
Patent Number(s):
11061042
Application Number:
16/376,380
Assignee:
Lawrence Livermore National Security, LLC (Livermore, CA)
Patent Classifications (CPCs):
B - PERFORMING OPERATIONS B01 - PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL B01L - CHEMICAL OR PHYSICAL LABORATORY APPARATUS FOR GENERAL USE
G - PHYSICS G01 - MEASURING G01N - INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
DOE Contract Number:  
AC52-07NA27344
Resource Type:
Patent
Resource Relation:
Patent File Date: 04/05/2019
Country of Publication:
United States
Language:
English

Citation Formats

Giera, Brian, Duoss, Eric B., Nguyen, Du, Smith, William Joseph, Talathi, Sachin Subhash, Wilson, Aaron Creighton, and Ye, Congwang. Automated control of microfluidic devices based on machine learning. United States: N. p., 2021. Web.
Giera, Brian, Duoss, Eric B., Nguyen, Du, Smith, William Joseph, Talathi, Sachin Subhash, Wilson, Aaron Creighton, & Ye, Congwang. Automated control of microfluidic devices based on machine learning. United States.
Giera, Brian, Duoss, Eric B., Nguyen, Du, Smith, William Joseph, Talathi, Sachin Subhash, Wilson, Aaron Creighton, and Ye, Congwang. Tue . "Automated control of microfluidic devices based on machine learning". United States. https://www.osti.gov/servlets/purl/1840253.
@article{osti_1840253,
title = {Automated control of microfluidic devices based on machine learning},
author = {Giera, Brian and Duoss, Eric B. and Nguyen, Du and Smith, William Joseph and Talathi, Sachin Subhash and Wilson, Aaron Creighton and Ye, Congwang},
abstractNote = {A system is provided to automatically monitor and control the operation of a microfluidic device using machine learning technology. The system receives images of a channel of a microfluidic device collected by a camera during operation of the microfluidic device. Upon receiving an image, the system applies a classifier to the image to classify the operation of the microfluidic device as normal, in which no adjustment to the operation is needed, or as abnormal, in which an adjustment to the operation is needed. When an image is classified as normal, the system may make no adjustment to the microfluidic device. If, however, an image is classified as abnormal, the system may output an indication that the operation is abnormal, output an indication of a needed adjustment, or control the microfluidic device to make the needed adjustment.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2021},
month = {7}
}

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