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Title: Automated detection and sorting of microencapsulation via machine learning

Abstract

Microfluidic-based microencapsulation requires significant oversight to prevent material and quality loss due to sporadic disruptions in fluid flow that routinely arise. State-of-the-art microcapsule production is laborious and relies on experts to monitor the process, e.g. through a microscope. Unnoticed defects diminish the quality of collected material and/or may cause irreversible clogging. To address these issues, we developed an automated monitoring and sorting system that operates on consumer-grade hardware in real-time. Using human-labeled microscope images acquired during typical operation, we train a convolutional neural network that assesses microencapsulation. Based on output from the machine learning algorithm, an integrated valving system collects desirable microcapsules or diverts waste material accordingly. Although the system notifies operators to make necessary adjustments to restore microencapsulation, we can extend the system to automate corrections. Since microfluidic-based production platforms customarily collect image and sensor data, machine learning can help to scale up and improve microfluidic techniques beyond microencapsulation.

Authors:
 [1];  [1];  [1];  [2];  [1];  [1];  [1];  [1];  [1]; ORCiD logo [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Google, Inc., Mountain View, CA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1507164
Alternate Identifier(s):
OSTI ID: 1568025
Report Number(s):
LLNL-JRNL-733470
Journal ID: ISSN 1473-0197; LCAHAM; 885205
Grant/Contract Number:  
AC52-07NA27344; LDRD Exploratory Research 17-ERD-037; LLNL-JRNL-748383
Resource Type:
Published Article
Journal Name:
Lab on a chip (Print)
Additional Journal Information:
Journal Name: Lab on a chip (Print); Journal Volume: 19; Journal Issue: 10; Journal ID: ISSN 1473-0197
Publisher:
Royal Society of Chemistry
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; 74 ATOMIC AND MOLECULAR PHYSICS

Citation Formats

Chu, Albert, Nguyen, Du, Talathi, Sachin S., Wilson, Aaron C., Ye, Congwang, Smith, William L., Kaplan, Alan D., Duoss, Eric B., Stolaroff, Joshua K., and Giera, Brian. Automated detection and sorting of microencapsulation via machine learning. United States: N. p., 2019. Web. doi:10.1039/C8LC01394B.
Chu, Albert, Nguyen, Du, Talathi, Sachin S., Wilson, Aaron C., Ye, Congwang, Smith, William L., Kaplan, Alan D., Duoss, Eric B., Stolaroff, Joshua K., & Giera, Brian. Automated detection and sorting of microencapsulation via machine learning. United States. doi:10.1039/C8LC01394B.
Chu, Albert, Nguyen, Du, Talathi, Sachin S., Wilson, Aaron C., Ye, Congwang, Smith, William L., Kaplan, Alan D., Duoss, Eric B., Stolaroff, Joshua K., and Giera, Brian. Mon . "Automated detection and sorting of microencapsulation via machine learning". United States. doi:10.1039/C8LC01394B.
@article{osti_1507164,
title = {Automated detection and sorting of microencapsulation via machine learning},
author = {Chu, Albert and Nguyen, Du and Talathi, Sachin S. and Wilson, Aaron C. and Ye, Congwang and Smith, William L. and Kaplan, Alan D. and Duoss, Eric B. and Stolaroff, Joshua K. and Giera, Brian},
abstractNote = {Microfluidic-based microencapsulation requires significant oversight to prevent material and quality loss due to sporadic disruptions in fluid flow that routinely arise. State-of-the-art microcapsule production is laborious and relies on experts to monitor the process, e.g. through a microscope. Unnoticed defects diminish the quality of collected material and/or may cause irreversible clogging. To address these issues, we developed an automated monitoring and sorting system that operates on consumer-grade hardware in real-time. Using human-labeled microscope images acquired during typical operation, we train a convolutional neural network that assesses microencapsulation. Based on output from the machine learning algorithm, an integrated valving system collects desirable microcapsules or diverts waste material accordingly. Although the system notifies operators to make necessary adjustments to restore microencapsulation, we can extend the system to automate corrections. Since microfluidic-based production platforms customarily collect image and sensor data, machine learning can help to scale up and improve microfluidic techniques beyond microencapsulation.},
doi = {10.1039/C8LC01394B},
journal = {Lab on a chip (Print)},
number = 10,
volume = 19,
place = {United States},
year = {2019},
month = {4}
}

Journal Article:
Free Publicly Available Full Text
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DOI: 10.1039/C8LC01394B

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Works referenced in this record:

Active droplet sorting in microfluidics: a review
journal, January 2017

  • Xi, Heng-Dong; Zheng, Hao; Guo, Wei
  • Lab on a Chip, Vol. 17, Issue 5
  • DOI: 10.1039/C6LC01435F

Microencapsulation of Dye- and Drug-Loaded Particles for Imaging and Controlled Release of Multiple Drugs
journal, January 2012

  • Khung, Yit-Lung; Li Lee, Wei; Chui, Kit Leong
  • Advanced Healthcare Materials, Vol. 1, Issue 2
  • DOI: 10.1002/adhm.201100007

CNC-loaded hydrogel particles generated from single- and double-emulsion drops
journal, March 2015

  • Ye, Congwang; Kennedy, Lauren; Shirk, Kathryn
  • Green Materials, Vol. 3, Issue 1
  • DOI: 10.1680/gmat.14.00016

Large-scale droplet production in microfluidic devices—an industrial perspective
journal, February 2013


Fabrication of solid lipid microcapsules containing ascorbic acid using a microfluidic technique
journal, June 2014


Deep learning
journal, May 2015

  • LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey
  • Nature, Vol. 521, Issue 7553
  • DOI: 10.1038/nature14539

Effective Formation of Silicone-in-Fluorocarbon-in-Water Double Emulsions: Studies on Droplet Morphology and Stability
journal, September 2002

  • Lee, Doo-Hyun; Goh, Yeong-Mee; Kim, Joong-Soo
  • Journal of Dispersion Science and Technology, Vol. 23, Issue 4
  • DOI: 10.1081/DIS-120014017

CO2 Absorption Kinetics of Micro-encapsulated Ionic Liquids
journal, July 2017


Optofluid-Based Reflective Displays
journal, April 2018

  • Jin, Mingliang; Shen, Shitao; Yi, Zichuan
  • Micromachines, Vol. 9, Issue 4
  • DOI: 10.3390/mi9040159

Nonviral gene vector formation in monodispersed picolitre incubator for consistent gene delivery
journal, January 2009

  • Hsieh, Albert Tsung-Hsi; Hori, Nicole; Massoudi, Rustin
  • Lab on a Chip, Vol. 9, Issue 18
  • DOI: 10.1039/b823191e

Novel Parallel Integration of Microfluidic Device Network for Emulsion Formation
journal, October 2009

  • Tetradis-Meris, Georgios; Rossetti, Damiano; Pulido de Torres, Concepción
  • Industrial & Engineering Chemistry Research, Vol. 48, Issue 19
  • DOI: 10.1021/ie900165b

Layer-by-Layer Assembled Nanocontainers for Self-Healing Corrosion Protection
journal, July 2006

  • Shchukin, D. G.; Zheludkevich, M.; Yasakau, K.
  • Advanced Materials, Vol. 18, Issue 13
  • DOI: 10.1002/adma.200502053

Microfluidics: Fluid physics at the nanoliter scale
journal, October 2005


Microencapsulation of advanced solvents for carbon capture
journal, January 2016

  • Stolaroff, Joshuah K.; Ye, Congwang; Oakdale, James S.
  • Faraday Discussions, Vol. 192
  • DOI: 10.1039/C6FD00049E

Microfluidic Fabrication of Monodisperse Biocompatible and Biodegradable Polymersomes with Controlled Permeability
journal, July 2008

  • Shum, Ho Cheung; Kim, Jin-Woong; Weitz, David A.
  • Journal of the American Chemical Society, Vol. 130, Issue 29
  • DOI: 10.1021/ja802157y

Art on the Nanoscale and Beyond
journal, December 2015

  • Yetisen, Ali K.; Coskun, Ahmet F.; England, Grant
  • Advanced Materials, Vol. 28, Issue 9
  • DOI: 10.1002/adma.201502382

Double emulsion production in glass capillary microfluidic device: Parametric investigation of droplet generation behaviour
journal, July 2015

  • Nabavi, Seyed Ali; Vladisavljević, Goran T.; Gu, Sai
  • Chemical Engineering Science, Vol. 130
  • DOI: 10.1016/j.ces.2015.03.004

Microfluidic Melt Emulsification for Encapsulation and Release of Actives
journal, November 2010

  • Sun, Bing Jie; Shum, Ho Cheung; Holtze, Christian
  • ACS Applied Materials & Interfaces, Vol. 2, Issue 12
  • DOI: 10.1021/am100860b

Microencapsulation of theophylline in whey proteins: effects of core-to-wall ratio
journal, September 2000


Monodisperse Double Emulsions Generated from a Microcapillary Device
journal, April 2005


The present and future role of microfluidics in biomedical research
journal, March 2014

  • Sackmann, Eric K.; Fulton, Anna L.; Beebe, David J.
  • Nature, Vol. 507, Issue 7491
  • DOI: 10.1038/nature13118

A review of microvalves
journal, March 2006


Microfluidic impedance-based flow cytometry
journal, May 2010

  • Cheung, Karen C.; Di Berardino, Marco; Schade-Kampmann, Grit
  • Cytometry Part A, Vol. 77A, Issue 7
  • DOI: 10.1002/cyto.a.20910

A Survey on Transfer Learning
journal, October 2010

  • Pan, Sinno Jialin; Yang, Qiang
  • IEEE Transactions on Knowledge and Data Engineering, Vol. 22, Issue 10
  • DOI: 10.1109/TKDE.2009.191

Silicon and glass very large scale microfluidic droplet integration for terascale generation of polymer microparticles
journal, March 2018


Microfluidic DNA microarray analysis: A review
journal, February 2011


Microfluidic systems for chemical kinetics that rely on chaotic mixing in droplets
journal, May 2004

  • Bringer, Michelle R.; Gerdts, Cory J.; Song, Helen
  • Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, Vol. 362, Issue 1818
  • DOI: 10.1098/rsta.2003.1364

Microfluidic platforms for lab-on-a-chip applications
journal, January 2007

  • Haeberle, Stefan; Zengerle, Roland
  • Lab on a Chip, Vol. 7, Issue 9
  • DOI: 10.1039/b706364b

Biosensors and their applications – A review
journal, May 2016


NIH Image to ImageJ: 25 years of image analysis
journal, June 2012

  • Schneider, Caroline A.; Rasband, Wayne S.; Eliceiri, Kevin W.
  • Nature Methods, Vol. 9, Issue 7
  • DOI: 10.1038/nmeth.2089

REVIEW: Pregnancy tests: a review
journal, May 1992


Nanoencapsulation of phase change materials for advanced thermal energy storage systems
journal, January 2018

  • Shchukina, E. M.; Graham, M.; Zheng, Z.
  • Chemical Society Reviews, Vol. 47, Issue 11
  • DOI: 10.1039/C8CS00099A

Self-Healing Polymer Coatings
journal, February 2009

  • Cho, Soo Hyoun; White, Scott R.; Braun, Paul V.
  • Advanced Materials, Vol. 21, Issue 6
  • DOI: 10.1002/adma.200802008

Acceleration of a Diels–Alder reaction by a self-assembled molecular capsule
journal, January 1997

  • Kang, Jongmin; Rebek, Julius
  • Nature, Vol. 385, Issue 6611, p. 50-52
  • DOI: 10.1038/385050a0

Surface-Engineered Nanocontainers for Entrapment of Corrosion Inhibitors
journal, April 2007


Encapsulated liquid sorbents for carbon dioxide capture
journal, February 2015

  • Vericella, John J.; Baker, Sarah E.; Stolaroff, Joshuah K.
  • Nature Communications, Vol. 6, Issue 1
  • DOI: 10.1038/ncomms7124

High throughput production of single core double emulsions in a parallelized microfluidic device
journal, January 2012

  • Romanowsky, Mark B.; Abate, Adam R.; Rotem, Assaf
  • Lab on a Chip, Vol. 12, Issue 4
  • DOI: 10.1039/c2lc21033a