Published September 7, 2022 | Version v1
Dataset Open

Surfactant-laden droplet size prediction in a flow-focusing microchannel: a data-driven approach

Authors/Creators

  • 1. ThAMeS Multiphase, Department of Chemical Engineering, University College London
  • 2. Data Science Institute, Imperial College London/Department of Earth Science and Engineering, Imperial College London
  • 3. School of Chemical Engineering, University of Birmingham
  • 4. Department of Chemical Engineering, Imperial College London

Description

Experimental data of the article: Surfactant-laden droplet size prediction in a flow-
focusing microchannel: a data-driven approach
DOI: 10.1039/D2LC00416J
contact: l.chagot@ucl.ac.uk

Matrix (MATLAB format) of the experimental training and test datasets
(respectively matTrainingDataSet and matTestDataSet)

For both matrix, the variable inputs contains:
    - the flow rate of the continous phase (:,1), unit [mL/min]
    - the flow rate of the dispered phase (:,2), unit [mL/min]
    - the equilibrium interfacial tension (:,3), unit [mN/m]
    - the surfactant concentration (:,4), unit [mM]
    - the critical micelle concentration (CMC) (:,5), unit [mM]

and the variable output contains:
     - the droplet diameter (:,1), unit [mm]

Files

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md5:a6c41bba18e4f232e7f25e2207fd183c
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Additional details

Funding

UK Research and Innovation
Health assessment across biological length scales for personal pollution exposure and its mitigation (INHALE) EP/T003189/1
UK Research and Innovation
DTP 2018-19 University College London EP/R513143/1
UK Research and Innovation
PREdictive Modelling with QuantIfication of UncERtainty for MultiphasE Systems (PREMIERE) EP/T000414/1