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Showing 1–2 of 2 results
Advanced filters: Author: Ali Lashkaripour Clear advanced filters
  • Devices for droplet generation are at the heart of many microfluidic applications but difficult to tailor for specific cases. Lashkaripour et al. show how design customization can greatly be simplified by combining rapid prototyping with data-driven machine learning strategies.

    • Ali Lashkaripour
    • Christopher Rodriguez
    • Douglas Densmore
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-14
  • Generating microfluidic droplets with application-specific desired characteristics is hard. Here the authors report fluid-agnostic machine learning models capable of accurately predicting device geometries and flow conditions required to generate stable single and double emulsions.

    • Ali Lashkaripour
    • David P. McIntyre
    • Polly M. Fordyce
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-16