YOLO models trained on synthetic datasets for four particle shapes identify 2D colloidal assemblies with near-perfect accuracy on synthetic images but 43.1% average error on experimental images, varying by particle geometry.
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Directed droplet motion via surface property gradients provides a versatile approach for fluid transport in applications like digital microfluidics and bio-diagnostics.
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Application of Machine Learning for the Identification of 2D Colloidal Assemblies: A Case Study on Particles of Distinct Shapes
YOLO models trained on synthetic datasets for four particle shapes identify 2D colloidal assemblies with near-perfect accuracy on synthetic images but 43.1% average error on experimental images, varying by particle geometry.
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Directed droplet motion -- Its versatile nature and anticipated applications
Directed droplet motion via surface property gradients provides a versatile approach for fluid transport in applications like digital microfluidics and bio-diagnostics.