Machine learning has recently been introduced in the context of droplet microfluidics to
simplify the process of droplet formation, which is usually controlled by a variety of …

Optical tweezers exploit light–matter interactions to trap particles ranging from single atoms
to micrometer-sized eukaryotic cells. For this reason, optical tweezers are a ubiquitous tool …

Due to its ability to record position, intensity, and intensity distribution information, camera-
based monitoring of nanoparticles in optical traps can enable multi-parametric morpho …

Microrheology, the study of material flow at micron scales, has advanced significantly since
Robert Brown's discovery of Brownian motion in 1827. Mason and Weitz's seminal work in …

Differential dynamic microscopy (DDM) typically relies on movies containing hundreds or
thousands of frames to accurately quantify motion in soft matter systems. Using movies much …

Flow-induced self-assembly (FISA) is the phenomena of particle chaining in viscoelastic
fluids while experiencing shear flow. FISA has a large number of applications across many …

Microrheology with optical tweezers (MOT) is an all-optical technique that allows the user to
investigate a materials' viscoelastic properties at microscopic scales, and is particularly …

Optical tweezers (OTs) with structured light expand degrees of freedom of particle
manipulation. However, the studies of structured optical tweezers are usually accompanied …

Rheology is a wide-reaching field whose applications are underpinned by a prior
knowledge of the 'viscoelastic'properties of (complex) materials generally employed across …

Machine Learning for Fast Statistical Sensing Page 1 Machine Learning for Fast Statistical
Sensing Jack Radford1, Matthew G. Smith2, Philip Binner1, Ilya Starshynov1, Manlio Tassieri2 …