Ordering and Encapsulation in Viscoelastic Microfluidic Flows

Abstract

Viscoelastic polymer solutions have been employed as suspending liquids for a myriad of microfluidic applications including particle or cell focusing and sorting. Very recently viscoelastic liquids have been shown to drive the formation of strings of equally spaced particles called "particle trains". The formation of "particle trains" may have unprecedented benefits on important biomedical applications. For example single cell analysis benefit from encapsulation of a single cell or particle in a droplet for high throughput decoding and sequencing of cellular information. In flow cytometry particle or cell train formation is crucial for analysing their properties without interference from overlapping cells or particles. To date, limited experimental studies are available on viscoelastic particle train formation. In Chapter 4 of the thesis, we demonstrate that a viscoelastic shear thinning aqueous 0.1 wt% xanthan gum XG solution drives the self-assembly of particle trains on channel centerline in a serpentine microfluidic device. In addition, to account for the fluctuations in the number of flowing particles, we introduced the concept of local particle concentration, observing that an increase in local particle concentration led to an increase multi-particle string formation. Thereafter, we simplified the microfluidic configuration to drastically reduce multi-particle string formation. In Chapter 5, we successfully employed a microfluidic device with sixteentrapezoidal elements to reduce multi-particle string formation down to 5 % and studied the effect of confinement ratio on ordering dynamics of particles in 0.2 wt% XG, where larger confinement ratios led to self-assembly at shorter distances. Subsequently, in Chapter 6 we studied the particle encapsulation in a T-junction microfluidic device, using a non-Newtonian viscoelastic 0.1 wt% hyaluronic acid HA solution in phosphate buffer saline as suspending liquid. We first studied the non-Newtonian droplet formation mechanisms, finding that the data for the normalised droplet length scaled as the Newtonian ones. We then performed viscoelastic encapsulation experiments and identified experimental conditions for which the single encapsulation efficiency was larger than the stochastic limit predicted by the Poisson statistics. Overall, our work provides insights into fluid characteristics, experimental conditions and microfluidic devices required to form particle trains and to encapsulate particles in droplets.• This work has not previously been accepted in substance for any degree and is not being concurrently submitted in candidature for any degree.Signed: Anoshanth Jeyasountharan Date: 29/09/2022• This thesis is the result of my own investigations, except where otherwise stated.Other sources are acknowledged by footnotes giving explicit references. A bibliography is appended.