arXiv subjects

Kaitlyn Hood

Publications and source records attributed to Kaitlyn Hood.

5 recordsLinked to original sources

arXiv2021

Fluid flow in the sarcomere

A highly organized and densely packed lattice of molecular machinery within the sarcomeres of muscle cells powers contraction. Although many of the proteins that drive contraction have been studied extensively, the mechanical impact of fluid shearing within the lattice of molecular machinery has received minimal attention. It was recently proposed that fluid flow augments substrate transport in the sarcomere, however, this analysis used analytical models of fluid flow in the molecular machinery that could not capture its full complexity. By building a finite element model of the sarcomere, we estimate the explicit flow field, and contrast it with analytical models. Our results demonstrate that viscous drag forces on sliding filaments are surprisingly small in contrast to the forces generated by single myosin molecular motors. This model also indicates that the energetic cost of fluid flow through viscous shearing with lattice proteins is likely minimal. The model also highlights a steep velocity gradient between sliding filaments and demonstrates that the maximal radial fluid velocity occurs near the tips of the filaments. To our knowledge, this is the first computational analysis of fluid flow within the highly structured sarcomere.

q-bio.SC↗

arXiv2019

Marine crustaceans with hairy appendages: role of hydrodynamic boundary layers in sensing and feeding

Decapod crustaceans have appendages with an array of rigid hairs covered in chemo-receptors, used to sense and track food. Crustaceans directly influence the flow behavior by changing the speed of flow past the hairy surface, thereby manipulating the Reynolds number (Re). Hairs act either as a rake - diverting flow around the hair array, or as a sieve - filtering flow through the hairs. In our experiments, we uncover a third transitional phase: deflection - where the flow partially penetrates the hair array and is deflected laterally. We develop a reduced order model that predicts the flow phase based on the depth of the boundary layer on a single hair. This model with no fitting parameters agrees very well with our experimental data. Additionally, our model agrees well with measurements of both chemo-sensing and suspension-feeding crustaceans, and can be generalized for many different geometries.

physics.flu-dyn↗

arXiv2018

Pairwise interactions in inertially-driven one-dimensional microfluidic crystals

In microfluidic devices, inertia drives particles to focus on a finite number of inertial focusing streamlines. Particles on the same streamline interact to form one-dimensional microfluidic crystals (or "particle trains"). Here we develop an asymptotic theory to describe the pairwise interactions underlying the formation of a 1D crystal. Surprisingly, we show that particles assemble into stable equilibria, analogous to the motion of a damped spring. Although previously it has been assumed that particle spacings scale with particle diameters, we show that the equilibrium spacing of particles depends on the distance between the inertial focusing streamline and the nearest channel wall, and therefore can be controlled by tuning the particle radius.

physics.flu-dyn↗

arXiv2017

Direct Measurement of Particle Inertial Migration in Rectangular Microchannels

Particles traveling at high velocities through microfluidic channels migrate from their starting streamlines due to inertial lift forces. Theories predict different scaling laws for these forces and there is little experimental evidence by which to validate theory. Here we experimentally measure the three dimensional positions and migration velocities of particles. Our experimental method relies on a combination of sub-pixel accurate particle tracking and velocimetric reconstruction of the depth dimension to track thousands of individual particles in three dimensions. We show that there is no simple scaling of inertial forces upon particle size, but that migration velocities agree well with numerical simulations and with a two-term asymptotic theory that contains no unmeasured parameters.

physics.flu-dyn↗

arXiv2014

Inertial migration of a rigid sphere in three-dimensional Poiseuille flow

Inertial lift forces are exploited within inertial microfluidic devices to position, segregate, and sort particles or droplets. However the forces and their focusing positions can currently only be predicted by numerical simulations, making rational device design very difficult. Here we develop theory for the forces on particles in microchannel geometries. We use numerical experiments to dissect the dominant balances within the Navier-Stokes equations and derive an asymptotic model to predict the lateral force on the particle as a function of particle size. Our asymptotic model is valid for a wide array of particle sizes and Reynolds numbers, and allows us to predict how focusing position depends on particle size.

physics.flu-dyn↗