Projects per year
Abstract
Flow linear dichroism is a biophysical spectroscopic technique that exploits the shearinduced alignment of elongated particles in suspension. Motivated by the broad aim of optimizing the sensitivity of this technique, and more specifically by a handheld synthetic biotechnology prototype for waterbornepathogen detection, a model of steady and oscillating pressuredriven channel flow and orientation dynamics of a suspension of slender microscopic fibres is developed. The model couples the FokkerPlanck equation for Brownian suspensions with the narrow channel flow equations, the latter modified to incorporate mechanical anisotropy induced by the particles. The linear dichroism signal is estimated through integrating the perpendicular components of the distribution function via an appropriate formula which takes the biaxial nature of the orientation into account. For the specific application of pathogen detection via binding of M13 bacteriophage, it is found that increases in the channel depth are more significant in improving the linear dichroism signal than increases in the channel width. Increasing the channel depth to 2 mm and pressure gradient to 5 × 10 4 Pa m 1 essentially maximizes the alignment. Oscillating flow can produce nearly equal alignment to steady flow at appropriate frequencies, which has significant potential practical value in the analysis of small sample volumes.
Original language  English 

Article number  20190184 
Number of pages  21 
Journal  Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 
Volume  475 
Issue number  2232 
DOIs  
Publication status  Published  18 Dec 2019 
Keywords
 Brownian suspensions
 FokkerPlanck equation
 flowinduced alignment
 linear dichroism spectroscopy
Fingerprint
Dive into the research topics of 'Oriented suspension mechanics with application to improving flow linear dichroism spectroscopy'. Together they form a unique fingerprint.Projects
 1 Finished

Rapid sperm capture: integrating live imaging and machine learning to optimise fertility treatment
Engineering & Physical Science Research Council
1/07/16 → 30/06/22
Project: Research Councils