The BioFM research group specialises in the modelling and simulation of fluid mechanics in biological systems and biologically relevant microfluidics.
My group is investigating how microfluidic devices can be designed and employed to characterise and separate particles, most prominently biological particles, such as blood cells, bacteria or cancer cells. The primary applications are lab-on-chip devices for point-of-care diagnostics. This includes deterministic lateral displacement (DLD), inertial microfluidics and other approaches. The challenge is the complex interaction of particle dynamics, device geometry and fluid flow.
K.K. Zeming, R. Vernekar, M.T. Chua, K.Y. Quek, G. Sutton, T. Krüger, W.S. Kuan, J. Han. Label-free biophysical markers from whole blood microfluidic immune profiling reveal severe immune response signatures. Small 2006123 (2021) Small
Q. Zhou, J. Fidalgo, M.O. Bernabeu, M.S.N. Oliveira, T. Krüger. Emergent cell-free layer asymmetry and biased haematocrit partition in a biomimetic vascular network of successive bifurcations. Soft Matter 17, 3619-3633 (2021) Soft Matter
Q. Zhou, J. Fidalgo, L. Calvi, M.O. Bernabeu, P.R. Hoskins, M.S.N. Oliveira, T. Krüger. Spatiotemporal Dynamics of Dilute Red Blood Cell Suspensions in Low-Inertia Microchannel Flow. Biophys. J. 118, 2561-2573 (2020). arXiv, ScienceDirect
D.W. Inglis, R. Vernekar, T. Krüger, S. Feng. The fluidic resistance of an array of obstacles and a method for improving boundaries for Deterministic Lateral Displacement arrays. Microfluidics Nanofluidics 24, 18 (2020). Springer Link
Blood flow modelling
The understanding of blood flow in health and disease is a central research topic in Engineering and Medicine. Typical diseases affecting or affected by blood flow are cancer, hypertension, diabetes and malaria. My group is developing advanced models and software to characterise particulate blood flow in capillary networks, tumour vasculature and the retina. Most of the blood flow modelling in my group is microscopic, which means that blood cells and their flow-induced deformations are resolved. This requires fluid-structure interaction algorithms, such as lattice Boltzmann, finite elements and immersed boundaries.
R. Enjalbert, D. Hardman, T Krüger, M.O. Bernabeu. Vessel compression biases red blood cell partitioning at bifurcations in a haematocrit-dependent manner: implications for tumour blood flow. PNAS (in press) bioRxiv
M.O. Bernabeu, J. Köry, J.A. Grogan, B. Markelc, A.B. Ricol, M. d’Avezac, R. Enjalbert, J. Kaeppler, N. Daly, J. Hetherington, T. Krüger, P.K. Maini, J.M. Pitt-Francis, R.J. Muschel, T. Alarcón, H.M. Byrne. Abnormal morphology biases haematocrit distribution in tumour vasculature and contributes to heterogeneity in tissue oxygenation. PNAS 117, 27811-27819 (2020) bioRxiv, PNAS
H. Wang, T. Krüger, F. Varnik. Effects of size and elasticity on the relation between flow velocity and wall shear stress in side-wall aneurysms: A lattice Boltzmann-based computer simulation study. PLoS ONE 15, e0227770 (2020). bioRxiv, PLoS
Complex flow modelling
There is no unique and clear definition of “complex flows”. It can be understood as a research field involving fluid flow coupled with additional physical mechanisms, such as diffusion, surface tension (capillary effects), phase change (e.g. boiling) and particle growth/precipitation out of solution. In my group, the unifying element is the lattice-Boltzmann method (see our book).