We are interested in controlling and understanding dynamics of complex networks in space and time, and using what we learn to solve problems. The networks we work with span networks of reactions, networks of cells, and networks of organisms. The problems include human health (including simple solutions for resource-limited settings) and environment. We find microfluidics to be useful in our work, both as a tool with which to control and understand networks, and as a tool with which to implement ideas.
By definition, microfluidics is a technology for liquid handling in very small size scales (femto- to micro liter volumes and characteristic lengths between 1 and 1000 µm). This technology represents a miniaturization strategy for chemical and biological analysis, involving different protocols of liquid metering, mixing, separation, dispensing etc. Many processes can be made cheaper, more rugged and portable, which is crucial in, for instance, various brabches of medical diagnostics and treatment. These and other reasons are a driving force for the development of so called "lab on a chip" technologies, which aim to make analytical procedures faster, cheaper and the involved devices smaller.
|Ion Channels and Cells
Ion channels are macromolecular pores that span through the cell plasma and organelle membranes. These pores govern the transport of ions and charged molecules across the membrane, which is one of the basic components in the frequent communication between cells in our bodies, underlying everything from thoughts to heartbeats. In fact, ion channels underlie basic processes for cell to cell communication such as muscle function, metabolism, and immunity, as well as more complicated ones such as feelings, learning, and memory formation.
|Nanomaterials and Nanochemistry
We are developing techniques for creating complex two- and three-dimensional networks of nanotubes and µm-sized containers from liquid crystalline lipid bilayer materials based on the propensity in such materials to undergo complex shape-transitions under mechanical and chemical excitations. Both forced shape transformations, and self organization in initially state-selected networks are used to obtain various end-point geometries. In the networks, we can control, among other properties; the connectivity, container size, container content, nanotube length, nanotube radius and angle between nanotube extensions.