Igor Aronson/Argonne Active magnetic colloids. m agnetic particles. oil. novel feature : liquid-liquid interface reduced density contrast/tension →reduction of size new control knobs novel self-assembled structures
A Snezhko & IAronson, Magnetic Manipulation of Self-Assembled Colloidal Asters, Nature Materials 2011
aster’s speed vs in-plane dc magnetic field
self-generated flow aster/anti-aster pair
magnetic field (Oe)
Materials opportunities for soft robotics, George Whitesides, AngChem 2011:
materials with actively tunable compliance … enable fundamentally new strategies for manipulation
4 aster-array: new functionality
“soft” colloidal robot: grip, move, release
Energy.gov: Tiny Terminators: New Micro-Robots Assemble, Repair Themselves and Are Surprisingly Strong
hive.msd.anl.gov GPU cluster
Nvidia GTX 480
ngene, 4 GPUs cluster,
-novel features: toroidal flows in the bulk
-modeling of asters and array of asters
MSD GPU cluster, BES DOE capital equipment (42 Fermi GPU cards, 50 TFlops, single precision)
featured in NY Times,Forbes, Wired, SciAmerican
highlighted as Argonne’s major success in 2010
YouTube > 100,000 views
Sokolov, Apodaca, Grzybowski, I. Aronson, PNAS, 2010
magnetically-controlled micro-shuttle powered by bacteria
Preliminary data suggests that cells stall during division. (Yellow arrow highlight additional time between frames during division. Red arrow point to septum forming)
Questions: How does polarity of mother cell relate to daughter cells?
Does phase of reversal period get passed to daughter cells?
M. xanthus is known to produce slime tracks when gliding on agar.
By highlighting cell trajectories, cell-slime track locations can be visualized and cell-track interactions can be analyzed
Questions: How much turning can cells undergo to get onto track?
Segmentation of raw image data is processed to form meshes on each cell. The mesh can be used to extract a central line that can be analyzed for bending of cells during collisions or during cell-trail interaction.
We are also interested in cell bending and cell orientation and spatial ordering as cells dynamical form and move as groups.
Simulation Movie Link (http://biomath.math.nd.edu/compbio/CellSim4.gif)
Simulations are being run to study flexibility, adhesion and cell reversals on cell clustering dynamics. Also, simulations that look at cell–slime track interaction are being run by coupling cells to a 2D substrate that simulates slime trails left by cells. (Slime not shown, but the 2d grid represents the scaler field discretization)