Carolina presents at the ISMC Poznań on the 23rd of September 2022

Trajectory of a microswimmer swimming inside an colloidal array (white dots) in the presence of 9% fuel. The trajectories are collor-coded according to the distance between the microswimmer and its nearest neighbour.(Image by C. van Baalen.)
On the 23rd of September Carolina will present her work on microswimmers in colloidal arrays at the ISMC in Poznań, Poland. In her talk, titled “Confounding Interactions with Obstacles: How Colloidal Lattices Steer the Dynamics of Catalytic Microswimmers“, she will show how colloidal lattices self-assembled at a fluid-fluid interface can steer the dynamics of catalytic microswimmers hovering along the interface.

Faster and more accurate geometrical-optics optical force calculation using neural networks on ArXiv

Focused rays scattered by an ellipsoidal particle (left). Optical torque along y calculated in the x-y plane using ray scattering with a grid of 400 rays (up, right) and using a trained neural network with the same number of rays (down, right). (Image by the Authors of the manuscript.)
Faster and more accurate geometrical-optics optical force calculation using neural networks
David Bronte Ciriza, Alessandro Magazzù, Agnese Callegari, Gunther Barbosa, Antonio A. R. Neves, Maria A. Iatì, Giovanni Volpe, Onofrio M. Maragò
arXiv: 2209.04032

Optical forces are often calculated by discretizing the trapping light beam into a set of rays and using geometrical optics to compute the exchange of momentum. However, the number of rays sets a trade-off between calculation speed and accuracy. Here, we show that using neural networks permits one to overcome this limitation, obtaining not only faster but also more accurate simulations. We demonstrate this using an optically trapped spherical particle for which we obtain an analytical solution to use as ground truth. Then, we take advantage of the acceleration provided by neural networks to study the dynamics of an ellipsoidal particle in a double trap, which would be computationally impossible otherwise.

Presentation by Chun-Jen Chen at DPG Meeting of the Condensed Matter Section, 4th – 9th of Sep. 2022

Chun-Jen Chen in front of the big screen with his presentation slide. (Photo by Robert C. Löffler.)
On the 7th of September, Chun-Jen Chen gave a talk titled “Collective response of microrobotic swarms to external threats” during his participation of the 2022 DPG Meeting of the Condensed Matter Section in Regensburg, Germany. The 15-minute talk focused on the novel stratergy to implement extra feature into a collective social behaviour and corresponding experimental results with microrobotic colloidal particles. The talk also delivered prospective impact of such findings on microrobotic swarm design and undiscovered phase behaviours between collective behavioural states. The meeting gethered a wide range of bio-physists and active/soft-matter physists and trigged inspiring discussion across different projects.

You can find out more detail about the presented work as the contents of this talk was based on Chun-Jen and Clemens Bechinger’s publication at New J. Phys. 24 033001 (2022).