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Presentation by G. Wang at ECIS, Copenhagen, 5 September 2024

Schematic and brightfield image (inset) of the movement of 16μm diameter micromotor under the illumination of linearly polarized 1064nm laser. (Image by G. Wang.)
Light-driven metamachines
Gan Wang, Marcel Rey, Antonio Ciarlo, Mohanmmad Mahdi Shanei, Kunli Xiong, Giuseppe Pesce, Mikael Käll and Giovanni Volpe
Date: 5 September 2024
Time: 15:45-16:00

The incorporation of Moore’s law into integrated circuits has spurred opportunities for downsizing traditional mechanical components. Despite advancements in single on-chip motors using electrical, optical, and magnetic drives under ~100 μm, creating complex machines with multiple units remains challenging. Here, we developed a ~10 μm on-chip micromotor using a method compatible with complementary metal oxide semiconductors (CMOS) process. The meta-surface is embedded with the motor to control the incident laser beam direction, enabling momentum exchange with light for movement. The rotation direction and speed are adjustable through the meta-surface, along with the intensity and polarization of applied light. By combining these motors and controlling the configuration, we create complex machines with a size similar to traditional machines below 50um, such as the rotary motion mode of multiple gear coupled gear trains, and the linear motion mode combined with rack and pinion, and combine the micro metal The mirror is introduced into the machine to realize the self-controlled scanning function of the laser in a fixed area.

Aarón Domenzain joins the Soft Matter Lab

(Photo by A. Ciarlo.)
Aarón Domenzain starts his PhD at the Physics Department of the University of Gothenburg on 2 September 2024.

Aarón has a Master degree in Nanotechnology from Chalmers University of Technology, Gothenburg.

In his PhD, he will focus on optical tweezers and applications.

Erik Olsén joins the Soft Matter Lab

(Photo by A. Ciarlo.)
Erik Olsén started his postdoc at the Physics Department of the University of Gothenburg on 26th August 2024. His research is funded by a Swedish research council internation postdoc fellowship with grant nr 2024-00439.

Erik received a PhD degree 2023 in physics from Chalmers University of Technology, Sweden. In his thesis he focused on optical particle characterisation of nanoparticles and submicron particles, with an emphasis on label-free characterisation methods.

The Soft Matter Lab will administrate the postdoc grant while Erik will be in the lab of Sabrina Leslie at University of British Columbia (UBC). At UBC, Erik will combine different image modalities with confined lens induced confinement (CLiC) to characterise different types of biological nanoparticles.

Flavia Theisel Bravo joins the Soft Matter Lab

(Photo by A. Ciarlo.)
Flavia Theisel Bravo starts her DAAD-RISE internship at the Physics Department of the University of Gothenburg on 26 August 2024.

Flavia is a masters student at the department of physics, TU Dresden, Germany.

In her internship, she will focus on the simulation of intracavity optical trapping.

Her internship will last until 18 October 2024.

Mirja Granfors won best early career researcher poster award at ETAI 2024, San Diego

Mirja Granfors with the Best Poster Award at SPIE conference in San Diego. (Photo by G. Volpe.)
Mirja Granfors won the best early career researcher poster award at Emerging Topics in Artificial Intelligence (ETAI) 2024 held in San Diego, from 18 to 24 August 2024. The award, consisting of a certificate and a cash prize, is offered by the organizers of the conference, and SPIE Optics + Photonics, and is sponsored by G-Research.

In this poster, Mirja presented her recent work on the development of a graph autoencoder. This graph autoencoder effectively summarizes graph structures while preserving important topological details through multiple hierarchical pooling steps. This enables the extraction of physical parameters describing the graphs. She demonstrated the performance of the graph autoencoder across diverse graph data originating from complicated systems, including the classification of protein assembly structures from single-molecule localization microscopy data, as well as the analysis of collective behavior and correlations between brain connections and age.

Best Poster Award (Image by M. Granfors.)
Mirja @ Poster Pops Presentation (Photo by A. Callegari.)
Mirja @ Poster Pops Presentation (Photo by A. Callegari.)
ETAI Best Poster and Best Presentation Award Ceremony @ SPIE-ETAI. People (left to right): Joana B. Pereira (conference chair), Patrick Grant, Yuzhu Li, Mirja Granfors, Diptabrata Paul. (Photo by G. Volpe.)

Presentation by A. Callegari at SPIE-OTOM, San Diego, 22 August 2024

One exemplar of the HEXBUGS used in the experiment. (Image by the Authors of the manuscript.)
Active Matter Experiments with Toy Robots
Angelo Barona Balda, Aykut Argun, Agnese Callegari, Giovanni Volpe
SPIE-OTOM, San Diego, CA, USA, 18 – 22 August 2024
Date: 22 August 2024
Time: 3:00 PM – 3:15 PM
Place: Conv. Ctr. Room 6D

Active matter is based on concepts of nonequilibrium thermodynamics applied to the most diverse disciplines. Active Brownian particles, unlike their passive counterparts, self-propel and give rise to complex behaviors distinctive of active matter. As the field is relatively recent, active matter still lacks curricular inclusion. Here, we propose macroscopic experiments using Hexbugs, a commercial toy robot, demonstrating effects peculiar of active systems, such as the setting into motion of passive objects via active particles, the sorting of active particles based on their mobility and chirality. Additionally, we provide a demonstration of Casimir-like attraction between planar objects mediated by active particles.

Reference
Angelo Barona Balda, Aykut Argun, Agnese Callegari, Giovanni Volpe, Playing with Active Matter, arXiv: 2209.04168

Poster by A. Callegari at SPIE-OTOM, San Diego, 19 August 2024

Trajectory of a hexagonal cluster formed by a transparent particle (blu circle) and six light-absorbing particles (red circles) in a traveling sinusoidal optical pattern, in the absence of thermal noise. The direction of the motion of the optical pattern is given by the arrow. The trajectory’s duration is 30 s. (Image by A. Bergsten.)
Chiral active molecules formation via non-reciprocal interactions
Agnese Callegari, Niphredil Klint, John Klint, Alfred Bergsten, Alex Lech, and Giovanni Volpe
SPIE-OTOM, San Diego, CA, USA, 18 – 22 August 2024
Date: 19 August 2024
Time: 5:30 PM – 7:00 PM
Place: Conv. Ctr. Exhibit Hall A

In 2019, Schmidt et al. demonstrated light-induced assembly of active colloidal molecules. They used two types of colloidal particles in a water-lutidine mixture: one transparent and one slightly absorbing light. In their experiment, this determined a non-reciprocal interaction between light-absorbing and transparent particles and promoted active molecule formation controlled by light. Beyond experimental details, we here explore the effects of this non-reciprocal interaction solely, showing its role in active molecule formation and self-propulsion. Simulation allows for the study of complex light profiles, enabling precise control over assembly and propulsion properties, relevant for targeted microscopic delivery.

Poster by A. Callegari at SPIE-OTOM, San Diego, 19 August 2024

Simplified sketch of the neural network used for the simulations of intracavity optical trapping. (Image by A. Callegari.)
Neural networks for intracavity optical trapping
Agnese Callegari, Mathias Samuelsson, Antonio Ciarlo, Giuseppe Pesce, David Bronte Ciriza, Alessandro Magazzù, Onofrio M. Maragò, Antonio Sasso, and Giovanni Volpe
SPIE-OTOM, San Diego, CA, USA, 18 – 22 August 2024
Date: 19 August 2024
Time: 5:30 PM – 7:00 PM
Place: Conv. Ctr. Exhibit Hall A

Intracavity optical tweezers have been proven successful for trapping microscopic particles at very low average power intensity – much lower than the one in standard optical tweezers. This feature makes them particularly promising for the study of biological samples. The modelling of such systems, though, requires time-consuming numerical simulations that affect its usability and predictive power. With the help of machine learning, we can overcome the numerical bottleneck – the calculation of optical forces, torques, and losses – and reproduce, in simulation, the results in the literature and generalize to the case of counterpropagating-beams intracavity optical trapping.