
Yuxin is a master student in Software Engineering at Chalmers University of Technology.
During his time at the Soft Matter Lab, he will work on using deep learning and graph theory to analyze the human brain connectome.

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 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.

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.





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

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.

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.

Agnese Callegari, 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
Janus particles possess dual properties that makes them very versatile for soft and active matter applications. Modeling their interaction with light, including optical force and torque, presents challenges. We present here a model of spherical, metal-coated Janus particles in the geometric optics approximation. Via an extension of the Optical Tweezers Geometrical Optics (OTGO) toolbox, we calculate optical forces, torques, and absorption. Through numerical simulation, we demonstrate control over Janus particle dynamics in traveling-wave optical landscapes by adjusting speed and periodicity.

Mirja Granfors, Jesús Pineda, Blanca Zufiria Gerbolés, Jiawei Sun, Joana B. Pereira, Carlo Manzo, and Giovanni Volpe
Date: 19 August 2024
Time: 17:30-19:00 (PDT)
Graphs are used to model complex relationships in various domains, such as interacting particles or neural connections within a brain. Efficient analysis and classification of graphs pose significant challenges due to their inherent structural complexity and variability. Here, an approach is presented to address these challenges through the development of the graph autoencoder GAUDI. GAUDI effectively summarizes graph structures while preserving important topological details through multiple hierarchical pooling steps. This enables the extraction of physical parameters describing the graphs. We demonstrate the performance of GAUDI 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. This approach holds great promise for examining diverse systems, enhancing our comprehension of various forms of graph data.

Gan Wang, Marcel Rey, Antonio Ciarlo, Mohanmmad Mahdi Shanei, Kunli Xiong, Giuseppe Pesce, Mikael Käll and Giovanni Volpe
Date: 19 August 2024
Time: 16:25-16:40 (PDT)
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.