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Invited Talk by G. Volpe at Gothenburg Lise Meitner Award 2024 Symposium, 27 September 2024

(Image created by G. Volpe with the assistance of DALL·E 2)
What is a physicist to do in the age of AI?
Giovanni Volpe
Gothenburg Lise Meitner Award 2024 Symposium
Date: 27 September 2024
Time: 15:00-15:30
Place: PJ Salen

In recent years, the rapid growth of artificial intelligence, particularly deep learning, has transformed fields from natural sciences to technology. While deep learning is often viewed as a glorified form of curve fitting, its advancement to multi-layered, deep neural networks has resulted in unprecedented performance improvements, often surprising experts. As AI models grow larger and more complex, many wonder whether AI will eventually take over the world and what role remains for physicists and, more broadly, humans.

A critical, yet underappreciated fact is that these AI systems rely heavily on vast amounts of training data, most of which are generated and annotated by humans. This dependency raises an intriguing issue: what happens when human-generated data is no longer available, or when AI begins to train on AI-generated data? The phenomenon of AI poisoning, where the quality of AI outputs declines due to self-referencing, demonstrates the limitations of current AI models. For example, in image recognition tasks, such as those involving the MNIST dataset, AI tends to gravitate towards ‘safe’ or average outputs, diminishing originality and accuracy.

In this context, the unique role of humans becomes clear. Physicists, with their capacity for originality, deep understanding of physical phenomena, and the ability to exploit fundamental symmetries in nature, bring invaluable perspectives to the development of AI. By incorporating physics-informed training architectures and embracing the human drive for meaning and discovery, we can guide the future of AI in truly innovative directions. The message is clear: physicists must remain original, pursue their passions, and continue searching for the hidden laws that govern the world and society.

Seminar by G. Volpe at ESPCI/Sorbonne, Paris, 26 September 2024

(Image by A. Argun)
Deep Learning for Microscopy
Giovanni Volpe
Date: 26 September 2024
Place: ESPCI/Sorbonne, Paris, France

Video microscopy has a long history of providing insights and breakthroughs for a broad range of disciplines, from physics to biology. Image analysis to extract quantitative information from video microscopy data has traditionally relied on algorithmic approaches, which are often difficult to implement, time consuming, and computationally expensive. Recently, alternative data-driven approaches using deep learning have greatly improved quantitative digital microscopy, potentially offering automatized, accurate, and fast image analysis. However, the combination of deep learning and video microscopy remains underutilized primarily due to the steep learning curve involved in developing custom deep-learning solutions. To overcome this issue, we have introduced a software, DeepTrack 2.1, to design, train and validate deep-learning solutions for digital microscopy.

Janko Vrcek joins the Soft Matter Lab

(Photo by A. Ciarlo.)
Janko Vrcek joined the Soft Matter Lab on 9 September 2024.

Janko is a master student in Physics at Chalmers University of Technology.

During his time at the Soft Matter Lab, he will work on Monte Carlo simulations of protein condensates.

Biomolecular condensation is a phenomenon where under certain conditions biological polymers like proteins or RNA segregate out of a solution into a condensate. Many cellular organelles such as nucleolus are considered to be biomolecular condensates. Disruption in the condensation can have serious effects on human health, causing illnesses such as Alzheimer’s disease and cancer. My research investigates conditions for formation of condensates from previously developed theoretical models such as Flory-Huggins theory. We do this by utilizing Monte Carlo simulations of polymer mixtures and comparing results with theoretical models, as well as experimental results.

Jesús Domínguez defended his PhD thesis on 6 September 2024. Congrats!

The three platforms developed to observe and characterise bacterial collective behaviour in different conditions. (Image by J. Dominguez.)
Jesús Manuel Antúnez Domínguez defended his PhD thesis on 6 September 2024. Congrats!
The defense took place in PJ, Institutionen för fysik, Origovägen 6b, Göteborg.

Title: Microscopic approaches for bacterial collective behaviour studies.

Abstract: Bacteria significantly impact our lives, from their beneficial role as probiotics to their involvement in infection environments. Their widespread presence is largely due to their ability to adapt to diverse conditions through collective behavior, which enables the development of complex strategies from the contributions of simple individual entities. However the understanding of these systems is limited by the reach of current study techniques. This work presents the development of three platforms designed to perform microscopic studies and characterise bacterial collective behaviors in situ, profiting the advantages of microfluidics over traditional culture techniques.

The first platform integrates bacterial culture on solid agar directly on the microscope stage, allowing for extended observation periods of up to a week. The agar is housed within an elastomer structure sealed with glass, ensuring environmental isolation while maintaining optical accessibility. This platform was used to document the complex social strategies of Myxococcus xanthus, including motility mechanisms, predation organisation, and fruiting body formation.

The second platform is an automated testing system for quantifying bacterial viability under various conditions. Using microfluidic technology, this platform streamlines and parallelise the process. It adapts the Ames genotoxicity test to a miniaturized version, using microscopy imaging as the readout. This approach reduces experimental turnaround time and minimizes the handling of hazardous substances.

The third platform is a microfluidic system designed for the microscopy observation of bacteria within stabilised droplets. This approach enhances throughput and allows for the production of various types of droplets on the same chip. Bacillus subtilis bacteria were encapsulated in these droplets, and their entire biofilm formation life cycle was observed in detail. Parallel to this, custom software was developed specifically for analysing microscopy images to automatically quantify biofilm formation.

Each of these platforms provides a unique perspectives in the study of bacterial collective behavior to offer a comprehensive toolkit for researchers. complementing one another. This work will equip researchers with the tools to address the mysteries of bacterial collective behavior and opens up new possibilities for application and investigation.

Thesis: https://hdl.handle.net/2077/81543

Supervisor: Caroline Beck Adiels
Examiner: Raimund Feifel
Opponent: Jana Jass
Committee: Edith Hammer, Per Augustsson, Johan Bengtsson-Palme
Alternate board member: Mattias Marklund

Jesús presenting in PJ. (Photo by A. Ciarlo.)

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.