Presentation – Page 21 – Soft Matter Lab

Flash Talk by F. Schmidt at 729. WE Heraeus Seminar on Fluctuation Induced Forces, Online, 16 February 2022

Title slide of the presentation. (Image by F. Schmidt.)

Casimir-Lifshitz forces vs. Critical Casimir forces: Trapping and releasing of flat metallic particles
Falko Schmidt
729. WE-Heraeus Stiftung Seminar on Fluctuation-induced Forces
16 February 2022, 14:50 CET

Casimir forces in quantum electrodynamics emerge between microscopic metallic objects because of the confinement of the vacuum electromagnetic fluctuations occuring even at zero temperature. Their generalization at finite temperature and in material media are referred to as Casimir-Lifshitz forces. These forces are typically attractive, leading to the widespread problem of stiction between the metallic parts of micro- and nanodevices. Recently, repulsive Casimir forces have been experimentally realized but their use of specialized materials stills means that the system can not be controlled dynamically and thus limits further implementation to real-world applications. Here, we experimentally demonstrate that repulsive critical Casimir forces, which emerge in a critical binary liquid mixture upon approaching the critical temperature, can be used to prevent stiction due to Casimir-Lifshitz forces. We show that critical Casimir forces can be dynamically tuned via temperature, eventually overcoming Casimir-Lifshitz attraction. We study a microscopic gold flake above a flat gold-coated substrate immersed in a critical mixture. Far from the critical temperature, stiction occurs because of Casimir-Lifshitz forces. Upon approaching the critical temperature, however, we observe the emergence of repulsive critical Casimir forces that are sufficiently strong to counteract stiction. By removing one of the key limitations to their deployment, this experimental demonstration can accelerate the development of micro- and nanodevices for a broad range of applications.

Flash Talk by A. Callegari at 729. WE Heraeus Seminar on Fluctuation Induced Forces, Online, 14 February 2022

Potential energy landscape for a flake suspended on a patterned substrate. *(Image by A. Callegari.)*

Theoretical and numerical study of the interplay of Casimir-Lifshitz and critical Casimir force for a metallic flake suspended on a metal-coated substrate
Agnese Callegari
729. WE-Heraeus Stiftung Seminar on Fluctuation-induced Forces
14 February 2022, 14:50 CET

Casimir-Lifshitz forces arise between uncharged metallic objects because of the confinement of the electromagnetic fluctuations. Typically, these forces are attractive, and they are the main cause of stiction between microscopic metallic parts of micro- and nanodevices. Critical Casimir forces emerge between objects suspended in a critical binary liquid mixture upon approaching the critical temperature, can be made either attractive or repulsive by choosing the appropriate boundary conditions, and dynamically tuned via the temperature.
Experiments show that repulsive critical Casimir forces can be used to prevent stiction due to Casimir-Lifshitz forces. In a recent work, a microscopic metallic flake was suspended in a liquid solution above a metal-coated substrate [1]. By suspending the flake in a binary critical mixture and tuning the temperature we can control the flake’s hovering height above the substrate and, in the case of repulsive critical Casimir forces, prevent stiction.
Here, we present the model for the system of the metallic flake suspended above a metal-coated substrate in a binary critical mixture and show that repulsive critical Casimir forces can effectively counteract Casimir-Lifshitz forces and can be used to control dynamically the height of the flake above the surface. This provides a validation of the experimental results and a base to explore and design the behavior of similar systems in view of micro- and nanotechnological applications.

References
[1] F. Schmidt, A. Callegari, A. Daddi-Moussa-Ider, B. Munkhbat, R. Verre, T. Shegai, M. Käll, H. Löwen, A. Gambassi and G. Volpe, to be submitted (2022)

Invited Talk by G. Volpe at UFS Day 10.02.22

DeepTrack 2.0 Logo. *(Image from DeepTrack 2.0 Project)*

Deep learning for experimental soft matter
Giovanni Volpe
Invited Talk at UFS Day 10.02.22
Online
10 February 2022
14:00 CET

Presentation by H. Bachimanchi at Prof. Metzler’s group at the University of Potsdam, 4 February 2022

Tracking of the planktons. *(Image by H. Bachimanchi.)*

Characterising plankton behaviours using deep learning powered inline holography
Harshith Bachimanchi
Presentation at Prof. Ralf Metzler’s Theoretical Physics group at University of Potsdam (Online)
4 February 2022, 14:15 CET

Digital holographic microscopy is a powerful label-free imaging technique for studying biological specimens. The complex optical fields of microscopic objects can be stored in the form of interference patterns and can be reconstructed by using the principles of holography. Recently, we have developed a digital inline holographic microscope with a deep learning powered analysis to track planktons through generations, and continuously measure their three-dimensional position and dry mass. By bringing planktons of different trophic levels together, we were able to perform a quantitative assessment of trophic interactions between planktons such as feeding events, biomass transfer from cell to cell, etc. In this talk, I will be giving a short overview of our method and present some of our recent results.

Keynote Talk by G. Volpe at IUPAP Conference on Condensed Matter Physics and Optics, 20 January 2022

Deep learning for microscopy, optical trapping, and active matter
Giovanni Volpe
Keynote Talk at IUPAP conference on Condensed Matter Physics and Optics
Online
20 January 2022
15:00 PST

After a brief overview of artificial intelligence, machine learning and deep learning, I will present a series of recent works in which we have employed deep learning for applications in photonics and active matter. In particular, I will explain how we employed deep learning to enhance digital video microscopy, to estimate the properties of anomalous diffusion, to characterize microscopic force fields, to improve the calculation of optical forces, and to characterize nanoparticles. Finally, I will provide an outlook for the application of deep learning in photonics and active matter.

Presentation by G. V. P. Kumar, 24 November 2021

Thermoplasmonic Tweezers: Probing single-molecules and more
G. V. Pavan Kumar
IISER, Pune, India.
24 November 2021
Online

In this presentation, we will discuss two specific issues: How to perform single-molecule surface enhanced Raman scattering (SERS) in an optothermal trap? and how to design optothermal fields to trap and interrogate molecules and colloids in a fluid?

In recent years, performing SERS in optical traps has emerged as an important development in nano- and bio-photonics. To this end, tweezer techniques based on surface-plasmons facilitate deeper optical potentials at sub-wavelength scales, and simultaneously provide enhanced electric and optothermal fields. In this
presentation, we will discuss various strategies developed in my laboratory to perform single-molecule SERS in optical and plasmonic tweezer platforms. Specifically, we will highlight some thermoplasmonic effects and directionality aspects of the tweezer platforms in metallic thin film and some plasmonic nano-architectures.

Short bio:

G.V. Pavan Kumar is an associate professor of physics at the Indian Institute of Science Education and Research (IISER), Pune, India.
He obtained his PhD from JNCASR, Bangalore. Subsequently he was a postdoctoral fellow at ICFO-Barcelona and Purdue University, before joining IISER in 2010.
His current research interests are optical, optothermal and nanophotonic forces and their utility in probing single molecules and soft-matter systems at micro and nanoscale.
To this end, his lab has been interfacing optical tweezer platforms with a variety of optical spectroscopy and microscopy tools.
He blogs on topics related to science: https://backscattering.wordpress.com/

Invited Presentation by G. Volpe at FiO LS, 4 November 2021

DeepTrack 2.0 Logo. *(Image from DeepTrack 2.1 Project)*

DeepTrack 2.1: A Framework for Deep Learning for Microscopy
Giovanni Volpe
Invited Presentation at Frontiers in Optics + Laser Science
Online
4 November 2021
4:00 PM

We present DeepTrack 2.0, a software to design, train, and validate deep-learning solutions for digital microscopy. We demonstrate it for applications from particle localization, tracking, and characterization, to cell counting and classification, to virtual staining.

Link: FTh6A.3

Seminar by D. Midtvedt at Freie Universität Berlin, 29 October 2021

Quantitative digital microscopy enhanced by deep learning
Daniel Midtvedt
(online at) Freie Universität Berlin, Germany
29 October 2021

Video microscopy has a long history of providing insight 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 recently introduced a software, DeepTrack 2.0, to design, train, and validate deep-learning solutions for digital microscopy.
In this talk, I will show how this software can be used in a broad range of applications, from particle localization, tracking, and characterization, to cell counting and classification. Thanks to its user-friendly graphical interface, DeepTrack 2.0 can be easily customized for user-specific applications, and thanks to its open-source, object-oriented programing, it can be easily expanded to add features and functionalities, potentially introducing deep-learning-enhanced video microscopy to a far wider audience.

Invited Talk by G. Volpe at Microscopies and Spectroscopies: Accessing the Nanoscale, 28 October 2021

Quantitative Digital Microscopy with Deep Learning
Giovanni Volpe
Invited Talk at the XXXVI Trobades Cientifíques de la Mediterránia – Josep Miquel Vidal
Microscopies and Spectroscopies: Accessing the Nanoscale
Menorca, Spain
28 October 2021
11:40 AM

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 introduce a software, DeepTrack 2.0, to design, train and validate deep- learning solutions for digital microscopy. We use it to exemplify how deep learning can be employed for a broad range of applications, from particle localization, tracking and characterization to cell counting and classification. Thanks to its user- friendly graphical interface, DeepTrack 2.0 can be easily customized for user-specific applications, and, thanks to its open-source object-oriented programming, it can be easily expanded to add features and functionalities, potentially introducing deep-learning-enhanced video microscopy to a far wider audience.