Workshop Program

Abstract: One of the most important control parameters in cellular systems is pH. Enzymes encapsulated in structures such as liposomes display bioinspired behaviour driven by pH changes, but the mechanisms involved are complex. Here, we compare pH-driven behaviour of enzyme reactions compartmentalized in these nano to micro-reactors using a combination of simulations and experiments. We determine how pH is governed by a combination of catalytic rate, and chemical and electrical gradients across membranes. We discuss how the coupling of mass transport and chemical feedback results in pH oscillations and collective dynamics driven by chemical communication between compartments. These studies aid in understanding how life-like properties in synthetic cellular systems might be used in materials and sensing applications.

Abstract: Many biological systems rely on the ability to self-assemble different target structures using the same set of components. Equilibrium self-assembly suffers from a limited capacity in such cases due to an increasing number of decoy states that grows rapidly with the number of targets encoded. Moreover, improving the kinetic stability of a target at equilibrium carries the price of introducing kinetic traps, leading to slower assembly. Using a toy physical model of interacting particles, we demonstrate that local driving can improve both the assembly time and kinetic stability of multitarget self-assembly. Our findings also extend to 3D simulations of patchy particle systems in biological-mimicking environments. We further show that a segmented description of the system dynamics, by the Bayesian estimator of abrupt changes (BEAST) algorithm, can be used to provide predictions of the first assembly times. Additionally, by leveraging the stochastic landscape method, a framework using energy trend-based segmentation to predict self-assembly behavior, we can dynamically analyze the system’s state and energy trends to guide control actions. Our results illustrate the role that nonequilibrium driving plays in overcoming tradeoffs inherent to equilibrium assemblies and establish a general quantitative framework for nonequilibrium systems.

References:

1. Nonequilibrium Self-Assembly Control by the Stochastic Landscape Method
Michael Faran and Gili Bisker
Journal of Chemical Information and Modeling, 65 (8), (2025)

2. Dissipative self-assembly of patchy particles under nonequilibrium drive: a computational study
Shubhadeep Nag and Gili Bisker
Journal of Chemical Theory and Computation (2024)

3. Driven Self-Assembly of Patchy Particles Overcoming Equilibrium Limitations
Shubhadeep Nag and Gili Bisker
Journal of Chemical Theory and Computation (2024)

4.  A Stochastic Landscape Approach for Protein Folding State Classification
Michael Faran, Dhiman Ray, Shubhadeep Nag, Umberto Raucci, Michele Parrinello, and Gili Bisker
Journal of Chemical Theory and Computation, 20, 13, (2024)

5.  Nonequilibrium Self-Assembly Time Forecasting by the Stochastic Landscape Method
Michael Faran and Gili Bisker
The Journal of Physical Chemistry B (2023)

6.  Nonequilibrium self-assembly of multiple stored targets in a dimer-based system
Adi Ben-Ari, Liron Ben-Ari, and Gili Bisker
The Journal of Chemical Physics, 155(23), 234113 (2021)

7.  Dissipate your way to self-assembly
Gili Bisker
Nature Physics, 16(7), 707-708, (2020)

8.  Nonequilibrium associative retrieval of multiple stored self-assembly targets
Gili Bisker and Jeremy L. England
PNAS, 115 (45), E10531-E10538 (2018)

Abstract: Swimming is used by a myriad of different organisms spanning micro- to macroscopic sizes. The physics behind swimming at the viscosity-dominated microscale and inertia-dominated macroscale is well studied. However, in between lies a complicated mesoscale with swimmers affected by non-linear and time-dependent fluid mechanics. The intricate motility strategies as well as the complex and periodically changing shapes of these meso-organisms add extra challenges for accurately modelling their dynamics. In this seminar, I will present two recent projects where we have studied the dynamics and crowding of living mesoswimmers. We have further developed the micropipette force sensor to directly probe the rapid swimming dynamics of the meso-organism Artemia sp [1]. By confining several swimmers in a 3D droplet, we investigate the effect of crowding on the swimming [2]. In both projects, we showcase simplistic approaches to capture the core physics of complex living systems by combining careful measurements with scaling law models. Our results provide guidance for future biomimicking technological applications in mesoscale actuators, robots, and sensors as well as swimmer-driven meso-machines.

[1] R. A. Lara‡, N. Sharadhi‡, A. A. L. Huttunen, L. Ansas, E. J. G. Rislakki, G. M. Bessa and M. Backholm, Forces and symmetry breaking of a living meso-swimmer, arXiv.2503.21396 (2025).

[2] L. Malik, N. Sharadhi, M. Lamminmäki, R. A. Lara, V. Jokinen, and M. Backholm, Living droplets with mesoscale swimmers, arXiv:2509.20005 (2025).

Abstract: Controlling microscale matter using light has traditionally relied on optical trapping, yet this approach struggles with absorbing particles due to thermal instabilities. In this talk, I present an alternative strategy that harnesses pulsed laser-induced thermophoresis as a precise means of manipulation. By focusing nanosecond pulses near the gold-capped Janus particles, we generate transient temperature gradients that drive directional motion without sustained heating or fluid convection. I will walk through our modeling of the heat source, the fabrication of asymmetric particles, and the experimental system we developed for tracking particle behavior under a range of pulse energies. Quantitative analysis using mean square displacement (MSD) reveals a clear dependence on laser parameters, offering tunable control over motion. This approach opens new avenues for non-invasive, thermally mediated manipulation in soft matter systems.

Abstract: Is it possible to define a correlation coefficient that is as simple and interpretable as classical measures like Pearson’s or Spearman’s, yet capable of capturing general, potentially nonlinear dependencies? In this talk, I will discuss some recent approaches that achieve exactly this: a model-free coefficient that equals zero if and only if the variables are independent and equals one if and only if one variable is a measurable function of the other. Unlike existing methods, it retains a simple and elegant asymptotic theory under independence and requires no assumptions on the underlying distributions. We demonstrate its effectiveness in applications such as variable selection.

Abstract: A core characteristic of today’s world is the growth of connected human-driven devices and intelligent machines that act without human intervention. In a dynamic environment, and while being uncertain about the incentives, preferences, and capabilities of others, these heterogeneous systems engage in real-time cooperative- or competitive interactions to fulfill their individual- or team goals. For such a distributed system of systems, self-organization is a crucial aspect, which emerges as the outcome of successive decision-making strategies of individuals. In this talk, I consider different features of self-organization, namely, self-configuration, self-optimization, and self-healing. I then provide decision-making strategies merging game theory and online learning to guarantee those features in cooperative and competitive settings. 

Abstract: Stochastic thermodynamics offers powerful tools to quantify entropy production, dissipation, and energy efficiency via measurements of time-reversal symmetry breaking (TRSB) in small-scale, fluctuating processes. These connections, however, rely on the assumption that all dissipative degrees of freedom are accessible and resolved in the model. In the presence of hidden degrees of freedom, the relation between TRSB and dissipation becomes elusive, creating a conceptual gap for complex many-body systems. Despite this challenge, growing research efforts aim to quantify dissipation and TRSB in active matter. I will review recent insights, open questions, and points of discussion. As an example, I will show how TRSB can serve as an order parameter for detecting dynamical phase transitions in systems with dissipative pattern formation.

Suchanek, Kroy, & Loos, PRL (2023).

Martynec, Klapp, & Loos, NJP (2021).

Loos, Klapp, & Martynec, PRL (2023).

Abstract: Synthetic micro- and nanomotors have emerged as a vibrant area of research in multidisciplinary nanotechnology. These artificial active materials derive their energy from a variety of physical processes and chemical reactions. Catalytic, peroxide-decomposing systems are by far the most common but allow only a limited degree of control. Light is widely available, easily controllable and biocompatible, making it an ideal tool to drive microscopic particles and add a level of control.[1] Environmental pollution is a major global challenge, and emerging pollutants such as microplastics have gained worldwide attention. As there is no large-scale solution for removing microplastics once they are in a water body, several new technologies are being discussed to help solve this problem. [2]  These include self-propelled photocatalytic micromotors, which have been shown to effectively collect passive colloids in raft-like structures, a strategy that works well at the microscopic scale.[3] To take this approach further towards application, we are developing not only scalable micromotors that combine the ability to collect microplastics with the photocatalytic degradation of polymeric materials, but we also investigate the microplastics themselves.[4]

[1] L Wang, MN Popescu, F Stavale, A Ali, T Gemming, J Simmchen, Cu@TiO2 Janus microswimmers with a versatile motion mechanism, Soft Matter, 14, 6969-6973 (2018).

[2] L Wang, A Kaeppler A, D Fischer, J Simmchen, Photocatalytic TiO2 micromotors for removal of microplastics and suspended matter, ACS AMI, 11, 3632937-32944 (2019).

[3] Chattopadhyay, P., Ariza-Tarazona, M. C., Cedillo-González, E. I., Siligardi, C., & Simmchen, J. Combining photocatalytic collection and degradation of microplastics using self-asymmetric Pac-Man TiO 2. Nanoscale, 15(36), 14774-14781 (2023).

[4] Maslen, C., Chattopadhyay, P., Kühne, M. T., McConnell, G., & Simmchen, J. Cryogenic milling of consumer plastics for high‐throughput characterization of polydisperse, amorphous microplastics. Journal of Applied Polymer Science, e57651 (2025).

Abstract: Quantifying how the accessible phase space expands under nonequilibrium conditions remains an open challenge, despite its central role in self-organization and pattern formation. We address this question experimentally using a driven colloidal system of non-interacting particles, which provides a minimal platform for isolating the physical origins of emergent order. The particles are confined in quasi-two dimensions and subjected to external forces. Despite the absence of interparticle  interactions or templating, the system explores a wide range of configurations, including Bravais lattices, Moiré superstructures, and coexisting states that evolve through dynamic transitions [1]. Moreover, these structures display a striking degree of universality across scales [2] and give rise to hyperuniform states upon removal of driving [3]. The formation and evolution of these states is governed by nonlinear coupling between driving, flow, and confinement, where hydrodynamic interactions mediate the collective response and fluctuations influence both topology and local correlations. We combine experimental observations with data-driven analysis and simulations to chart the emergence, stability and transitions of steady states across parameter space. Our results illuminate how driving, stochasticity, and geometry regulate complexity and collective behaviour in a minimal non-interacting system.

[1] S Ilday, G Makey, G B Akguc, Ö Yavuz, O Tokel, I Pavlov, O Gulseren, F Ö Ilday, Rich complex behaviour of self-assembled nanoparticles far from equilibrium, Nat. Commun., 8, 14942 (2017).

[2] G Makey, S Galioglu, R Ghaffari, E D Engin, G Yıldırım, Ö Yavuz, O Bektaş, Ü S Nizam, Ö Akbulut, Ö Şahin, K Güngör, D Dede, H V Demir, F Ö Ilday, S Ilday, Universality of dissipative self-assembly from quantum dots to human cells, Nat. Phys., 16, 795–801 (2020).

[3] Ü S Nizam, G Makey, M Barbier, S S Kahraman, E Demir, E E Shafigh, S Galioglu, D Vahabli, S Hüsnügil, M H Güneş, E Yelesti, S Ilday, Dynamic evolution of hyperuniformity in a driven dissipative colloidal system, J. Phys.: Condens. Matter, 33, 304002 (2021).