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Jannis Fischer

Publications and source records attributed to Jannis Fischer.

3 recordsLinked to original sources

Self-propelled particles driven by light

Recent advances in the field of active soft matter promise a lot. Both, experimental advances and theoretical understanding point towards new material classes in reach, for example self-healing materials that might switch their properties from elastic to solid easily or switch their macroscopic shapes. All these materials require an active force to propel parts of themselves on the micrometer scale. While chemical fuels are often used to generate these active forces, applying energy in a simple and continuous way remains unsolved. Here we explore using light as such an energy source. Overall, generating active driven, self-propelled particles is hence not only of great interest but also a general challenge. Moreover, controlling such particles even within living tissue would open new worlds, for example to enable specific drug delivery or the design of micro-robots. One recently proposed method to establish light driven self propelled particles is to create specific shaped and transparent objects, that move when illuminated with homogeneous light. In these particles, the refraction of the light leads to a momentum transfer, which then drives the active movement. Here, we show both in simulation and experiments that the production of such particles is possible and demonstrate the feasibility of this propulsion effect, while investigating different shapes. Our experiments show that breaking the shape-symmetry of the particles creates a refraction-based propulsion under homogeneous illumination. Subsequent simulations reveal that total reflection leads to the largest momentum transfer among all different geometries considered. Overall, our study introduces the proof-of-principle for refraction-propelled particles, which has the potential to benefit many fields of study including cellular behaviour, collective dynamics and the understanding of disease mechanisms.

physics.bio-ph

Active Intracellular Mechanics: A Key to Cellular Function and Organization

While mechanobiology has demonstrated that precise control over mechanical properties at the whole-cell level is crucial for many biological functions, comparatively little attention has been paid to the intracellular mechanical properties. Experimental tools have only recently become available to adequately measure the viscoelasticity and activity of the cytosol, revealing, revealing that the active, non-equilibrium nature of the intracellular environment must be carefully considered. To explore the interplay between active forces and viscoelastic properties, it is helpful to consider our current understanding of intracellular active mechanics. In this review, we aim not only to provide an intuitive and quantitative introduction to the relevant physical concepts, but also to offer an overview of the proteins that establish intracellular active mechanics, highlighting their spatial and temporal variation with a particular focus on the role of activity. Although we are only beginning to uncover the importance of intracellular active mechanics for cellular mechanisms, it is increasingly clear that these properties must be precisely regulated to ensure proper cellular function.

q-bio.SC

Real-Time Computation of Parameter Fitting and Image Reconstruction Using Graphical Processing Units

In recent years graphical processing units (GPUs) have become a powerful tool in scientific computing. Their potential to speed up highly parallel applications brings the power of high performance computing to a wider range of users. However, programming these devices and integrating their use in existing applications is still a challenging task. In this paper we examined the potential of GPUs for two different applications. The first application, created at Paul Scherrer Institut (PSI), is used for parameter fitting during data analysis of muSR (muon spin rotation, relaxation and resonance) experiments. The second application, developed at ETH, is used for PET (Positron Emission Tomography) image reconstruction and analysis. Applications currently in use were examined to identify parts of the algorithms in need of optimization. Efficient GPU kernels were created in order to allow applications to use a GPU, to speed up the previously identified parts. Benchmarking tests were performed in order to measure the achieved speedup During this work, we focused on single GPU systems to show that real time data analysis of these problems can be achieved without the need for large computing clusters. The results show that the currently used application for parameter fitting, which uses OpenMP to parallelize calculations over multiple CPU cores, can be accelerated around 40 times through the use of a GPU. The speedup may vary depending on the size and complexity of the problem. For PET image analysis, the obtained speedups of the GPU version was more than x40 larger compared to a single core CPU implementation. The achieved results show that it is possible to improve the execution time by orders of magnitude.

cs.DC