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2018


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Direct observations of sub-100 nm spin wave propagation in magnonic wave-guides

Träger, N., Gruszecki, P., Lisiecki, F., Förster, J., Weigand, M., Kuswik, P., Dubowik, J., Schütz, G., Krawczyk, M., Gräfe, J.

In 2018 IEEE International Magnetics Conference (INTERMAG 2018), IEEE, Singapore, 2018 (inproceedings)

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DOI [BibTex]

2018


DOI [BibTex]


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Assessment methodology of promising porous materials for near ambient temperature hydrogen storage applications

Minuto, F. D., Balderas-Xicohténcatl, R., Policicchio, A., Hirscher, M., Agostino, R. G.

{International Journal of Hydrogen Energy}, 43(31):14550-14556, Elsevier, Amsterdam, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Emission and propagation of multi-dimensional spin waves in anisotropic spin textures

Sluka, V., Schneider, T., Gallardo, R. A., Kakay, A., Weigand, M., Warnatz, T., Mattheis, R., Roldan-Molina, A., Landeros, P., Tiberkevich, V., Slavin, A., Schütz, G., Erbe, A., Deac, A., Lindner, J., Raabe, J., Fassbender, J., Wintz, S.

2018 (misc)

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link (url) [BibTex]

link (url) [BibTex]


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3d nanofabrication of high-resolution multilayer Fresnel zone plates

Sanli, U. T., Jiao, C., Baluktsian, M., Grévent, C., Hahn, K., Wang, Y., Srot, V., Richter, G., Bykova, I., Weigand, M., Schütz, G., Keskinbora, K.

{Advanced Science}, 5(9), Wiley-VCH, Weinheim, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Photocatalytic CO2 reduction by Cr-substituted Ba2(In2-xCrx)O5\mbox⋅(H2O)δ(0.04 ≤x ≤0.60)

Yoon, S., Gaul, M., Sharma, S., Son, K., Hagemann, H., Ziegenbalg, D., Schwingenschlogl, U., Widenmeyer, M., Weidenkaff, A.

{Solid State Sciences}, 78, pages: 22-29, Elsevier Masson SAS, Paris, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Correction of axial position uncertainty and systematic detector errors in ptychographic diffraction imaging

Loetgering, L., Rose, M., Keskinbora, K., Baluktsian, M., Dogan, G., Sanli, U., Bykova, I., Weigand, M., Schütz, G., Wilhein, T.

{Optical Engineering}, 57(8), The Society, Redondo Beach, Calif., 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Thermodynamics, kinetics and selectivity of H2 and D2 on zeolite 5A below 77K

Xiong, R., Balderas-Xicohténcatl, R., Zhang, L., Li, P., Yao, Y., Sang, G., Chen, C., Tang, T., Luo, D., Hirscher, M.

{Microporous and Mesoporous Materials}, 264, pages: 22-27, Elsevier, Amsterdam, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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The role of surface oxides on hydrogen sorption kinetics in titanium thin films

Hadjixenophontos, E., Michalek, L., Roussel, M., Hirscher, M., Schmitz, G.

{Applied Surface Science}, 441, pages: 324-330, Elsevier B.V., Amsterdam, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Volumetric hydrogen storage capacity in metal-organic frameworks

Balderas-Xicohténcatl, R., Schlichtenmayer, M., Hirscher, M.

{Energy Technology}, 6(3):578-582, Wiley-VCH, Weinheim, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Ferromagnetism in nitrogen and fluorine substituted BaTiO3

Yoon, S., Son, K., Ebbinghaus, S. G., Widenmeyer, M., Weidenkaff, A.

{Journal of Alloys and Compounds}, 749, pages: 628-633, Elsevier B.V., Lausanne, Switzerland, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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New concepts for 3d optics in x-ray microscopy

Sanli, U., Ceylan, H., Jiao, C., Baluktsian, M., Grevent, C., Hahn, K., Wang, Y., Srot, V., Richter, G., Bykova, I., Weigand, M., Sitti, M., Schütz, G., Keskinbora, K.

{Microscopy and Microanalysis}, 24(Suppl 2):288-289, Cambridge University Press, New York, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Thermal skyrmion diffusion applied in probabilistic computing

Zázvorka, J., Jakobs, F., Heinze, D., Keil, N., Kromin, S., Jaiswal, S., Litzius, K., Jakob, G., Virnau, P., Pinna, D., Everschor-Sitte, K., Donges, A., Nowak, U., Kläui, M.

2018 (misc)

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link (url) [BibTex]

link (url) [BibTex]


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High volumetric hydrogen storage capacity using interpenetrated metal-organic frameworks

Balderas-Xicohténcatl, R., Schmieder, P., Denysenko, D., Volkmer, D., Hirscher, M.

{Energy Technology}, 6(3):510-512, Wiley-VCH, Weinheim, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Spin-wave interference in magnetic vortex stacks

Behncke, C., Adolff, C. F., Lenzing, N., Hänze, M., Schulte, B., Weigand, M., Schütz, G., Meier, G.

{Communications Physics}, 1, Nature Publishing Group, London, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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High-throughput synthesis of modified Fresnel zone plate arrays via ion beam lithography

Keskinbora, K., Sanli, U. T., Baluktsian, M., Grévent, C., Weigand, M., Schütz, G.

{Beilstein Journal of Nanotechnology}, 9, pages: 2049-2056, Beilstein-Institut, Frankfurt am Main, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Deterministic creation and deletion of a single magnetic skyrmion observed by direct time-resolved X-ray microscopy

Woo, S., Song, K. M., Zhang, X., Ezawa, M., Zhou, Y., Liu, X., Weigand, M., Finizio, S., Raabe, J., Park, M.-C., Lee, K.-Y., Choi, J. W., Min, B.-C., Koo, H. C., Chang, J.

{Nature Electronics}, 1(5):288-296, Springer Nature, London, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Magnetic skyrmion as a nonlinear resistive element: A potential building block for reservoir computing

Prychynenko, D., Sitte, M., Litzius, K., Krüger, B., Bourianoff, G., Kläui, M., Sinova, J., Everschor-Sitte, K.

{Physical Review Applied}, 9(1), American Physical Society, College Park, Md. [u.a.], 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Tunable geometrical frustration in magnoic vortex crystals

Behncke, C., Adolff, C. F., Wintz, S., Hänze, M., Schulte, B., Weigand, M., Finizio, S., Raabe, J., Meier, G.

{Scientific Reports}, 8, Nature Publishing Group, London, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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High-Resolution X-ray Ptychography for Magnetic Imaging

Bykova, I.

Universität Stuttgart, Stuttgart, 2018 (phdthesis)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Interpreting FORC diagrams beyond the Preisach model: an experimental permalloy micro array investigation

Gross, F., Ilse, S., Schütz, G., Gräfe, J., Goering, E.

In 2018 IEEE International Magnetics Conference (INTERMAG 2018), IEEE, Singapore, 2018 (inproceedings)

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DOI [BibTex]

DOI [BibTex]

2017


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Active colloidal propulsion over a crystalline surface

Choudhury, U., Straube, A., Fischer, P., Gibbs, J., Höfling, F.

New Journal of Physics, 19, pages: 125010, December 2017 (article)

Abstract
We study both experimentally and theoretically the dynamics of chemically self-propelled Janus colloids moving atop a two-dimensional crystalline surface. The surface is a hexagonally close-packed monolayer of colloidal particles of the same size as the mobile one. The dynamics of the self-propelled colloid reflects the competition between hindered diffusion due to the periodic surface and enhanced diffusion due to active motion. Which contribution dominates depends on the propulsion strength, which can be systematically tuned by changing the concentration of a chemical fuel. The mean-square displacements obtained from the experiment exhibit enhanced diffusion at long lag times. Our experimental data are consistent with a Langevin model for the effectively two-dimensional translational motion of an active Brownian particle in a periodic potential, combining the confining effects of gravity and the crystalline surface with the free rotational diffusion of the colloid. Approximate analytical predictions are made for the mean-square displacement describing the crossover from free Brownian motion at short times to active diffusion at long times. The results are in semi-quantitative agreement with numerical results of a refined Langevin model that treats translational and rotational degrees of freedom on the same footing.

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link (url) DOI [BibTex]

2017


link (url) DOI [BibTex]


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On the Design of LQR Kernels for Efficient Controller Learning

Marco, A., Hennig, P., Schaal, S., Trimpe, S.

Proceedings of the 56th IEEE Annual Conference on Decision and Control (CDC), pages: 5193-5200, IEEE, IEEE Conference on Decision and Control, December 2017 (conference)

Abstract
Finding optimal feedback controllers for nonlinear dynamic systems from data is hard. Recently, Bayesian optimization (BO) has been proposed as a powerful framework for direct controller tuning from experimental trials. For selecting the next query point and finding the global optimum, BO relies on a probabilistic description of the latent objective function, typically a Gaussian process (GP). As is shown herein, GPs with a common kernel choice can, however, lead to poor learning outcomes on standard quadratic control problems. For a first-order system, we construct two kernels that specifically leverage the structure of the well-known Linear Quadratic Regulator (LQR), yet retain the flexibility of Bayesian nonparametric learning. Simulations of uncertain linear and nonlinear systems demonstrate that the LQR kernels yield superior learning performance.

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arXiv PDF On the Design of LQR Kernels for Efficient Controller Learning - CDC presentation DOI Project Page [BibTex]

arXiv PDF On the Design of LQR Kernels for Efficient Controller Learning - CDC presentation DOI Project Page [BibTex]


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Wireless Acoustic-Surface Actuators for Miniaturized Endoscopes

Qiu, T., Adams, F., Palagi, S., Melde, K., Mark, A. G., Wetterauer, U., Miernik, A., Fischer, P.

ACS Applied Materials & Interfaces, 9(49):42536 - 42543, November 2017 (article)

Abstract
Endoscopy enables minimally invasive procedures in many medical fields, such as urology. However, current endoscopes are normally cable-driven, which limits their dexterity and makes them hard to miniaturize. Indeed current urological endoscopes have an outer diameter of about 3 mm and still only possess one bending degree of freedom. In this paper, we report a novel wireless actuation mechanism that increases the dexterity and that permits the miniaturization of a urological endoscope. The novel actuator consists of thin active surfaces that can be readily attached to any device and are wirelessly powered by ultrasound. The surfaces consist of two-dimensional arrays of micro-bubbles, which oscillate under ultrasound excitation and thereby generate an acoustic streaming force. Bubbles of different sizes are addressed by their unique resonance frequency, thus multiple degrees of freedom can readily be incorporated. Two active miniaturized devices (with a side length of around 1 mm) are demonstrated: a miniaturized mechanical arm that realizes two degrees of freedom, and a flexible endoscope prototype equipped with a camera at the tip. With the flexible endoscope, an active endoscopic examination is successfully performed in a rabbit bladder. This results show the potential medical applicability of surface actuators wirelessly powered by ultrasound penetrating through biological tissues.

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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Optimizing Long-term Predictions for Model-based Policy Search

Doerr, A., Daniel, C., Nguyen-Tuong, D., Marco, A., Schaal, S., Toussaint, M., Trimpe, S.

Proceedings of 1st Annual Conference on Robot Learning (CoRL), 78, pages: 227-238, (Editors: Sergey Levine and Vincent Vanhoucke and Ken Goldberg), 1st Annual Conference on Robot Learning, November 2017 (conference)

Abstract
We propose a novel long-term optimization criterion to improve the robustness of model-based reinforcement learning in real-world scenarios. Learning a dynamics model to derive a solution promises much greater data-efficiency and reusability compared to model-free alternatives. In practice, however, modelbased RL suffers from various imperfections such as noisy input and output data, delays and unmeasured (latent) states. To achieve higher resilience against such effects, we propose to optimize a generative long-term prediction model directly with respect to the likelihood of observed trajectories as opposed to the common approach of optimizing a dynamics model for one-step-ahead predictions. We evaluate the proposed method on several artificial and real-world benchmark problems and compare it to PILCO, a model-based RL framework, in experiments on a manipulation robot. The results show that the proposed method is competitive compared to state-of-the-art model learning methods. In contrast to these more involved models, our model can directly be employed for policy search and outperforms a baseline method in the robot experiment.

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PDF Project Page [BibTex]

PDF Project Page [BibTex]


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Probabilistic Line Searches for Stochastic Optimization

Mahsereci, M., Hennig, P.

Journal of Machine Learning Research, 18(119):1-59, November 2017 (article)

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link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Active Acoustic Surfaces Enable the Propulsion of a Wireless Robot

Qiu, T., Palagi, S., Mark, A. G., Melde, K., Adams, F., Fischer, P.

Advanced Materials Interfaces, 4(21):1700933, September 2017 (article)

Abstract
A major challenge that prevents the miniaturization of mechanically actuated systems is the lack of suitable methods that permit the efficient transfer of power to small scales. Acoustic energy holds great potential, as it is wireless, penetrates deep into biological tissues, and the mechanical vibrations can be directly converted into directional forces. Recently, active acoustic surfaces are developed that consist of 2D arrays of microcavities holding microbubbles that can be excited with an external acoustic field. At resonance, the surfaces give rise to acoustic streaming and thus provide a highly directional propulsive force. Here, this study advances these wireless surface actuators by studying their force output as the size of the bubble-array is increased. In particular, a general method is reported to dramatically improve the propulsive force, demonstrating that the surface actuators are actually able to propel centimeter-scale devices. To prove the flexibility of the functional surfaces as wireless ready-to-attach actuator, a mobile mini-robot capable of propulsion in water along multiple directions is presented. This work paves the way toward effectively exploiting acoustic surfaces as a novel wireless actuation scheme at small scales.

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link (url) DOI Project Page [BibTex]


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Corrosion-Protected Hybrid Nanoparticles

Jeong, H. H., Alarcon-Correa, M., Mark, A. G., Son, K., Lee, T., Fischer, P.

Advanced Science, 4(12):1700234, September 2017 (article)

Abstract
Nanoparticles composed of functional materials hold great promise for applications due to their unique electronic, optical, magnetic, and catalytic properties. However, a number of functional materials are not only difficult to fabricate at the nanoscale, but are also chemically unstable in solution. Hence, protecting nanoparticles from corrosion is a major challenge for those applications that require stability in aqueous solutions and biological fluids. Here, this study presents a generic scheme to grow hybrid 3D nanoparticles that are completely encapsulated by a nm thick protective shell. The method consists of vacuum-based growth and protection, and combines oblique physical vapor deposition with atomic layer deposition. It provides wide flexibility in the shape and composition of the nanoparticles, and the environments against which particles are protected. The work demonstrates the approach with multifunctional nanoparticles possessing ferromagnetic, plasmonic, and chiral properties. The present scheme allows nanocolloids, which immediately corrode without protection, to remain functional, at least for a week, in acidic solutions.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Coupling Adaptive Batch Sizes with Learning Rates

Balles, L., Romero, J., Hennig, P.

In Proceedings Conference on Uncertainty in Artificial Intelligence (UAI) 2017, pages: 410-419, (Editors: Gal Elidan and Kristian Kersting), Association for Uncertainty in Artificial Intelligence (AUAI), Conference on Uncertainty in Artificial Intelligence (UAI), August 2017 (inproceedings)

Abstract
Mini-batch stochastic gradient descent and variants thereof have become standard for large-scale empirical risk minimization like the training of neural networks. These methods are usually used with a constant batch size chosen by simple empirical inspection. The batch size significantly influences the behavior of the stochastic optimization algorithm, though, since it determines the variance of the gradient estimates. This variance also changes over the optimization process; when using a constant batch size, stability and convergence is thus often enforced by means of a (manually tuned) decreasing learning rate schedule. We propose a practical method for dynamic batch size adaptation. It estimates the variance of the stochastic gradients and adapts the batch size to decrease the variance proportionally to the value of the objective function, removing the need for the aforementioned learning rate decrease. In contrast to recent related work, our algorithm couples the batch size to the learning rate, directly reflecting the known relationship between the two. On three image classification benchmarks, our batch size adaptation yields faster optimization convergence, while simultaneously simplifying learning rate tuning. A TensorFlow implementation is available.

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Code link (url) Project Page [BibTex]

Code link (url) Project Page [BibTex]


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Dynamic Time-of-Flight

Schober, M., Adam, A., Yair, O., Mazor, S., Nowozin, S.

Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, pages: 170-179, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017 (conference)

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DOI [BibTex]

DOI [BibTex]


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Locomotion of light-driven soft microrobots through a hydrogel via local melting

Palagi, S., Mark, A. G., Melde, K., Qiu, T., Zeng, H., Parmeggiani, C., Martella, D., Wiersma, D. S., Fischer, P.

In 2017 International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS), pages: 1-5, July 2017 (inproceedings)

Abstract
Soft mobile microrobots whose deformation can be directly controlled by an external field can adapt to move in different environments. This is the case for the light-driven microrobots based on liquid-crystal elastomers (LCEs). Here we show that the soft microrobots can move through an agarose hydrogel by means of light-controlled travelling-wave motions. This is achieved by exploiting the inherent rise of the LCE temperature above the melting temperature of the agarose gel, which facilitates penetration of the microrobot through the hydrogel. The locomotion performance is investigated as a function of the travelling-wave parameters, showing that effective propulsion can be obtained by adapting the generated motion to the specific environmental conditions.

pf

DOI [BibTex]

DOI [BibTex]


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Event-based State Estimation: An Emulation-based Approach

Trimpe, S.

IET Control Theory & Applications, 11(11):1684-1693, July 2017 (article)

Abstract
An event-based state estimation approach for reducing communication in a networked control system is proposed. Multiple distributed sensor agents observe a dynamic process and sporadically transmit their measurements to estimator agents over a shared bus network. Local event-triggering protocols ensure that data is transmitted only when necessary to meet a desired estimation accuracy. The event-based design is shown to emulate the performance of a centralised state observer design up to guaranteed bounds, but with reduced communication. The stability results for state estimation are extended to the distributed control system that results when the local estimates are used for feedback control. Results from numerical simulations and hardware experiments illustrate the effectiveness of the proposed approach in reducing network communication.

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arXiv Supplementary material PDF DOI Project Page [BibTex]

arXiv Supplementary material PDF DOI Project Page [BibTex]


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Non-Equilibrium Assembly of Light-Activated Colloidal Mixtures

Singh, D. P., Choudhury, U., Fischer, P., Mark, A. G.

Advanced Materials, 29, pages: 1701328, June 2017, 32 (article)

Abstract
The collective phenomena exhibited by artificial active matter systems present novel routes to fabricating out-of-equilibrium microscale assemblies. Here, the crystallization of passive silica colloids into well-controlled 2D assemblies is shown, which is directed by a small number of self-propelled active colloids. The active colloids are titania–silica Janus particles that are propelled when illuminated by UV light. The strength of the attractive interaction and thus the extent of the assembled clusters can be regulated by the light intensity. A remarkably small number of the active colloids is sufficient to induce the assembly of the dynamic crystals. The approach produces rationally designed colloidal clusters and crystals with controllable sizes, shapes, and symmetries. This multicomponent active matter system offers the possibility of obtaining structures and assemblies that cannot be found in equilibrium systems.

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link (url) DOI [BibTex]


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Nanodiamonds That Swim

Kim, J. T., Choudhury, U., Hyeon-Ho, J., Fischer, P.

Advanced Materials, 29(30):1701024, June 2017, Back Cover (article)

Abstract
Nanodiamonds are emerging as nanoscale quantum probes for bio-sensing and imaging. This necessitates the development of new methods to accurately manipulate their position and orientation in aqueous solutions. The realization of an “active” nanodiamond (ND) swimmer in fluids, composed of a ND crystal containing nitrogen vacancy centers and a light-driven self-thermophoretic micromotor, is reported. The swimmer is propelled by a local temperature gradient created by laser illumination on its metal-coated side. Its locomotion—from translational to rotational motion—is successfully controlled by shape-dependent hydrodynamic interactions. The precise engineering of the swimmer's geometry is achieved by self-assembly combined with physical vapor shadow growth. The optical addressability of the suspended ND swimmers is demonstrated by observing the electron spin resonance in the presence of magnetic fields. Active motion at the nanoscale enables new sensing capabilities combined with active transport including, potentially, in living organisms.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Model-Based Policy Search for Automatic Tuning of Multivariate PID Controllers

Doerr, A., Nguyen-Tuong, D., Marco, A., Schaal, S., Trimpe, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 5295-5301, IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017 (inproceedings)

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PDF arXiv DOI Project Page [BibTex]

PDF arXiv DOI Project Page [BibTex]


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Virtual vs. Real: Trading Off Simulations and Physical Experiments in Reinforcement Learning with Bayesian Optimization

Marco, A., Berkenkamp, F., Hennig, P., Schoellig, A. P., Krause, A., Schaal, S., Trimpe, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 1557-1563, IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017 (inproceedings)

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PDF arXiv ICRA 2017 Spotlight presentation Virtual vs. Real - Video explanation DOI Project Page [BibTex]

PDF arXiv ICRA 2017 Spotlight presentation Virtual vs. Real - Video explanation DOI Project Page [BibTex]


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Soft 3D-Printed Phantom of the Human Kidney with Collecting System

Adams, F., Qiu, T., Mark, A., Fritz, B., Kramer, L., Schlager, D., Wetterauer, U., Miernik, A., Fischer, P.

Ann. of Biomed. Eng., 45(4):963-972, April 2017 (article)

Abstract
Organ models are used for planning and simulation of operations, developing new surgical instruments, and training purposes. There is a substantial demand for in vitro organ phantoms, especially in urological surgery. Animal models and existing simulator systems poorly mimic the detailed morphology and the physical properties of human organs. In this paper, we report a novel fabrication process to make a human kidney phantom with realistic anatomical structures and physical properties. The detailed anatomical structure was directly acquired from high resolution CT data sets of human cadaveric kidneys. The soft phantoms were constructed using a novel technique that combines 3D wax printing and polymer molding. Anatomical details and material properties of the phantoms were validated in detail by CT scan, ultrasound, and endoscopy. CT reconstruction, ultrasound examination, and endoscopy showed that the designed phantom mimics a real kidney's detailed anatomy and correctly corresponds to the targeted human cadaver's upper urinary tract. Soft materials with a tensile modulus of 0.8-1.5 MPa as well as biocompatible hydrogels were used to mimic human kidney tissues. We developed a method of constructing 3D organ models from medical imaging data using a 3D wax printing and molding process. This method is cost-effective means for obtaining a reproducible and robust model suitable for surgical simulation and training purposes.

pf

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets

Klein, A., Falkner, S., Bartels, S., Hennig, P., Hutter, F.

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017), 54, pages: 528-536, Proceedings of Machine Learning Research, (Editors: Sign, Aarti and Zhu, Jerry), PMLR, April 2017 (conference)

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pdf link (url) Project Page [BibTex]

pdf link (url) Project Page [BibTex]


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Chapter 8 - Micro- and nanorobots in Newtonian and biological viscoelastic fluids

Palagi, S., (Walker) Schamel, D., Qiu, T., Fischer, P.

In Microbiorobotics, pages: 133 - 162, 8, Micro and Nano Technologies, Second edition, Elsevier, Boston, March 2017 (incollection)

Abstract
Swimming microorganisms are a source of inspiration for small scale robots that are intended to operate in fluidic environments including complex biomedical fluids. Nature has devised swimming strategies that are effective at small scales and at low Reynolds number. These include the rotary corkscrew motion that, for instance, propels a flagellated bacterial cell, as well as the asymmetric beat of appendages that sperm cells or ciliated protozoa use to move through fluids. These mechanisms can overcome the reciprocity that governs the hydrodynamics at small scale. The complex molecular structure of biologically important fluids presents an additional challenge for the effective propulsion of microrobots. In this chapter it is shown how physical and chemical approaches are essential in realizing engineered abiotic micro- and nanorobots that can move in biomedically important environments. Interestingly, we also describe a microswimmer that is effective in biological viscoelastic fluids that does not have a natural analogue.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Wireless micro-robots for endoscopic applications in urology

Adams, F., Qiu, T., Mark, A. G., Melde, K., Palagi, S., Miernik, A., Fischer, P.

In Eur Urol Suppl, 16(3):e1914, March 2017 (inproceedings)

Abstract
Endoscopy is an essential and common method for both diagnostics and therapy in Urology. Current flexible endoscope is normally cable-driven, thus it is hard to be miniaturized and its reachability is restricted as only one bending section near the tip with one degree of freedom (DoF) is allowed. Recent progresses in micro-robotics offer a unique opportunity for medical inspections in minimally invasive surgery. Micro-robots are active devices that has a feature size smaller than one millimeter and can normally be actuated and controlled wirelessly. Magnetically actuated micro-robots have been demonstrated to propel through biological fluids.Here, we report a novel micro robotic arm, which is actuated wirelessly by ultrasound. It works as a miniaturized endoscope with a side length of ~1 mm, which fits through the 3 Fr. tool channel of a cystoscope, and successfully performs an active cystoscopy in a rabbit bladder.

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link (url) DOI [BibTex]


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Pattern formation and collective effects in populations of magnetic microswimmers

Vach, P. J., (Walker) Schamel, D., Fischer, P., Fratzl, P., Faivre, D.

J. of Phys. D: Appl. Phys., 50(11):11LT03, Febuary 2017 (article)

Abstract
Self-propelled particles are one prototype of synthetic active matter used to understand complex biological processes, such as the coordination of movement in bacterial colonies or schools of fishes. Collective patterns such as clusters were observed for such systems, reproducing features of biological organization. However, one limitation of this model is that the synthetic assemblies are made of identical individuals. Here we introduce an active system based on magnetic particles at colloidal scales. We use identical but also randomly-shaped magnetic micropropellers and show that they exhibit dynamic and reversible pattern formation.

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DOI [BibTex]

DOI [BibTex]


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On-chip enzymatic microbiofuel cell-powered integrated circuits

Mark, A. G., Suraniti, E., Roche, J., Richter, H., Kuhn, A., Mano, N., Fischer, P.

Lab on a Chip, 17(10):1761-1768, Febuary 2017, Recent HOT Article (article)

Abstract
A variety of diagnostic and therapeutic medical technologies rely on long term implantation of an electronic device to monitor or regulate a patient's condition. One proposed approach to powering these devices is to use a biofuel cell to convert the chemical energy from blood nutrients into electrical current to supply the electronics. We present here an enzymatic microbiofuel cell whose electrodes are directly integrated into a digital electronic circuit. Glucose oxidizing and oxygen reducing enzymes are immobilized on microelectrodes of an application specific integrated circuit (ASIC) using redox hydrogels to produce an enzymatic biofuel cell, capable of harvesting electrical power from just a single droplet of 5 mM glucose solution. Optimisation of the fuel cell voltage and power to match the requirements of the electronics allow self-powered operation of the on-board digital circuitry. This study represents a step towards implantable self-powered electronic devices that gather their energy from physiological fluids.

Recent HOT Article.

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DOI [BibTex]

DOI [BibTex]


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Strong Rotational Anisotropies Affect Nonlinear Chiral Metamaterials

Hooper, D. C., Mark, A. G., Kuppe, C., Collins, J. T., Fischer, P., Valev, V. K.

Advanced Materials, 29(13):1605110, January 2017 (article)

Abstract
Masked by rotational anisotropies, the nonlinear chiroptical response of a metamaterial is initially completely inaccessible. Upon rotating the sample the chiral information emerges. These results highlight the need for a general method to extract the true chiral contributions to the nonlinear optical signal, which would be hugely valuable in the present context of increasingly complex chiral meta/nanomaterials.

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DOI [BibTex]

DOI [BibTex]


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Early Stopping Without a Validation Set

Mahsereci, M., Balles, L., Lassner, C., Hennig, P.

arXiv preprint arXiv:1703.09580, 2017 (article)

Abstract
Early stopping is a widely used technique to prevent poor generalization performance when training an over-expressive model by means of gradient-based optimization. To find a good point to halt the optimizer, a common practice is to split the dataset into a training and a smaller validation set to obtain an ongoing estimate of the generalization performance. In this paper we propose a novel early stopping criterion which is based on fast-to-compute, local statistics of the computed gradients and entirely removes the need for a held-out validation set. Our experiments show that this is a viable approach in the setting of least-squares and logistic regression as well as neural networks.

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link (url) Project Page Project Page [BibTex]


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Krylov Subspace Recycling for Fast Iterative Least-Squares in Machine Learning

Roos, F. D., Hennig, P.

arXiv preprint arXiv:1706.00241, 2017 (article)

Abstract
Solving symmetric positive definite linear problems is a fundamental computational task in machine learning. The exact solution, famously, is cubicly expensive in the size of the matrix. To alleviate this problem, several linear-time approximations, such as spectral and inducing-point methods, have been suggested and are now in wide use. These are low-rank approximations that choose the low-rank space a priori and do not refine it over time. While this allows linear cost in the data-set size, it also causes a finite, uncorrected approximation error. Authors from numerical linear algebra have explored ways to iteratively refine such low-rank approximations, at a cost of a small number of matrix-vector multiplications. This idea is particularly interesting in the many situations in machine learning where one has to solve a sequence of related symmetric positive definite linear problems. From the machine learning perspective, such deflation methods can be interpreted as transfer learning of a low-rank approximation across a time-series of numerical tasks. We study the use of such methods for our field. Our empirical results show that, on regression and classification problems of intermediate size, this approach can interpolate between low computational cost and numerical precision.

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link (url) Project Page [BibTex]


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Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings

Kanagawa, M., Sriperumbudur, B. K., Fukumizu, K.

Arxiv e-prints, arXiv:1709.00147v1 [math.NA], 2017 (article)

Abstract
This paper presents convergence analysis of kernel-based quadrature rules in misspecified settings, focusing on deterministic quadrature in Sobolev spaces. In particular, we deal with misspecified settings where a test integrand is less smooth than a Sobolev RKHS based on which a quadrature rule is constructed. We provide convergence guarantees based on two different assumptions on a quadrature rule: one on quadrature weights, and the other on design points. More precisely, we show that convergence rates can be derived (i) if the sum of absolute weights remains constant (or does not increase quickly), or (ii) if the minimum distance between distance design points does not decrease very quickly. As a consequence of the latter result, we derive a rate of convergence for Bayesian quadrature in misspecified settings. We reveal a condition on design points to make Bayesian quadrature robust to misspecification, and show that, under this condition, it may adaptively achieve the optimal rate of convergence in the Sobolev space of a lesser order (i.e., of the unknown smoothness of a test integrand), under a slightly stronger regularity condition on the integrand.

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arXiv [BibTex]

arXiv [BibTex]


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Fast Bayesian hyperparameter optimization on large datasets

Klein, A., Falkner, S., Bartels, S., Hennig, P., Hutter, F.

Electronic Journal of Statistics, 11, 2017 (article)

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[BibTex]

[BibTex]