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2017


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Electroencephalographic identifiers of motor adaptation learning

Ozdenizci, O., Yalcin, M., Erdogan, A., Patoglu, V., Grosse-Wentrup, M., Cetin, M.

Journal of Neural Engineering, 14(4):046027, 2017 (article)

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link (url) [BibTex]

2017


link (url) [BibTex]


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Gene delivery particle engineering strategies for shape-dependent targeting of cells and tissues.

Kozielski, K., Sitti, M.

Current Gene Therapy, 17, 2017 (article)

Abstract
Background: Successful gene delivery requires overcoming both systemic and intracellular obstacles before the nucleic acid cargo can successfully reach its tissue and subcellular target location. Materials & Methods: Non-viral mechanisms to enable targeting while avoiding off-target delivery have arisen via biological, chemical, and physical engineering strategies. Discussion: Herein we will discuss the physical parameters in particle design that promote tissue- and cell-targeted delivery of genetic cargo. We will discuss systemic concerns, such as circulation, tissue localization, and clearance, as well as cell-scale obstacles, such as cellular uptake and nucleic acid packaging. Conclusion: In particular, we will focus on engineering particle shape and size in order to enhance delivery and promote precise targeting. We will also address methods to program or change particle shape in situ using environmentally triggered cues.

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DOI [BibTex]


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Self-Organized Behavior Generation for Musculoskeletal Robots

Der, R., Martius, G.

Frontiers in Neurorobotics, 11, pages: 8, 2017 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Detecting distortions of peripherally presented letter stimuli under crowded conditions

Wallis, T. S. A., Tobias, S., Bethge, M., Wichmann, F. A.

Attention, Perception, & Psychophysics, 79(3):850-862, 2017 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


Multi-fractal characterization of bacterial swimming dynamics: a case study on real and simulated Serratia marcescens
Multi-fractal characterization of bacterial swimming dynamics: a case study on real and simulated Serratia marcescens

Koorehdavoudi, H., Bogdan, P., Wei, G., Marculescu, R., Zhuang, J., Carlsen, R. W., Sitti, M.

Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 473(2203), The Royal Society, 2017 (article)

Abstract
To add to the current state of knowledge about bacterial swimming dynamics, in this paper, we study the fractal swimming dynamics of populations of Serratia marcescens bacteria both in vitro and in silico, while accounting for realistic conditions like volume exclusion, chemical interactions, obstacles and distribution of chemoattractant in the environment. While previous research has shown that bacterial motion is non-ergodic, we demonstrate that, besides the non-ergodicity, the bacterial swimming dynamics is multi-fractal in nature. Finally, we demonstrate that the multi-fractal characteristic of bacterial dynamics is strongly affected by bacterial density and chemoattractant concentration.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


{Temperature-dependent first-order reversal curve measurements on unusually hard magnetic low-temperature phase of MnBi}
Temperature-dependent first-order reversal curve measurements on unusually hard magnetic low-temperature phase of MnBi

Muralidhar, S., Gräfe, J., Chen, Y., Etter, M., Gregori, G., Ener, S., Sawatzki, S., Hono, K., Gutfleisch, O., Kronmüller, H., Schütz, G., Goering, E. J.

{Physical Review B}, 95(2), American Physical Society, Woodbury, NY, 2017 (article)

Abstract
We have performed first-order reversal curve (FORC) measurements to investigate the irreversible magnetization processes in the low-temperature phase of MnBi. Using temperature-dependent FORC analysis, we are able to provide a clear insight into the effects of microstructural parameters such as grain diameter, shape, and surface composition on the coercivity of nucleation hardened permanent magnet MnBi. FORC diagrams of MnBi show a unique broadening and narrowing of the coercive field distribution with increasing temperature. We were able to microscopically identify the reason for this behavior, based on the shift in the single domain critical diameter from nearly 1 to 2 μm, thereby changing the dependence of coercivity with particle size. This is based on a strong increase in the uniaxial anisotropy constant with increasing temperature. Furthermore, the results also give an additional confirmation that the magnetic hardening in low-temperature phase MnBi occurs due to nucleation mechanisms. In our case, we show that temperature-dependent FORC measurements provide a powerful tool for the microscopic understanding of high-performance permanent magnet systems.

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Perils of ad hoc approximations for the activity function of chemically powered colloids

Popescu, M. N., Uspal, W. E., Tasinkevych, M., Dietrich, S.

The European Physical Journal E, 40, EDP Sciences; Società Italiana di Fisica; Springer, Les Ulis; Bologna; Heidelberg, 2017 (article)

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DOI [BibTex]

DOI [BibTex]


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Transient Casimir Forces from Quenches in Thermal and Active Matter

Rohwer, C. M., Kardar, M., Krüger, M.

Physical Review Letters, 118(1), American Physical Society, Woodbury, N.Y., 2017 (article)

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DOI [BibTex]

DOI [BibTex]


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Rotational motion of dimers of Janus particles

Majee, A.

European Physical Journal E, 40(3), Springer, Berlin, 2017 (article)

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DOI [BibTex]

DOI [BibTex]


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Designing Micro- and Nanoswimmers for Specific Applications

Katuri, J., Ma, X., Stanton, M. M., Sanchez, S.

Accounts of Chemical Research, 50(1):2-11, American Chemical Society, Easton, Pa., 2017 (article)

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DOI [BibTex]

DOI [BibTex]


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Wedge wetting by electrolyte solutions

Mußotter, M., Bier, M.

Physical Review E, 96(3), American Physical Society, Melville, NY, 2017 (article)

icm

DOI [BibTex]

DOI [BibTex]


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Effect of boundaries on vacuum field fluctuations and radiation-mediated interactions between atoms

Armata, F., Butera, S., Fiscelli, G., Incardone, R., Notararigo, V., Palacino, R., Passante, R., Rizzuto, L., Spagnolo, S.

Journal of Physics: Conference Series, 880, IOP Publishing, Bristol, 2017 (article)

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DOI [BibTex]

DOI [BibTex]


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Non-equilibrium forces after temperature quenches in ideal fluids with conserved density

Hölzl, Christian

Universität Stuttgart, Stuttgart, 2017 (mastersthesis)

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[BibTex]

[BibTex]


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Numerical studies of active colloids at fluid interfaces

Peter, Toni

Universität Stuttgart, Stuttgart, 2017 (mastersthesis)

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[BibTex]

[BibTex]


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Smectic phases in ionic liquid crystals

Bartsch, H., Bier, M., Dietrich, S.

Journal of Physics: Condensed Matter, 29(46), IOP Publishing, Bristol, 2017 (article)

icm

DOI [BibTex]

DOI [BibTex]


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Pushing Bacterial Biohybrids to In Vivo Applications

Stanton, M. M., Sánchez, S.

Trends in Biotechnology, 35(10):910-913, Elsevier Current Trends, Amsterdam, Netherlands, 2017 (article)

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DOI [BibTex]

DOI [BibTex]


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Thermally activated diffusion of copper into amorphous carbon

Appy, D., Wallingford, M., Jing, D. P., Ott, R., Tringides, M. C., Richter, G., Thiel, P. A.

Journal of Vacuum Science & Technology A, 35(6), 2017 (article)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Unsupervised clustering of EOG as a viable substitute for optical eye-tracking

Flad, N., Fomina, T., Bülthoff, H. H., Chuang, L. L.

In First Workshop on Eye Tracking and Visualization (ETVIS 2015), pages: 151-167, Mathematics and Visualization, (Editors: Burch, M., Chuang, L., Fisher, B., Schmidt, A., and Weiskopf, D.), Springer, 2017 (inbook)

ei

DOI [BibTex]

DOI [BibTex]


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BundleMAP: Anatomically Localized Classification, Regression, and Hypothesis Testing in Diffusion MRI

Khatami, M., Schmidt-Wilcke, T., Sundgren, P. C., Abbasloo, A., Schölkopf, B., Schultz, T.

Pattern Recognition, 63, pages: 593-600, 2017 (article)

ei

DOI [BibTex]

DOI [BibTex]


Data-Driven Physics for Human Soft Tissue Animation
Data-Driven Physics for Human Soft Tissue Animation

Kim, M., Pons-Moll, G., Pujades, S., Bang, S., Kim, J., Black, M. J., Lee, S.

ACM Transactions on Graphics, (Proc. SIGGRAPH), 36(4):54:1-54:12, 2017 (article)

Abstract
Data driven models of human poses and soft-tissue deformations can produce very realistic results, but they only model the visible surface of the human body and cannot create skin deformation due to interactions with the environment. Physical simulations can generalize to external forces, but their parameters are difficult to control. In this paper, we present a layered volumetric human body model learned from data. Our model is composed of a data-driven inner layer and a physics-based external layer. The inner layer is driven with a volumetric statistical body model (VSMPL). The soft tissue layer consists of a tetrahedral mesh that is driven using the finite element method (FEM). Model parameters, namely the segmentation of the body into layers and the soft tissue elasticity, are learned directly from 4D registrations of humans exhibiting soft tissue deformations. The learned two layer model is a realistic full-body avatar that generalizes to novel motions and external forces. Experiments show that the resulting avatars produce realistic results on held out sequences and react to external forces. Moreover, the model supports the retargeting of physical properties from one avatar when they share the same topology.

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video paper link (url) Project Page [BibTex]

video paper link (url) Project Page [BibTex]


Learning Inference Models for Computer Vision
Learning Inference Models for Computer Vision

Jampani, V.

MPI for Intelligent Systems and University of Tübingen, 2017 (phdthesis)

Abstract
Computer vision can be understood as the ability to perform 'inference' on image data. Breakthroughs in computer vision technology are often marked by advances in inference techniques, as even the model design is often dictated by the complexity of inference in them. This thesis proposes learning based inference schemes and demonstrates applications in computer vision. We propose techniques for inference in both generative and discriminative computer vision models. Despite their intuitive appeal, the use of generative models in vision is hampered by the difficulty of posterior inference, which is often too complex or too slow to be practical. We propose techniques for improving inference in two widely used techniques: Markov Chain Monte Carlo (MCMC) sampling and message-passing inference. Our inference strategy is to learn separate discriminative models that assist Bayesian inference in a generative model. Experiments on a range of generative vision models show that the proposed techniques accelerate the inference process and/or converge to better solutions. A main complication in the design of discriminative models is the inclusion of prior knowledge in a principled way. For better inference in discriminative models, we propose techniques that modify the original model itself, as inference is simple evaluation of the model. We concentrate on convolutional neural network (CNN) models and propose a generalization of standard spatial convolutions, which are the basic building blocks of CNN architectures, to bilateral convolutions. First, we generalize the existing use of bilateral filters and then propose new neural network architectures with learnable bilateral filters, which we call `Bilateral Neural Networks'. We show how the bilateral filtering modules can be used for modifying existing CNN architectures for better image segmentation and propose a neural network approach for temporal information propagation in videos. Experiments demonstrate the potential of the proposed bilateral networks on a wide range of vision tasks and datasets. In summary, we propose learning based techniques for better inference in several computer vision models ranging from inverse graphics to freely parameterized neural networks. In generative vision models, our inference techniques alleviate some of the crucial hurdles in Bayesian posterior inference, paving new ways for the use of model based machine learning in vision. In discriminative CNN models, the proposed filter generalizations aid in the design of new neural network architectures that can handle sparse high-dimensional data as well as provide a way for incorporating prior knowledge into CNNs.

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pdf [BibTex]

pdf [BibTex]


Recent Advances in Skin Penetration Enhancers for Transdermal Gene and Drug Delivery
Recent Advances in Skin Penetration Enhancers for Transdermal Gene and Drug Delivery

Amjadia, M., Mostaghacia, B., Sittia, M.

Current Gene Therapy, 17, 2017 (article)

Abstract
There is a growing interest in transdermal delivery systems because of their noninvasive, targeted, and on-demand delivery of gene and drugs. However, efficient penetration of therapeutic compounds into the skin is still challenging largely due to the impermeability of the outermost layer of the skin, known as stratum corneum. Recently, there have been major research activities to enhance the skin penetration depth of pharmacological agents. This article reviews recent advances in the development of various strategies for skin penetration enhancement. We show that approaches such as ultrasound waves, laser, and microneedle patches have successfully been employed to physically disrupt the stratum corneum structure for enhanced transdermal delivery. Rather than physical approaches, several non-physical route have also been utilized for efficient transdermal delivery across the skin barrier. Finally, we discuss some clinical applications of transdermal delivery systems for gene and drug delivery. This paper shows that transdermal delivery devices can potentially function for diverse healthcare and medical applications while further investigations are still necessary for more efficient skin penetration of gene and drugs.

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DOI [BibTex]


A fully dense and globally consistent 3D map reconstruction approach for GI tract to enhance therapeutic relevance of the endoscopic capsule robot
A fully dense and globally consistent 3D map reconstruction approach for GI tract to enhance therapeutic relevance of the endoscopic capsule robot

Turan, M., Pilavci, Y. Y., Jamiruddin, R., Araujo, H., Konukoglu, E., Sitti, M.

arXiv preprint arXiv:1705.06524, 2017 (article)

Abstract
In the gastrointestinal (GI) tract endoscopy field, ingestible wireless capsule endoscopy is emerging as a novel, minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range of diseases and pathologies. Since the development of this technology, medical device companies and many research groups have made substantial progress in converting passive capsule endoscopes to robotic active capsule endoscopes with most of the functionality of current active flexible endoscopes. However, robotic capsule endoscopy still has some challenges. In particular, the use of such devices to generate a precise three-dimensional (3D) mapping of the entire inner organ remains an unsolved problem. Such global 3D maps of inner organs would help doctors to detect the location and size of diseased areas more accurately and intuitively, thus permitting more reliable diagnoses. To our knowledge, this paper presents the first complete pipeline for a complete 3D visual map reconstruction of the stomach. The proposed pipeline is modular and includes a preprocessing module, an image registration module, and a final shape-from-shading-based 3D reconstruction module; the 3D map is primarily generated by a combination of image stitching and shape-from-shading techniques, and is updated in a frame-by-frame iterative fashion via capsule motion inside the stomach. A comprehensive quantitative analysis of the proposed 3D reconstruction method is performed using an esophagus gastro duodenoscopy simulator, three different endoscopic cameras, and a 3D optical scanner.

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link (url) Project Page [BibTex]


Mobile Microrobotics
Mobile Microrobotics

Sitti, M.

Mobile Microrobotics, The MIT Press, Cambridge, MA, 2017 (book)

Abstract
Progress in micro- and nano-scale science and technology has created a demand for new microsystems for high-impact applications in healthcare, biotechnology, manufacturing, and mobile sensor networks. The new robotics field of microrobotics has emerged to extend our interactions and explorations to sub-millimeter scales. This is the first textbook on micron-scale mobile robotics, introducing the fundamentals of design, analysis, fabrication, and control, and drawing on case studies of existing approaches. The book covers the scaling laws that can be used to determine the dominant forces and effects at the micron scale; models forces acting on microrobots, including surface forces, friction, and viscous drag; and describes such possible microfabrication techniques as photo-lithography, bulk micromachining, and deep reactive ion etching. It presents on-board and remote sensing methods, noting that remote sensors are currently more feasible; studies possible on-board microactuators; discusses self-propulsion methods that use self-generated local gradients and fields or biological cells in liquid environments; and describes remote microrobot actuation methods for use in limited spaces such as inside the human body. It covers possible on-board powering methods, indispensable in future medical and other applications; locomotion methods for robots on surfaces, in liquids, in air, and on fluid-air interfaces; and the challenges of microrobot localization and control, in particular multi-robot control methods for magnetic microrobots. Finally, the book addresses current and future applications, including noninvasive medical diagnosis and treatment, environmental remediation, and scientific tools.

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Mobile Microrobotics By Metin Sitti - Chapter 1 (PDF) link (url) [BibTex]

Mobile Microrobotics By Metin Sitti - Chapter 1 (PDF) link (url) [BibTex]


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New Directions for Learning with Kernels and Gaussian Processes (Dagstuhl Seminar 16481)

Gretton, A., Hennig, P., Rasmussen, C., Schölkopf, B.

Dagstuhl Reports, 6(11):142-167, 2017 (book)

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DOI [BibTex]

DOI [BibTex]


Planning spin-walking locomotion for automatic grasping of microobjects by an untethered magnetic microgripper
Planning spin-walking locomotion for automatic grasping of microobjects by an untethered magnetic microgripper

Dong, X., Sitti, M.

In 2017 IEEE International Conference on Robotics and Automation (ICRA), pages: 6612-6618, 2017 (inproceedings)

Abstract
Most demonstrated mobile microrobot tasks so far have been achieved via pick-and-placing and dynamic trapping with teleoperation or simple path following algorithms. In our previous work, an untethered magnetic microgripper has been developed which has advanced functions, such as gripping objects. Both teleoperated manipulation in 2D and 3D have been demonstrated. However, it is challenging to control the magnetic microgripper to carry out manipulation tasks, because the grasping of objects so far in the literature relies heavily on teleoperation, which takes several minutes with even a skilled human expert. Here, we propose a new spin-walking locomotion and an automated 2D grasping motion planner for the microgripper, which enables time-efficient automatic grasping of microobjects that has not been achieved yet for untethered microrobots. In its locomotion, the microgripper repeatedly rotates about two principal axes to regulate its pose and move precisely on a surface. The motion planner could plan different motion primitives for grasping and compensate the uncertainties in the motion by learning the uncertainties and planning accordingly. We experimentally demonstrated that, using the proposed method, the microgripper could align to the target pose with error less than 0.1 body length and grip the objects within 40 seconds. Our method could significantly improve the time efficiency of micro-scale manipulation and have potential applications in microassembly and biomedical engineering.

pi

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Statistical Asymmetries Between Cause and Effect

Janzing, D.

In Time in Physics, pages: 129-139, Tutorials, Schools, and Workshops in the Mathematical Sciences, (Editors: Renner, Renato and Stupar, Sandra), Springer International Publishing, Cham, 2017 (inbook)

ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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A parametric texture model based on deep convolutional features closely matches texture appearance for humans

Wallis, T. S. A., Funke, C. M., Ecker, A. S., Gatys, L. A., Wichmann, F. A., Bethge, M.

Journal of Vision, 17(12), 2017 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Die Bedeutung der Beobachtungsperspektive beim Bewegungslernen von Mensch-Roboter-Dyaden

Kollegger, G., Reinhardt, N., Ewerton, M., Peters, J., Wiemeyer, J.

DVS Sportmotorik 2017, 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Robot Learning

Peters, J., Tedrake, R., Roy, N., Morimoto, J.

In Encyclopedia of Machine Learning and Data Mining, pages: 1106-1109, 2nd, (Editors: Sammut, Claude and Webb, Geoffrey I.), Springer US, 2017 (inbook)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Lens Depth Function and k-Relative Neighborhood Graph: Versatile Tools for Ordinal Data Analysis

Kleindessner, M., von Luxburg, U.

Journal of Machine Learning Research (JMLR), Journal of Machine Learning Research, 18, 2017 (article)

slt

Project Page [BibTex]

Project Page [BibTex]


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Development and Evaluation of a Portable BCI System for Remote Data Acquisition

Emde, T.

Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

ei

[BibTex]

[BibTex]


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Brain-Computer Interfaces for patients with Amyotrophic Lateral Sclerosis

Fomina, T.

Eberhard Karls Universität Tübingen, Germany, 2017 (phdthesis)

ei

[BibTex]

[BibTex]


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Exploiting diffusion barrier and chemical affinity of metal-organic frameworks for efficient hydrogen isotope separation

Kim, J. Y., Balderas-Xicohténcatl, R., Zhang, L., Kang, S. G., Hirscher, M., Oh, H., Moon, H. R.

{Journal of the American Chemical Society}, 139(42):15135-15141, American Chemical Society, Washington, DC, 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Facile fabrication of mesoporous silica micro-jets with multi-functionalities

Vilela, D., Hortelao, A. C., Balderas-Xicohténcatl, R., Hirscher, M., Hahn, K., Ma, X., Sánchez, S.

{Nanoscale}, 9(37):13990-13997, Royal Society of Chemistry, Cambridge, UK, 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Functionalised metal-organic frameworks: a novel approach to stabilising single metal atoms

Szilágyi, P. Á., Rogers, D. M., Zaiser, I., Callini, E., Turner, S., Borgschulte, A., Züttel, A., Geerlings, H., Hirscher, M., Dam, B.

{Journal of Materials Chemistry A}, 5(30):15559-15566, Royal Society of Chemistry, Cambridge, UK, 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Particles with nonlinear electric response: Suppressing van der Waals forces by an external field

Soo, H., Dean, D. S., Krüger, M.

Physical Review E, 95(1), American Physical Society, Melville, NY, 2017 (article)

icm

DOI [BibTex]

DOI [BibTex]


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Electrolyte solutions at curved electrodes. I. Mesoscopic approach

Reindl, A., Bier, M., Dietrich, S.

The Journal of Chemical Physics, 146(15), American Institute of Physics, Woodbury, N.Y., 2017 (article)

icm

DOI [BibTex]

DOI [BibTex]


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Self-propelling micro-nanorobots: challenges and fututre perspectives in nanomedicine

Ma, X., Sánchez, S.

Nanomedicine, 12(12):1363-1367, Future Medicine Ltd, London, UK, 2017 (article)

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DOI [BibTex]

DOI [BibTex]


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Salt-induced microheterogeneities in binary liquid mixtures

Bier, M., Mars, J., Li, H., Mezger, M.

Physical Review E, 96(2), American Physical Society, Melville, NY, 2017 (article)

icm

DOI [BibTex]

DOI [BibTex]


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Forward-backward multiplicity correlations in proton-proton collisions from several GeV to LHC energies

Bravina, L., Bleibel, J., Emaus, R., Zabrodin, E.

EPJ Web of Conferences, 164, EDP Sciences, Les Ulis, 2017 (article)

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DOI [BibTex]

DOI [BibTex]


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Key-lock colloids in a nematic liquid crystal

Silvestre, N. M., Tasinkevych, M.

Physical Review E, 95(1), American Physical Society, Melville, NY, 2017 (article)

icm

DOI [BibTex]

DOI [BibTex]


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Collective dynamics of laterally confined active particles near fluid-fluid interfaces

Kistner, Irina

Universität Stuttgart, Stuttgart, 2017 (mastersthesis)

icm

[BibTex]

[BibTex]


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Fluctuation induced forces in critical films with disorder at their surfaces

Maciolek, A., Vasilyev, O., Dotsenko, V., Dietrich, S.

Journal of Statistical Mechanics: Theory and Experiment, Institute of Physics Publishing, Bristol, England, 2017 (article)

icm

DOI [BibTex]

DOI [BibTex]


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Action at a distance in classical uniaxial ferromagnetic arrays

Abraham, D. B., Maciolek, A., Squarcini, A., Vasilyev, O.

Physical Review E, 96(4), American Physical Society, Melville, NY, 2017 (article)

icm

DOI [BibTex]

DOI [BibTex]