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2018


A Value-Driven Eldercare Robot: Virtual and Physical Instantiations of a Case-Supported Principle-Based Behavior Paradigm
A Value-Driven Eldercare Robot: Virtual and Physical Instantiations of a Case-Supported Principle-Based Behavior Paradigm

Anderson, M., Anderson, S., Berenz, V.

Proceedings of the IEEE, pages: 1,15, October 2018 (article)

Abstract
In this paper, a case-supported principle-based behavior paradigm is proposed to help ensure ethical behavior of autonomous machines. We argue that ethically significant behavior of autonomous systems should be guided by explicit ethical principles determined through a consensus of ethicists. Such a consensus is likely to emerge in many areas in which autonomous systems are apt to be deployed and for the actions they are liable to undertake. We believe that this is the case since we are more likely to agree on how machines ought to treat us than on how human beings ought to treat one another. Given such a consensus, particular cases of ethical dilemmas where ethicists agree on the ethically relevant features and the right course of action can be used to help discover principles that balance these features when they are in conflict. Such principles not only help ensure ethical behavior of complex and dynamic systems but also can serve as a basis for justification of this behavior. The requirements, methods, implementation, and evaluation components of the paradigm are detailed as well as its instantiation in both a simulated and real robot functioning in the domain of eldercare.

am

link (url) DOI [BibTex]

2018



Probabilistic Solutions To Ordinary Differential Equations As Non-Linear Bayesian Filtering: A New Perspective
Probabilistic Solutions To Ordinary Differential Equations As Non-Linear Bayesian Filtering: A New Perspective

Tronarp, F., Kersting, H., Särkkä, S., Hennig, P.

ArXiv preprint 2018, arXiv:1810.03440 [stat.ME], October 2018 (article)

Abstract
We formulate probabilistic numerical approximations to solutions of ordinary differential equations (ODEs) as problems in Gaussian process (GP) regression with non-linear measurement functions. This is achieved by defining the measurement sequence to consists of the observations of the difference between the derivative of the GP and the vector field evaluated at the GP---which are all identically zero at the solution of the ODE. When the GP has a state-space representation, the problem can be reduced to a Bayesian state estimation problem and all widely-used approximations to the Bayesian filtering and smoothing problems become applicable. Furthermore, all previous GP-based ODE solvers, which were formulated in terms of generating synthetic measurements of the vector field, come out as specific approximations. We derive novel solvers, both Gaussian and non-Gaussian, from the Bayesian state estimation problem posed in this paper and compare them with other probabilistic solvers in illustrative experiments.

pn

link (url) Project Page [BibTex]


Playful: Reactive Programming for Orchestrating Robotic Behavior
Playful: Reactive Programming for Orchestrating Robotic Behavior

Berenz, V., Schaal, S.

IEEE Robotics Automation Magazine, 25(3):49-60, September 2018 (article) In press

Abstract
For many service robots, reactivity to changes in their surroundings is a must. However, developing software suitable for dynamic environments is difficult. Existing robotic middleware allows engineers to design behavior graphs by organizing communication between components. But because these graphs are structurally inflexible, they hardly support the development of complex reactive behavior. To address this limitation, we propose Playful, a software platform that applies reactive programming to the specification of robotic behavior.

am

playful website playful_IEEE_RAM link (url) DOI [BibTex]


ClusterNet: Instance Segmentation in RGB-D Images
ClusterNet: Instance Segmentation in RGB-D Images

Shao, L., Tian, Y., Bohg, J.

arXiv, September 2018, Submitted to ICRA'19 (article) Submitted

Abstract
We propose a method for instance-level segmentation that uses RGB-D data as input and provides detailed information about the location, geometry and number of {\em individual\/} objects in the scene. This level of understanding is fundamental for autonomous robots. It enables safe and robust decision-making under the large uncertainty of the real-world. In our model, we propose to use the first and second order moments of the object occupancy function to represent an object instance. We train an hourglass Deep Neural Network (DNN) where each pixel in the output votes for the 3D position of the corresponding object center and for the object's size and pose. The final instance segmentation is achieved through clustering in the space of moments. The object-centric training loss is defined on the output of the clustering. Our method outperforms the state-of-the-art instance segmentation method on our synthesized dataset. We show that our method generalizes well on real-world data achieving visually better segmentation results.

am

link (url) [BibTex]

link (url) [BibTex]


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Convergence Rates of Gaussian ODE Filters

Kersting, H., Sullivan, T. J., Hennig, P.

arXiv preprint 2018, arXiv:1807.09737 [math.NA], July 2018 (article)

Abstract
A recently-introduced class of probabilistic (uncertainty-aware) solvers for ordinary differential equations (ODEs) applies Gaussian (Kalman) filtering to initial value problems. These methods model the true solution $x$ and its first $q$ derivatives a priori as a Gauss--Markov process $\boldsymbol{X}$, which is then iteratively conditioned on information about $\dot{x}$. We prove worst-case local convergence rates of order $h^{q+1}$ for a wide range of versions of this Gaussian ODE filter, as well as global convergence rates of order $h^q$ in the case of $q=1$ and an integrated Brownian motion prior, and analyse how inaccurate information on $\dot{x}$ coming from approximate evaluations of $f$ affects these rates. Moreover, we present explicit formulas for the steady states and show that the posterior confidence intervals are well calibrated in all considered cases that exhibit global convergence---in the sense that they globally contract at the same rate as the truncation error.

pn

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


Real-time Perception meets Reactive Motion Generation
Real-time Perception meets Reactive Motion Generation

(Best Systems Paper Finalists - Amazon Robotics Best Paper Awards in Manipulation)

Kappler, D., Meier, F., Issac, J., Mainprice, J., Garcia Cifuentes, C., Wüthrich, M., Berenz, V., Schaal, S., Ratliff, N., Bohg, J.

IEEE Robotics and Automation Letters, 3(3):1864-1871, July 2018 (article)

Abstract
We address the challenging problem of robotic grasping and manipulation in the presence of uncertainty. This uncertainty is due to noisy sensing, inaccurate models and hard-to-predict environment dynamics. Our approach emphasizes the importance of continuous, real-time perception and its tight integration with reactive motion generation methods. We present a fully integrated system where real-time object and robot tracking as well as ambient world modeling provides the necessary input to feedback controllers and continuous motion optimizers. Specifically, they provide attractive and repulsive potentials based on which the controllers and motion optimizer can online compute movement policies at different time intervals. We extensively evaluate the proposed system on a real robotic platform in four scenarios that exhibit either challenging workspace geometry or a dynamic environment. We compare the proposed integrated system with a more traditional sense-plan-act approach that is still widely used. In 333 experiments, we show the robustness and accuracy of the proposed system.

am

arxiv video video link (url) DOI Project Page [BibTex]


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Distributed Event-Based State Estimation for Networked Systems: An LMI Approach

Muehlebach, M., Trimpe, S.

IEEE Transactions on Automatic Control, 63(1):269-276, January 2018 (article)

am ics

arXiv (extended version) DOI Project Page [BibTex]

arXiv (extended version) DOI Project Page [BibTex]


{Direct observation of Zhang-Li torque expansion of magnetic droplet solitons}
Direct observation of Zhang-Li torque expansion of magnetic droplet solitons

Chung, S., Tuan Le, Q., Ahlberg, M., Awad, A. A., Weigand, M., Bykova, I., Khymyn, R., Dvornik, M., Mazraati, H., Houshang, A., Jiang, S., Nguyen, T. N. A., Goering, E., Schütz, G., Gräfe, J., \AAkerman, J.

{Physical Review Letters}, 120(21), American Physical Society, Woodbury, N.Y., 2018 (article)

Abstract
Magnetic droplets are nontopological dynamical solitons that can be nucleated in nanocontact based spin torque nano-oscillators (STNOs) with perpendicular magnetic anisotropy free layers. While theory predicts that the droplet should be of the same size as the nanocontact, its inherent drift instability has thwarted attempts at observing it directly using microscopy techniques. Here, we demonstrate highly stable magnetic droplets in all-perpendicular STNOs and present the first detailed droplet images using scanning transmission X-ray microscopy. In contrast to theoretical predictions, we find that the droplet diameter is about twice as large as the nanocontact. By extending the original droplet theory to properly account for the lateral current spread underneath the nanocontact, we show that the large discrepancy primarily arises from current-in-plane Zhang-Li torque adding an outward pressure on the droplet perimeter. Electrical measurements on droplets nucleated using a reversed current in the antiparallel state corroborate this picture.

mms

DOI [BibTex]

DOI [BibTex]


{Transmission x-ray microscopy at low temperatures: Irregular supercurrent flow at small length scales}
Transmission x-ray microscopy at low temperatures: Irregular supercurrent flow at small length scales

Simmendinger, J., Ruoss, S., Stahl, C., Weigand, M., Gräfe, J., Schütz, G., Albrecht, J.

{Physical Review B}, 97(13), American Physical Society, Woodbury, NY, 2018 (article)

Abstract
Scanning transmission x-ray microscopy has been used to image electric currents in superconducting films at temperatures down to 20 K. We detect significant deviations from a regular current path driven by macroscopic geometrical constraints. The magnetic stray field of supercurrents in a thin YBaCuO film is mapped into a soft-magnetic coating of permalloy. The so-created local magnetization of the ferromagnetic film can be detected by dichroic absorption of polarized x rays. To enable high-quality measurements in transmission geometry, the whole heterostructure of ferromagnet, superconductor, and single-crystalline substrate has been thinned to an overall thickness of less than 1 µm. With this technique, local supercurrents can be analyzed in a wide range of temperatures and magnetic fields. The less than 100 nm spatial resolution of the magnetic signal together with simultaneously obtained nanostructural data allow the correlation of local supercurrents with the micro- and nanostructure of the superconducting film.

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DOI [BibTex]

DOI [BibTex]


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Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences

Kanagawa, M., Hennig, P., Sejdinovic, D., Sriperumbudur, B. K.

Arxiv e-prints, arXiv:1805.08845v1 [stat.ML], 2018 (article)

Abstract
This paper is an attempt to bridge the conceptual gaps between researchers working on the two widely used approaches based on positive definite kernels: Bayesian learning or inference using Gaussian processes on the one side, and frequentist kernel methods based on reproducing kernel Hilbert spaces on the other. It is widely known in machine learning that these two formalisms are closely related; for instance, the estimator of kernel ridge regression is identical to the posterior mean of Gaussian process regression. However, they have been studied and developed almost independently by two essentially separate communities, and this makes it difficult to seamlessly transfer results between them. Our aim is to overcome this potential difficulty. To this end, we review several old and new results and concepts from either side, and juxtapose algorithmic quantities from each framework to highlight close similarities. We also provide discussions on subtle philosophical and theoretical differences between the two approaches.

pn ei

arXiv [BibTex]

arXiv [BibTex]


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Counterfactual Mean Embedding: A Kernel Method for Nonparametric Causal Inference

Muandet, K., Kanagawa, M., Saengkyongam, S., Marukata, S.

Arxiv e-prints, arXiv:1805.08845v1 [stat.ML], 2018 (article)

Abstract
This paper introduces a novel Hilbert space representation of a counterfactual distribution---called counterfactual mean embedding (CME)---with applications in nonparametric causal inference. Counterfactual prediction has become an ubiquitous tool in machine learning applications, such as online advertisement, recommendation systems, and medical diagnosis, whose performance relies on certain interventions. To infer the outcomes of such interventions, we propose to embed the associated counterfactual distribution into a reproducing kernel Hilbert space (RKHS) endowed with a positive definite kernel. Under appropriate assumptions, the CME allows us to perform causal inference over the entire landscape of the counterfactual distribution. The CME can be estimated consistently from observational data without requiring any parametric assumption about the underlying distributions. We also derive a rate of convergence which depends on the smoothness of the conditional mean and the Radon-Nikodym derivative of the underlying marginal distributions. Our framework can deal with not only real-valued outcome, but potentially also more complex and structured outcomes such as images, sequences, and graphs. Lastly, our experimental results on off-policy evaluation tasks demonstrate the advantages of the proposed estimator.

ei pn

arXiv [BibTex]

arXiv [BibTex]


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Model-based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models

Nishiyama, Y., Kanagawa, M., Gretton, A., Fukumizu, K.

Arxiv e-prints, arXiv:1409.5178v2 [stat.ML], 2018 (article)

Abstract
Kernel Bayesian inference is a powerful nonparametric approach to performing Bayesian inference in reproducing kernel Hilbert spaces or feature spaces. In this approach, kernel means are estimated instead of probability distributions, and these estimates can be used for subsequent probabilistic operations (as for inference in graphical models) or in computing the expectations of smooth functions, for instance. Various algorithms for kernel Bayesian inference have been obtained by combining basic rules such as the kernel sum rule (KSR), kernel chain rule, kernel product rule and kernel Bayes' rule. However, the current framework only deals with fully nonparametric inference (i.e., all conditional relations are learned nonparametrically), and it does not allow for flexible combinations of nonparametric and parametric inference, which are practically important. Our contribution is in providing a novel technique to realize such combinations. We introduce a new KSR referred to as the model-based KSR (Mb-KSR), which employs the sum rule in feature spaces under a parametric setting. Incorporating the Mb-KSR into existing kernel Bayesian framework provides a richer framework for hybrid (nonparametric and parametric) kernel Bayesian inference. As a practical application, we propose a novel filtering algorithm for state space models based on the Mb-KSR, which combines the nonparametric learning of an observation process using kernel mean embedding and the additive Gaussian noise model for a state transition process. While we focus on additive Gaussian noise models in this study, the idea can be extended to other noise models, such as the Cauchy and alpha-stable noise models.

pn

arXiv [BibTex]

arXiv [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]


A probabilistic model for the numerical solution of initial value problems
A probabilistic model for the numerical solution of initial value problems

Schober, M., Särkkä, S., Philipp Hennig,

Statistics and Computing, Springer US, 2018 (article)

Abstract
We study connections between ordinary differential equation (ODE) solvers and probabilistic regression methods in statistics. We provide a new view of probabilistic ODE solvers as active inference agents operating on stochastic differential equation models that estimate the unknown initial value problem (IVP) solution from approximate observations of the solution derivative, as provided by the ODE dynamics. Adding to this picture, we show that several multistep methods of Nordsieck form can be recast as Kalman filtering on q-times integrated Wiener processes. Doing so provides a family of IVP solvers that return a Gaussian posterior measure, rather than a point estimate. We show that some such methods have low computational overhead, nontrivial convergence order, and that the posterior has a calibrated concentration rate. Additionally, we suggest a step size adaptation algorithm which completes the proposed method to a practically useful implementation, which we experimentally evaluate using a representative set of standard codes in the DETEST benchmark set.

pn

PDF Code DOI Project Page [BibTex]


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Incorporation of Terbium into a Microalga Leads to Magnetotactic Swimmers

Santomauro, G., Singh, A., Park, B. W., Mohammadrahimi, M., Erkoc, P., Goering, E., Schütz, G., Sitti, M., Bill, J.

Advanced Biosystems, 2(12):1800039, 2018 (article)

mms pi

[BibTex]

[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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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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3D nanoprinted plastic kinoform x-ray optics

Sanli, U. T., Ceylan, H., Bykova, I., Weigand, M., Sitti, M., Schütz, G., Keskinbora, K.

{Advanced Materials}, 30(36), Wiley-VCH, Weinheim, 2018 (article)

mms pi

DOI [BibTex]

DOI [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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Thick permalloy films for the imaging of spin texture dynamics in perpendicularly magnetized systems

Finizio, S., Wintz, S., Bracher, D., Kirk, E., Semisalova, A. S., Förster, J., Zeissler, K., We\ssels, T., Weigand, M., Lenz, K., Kleibert, A., Raabe, J.

{Physical Review B}, 98(10), American Physical Society, Woodbury, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Dynamic Janus metasurfaces in the visible spectral region

Yu, P., Li, J., Zhang, S., Jin, Z., Schütz, G., Qiu, C., Hirscher, M., Liu, N.

{Nano Letters}, 18(7):4584-4589, American Chemical Society, Washington, DC, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Review of ultrafast demagnetization after femtosecond laser pulses: A complex interaction of light with quantum matter

Fähnle, M., Haag, M., Illg, C., Müller, B. Y., Weng, W., Tsatsoulis, T., Huang, H., Briones Paz, J. Z., Teeny, N., Zhang, L., Kuhn, T.

{American Journal of Modern Physics}, 7(2):68-74, Science Publishing Group, New York, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Current-induced skyrmion generation through morphological thermal transitions in chiral ferromagnetic heterostructures

Lemesh, I., Litzius, K., Böttcher, M., Bassirian, P., Kerber, N., Heinze, D., Zázvorka, J., Büttner, F., Caretta, L., Mann, M., Weigand, M., Finizio, S., Raabe, J., Im, M., Stoll, H., Schütz, G., Dupé, B., Kläui, M., Beach, G. S. D.

{Advanced Materials}, 30(49), Wiley-VCH, Weinheim, 2018 (article)

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DOI [BibTex]

DOI [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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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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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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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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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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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]

2012


Entropy Search for Information-Efficient Global Optimization
Entropy Search for Information-Efficient Global Optimization

Hennig, P., Schuler, C.

Journal of Machine Learning Research, 13, pages: 1809-1837, -, June 2012 (article)

Abstract
Contemporary global optimization algorithms are based on local measures of utility, rather than a probability measure over location and value of the optimum. They thus attempt to collect low function values, not to learn about the optimum. The reason for the absence of probabilistic global optimizers is that the corresponding inference problem is intractable in several ways. This paper develops desiderata for probabilistic optimization algorithms, then presents a concrete algorithm which addresses each of the computational intractabilities with a sequence of approximations and explicitly adresses the decision problem of maximizing information gain from each evaluation.

ei pn

PDF Web Project Page [BibTex]

2012


PDF Web Project Page [BibTex]


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From Dynamic Movement Primitives to Associative Skill Memories

Pastor, P., Kalakrishnan, M., Meier, F., Stulp, F., Buchli, J., Theodorou, E., Schaal, S.

Robotics and Autonomous Systems, 2012 (article)

am

Project Page [BibTex]

Project Page [BibTex]


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Vortex dynamics in nonparabolic potentials

Langner, H. H., Kamionka, T., Martens, M., Weigand, M., Adolff, C. F., Merkt, U., Meier, G.

{Physical Review B}, 85(17), 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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Micromagnetic simulations on GPU, a case study: Vortex core switcing by high-frequency magnetic fields

Van de Wiele, B, Vansteenkiste, A., Kammerer, M., Van Waeyenberge, B., Dupré, L., De Zutter, D.

{IEEE Transactions on Magnetics}, 48(6):2068-2072, 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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On the energetics of transversal and longitudinal fluctuations of atomic magnetic moments

Dietermann, F., Sandratskii, L. M., Fähnle, M.

{Journal of Magnetism and Magnetic Materials}, 324(18):2693-2695, 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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Gradual softening of Al-Zn alloys during high-pressure torsion

Mazilkin, A. A., Straumal, B. B., Borodachenkova, M. V., Valiev, R. Z., Kogtenkova, O. A., Baretzky, B.

{Materials Letters}, 84, pages: 63-65, North-Holland, Amsterdam, 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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Direct imaging of phase relation in a pair of coupled vortex oscillators

Vogel, A., Drews, A., Weigand, M., Meier, G.

{AIP Advances}, 2, 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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Accurate dosimetry in scanning transmission X-ray microscopes via the cross-linking threshold dose of poly(methyl methacrylate)

Leontowich, A. F. G., Hitchcock, A. P., Tyliszczak, T., Weigand, M., Wang, J., Karunakaran, C.

{Journal of Synchrotron Radiation}, 19(6):976-987, 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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Biogenic potassium salt particles as seeds for secondary organic aerosal in the amazon

Pöhlker, C., Wiedemann, K. T., Sinha, B., Shiraiwa, M., Gunthe, S. S., Smith, M., Su, H., Artaxo, P., Chen, Q., Cheng, Y., Elbert, W., Gilles, M. K., Kilcoyne, A. L. D., Moffet, R. C., Weigand, M., Martin, S. T., Pöschl, U., Andreae, M. O.

{Science}, 337, pages: 1075-1078, 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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Metal@COFs: Covalent organic frameworks as templates for Pd nanoparticles and hydrogen storage properties of Pd@COF-102 hybrid material

Kalidindi, S. B., Oh, H., Hirscher, M., Esken, D., Wiktor, C., Turner, S., Van Tendeloo, G., Fischer, R. A.

{Chemistry-a European Journal}, 18(35):10848-10856, VCH Verlagsgesellschaft, Weinheim, Germany, 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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Ion beam lithography for direct patterning of high accuracy large area X-ray elements in gold on membranes

Nadzeyka, A., Peto, L., Bauerdick, S., Mayer, M., Keskinbora, K., Grévent, C., Weigand, M., Hirscher, M., Schütz, G.

{Microelectronic Engineering}, 98, pages: 198-201, 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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Micro- and nanoscale fluid flow on chemical channels

Dörfler, Fabian, Rauscher, Markus, Koplik, Joel, Harting, Jens, Dietrich, S.

{Soft Matter}, 8(35):9221-9234, 2012 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Novel characterization of the adsorption sites in large pore Metal-Organic Frameworks: Combination of X-ray powder diffraction and thermal desorption spectroscopy

Soleimani Dorcheh, A., Dinnebier, R. E., Kuc, A., Magdysyuk, O., Adams, F., Denysenko, D., Heine, T., Volkmer, D., Donner, W., Hirscher, M.

{Physical Chemistry Chemical Physics}, 14(37):12892-12897, 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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Tunnel contacts for spin injection into silicon: The Si-Co interface with and without a MgO tunnel barrier - A study by high-resolution Rutherford backscattering

Dash, S. P., Goll, D., Kopold, P., Carstanjen, H. D.

{Advances in Materials Science and Engineering}, 2012, 2012 (article)

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DOI [BibTex]

DOI [BibTex]