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2018


Deep Reinforcement Learning for Event-Triggered Control
Deep Reinforcement Learning for Event-Triggered Control

Baumann, D., Zhu, J., Martius, G., Trimpe, S.

In Proceedings of the 57th IEEE International Conference on Decision and Control (CDC), pages: 943-950, 57th IEEE International Conference on Decision and Control (CDC), December 2018 (inproceedings)

al ics

arXiv PDF DOI Project Page Project Page [BibTex]

2018


arXiv PDF DOI Project Page Project Page [BibTex]


Efficient Encoding of Dynamical Systems through Local Approximations
Efficient Encoding of Dynamical Systems through Local Approximations

Solowjow, F., Mehrjou, A., Schölkopf, B., Trimpe, S.

In Proceedings of the 57th IEEE International Conference on Decision and Control (CDC), pages: 6073 - 6079 , Miami, Fl, USA, December 2018 (inproceedings)

ei ics

arXiv PDF DOI Project Page [BibTex]

arXiv PDF DOI Project Page [BibTex]


Depth Control of Underwater Robots using Sliding Modes and Gaussian Process Regression
Depth Control of Underwater Robots using Sliding Modes and Gaussian Process Regression

Lima, G. S., Bessa, W. M., Trimpe, S.

In Proceeding of the 15th Latin American Robotics Symposium, João Pessoa, Brazil, 15th Latin American Robotics Symposium, November 2018 (inproceedings)

Abstract
The development of accurate control systems for underwater robotic vehicles relies on the adequate compensation for hydrodynamic effects. In this work, a new robust control scheme is presented for remotely operated underwater vehicles. In order to meet both robustness and tracking requirements, sliding mode control is combined with Gaussian process regression. The convergence properties of the closed-loop signals are analytically proven. Numerical results confirm the stronger improved performance of the proposed control scheme.

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[BibTex]

[BibTex]


Gait learning for soft microrobots controlled by light fields
Gait learning for soft microrobots controlled by light fields

Rohr, A. V., Trimpe, S., Marco, A., Fischer, P., Palagi, S.

In International Conference on Intelligent Robots and Systems (IROS) 2018, pages: 6199-6206, International Conference on Intelligent Robots and Systems 2018, October 2018 (inproceedings)

Abstract
Soft microrobots based on photoresponsive materials and controlled by light fields can generate a variety of different gaits. This inherent flexibility can be exploited to maximize their locomotion performance in a given environment and used to adapt them to changing environments. However, because of the lack of accurate locomotion models, and given the intrinsic variability among microrobots, analytical control design is not possible. Common data-driven approaches, on the other hand, require running prohibitive numbers of experiments and lead to very sample-specific results. Here we propose a probabilistic learning approach for light-controlled soft microrobots based on Bayesian Optimization (BO) and Gaussian Processes (GPs). The proposed approach results in a learning scheme that is highly data-efficient, enabling gait optimization with a limited experimental budget, and robust against differences among microrobot samples. These features are obtained by designing the learning scheme through the comparison of different GP priors and BO settings on a semisynthetic data set. The developed learning scheme is validated in microrobot experiments, resulting in a 115% improvement in a microrobot’s locomotion performance with an experimental budget of only 20 tests. These encouraging results lead the way toward self-adaptive microrobotic systems based on lightcontrolled soft microrobots and probabilistic learning control.

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arXiv IEEE Xplore DOI Project Page [BibTex]

arXiv IEEE Xplore DOI Project Page [BibTex]


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Learning-Based Robust Model Predictive Control with State-Dependent Uncertainty

Soloperto, R., Müller, M. A., Trimpe, S., Allgöwer, F.

In Proceedings of the IFAC Conference on Nonlinear Model Predictive Control (NMPC), Madison, Wisconsin, USA, 6th IFAC Conference on Nonlinear Model Predictive Control, August 2018 (inproceedings)

ics

PDF [BibTex]

PDF [BibTex]


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Kernel Recursive ABC: Point Estimation with Intractable Likelihood

Kajihara, T., Kanagawa, M., Yamazaki, K., Fukumizu, K.

Proceedings of the 35th International Conference on Machine Learning, pages: 2405-2414, PMLR, July 2018 (conference)

Abstract
We propose a novel approach to parameter estimation for simulator-based statistical models with intractable likelihood. Our proposed method involves recursive application of kernel ABC and kernel herding to the same observed data. We provide a theoretical explanation regarding why the approach works, showing (for the population setting) that, under a certain assumption, point estimates obtained with this method converge to the true parameter, as recursion proceeds. We have conducted a variety of numerical experiments, including parameter estimation for a real-world pedestrian flow simulator, and show that in most cases our method outperforms existing approaches.

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Paper [BibTex]

Paper [BibTex]


Probabilistic Recurrent State-Space Models
Probabilistic Recurrent State-Space Models

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

In Proceedings of the International Conference on Machine Learning (ICML), International Conference on Machine Learning (ICML), July 2018 (inproceedings)

Abstract
State-space models (SSMs) are a highly expressive model class for learning patterns in time series data and for system identification. Deterministic versions of SSMs (e.g., LSTMs) proved extremely successful in modeling complex time-series data. Fully probabilistic SSMs, however, unfortunately often prove hard to train, even for smaller problems. To overcome this limitation, we propose a scalable initialization and training algorithm based on doubly stochastic variational inference and Gaussian processes. In the variational approximation we propose in contrast to related approaches to fully capture the latent state temporal correlations to allow for robust training.

am ics

arXiv pdf Project Page [BibTex]

arXiv pdf Project Page [BibTex]


Event-triggered Learning for Resource-efficient Networked Control
Event-triggered Learning for Resource-efficient Networked Control

Solowjow, F., Baumann, D., Garcke, J., Trimpe, S.

In Proceedings of the American Control Conference (ACC), pages: 6506 - 6512, American Control Conference, June 2018 (inproceedings)

ics

arXiv PDF DOI Project Page [BibTex]

arXiv PDF DOI Project Page [BibTex]


Evaluating Low-Power Wireless Cyber-Physical Systems
Evaluating Low-Power Wireless Cyber-Physical Systems

Baumann, D., Mager, F., Singh, H., Zimmerling, M., Trimpe, S.

In Proceedings of the IEEE Workshop on Benchmarking Cyber-Physical Networks and Systems (CPSBench), pages: 13-18, IEEE Workshop on Benchmarking Cyber-Physical Networks and Systems (CPSBench), April 2018 (inproceedings)

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arXiv PDF DOI Project Page [BibTex]

arXiv PDF DOI Project Page [BibTex]


Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients
Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients

Balles, L., Hennig, P.

In Proceedings of the 35th International Conference on Machine Learning (ICML), 2018 (inproceedings) Accepted

Abstract
The ADAM optimizer is exceedingly popular in the deep learning community. Often it works very well, sometimes it doesn't. Why? We interpret ADAM as a combination of two aspects: for each weight, the update direction is determined by the sign of stochastic gradients, whereas the update magnitude is determined by an estimate of their relative variance. We disentangle these two aspects and analyze them in isolation, gaining insight into the mechanisms underlying ADAM. This analysis also extends recent results on adverse effects of ADAM on generalization, isolating the sign aspect as the problematic one. Transferring the variance adaptation to SGD gives rise to a novel method, completing the practitioner's toolbox for problems where ADAM fails.

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link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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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]

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)

mms

DOI [BibTex]

DOI [BibTex]

2015


Automatic LQR Tuning Based on Gaussian Process Optimization: Early Experimental Results
Automatic LQR Tuning Based on Gaussian Process Optimization: Early Experimental Results

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

Machine Learning in Planning and Control of Robot Motion Workshop at the IEEE/RSJ International Conference on Intelligent Robots and Systems (iROS), pages: , , Machine Learning in Planning and Control of Robot Motion Workshop, October 2015 (conference)

Abstract
This paper proposes an automatic controller tuning framework based on linear optimal control combined with Bayesian optimization. With this framework, an initial set of controller gains is automatically improved according to a pre-defined performance objective evaluated from experimental data. The underlying Bayesian optimization algorithm is Entropy Search, which represents the latent objective as a Gaussian process and constructs an explicit belief over the location of the objective minimum. This is used to maximize the information gain from each experimental evaluation. Thus, this framework shall yield improved controllers with fewer evaluations compared to alternative approaches. A seven-degree-of-freedom robot arm balancing an inverted pole is used as the experimental demonstrator. Preliminary results of a low-dimensional tuning problem highlight the method’s potential for automatic controller tuning on robotic platforms.

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PDF DOI Project Page [BibTex]

2015


PDF DOI Project Page [BibTex]


Direct Loss Minimization Inverse Optimal Control
Direct Loss Minimization Inverse Optimal Control

Doerr, A., Ratliff, N., Bohg, J., Toussaint, M., Schaal, S.

In Proceedings of Robotics: Science and Systems, Rome, Italy, Robotics: Science and Systems XI, July 2015 (inproceedings)

Abstract
Inverse Optimal Control (IOC) has strongly impacted the systems engineering process, enabling automated planner tuning through straightforward and intuitive demonstration. The most successful and established applications, though, have been in lower dimensional problems such as navigation planning where exact optimal planning or control is feasible. In higher dimensional systems, such as humanoid robots, research has made substantial progress toward generalizing the ideas to model free or locally optimal settings, but these systems are complicated to the point where demonstration itself can be difficult. Typically, real-world applications are restricted to at best noisy or even partial or incomplete demonstrations that prove cumbersome in existing frameworks. This work derives a very flexible method of IOC based on a form of Structured Prediction known as Direct Loss Minimization. The resulting algorithm is essentially Policy Search on a reward function that rewards similarity to demonstrated behavior (using Covariance Matrix Adaptation (CMA) in our experiments). Our framework blurs the distinction between IOC, other forms of Imitation Learning, and Reinforcement Learning, enabling us to derive simple, versatile, and practical algorithms that blend imitation and reinforcement signals into a unified framework. Our experiments analyze various aspects of its performance and demonstrate its efficacy on conveying preferences for motion shaping and combined reach and grasp quality optimization.

am ics

PDF Video Project Page [BibTex]

PDF Video Project Page [BibTex]


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LMI-Based Synthesis for Distributed Event-Based State Estimation

Muehlebach, M., Trimpe, S.

In Proceedings of the American Control Conference, July 2015 (inproceedings)

Abstract
This paper presents an LMI-based synthesis procedure for distributed event-based state estimation. Multiple agents observe and control a dynamic process by sporadically exchanging data over a broadcast network according to an event-based protocol. In previous work [1], the synthesis of event-based state estimators is based on a centralized design. In that case three different types of communication are required: event-based communication of measurements, periodic reset of all estimates to their joint average, and communication of inputs. The proposed synthesis problem eliminates the communication of inputs as well as the periodic resets (under favorable circumstances) by accounting explicitly for the distributed structure of the control system.

am ics

PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


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Guaranteed H2 Performance in Distributed Event-Based State Estimation

Muehlebach, M., Trimpe, S.

In Proceeding of the First International Conference on Event-based Control, Communication, and Signal Processing, June 2015 (inproceedings)

am ics

PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


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On the Choice of the Event Trigger in Event-based Estimation

Trimpe, S., Campi, M.

In Proceeding of the First International Conference on Event-based Control, Communication, and Signal Processing, June 2015 (inproceedings)

am ics

PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


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Event-based Estimation and Control for Remote Robot Operation with Reduced Communication

Trimpe, S., Buchli, J.

In Proceedings of the IEEE International Conference on Robotics and Automation, May 2015 (inproceedings)

Abstract
An event-based communication framework for remote operation of a robot via a bandwidth-limited network is proposed. The robot sends state and environment estimation data to the operator, and the operator transmits updated control commands or policies to the robot. Event-based communication protocols are designed to ensure that data is transmitted only when required: the robot sends new estimation data only if this yields a significant information gain at the operator, and the operator transmits an updated control policy only if this comes with a significant improvement in control performance. The developed framework is modular and can be used with any standard estimation and control algorithms. Simulation results of a robotic arm highlight its potential for an efficient use of limited communication resources, for example, in disaster response scenarios such as the DARPA Robotics Challenge.

am ics

PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


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Inference of Cause and Effect with Unsupervised Inverse Regression

Sgouritsa, E., Janzing, D., Hennig, P., Schölkopf, B.

In Proceedings of the 18th International Conference on Artificial Intelligence and Statistics, 38, pages: 847-855, JMLR Workshop and Conference Proceedings, (Editors: Lebanon, G. and Vishwanathan, S.V.N.), JMLR.org, AISTATS, 2015 (inproceedings)

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Web PDF [BibTex]

Web PDF [BibTex]


Probabilistic Line Searches for Stochastic Optimization
Probabilistic Line Searches for Stochastic Optimization

Mahsereci, M., Hennig, P.

In Advances in Neural Information Processing Systems 28, pages: 181-189, (Editors: C. Cortes, N.D. Lawrence, D.D. Lee, M. Sugiyama and R. Garnett), Curran Associates, Inc., 29th Annual Conference on Neural Information Processing Systems (NIPS), 2015 (inproceedings)

Abstract
In deterministic optimization, line searches are a standard tool ensuring stability and efficiency. Where only stochastic gradients are available, no direct equivalent has so far been formulated, because uncertain gradients do not allow for a strict sequence of decisions collapsing the search space. We construct a probabilistic line search by combining the structure of existing deterministic methods with notions from Bayesian optimization. Our method retains a Gaussian process surrogate of the univariate optimization objective, and uses a probabilistic belief over the Wolfe conditions to monitor the descent. The algorithm has very low computational cost, and no user-controlled parameters. Experiments show that it effectively removes the need to define a learning rate for stochastic gradient descent. [You can find the matlab research code under `attachments' below. The zip-file contains a minimal working example. The docstring in probLineSearch.m contains additional information. A more polished implementation in C++ will be published here at a later point. For comments and questions about the code please write to mmahsereci@tue.mpg.de.]

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Matlab research code link (url) [BibTex]

Matlab research code link (url) [BibTex]


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A Random Riemannian Metric for Probabilistic Shortest-Path Tractography

Hauberg, S., Schober, M., Liptrot, M., Hennig, P., Feragen, A.

In 18th International Conference on Medical Image Computing and Computer Assisted Intervention, 9349, pages: 597-604, Lecture Notes in Computer Science, MICCAI, 2015 (inproceedings)

ei pn

PDF DOI [BibTex]

PDF DOI [BibTex]


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A New Perspective and Extension of the Gaussian Filter

Wüthrich, M., Trimpe, S., Kappler, D., Schaal, S.

In Robotics: Science and Systems, 2015 (inproceedings)

Abstract
The Gaussian Filter (GF) is one of the most widely used filtering algorithms; instances are the Extended Kalman Filter, the Unscented Kalman Filter and the Divided Difference Filter. GFs represent the belief of the current state by a Gaussian with the mean being an affine function of the measurement. We show that this representation can be too restrictive to accurately capture the dependencies in systems with nonlinear observation models, and we investigate how the GF can be generalized to alleviate this problem. To this end we view the GF from a variational-inference perspective, and analyze how restrictions on the form of the belief can be relaxed while maintaining simplicity and efficiency. This analysis provides a basis for generalizations of the GF. We propose one such generalization which coincides with a GF using a virtual measurement, obtained by applying a nonlinear function to the actual measurement. Numerical experiments show that the proposed Feature Gaussian Filter (FGF) can have a substantial performance advantage over the standard GF for systems with nonlinear observation models.

am ics

Web PDF Project Page [BibTex]


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Combined FORC and x-ray microscopy study of magnetisation reversal in antidot lattices

Gräfe, J., Haering, F., Stahl, C., Weigand, M., Skripnik, M., Nowak, U., Ziemann, P., Wiedwald, U., Schütz, G., Goering, E.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

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DOI Project Page Project Page [BibTex]

DOI Project Page Project Page [BibTex]


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Local control of domain wall dynamics in ferromagnetic rings

Richter, K., Mawass, M., Krone, A., Krüger, B., Weigand, M., Stoll, H., Schütz, G., Kläui, M.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Ultrafast demagnetization after laser pulse irradiation in Ni: Ab-initio electron-phonon scattering and phase space calculations

Illg, C., Haag, M., Fähnle, M.

In Ultrafast Magnetism I. Proceedings of the International Conference UMC 2013, 159, pages: 131-133, Springer Proceedings in Physics, Springer, Strasbourg, 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Automotive domain wall propagation in ferromagnetic rings

Richter, K., Mawass, M., Krone, A., Krüger, B., Weigand, M., Schütz, G., Stoll, H., Kläui, M.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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The third dimension: Vortex core reversal by interaction with \textquotesingleflexure modes’

Noske, M., Stoll, H., Fähnle, M., Weigand, M., Dieterle, G., Förster, J., Gangwar, A., Slavin, A., Back, C. H., Schütz, G.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Skyrmions at room temperature in magnetic multilayers

Moreau-Luchaire, C., Reyren, N., Moutafis, C., Sampaio, J., Van Horne, N., Vaz, C. A., Warnicke, P., Garcia, K., Weigand, M., Bouzehouane, K., Deranlot, C., George, J., Raabe, J., Cros, V., Fert, A.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]

2007


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2001


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Computational micromagnetism of magnetic structures and magnetization processes in thin plantelets and small particles

Kronmüller, H., Hertel, R.

In Magnetic Storage Sstems Beyond 2000, 41, pages: 345-362, Nato Science Series II: Mathematics, Physics and Chemistry, Kluwer Academic Publishers, Rhodos, Greece, 2001 (inproceedings)

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[BibTex]

2001


[BibTex]


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Hydrogen storage in mechanically treated single wall carbon nanotrubes

Haluska, M., Hulman, M., Hirscher, M., Becher, M., Roth, S., Stepanek, I., Bernier, P.

In Electronic Properties of Molecular Nanostructures: XV International Winterschool/Euroconference, 591, pages: 603-608, American Institute of Physics Conference Proceedings, AIP, Kirchberg [Austria], 2001 (inproceedings)

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[BibTex]

[BibTex]


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Isotopic mass and lattice constant of Si and Ge: X-Ray standing wave measurements

Zegenhagen, J., Kazimirov, A., Cao, L. X., Konuma, M., Sozontov, E., Plachke, D., Carstanjen, H. D., Bilger, G., Haller, E., Kohn, V., Cardona, M.

In Proceedings of the 25th Conference on the Physics of Semiconductors, 87, pages: 125-127, Springer proceedings in physics, Springer, Osaka, Japan, 2001 (inproceedings)

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[BibTex]

[BibTex]


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Positron Annihilation Studies on Stable and Undercooled Metal Melts at the Stuttgart Pelletron

Stoll, H., Siegle, A., Major, J.

In Application of Accelerators in Research and Industry, 576, pages: 749-752, AIP Conference Proceedings, Denton, Texas, USA, 2001 (inproceedings)

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[BibTex]

[BibTex]


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Submicrometer spatially resolved measurements of mechanical properties and correlation to microstructure and composition

Kunert, M., Baretzky, B., Baker, S. P., Mittemeijer, E. J.

In Fundamentals of Nanoindentation and Nanotribology II, 649, pages: Q3.2.1-Q3.2.6, Materials Research Society Symposium Proceedings, MRS, Boston, MA, USA, 2001 (inproceedings)

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[BibTex]

[BibTex]


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The six-jump diffusion cycles in B2-compounds

Drautz, R., Meyer, B., Fähnle, M.

In Proceedings of DIMAT 2000, the Fifth International Conference on Diffusion in Materials, pages: 417-422, Defect and Diffusion Forum, Scitec Publications Ltd., Paris, France, 2001 (inproceedings)

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[BibTex]

[BibTex]


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Ionic nitriding of austenitic and ferritic steel with the aid of a high aperture hall current accelerator

Straumal, B. B., Vershinin, N. F., Friesel, M., Ishenko, S. A., Gust, W.

In Diffusion in Materials DIMAT2000, 194, pages: 1457-1462, Defect and Diffusion Forum, Trans Tech, Paris, France, 2001 (inproceedings)

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[BibTex]

[BibTex]


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First proof of slow trapping of positronium in polymers by an Age-Momentum-Correlation (AMOC) experiment

Dauwe, C., Balcaen, N., van Waeyenberge, B., van Petegem, S., Stoll, H.

In Positron Annihilation. Proceedings of the 12th International Conference on Positron Annihilation, 363/365, pages: 254-256, Materials Science Forum, Trans Tech Publications Ltd., München, 2001 (inproceedings)

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[BibTex]

[BibTex]


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Positron-age-momentum correlation

Stoll, H., Bandzuch, P., Siegle, A.

In Positron Annihilation: Proceedings of the 12th International Conference on Positron Annihilation, 363-365, pages: 547-551, Materials Science Forum, Trans Tech Publications Ltd., München, 2001 (inproceedings)

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[BibTex]

[BibTex]


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Nanocrystalline and nanostructured high-performance permanent magnets

Goll, D., Hadjipanayis, G. C., Kronmüller, H.

In Applications of Ferromagnetic and Optical Materials, Storage and Magnetoelectronics, 674, pages: U2.4.1-U2.4.12, Materials Research Society Symposium Proceedings, MRS, San Francisco, Calif., 2001 (inproceedings)

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[BibTex]

[BibTex]


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Ion beam analysis with monolayer depth resolution using the electrostatic spectrometer at the MPI Stuttgart

Plachke, D., Blohm, G., Fischer, T., Khellaf, A., Kruse, O., Stoll, H., Carstanjen, H. D.

In Proceedings of the 16th International Conference on Applications of Accelerators in Research and Industry, 576, pages: 458-462, American Institute of Physics Conference Proceedings, AIP, Denton, Texas, 2001 (inproceedings)

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[BibTex]

[BibTex]


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From the electronic structure to the macroscopiy behavior: A multi-scale analysis of plasticity in intermetallic compounds

Fähnle, M., Kohlhammer, S., Bester, G.

In Influences of Interface and Dislocation Behavior on Microstructure Evolution, 652, pages: Y4.5.1.-Y4.5.12, Materials Research Society Symposium Proceedings, MRS, Boston, Mass., USA, 2001 (inproceedings)

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[BibTex]

[BibTex]


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Influence of the microstructure on the magnetic properties of giant-magnetostrictive TbDyFe films

Hirscher, M., Winzek, B., Fischer, S. F., Kronmüller, H.

In Smart Materials. Proceedings of the 1st Caesarium, pages: 23-37, Springer, Bonn, 2001 (inproceedings)

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[BibTex]

[BibTex]


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Materials analysis with monolayer depth resolution using MeV ion beams

Carstanjen, H. D.

In 117, Las Vegas, USA, 2001 (inproceedings)

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[BibTex]

[BibTex]


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Flux-line pinning in low-angle grain boundaries.

Albrecht, J., Leonhardt, S., Kronmüller, H.

In Proceedings 10th International Workshop on Critical Currents (IWCC 2001), pages: 41-43, Göttingen, Germany, 2001 (inproceedings)

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[BibTex]

[BibTex]


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Measurement of the low-temperature self-diffusivity of lithium by elastic recoil detection analysis

Wieland, O., Carstanjen, H. D.

In Proceedings of DIMAT 2000, the Fifth International Conference on Diffusion in Materials, 194/199, pages: 35-41, Defect and Diffusion Forum, Scitec Publications Ltd., Paris, France, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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From the electronic structure to the macroscopic behaviour: a multi-scale analysis of plasticity in intermetallic compounds

Fähnle, M., Kohlhammer, S., Bester, G.

In Influences of Interface and Dislocation Behavior on Microstructure Evolution, 652, pages: Y.4.5.1-Y.4.5.12, Materials Research Society Symposium Proceedings, MRS, Boston, Mass., 2001 (inproceedings)

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[BibTex]

[BibTex]


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Enhancement of the critical current density of YBa2Cu3O7-8-films by substracte irradiation

Leonhardt, S., Albrecht, J., Warthmann, R., Kronmüller, H.

In High-Tc Superconductors and Related Applications: Materials Science, Fundamental Properties, and Some Future Electronic Applications. Proceedings of the NATO Advanced Study Institute, 86, pages: 529-534, NATO Science Series 3. High Technology, Kluwer Academic Publishers, Albena, Bulgaria, 2001 (inproceedings)

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[BibTex]

[BibTex]


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AMOC studies of positronium in fine MgO powder

van Waeyenberge, B., Dauwe, C., Stoll, H.

In Positron Annihilation. Proceedings of the 12th International Conference on Positron Annihilation, 363/365, pages: 401-403, Materials Science Forum, Trans Tech Publications Ltd., München, 2001 (inproceedings)

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[BibTex]

[BibTex]


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Atomic defects and electronic structure of B2-FeAl, CoAl and NiAl

Fähnle, M., Meyer, B., Bester, G., Majer, J., Börnsen, N.

In Proceedings of DIMAT 2000, the Fifth International Conference on Diffusion in Materials, 194/199, pages: 279-285, Defect and Diffusion Forum, Scitec Publications Ltd., Paris, France, 2001 (inproceedings)

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[BibTex]

[BibTex]