Kirchhoff Institute for Physics

Heidelberg, Germany

Kirchhoff Institute for Physics

Heidelberg, Germany
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Cataldo S.,University of Stuttgart | Zhao J.,University of Stuttgart | Neubrech F.,Kirchhoff Institute for Physics | Frank B.,University of Stuttgart | And 3 more authors.
ACS Nano | Year: 2012

Figure Persented: We use low-cost hole-mask colloidal nanolithography to manufacture large-area resonant split-ring metamaterials and measure their infrared optical properties. This novel substrate is employed for antenna-assisted surface-enhanced infrared absorption measurements using octadecanethiol (ODT) and deuterated ODT, which demonstrates easy adjustability of our material to vibrational modes. Our method has the potential to make resonant plasmon-enhanced infrared spectroscopy a standard lab tool in biology, pharmacology, and medicine. © 2011 American Chemical Society.


Petrich W.,Kirchhoff Institute for Physics
Faraday Discussions | Year: 2016

The Faraday Discussion meeting "Advanced Vibrational Spectroscopy for Biomedical Applications" provided an excellent opportunity to share and discuss recent research and applications on a highly interdisciplinary level. Spectral pathology, single cell analysis, data handling, clinical spectroscopy, and the spectral analysis of biofluids were among the topics covered during the meeting. The focus on discussion rather than "merely" presentation was highly appreciated and fruitful discussions evolved around the interpretation of the amide-bands, optical resolution, the role of diffraction and data analysis procedure, to name a few. The meeting made clear that the spectroscopy of molecular vibrations in biomolecules has evolved from a purely academic research tool to a technology used in clinical practice in some cases. In this sense, biomedical vibrational spectroscopy has reached a pivotal point at which questions like diagnostic value, therapeutic consequence and financial viability are gaining more and more importance. © 2016 The Royal Society of Chemistry.


Scelle R.,Kirchhoff Institute for Physics | Rentrop T.,Kirchhoff Institute for Physics | Trautmann A.,Kirchhoff Institute for Physics | Schuster T.,Kirchhoff Institute for Physics | Oberthaler M.K.,Kirchhoff Institute for Physics
Physical Review Letters | Year: 2013

We prepare a superposition of two motional states by addressing lithium atoms immersed in a Bose-Einstein condensate of sodium with a species-selective potential. The evolution of the superposition state is characterized by the populations of the constituent states as well as their coherence. The latter we extract employing a novel scheme analogous to the spin-echo technique. Comparing the results directly to measurements on freely evolving fermions allows us to isolate the decoherence effects induced by the bath. In our system, the decoherence time is close to the maximal possible value since the decoherence is dominated by population relaxation processes. The measured data are in good agreement with a theoretical model based on Fermi's golden rule. © 2013 American Physical Society.


Muller P.,Kirchhoff Institute for Physics
International journal of molecular sciences | Year: 2010

With the completeness of genome databases, it has become possible to develop a novel FISH (Fluorescence in Situ Hybridization) technique called COMBO-FISH (COMBinatorial Oligo FISH). In contrast to other FISH techniques, COMBO-FISH makes use of a bioinformatics approach for probe set design. By means of computer genome database searching, several oligonucleotide stretches of typical lengths of 15-30 nucleotides are selected in such a way that all uniquely colocalize at the given genome target. The probes applied here were Peptide Nucleic Acids (PNAs)-synthetic DNA analogues with a neutral backbone-which were synthesized under high purity conditions. For a probe repetitively highlighted in centromere 9, PNAs labeled with different dyes were tested, among which Alexa 488(®) showed reversible photobleaching (blinking between dark and bright state) a prerequisite for the application of SPDM (Spectral Precision Distance/Position Determination Microscopy) a novel technique of high resolution fluorescence localization microscopy. Although COMBO-FISH labeled cell nuclei under SPDM conditions sometimes revealed fluorescent background, the specific locus was clearly discriminated by the signal intensity and the resulting localization accuracy in the range of 10-20 nm for a detected oligonucleotide stretch. The results indicate that COMBO-FISH probes with blinking dyes are well suited for SPDM, which will open new perspectives on molecular nanostructural analysis of the genome.


Steinbeck T.M.,Kirchhoff Institute for Physics
Journal of Physics: Conference Series | Year: 2010

For the ALICE heavy-ion experiment a large computing cluster will be used to perform the last triggering stages in the High Level Trigger (HLT). For the first year of operation the cluster consisted of about 100 multi-processing nodes with 4 or 8 CPU cores each, to be increased to more than 1000 nodes for the coming years of operation. During the commissioning phases of the detector, the preparations for first LHC beam, as well as during the periods of first LHC beam, the HLT has been used extensively already to reconstruct, compress, and display data from the different detectors. For example the HLT has been used to compress Silicon Drift Detector (SDD) data by a factor of 15, lossless, on the fly at a rate of more than 800 Hz. For ALICE's Time Projection Chamber (TPC) detector the HLT has been used to reconstruct tracks online and show the reconstructed tracks in an online event display. The event display can also display online reconstructed data from the Dimuon and Photon Spectrometer (PHOS) detectors. For the latter detector a first selection mechanism has also been put into place to select only events for forwarding to the online display in which data has passed through the PHOS detector. In this contribution we will present experiences and results from these commissioning phases. © 2010 IOP Publishing Ltd.


Bochterle J.,Kirchhoff Institute for Physics | Neubrech F.,Kirchhoff Institute for Physics | Nagao T.,Japan National Institute of Materials Science | Pucci A.,Kirchhoff Institute for Physics
ACS Nano | Year: 2012

The resonantly enhanced near-field of micrometer-sized gold antennas has been probed with Angstrom-scale resolution. In situ surface-enhanced infrared spectroscopic vibrational signals of carbon monoxide (CO) layers cold-condensed on the antennas in ultrahigh-vacuum conditions are compared to the signals of CO layers with corresponding thicknesses on a flat gold surface. Vibrational signals of CO as well as the shift of the plasmonic resonance frequency were used to analyze the distance dependence of the near-field. The signal enhancement induced by the antennas not only decays monotonically from the surface but, in contrast to classical near-field models, shows a maximum between 10 and 15 Å and decays also toward the surface of the antenna. This effect is attributed to the spill-out of the electron wave function, as expected from quantum mechanical calculations. © 2012 American Chemical Society.


Zakharova G.S.,Kirchhoff Institute for Physics
Russian Journal of Inorganic Chemistry | Year: 2014

Anatase titanium dioxide nanotubes were prepared by hydrothermal synthesis with subsequent annealing in a nitrogen atmosphere. The outer diameter of particles is 10-15 nm, their inner diameter is 4-6 nm, and their length is several hundreds of nanometers. The structural transformation of polytitanic acid to TiO2, which preserves the tubular morphology until 500 C, was studied by X-ray powder diffraction and thermal analyses, scanning and transmission electron microscopies, and IR and Raman spectroscopies. © 2014 Pleiades Publishing, Ltd.


Schmitt E.,Kirchhoff Institute for Physics
Methods in molecular biology (Clifton, N.J.) | Year: 2010

With the improvement and completeness of genome databases, it has become possible to develop a novel fluorescence in situ hybridization (FISH) technique called COMBinatorial Oligo FISH (COMBO-FISH). In contrast to other (standard) FISH applications, COMBO-FISH makes use of a bioinformatic approach for probe set design. By means of computer genome database search, oligonucleotide stretches of typical lengths of 15-30 nucleotides are selected in such a way that they all colocalize within a given genome (gene) target. Typically, probe sets of about 20-40 stretches are designed within 50-250 kb, which is enough to get an increased fluorescence signal specifically highlighting the target from the background. Although "specific colocalization" is the only necessary condition for probe selection, i.e. the probes of different lengths can be composed of purines and pyrimidines, we additionally refined the design strategy restricting the probe sets to homopurine or homopyrimidine oligonucleotides so that depending on the probe orientation either double (requiring denaturation of the target double strand) or triple (omitting denaturation of the target strand) strand bonding of the probes is possible. The probes used for the protocols described below are DNA or PNA oligonucleotides, which can be synthesized by established automatized techniques. We describe different protocols that were successfully applied to label gene targets via double- or triple-strand bonding in fixed lymphocyte cell cultures, bone marrow smears, and formalin-fixed, paraffin-wax embedded tissue sections. In addition, we present a procedure of probe microinjection in living cells resulting in specific labeling when microscopically detected after fixation.


News Article | November 11, 2016
Site: phys.org

For observations based on sensory data, the human brain must constantly verify which "version" of reality underlies the perception. The answer is gleaned from probability distributions that are stored in the nerve cell network itself. The neurons are able to detect patterns that reflect acquired knowledge. Applying mathematical methods, physicists from Heidelberg University and researchers from Graz University of Technology have proven this phenomenon in their investigations. The current research results, published in the journal Physical Review E, are of major significance in developing new types of computer systems. One of the most important functions of our brain is to create an internal model of our environment. There are two categories of information available for this purpose – the acquired knowledge about known objects and a constant stream of sensory data that can be compared against and continually added to existing knowledge. These sensory data are the simplest, "directly" available building blocks of perception. However, observations that are based on sensory data are often compatible with multiple "realities" at the same time, as the phenomenon of optical illusions clearly proves. The brain is therefore faced with the challenge of knowing all the possible versions of the underlying reality. To make this determination, the brain jumps back and forth between these versions of reality, sampling a probability distribution. The researchers working with Heidelberg physicist Prof. Dr Karlheinz Meier studied this process with the help of formal mathematical methods applied at the level of individual nerve cells, called neurons. The model of individual neurons used is strictly deterministic. This means that each repeated stimulation from external stimuli always evokes the same response behaviour. The brain, however, is a network of neurons that communicate with one another. When a nerve cell is sufficiently stimulated by its neighbour, it fires off a short electrical pulse, thereby stimulating other neurons. In a large network of active neurons, nerve cells become stochastic – their "response" is no longer determined, i.e., precisely predictable, but follows statistical probability rules. "In our studies we were able to show that such neurons obtain their response from probability distributions that are stored in the network itself and that are sampled by the nerve cells," explains Prof. Meier. This is how neurons are able to detect patterns that reflect acquired knowledge. The research was conducted as part of the European Human Brain Project, in which the Heidelberg researchers under the direction of Karlheinz Meier are developing new computer systems using the brain as a model. "The concept of statistical sampling of acquired probabilities is extremely well-suited for implementing a new computer architecture. It is one focus of the current research our working group is conducting," states the physicist, who teaches and pursues research at Heidelberg University's Kirchhoff Institute for Physics. Explore further: How synaptic connections in the brain force nerve cells to coordinate their work More information: Mihai A. Petrovici et al. Stochastic inference with spiking neurons in the high-conductance state, Physical Review E (2016). DOI: 10.1103/PhysRevE.94.042312


News Article | November 12, 2016
Site: www.sciencedaily.com

For observations based on sensory data, the human brain must constantly verify which "version" of reality underlies the perception. The answer is gleaned from probability distributions that are stored in the nerve cell network itself. The neurons are able to detect patterns that reflect acquired knowledge. Applying mathematical methods, physicists from Heidelberg University and researchers from Graz University of Technology have proven this phenomenon in their investigations. The current research results, published in the journal Physical Review, are of major significance in developing new types of computer systems. One of the most important functions of our brain is to create an internal model of our environment. There are two categories of information available for this purpose -- the acquired knowledge about known objects and a constant stream of sensory data that can be compared against and continually added to existing knowledge. These sensory data are the simplest, "directly" available building blocks of perception. However, observations that are based on sensory data are often compatible with multiple "realities" at the same time, as the phenomenon of optical illusions clearly proves. The brain is therefore faced with the challenge of knowing all the possible versions of the underlying reality. To make this determination, the brain jumps back and forth between these versions of reality, sampling a probability distribution. The researchers working with Heidelberg physicist Prof. Dr Karlheinz Meier studied this process with the help of formal mathematical methods applied at the level of individual nerve cells, called neurons. The model of individual neurons used is strictly deterministic. This means that each repeated stimulation from external stimuli always evokes the same response behaviour. The brain, however, is a network of neurons that communicate with one another. When a nerve cell is sufficiently stimulated by its neighbour, it fires off a short electrical pulse, thereby stimulating other neurons. In a large network of active neurons, nerve cells become stochastic -- their "response" is no longer determined, i.e., precisely predictable, but follows statistical probability rules. "In our studies we were able to show that such neurons obtain their response from probability distributions that are stored in the network itself and that are sampled by the nerve cells," explains Prof. Meier. This is how neurons are able to detect patterns that reflect acquired knowledge. The research was conducted as part of the European Human Brain Project, in which the Heidelberg researchers under the direction of Karlheinz Meier are developing new computer systems using the brain as a model. "The concept of statistical sampling of acquired probabilities is extremely well-suited for implementing a new computer architecture. It is one focus of the current research our working group is conducting," states the physicist, who teaches and pursues research at Heidelberg University's Kirchhoff Institute for Physics.

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