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Institution

Johannes Kepler University of Linz

EducationLinz, Oberösterreich, Austria
About: Johannes Kepler University of Linz is a education organization based out in Linz, Oberösterreich, Austria. It is known for research contribution in the topics: Thin film & Quantum dot. The organization has 6605 authors who have published 19243 publications receiving 385667 citations.


Papers
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Journal ArticleDOI
TL;DR: It is argued that the systematic organization of knowledge into AOP frameworks can inform and help direct the design and development of computational prediction models that can further enhance the utility of mechanistic and in silico data for chemical safety assessment.

125 citations

Journal ArticleDOI
TL;DR: In this paper, the authors integrate resonant-cavity light-emitting diodes containing quantum dots onto substrates with giant piezoelectric response, and the energy of the photons emitted by the diode can be precisely controlled during electrical injection over a spectral range larger than 20 meV.
Abstract: We integrate resonant-cavity light-emitting diodes containing quantum dots onto substrates with giant piezoelectric response. Via strain, the energy of the photons emitted by the diode can be precisely controlled during electrical injection over a spectral range larger than 20 meV. Simultaneously, the exciton fine-structure-splitting and the biexciton binding energy can be tuned to the values required for entangled photon generation.

125 citations

Book ChapterDOI
20 Mar 2010
TL;DR: This work shows that BCE is surprisingly effective both in theory and in practice on CNFs resulting from a standard CNF encoding for circuits: without explicit knowledge of the underlying circuit structure, it achieves the same level of simplification as a combination of circuit-level simplifications and previously suggested polarity-based CNF encodings.
Abstract: Boolean satisfiability (SAT) and its extensions are becoming a core technology for the analysis of systems. The SAT-based approach divides into three steps: encoding, preprocessing, and search. It is often argued that by encoding arbitrary Boolean formulas in conjunctive normal form (CNF), structural properties of the original problem are not reflected in the CNF. This should result in the fact that CNF-level preprocessing and SAT solver techniques have an inherent disadvantagecompared to related techniques applicable on the level of more structural SAT instance representations such as Boolean circuits. In this work we study the effect of a CNF-level simplification technique called blocked clause elimination (BCE). We show that BCE is surprisingly effective both in theory and in practice on CNFs resulting from a standard CNF encoding for circuits: without explicit knowledge of the underlying circuit structure, it achieves the same level of simplification as a combination of circuit-level simplifications and previously suggested polarity-based CNF encodings. Experimentally, we show that by applying BCE in preprocessing, further formula reduction and faster solving can be achieved, giving promise for applying BCE to speed up solvers.

125 citations

Journal ArticleDOI
TL;DR: In this article, a structural equation model with two latent variables is used to extract information on various dimensions of corruption and the shadow economy, and empirical evidence for a complementary relationship between corruption and shadow economy is presented.
Abstract: From a theoretical point of view, the relationship between corruption and the shadow economy is ambiguous: They can either be substitutes or complements. This paper contributes to this debate by using a structural equation model with two latent variables to extract information on various dimensions of corruption and the shadow economy. Analyzing a sample of 51 countries around the world over the period 2000 to 2005, we present empirical evidence for a complementary (positive) relationship of corruption and the shadow economy.

125 citations

Journal ArticleDOI
TL;DR: The proposed procedure of calibrated complex impedance measurements and dielectric quantification with scanning microwave microscopy is simple and fast and the accuracy of the results is not affected by varying stray capacitances.
Abstract: We present a procedure for calibrated complex impedance measurements and dielectric quantification with scanning microwave microscopy. The calibration procedure works in situ directly on the substrate with the specimen of interest and does not require any specific calibration sample. In the workflow tip‐sample approach curves are used to extract calibrated complex impedance values and to convert measured S11 reflection signals into sample capacitance and resistance images. The dielectric constant of thin dielectric SiO2 films were determined from the capacitance images and approach curves using appropriate electrical tip‐sample models and the"r value extracted at fD 19:81 GHz is in good agreement with the nominal value of"r 4. The capacitive and resistive material properties of a doped Si semiconductor sample were studied at different doping densities and tip‐sample bias voltages. Following a simple serial model the capacitance‐voltage spectroscopy curves are clearly related to the semiconductor depletion zone while the resistivity is rising with falling dopant density from 20 to 20 k. The proposed procedure of calibrated complex impedance measurements is simple and fast and the accuracy of the results is not affected by varying stray capacitances. It works for nanoscale samples on either fully dielectric or highly conductive substrates at frequencies between 1 and 20 GHz.

125 citations


Authors

Showing all 6718 results

NameH-indexPapersCitations
Wolfgang Wagner1562342123391
A. Paul Alivisatos146470101741
Klaus-Robert Müller12976479391
Christoph J. Brabec12089668188
Andreas Heinz108107845002
Niyazi Serdar Sariciftci9959154055
Lars Samuelson9685036931
Peter J. Oefner9034830729
Dmitri V. Talapin9030339572
Tomás Torres8862528223
Ramesh Raskar8667030675
Siegfried Bauer8442226759
Alexander Eychmüller8244423688
Friedrich Schneider8255427383
Maksym V. Kovalenko8136034805
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20242
202354
2022187
20211,404
20201,412
20191,365