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Institution

Karlsruhe Institute of Technology

EducationKarlsruhe, Germany
About: Karlsruhe Institute of Technology is a education organization based out in Karlsruhe, Germany. It is known for research contribution in the topics: Computer science & Catalysis. The organization has 37946 authors who have published 82138 publications receiving 2197068 citations. The organization is also known as: KIT & University of Karlsruhe.


Papers
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Journal ArticleDOI
TL;DR: The so-called hypoelastic constitutive equations, defined by the equationℸ=h(T, D), are limited by the requirement that h is linear in D.
Abstract: The so-called hypoelastic constitutive equations, defined by the equationℸ=h(T, D), are limited by the requirement thath is linear inD. Dropping this requirement and retaining positive homogeneity of the first degreen inD leads to a broader class of equations which can be calledhypoplastic. Such equations are appropriate to describe the anelastic behaviour of granular materials. Some properties of hypoplastic equations are discussed in this paper including the new notions of yield and bound surfaces which are given a completely different meaning than in classical elastoplasticity. Possiblities to enlarge hypoplasticity towards rate-dependence and more complex intrinsic memory of the material are pointed to.

351 citations

Journal ArticleDOI
TL;DR: In this paper, the role of underreLAXATION in MOMENTUM INTERPOLATION for CALCULATION OF FLOW with non-staggered GRIDS is discussed.
Abstract: (1988). ROLE OF UNDERRELAXATION IN MOMENTUM INTERPOLATION FOR CALCULATION OF FLOW WITH NONSTAGGERED GRIDS. Numerical Heat Transfer: Vol. 13, No. 1, pp. 125-132.

351 citations

Journal ArticleDOI
TL;DR: A statistical theory for overtraining is proposed and it is shown that the asymptotic gain in the generalization error is small if the authors perform early stopping, even if they have access to the optimal stopping time.
Abstract: A statistical theory for overtraining is proposed. The analysis treats general realizable stochastic neural networks, trained with Kullback-Leibler divergence in the asymptotic case of a large number of training examples. It is shown that the asymptotic gain in the generalization error is small if we perform early stopping, even if we have access to the optimal stopping time. Based on the cross-validation stopping we consider the ratio the examples should be divided into training and cross-validation sets in order to obtain the optimum performance. Although cross-validated early stopping is useless in the asymptotic region, it surely decreases the generalization error in the nonasymptotic region. Our large scale simulations done on a CM5 are in good agreement with our analytical findings.

350 citations

Journal ArticleDOI
TL;DR: In this paper, the spectral distributions of the fluctuations in velocity are quantitatively related to the dimensions of the two unequal regions of flow recirculation, and it is shown that the intensity of fluctuating energy in these low Reynolds number flows can be larger than that in corresponding turbulent flows.
Abstract: Flow visualization and laser-Doppler anemometry have been used to provide a detailed description of the velocity characteristics of the asymmetric flows which form in symmetric, two-dimensional, plane, sudden-expansion geometries. The flow and geometry boundary conditions which give rise to asymmetric flow are indicated, and the reason for the phenomenon is shown to lie in disturbances generated at the edge of the expansion and amplified in the shear layers. The spectral distributions of the fluctuations in velocity are quantitatively related to the dimensions of the two unequal regions of flow recirculation. It is also shown that the intensity of fluctuating energy in these low Reynolds number flows can be larger than that in corresponding turbulent flows.

350 citations

Journal ArticleDOI
TL;DR: In this article, a planar, optical microcavity was used to control the efficiency and spectral selection of photocurrent generation in the integrated graphene device, and a twenty-fold enhancement of the photocurrent was demonstrated.
Abstract: Graphene has extraordinary electronic and optical properties and holds great promise for applications in photonics and optoelectronics. Demonstrations including high-speed photodetectors, optical modulators, plasmonic devices, and ultrafast lasers have now been reported. More advanced device concepts would involve photonic elements such as cavities to control light–matter interaction in graphene. Here we report the first monolithic integration of a graphene transistor and a planar, optical microcavity. We find that the microcavity-induced optical confinement controls the efficiency and spectral selection of photocurrent generation in the integrated graphene device. A twenty-fold enhancement of photocurrent is demonstrated. The optical cavity also determines the spectral properties of the electrically excited thermal radiation of graphene. Most interestingly, we find that the cavity confinement modifies the electrical transport characteristics of the integrated graphene transistor. Our experimental approach opens up a route towards cavity-quantum electrodynamics on the nanometre scale with graphene as a current-carrying intra-cavity medium of atomic thickness.

349 citations


Authors

Showing all 38468 results

NameH-indexPapersCitations
Hyun-Chul Kim1764076183227
Yury Gogotsi171956144520
Marc Weber1672716153502
Chad A. Mirkin1641078134254
J. S. Lange1602083145919
Hannes Jung1592069125069
Wolfgang Wagner1562342123391
Vivek Sharma1503030136228
Teresa Lenz1501718114725
Andreas Pfeiffer1491756131080
Daniel Bloch1451819119556
Th. Müller1441798125843
Martin Erdmann1441562100470
Tim Adye1431898109010
Daniela Bortoletto1431883108433
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023412
2022828
20214,635
20204,874
20194,830
20184,412