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Institution

Solid State Physics Laboratory

FacilityDelhi, India
About: Solid State Physics Laboratory is a facility organization based out in Delhi, India. It is known for research contribution in the topics: Quantum dot & Dielectric. The organization has 1754 authors who have published 2597 publications receiving 50601 citations.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors used a scanning confocal approach to collect spectral data with spatial resolution, which allows them to directly compare Raman images with scanning force micrographs.
Abstract: We present Raman spectroscopy measurements on single- and few-layer graphene flakes. By using a scanning confocal approach, we collect spectral data with spatial resolution, which allows us to directly compare Raman images with scanning force micrographs. Single-layer graphene can be distinguished from double- and few-layer by the width of the D' line: the single peak for single-layer graphene splits into different peaks for the double-layer. These findings are explained using the double-resonant Raman model based on ab initio calculations of the electronic structure and of the phonon dispersion. We investigate the D line intensity and find no defects within the flake. A finite D line response originating from the edges can be attributed either to defects or to the breakdown of translational symmetry.

2,310 citations

Journal ArticleDOI
TL;DR: In this article, the electronic structure of the perovskite LaCoO 3$ for different spin states of Co ions was calculated in the local density approximation LDA+U approach.
Abstract: The electronic structure of the perovskite ${\mathrm{LaCoO}}_{3}$ for different spin states of Co ions was calculated in the local-density approximation LDA+U approach The ground state is found to be a nonmagnetic insulator with Co ions in a low-spin state Somewhat higher in energy, we find two intermediate-spin states followed by a high-spin state at significantly higher energy The calculations show that Co 3d states of ${\mathit{t}}_{2\mathit{g}}$ symmetry form narrow bands which could easily localize, while ${\mathit{e}}_{\mathit{g}}$ orbitals, due to their strong hybridization with the oxygen 2p states, form a broad \ensuremath{\sigma}* band With temperature variation which is simulated by a corresponding change of the lattice parameters, a transition from the low- to intermediate-spin state occurs This intermediate-spin (occupation ${\mathit{t}}_{2\mathit{g}}^{5}$${\mathit{e}}_{\mathit{g}}^{1}$) can develop an orbital ordering which can account for the nonmetallic nature of ${\mathrm{LaCoO}}_{3}$ at 90 KT500 K Possible explanations of the magnetic behavior and gradual insulator-metal transition are suggested \textcopyright{} 1996 The American Physical Society

641 citations

Journal ArticleDOI
TL;DR: An algorithm to compute initial cluster centers for K-means clustering based on two observations that some of the patterns are very similar to each other and that is why they have same cluster membership irrespective to the choice of initial cluster center.

629 citations

Journal ArticleDOI
01 Nov 2007
TL;DR: A clustering algorithm based on k-mean paradigm that works well for data with mixed numeric and categorical features is presented and a new cost function and distance measure based on co-occurrence of values is proposed.
Abstract: Use of traditional k-mean type algorithm is limited to numeric data. This paper presents a clustering algorithm based on k-mean paradigm that works well for data with mixed numeric and categorical features. We propose new cost function and distance measure based on co-occurrence of values. The measures also take into account the significance of an attribute towards the clustering process. We present a modified description of cluster center to overcome the numeric data only limitation of k-mean algorithm and provide a better characterization of clusters. The performance of this algorithm has been studied on real world data sets. Comparisons with other clustering algorithms illustrate the effectiveness of this approach.

621 citations

Journal ArticleDOI
22 Feb 2001-Nature
TL;DR: In this article, acceleration measurements using a detector adapted from high-energy physics to track particles in a laboratory water flow at Reynolds numbers up to 63,000 were reported, indicating that the acceleration is an extremely intermittent variable.
Abstract: The motion of fluid particles as they are pushed along erratic trajectories by fluctuating pressure gradients is fundamental to transport and mixing in turbulence. It is essential in cloud formation and atmospheric transport, processes in stirred chemical reactors and combustion systems, and in the industrial production of nanoparticles. The concept of particle trajectories has been used successfully to describe mixing and transport in turbulence, but issues of fundamental importance remain unresolved. One such issue is the Heisenberg-Yaglom prediction of fluid particle accelerations, based on the 1941 scaling theory of Kolmogorov. Here we report acceleration measurements using a detector adapted from high-energy physics to track particles in a laboratory water flow at Reynolds numbers up to 63,000. We find that, within experimental errors, Kolmogorov scaling of the acceleration variance is attained at high Reynolds numbers. Our data indicate that the acceleration is an extremely intermittent variable--particles are observed with accelerations of up to 1,500 times the acceleration of gravity (equivalent to 40 times the root mean square acceleration). We find that the acceleration data reflect the anisotropy of the large-scale flow at all Reynolds numbers studied.

606 citations


Authors

Showing all 1757 results

NameH-indexPapersCitations
J. Karpinski5350411374
Victor Ryzhii5349310063
Christian H. Back5224310058
Andrea Damascelli5121412527
Mathieu Kociak512279211
Mansour Shayegan514589171
Mohan Singh493138526
Kalina Hristova481787888
O.N. Srivastava4754810308
F. M. F. de Groot4715710518
Gianni Blatter4627712191
Ludger Wirtz4613910649
D. van der Marel452659816
Luciano Pietronero452959471
Yigal Meir4418211014
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
202210
202174
202087
201992
201878