[Show abstract][Hide abstract] ABSTRACT: Two-dimensional (2D) materials are a new class of materials with interesting physical properties and applications ranging from nanoelectronics to sensing and photonics. In addition to graphene, the most studied 2D material, monolayers of other layered materials such as semiconducting dichalcogenides MoS2 or WSe2 are gaining in importance as promising channel materials for field-effect transistors (FETs). The presence of a direct bandgap in monolayer MoS2 due to quantum-mechanical confinement allows room-temperature FETs with an on/off ratio exceeding 10(8). The presence of high- κ dielectrics in these devices enhanced their mobility, but the mechanisms are not well understood. Here, we report on electrical transport measurements on MoS2 FETs in different dielectric configurations. The dependence of mobility on temperature shows clear evidence of the strong suppression of charged-impurity scattering in dual-gate devices with a top-gate dielectric. At the same time, phonon scattering shows a weaker than expected temperature dependence. High levels of doping achieved in dual-gate devices also allow the observation of a metal-insulator transition in monolayer MoS2 due to strong electron-electron interactions. Our work opens up the way to further improvements in 2D semiconductor performance and introduces MoS2 as an interesting system for studying correlation effects in mesoscopic systems.
[Show abstract][Hide abstract] ABSTRACT: Two-dimensional materials are an emerging class of new materials with a wide range of electrical properties and potential practical applications. Although graphene is the most well-studied two-dimensional material, single layers of other materials, such as insulating BN (ref. 2) and semiconducting MoS2 (refs 3, 4) or WSe2 (refs 5, 6), are gaining increasing attention as promising gate insulators and channel materials for field-effect transistors. Because monolayer MoS2 is a direct-bandgap semiconductor due to quantum-mechanical confinement, it could be suitable for applications in optoelectronic devices where the direct bandgap would allow a high absorption coefficient and efficient electron-hole pair generation under photoexcitation. Here, we demonstrate ultrasensitive monolayer MoS2 phototransistors with improved device mobility and ON current. Our devices show a maximum external photoresponsivity of 880 A W(-1) at a wavelength of 561 nm and a photoresponse in the 400-680 nm range. With recent developments in large-scale production techniques such as liquid-scale exfoliation and chemical vapour deposition-like growth, MoS2 shows important potential for applications in MoS2-based integrated optoelectronic circuits, light sensing, biomedical imaging, video recording and spectroscopy.
[Show abstract][Hide abstract] ABSTRACT: Memory cells are an important building block of digital electronics. We combine here the unique electronic properties of semiconducting monolayer MoS2 with the high conductivity of graphene to build a 2D heterostructure capable of information storage. MoS2 acts as a channel in an intimate contact with graphene electrodes in a field-effect transistor geometry. Our prototypical all-2D transistor is further integrated with a multilayer graphene charge trapping layer into a device that can be operated as a nonvolatile memory cell. Because of its band gap and 2D nature, monolayer MoS2 is highly sensitive to the presence of charges in the charge trapping layer, resulting in a factor of 10(4) difference between memory program and erase states. The two-dimensional nature of both the contact and the channel can be harnessed for the fabrication of flexible nanoelectronic devices with large-scale integration.
[Show abstract][Hide abstract] ABSTRACT: In our previous paper, we reported on switchable monolayer MoS2
transistors with a high on-off ratio and we claim that dielectric
screening can be used to increase the mobility of monolayer MoS2. We
estimated its mobility using a method previously applied by Lemme et al.
to top-gated graphene nanoribbons. We discuss here the comments raised
by M. Fuhrer and J. Hone in their post 1301.4288 and give our own
estimates of the possible errors in previous mobility measurements and
[Show abstract][Hide abstract] ABSTRACT: Two-dimensional (2D) materials such as monolayer molybdenum disulfide (MoS(2)) are extremely interesting for integration in nanoelectronic devices where they represent the ultimate limit of miniaturization in the vertical direction. Thanks to the presence of a band gap and subnanometer thickness, monolayer MoS(2) can be used for the fabrication of transistors exhibiting extremely high on/off ratios and very low power dissipation. Here, we report on the development of 2D MoS(2) transistors with improved performance due to enhanced electrostatic control. Our devices show currents in the 100 μA/μm range and transconductance exceeding 20 μS/μm as well as current saturation. We also record electrical breakdown of our devices and find that MoS(2) can support very high current densities, exceeding the current-carrying capacity of copper by a factor of 50. Our results push the performance limit of MoS(2) and open the way to their use in low-power and low-cost analog and radio frequency circuits.
[Show abstract][Hide abstract] ABSTRACT: We propose a novel compressed sensing technique to accelerate the magnetic resonance imaging (MRI) acquisition process. The method, coined spread spectrum MRI or simply s(2)MRI, consists of premodulating the signal of interest by a linear chirp before random k-space under-sampling, and then reconstructing the signal with nonlinear algorithms that promote sparsity. The effectiveness of the procedure is theoretically underpinned by the optimization of the coherence between the sparsity and sensing bases. The proposed technique is thoroughly studied by means of numerical simulations, as well as phantom and in vivo experiments on a 7T scanner. Our results suggest that s(2)MRI performs better than state-of-the-art variable density k-space under-sampling approaches.
IEEE transactions on medical imaging. 03/2012; 31(3):586-98.
[Show abstract][Hide abstract] ABSTRACT: Optical fiber sensors based on stimulated Brillouin scattering in optical fibers have now clearly demonstrated their excellent capability for long-range distributed strain and temperature measurements. The fiber is used as sensing element and a value for temperature and/or strain can be obtained from any point along the fiber. While the spatial resolution of classical configurations is practically limited to 1 meter by the phonon lifetime, novel approaches have been demonstrated these past years that can overcome this limit. In this paper, this could be achieved by two physical processes: prior activation of a steady acoustic wave through the classical Brillouin interaction between two Brillouin pumps, and interrogation by Bragg reflection on the acoustic wave using a distinct ultra-short pulse in a highly birefringent fiber. We could achieve a spatial resolution below one centimeter, while preserving the full accuracy on the determination of temperature and strain.
[Show abstract][Hide abstract] ABSTRACT: We propose a method to compute scale-invariant features in omnidirectional images. We present a formulation based on the Riemannian geometry for the definition of differential operators on non-Euclidian manifolds that adapt to the mirror and lens structures in omnidirectional imaging. These operators lead to a scale-space analysis that preserves the geometry of the visual information in omnidirectional images. We then build a novel scale-invariant feature detection framework for omnidirectional images that can be mapped on the sphere. We further present a new descriptor and feature matching solution for these omnidirectional images. The descriptor builds on the log-polar planar descriptors and adapts the descriptor computation to the specific geometry and the nonuniform sampling density of omnidirectional images. We also propose a rotation-invariant matching method that eliminates the orientation computation during the feature detection phase and thus decreases the computational complexity. Experimental results demonstrate that the new feature computation method combined with the adapted descriptors offers promising detection and matching performance, i.e., it improves on the common scale-invariant feature transform (SIFT) features computed on the unwrapped omnidirectional images, as well as spherical SIFT features. Finally, we show that the proposed framework also permits to match features between images with different native geometry.
IEEE Transactions on Image Processing 01/2012; 21(5):2412-23.
[Show abstract][Hide abstract] ABSTRACT: We present the experimental demonstration of broadband four-wave mixing in a 2.5 cm-long segment of AsSe Chalcogenide microstructured fiber. The parametric mixing was driven by a continuous-wave pump compatible with data signal wavelength conversion. Four-wave mixing products over more than 70 nm on the anti-stoke side of the pump were measured for 345 mW of pump power and 1.5 dBm of signal power. The ultrafast signal processing capability was verified through wavelength conversion of 1.4 ps pulses at 8 GHz repetition rate.
[Show abstract][Hide abstract] ABSTRACT: This paper addresses the problem of distributed coding of images whose
correlation is driven by the motion of objects or positioning of the vision
sensors. It concentrates on the problem where images are encoded with
compressed linear measurements. We propose a geometry-based correlation model
in order to describe the common information in pairs of images. We assume that
the constitutive components of natural images can be captured by visual
features that undergo local transformations (e.g., translation) in different
images. We first identify prominent visual features by computing a sparse
approximation of a reference image with a dictionary of geometric basis
functions. We then pose a regularized optimization problem to estimate the
corresponding features in correlated images given by quantized linear
measurements. The estimated features have to comply with the compressed
information and to represent consistent transformation between images. The
correlation model is given by the relative geometric transformations between
corresponding features. We then propose an efficient joint decoding algorithm
that estimates the compressed images such that they stay consistent with both
the quantized measurements and the correlation model. Experimental results show
that the proposed algorithm effectively estimates the correlation between
images in multi-view datasets. In addition, the proposed algorithm provides
effective decoding performance that compares advantageously to independent
coding solutions as well as state-of-the-art distributed coding schemes based
on disparity learning.
IEEE Transactions on Image Processing 11/2011; 21(7).
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