The Experts below are selected from a list of 252 Experts worldwide ranked by ideXlab platform
Chen Ying - One of the best experts on this subject based on the ideXlab platform.
-
WebWeb Multimedia Information Storage
Computer Engineering, 2001Co-Authors: Chen YingAbstract:The technique of Web multimedia Information Storage based on ASP(Active server pages) and SQL Server database are discussed in the paper ,whose main principles of ASP and multimedia Information Storage are also introduced.
Jonathan S. Lindsey - One of the best experts on this subject based on the ideXlab platform.
-
Porphyrin architectures tailored for studies of molecular Information Storage.
The Journal of organic chemistry, 2004Co-Authors: Carole M. Carcel, Joydev K. Laha, Robert S. Loewe, Patchanita Thamyongkit, Karl-heinz Schweikart, Veena Misra, David F. Bocian, Jonathan S. LindseyAbstract:A molecular approach to Information Storage employs redox-active molecules tethered to an electroactive surface. Zinc porphyrins tethered to Au(111) or Si(100) provide a benchmark for studies of Information Storage. Three sets of porphyrins have been synthesized for studies of the interplay of molecular design and charge-Storage properties: (1) A set of porphyrins is described for probing the effect of surface attachment atom on electron-transfer kinetics. Each porphyrin bears a meso-CH2X group for surface attachment where X = OH, SAc, or SeAc. (2) A set of porphyrins is described for studying the effect of surface-charge density in monolayers. Each porphyrin bears a benzyl alcohol for surface attachment and three nonlinking meso substituents of a controlled degree of bulkiness. (3) A set of porphyrins is described that enables investigation of on-chip patterning of the electrolyte. Each porphyrin bears a formyl group distal to the surface attachment group for subsequent derivatization with a molecular entity that comprises the electrolyte. Taken together, this collection of molecules enables a variety of studies to elucidate design issues in molecular-based Information Storage.
Guilhem Larrieu - One of the best experts on this subject based on the ideXlab platform.
-
Pushing the limits of optical Information Storage using deep learning
Nature Nanotechnology, 2019Co-Authors: Peter Wiecha, Aurélie Lecestre, Nicolas Mallet, Guilhem LarrieuAbstract:Diffraction drastically limits the bit density in optical data Storage. To increase the Storage density, alternative strategies involving supplementary recording dimensions and robust readout schemes must be explored. Here, we propose to encode multiple bits of Information in the geometry of subwavelength dielectric nanostructures. A crucial problem in high-density Information Storage concepts is the robustness of the Information readout with respect to fabrication errors and experimental noise. Using a machine-learning-based approach in which the scattering spectra are analysed by an artificial neural network, we achieve quasi-error-free readout of sequences of up to 9 bits, encoded in top-down fabricated silicon nanostructures. We demonstrate that probing few wavelengths instead of the entire spectrum is sufficient for robust Information retrieval and that the readout can be further simplified, exploiting the RGB values from microscopy images. Our work paves the way towards high-density optical Information Storage using planar silicon nanostructures, compatible with mass-production-ready complementary metal–oxide–semiconductor technology.
-
Pushing the limits of optical Information Storage using deep learning
2018Co-Authors: Peter Wiecha, Aurélie Lecestre, Nicolas Mallet, Guilhem LarrieuAbstract:Diffraction drastically limits the bit density in optical data Storage. To increase the Storage density, alternative strategies involving supplementary recording dimensions and robust read-out schemes must be explored. Here, we propose to encode multiple bits of Information in the geometry of subwavelength dielectric nanostructures. A crucial problem in high-density Information Storage concepts is the robustness of the Information readout with respect to fabrication errors and experimental noise. Using a machine-learning based approach in which the scattering spectra are analyzed by an artificial neural network, we achieve quasi error free read-out of 4-bit sequences, encoded in top-down fabricated silicon nanostructures. The read-out speed can further be increased exploiting the RGB values of microscopy images, and the Information density could be increased beyond current state of the art. Our work paves the way towards high-density optical Information Storage using planar silicon nanostructures, compatible with mass-production ready CMOS technology.
John M. Doyle - One of the best experts on this subject based on the ideXlab platform.
-
Quantum computing and quantum Information Storage.
Physical chemistry chemical physics : PCCP, 2021Co-Authors: Anna I. Krylov, John M. DoyleAbstract:This themed collection includes a selection of articles on quantum computing and quantum Information Storage.
M. Rooks - One of the best experts on this subject based on the ideXlab platform.
-
Nanostructured Materials in Information Storage
MRS Bulletin, 2008Co-Authors: Zvonimir Z. Bandić, Dmitri Litvinov, M. RooksAbstract:The ever-increasing demand for Information Storage has pushed research and development of nonvolatile memories, particularly magnetic disk drives and silicon-based memories, to areal densities where bit sizes are approaching nanometer dimensions. At this level, material and device phenomena make further scaling increasingly difficult. The difficulties are illustrated in the examples of magnetic media and flash memory, such as thermal instability of sub-100-nm bits in magnetic memory and charge retention in flash memory, and solutions are discussed in the form of patterned media and crosspoint memories. The materials-based difficulties are replaced by nanofabrication challenges, requiring the introduction of new techniques such as nanoimprinting lithography for cost-effective manufacturing and self-assembly for fabrication on the sub-25-nm scale. Articles in this issue describe block-copolymer lithographic fabrication of patterned media, materials studies on the scaling limits of phase-change-based crosspoint memories, nanoscale fabrication using imprint lithography, and biologically inspired protein-based memory.
