In this paper, a new multiple-image encryption and decryption technique that utilizes the compressive sensing (CS) concept along with a double-random phase encryption (DRPE) has been proposed. The space multiplexing method is employed for integrating multiple-image data. The method, which results in a nonlinear encryption system, is able to overcome the vulnerability of classical DRPE. The CS technique and space multiplexing are able to provide additional key space in the proposed method. A numerical experiment of the proposed method is implemented and the results show that the proposed method has good accuracy and is more robust than classical DRPE. The proposed system is also employed against chosen-plaintext attacks and it is found that the inclusion of compressive sensing enhances robustness against the attacks.
Fast, direct electron detectors have significantly improved the spatio-temporal resolution of electron microscopy movies. Preserving both spatial and temporal resolution in extended observations, however, requires storing prohibitively large amounts of data. Here, we describe an efficient and flexible data reduction and compression scheme (ReCoDe) that retains both spatial and temporal resolution by preserving individual electron events. Running ReCoDe on a workstation we demonstrate on-the-fly reduction and compression of raw data streaming off a detector at 3 GB/s, for hours of uninterrupted data collection. The output was 100-fold smaller than the raw data and saved directly onto network-attached storage drives over a 10 GbE connection. We discuss calibration techniques that support electron detection and counting (e.g., estimate electron backscattering rates, false positive rates, and data compressibility), and novel data analysis methods enabled by ReCoDe (e.g., recalibration of data post acquisition, and accurate estimation of coincidence loss).
Robust processes to fabricate densely packed highaspect-ratio (HAR) vertical semiconductor nanostructures are important for applications in microelectronics, energy storage and conversion. One of the main challenges in manufacturing these nanostructures is pattern collapse, which is the damage induced by capillary forces from numerous solution-based processes used during their fabrication. Here, using an array of vertical silicon (Si) nanopillars as test structures, we demonstrate that pattern collapse can be greatly reduced by a solution-phase deposition method to coat the nanopillars with self-assembled monolayers (SAMs). As the main cause for pattern collapse is strong adhesion between the nanopillars, we systematically evaluated SAMs with different surface energy components and identified H-bonding between the surfaces to have the largest contribution to the adhesion. The advantage of the solution-phase deposition method is that it can be implemented before any drying step, which causes patterns to collapse. Moreover, after drying, these SAMs can be easily removed using a gentle air-plasma treatment right before the next fabrication step, leaving a clean nanopillar surface behind. Therefore, our approach provides a facile and effective method to prevent the drying-induced pattern collapse in micro-and nanofabrication processes.
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