Embedded data are used to retrieve phases quicker with high accuracy in phase-modulated holographic data storage (HDS). We propose a method to design an embedded data distribution using iterations to enhance the intensity of the high-frequency signal in the Fourier spectrum. The proposed method increases the anti-noise performance and signal-to-noise ratio (SNR) of the Fourier spectrum distribution, realizing a more efficient phase retrieval. Experiments indicate that the bit error rate (BER) of this method can be reduced by a factor of one after 10 iterations.
Semiconductor optoelectronic fiber technology has seen rapid development in recent years thanks to advancements in fabrication and post-processing techniques. Integrating the optical and electronic functionality of semiconductor materials into a fiber geometry has opened up many possibilities, such as in-fiber frequency generation, signal modulation, photodetection, and solar energy harvesting. This review provides an overview of the state-of-the-art in semiconductor optoelectronic fibers, including fabrication and post-processing methods, materials and their optical properties. The applications in nonlinear optics, optical-electrical conversion, lasers and multimaterial functional fibers will also be highlighted.
A near-infrared femtosecond laser is focused by a 100 mm-focal-length plano-convex lens to form a laser filament, which is employed to drill holes on copper targets. By shifting or rotating the focusing lens, additional aberration is imposed on the focused laser beam, and significant influence is produced on the aspect ratio and cross-sectional shape of the micro-holes. Experimental results show that when proper aberration is introduced, the copper plate with a thickness of 3 mm can be drilled through with an aspect ratio of 30, while no through-holes can be drilled on 3-mm-thickness copper plates by femtosecond laser with minimized aberration. In addition, when femtosecond laser filament with large astigmatism is used, micro-holes that had a length to width ratio up to 3.3 on the cross-section are obtained. Therefore, the method proposed here can be used to fabricate long oval holes with high aspect ratios.
Indium Gallium Nitride based blue light-emitting diodes (LEDs) suffer from insufficient crystal quality and serious efficiency droop in large forward current. In this paper, the InGaN-based blue LEDs are grown on sputtered aluminum nitride (AlN) films to improve the device light power and weaken the efficiency droop. The effects of oxygen flow rate on the sputtering of AlN films on sapphire and device performance of blue LEDs are studied in detail. The mechanism of external quantum efficiency improvement is related to the change of V-pits density in multiple quantum wells. The external quantum efficiency of 66% and 3-V operating voltage are measured at a 40-mA forward current of with the optimal oxygen flow rate of 4 SCCM.
Cadmium selenide (CdSe) belongs to the binary II-VI group semiconductor with a direct bandgap of ~1.7 eV. The suitable bandgap, high stability, and low manufacturing cost make CdSe an extraordinary candidate as the top cell material in silicon-based tandem solar cells. However, only a few studies have focused on CdSe thin-film solar cells in the past decades. With the advantages of a high deposition rate (~2 µm/min) and high uniformity, rapid thermal evaporation (RTE) was used to maximize the use efficiency of CdSe source material. A stable and pure hexagonal phase CdSe thin film with a large grain size was achieved. The CdSe film demonstrated a 1.72 eV bandgap, narrow photoluminescence peak, and fast photoresponse. With the optimal device structure and film thickness, we finally achieved a preliminary efficiency of 1.88% for CdSe thin-film solar cells, suggesting the applicability of CdSe thin-film solar cells.
Circadian rhythms are considered a masterstroke of natural selection, which gradually increase the adaptability of species to the Earth’s rotation. Importantly, the nervous system plays a key role in allowing organisms to maintain circadian rhythmicity. Circadian rhythms affect multiple aspects of cognitive functions (mainly via arousal), particularly those needed for effort-intensive cognitive tasks, which require considerable top-down executive control. These include inhibitory control, working memory, task switching, and psychomotor vigilance. This mini review highlights the recent advances in cognitive functioning in the optical and multimodal neuroimaging fields; it discusses the processing of brain cognitive functions during the circadian rhythm phase and the effects of the circadian rhythm on the cognitive component of the brain and the brain circuit supporting cognition.
Optical traps have emerged as powerful tools for immobilizing and manipulating small particles in three dimensions. Fiber-based optical traps (FOTs) significantly simplify optical setup by creating trapping centers with single or multiple pieces of optical fibers. In addition, they inherit the flexibility and robustness of fiber-optic systems. However, trapping 10-nm-diameter nanoparticles (NPs) using FOTs remains challenging. In this study, we model a coaxial waveguide that works in the optical regime and supports a transverse electromagnetic (TEM)-like mode for NP trapping. Single NPs at waveguide front-end break the symmetry of TEM-like guided mode and lead to high transmission efficiency at far-field, thereby strongly altering light momentum and inducing a large-scale back-action on the particle. We demonstrate, via finite-difference time-domain (FDTD) simulations, that this FOT allows for trapping single 10-nm-diameter NPs at low power.
The broad emission and high photoluminescence quantum yield of self-trapped exciton (STE) radiative recombination emitters make them an ideal solution for single-substrate, white, solid-state lighting sources. Unlike impurities and defects in semiconductors, the formation of STEs requires a lattice distortion, along with strong electron–phonon coupling, in low electron-dimensional materials. The photoluminescence of inorganic copper(I) metal halides with low electron-dimensionality has been found to be the result of STEs. These materials were of significant interest because of their lead-free, all-inorganic structures, and high luminous efficiencies. In this paper, we summarize the luminescence characteristics of zero- and one-dimensional inorganic copper(I) metal halides with STEs to provide an overview of future research opportunities.
With the benefits of low latency, wide transmission bandwidth, and large mode field area, hollow-core antiresonant fiber (HC-ARF) has been a research hotspot in the past decade. In this paper, a hollow core step-index antiresonant fiber (HC-SARF), with stepped refractive indices cladding, is proposed and numerically demonstrated with the benefits of loss reduction and bending improvement. Glass-based capillaries with both high (n = 1.45) and low (as low as n = 1.36) refractive indices layers are introduced and formatted in the cladding air holes. Using the finite element method to perform numerical analysis of the designed fiber, results show that at the laser wavelengths of 980 and 1064 nm, the confinement loss is favorably reduced by about 6 dB/km compared with the conventional uniform cladding HC-ARF. The bending loss, around 15 cm bending radius of this fiber, is also reduced by 2 dB/km. The cladding air hole radius in this fiber is further investigated to optimize the confinement loss and the mode field diameter with single-mode transmission behavior. This proposed HC-SARF has great potential in optical fiber transmission and high energy delivery.
In this paper, we proposed a quality of transmission (QoT) prediction technique for the quality of service (QoS) link setup based on machine learning classifiers, with synthetic data generated using the transmission equations instead of the Gaussian noise (GN) model. The proposed technique uses some link and signal characteristics as input features. The bit error rate (BER) of the signals was compared with the forward error correction threshold BER, and the comparison results were employed as labels. The transmission equations approach is a better alternative to the GN model (or other similar margin-based models) in the absence of real data (i.e., at the deployment stage of a network) or the case that real data are scarce (i.e., for enriching the dataset/reducing probing lightpaths); furthermore, the three classifiers trained using the data of the transmission equations are more reliable and practical than those trained using the data of the GN model. Meanwhile, we noted that the priority of the three classifiers should be support vector machine (SVM)>K nearest neighbor (KNN)>logistic regression (LR) as shown in the results obtained by the transmission equations, instead of SVM>LR>KNN as in the results of the GN model.