Polyacrylonitrile–poly(1-vinyl pyrrolidone-co-vinyl acetate) blend based gel polymer electrolytes incorporated with sodium iodide salt for dye-sensitized solar cell applications

New gel polymer electrolytes (GPEs) were prepared via the blending of a polyacrylonitrile polymer and a poly(1-vinyl pyrrolidone-co-vinyl acetate) copolymer. The sodium iodide (NaI) salt concentration was varied for each GPE sample. From ionic conductivity (σ) studies, we observed that the sample with a 40 wt % NaI salt content (N40) showed the highest σ of 3.54 × 10⁻³ ± 0.05 S/cm at room temperature, and all of the GPE samples obeyed Arrhenius behavior. The dielectric properties of the GPE samples were also analyzed to study the electrical polarization of the materials. The developed GPE samples were also characterized with X-ray diffraction and Fourier transform infrared spectroscopy. We also then used the developed GPE samples for the fabrication of dye-sensitized solar cells by sandwiching them between a photoanode and Pt counter electrode for photovoltaic studies. The highest photovoltaic performance was achieved by N40, with an efficiency of 3.04%. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47810.     

Bias voltage effect on the dielectric properties of organic–inorganic blend SiNWs elaborated via metal assisted chemical etching

The electrical proprieties of poly (3-hexylthiophene): Silicon nanowires (P3HT: SiNWs) nanocomposite was investigated by impedance spectroscopy technique. The effect of bias voltage under and without illumination was discussed. Indeed, the imaginary part of the impedance shows a high relaxation frequency related to Maxwell–Wagner–Sillars (MWS) polarization. The relaxation time was found in the range of ms and it was shifted towards high frequency with increasing the bias voltage especially at 0.6 V At bias voltage equal to V_th and under illumination, the conductivity increases because the trapped charges acquire the necessary energy to escape from the interface and the hopping time found was reduced. This indicates a change of the conduction mechanism. The Cole–Cole diagram was excellently fitted through an equivalent circuit including a chemical capacitance Cµ, a contact electrical resistance Rs and recombination resistance Rp.     

Multispectral photodetection using low-cost sputtered NiO/Ag/ITO heterostructure: From design concept to elaboration

High-performance multispectral photodetectors (PDs) are highly attractive for the emerging optoelectronic applications. In this work, a new broadband PD based on p-NiO/Ag/n-ITO heterostructure was fabricated by RF magnetron sputtering technique at room temperature. The tri-layered structure offering multispectral detection property was first identified using theoretical calculations based on combined FDTD and Particle Swarm Optimization (PSO) techniques. The crystal structure of the elaborated sensor was analyzed using X-ray diffraction (XRD) method. The device optical properties were investigated by UV–Vis–NIR spectroscopy. The NiO/Ag/ITO heterostructured PD shows a high average absorbance of 63% over a wide spectrum range of [200 nm–1100nm]. Compared with NiO and ITO thin-films, the performances of the heterostructured device are considerably enhanced. It was found that the prepared PD with NiO/Ag/ITO heterostructure merges the benefits of multispectral photodetection with reduced optical losses and efficient transfer of photo-induced carrier. The device demonstrated a high I_ON/I_OFF ratio of 78 dB and an enhanced responsivity under UV, visible and NIR lights (171 mA/W at 365 nm, 67 mA/W at 550 nm and 93 mA/W at 850 nm). The broadband photodetection property enabled by the optimized NiO/Ag/ITO heterostructure opens a new route for the elaboration of low-cost devices that can offer multiple sensing purposes, which are highly suitable for optoelectronic applications.     

The Effect of Ti Addition on Microstructure and Magnetic Properties of Nanocrystalline FeAl40 Alloy Powders Prepared by Mechanical Alloying

Powder Metallurgy and Metal Ceramics - Recent research on nanocrystalline FeAl alloys has shown that these alloys are of high importance due to their promising structural and mechanical properties,...     

USAD: undetectable steganographic approach in DCT domain

In this work, we propose a new adaptive chaotic steganographic method based on the Discrete Cosine Transform (DCT) and a reversible mapping function. The mapping function is used to map the secret bits into their corresponding symbols. This mapping technique has to preserve the same dynamics, properties and distribution of the original DCT coefficients. The novelty of our approach is based on the adaptive selection phase of embedding spots. This selection is established through a blindness condition which is applied over each image of the database. The proposed embedding scheme within the middle DCT coefficients shows lower probability of detection and higher flexibility in extraction. We evaluate the detection of our method using the Ensemble Classifiers and a set of frequency and spatial domain feature extractors such as the Spatial domain Rich Model (SRM) features, Chen et al.'s 486-dimensional both inter- and intra-block Markov-based features and Liu's 216-dimensional adaptive steganography-based features.     

An improved machine learning technique based on downsized KPCA for Alzheimer's disease classification

Alzheimer's disease (AD), a neurodegenerative disorder, is a very serious illness that cannot be cured, but the early diagnosis allows precautionary measures to be taken. The current used methods to detect Alzheimer's disease are based on tests of cognitive impairment, which does not provide an exact diagnosis before the patient passes a moderate stage of AD. In this article, a novel classifier of brain magnetic resonance images (MRI) based on the new downsized kernel principal component analysis (DKPCA) and multiclass support vector machine (SVM) is proposed. The suggested scheme classifies AD MRIs. First, a multiobjective optimization technique is used to determine the optimal parameter of the kernel function in order to ensure good classification results and to minimize the number of retained principle components simultaneously. The optimal parameter is used to build the optimized DKPCA model. Second, DKPCA is applied to normalized features. Downsized features are then fed to the classifier to output the prediction. To validate the effectiveness of the proposed method, DKPCA was tested using synthetic data to demonstrate its efficiency on dimensionality reduction, then the DKPCA based technique was tested on the OASIS MRI database and the results were satisfactory compared to conventional approaches.     

Solution combustion synthesis of iron tungstate nanoparticles for photoelectrochemical water splitting towards oxygen evolution

Journal of Materials Science: Materials in Electronics - Iron tungstate (FeWO4) nanoparticles were prepared by simple solution combustion technique. The preparation method discloses the first...     

Probing entropic uncertainty relations under a two-atom system coupled with structured bosonic reservoirs

The uncertainty principle imposes constraints on an observer’s ability to make precision measurements for two incompatible observables; thus, uncertainty relations play a key role in quantum precision measurement in the field of quantum information science. Here, our aim is to examine non-Markovian effects on quantum-memory-assisted entropic uncertainty relations in a system consisting of two atoms coupled with structured bosonic reservoirs. Explicitly, we explore the dynamics of the uncertainty relations via entropic measures in non-Markovian regimes when two atomic qubits independently interact with their own infinite degree-of-freedom bosonic reservoir. We show that measurement uncertainty vibrates with periodically increasing amplitude with growing non-Markovianity of the observed system and ultimately saturates toward a fixed value at a long time limit. It is worth noting that there are several appealing conclusions raised by us: First, the uncertainty’s lower bound does not entirely depend on the quantum correlations within the two-qubit system, being affected by an interplay between the quantum discord and the minimal von Neumann conditional entropy \(\mathcal{S}_\mathrm{ce}\). Second, the dynamic characteristic of the measurement uncertainty is considerably distinctive with regard to Markovian and non-Markovian regimes, respectively. Third, the measurement uncertainty is closely correlated with the Bell non-locality \({\mathcal{B}}\). Moreover, we claim that the entropic uncertainty relation could be a promising tool with which to probe entanglement in current architecture.     

Attractor selection in a modulated laser and in the Lorenz circuit

By tuning a control parameter, a chaotic system can either display two or more attractors (generalized multistability) or exhibit an interior crisis, whereby a chaotic attractor suddenly expands to include the region of an unstable orbit (bursting regime).Recently, control of multistability and bursting have been experimentally proved in a modulated class B laser by means of a feedback method. In a bistable regime, the method relies on the knowledge of the frequency components of the two attractors. Near an interior crisis, the method requires retrieval of the unstable orbit colliding with the chaotic attractor.We also show that a suitable parameter modulation is able to control bistability in the Lorenz system. We observe that, for every given modulation frequency, the chaotic attractor is destroyed under a boundary crisis. The threshold control amplitude depends on the control frequency and the location of the operating point in the bistable regime. Beyond the boundary crisis, the system remains in the steady state even if the control is switched off, demonstrating control of bistability.