Interest For Many Applications Research Articles

Boosting visible light photocatalysis in an Au@TiO2 yolk-in-shell nanohybrid

Yolk-shell nanohybrids have garnered increasing interests in many applications, such as in catalysis, energy, and molecular sensing. However, their intrinsic architectural limitations have led to insufficient synergistic effects and instability which are unfavorable for nanocatalysis. Designing a unique yolk-in-shell nanostructure where the “yolk” is embedded in the “shell” can overcome this challenge to boost nanocatalysis. Herein, an unprecedented Au@TiO2 yolk-in-shell nanocatalyst has been developed to dramatically improve the visible light photocatalysis. The as-designed Au@TiO2 nanohybrid displays an efficient hydrogen-production (95.6 mmol h-1 g-1, Au: 0.04 wt%), 3- and 14-times better than conventional Au@TiO2 yolk-shell nanostructure and pure TiO2 hollow nanosphere, respectively. Our unique design also notably achieves high selectivity (~100%) towards CO production (0.75 mmol h-1 g-1) under visible light irradiation. This unique yolk-in-shell nanoarchitecture promises enormous opportunities for the design of next-generation hybrid nanocatalysts with enhanced catalytic performances.

Magnetic-field-induced acicular nickel immobilized on carbon nanofibers as electrodes for electrochemical glucose sensing

BackgroundEffective high-throughput strategies to prepare nanostructured electrodes for glucose sensing remain significant interest for many applications. In this study, acicular nickel was immobilized on carbon nanofibers (CNFs) via electroless plating under a magnetic field to form CNFs-Ni, and its application as an electrode in amperometric non-enzymatic glucose sensing was investigated. MethodsPolyacrylonitrile (PAN) nanofibers (NFs) were fabricated by centrifuged-electrospinning, in which the combination of electrostatic and centrifugal forces produces a strong stretching force. PAN polymer chains were aligned parallel to the axis of the NFs, thereby stretching the dispersed PAN droplets into thin and molecularly orientated NFs. The PAN NFs were then subjected to stabilization followed by carbonization at 1200, 1300, 1400, or 1500 °C to produce PAN CNFs. The characteristics of the CNFs were confirmed by scanning electron microscopy (SEM), electron spectroscopy for chemical analysis, Raman spectroscopy, and four-point probe analysis. Additionally, the CNFs coated with acicular nickel (CNFs-Ni) were analyzed by SEM, X-ray diffraction, and high-resolution transmission electron microscopy. Significant FindingsUnder the optimal conditions (CNFs1400-Ni), the glucose sensor showed a high sensitivity (7404 μA mM−1 cm−2) with a linear range from 2.1 × 10−2 to 6.0 × 10−1 mM (R2 = 0.993) and fast response (10 s).

Development of Amino Acids Functionalized SBA-15 for the Improvement of Protein Adsorption.

Ordered mesoporous materials and their modification with multiple functional groups are of wide scientific interest for many applications involving interaction with biological systems and biomolecules (e.g., catalysis, separation, sensor design, nano-science or drug delivery). In particular, the immobilization of enzymes onto solid supports is highly attractive for industry and synthetic chemistry, as it allows the development of stable and cheap biocatalysts. In this context, we developed novel silylated amino acid derivatives (Si-AA-NH2) that have been immobilized onto SBA-15 materials in biocompatible conditions avoiding the use of toxic catalyst, solvents or reagents. The resulting amino acid-functionalized materials (SBA-15@AA) were characterized by XRD, TGA, EA, Zeta potential, nitrogen sorption and FT-IR. Differences of the physical properties (e.g., charges) were observed while the structural ones remained unchanged. The adsorption of the enzyme lysozyme (Lyz) onto the resulting functionalized SBA-15@AA materials was evaluated at different pHs. The presence of different functional groups compared with bare SBA-15 showed better adsorption results, for example, 79.6 nmol of Lyz adsorbed per m2 of SBA-15@Tyr compared with the 44.9 nmol/m2 of the bare SBA-15.

A General Strategy toward Metal Sulfide Nanoparticles Confined in a Sulfur-Doped Ti3 C2 Tx MXene 3D Porous Aerogel for Efficient Ambient N2 Electroreduction.

Three-dimensional (3D) porous MXene-based aerogel architectures have attracted great interest for many applications, despite limits in renewable energy conversion owing to the lack of multifunctionality in their components. Herein, a simple and general strategy for constructing a novel functional 3D MXene-based composite heterojunction aerogel (MS@S-MAs) is presented via divalent metal-ion assembly and subsequent thermal sulfidation, and its application in electrochemical nitrogen reduction reaction (NRR) is studied. The as-prepared MS@S-MAs comprises metal sulfide nanoparticles uniformly confined in 3D interconnected conductive S-doped MXene sheets with intimate interfacial interaction. Benefiting from the unique properties and an interfacial interaction, MS@S-MAs exhibit significantly improved NRR catalytic performance and excellent stability because of the higher exposure of electrochemically active sites coupled with easier accessibility, faster mass diffusion, and quicker carrier transport at the interface. Remarkably, CoS@S-MAs show an NH3 yield rate and a Faradaic efficiency of 12.4 µg h-1 mg-1 cat and 27.05% at the lower potential of -0.15V versus a reversible hydrogen electrode in 0.1 m Na2 SO4 solution under ambient conditions, which rivals or exceeds most of the previously reported MXene-based and Co-based catalysts. This work will open avenues to construct 3D MXene-based materials with rich functionalities for energy storage and conversion, catalysis, and other applications.

Delay Independent Stability Control for Commensurate Multiple Time-Delay Systems

Commensurate Multiple Time-Delay Systems (CMTDSs) are of considerable interest for many applications, ranging from process control to decision-making systems. A stable CMTDS can become unstable when a small delay is introduced and vice-versa. The letter proposes an innovative controller design procedure for CMTDSs, able to transform the system into a Delay Independent Stable System (DISS). A controller based on a single parameter is used to make the system DISS. The controller gain may be determined by adopting different strategies, either analytical or graphical. Several case studies are reported to illustrate and validate the approach.

Highly Conductive Ceramics with Multiple Types of Mobile Charge Carriers

Functional ceramic materials are of interest in many applications due to their structural and chemical richness and the huge range of physical properties that can be generated and modified by the control of the former (electrical conductivity, thermo-mechanical properties, dielectric, piezoelectric, ferroelectric properties, etc [...]

Effects of O2 and H2O on TiO2 photocatalytic mass loss self-cleaning efficiency for thin hydrocarbons layers

The self-cleaning properties provided by photocatalytic reactions have raised a lot of interest for many applications. Nowadays, the widespread analysis methods to study photocatalytic self-cleaning comprise mainly indirect methods such as UV–VIS spectroscopy, chromatography or contact angles measurements. Quartz Crystal Microbalance is another appropriate way to study how the surface is decontaminated because it has the advantage to directly measure the reactant mass. In this study the latter was used to investigate various parameters such as mass loss kinetics, effect of photocatalyst or contaminant effective thicknesses, illumination flux … A special attention was paid to the effects of humidity and O2 on the photocatalytic removal of nanometric paraffin oil (hydrocarbons) films over TiO2. QCM measurements were carried out for several H2O and O2 relative contents in the exposure. Ultimately, water is not essential but acts as a reaction promoter while O2 tends to be essential without significantly affecting the photocatalytic rate provided it is present in sufficient amount. Considering these observations and potential degradation pathways of paraffin oil hydrocarbons, the role of H2O and O2 is discussed.

Microalgae as Contributors to Produce Biopolymers.

Biopolymers are very favorable materials produced by living organisms, with interesting properties such as biodegradability, renewability, and biocompatibility. Biopolymers have been recently considered to compete with fossil-based polymeric materials, which rase several environmental concerns. Biobased plastics are receiving growing interest for many applications including electronics, medical devices, food packaging, and energy. Biopolymers can be produced from biological sources such as plants, animals, agricultural wastes, and microbes. Studies suggest that microalgae and cyanobacteria are two of the promising sources of polyhydroxyalkanoates (PHAs), cellulose, carbohydrates (particularly starch), and proteins, as the major components of microalgae (and of certain cyanobacteria) for producing bioplastics. This review aims to summarize the potential of microalgal PHAs, polysaccharides, and proteins for bioplastic production. The findings of this review give insight into current knowledge and future direction in microalgal-based bioplastic production considering a circular economy approach. The current review is divided into three main topics, namely (i) the analysis of the main types and properties of bioplastic monomers, blends, and composites; (ii) the cultivation process to optimize the microalgae growth and accumulation of important biobased compounds to produce bioplastics; and (iii) a critical analysis of the future perspectives on the field.

Parahydrogen-Induced Polarization of Amino Acids.

Nuclear magnetic resonance (NMR) has become a universal method for biochemical and biomedical studies, including metabolomics, proteomics, and magnetic resonance imaging (MRI). By increasing the signal of selected molecules, the hyperpolarization of nuclear spin has expanded the reach of NMR and MRI even further (e.g. hyperpolarized solid‐state NMR and metabolic imaging in vivo). Parahydrogen (pH2) offers a fast and cost‐efficient way to achieve hyperpolarization, and the last decade has seen extensive advances, including the synthesis of new tracers, catalysts, and transfer methods. The portfolio of hyperpolarized molecules now includes amino acids, which are of great interest for many applications. Here, we provide an overview of the current literature and developments in the hyperpolarization of amino acids and peptides.

Microwave Photonic I/Q Mixer With Phase Shifting Ability

A compact system with multiple signal processing functions is of interest in many applications. The purpose of this paper is to present a microwave photonic structure that is capable of simultaneously realising in-phase/quadrature (I/Q) mixing and phase shifting operations. The multi-function signal processor has a simple structure and can be constructed using off-the-shelf components. It is designed to enable commercial modulator bias controllers to be incorporated into the system to provide accurate phase shift and to improve system stability. Non-ideal effects in the system that cause deviation in the two output IF signal phase difference from 90° can be mitigated by adjusting a modulator bias voltage. The multi-function signal processor is theoretically analysed and experimentally demonstrated. Its performance including two output IF signals with a quadrature phase difference, wideband operation, continuous 0° to 360° IF signal phase shift and long-term stable operation are verified experimentally.

Sub-Pixel Scanning High-Resolution Panoramic 3D Imaging Based on a SPAD Array

3D imaging based on single-photon avalanche diode (SPAD) arrays is of interest in many applications. Limited by the small array size and low fill-factor of the available SPAD array, it is difficult for SPAD array-based lidars to achieve high-resolution and high-quality 3D images currently. Here, we propose a sub-pixel continuously scanning panoramic 3D imaging method. This method uses sub-pixel scanning to increase spatial resolution and employs accumulating photon counts at the different pixel of the array for the same target point to improve 3D image quality. We have established an experimental system based on a 32 × 32 SPAD array and a diffraction optical element (DOE) with 32 × 32 beamlet. By sub-pixel scanning for a target 3 m away and accumulating photon counts, we demonstrated that the spatial resolution has been improved from 3 mm to 0.33 mm and the 3D image quality has been improved evidently.

Ultra-fast fiber Bragg grating inscription in CYTOP polymer optical fibers using phase mask and 400 nm femtosecond laser.

Fiber Bragg gratings (FBGs) in cyclic transparent fluoropolymer (CYTOP) optical fiber are the subject of a lot of research as they can be of interest for many applications, such as temperature, humidity, strain, and radiation sensing. We report here a new technique to produce high quality FBGs in CYTOP fiber. It uses a femtosecond laser system operating at 400 nm and a phase mask. In contrast to previously reported results, the gratings are obtained in a few seconds with a writing power as low as 80 μW. With this setup, 2 mm-long gratings with reflectivity up to 92 % and full width at half maximum bandwidth around 0.5 nm were obtained in less than 10 s. The resonance wavelengths of the FBGs are confirmed by numerical computation in the graded-index multimode CYTOP fiber, and the mode selection characteristic of FBGs in CYTOP is investigated. Finally, the temperature sensitivity of CYTOP FBG is measured in different mode groups for heating up and cooling down, showing values independent of the mode group measured, but with a small hysteresis.

Optimisation of an ultrasonic torsion fatigue system for high strength materials

The bearable shear stress amplitude in very high cycle fatigue regime (VHCF) is of interest for many applications in mechanics (springs, crankshafts, ball bearings, etc.) when a very high repetition of load cycles occur. This paper proposes to optimise an existing torsion gigacycle fatigue testing system, developed fifteen years ago by the Pr C. Bathias’ research team. The aim is to increase the shear stress amplitude applied to the investigated specimen and, consequently, meet the expectations from industries about fatigue life for high strength materials under shear loading. The system differs from other ultrasonic torsion fatigue machines that can be found in the literature, by the combination of two amplification horns, transforming a translation movement into a rotational one. In this work, there are two optimisation objective functions: (i) maximize the shear stress level in the specimen and (ii) minimize the stress level in the fatigue system and mainly in the pin connecting the two horns. The development of the optimised device is essentially carried out by a parametric study and numerical simulations through modal and harmonic analysis. Numerical results are compared with the analytical 1D solution and with experimental results obtained from the new real experimental set-up. Finally, new results in the gigacycle domain are presented concerning the torsion fatigue strength of high strength steels (50CrV4 and 16MnCr5) and discussed.

A Novel Scheme for Real-Time Max/Min-Set-Selection Sorters on FPGA

Partial sorting, selecting M largest/smallest numbers from N inputs, is of interest in many applications. Thus, this brief presents a novel scheme for real-time max/min-set-selection sorters on field-programmable gate arrays (FPGAs). Our scheme has good expansibility but no close relation with the vector length, whose basic idea is reducing the programming complexity through the essence of sorting networks for Bitonic sequences. In addition, two modified forms of our scheme are proposed to solve the high data rate sequence and a multiple of 2 max/min-set-selection problem respectively. Finally, the effectiveness of our scheme is demonstrated on one Xilinx XC7VX690T FPGA by performing comparisons with state-of-the-arts.

Full depth CNN classifier for handwritten and license plate characters recognition

Character recognition is an important research field of interest for many applications. In recent years, deep learning has made breakthroughs in image classification, especially for character recognition. However, convolutional neural networks (CNN) still deliver state-of-the-art results in this area. Motivated by the success of CNNs, this paper proposes a simple novel full depth stacked CNN architecture for Latin and Arabic handwritten alphanumeric characters that is also utilized for license plate (LP) characters recognition. The proposed architecture is constructed by four convolutional layers, two max-pooling layers, and one fully connected layer. This architecture is low-complex, fast, reliable and achieves very promising classification accuracy that may move the field forward in terms of low complexity, high accuracy and full feature extraction. The proposed approach is tested on four benchmarks for handwritten character datasets, Fashion-MNIST dataset, public LP character datasets and a newly introduced real LP isolated character dataset. The proposed approach tests report an error of only 0.28% for MNIST, 0.34% for MAHDB, 1.45% for AHCD, 3.81% for AIA9K, 5.00% for Fashion-MNIST, 0.26% for Saudi license plate character and 0.97% for Latin license plate characters datasets. The license plate characters include license plates from Turkey (TR), Europe (EU), USA, United Arab Emirates (UAE) and Kingdom of Saudi Arabia (KSA).

Broadband decoupling of intensity and polarization with vectorial Fourier metasurfaces

Intensity and polarization are two fundamental components of light. Independent control of them is of tremendous interest in many applications. In this paper, we propose a general vectorial encryption method, which enables arbitrary far-field light distribution with the local polarization, including orientations and ellipticities, decoupling intensity from polarization across a broad bandwidth using geometric phase metasurfaces. By revamping the well-known iterative Fourier transform algorithm, we propose “à la carte” design of far-field intensity and polarization distribution with vectorial Fourier metasurfaces. A series of non-conventional vectorial field distribution, mimicking cylindrical vector beams in the sense that they share the same intensity profile but with different polarization distribution and a speckled phase distribution, is demonstrated. Vectorial Fourier optical metasurfaces may enable important applications in the area of complex light beam generation, secure optical data storage, steganography and optical communications.

A THz Metamaterial Absorber with Multiple Polarization - Insensitive, Sensitive, and Tunable

Terahertz (THz) absorbers are gaining interest in many applications. In this paper, we present the design and simulation of a multiband metamaterial absorber (MMA) with combined polarization properties and prominent absorption at 2.2 THz and 3.9 THz. The MMA comprises two square split-ring resonators and one square ring resonator placed on top of a polyimide dielectric spacer, offering multiband absorption characteristics with maximum absorptivity of 93.18% and 96.09%, respectively. The most protruding feature of this design is that it displays multiple polarization characteristics, including insensitivity, sensitivity, and tunability, even though the structure is similar to those of conventional absorbers. Firstly, the distinctly visible absorption spectra at 1.8 THz, gradually diminishes with an increase in polarization angle and then completely vanishes for TM polarization. Secondly, the prominent band at 2.2 THz is insensitive to changes in polarization of the incident wave, whereas, at 3.9 THz, the absorption band displays polarization tunability characteristics. Due to the multiple characteristics displayed by the structure, this MMA can be simultaneously used for several applications in the terahertz frequency regime such as imaging, terahertz spectroscopy, sensing, and stealth technology.

WO3 Nanoparticles and Nanoflakes Based Sensors for Selective Detection of Alcohols

Ethanol is an important chemical raw material widely used in chemical industry, medicine, cosmetics, paints, and biofuels [1]. It is volatile and flammable and a human exposure to its vapours could result in headache, drowsiness, irritation of eyes and difficulty in breathing. It derives that the precise quantitative detection of ethanol vapours is of interest for many applications. Different studies were focused on semiconducting metal oxides as sensing materials for the selective ethanol detection. It is well known that, despite their high stability over time and the low cost of production, these semiconductors suffer of low selectivity, which affects their effective use for real applications.Among the wide palette of the metal oxides, tungsten oxide (WO3) is an important intrinsic n-type wide gap semiconductor, which has attracted considerable attention to detect various hazardous gases. However, it is still challenging to significantly enhance the sensibility and selectivity of WO3 based gas sensors by tuning its crystal structures, morphology and adding dopants [2]. WO3 can be a promising candidate for alcohols detection for the presence of acidic sites that can promote the alcohol decomposition through dehydration [3].In this work, the synthesis of WO3 nanoflakes (WO3-NF) was achieved via solvothermal route [4]. The peculiar morphology was characterized by SEM microscopy. XRD analysis reveals that the investigated sample is biphasic, composed by triclinic (s.g. P-1) and hexagonal (s.g. form with P63/mcm) WO3 with a phase fraction of about 97 and 3 wt.%, respectively.Sensing performance of the WO3-NF were studied and compared to those of WO3 nanoparticles synthetized by precipitation method. Tested sensors were realized by screen-printing of the functional material on alumina substrates with interdigitated electrodes. After a systematic investigation on the optimal working temperature, WO3 based sensors were tested at 250°C and 300°C for WO3-NF and WO3-NP, respectively. Gas measurements were performed testing the WO3-based sensors towards various gaseous molecules: H2S (10 ppm), H2 (50 ppm), CO (35 ppm), NO2 (1 ppm), NH3 (2 ppm) and different concentrations of methanol, ethanol and butanol (5-10, 25, 50 ppm). The sensing analysis indicates that the WO3-NF is sensitive towards alcohols, remarkably to ethanol, with negligible responses to other analytes.Fig. 1a, where the dynamic response to different concentration of ethanol for WO3-based sensors is shown, clearly highlights the enhanced sensing performance of the WO3-NF based sensor when compared to that of the WO3-NP. The influence of humidity on WO3-based sensors exposed to ethanol was also investigated (Fig. 1b). Even at low ethanol concentration (5 ppm), the influence of water vapour is limited, and after a partial drop up to 30 RH%, the WO3-based sensors performance seems to reach a stabilization, and no variations are observed up to 60 RH%. Noteworthy, the WO3-NF response to ethanol is always more than two times higher when compared to that of WO3-NP. The sensing response towards 50 ppm of methanol, ethanol and butanol are shown in Fig. 1c. While WO3-NP sensibility increases with the length of the alcohol chain, this trend is not observed for WO3-NF, which has higher response for ethanol. This peculiar behaviour will be the object of further investigation.

A biomimetic skin-like sensor with multiple sensory capabilities based on hybrid ionogel

In the past decades, biomimetic skin-like materials have received increasing research interests for many applications in flexible devices, soft robotics and artificial intelligence. However, such highly sophisticated intelligence has been mainly found in natural creatures while rarely realized in artificial materials, owing to the challenge in integration of multifaceted mechanical performances and multiple sensory capabilities. Herein, a novel hybrid ionogel is developed by combining a dynamically entangled network with a covalently crosslinked network in an ionic liquid. The dynamically entangled network provides the hybrid ionogel with a wide spectrum of mechanical properties including high stretchability, recoverability, self-healing and 3D printability. The functional groups (hydroxyl and carbonyl) from polymer chains endow the hybrid ionogel with long-term and repeatable adhesiveness. More importantly, the assembled hybrid ionogel-based sensory systems demonstrate multiple sensory capabilities toward strain, temperature, and even recognition of various materials. This work not only provides insights for the fabrication of novel multifunctional ionogel, but also promotes the development of flexible devices with sophisticated intelligence.

Modeling Bacterial Adhesion to Unconditioned Abiotic Surfaces

Understanding bacterial adhesion as a first step toward biofilm formation is of fundamental interests in many applications. While adhesion to abiotic surfaces is directly relevant for some applications, it also provides a controlled reference setting to study details of the adhesion process in general. This review describes the traditional approaches from contact mechanics and colloidal science, which treat the bacterium–substratum interaction in a continuous manner. We will discuss its shortcomings and provide an introduction to different approaches, which understand the adhesion process as a result of individual stochastic interactions of many macromolecules with the substratum.