Application Point Of View Research Articles

Metal-organic framework and MXene (ZIF-8:Ti3C2Tx) based organic and inorganic nanocomposite for bio-synaptic applications

Organic and inorganic hybrid materials have drawn more interest in the field of electronic devices. The metal-organic frameworks (MOFs) have emerged as one of the promising hybrid materials for electronic devices. However, their limited electrical conductivity hinders their electronic applications. To overcome these shortcomings, we synthesized MOF:MXene nanocomposite to enhance the stability and electrical conductivity of MOF. In particular, we synthesized and characterized zeolitic imidazolate framework-8 (ZIF-8):MXene (Ti3C2Tx) hybrid nanocomposite. From the application point of view, we demonstrated the analog memory effect and mimicked various synaptic learning functionalities using Ag/ZIF-8:Ti3C2Tx/FTO resistive switching (RS) device. The fabricated device exhibits a good analog-type bipolar RS effect. The device mimics various bio-synaptic properties such as potentiation, depression, excitatory-post synaptic current, and paired-pulse facilitation (PPF) index (%). The inherent non-ideal memristor property was dominated in the device, owing to the double-valued charge-flux relation. The conduction and possible RS mechanisms of the Ag/ZIF-8:Ti3C2Tx/FTO device were reported. These results suggested that the ZIF-8:Ti3C2Tx nanocomposite is a potential nanomaterial for brain-inspired computing applications.

Expected Value of the Occupation Times of Brownian Motion

Occupation times of a stochastic process describes the amount of time the process spends inside a spatial interval during a certain finite time horizon. It appears in the fiber lay-down process in nonwoven production industry. The occupation time can be interpreted as the mass of fiber material deposited inside some region. From application point of view, it is important to know the average mass per unit area of the final fleece. In this paper derive an expression for the expected value of the occupation times in terms of Gaussian error functions.

New L-fuzzy fixed point techniques for studying integral inclusions

The survey of the available literature shows that a lot of important invariant point problems of Banach and Heilpern types have been examined in both metric and quasimetric spaces. However, a handful of the existing results employed the recent approaches of interpolative contractions. Therefore, based on the new idea of interpolation techniques in fixed point theory, this article studies new notions of L-fuzzy contractions and investigates conditions for the existence of L-fuzzy fixed points for such mappings. On the fact that fixed points of point-to-point mappings satisfying interpolative-type contraction are not always unique, whence making the concepts more fitted for invariant point results of crisp set-valued maps, new multi-valued analogues of the key findings put forward in this work are derived. Comparative illustrations, which indicate the preeminence of the results presented herein, are constructed. From application viewpoint, one of the theorems so obtained is employed to introduce new solvability conditions of Fredholm-type integral inclusions.

Recent Progress in Nonconventional Luminescent Macromolecules and their Applications.

Traditional π-conjugated luminescent macromolecules typically suffer from aggregation-caused quenching (ACQ) and high cytotoxicity, and they require complex synthetic processes. In contrast, nonconventional luminescent macromolecules (NCLMs) with nonconjugated structures possess excellent biocompatibility, ease of preparation, unique luminescence behavior, and emerging applications in optoelectronics, biology, and medicine. NCLMs are currently believed to produce inherent luminescence due to through-space conjugation of overlapping electron orbitals in solid/aggregate states. However, as experimental facts continue to exceed expectations or even overturn some previous assumptions, there is still controversy about the detailed luminous mechanism of NCLMs, and extensive studies are needed to further explore the mechanism. This Perspective highlights recent progress in NCLMs and classifies and summarizes these advances from the viewpoint of molecular design, mechanism exploration, applications, and challenges and prospects. The aim is to provide guidance and inspiration for the huge fundamental and practical potential of NCLMs.

The synthesis of the rare earth A2Zr2O7 single crystals by simplified laser-heated floating hot zone and pedestal methods

The condensed matter community is in constant search for efficient and feasible methods for the synthesis of diverse compounds, especially in the single-crystalline form. We present a recipe for the simplified synthesis of high-quality single crystals of rare-earth zirconates A2Zr2O7, important from both the fundamental and technical application viewpoints,. The developed preparation route allows to effectively, repeatedly, and reliably synthesise the high-quality precursors and single crystals of desired compositions, avoiding contamination and difficulties connected with standard polycrystalline-precursor preparation. Simultaneously, the method is straightforward, saving time, energy, and personnel. In addition to previously reported single crystals, several new single crystals from the A2Zr2O7 series were prepared, including the previously unreported compound Tm2Zr2O7. The high quality of the synthesised samples was proven employing electron microscopy, X-ray diffraction, laboratory and synchrotron radiation diffraction, and neutron powder and Laue diffraction techniques. The crystal structures and structural parameters of the individual compounds were determined and discussed in view of previous reports on A2Zr2O7 and other A2B2O7 series (B stands for d- or p-elements). The introduced synthesis route is proposed to serve well not only for several other A2B2O7 series, but also for a variety of unrelated compounds.

Adaptive control for memristive system via compensatory controller and Chebyshev neural network

In this paper, based on linear matrix inequality technique, a simple controller and a compensatory controller are designed. It can track arbitrary fixed points and any periodic orbits. In addition, a synchronization control method via Chebyshev neural network with external disturbances is proposed. An adaptive controller is given. The Chebyshev neural network is used to approximate the uncertain nonlinear function and the adaptive law is used to adjust the corresponding parameters in the system. Taking a 4D memristive chaotic system as examples, the results are in consistent with the simulations. From a framework and control theoretical point of view, the proposed synchronization approach via compensation controller and Chebyshev neural network is firstly presented. From an application point of view, the proposed scheme can simplify the complexity of controller design. It is promising in many applications for mem-systems as secure communications and neural networks.

Analysis of the implementation methods for emotion recognition in music based on machine learning

Music is a carrier of emotions, capable of triggering, expressing, and conveying people's innermost emotional experiences. With the development of digital technology, the recognition of emotions in music has been the subject of extensive research. From the viewpoint of application, MER is of great significance in music personalized recommendation services, psychotherapy, music creation, and music visualization. Currently, MER implementation methods based on machine learning are gradually becoming mainstream. This study starts from the basic knowledge of MER, first introduces the relevant research directions and research background of MER, and then proposes a three-part research framework combining MER and MEC. Based on this research framework, the machine learning algorithms and specific applications involved in the framework are introduced. Finally, the challenges and future paths facing the implementation of MER technology are proposed. Provide a reference for improving the accuracy and quality of using artificial intelligence methods to capture music characteristics and expressiveness.

Selective pressure leads to an improved synthetic consortium fit for dye degradation

Microorganisms have great potential for bioremediation as they have powerful enzymes and machineries that can transform xenobiotics. The use of a microbial consortium provides more advantages in application point of view than pure cultures due to cross-feeding, adaptations, functional redundancies, and positive interactions among the organisms. In this study, we screened about 107 isolates for their ability to degrade dyes in aerobic conditions and without additional carbon source. From our screening results, we finally limited our synthetic consortium to Gordonia and Rhodococcus isolates. The synthetic consortium was trained and optimized for azo dye degradation using sequential treatment of small aromatic compounds such as phenols that act as selective pressure agents. After four rounds of optimization with different aims for each round, the consortium was able to decolorize and degrade various dyes after 48 h (80%–100% for brilliant black bn, methyl orange, and chromotrop 2b; 50–70% for orange II and reactive orange 16; 15–30% for chlorazol black e, reactive red 120, and allura red ac). Through rational approaches, we can show that treatment with phenolic compounds at micromolar dosages can significantly improve the degradation of bulky dyes and increase its substrate scope. Moreover, our selective pressure approach led to the production of various dye-degrading enzymes as azoreductase, laccase-like, and peroxidase-like activities were detected from the phenol-treated consortium. Evidence of degradation was also shown as metabolites arising from the degradation of methyl red and brilliant black bn were detected using HPLC and LC-MS analysis. Therefore, this study establishes the importance of rational and systematic screening and optimization of a consortium. Not only can this approach be applied to dye degradation, but this study also offers insights into how we can fully maximize microbial consortium activity for other applications, especially in biodegradation and biotransformation.

Investigation of stabilization and survival of skyrmion vortices in the presence of magnetic field disorder in two-dimensional lattices: a case study for Janus dichalcogenides

Due to the lack of inversion symmetry, very large Dzyaloshinskii–Moriya interaction (DMI) has been reported for a series of Janus monolayers of manganese dichalcogenides within the framework of first-principles calculations (Liang et al 2020 Phys. Rev. B 101 184401). However, from the viewpoint of potential applications, the current ongoing research mainly focuses on the magnetism in pristine two-dimensional (2D) materials exhibiting non-zero DMI, and the effects of disorder in such systems remain an open problem since the influence of randomness may create some drastic effects on the magnetism of low dimensional systems. Here, we present Monte Carlo simulation results regarding the magnetic properties of a 2D manganese based Janus dichalcogenide material MnSTe in the presence of quenched random magnetic fields where the local field variables have been sampled from a Gaussian distribution. For the selected benchmark material, it has been found that the magnetic skyrmion vortexes emerging at (10 K, 3 T) may survive in the presence of weak and moderate quenched randomness, which is important from the viewpoint of technological applications. In both the pristine and random field cases, the stabilization of magnetic skyrmions are achieved by the major contribution of the ferromagnetic exchange energy to the total energy of the system, and the materials exhibiting large DMI/exchange ratios may exhibit resilient magnetic skyrmion vortexes in the presence of weak and moderate amount of randomness.

Novel design of composite broad-crested weir for determining open-channel emissions.

The current study deals with a composite broad-crested weir which is specially designed with the unique idea for a 'constant discharge coefficient (Cd) of 0.6'. It is investigated experimentally and numerically. The available designs of the weir are unable to give constant Cd over a wide range of discharge as 'Cd' itself is relative to the head over the weir crest. Therefore an attempt is made to restrict Cd value to 0.6 irrespective of the variable head on the weir crest. This is achieved by adjusting the widths of the weir. With the novel objective, Cd is frozen to constant value and instead of it, 'b' is allowed to vary. The weir so designed is capable of producing constant Cd over a wide range of discharge and hence will be helpful from the viewpoint of field applications. Under existing laboratory conditions, the research reports for emissions varying from 20 to 100% of the design discharge. The numerical performance of the CBC weir through FLOW 3D is experimentally validated to examine the crest width effect and head over weir crest. In the experiments, Cd is found to vary proportionally with discharge from 0.518 to 0.648. The R-value is 0.999, with a mean error in discharge measurement being much less.

Enhanced energy storage performance, breakdown strength, and thermal stability in compositionally designed relaxor Eu3+ substituted Na0.2K0.3Bi0.5TiO3

Lead-free Eu3+ substituted NKBT ceramics (Na0.2K0.3Bi0.5-xEuxTiO3, x = 0 (Eu 0),0.02(Eu 2),0.04(Eu 4), and 0.06(Eu 6)) were strategically designed via a local random field approach. The structural evolution had been confirmed through X-ray diffraction analysis. The observation of a broad dielectric curve supported the enhanced relaxor nature and the phenomena reflected in the P-E and S-E loops. The diffuse phase transition transforms to the plateau-type feature with excellent thermal stability with ±20 % and ± 40 % variation in dielectric constant over the temperature range of 120 to 500 °C and 90 to 500 °C, respectively in Eu 4. A large recoverable energy density of 1.7 J/cm3 with a high breakdown strength of 188 kV/cm was achieved in the Eu 2 sample at room temperature, making it a potential candidate for energy storage application. Moreover, the frequency stability (0.1 to 500 Hz range), thermal stability (45 °C to 85 °C), and fatigue measurement (10−1 to 106 cycles) were performed from the application point of view. The highest efficiency (82 %) was also achieved in the Eu 6. The negligible Sneg of Eu-rich compositions proves the existence of a relaxor state when the field is removed, and it transforms into the ergodic relaxor state. Furthermore, the SRBRF model is exploited to understand and correlate the transformation from normal to relaxor ferroelectrics with their properties. The current study provides a novel idea for compositional design for energy density, efficiency, and thermal stability ceramics by modifying and creating weakly coupled polar phases with rare earth substitution.

Architecture for Surface-Emitting Lasers with On-Demand Lasing Wavelength by Nanowire Optical Cavities.

Despite the importance and exciting progress of surface-emitting (SE) semiconductor lasers, we have limited choices of lasing wavelength even today. From an application viewpoint, it is desirable to have an architecture that can allow SE lasing in a wide spectral range, based on the need of applications. Herein, we demonstrate a path for SE lasers with lasing wavelength on demand by exploiting III-nitride nanowire optical cavities formed by low-temperature selective area epitaxy (SAE), combined with fine-tuning of substrate patterns and photonic bands. Moreover, in this study, we focus on the device demonstration in the ultraviolet (UV) spectral range, considering the severe lag in developing SE lasers in the UV wavelength range compared to longer wavelengths, e.g., near-infrared (NIR), as well as the potential applications enabled by UV lasers such as solar blind optical wireless communications. Ultralow threshold wavelength-tunable SE UV lasing is achieved by optical pumping. Moreover, SE UV lasing under direct electric current injection is also achieved. This study not only represents an important step in the journey of SE UV laser development but, more importantly, it lays the ground for SE lasers with lasing wavelength on demand, broadly from NIR to UV.

Broadband terahertz absorber based on patterned slotted vanadium dioxide

This study aims to explore broadband terahertz absorbers based on metamaterials by introducing a design featuring patterned slotted vanadium dioxide. This absorber structure includes a vanadium dioxide resonator layer, an intermediate Topas dielectric layer, and an underlying metal reflector layer. To enhance the absorption bandwidth, the vanadium dioxide resonant layer is strategically patterned to optimize impedance matching. Simulation outcomes reveal that, under positive incidence, the absorption rate exceeds 90 % within the frequency range of 1.5–4.2 THz. The absorber demonstrates a substantial absorption bandwidth of 2.7 THz, centered at 2.85 THz, corresponding to a relative bandwidth of 94.7 %. Additionally, through modulation of the conductivity of vanadium dioxide, the absorption peak can be finely tuned, spanning from approximately 2.5 %–99 %. In addition, it's angularly symmetrical and exhibits absorption properties for wide-angle incidence. The tunable terahertz absorber designed in this paper simultaneously achieves high absorption over a wide frequency range, is dynamically tunable, and has a simple structure. From the application point of view, it can provide a way to realize detection, and imaging in the terahertz range.

Influence of grain boundary plane distribution on ionic conductivity in yttria-stabilized zirconia sintered at elevated temperatures

The paper investigates electrical properties of fully stabilized zirconia, which is widely applied as a solid electrolyte in electrochemical devices such as solid oxide fuel cells. High ionic conductivity of these materials is crucial for effective operating of the devices; however, grain boundary resistivity limits conductivity in polycrystalline ceramics. Thus, optimisation of the microstructure of zirconia is necessary from an application point of view. Based on three-dimensional electron backscatter diffraction (3D EBSD) data, the research employed a complex impedance spectroscopy to establish a correlation between microstructure of cubic zirconia sinters and their conductivity. Samples with different levels of anisotropy in grain boundary plane parameters were investigated. The obtained results indicate that the conduction of ions through the grain boundaries is higher in the sample with the higher representation of the near-(001) grain boundaries. Such a relationship suggests that an over-representation of low-energy grain boundaries in zirconia polycrystals leads to an increase of ionic conductivity.

Analytical Solution of Generalized Bratu-Type Fractional Differential Equations Using the Homotopy Perturbation Transform Method

In this study, we present the generalized form of the higher-order nonlinear fractional Bratu-type equation. In this generalization, we deal with a generalized fractional derivative, which is quite useful from an application point of view. Furthermore, some special cases of the generalized fractional Bratu equation are recognized and examined. To solve these nonlinear differential equations of fractional order, we employ the homotopy perturbation transform method. This work presents a useful computational method for solving these equations and advances our understanding of them. We also plot some numerical outcomes to show the efficiency of the obtained results.

Optomechanical methodology for characterizing the thermal properties of 2D materials

Heat transport in two dimensions is fundamentally different from that in three dimensions. As a consequence, the thermal properties of 2D materials are of great interest, from both scientific and application points of view. However, few techniques are available for the accurate determination of these properties in ultrathin suspended membranes. Here, we present an optomechanical methodology for extracting the thermal expansion coefficient, specific heat, and thermal conductivity of ultrathin membranes made of 2H-TaS2, FePS3, polycrystalline silicon, MoS2, and WSe2. The obtained thermal properties are in good agreement with the values reported in the literature for the same materials. Our work provides an optomechanical method for determining the thermal properties of ultrathin suspended membranes, which are difficult to measure otherwise. It provides a route toward improving our understanding of heat transport in the 2D limit and facilitates engineering of 2D structures with a dedicated thermal performance.

Electric chiral magnonic resonators utilizing spin–orbit torques

The recently proposed concept of electric chiral magnonic resonator (ECMR) has been extended to include usage of spin–orbit torques (SOT). Unlike the original version of ECMR which was based on voltage controlled magnetic anisotropy (VCMA), the spin wave amplification power by this new version of ECMR (pumped by SOT) no longer depends on the phase of the incident wave, which is highly desirable from an application point of view. The performance of the SOT pumped ECMR has been compared with the case of amplification by applying SOT pumping directly to a waveguide (without any ECMR involved). It is argued that at the expense of narrowing the bandwidth (i.e., slower amplifier response), the advantage of the former configuration (amplification by a SOT pumped ECMR) over the latter (amplification by direct SOT pumping the waveguide) is to offer gain, while at the same time, maintaining system stability (avoidance of auto-oscillations). Non-linear behavior of the SOT pumped ECMR has been analyzed. It is demonstrated that by cascading a SOT ECMR operating in an off-resonance mode together with a VCMA biased passive ECMR, it is possible to produce a magnonic neuron with a transmitted signal magnitude larger than the input in the firing state.

Designing of novel microstructure and its impact on the improved service temperature mechanical performance of 2nd and 3rd generation advanced intermetallic TiAl alloys

Advanced lightweight TiAl based intermetallic systems, capable of surviving elevated temperatures, have been a topic of interest, considering their ever-increasing demands in aerospace industries. The optimization of solidification and processing methods stands as a pivotal factor in microstructural engineering for TiAl systems, aiming to attain desired mechanical properties. The present study focuses on two distinct alloy systems, a commercial grade 2nd generation, i.e., Ti–48Al–2Cr–2Nb (at. %), and a newly developed 3rd generation, i.e., Ti–45Al–2Cr-7.5Nb-0.2B (at. %) alloys. Interestingly, the variation in the solidification path, triggered by higher Nb content along with a minor amount of B, accounts for the substantial microstructural refinement for the 3rd generation TiAl alloy. Nevertheless, prominent segregation of Nb and Cr to the β0 phase is observed in both the as-cast microstructure, which restricts the applicability of the alloys. Remarkably, a novel bilamellar-biglobular (BLBG) microstructure consisting of γ and α2 phases in both lamellar and globular morphologies is achieved through heat treatment for both categories of alloy. Elevated temperature tensile testing depicts an exceptional strength-ductility combination for 3rd generation BLBG microstructure. Excellent twin-twin activity and twin-induced plasticity effect are observed to govern the deformation mechanism. Overall, the path of solidification, phase distribution, and its effect on the deformation mechanism are thoroughly analyzed, which is of particular interest from a design and application point of view.

Review of Prediction of Stress Corrosion Cracking in Gas Pipelines Using Machine Learning

Pipeline integrity and safety depend on the detection and prediction of stress corrosion cracking (SCC) and other defects. In oil and gas pipeline systems, a variety of corrosion-monitoring techniques are used. The observed data exhibit characteristics of nonlinearity, multidimensionality, and noise. Hence, data-driven modeling techniques have been widely utilized. To accomplish intelligent corrosion prediction and enhance corrosion control, machine learning (ML)-based approaches have been developed. Some published papers related to SCC have discussed ML techniques and their applications, but none of the works has shown the real ability of ML to detect or predict SCC in energy pipelines, though fewer researchers have tested their models to prove them under controlled environments in laboratories, which is completely different from real work environments in the field. Looking at the current research status, the authors believe that there is a need to explore the best technologies and modeling approaches and to identify clear gaps; a critical review is, therefore, required. The objective of this study is to assess the current status of machine learning’s applications in SCC detection, identify current research gaps, and indicate future directions from a scientific research and application point of view. This review will highlight the limitations and challenges of employing machine learning for SCC prediction and also discuss the importance of incorporating domain knowledge and expert inputs to enhance the accuracy and reliability of predictions. Finally, a framework is proposed to demonstrate the process of the application of ML to condition assessments of energy pipelines.

Reliability estimation for Kumaraswamy distribution under block progressive type-II censoring

In this article, estimates of reliability performance characteristics are discussed when life test is conducted upon various test facilities under block progressive type-II censoring. When the differences in different test facilities are taken into account and lifetime of products follows a distribution with Kumaraswamy hazard function, different estimates are obtained from classical and hierarchical Bayesian frameworks, respectively. The existence and uniqueness of maximum likelihood estimators of model parameters are established, and approximate confidence intervals are obtained as well based on asymptotic theory and delta method. Moreover, associated Bayes estimators are also evaluated using a hybrid Metropolis–Hasting sampling in hierarchical framework. Finally, performances of the proposed approaches are compared via extensive simulation study, and two real data examples are also presented for application viewpoint.