Structural evolution and dopant occupancy preference of yttrium-doped potassium sodium niobate thin films

Sodium potassium niobate (KNN) is the most promising candidate for lead-free piezoelectric material, owing to its high Curie temperature and piezoelectric coefficients among the non-lead piezoelectric. Numerous studies have been carried out to enhance piezoelectric properties of KNN through composition design. This research studied the effects of yttrium concentrations and lattice site occupancy preference in KNN films. For this research, the yttrium-doped KNN thin films (mol% = 0, 0.1, 0.3, 0.5, 0.7 and 0.9) were fabricated using the sol-gel spin coating technique and had revealed the orthorhombic perovskite structures. Based on the replacement of Y³⁺ ions for K⁺/ Na⁺ ions, it was found that the films doped with 0.1 to 0.5 mol% of yttrium had less lattice strain, while films with more than 0.5 mol% of Y³⁺ ions had increased strain due to the tendency of Y³⁺ to occupy the B-site in the perovskite lattice. Furthermore, by analysing the vibrational attributes of octahedron bonding, the dopant occupancy at A-site and B-site lattices could be identified. O-Nb-O bonding was asymmetric and became distorted due to the B-site occupancy of yttrium dopants at high dopant concentrations of >0.5 mol%. Extra conduction electrons had resulted in better resistivity of 2.153× 10⁶ Ω at 0.5 mol%, while higher resistivity was recorded for films prepared with higher concentration of more than 0.5 mol%. The introduction of Y³⁺ improved the grain distribution of KNN structure. Further investigations indicated that yttrium enhances the surface smoothness of the films. However, at high concentrations (0.9 mol%), the yttrium increases the roughness of the surface. Within the studied range of Y³⁺ _, the film with 0.5 mol% Y³⁺ represented a relatively desirable improvement in dielectric loss, tan δ and quality factor, Q_m.     

Transient analysis of diffusion least‐mean squares adaptive networks with noisy channels

In this paper, we study the effect of noisy channels on the transient performance of diffusion adaptive network with least‐mean squares (LMS) learning rule. We first drive the update equation of diffusion LMS which incorporates the effects of noisy channels. Then, using the framework of fundamental weighted energy conservation relation, we derive closed‐form expressions for learning curves in terms of mean‐square deviation and excess mean‐square error. We also find the mean and mean‐square stability bounds of step‐size for diffusion LMS with noisy channels. We show that although noisy channels affect the performance of the diffusion LMS network, the stability bounds of the step‐size are the same form as in the ideal channels case. The derived closed‐form expressions are shown to provide a good match with values found by simulation. Copyright © 2011 John Wiley & Sons, Ltd.     

Investigating the wicking behavior of micro/nanofibrous core-sheath PET–PAN yarn modified by dimethyl 5-sodium sulfoisophthalate

The present research aims at imparting an improved wicking ability to the recycled multifilament yarns by wrapping composite nanofibers to attain an efficient material for filtration purposes. Therefore, polyacrylonitrile nanofibers containing dimethyl 5-sodium sulfoisophthalate nanoparticles were wrapped around the recycled poly(ethylene terephthalate) yarn by means of a novel electrospinning technique. Several tests were performed to investigate the parameters affecting wicking rise and moisture regain of the samples. Taguchi method was used in two separate designs (with or without nanoparticles). Some factors such as polymer solution concentration, mass ratio of nanoparticles, take-up rate, and number of filaments were considered as the variable factors while yarn wicking rate and moisture regain were the response factors. It was found that the hydrophilic nature of nanoparticles together with the ultrafine structure of nanofibers provide yarns with enhanced wicking properties. Although solution concentration is the predominant factor in wicking rate of the yarns containing nanoparticles, the most effective factor in wicking rise and moisture regain for other cases is the number of filaments. The mechanism of nanoparticle effect on fluidic jet during electrospinning process is explained by theory of nanofluids stability which has never been validated experimentally in previous research studies. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48185.     

Preparation of binary and hybrid epoxy nanocomposites containing graphene oxide and rubber nanoparticles: Fracture toughness and mechanical properties

Binary and hybrid epoxy nanocomposites modified with graphene oxide (GO) and core–shell rubbers (CSR) were synthesized via the solvent-exchange method. X-ray diffraction analysis and scanning electron microscopy of the samples showed a homogeneous dispersion of GO and CSR in the epoxy matrix. The tensile modulus and tensile strength of the samples modified with CSR decreased continuously with increasing CSR content; however, with the addition of only 0.05 phr GO to the neat epoxy and rubber-modified epoxy, these properties significantly increased. The use of GO and CSR individually improved the fracture toughness, but the impact of GO was greater. The simultaneous use of GO and CSR improved both the fracture toughness and the mechanical properties. Our investigation of the toughening mechanism indicated that crack deflection–bifurcation, crack pinning, and particle debonding–pullout in the presence of GO nanosheets and limited rubber particle cavitation contributed to fracture toughness improvement in the hybrid systems. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 46988.     

In Vitro Antiamoebic Activity Evaluation and Docking Studies of Metronidazole–Triazole Hybrids

An in‐house database of 520 compounds was docked against Entamoeba histolytica thioredoxin reductase (EhTrR), a promising target for the treatment of amoebiasis. Amongst these, some metronidazole (MTZ)–triazole hybrids were ranked high, with docking scores from ?10.23 to ?7.56. Studies of the binding orientations and conformations show that the head groups of MTZ–triazole hybrids interact with the arginine residues within the binding pocket of EhTrR, making it clear that such is the optimal and most reliable orientation for this class of compounds. The top‐ten MTZ–triazole hybrids were then selected for evaluation of their activity against the HM1:IMSS strain of amoeba. The most active compound, 2‐pyridyl‐(1,2,3‐triazolyl)metronidazole 10 , with an IC₅₀ value of 8.4 nM , was significantly more active than the standard drug MTZ alone. Docking studies revealed that compound 10 may act as an EhTrR inhibitor with activity in the nanomolar range and satisfactory ADME properties; it is a suitable candidate to be carried forward as a potential lead in the discovery of drugs to combat amoebiasis.     

Polyaniline matrix containing nickel ferromagnet

Metallic nickel (Ni) was successfully dispersed onto a polyaniline (PANI) matrix by a simple one‐step electrochemical method. Ni particles as deposited onto the polymer seemed to be much smaller compared to those deposited onto bare Pt. The size of the Ni deposits was found to be influenced by the electrolytic bath composition and potential sweep rate. The PANI matrix thus dispersed with Ni particles exhibited ferromagnetic behavior and a lower electrical conductance. The decrease in conductivity may be attributed to the partial blockage of the conductive path by the Ni particles thus embedded in the polymer matrix. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 321–327, 2006     

Incremental augmented complex adaptive IIR algorithm for training widely linear ARMA model

In this paper, we propose a distributed adaptive learning algorithm to train the coefficients of a widely linear autoregressive moving average model by measurements collected by the nodes of a network. We assume that each node uses the augmented complex adaptive infinite impulse response (ACA-IIR) filter as the learning rule, and nodes interact with each other under an incremental mode of cooperation. To derive the proposed algorithm, called the incremental ACAIIR (IACA-IIR), we firstly formulate the distributed adaptive learning problem as an unconstrained minimization problem. Then, we apply stochastic gradient optimization argument to solve it and derive the proposed algorithm. We further find the step size range where the stability of the proposed algorithm is guaranteed. We also introduce a reduced-complexity version of the IACA-IIR algorithm. Since the proposed algorithm relies on the augmented complex statistics, it can be used to model both types of complex-valued signals (proper and improper signals). To evaluate the performance of the proposed algorithm, we use both synthetic and real-world complex signals in our simulations. The results exhibit superior performance of the proposed algorithm over the non-cooperative ACA-IIR algorithm.     

Terpenoids as Human Neutrophil Elastase (HNE) Inhibitors: A Comprehensive Review of Natural Anti-inflammatory Isoprenoids

Human neutrophil elastase (HNE) is an enzyme that plays a key role in the body‘s inflammatory response. It has been linked to several diseases such as chronic obstructive pulmonary disease (COPD), emphysema, and cystic fibrosis. As potential treatments for these diseases, HNE inhibitors are of great interest. Metabolites derived from plants, particularly terpenoids such as β-caryophyllene found in black pepper and other plants, and geraniol present in several essential oils, are recognized as significant sources of inhibitors for HNE. Because of their ability to inhibit HNE, terpenoids are considered promising candidates for developing novel therapies to treat inflammatory conditions such as COPD and emphysema. Furthermore, nature can serve as an excellent designer, and it may offer a safer drug candidate for inhibiting HNE production and activity in the future. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses were searched to get relevant and up-to-date literature on terpenoids as human neutrophil elastase inhibitors. This review focuses on the isolation, chemical diversity, and inhibition of human neutrophil elastase (HNE) of various terpenoids reported from natural sources up to 2022. A total of 251 compounds from various terpenoids classes have been reported. Further, it also provides a summary of HNE inhibitors and includes a thorough discussion on the structure-activity relationship.     

Carrier Transport Enhancement Mechanism in Highly Efficient Antimony Selenide Thin-Film Solar Cell

Exhibiting outstanding optoelectronic properties, antimony selenide (Sb₂Se₃) has attracted considerable interest and has been developed as a light absorber layer for thin-film solar cells over the decade. However, current state-of-the-art Sb₂Se₃ devices suffer from unsatisfactory “cliff-like” band alignment and severe interface recombination loss, which deteriorates device performance. In this study, the heterojunction interface of an Sb₂Se₃ solar cell is improved by introducing effective aluminum (Al³⁺) cation into the CdS buffer layer. Then, the energy band alignment of Sb₂Se₃/CdS:Al heterojunction is modified from a “cliff-like” structure to a “spike-like” structure. Finally, heterojunction interface engineering suppresses recombination losses and strengthens carrier transport, resulting in a high efficiency of 8.41% for the substrate-structured Sb₂Se₃ solar cell. This study proposes a facile strategy for interfacial treatment and elucidates the related carrier transport enhancement mechanism, paving a bright avenue to overcome the efficiency bottleneck of Sb₂Se₃ thin-film solar cells.