Reactive Magnetron Sputter Deposition of Titanium Oxynitride TiNxOy Coatings: Influence of Substrate Bias Voltage on the Structure,Composition, and Properties

Protection of Metals and Physical Chemistry of Surfaces - TiOxNy films were grown onto 316L stainless steel substrate using radiofrequency (rf) magnetron sputtering from a pure titanium nitride...     

Effective electrodeposition of poly(3,4-ethylenedioxythiophene)-based organic coating on metallic food packaging for active corrosion protection

Journal of Applied Electrochemistry - Modern technologies continuously need special materials with specific properties to adopt the desired application. Recently, numerous researches have been...     

Niobium addition effect in molds at last cooling step on EN-GJL250 gray cast iron: Microstructural changes and electrochemical behavior

The purpose of this study was to determine the impact of niobium addition as an inoculation element on the microstructure and electrochemical properties of EN-FGL250 gray cast iron. Niobium additions are in a powder form and have a 0.5 mm particle size at dfferent proportions of 1 wt.% and 3 wt.%. The addition was done during casting of the metal in the mold at the last cooling step of the melt cast iron. These additions have a significant impact on the phenomenon of solidifi cation as the metal powder deposited in the sand molds creates new centers of germination and absorbs a lot of heat. The cooling rate directly affects the microstructure and electrochemical behavior. This is confirmed by SEM observations and electrochemical tests. Furthermore, the addition of niobium transforms the microstructure of gray cast iron from cellular structure into totally dendritic structure. As a consequence, the niobium addition affected the shape and size of graphite, thus considerably reducing the corrosion current density by increasing the polarization resistance Rp.     

Modified Galacto- or Fuco-Clusters Exploiting the Siderophore Pathway to Inhibit the LecA- or LecB-Associated Virulence of Pseudomonas aeruginosa

Galacto- and fuco-clusters conjugated with one to three catechol or hydroxamate motifs were synthesised to target LecA and LecB lectins of Pseudomonas aeruginosa (PA) localised in the outer membrane and inside the bacterium. The resulting glycocluster–pseudosiderophore conjugates were evaluated as Trojan horses to cross the outer membrane of PA by iron transport. The data suggest that glycoclusters with catechol moieties are able to hijack the iron transport, whereas those with hydroxamates showed strong nonspecific interactions. Mono- and tricatechol galactoclusters ( G1C and G3C ) were evaluated as inhibitors of infection by PA in comparison with the free galactocluster ( G0 ). All of them exhibited an inhibitory effect between 46 to 75 % at 100 μM, with a higher potency than G0 . This result shows that LecA localised in the outer membrane of PA is involved in the infection mechanism.     

Design and Synthesis of Galactosylated Bifurcated Ligands with Nanomolar Affinity for Lectin LecA from Pseudomonas aeruginosa

Lectin A (LecA) from Pseudomonas aeruginosa is an established virulence factor. Glycoclusters that target LecA and are able to compete with human glycoconjugates present on epithelial cells are promising candidates to treat P. aeruginosa infection. A family of 32 glycodendrimers of generation 0 and 1 based on a bifurcated bis‐galactoside motif have been designed to interact with LecA. The influences both of the central multivalent core and of the aglycon of these glycodendrimers on their affinity toward LecA have been evaluated by use of a microarray technique, both qualitatively for rapid screening of the binding properties and also quantitatively (K_d). This has led to high‐affinity LecA ligands with K_d values in the low nanomolar range (K_d=22 nm for the best one).     

The effect of substrate bias voltage on the electrochemical corrosion behaviors of thin film deposited on stainless steel by r. f magnetron sputtering

Protection of Metals and Physical Chemistry of Surfaces - Anticorrosion TiO2 films were deposited by reactive r.f. magnetron sputtering method, on stainless steel substrates. The effect of bias...     

Effects of single-walled carbon nanotubes on the optical and photo-conductive properties of their composite films with regio-regular poly(3-hexylthiophene)

The effect of a small admixture of single-walled carbon nanotubes (SWNTs) HiPCO (high pressure carbon monoxide) (from 0.5 to 2 wt%) on the supramolecular structure in regio-regular poly(3-hexylthiophene) (RR-P3HT) thin films is studied and their optical and photoconductivity properties are investigated. It is demonstrated that the presence of such small amounts of nanotubes improves the structural organization in the films as evidenced by X-ray diffraction (XRD) studies. This is confirmed by UV–visible optical absorption investigations which clearly show a better conjugation of P3HT in the presence of nanotubes. In Raman spectra of composites, changes in intensities and frequencies of the radial breathing modes are observed upon addition of nanotubes. This can be rationalized by a modification of the resonance conditions caused by a selective dispersion and wrapping of SWNTs via π-interaction (π-stacking). As a consequence of these interactions, a dramatic photoluminescence (PL) quenching is observed which becomes more and more pronounced with increasing the nanotube content. This implies a fast photo-induced electron transfer favoured by a large area of the SWNTs/P3HT interface and strong interactions between these two components. An increase in the composite photocurrent by at least one-order of magnitude, as compared to the case of pure P3HT film, is the most pronounced effect of this electron transfer. These two effects are of crucial importance for the application of the investigated composites in bulk hetero-junction photovoltaic cells (BHJPCs) and organic photo-detectors (OPDs).     

Automated Deep Learning Based Melanoma Detection and Classification Using Biomedical Dermoscopic Images

Melanoma remains a serious illness which is a common form of skin cancer. Since the earlier detection of melanoma reduces the mortality rate, it is essential to design reliable and automated disease diagnosis model using dermoscopic images. The recent advances in deep learning (DL) models find useful to examine the medical image and make proper decisions. In this study, an automated deep learning based melanoma detection and classification (ADL-MDC) model is presented. The goal of the ADL-MDC technique is to examine the dermoscopic images to determine the existence of melanoma. The ADL-MDC technique performs contrast enhancement and data augmentation at the initial stage. Besides, the k-means clustering technique is applied for the image segmentation process. In addition, Adagrad optimizer based Capsule Network (CapsNet) model is derived for effective feature extraction process. Lastly, crow search optimization (CSO) algorithm with sparse autoencoder (SAE) model is utilized for the melanoma classification process. The exploitation of the Adagrad and CSO algorithm helps to properly accomplish improved performance. A wide range of simulation analyses is carried out on benchmark datasets and the results are inspected under several aspects. The simulation results reported the enhanced performance of the ADL-MDC technique over the recent approaches.