Improved pitting corrosion resistance of S.S 316L by Pulsed Current Gas Tungsten Arc Welding

In this study, S.S 316L was welded using Direct Current Gas Tungsten Arc Welding (DGTAW) and Pulsed Current Gas Tungsten Arc Welding (PGTAW) methods. Optical observations, scanning electron microscopy (SEM) and X-ray diffraction analysis (XRD) were employed to study the effect of continuous and pulse currents on microstructure and phase transformation in weld metal (WM). In addition pits morphology were evaluated by SEM. The corrosion behaviour was analyzed using cyclic polarizaton tests and Mott-schottky measurements. The pulse current resulted in finer grain and more ferrite in WM. This can be due to the decrease in heat input and higher cooling rate encouraged by pulse current. Cyclic potentiodynamic polarization tests showed that the WM of sample produced by pulse current show higher corrosion and pitting resistances than that in sample produced by continuous current. The reason is attributed to lower segregation of solute elements such as chromium and molybdenum into the delta-ferrite and also finer grain size produced in WM due to lower heat input and higher cooling rate. Both of these factors increase the stability of passive layer formed. The results showed that the corrosion behaviour of WM in both conditions (pulse and continuous current) is higher than the base metal (BM). This fact is attributed to the presence of ferrite bands formed in BM due to the segregation of alloy elements. The Mott-schottky plots confirmed that the passive layer formed on welded samples was an n-type semiconductor. The results showed that the samples showed less pitting resistance contained more oxygen vacancies in their passive film structure. It is also concluded that the breakdown of passive layer and pitting formation obey point defect model (PDM). Keywords: S.S 316L, Pulsed Current Gas Tungsten Arc Welding (PGTAW), lacy ferrite, vermicular ferrite, Pitting corrosion, Mott- Schottky

Detecting and Tracking Skin Lesions on 3D Whole Body Skin Images using Deep Learning

Given the increasing need for automatic diagnosis of skin-related diseases, it’s important to leverage full-body image acquisition as well as AI tools. Many computer-aided approaches to analyze skin conditions rely on static 2D color images; however, limited works have focused on 3D whole-body images or tracking lesions across time. Imaging the entire body gives additional context that may not be visible in a single localized photograph. Further, imaging and tracking skin conditions across time may allow for lesion changes or the progression of treatments to be monitored.Given the importance of early detection, diagnosis, and treatment of skin conditions, we propose a new dataset and a novel computational pipeline to detect and track lesions using 3D human skin images. Our pipeline is based on recent advances in computer vision for multi-view 3D colored skin surface reconstruction (such as structured light 3D scanning using Artec EVA scanner and 3D photogrammetry scanning using smartphones), 3D geometry processing, point correspondence, and deep learning-based object localization and classification (such as Faster R-CNN). To perform analysis on 3D whole-body scans, we map the 3D scans of human subjectsto 2D texture images, where a trained region-based convolutional neural network localizes the lesions within the 2D domain. For subjects with multiple scans, we apply a matching algorithm to track and monitor the lesions across time. We test our methods on a scanned mannequin, with varying postures and artificial skin lesions, as well as a newly created synthetic 3D dataset comprising 900 whole-body, skin-colored meshes with lesions of varying appearances and diagnoses under different postures, and a public digital 3D dataset with manually annotated lesions. 3D full-body imaging and deep learning-based lesion detection methods show great potential in the future of automatic skin-related disease diagnosis

The dynamics of organismal proteome response to drugs

This study analyzes how the dynamics of organismal proteome responded to the drug over 48 hours. To answer this question, the mouse proteome was studied by analyzing up to 13 major organ proteomes in 4 inbred strains for drug responses over 48 hours. To analyze the organismal proteome similarity, we used probability density function to compute the likelihood. As our statistical knowledge suggests, probability density function (PDF) is a statistical expression that defines a probability distribution (here the likelihood of two conditions) for a discrete random variable. We used this statistic to analyze our data since it provides the relationship or similarities between two different conditions. Outcomes will show how conditions differ from each other. These results could be used to reveal different drug responses

Mineralogy, geochemistry and genesis of the Gheshlagh bauxite deposit, southeast of Gorgan

The Gheshlagh bauxite deposit is located 110 km southeast of Gorgan. The deposit has been developed as a stratiform horizon with more than 2 km length and a thickness of about 25 m along the contact of Ruteh and Elika carbonate formations. Textural analysis indicates both allochthonous and autochtonous origins for the bauxites. Bohemite, diaspore, anatase, rutile, hematite, goethite, kaolinite, svanbergite, pyrite, and quartz were identified in the ore paragenesis. Based on textural and mineralogical evidence, the deposit can be divided into five distinct units including upper bauxite, upper kaolinite, hard bauxite, lower kaolinite and lower bauxite. Accumulation coefficients of trace elements and geochemical indices such as Ti/Cr, TiO2/Al2O3, Zr/Ti and Nb/Y, combined with the geological evidence suggest the basaltic rocks of the Soltanmeidan Formation as the main source of bauxite materials. Combination of mineralogical and geochemical data shows that the deposit formed in two main stages. First, bauxite materials, Fe and Ti oxides and clay minerals developed as authigenic bauxitization processes of basaltic parent rock. Then, these materials were transported to karst depressions and were accumulated as a bauxite horizon

Microstructure and Corrosion Behavior Investigation of Al5083-H321 GMAW Weldment in Sea Water

Aluminium 5xxx alloys excellent properties make them suitable for many industrial applications. The corrosion behavior of this alloy family in industrial environments such as sea water is the main focus of many researches. Due to need for joining large segments of this alloys, the effect of single as well as multipass (double and triple pass) gas metal arc welding (GMAW) on microstructure and corrosion behavior of Al5083-H321 alloy was studied. For this purpose, ER5183 filler metal was used. Microstructures were evaluated using optical and scanning electron microscopy (SEM). Corrosion measurements were performed using open circuit potential test, immersion test in 3.5%NaCl solution and polarization tests. Results indicated that the corrosion resistance of the two passes weldment was improved in comparison with the base metal and its icorr and Ecorr were equal to 0.087´10-6 (µA/cm2) and -0.4395 (V), respectively

Electroplating of Ni-Mo Coating on Stainless Steel for Application in Proton Exchange Membrane Fuel Cell Bipolar Plate

Stainless steel bipolar plates are preferred choice for use in Proton Exchange Membrane Fuel Cells (PEMFCs). However, regarding the working temperature of 80 °C and corrosive and acidic environment of PEMFC, it is necessary to apply conductive protective coatings resistant to corrosion on metallic bipolar plate surfaces to enhance its chemical stability and performance. In the present study, by applying Ni-Mo and Ni-Mo-P alloy coatings via electroplating technique, corrosion resistance was improved, oxid layers formation on substrates which led to increased electrical conductivity of the surface was reduced and consequently bipolar plates fuction was enhanced. Evaluation tests included microstructural and phase characterizations for evaluating coating components; cyclic voltammetry test for electrochemical behavior investigations; wettability test for measuring hydrophobicity characterizations of the coatings surfaces; interfacial contact resistance measurements of the coatings for evaluating the composition of applied coatings; and polarization tests of fuel cells for evaluating bipolar plates function in working conditions. Finally, the results showed that the above-mentioned coatings considerably decreased the corrosion and electrical resistance of the stainless steel

Optimization of Surface Mechanical Properties and Characterization of AZ31B/CNT Nano-composite through Friction Stir Processing (FSP) using Response Surface Methodology (RSM) Design of Experiment

In this paper, the optimization of the surface composite of Mg AZ31B-carbon nanotub(CNT) via friction stir processing was investigated. Then, the most effective process parameters such as transverse speed, rotational speed, CNT weight percent and welding passes were studied by Response Surface Methodology (RSM) design of experiment. The specimens were also characterized by micro-hardness, tensile, shear punch and pin on disk dry sliding wear tests. The optimization results of hardness and weight reduction responses showed that the best conditions would be achievable with a transverse speed of 24 mm/min, rotational speed of 660 rpm, 4wt.% CNT and 3 welding passes. Moreover, fracture analysis of the surfaces proved a uniform distribution of CNTs in the matrix resulted in higher tensile and shear strength. &nbsp