Corrosion and tribological performance of quasi-stoichiometric titanium containing carbo-nitride coatings

Zr, Nb and Si doped TiCN coatings, with (C+N)/(metal + Si) ratios of approximately 1, were deposited on stainless steel and Si wafer substrates using a cathodic arc technique in a mixture of N2 and CH4 gases. The coatings were comparatively analysed for elemental and phase composition, adhesion, anticorrosive properties and tribological performance at ambient and 250 °C. Zr, Nb and Si alloying contents in the coatings were in the range 2.9–9.6 at.%. All the coatings exhibited f.c.c. solid solution structures and had a 〈1 1 1〉 preferred orientation. In the adhesion tests conducted, critical loads ranged from 20 to 30 N, indicative of a good adhesion to substrate materials. The Ti based coatings with Nb or Si alloying elements proved to be resistant to corrosive attack in 3.5% NaCl and of these coatings the TiNbCN was found to have the best corrosion resistance. TiCN exhibited the best tribological performance at 250 °C, while at ambient temperatures it was TiNbCN. Abrasive and oxidative wear was found to be the main wear mechanism for all of the coatings. Of the tested coatings, TiNbCN coatings would be the most suitable candidate for severe service (high temperature, corrosive, etc.) applications

A geographic cline induced by negative frequency-dependent selection

<p>Abstract</p> <p>Background</p> <p>Establishment of geographic morph frequency clines is difficult to explain in organisms with limited gene flow. Balancing selection, such as negative frequency-dependent selection (NFDS), is instead suggested to establish a morph frequency cline on a geographic scale at least theoretically. Here we tested whether a large-scale smooth cline in morph frequency is established by NFDS in the female-dimorphic damselfly, <it>Ischnura senegalensis</it>, where andromorphs and gynomorphs are maintained by NFDS.</p> <p>Results</p> <p>We found a large-scale latitudinal cline in the morph frequency: andromorph frequency ranged from 0.05 (South) to 0.79 (North). Based on the empirical data on the numbers of eggs, the number of ovariole, abdomen length and latitude, the potential fitness of andromorphs was estimated to be lower than that of gynomorphs in the south, and higher in the north, suggesting the gene-by-environment interaction. From the morph-specific latitudinal cline in potential fitness, the frequency of andromorphs was expected to shift from 0 to 1 without NFDS, because a morph with higher potential fitness wins completely and the two morphs will switch at some point. In contrast, NFDS led to the coexistence of two morphs with different potential fitness in a certain geographic range along latitude due to rare morph advantage, and resulted in a smooth geographic cline of morph frequency.</p> <p>Conclusion</p> <p>Our results provide suggestive evidence that the combination of NFDS and gene-by-environment interaction, i.e., multi-selection pressure on color morphs, can explain the geographic cline in morph frequency in the current system.</p

The influence of variations of geometrical parameters on the notching stress intensity factors of cylindrical shells

The modern approach of Virtual Engineering allows one to detect with some accuracy the residual life of components especially free of cracks. The life estimation becomes cumbersome when the components contain a crack. A straightforward formulation requires a parameter that considers geometrical constraints and materials properties. The magnitude of the stress singularity developed by the tip of a crack, needs to be expressed by the Stress Intensity Factors (SIF). In order to prove the validity of the results, calibration by experimental and/or analytical technique is required. To have a better understanding of this parameter, in the first part of this paper an analytical model to compute the SIF connected to crack propagation into Mode I has been implemented. The case study displays a pipeline component with a crack defect submitted to internal pressure. Therefore, an appropriate correlation between the analytical approach and numerical simulation has been established embedded

Towards a Diagnostic Tool for Diagnosing Joint Pathologies:Supervised Learning of Acoustic Emission Signals

Acoustic emission (AE) testing detects the onset and progression of mechanical flaws. AE as a diagnostic tool is gaining traction for providing a tribological assessment of human joints and orthopaedic implants. There is potential for using AE as a tool for diagnosing joint pathologies such as osteoarthritis and implant failure, but the signal analysis must differentiate between wear mechanisms&mdash;a challenging problem! In this study, we use supervised learning to classify AE signals from adhesive and abrasive wear under controlled joint conditions. Uncorrelated AE features were derived using principal component analysis and classified using three methods, logistic regression, k-nearest neighbours (KNN), and back propagation (BP) neural network. The BP network performed best, with a classification accuracy of 98%, representing an exciting development for the clustering and supervised classification of AE signals as a bio-tribological diagnostic tool