Micro-abrasion resistance of thermochemically treated steels in aqueous solutions: Mechanisms, maps, materials selection

The area of micro-abrasion is an interesting and relatively recent area in tribo-testing methodologies, where small particles of less than 10 μm are employed between interacting surfaces. It is topical for a number of reasons; its direct relation to the mechanisms of the wear process in bio-tribological applications, ease in conducting tests and the good repeatability of the test results. It has widespread applications in conditions used in the space and offshore industries to bio-engineering for artificial joints and implants. There have been many recent studies on the micro-abrasion performance of materials, ranging from work basic metals to nano-structured coatings. However, no significant work is reported on the micro-abrasion resistance of thermochemically treated steels. Hence, this paper looks at the performance of two thermochemically treated steels, Tenifer bath nitride stainless steel (T-SS) and vanadized carbon steel (V-CS) in such conditions with reference to the stainless steel (SS) by varying the applied load and sliding distance. The results indicated that T-SS demonstrates exceptionally poor resistance to micro-abrasion. It was observed that the heat treatment process and properties of the hardened layer (hardness and thickness) are extremely important in determining the micro-abrasion resistance of such steels. Finally, the results were used to develop micro-abrasion mechanism and wastage maps, which can be used to optimize the surface treated materials for micro-abrasion resistance

Some thoughts on neural network modelling of micro-abrasion-corrosion processes

There is increasing interest in the interactions of microabrasion, involving small particles of less than 10 μm in size, with corrosion. This is because such interactions occur in many environments ranging from the offshore to health care sectors. In particular, micro-abrasion-corrosion can occur in oral processing, where the abrasive components of food interacting with the acidic environment, can lead to degradation of the surface dentine of teeth. Artificial neural networks (ANNs) are computing mechanisms based on the biological brain. They are very effective in various areas such as modelling, classification and pattern recognition. They have been successfully applied in almost all areas of engineering and many practical industrial applications. Hence, in this paper an attempt has been made to model the data obtained in microabrasion-corrosion experiments on polymer/steel couple and a ceramic/lasercarb coating couple using ANN. A multilayer perceptron (MLP) neural network is applied and the results obtained from modelling the tribocorrosion processes will be compared with those obtained from a relatively new class of neural networks namely resource allocation network

Micro-abrasion–corrosion of a Co–Cr/UHMWPE couple in Ringer's solution : an approach to construction of mechanism and synergism maps for application to bio-implants

In studies of tribo-corrosion, the degradation of bio-materials has become of increasing research interest in recent years. This is because, in many cases, the interactions of the tribological and corrosion component in biological environments are not well understood. Moreover, the wide range of variables involved in the tribo-corrosion process, and the variety of materials used in such conditions, means that there are few systematic studies where materials and operating conditions are optimized. In the total replacement of hip joints, the Co-Cr/UHMWPE couple has been used widely. However, the application of any replacement joint for biological conditions will depend on many factors including the activity of the patient and the overall load imposed on the artificial joint. This means evaluation of the tribo-corrosion behaviour over a multi parameter space is important in order to assess the degradation possible for many patient/activity and body mass categories.In this work, the performance of a Co-Cr/UHMWPE couple was evaluated in Ringer's solution in a tribological situation where micron size particles particles were entrained in the contact - micro-abrasion-corrosion. The effects of applied load and potential were investigated in the study. Micro-abrasion-corrosion maps were constructed for the material indicating the mechanism of degradation, the extent of wastage and of synergy/antagonism involved in the tribo-corrosion interaction

Tribocorrosion behavior of CoCrMo alloy for hip prosthesis as a function of loads: A comparison between two testing systems

Metal-on-metal (MOM) hip prosthesis bearings have enjoyed renewed popularity, but concerns remain with wear debris and metal ion release causing a negative response in the surrounding tissues. Further understanding into the wear and corrosion mechanisms occurring in MOM hips is therefore essential. The purpose of this study was to evaluate the tribocorrosion behavior, or interplay between corrosion and wear, of a low-carbon CoCrMo alloy as a function of loading. The tribocorrosion tests were performed using two tribometer configurations. In the first configuration, “System A”, a linearly reciprocating alumina ball slid against the flat metal immersed in a phosphate buffer solution (PBS). In the second configuration, “System B”, the flat end of a cylindrical metal pin was pressed against an alumina ball that oscillated rotationally, using bovine calf serum (BCS) as the lubricant and electrolyte. System B was custom-built to emulate in vivo conditions. The tribocorrosion tests were performed under potentiostatic conditions at −0.345 V, with a sliding duration of 1800 s and a frequency of 1 Hz. In System A the applied loads were 0.05, 0.5, and 1 N (138, 296 and 373 MPa, respectively) and in System B were 16, 32, and 64 N (474, 597, and 752 MPa, respectively). Electrochemical impedance spectroscopy (EIS) and polarization resistance were estimated. The total mass loss (Kwc) in the CoCrMo was determined. The mass loss due to wear (Kw) and that due to corrosion (Kc) were determined. The dominant wear regime for the CoCrMo alloy subjected to sliding changes from wear–corrosion to mechanical wear as the contact stress increases. An attempt was made to compare both system, in their tribochemical responses and formulate some insights in the total degradation processes. Our results also suggest that the proteins in the serum lubricant assist in the generation of a protective layer against corrosion during sliding. The study highlights the need of adequate methodology/guidelines to compare the results from different test systems and translating in solving the practical problems

Sumatran rhinoceros and wildlife survey East of Segama, Danum Valley, Sabah, Malaysia

The purpose of this survey was to assess the Sumatran rhinoceros population occurring around DVFC on the eastern part of Sungai Segama, Sabah

Through-Thickness Residual Stress Profiles in Austenitic Stainless Steel Welds: A Combined Experimental and Prediction Study

Economic and safe management of nuclear plant components relies on accurate prediction of welding-induced residual stresses. In this study, the distribution of residual stress through the thickness of austenitic stainless steel welds has been measured using neutron diffraction and the contour method. The measured data are used to validate residual stress profiles predicted by an artificial neural network approach (ANN) as a function of welding heat input and geometry. Maximum tensile stresses with magnitude close to the yield strength of the material were observed near the weld cap in both axial and hoop direction of the welds. Significant scatter of more than 200 MPa was found within the residual stress measurements at the weld center line and are associated with the geometry and welding conditions of individual weld passes. The ANN prediction is developed in an attempt to effectively quantify this phenomenon of ‘innate scatter’ and to learn the non-linear patterns in the weld residual stress profiles. Furthermore, the efficacy of the ANN method for defining through-thickness residual stress profiles in welds for application in structural integrity assessments is evaluated

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Search for dark mesons decaying to top and bottom quarks in proton-proton collisions at √s = 13 TeV with the ATLAS detector

A search for dark mesons originating from strongly-coupled, SU(2) dark favor symmetry conserving models and decaying gaugephobically to pure Standard Model final states containing top and bottom quarks is presented. The search targets fully hadronic final states and final states with exactly one electron or muon and multiple jets. The analyzed data sample corresponds to an integrated luminosity of 140 fb−1 of proton-proton collisions collected at √s = 13 TeV with the ATLAS detector at the Large Hadron Collider. No significant excess over the Standard Model background expectation is observed and the results are used to set the first direct constraints on this type of model. The two-dimensional signal space of dark pion masses mπD and dark rho-meson masses mρD is scanned. For mπD /mρD = 0.45, dark pions with masses mπD < 940 GeV are excluded at the 95% CL, while for mπD /mρD = 0.25 masses mπD < 740 GeV are excluded