Solid lubricant behavior of MoS2 and WSe2-based nanocomposite coatings

Abstract

Tribological coatings made of MoS₂ and WSe₂ phases and their corresponding combinations with tungsten carbide (WC) were prepared by non-reactive magnetron sputtering of individual targets of similar composition. A comparative tribological analysis of these multiphase coatings was done in both ambient air (30–40% relative humidity, RH) and dry nitrogen (RH<7%) environments using the same tribometer and testing conditions. A nanostructural study using advanced transmission electron microscopy of the initial coatings and examination of the counterfaces after the friction test using different analytical tools helped to elucidate what governs the tribological behavior for each type of environment. This allowed conclusions to be made about the influence of the coating microstructure and composition on the tribological response. The best performance obtained with a WSe_x film (specific wear rate of 2 × 10^?8 mm³ N^–1m^–1 and a friction coefficient of 0.03–0.05) was compared with that of the well-established MoS₂ lubricant material.     

Phase and Microstructural Characterization of Iron Ore Pellet and their Relation with Cold Crushing Strength Test

In the production of the pellets, phase identification for specific sintering condition is of prime importance in understanding the basis for the production and the required properties. The application of a methodology involving optical and scanning electron microscope equipped with an EBSD opened a broad possibility to establish a base for the relationship between heat-treated pellet microstructural features and cold crushing strength. The first results from the conjoined application of these techniques show that the cold crushing strength of the pellet increase with the decrease of porosity, the appearance of the fayalite, as well as the presence of magnetite-unoxidized.     

Effect of Combined Natural Antimicrobials on Spoilage Microorganisms and Listeria Innocua in a Whey Cheese “Ricotta”

The effect of nisin alone and in combination with Microgard? on the natural microbial flora of ricotta cheese and in post-process contamination with Listeria innocua was studied. Microbial groups studied were mesophilic, psychrotrophic, proteolytic, lactic acid and coliform bacteria, and total molds and yeasts. Considering the evolution of all microbial groups and failure criteria adopted for mesophilic and coliform bacteria, this product reached the end of its shelf life before 5 days, which is insufficient time for product commercialization. The combined use of nisin and Microgard? proved to be more effective than the individual application on these microbial groups, resulting in a 13 days shelf life extension. Additionally, the combined treatment reduced the growth of L. innocua as a post-process contamination.     

A bill of materials-based approach for end-of-life decision making in design for the environment

Re-use, recycling or remanufacturing of products and components are good alternatives for reducing the environmental problems resulting from the huge amounts of waste currently arriving at landfills. A new approach is proposed in this paper for enhancing these alternatives from the earliest stages of product design. Given the product structure (obtained from its bill of materials (BOM)) and the joining and geometrical relationships among the components (obtained from the three-dimensional, computer-aided design representation), a model is proposed that will determine the EOL (EOL) strategy, i.e. the depth of disassembly inside the structure and the final end (re-use, recycle, remanufacture or disposal) for each disassembled part leading to the highest profit. A scatter search (SS) metaheuristic is used to determine the disassembly cost at each level of the BOM. The model presents a number of major improvements with respect to previous research. It addresses the problems of simultaneously determining both the best EOL strategy and the disassembly sequence, as well as allowing removal of components not only over the two or three Cartesian axes and affording the possibility of modifying the encountered strategy in a further step so as to fulfil other business criteria (such as disassembly time, resources availability or maximum waste generation rate).     

Automatic adjustment of a medical imaging data acquisition system to unknown delays in the input communication channels

In this article, novel FIFO and RAM-based Synchronization Modules to keep synchronism throughout the input channels of a Data Acquisition Electronics (DAE) system are proposed. DAE is a main component of a Medical Imaging System, namely, a Positron Emission Mammography (PEM) system. DAE input data comes from a scanner constituted by an array of scintillating crystals. The scanner captures radiation generated by human cells injected with a radioactive substance and converts it into electrical signals. The corresponding digital information is sent to the DAE. In order to deal with the huge amount of data, flowing at high data rates, point-to-point (p2p) communication channels are used between the scanner and the DAE. Propagation delays associated with the different communication channels may change differently. Additionally, differences among channel delays may exceed one clock period. Keeping synchronism in these circumstances requires more than the classical asynchronous FIFO solution. All these aspects motivate the work proposed in this article. The PEM DAE system is a multi-board, multi-FPGA, multi-clock domain system. Therefore, the DAE architecture follows a Globally Asynchronous, Locally Synchronous (GALS) design style. The novel Synchronization Modules proposed in this article are implemented in the DAE. The effectiveness of these new structures is validated through simulation and laboratorial test. Simulation and test results are presented.     

Application of digital image correlation at the microscale in fiber-reinforced composites

Digital image correlation (DIC) is applied to analyzing the deformation mechanisms under transverse compression in a fiber-reinforced composite. To this end, compression tests in a direction perpendicular to the fibers were carried out inside a scanning electron microscope and secondary electron images obtained at different magnifications during the test. Optimum DIC parameters to resolve the displacement and strain field were computed from numerical simulations of a model composite and they were applied to micrographs obtained at different magnifications (250×, 2000×, and 6000×). It is shown that DIC of low-magnification micrographs was able to capture the long range fluctuations in strain due to the presence of matrix-rich and fiber-rich zones, responsible for the onset of damage. At higher magnification, the strain fields obtained with DIC qualitatively reproduce the non-homogeneous deformation pattern due to the presence of stiff fibers dispersed in a compliant matrix and provide accurate results of the average composite strain. However, comparison with finite element simulations revealed that DIC was not able to accurately capture the average strain in each phase.     

An optimization algorithm inspired by the States of Matter that improves the balance between exploration and exploitation

The ability of an Evolutionary Algorithm (EA) to find a global optimal solution depends on its capacity to find a good rate between exploitation of found-so-far elements and exploration of the search space. Inspired by natural phenomena, researchers have developed many successful evolutionary algorithms which, at original versions, define operators that mimic the way nature solves complex problems, with no actual consideration of the exploration-exploitation balance. In this paper, a novel nature-inspired algorithm called the States of Matter Search (SMS) is introduced. The SMS algorithm is based on the simulation of the states of matter phenomenon. In SMS, individuals emulate molecules which interact to each other by using evolutionary operations which are based on the physical principles of the thermal-energy motion mechanism. The algorithm is devised by considering each state of matter at one different exploration–exploitation ratio. The evolutionary process is divided into three phases which emulate the three states of matter: gas, liquid and solid. In each state, molecules (individuals) exhibit different movement capacities. Beginning from the gas state (pure exploration), the algorithm modifies the intensities of exploration and exploitation until the solid state (pure exploitation) is reached. As a result, the approach can substantially improve the balance between exploration–exploitation, yet preserving the good search capabilities of an evolutionary approach. To illustrate the proficiency and robustness of the proposed algorithm, it is compared to other well-known evolutionary methods including novel variants that incorporate diversity preservation schemes. The comparison examines several standard benchmark functions which are commonly considered within the EA field. Experimental results show that the proposed method achieves a good performance in comparison to its counterparts as a consequence of its better exploration–exploitation balance.     

Forecasting Financial Failure of Firms via Genetic Algorithms

Given a wide amount of possible ratios available for constructing a LOGIT model for forecasting bankruptcy, this paper provides a computational search methodology, only guided by data, for selecting the financial ratios employed in the model. This procedure is based on genetic algorithms which are used to explore the universe of models made available by all possible existing financial ratios (with very redundant information). This search process of the correct model is guided by the Schwarz information criterion. As an empirical illustration, the methodology is applied to forecasting the failure of firms in the Spanish building industry using annual public accounting information.