Laser Texturing to Increase the Wear Resistance of an Electrophoretic Graphene Coating on Copper Substrates.

In the present paper, different surface preparations are investigated with the aim of increasing the wear behaviour of an electrophoretic graphene coating on a copper plate. The study was divided into two steps: In the first step (pre-tests), to detect the most promising pretreatment technology, five different surface preparations were investigated (electropolishing, sandblasting, degreasing and pickling, laser cleaning and laser dots).In the second step, on the basis of the results of the first step, a 32 full factorial plan was developed and tested; three treatment types (pickled and degreased, laser-cleaned, and laser dots) and three different voltages (30, 45 and 60 V) were adopted. Analysis of variance (ANOVA) was used to evaluate their influence on wear resistance; in particular, the maximum depth and width of the wear tracks and the coating break distance were investigated. The results of this study show that, in optimal conditions, laser treatment (particularly laser dots) canlead to as high as a four-fold increase in wear resistance.

Study on Pulse-Reverse Electroplating Process for the Manufacturing of a Graphene-Based Coating.

This work investigates the feasibility of increasing the electric conductivity of an AA1370 aluminium wire by using pulse-reverse electrodeposition to realize Cu-Graphene composite coating. The graphene adopted was in the form of nanoplates (GnP). To study the effects of plating parameters, a 23 factorial plan was developed and tested. During the tests, the following process parameters were varied: the current density, the frequency and the duty cycle. The ANalysis Of VAriance (ANOVA)) was adopted to evaluate their influence on the coated wires' morphology and electrical conductivity resistance. The results show that all the tested conditions allow good compactness to the coating, and the amount of graphene is well incorporated within the microstructure of the copper deposit. In addition, in the best conditions, the electrical resistivity decreases up to 3.4% than the uncoated aluminum.

Design and Mechanical Characterization of Voronoi Structures Manufactured by Indirect Additive Manufacturing.

Additive manufacturing (AM) is a production process for the fabrication of three-dimensional items characterized by complex geometries. Several technologies employ a localized melting of metal dust through the application of focused energy sources, such as lasers or electron beams, on a powder bed. Despite the high potential of AM, numerous burdens afflict this production technology; for example, the few materials available, thermal stress due to the focused thermal source, low surface finishing, anisotropic properties, and the high cost of raw materials and the manufacturing process. In this paper, the combination by AM of meltable resins with metal casting for an indirect additive manufacturing (I-AM) is proposed. The process is applied to the production of open cells metal foams, similar in shape to the products available in commerce. However, their cellular structure features were designed and optimized by graphical editor Grasshopper®. The metal foams produced by AM were cast with a lost wax process and compared with commercial metal foams by means of compression tests.

Artificial Neural Network in Fibres Length Prediction for High Precision Control of Cellulose Refining.

Paper, a web of interconnected cellulose fibres, is widely used as a base substrate. It has been applied in several applications since it features interesting properties, such as renewability, biodegradability, recyclability, affordability and mechanical flexibility. Furthermore, it offers a broad possibility to modify its surface properties toward specifics additives. The fillers retention and the fibres bonding ability are heavily affected by the cellulose refining process that influences chemical and morphological features of the fibres. Several refining theories were developed in order to determine the best refining conditions. However, it is not trivial to control the cellulose refining as different phenomena occur simultaneously. Therefore, it is intuitively managed by experienced papermakers to improve paper structures and properties. An approach based on the machine learning aimed at estimating the effects of refining on the fibres morphology is proposed in this study. In particular, an artificial neural network (ANN) was implemented and trained with experimental data to predict the fibres length as a function of refining process variables. The prediction of this parameter is crucial to obtain a high-performance process in terms of effectiveness and the optimisation of the final product performance as a function of the process parameter. To achieve these results, data mining of the experimental patterns collected was exploited. It led to the achievement of excellent performance and high accuracy in fibres length prediction.

Heat Treatment of AZ91 Magnesium Alloy Coated with an Al2O3 Thin Film with Fluidized Bed Technology.

Fluidized bed technology is a methodology widely known in the manufacturing environment for surface treatment of metals. Within the field of surface coating, it has already been exploited for the coating of a magnesium alloy creating a compact layer of Al2O3. The result was an improvement in mechanical and tribological properties, along with improved corrosion resistance. In this context, the work proposed is addressed towards the evaluation of the effects of thermal post-treatment on the alumina coating produced by means of the fluidized-bed technology. To analyse the effects of heat treatments the morphology, composition and hardness of the samples were investigated along with adhesion and wear resistance of the alumina film. The results obtained show how the temperature affects the surface morphology and promotes the diffusion of magnesium towards the alumina superficial layer. The mechanisms triggered by heat treatments increase the adhesion of the surface film obtained in the deposition process, improving its mechanical and tribological properties.

Al2O3 Coatings on Magnesium Alloy Deposited by the Fluidized Bed (FB) Technique.

Magnesium alloys are widely employed in several industrial domains for their outstanding properties. They have a high strength-weight ratio, with a density that is lower than aluminum (33% less), and feature good thermal properties, dimensional stability, and damping characteristics. However, they are vulnerable to oxidation and erosion-corrosion phenomena when applied in harsh service conditions. To avoid the degradation of magnesium, several coating methods have been presented in the literature; however, all of them deal with drawbacks that limit their application in an industrial environment, such as environmental pollution, toxicity of the coating materials, and high cost of the necessary machinery. In this work, a plating of Al2O3 film on a magnesium alloy realized by the fluidized bed (FB) technique and using alumina powder is proposed. The film growth obtained through this cold deposition process is analyzed, investigating the morphology as well as tribological and mechanical features and corrosion behavior of the plated samples. The resulting Al2O3 coatings show consistent improvement of the tribological and anti-corrosive performance of the magnesium alloy.