Use of cryogenic machining to improve the adhesion of sphene bioceramic coatings on titanium substrates for dental and orthopaedic applications

Rods of commercially pure titanium were machined using standard oil-based emulsion and cryogenic cooling, and were then coated with sphene (CaTiSiO₅) bioceramic by spray coating using an automatic airbrush. The sphene bioceramic was synthesized in-situ starting from a suspension of polysiloxane that used as SiO₂ precursor, CaCO₃ and TiO₂ nanoparticles. The suspension was deposited on the machined substrates, which were heat treated up to 950?°C in order to promote the formation of sphene ceramic. The produced coated prototypes were characterized to evaluate the effect of the machining conditions on surface roughness and microstructure of the substrate, and thereby their effect on coating adhesion. Nanoindentation tests were employed to determine the hardness and elastic modulus of the coating through its thickness. Results showed that the reduced amount of defects on the surface of the cryo-machined substrates, contributed to increase the hardness, elastic modulus and adhesion strength of the coating-substrate interfaces compared to standard machined samples, therefore improving adhesion of the coating to the underlying substrate.     

High Electrical and Thermal Conductivity Cast Al-Fe-Mg-Si Alloys with Ni Additions

Metallurgical and Materials Transactions A - Aluminum alloys with transition metals Fe and Ni show potential to form the basis for castable alloys with high electrical and thermal conductivity for...     

Computational intelligence modelling of pharmaceutical tabletting processes using bio-inspired optimization algorithms

In pharmaceutical development, it is very useful to exploit the knowledge of the causal relationship between product quality and critical material attributes (CMA) in developing new formulations and products, and optimizing manufacturing processes. With the big data captured in the pharmaceutical industry, computational intelligence (CI) models could potentially be used to identify critical quality attributes (CQA), CMA and critical process parameters (CPP). The objective of this study was to develop computational intelligence models for pharmaceutical tabletting processes, for which bio-inspired feature selection algorithms were developed and implemented for optimisation while artificial neural network (ANN) was employed to predict the tablet characteristics such as porosity and tensile strength. Various pharmaceutical excipients (MCC PH 101, MCC PH 102, MCC DG, Mannitol Pearlitol 200SD, Lactose, and binary mixtures) were considered. Granules were also produced with dry granulation using roll compaction. The feed powders and granules were then compressed at various compression pressures to produce tablets with different porosities, and the corresponding tensile strengths were measured. For the CI modelling, the efficiency of seven bio-inspired optimization algorithms were explored: grey wolf optimization (GWO), bat optimization (BAT), cuckoo search (CS), flower pollination algorithm (FPA), genetic algorithm (GA), particle swarm optimization (PSO), and social spider optimization (SSO). Two-thirds of the experimental dataset was randomly chosen as the training set, and the remaining was used to validate the model prediction. The model efficiency was evaluated in terms of the average reduction (representing the fraction of selected input variables) and the mean square error (MSE). It was found that the CI models can well predict the tablet characteristics (i.e. porosity and tensile strength). It was also shown that the GWO algorithm was the most accurate in predicting porosity. While the most accurate prediction for the tensile strength was achieved using the SSO algorithm. In terms of the average reduction, the GA algorithm resulted in the highest reduction of inputs (i.e. 60%) for predicting both the porosity and the tensile strength.     

Radio resource management for LTE-A relay-enhanced cells with spatial reuse and max–min fairness

One of the major issues in LTE-Advanced (LTE-A) systems is the poor capacity at the cell edge. This is mainly due to the interference experienced by the users as a result of the aggressive frequency reuse usually implemented. Relaying offers an attractive solution for this problem by offering better links than those with the eNodeB (eNB) for the terminals suffering from high path loss or high interference. However, adding relays complicates the resource allocation problem at the eNB and therefore the need for more efficient schemes arises. This is also aggravated by the reuse of resource blocks (RBs) by the relays to fully exploit the scarce spectrum, which, in turn, leads to intra-cell interference. In this paper, we study the joint power and resource allocation problem in LTE-A relay-enhanced cells that exploit spatial reuse. To guarantee fairness among users, a max–min fair optimization objective is used. This complex problem is solved using coordinate ascent and the difference of two convex functions (DC) programming techniques and the proposed scheme indeed converges to a local-optimum quickly. This is shown to be a satisfactory solution according to the simulation results that indicate an almost sevenfold increase in the 10th percentile capacity when compared to previously proposed solutions.     

Evaluation of direct light processing for the fabrication of bioactive ceramic scaffolds: Effect of pore/strut size on manufacturability and mechanical performance

Bioactive ceramic scaffolds for bone regeneration consisting of a three-dimensional mesh of interpenetrating struts with square section were fabricated via Digital Light Processing (DLP). The ability of the technique to manufacture 3D porous structures from β-tricalcium phosphate (β-TCP) powders with different dimensions of struts and pores was evaluated, identifying the possibilities and limitations of the manufacturing process. Small pore sizes were found to seriously complicate the elimination of excess slurry from the scaffold’s innermost pores. The effect of the strut/pore size on the mechanical performance of the scaffolds under compressive stresses was also evaluated, but no significant influence was found. Under compressive stresses, the structures resulted weaker when tested perpendicularly to the printing plane due to interlayer shear failure. Interlayer superficial grooves are proposed as potential failure-controlling defects, which could also explain the lack of a Weibull size effect on the mechanical strength of the fabricated DLP scaffolds.     

Numerical characterization of a piezoelectric composite with hollow metal fillers including new figures of merit,pore shape effects,and distinct piezoceramic types

International Journal of Mechanics and Materials in Design - This paper focuses on the numerical analysis of the properties of porous piezoelectric composites with metal-doped pore surfaces and...     

A multi-variate heart disease optimization and recognition framework

Neural Computing and Applications - Cardiovascular diseases (CVD) are the most widely spread diseases all over the world among the common chronic diseases. CVD represents one of the main causes of...