Spark plasma sintering and thermoelectric evaluation of nanocrystalline magnesium silicide (Mg2Si)

Recently magnesium silicide (Mg₂Si) has received great interest from thermoelectric (TE) society because of its non-toxicity, environmental friendliness, comparatively high abundance, and low production material cost as compared to other TE systems. It also exhibited promising transport properties, including high electrical conductivity and low thermal conductivity, which improved the overall TE performance (ZT). In this work, Mg₂Si powder was obtained through high energy ball milling under inert atmosphere, starting from commercial magnesium silicide pieces (99.99 %, Alfa Aesar). To maintain fine microstructure of the powder, spark plasma sintering (SPS) process has been used for consolidation. The Mg₂Si powder was filled in a graphite die to perform SPS and the influence of process parameters as temperature, heating rate, holding time and applied pressure on the microstructure, and densification of compacts were studied in detail. The aim of this study is to optimize SPS consolidation parameters for Mg₂Si powder to achieve high density of compacts while maintaining the nanostructure. X-Ray diffraction (XRD) was utilized to investigate the crystalline phase of compacted samples and scanning and transmission electron microscopy (SEM & TEM) coupled with Energy-Dispersive X-ray Analysis (EDX) was used to evaluate the detailed microstructural and chemical composition, respectively. All sintered samples showed compaction density up to 98 %. Temperature dependent TE characteristics of SPS compacted Mg₂Si as thermal conductivity, electrical resistivity, and Seebeck coefficient were measured over the temperature range of RT 600 °C for samples processed at 750 °C, reaching a final ZT of 0.14 at 600 °C.     

Synthesis and Characterization of Al-Doped Mg2Si Thermoelectric Materials

Magnesium silicide (Mg₂Si)-based alloys are promising candidates for thermoelectric (TE) energy conversion for the middle to high range of temperature. These materials are very attractive for TE research because of the abundance of their constituent elements in the Earth’s crust. Mg₂Si could replace lead-based TE materials, due to its low cost, nontoxicity, and low density. In this work, the role of aluminum doping (Mg₂Si:Al = 1:x for x = 0.005, 0.01, 0.02, and 0.04 molar ratio) in dense Mg₂Si materials was investigated. The synthesis process was performed by planetary milling under inert atmosphere starting from commercial Mg₂Si pieces and Al powder. After ball milling, the samples were sintered by means of spark plasma sintering to density >95%. The morphology, composition, and crystal structure of the samples were characterized by field-emission scanning electron microscopy, energy-dispersive spectroscopy, and x-ray diffraction analyses. Moreover, Seebeck coefficient analyses, as well as electrical and thermal conductivity measurements were performed for all samples up to 600°C. The resultant estimated ZT values are comparable to those reported in the literature for these materials. In particular, the maximum ZT achieved was 0.50 for the x = 0.01 Al-doped sample at 600°C.     

In vitro evaluation of bioactivity of SiO2-CaO-P2O5-Na2O-CaF2-ZnO glass-ceramics

Zinc is an essential trace element that stimulates bone formation but it is also known as an inhibitor of apatite crystal growth. In this work addition of ZnO to SiO₂-CaO-P₂O₅-Na₂O-CaF₂ glass-ceramic system was made by conventional melt-quenching technique. DSC curves showed that the addition of ZnO moved the endothermic and exothermic peaks to lower temperatures. X-ray diffraction analysis did not reveal any additional phase caused by ZnO addition and showed the presence of wollastonite and hydroxyapatite crystalline phases only in all the glass-ceramic samples. As bio-implant apatite forming ability is an essential condition, the surface reactivity of the prepared glass-ceramic specimens was studied in vitro in Kokubo’s simulated body fluid (SBF) [1] with ion concentration nearly equal to human blood plasma for 30 days at 37 °C under static condition. Atomic absorption spectroscopy (AAS) was used to study the changes in element concentrations in soaking solutions and XRD, FT-IR and SEM were used to elucidate surface properties of prepared glass-ceramics, which confirmed the formation of HCAp on the surface of all glass-ceramics. It was found that the addition of ZnO had a positive effect on bioactivity of glass-ceramics and made it a potential candidate for restoration of damaged bones.     

Fabrication and modelling of the macro-mechanical properties of cross-ply laminated fibre-reinforced polymer composites using artificial neural network

The mechanical behaviour of fibre-reinforced polymer composites (FRPCs) is considered very complex due to many factors such as composition, material type, manufacturing process and end user applications. This article presents the mechanical properties and artificial neural network (ANN) modelling results of cross-ply laminated FRPCs. Twenty composite samples were fabricated by varying the number of layers of carbon fibre and glass fibre as reinforcement and polyphenylene sulphide and high-density polyethylene as matrix. Mechanical properties were measured in terms of flexural modulus, hardness, impact and transverse rupture strength. Multilayer feed-forward backpropagation ANN approach was used to predict the mechanical properties by using material type, composition and number of reinforcement and matrix layers as input variables. From 20 data patterns, 16 were used for network training and remaining 4 were used to test the models. Furthermore, trend analysis was also performed to understand the influence of inputs on developed models. It is evident from the ANN prediction results that there is good correlation between predicted and actual values within acceptable mean absolute error. The outcomes of this research will help to reduce cost and time by eliminating tedious composite property measurements and to fabricate tailored composites meeting application requirements.     

Probabilistic Modeling of Scene Dynamics for Applications in Visual Surveillance

We propose a novel method to model and learn the scene activity, observed by a static camera. The proposed model is very general and can be applied for solution of a variety of problems. The motion patterns of objects in the scene are modeled in the form of a multivariate nonparametric probability density function of spatiotemporal variables (object locations and transition times between them). Kernel Density Estimation is used to learn this model in a completely unsupervised fashion. Learning is accomplished by observing the trajectories of objects by a static camera over extended periods of time. It encodes the probabilistic nature of the behavior of moving objects in the scene and is useful for activity analysis applications, such as persistent tracking and anomalous motion detection. In addition, the model also captures salient scene features, such as the areas of occlusion and most likely paths. Once the model is learned, we use a unified Markov Chain Monte Carlo (MCMC)-based framework for generating the most likely paths in the scene, improving foreground detection, persistent labeling of objects during tracking, and deciding whether a given trajectory represents an anomaly to the observed motion patterns. Experiments with real-world videos are reported which validate the proposed approach.     

Exploiting smart spaces for interactive TV applications development

The integration of semantic technologies and TV services is a substantial innovation to improve the services to users in an environment that is extended beyond the fixed home environment. But currently, this integration is mainly limited to provide personalized recommendation services and systems by matching user static preferences. Designing and development of interactive TV (iTV) applications using semantic technologies are not realized yet. In this work, we explore the potential of introduction semantic technologies and smart spaces in design and development of iTV applications. We use an example scenario to show how future iTV applications include the mesh-up of information from different sources. We proposed a methodology and show how ontology-driven approach can help to design and develop these iTV applications. We demonstrate the suitability of our ontology-driven application development tools and rule-based approach for the development of highly dynamic context-aware iTV applications.     

Introduction of Metal Oxides into Mg2Si Thermoelectric Materials by Spark Plasma Sintering

Oxide incorporation into thermoelectric Mg₂Si-based materials was performed starting from commercial Mg₂Si and commercial metal oxides by applying ball milling and spark plasma sintering (SPS) processing. The SPS conditions, such as sintering temperature, pressure, and holding time, were optimized with the aim of obtaining both full densification and oxide incorporation. Thermoelectric characterizations, such as Seebeck coefficient and electrical and thermal conductivity, were carried out and related to the pellet compositions. The morphology, composition, and crystallographic structure of the samples were characterized by field-emission scanning electron microscopy, energy-dispersive spectrometry, and x-ray diffraction analyses, respectively.