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Magnesium silicide (MgSi)-based alloys are promising candidates for thermoelectric (TE) energy conversion in the middle-high temperature range. The detrimental effect of the presence of MgO on the TE properties of MgSi based materials is widely known. For this reason, the conditions used for synthesis and sintering were optimized to limit oxygen contamination. The effect of Bi doping on the TE performance of dense MgSi materials was also investigated. Synthesis was performed by ball milling in an inert atmosphere starting from commercial MgSi powder and Bi powder. The samples were consolidated, by spark plasma sintering, to a density >95%. The morphology, and the composition and crystal structure of samples were characterized by field-emission scanning electronic microscopy and x-ray diffraction, respectively. Moreover, determination of Seebeck coefficients and measurement of electrical and thermal conductivity were performed for all the samples. MgSi with 0.1 mol% Bi doping had a ZT value of 0.81, indicative of the potential of this method for fabrication of n-type bulk material with good TE performance. [ABSTRACT FROM AUTHOR]

The higher manganese silicides (HMS), represented by MnSi ( x = 1.71 to 1.75), are promising p-type leg candidates for thermoelectric energy harvesting systems in the middle-high temperature range. They are very attractive as they could replace lead-based compounds due to their nontoxicity, low-cost starting materials, and high thermal and chemical stability. Dense pellets were obtained through direct reaction between Mn and Si powders during the spark plasma sintering process. The tetragonal HMS and cubic MnSi phase amounts and the functional properties of the material such as the Seebeck coefficient and electrical and thermal conductivity were evaluated as a function of the SPS processing conditions. The morphology, composition, and crystal structure of the samples were characterized by scanning electron microscopy, energy-dispersive x-ray spectroscopy, and x-ray diffraction analyses, respectively. Differential scanning calorimetry and thermogravimetric analysis were performed to evaluate the thermal stability of the final sintered material. A ZT value of 0.34 was obtained at 600°C for the sample sintered at 900°C and 90 MPa with 5 min holding time. [ABSTRACT FROM AUTHOR]

A high-temperature test rig to simultaneously measure electrical conductivity and thermopower is described. The apparatus allows to perform measurements in a controlled atmosphere or vacuum to protect oxygen-sensitive materials. A spring-loaded mounting placed in the cold zone reduces the thermal contact resistance between the sample and two metallic blocks (the hot side and the heat sink) even at high temperatures. The hot-side metal block is periodically heated to obtain the thermopower from the slope of Δ V versus Δ T. Conductivity is measured before each thermopower measurement by a linear four-wire method. The automatic data acquisition and analysis are controlled by a LabView-based interface. Two interchangeable setups are possible. The first one uses silver blocks and K-type thermocouples and is suitable for temperatures from 300 K to about 1000 K. The second one uses W blocks and S-type thermocouples to allow higher-temperature measurements since all the hot-zone parts are made of AlO, Pt or W. The device was tested using PdAg alloy and Ni rods and, for the low-temperature range, the NIST standard reference material 3451 (bismuth telluride), strictly confirming the reference data. [ABSTRACT FROM AUTHOR]

Oxide incorporation into thermoelectric MgSi-based materials was performed starting from commercial MgSi 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. [ABSTRACT FROM AUTHOR]

Magnesium silicide (MgSi)-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. MgSi could replace lead-based TE materials, due to its low cost, nontoxicity, and low density. In this work, the role of aluminum doping (MgSi:Al = 1: x for x = 0.005, 0.01, 0.02, and 0.04 molar ratio) in dense MgSi materials was investigated. The synthesis process was performed by planetary milling under inert atmosphere starting from commercial MgSi 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. [ABSTRACT FROM AUTHOR]

Recently magnesium silicide (MgSi) 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, MgSi 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 MgSi 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 MgSi 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 MgSi 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. [ABSTRACT FROM AUTHOR]

We introduce a general framework for models of cascade and contagion processes on networks, to identify their commonalities and differences. In particular, models of social and financial cascades, as well as the fiber bundle model, the voter model, and models of epidemic spreading are recovered as special cases. To unify their description, we define the net fragility of a node, which is the difference between its fragility and the threshold that determines its failure. Nodes fail if their net fragility grows above zero and their failure increases the fragility of neighbouring nodes, thus possibly triggering a cascade. In this framework, we identify three classes depending on the way the fragility of a node is increased by the failure of a neighbour. At the microscopic level, we illustrate with specific examples how the failure spreading pattern varies with the node triggering the cascade, depending on its position in the network and its degree. At the macroscopic level, systemic risk is measured as the final fraction of failed nodes, X*, and for each of the three classes we derive a recursive equation to compute its value. The phase diagram of X* as a function of the initial conditions, thus allows for a prediction of the systemic risk as well as a comparison of the three different model classes. We could identify which model class leads to a first-order phase transition in systemic risk, i.e. situations where small changes in the initial conditions determine a global failure. Eventually, we generalize our framework to encompass stochastic contagion models. This indicates the potential for further generalizations. [ABSTRACT FROM AUTHOR]

The boards of directors of the largest corporations of a country together with the directors form a dense bipartite network. The board network consists of boards connected through common directors. The director network is obtained taking the directors as nodes, and a membership in the same board as a link. These networks are involved in the decision making processes relevant to the macro-economy of a country. We present an extensive and comparative analysis of the statistical properties of the board network and the director network for the first 1000 US corporations ranked by revenue (“Fortune 1000”) in the year 1999 and for the corporations of the Italian Stock Market. We find several common statistical properties across the data sets, despite the fact that they refer to different years and countries. This suggests an underlying universal formation mechanism which is not captured in a satisfactory way by the existent network models. In particular we find that all the considered networks are Small Worlds, assortative, highly clustered and dominated by a giant component. Several other properties are examined. The presence of a lobby in a board, a feature relevant to decision making dynamics, turns out to be a macroscopic phenomenon in all the data sets. [ABSTRACT FROM AUTHOR]

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