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We propose a mapping from NACE codes of economic activities, into Climate Policy Relevant Sectors (CPRS) and into the variables of the process-based Integrated Assessment Models (IAM) used by the Network for Greening the Financial System (NGFS) to provide its climate scenarios. We discuss the classification of CPRS at the disaggregation level provided by CPRS Granular, which distinguishes across energy technologies (e.g. within transport, motor vehicles powered by combustion vs electric engines). Then, we describe the mapping of NACE 4-digit – CPRS Granular – IAM variables used in the scenarios of the NGFS. CPRS enable users to group the large number of NACE codes into few categories of climate transition risk. At this point, it is possible to identify for each NACE economic activity the most relevant IAM variable to use in the NGFS scenarios. This procedure enables the use of climate scenarios (e.g. NGFS) for climate-related financial disclosure and climate stress testing. The goal of this note, and of the proposed mapping is to support practitioners, financial supervisors, investors and academics in climate transition risk disclosure and climate transition risk assessment, providing a science-based, transparent and operational tool.

We propose a mapping from NACE codes of economic activities, into Climate Policy Relevant Sectors (CPRS) and into the variables of the process-based Integrated Assessment Models (IAM) used by the Network for Greening the Financial System (NGFS) to provide its climate scenarios. We discuss the classification of CPRS at the disaggregation level provided by CPRS Granular, which distinguishes across energy technologies (e.g. within transport, motor vehicles powered by combustion vs electric engines). Then, we describe the mapping of NACE 4-digit – CPRS Granular – IAM variables used in the scenarios of the NGFS. CPRS enable users to group the large number of NACE codes into few categories of climate transition risk. At this point, it is possible to identify for each NACE economic activity the most relevant IAM variable to use in the NGFS scenarios. This procedure enables the use of climate scenarios (e.g. NGFS) for climate-related financial disclosure and climate stress testing. The goal of this note, and of the proposed mapping is to support practitioners, financial supervisors, investors and academics in climate transition risk disclosure and climate transition risk assessment, providing a science-based, transparent and operational tool.

We propose a mapping from NACE codes of economic activities, into Climate Policy Relevant Sectors (CPRS) and into the variables of the process-based Integrated Assessment Models (IAM) used by the Network for Greening the Financial System (NGFS) to provide its climate scenarios. We discuss the classification of CPRS at the disaggregation level provided by CPRS Granular, which distinguishes across energy technologies (e.g. within transport, motor vehicles powered by combustion vs electric engines). Then, we describe the mapping of NACE 4-digit – CPRS Granular – IAM variables used in the scenarios of the NGFS. CPRS enable users to group the large number of NACE codes into few categories of climate transition risk. At this point, it is possible to identify for each NACE economic activity the most relevant IAM variable to use in the NGFS scenarios. This procedure enables the use of climate scenarios (e.g. NGFS) for climate-related financial disclosure and climate stress testing. The goal of this note, and of the proposed mapping is to support practitioners, financial supervisors, investors and academics in climate transition risk disclosure and climate transition risk assessment, providing a science-based, transparent and operational tool.

The financial system—the ecosystem of investors (e.g., banks, investment funds, insurance), markets, and instruments—is often considered to play an enabling role in climate mitigation pathways to a low-carbon transition. But it can also have a hampering role, e.g., if investors’ perceptions of low risk from a missed transition and low opportunities from a transition fail to trigger a reallocation of capital into low-carbon investments. This increases the chance of the transition not occurring within the time window required to stabilize the climate or occurring in a disorderly fashion. Indeed investors, who can influence the realization of climate mitigation pathways, themselves rely on estimates of climate mitigation pathways from process-based integrated assessment models (IAMs). And IAMs do not model the financial system or investors’ decisions; thus, the feedback loop between the financial system and mitigation pathways is not taken into account, neither by the IAMs nor by the finance community. This limitation to our understanding of the dynamics and the feasibility of the low-carbon transition weakens the ability of IAMs to inform policy and investment decisions. We propose a framework to capture the interdependence between investors’ perception of future climate risk, depending on the credibility of climate policies, and the allocation of investments in the economy.

The financial system—the ecosystem of investors (e.g., banks, investment funds, insurance), markets, and instruments—is often considered to play an enabling role in climate mitigation pathways to a low-carbon transition. But it can also have a hampering role, e.g., if investors’ perceptions of low risk from a missed transition and low opportunities from a transition fail to trigger a reallocation of capital into low-carbon investments. This increases the chance of the transition not occurring within the time window required to stabilize the climate or occurring in a disorderly fashion. Indeed investors, who can influence the realization of climate mitigation pathways, themselves rely on estimates of climate mitigation pathways from process-based integrated assessment models (IAMs). And IAMs do not model the financial system or investors’ decisions; thus, the feedback loop between the financial system and mitigation pathways is not taken into account, neither by the IAMs nor by the finance community. This limitation to our understanding of the dynamics and the feasibility of the low-carbon transition weakens the ability of IAMs to inform policy and investment decisions. We propose a framework to capture the interdependence between investors’ perception of future climate risk, depending on the credibility of climate policies, and the allocation of investments in the economy.

The financial system—the ecosystem of investors (e.g., banks, investment funds, insurance), markets, and instruments—is often considered to play an enabling role in climate mitigation pathways to a low-carbon transition. But it can also have a hampering role, e.g., if investors’ perceptions of low risk from a missed transition and low opportunities from a transition fail to trigger a reallocation of capital into low-carbon investments. This increases the chance of the transition not occurring within the time window required to stabilize the climate or occurring in a disorderly fashion. Indeed investors, who can influence the realization of climate mitigation pathways, themselves rely on estimates of climate mitigation pathways from process-based integrated assessment models (IAMs). And IAMs do not model the financial system or investors’ decisions; thus, the feedback loop between the financial system and mitigation pathways is not taken into account, neither by the IAMs nor by the finance community. This limitation to our understanding of the dynamics and the feasibility of the low-carbon transition weakens the ability of IAMs to inform policy and investment decisions. We propose a framework to capture the interdependence between investors’ perception of future climate risk, depending on the credibility of climate policies, and the allocation of investments in the economy.

In the first collaboration between climate economists, climate financial risk modellers and financial regulators, we apply the CLIMAFIN framework described in Battiston at al. (2019) to provide a forward-looking climate transition risk assessment of the sovereign bonds’ portfolios of solo insurance companies in Europe. We consider a scenario of a disorderly introduction of climate policies that cannot be fully anticipated and priced in by investors. First, we analyse the shock on the market share and profitability of carbon-intensive and low-carbon activities under climate transition risk scenarios. Second, we define the climate risk management strategy under uncertainty for a risk averse investor that aims to minimise her largest losses. Third, we price the climate policies scenarios in the probability of default of the individual sovereign bonds and in the bonds’ climate spread. Finally, we estimate the largest gains/losses on the insurance companies’ portfolios conditioned to the climate scenarios. We find that the potential impact of a disorderly transition to low-carbon economy on insurers portfolios of sovereign bonds is moderate in terms of its magnitude. However, it is non-negligible in several scenarios. Thus, it should be regularly monitored and assessed given the importance of sovereign bonds in insurers’ investment portfolios.

In the first collaboration between climate economists, climate financial risk modellers and financial regulators, we apply the CLIMAFIN framework described in Battiston at al. (2019) to provide a forward-looking climate transition risk assessment of the sovereign bonds’ portfolios of solo insurance companies in Europe. We consider a scenario of a disorderly introduction of climate policies that cannot be fully anticipated and priced in by investors. First, we analyse the shock on the market share and profitability of carbon-intensive and low-carbon activities under climate transition risk scenarios. Second, we define the climate risk management strategy under uncertainty for a risk averse investor that aims to minimise her largest losses. Third, we price the climate policies scenarios in the probability of default of the individual sovereign bonds and in the bonds’ climate spread. Finally, we estimate the largest gains/losses on the insurance companies’ portfolios conditioned to the climate scenarios. We find that the potential impact of a disorderly transition to low-carbon economy on insurers portfolios of sovereign bonds is moderate in terms of its magnitude. However, it is non-negligible in several scenarios. Thus, it should be regularly monitored and assessed given the importance of sovereign bonds in insurers’ investment portfolios.

Conjugated polymer poly(3,4-dioxyethylenthiofene) (PEDOT) has recently gained attention for room-temperature thermoelectric applications due to its low cost, safety and the possibility of easy processing. This makes it an interesting prospective alternative to tellurides commonly used around room temperature. Still, low thermoelectric efficiencies of polymers might be more easily increased, were a model of its transport properties available. The aim of this paper is to validate a model recently reported, making use of the concept of transport energy to frame the onset of transport properties reported over the last few years in the literature. To this aim, PEDOT and PEDOT-based nanocomposites embedding CuO nanoplatelets were prepared and analysed. We found that the model adequately fits the trends observed in pure PEDOT and in its nanocomposites. Transport and Fermi energy were verified to depend on the polymer oxidation level only,while the transport coefficient was found to be sensitive to PEDOT stacking and was modulated by the introduction of CuO nanoplatelets.

This paper describes the vision of a European Exploratory for economics and finance using an interdisciplinary consortium of economists, natural scientists, computer scientists and engineers, who will combine their expertise to address the enormous challenges of the 21st century. This Academic Public facility is intended for economic modelling, investigating all aspects of risk and stability, improving financial technology, and evaluating proposed regulatory and taxation changes. The European Exploratory for economics and finance will be constituted as a network of infrastructure, observatories, data repositories, services and facilities and will foster the creation of a new cross-disciplinary research community of social scientists, complexity scientists and computing (ICT) scientists to collaborate in investigating major issues in economics and finance. It is also considered a cradle for training and collaboration with the private sector to spur spin-offs and job creations in Europe in the finance and economic sectors. The Exploratory will allow Social Scientists and Regulators as well as Policy Makers and the private sector to conduct realistic investigations with real economic, financial and social data. The Exploratory will (i) continuously monitor and evaluate the status of the economies of countries in their various components, (ii) use, extend and develop a large variety of methods including data mining, process mining, computational and artificial intelligence and every other computer and complex science techniques coupled with economic theory and econometric, and (iii) provide the framework and infrastructure to perform what-if analysis, scenario evaluations and computational, laboratory, field and web experiments to inform decision makers and help develop innovative policy, market and regulation designs. Graphical abstract

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

Higher manganese silicides (HMS), represented by MnSix (x = 1.71-1.75), are promising p-type candidates for thermoelectric (TE) energy harvesting systems at intermediate temperature range. The materials are very attractive as they may replace lead based compounds due to their non-toxicity, low cost of starting materials, and high thermal and chemical stability. Dense pellets were obtained through fast reactive sintering by spark plasma sintering (SPS). The addition -or nanoinclusion, of Al and Mg permitted the figure of merit enhancement of the material obtained with this technique, reaching the highest value of 0.40 at 600°C. Morphology, composition and crystal structure of the samples were characterized by electron microscopies, energy dispersive X-ray spectroscopy, and X-ray diffraction analyses, respectively., QC 20170208

Higher manganese silicides (HMS), represented by MnSix (x = 1.71-1.75), are promising p-type candidates for thermoelectric (TE) energy harvesting systems at intermediate temperature range. The materials are very attractive as they may replace lead based compounds due to their nontoxicity, low cost of starting materials, and high thermal and chemical stability. Dense pellets were obtained through fast reactive sintering by spark plasma sintering (SPS). The addition -or nanoinclusion, of Al and Mg permitted the figure of merit enhancement of the material obtained with this technique, reaching the highest value of 0.40 at 600 degrees C. Morphology, composition and crystal structure of the samples were characterized by electron microscopies, energy dispersive X-ray spectroscopy, and X-ray diffraction analyses, respectively.

Possibilities to use conjugated polymers as thermoelectric materials have been widely explored in the last few years, giving rewarding results1,2. Such materials are particularly appealing for room temperature application and flexible devices. Since the main drawback in conjugated polymer thermoelectric application is their low efficiency, several different paths have been explored in order to optimize performances3,4. Among them, the development of copolymers is still a mostly unexplored field, due to the increase of the system complexity that they involve. Although the challenge that they represent under a solid-state physics point of view, copolymers are also a novel chance to gain new information about thermoelectric related features in conjugated polymers. Copolymers mainly used for this purpose are copolymers within two different categories. On one side there are donor-acceptor copolymers5, on the other conjugated-not conjugated copolymers6, or partially conjugated copolymers. An overview of the state of art will be given, in order to collect the results currently achieved in this field considering both categories, with a particular attention to synthetic strategies and performance enhancing procedures adopted. Specifically, the thermoelectric behaviour of a novel poly(3,4-ethylenedioxythiophene) (PEDOT) based copolymer (Figure 1) and its blends with PEDOT:tosylate will be presented and discussed. Such derivative belongs to the second category and the study of thermoelectric properties of its blends with the pristine PEDOT has shown that charge transport is percolative (Figure 2). Percolation (Figure 3) can be a key to tune the organic material thermoelectric properties in order to achieve better performances. The results obtained will be discussed in the light of such purpose and possible future developments will be presented. [1] Q. Wei, M. Mukaida, K. Kirihara, Y. Naitoh and T. Ishida, Materials (Basel)., 2015, 8, 732-750. [2] B. Russ, A. Glaudell, J. J. Ur

Thermoelectric application of conjugated polymers has recently become a subject of scientific interest. This is due to the peculiar features of these organic materials, such as low cost, safety, abundance of atomic components, and easy processing, which make them an interesting alternative to inorganic materials commonly used for this application in the room temperature range, i.e., tellurides derivatives, such as Bi2Te3 and Sb2Te3. Two are the main drawbacks of organic materials employment: the first is their poor thermoelectrical performance, which is still low in comparison with inorganic benchmark, the second is the scarcity of stable and easy-to-dope n-type polymers. In order to address the first issue, we tried to obtain a further and crucial efficiency improvement, developing a nanocomposite embedding inorganic nanoparticles in a matrix of conjugated polymer. A hybrid film of poly(3,4-ethylenedioxithiophene):Tosylate (PEDOT:Tos) and Mn3O4 nanoparticles have been achieved through a novel strategy, involving nanoparticle functionalization and in situ polymerization. The purpose is to enable energy filtering thanks to the presence of the NPs so as to extend this beneficial effect already been observed in inorganic semiconductor to polymers. Our study indicates a new path to obtain PEDOT-based nanocomposite and enlightens the peculiar behaviour of this hybrid material.

Organic materials have recently gained attention as a valuable choice for electronic applications, such as organic field-effect transistors (OFETs)1, organic light-emitting diodes (OLEDs)2, memories3, photovoltaic cells4 and sensors5. Also thermoelectric applications have been proposed, and a variety of studies about this topic have been developed in the last few years6,7. Particularly, the use of the conductive polymer poly(3,4-ethylendioxithiophene), or PEDOT, appeared attractive due to its high electrical conductivity, its low thermal conductivity, its good environmental stability and its easy processability. Now a days the thermoelectric performance of this polymer is still poor, in comparison with inorganic benchmarks, though several attempts have been made to increase its efficiency8,9. In order to obtain a PEDOT-based material with improved features, we decided to embed inorganic nanoparticles in the polymeric matrix. This will generate an energy filtering effect in the hybrid material, which can lead to an increase of the Seebeck coefficient and, at the same time, an improvement of the carrier average mobility through a selection of the more energetic holes. The expected total result is the enhancement of the nanocomposite power factor10. For such purpose, we developed a chemical path to allow an interaction between the polymer and the inorganic nanoparticles, which involves the grafting of the monomer on the nanoparticle surface (Figure 1), and defined a protocol to obtain samples of hybrid material that can be thermoelectrically characterized. In order to understand if it is possible to exploit the energy filtering effect in such samples, several parameters have to be modified, such as the oxidation level of the polymer and the size and the concentration of the nanoparticles, and the resulting variations in the features of the material are currently being studied. In the present work we report the investigation of the variation of the nanoparticle concentr

Organic materials have recently gained attention as a valuable choice for electronic applications, such as organic field-effect transistors (OFETs)1, organic light-emitting diodes (OLEDs)2, memories3, photovoltaic cells4 and sensors5. Also thermoelectric applications have been proposed, and a variety of studies about this topic have been developed in the last few years6,7. Particularly, the use of the conductive polymer poly(3,4-ethylendioxithiophene), or PEDOT, appeared attractive due to its high electrical conductivity, its low thermal conductivity, its good environmental stability and its easy processability. Now a days the thermoelectric performance of this polymer is still poor, in comparison with inorganic benchmarks, though several attempts have been made to increase its efficiency8,9. In order to obtain a PEDOT-based material with improved features, we decided to embed inorganic nanoparticles in the polymeric matrix. This will generate an energy filtering effect in the hybrid material, which can lead to an increase of the Seebeck coefficient and, at the same time, an improvement of the carrier average mobility through a selection of the more energetic holes. The expected total result is the enhancement of the nanocomposite power factor10. For such purpose, we developed a chemical path to allow an interaction between the polymer and the inorganic nanoparticles, which involves the grafting of the monomer on the nanoparticle surface (Figure 1), and defined a protocol to obtain samples of hybrid material that can be thermoelectrically characterized. In order to understand if it is possible to exploit the energy filtering effect in such samples, several parameters have to be modified, such as the oxidation level of the polymer and the size and the concentration of the nanoparticles, and the resulting variations in the features of the material are currently being studied. In the present work we report the investigation of the variation of the nanoparticle concentr

Higher manganese silicides (HMS) are proven to be promising candidates as p-type thermoelectric material in the temperature range of 400-700 K. In this work, a series of nanostructured (NS) bulk MnSi1.73 with different levels of Ytterbium inclusions were fabricated via ball milling and the solid state reaction was completed by spark plasma sintering (SPS). Nanopowders and SPS consolidated Yb-HMS nanocomposites (NC) were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM) to reveal the crystal structure and morphology respectively. High resolution transmission electron microscopy (HRTEM) coupled with energy dispersive X-ray spectroscopy (EDS) was used to investigate the material composition in bulk grains. Yb was observed to stay as nanoinclusions at the grain boundaries. TE transport properties, including Seebeck coefficient, electrical resistivity, and thermal diffusivity as well as charge carrier concentrations were evaluated. Thermal conductivity decreased with increasing Yb content, while the electrical conductivity improved for the highest Yb content. A highest figure of merit (ZT) of 0.42 at 600 degrees C was achieved for 1% Yb-HMS NC sample., QC 20141212

Higher manganese silicides (HMS) are proven to be promising candidates as p-type thermoelectric material in the temperature range of 400-700 K. In this work, a series of nanostructured (NS) bulk MnSi1.73 with different levels of Ytterbium inclusions were fabricated via ball milling and the solid state reaction was completed by spark plasma sintering (SPS). Nanopowders and SPS consolidated Yb-HMS nanocomposites (NC) were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM) to reveal the crystal structure and morphology respectively. High resolution transmission electron microscopy (HRTEM) coupled with energy dispersive X-ray spectroscopy (EDS) was used to investigate the material composition in bulk grains. Yb was observed to stay as nanoinclusions at the grain boundaries. TE transport properties, including Seebeck coefficient, electrical resistivity, and thermal diffusivity as well as charge carrier concentrations were evaluated. Thermal conductivity decreased with increasing Yb content, while the electrical conductivity improved for the highest Yb content. A highest figure of merit (ZT) of 0.42 at 600 degrees C was achieved for 1% Yb-HMS NC sample., AuthorCount:8

Magnesium silicide (Mg2Si)-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 Mg2Si 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 Mg2Si materials was also investigated. Synthesis was performed by ball milling in an inert atmosphere starting from commercial Mg2Si 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. Mg2Si 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., QC 20140707

Magnesium silicide (Mg2Si)-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 Mg2Si 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 Mg2Si materials was also investigated. Synthesis was performed by ball milling in an inert atmosphere starting from commercial Mg2Si 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. Mg2Si 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., AuthorCount:9

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 A degrees C for samples processed at 750 A degrees C, reaching a final ZT of 0.14 at 600 A degrees C., QC 20130201

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., QC 20130812

The higher manganese silicides (HMS), represented by MnSi (x) (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 600A degrees C for the sample sintered at 900A degrees C and 90 MPa with 5 min holding time., QC 20130812

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 600A degrees 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 600A degrees C., QC 20130812

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., AuthorCount:9

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 A degrees C for samples processed at 750 A degrees C, reaching a final ZT of 0.14 at 600 A degrees C., AuthorCount:9

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 600A degrees 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 600A degrees C., AuthorCount:10

In this paper we study the conditions upon which a default cascade (i.e. an avalanche of bankruptcies) can occur.

This paper describes the vision of a European Exploratory for economics and finance using an interdisciplinary consortium of economists, natural scientists, computer scientists and engineers, who will combine their expertise to address the enormous challenges of the 21st century. This Academic Public facility is intended for economic modelling, investigating all aspects of risk and stability, improving financial technology, and evaluating proposed regulatory and taxation changes. The European Exploratory for economics and finance will be constituted as a network of infrastructure, observatories, data repositories, services and facilities and will foster the creation of a new cross-disciplinary research community of social scientists, complexity scientists and computing (ICT) scientists to collaborate in investigating major issues in economics and finance. It is also considered a cradle for training and collaboration with the private sector to spur spin-offs and job creations in Europe in the finance and economic sectors. The Exploratory will allow Social Scientists and Regulators as well as Policy Makers and the private sector to conduct realistic investigations with real economic, financial and social data. The Exploratory will (i) continuously monitor and evaluate the status of the economies of countries in their various components, (ii) use, extend and develop a large variety of methods including data mining, process mining, computational and artificial intelligence and every other computer and complex science techniques coupled with economic theory and econometric, and (iii) provide the framework and infrastructure to perform what-if analysis, scenario evaluations and computational, laboratory, field and web experiments to inform decision makers and help develop innovative policy, market and regulation designs. Graphical abstract

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