Phonon Bottleneck Identification in Disordered Nanoporous Materials

Nanoporous materials are a promising platform for thermoelectrics in that they offer high thermal conductivity tunability while preserving good electrical properties, a crucial requirement for high- effciency thermal energy conversion. Understanding the impact of the pore arrangement on thermal transport is pivotal to engineering realistic materials, where pore disorder is unavoidable. Although there has been considerable progress in modeling thermal size effects in nanostructures, it has remained a challenge to screen such materials over a large phase space due to the slow simulation time required for accurate results. We use density functional theory in connection with the Boltzmann transport equation, to perform calculations of thermal conductivity in disordered porous materials. By leveraging graph theory and regressive analysis, we identify the set of pores representing the phonon bottleneck and obtain a descriptor for thermal transport, based on the sum of the pore-pore distances between such pores. This approach provides a simple tool to estimate phonon suppression in realistic porous materials for thermoelectric applications and enhance our understanding of heat transport in disordered materials

Toward phonon-boundary engineering in nanoporous materials

Tuning thermal transport in nanostructured materials is a powerful approach to develop high-efficiency thermoelectric materials. Using a recently developed approach based on the phonon mean free path dependent Boltzmann transport equation, we compute the effective thermal conductivity of nanoporous materials with pores of various shapes and arrangements. We assess the importance of pore-pore distance in suppressing thermal transport, and identify the pore arrangement that minimizes the thermal conductivity, composed of a periodic arrangement of two misaligned rows of triangular pores. Such a configuration yields a reduction in the thermal conductivity of more than $60 \%$ with respect the simple circular aligned case with the same porosity.Comment: 4 pages, 4 figures, 1 tabl

Directional Phonon Suppression Function as a Tool for the Identification of Ultralow Thermal Conductivity Materials

Boundary-engineering in nanostructures has the potential to dramatically impact the development of materials for high-efficiency conversion of thermal energy directly into electricity. In particular, nanostructuring of semiconductors can lead to strong suppression of heat transport with little degradation of electrical conductivity. Although this combination of material properties is promising for thermoelectric materials, it remains largely unexplored. In this work, we introduce a novel concept, the directional phonon suppression function, to unravel boundary-dominated heat transport in unprecedented detail. Using a combination of density functional theory and the Boltzmann transport equation, we compute this quantity for nanoporous silicon materials. We first compute the thermal conductivity for the case with aligned circular pores, confirming a significant thermal transport degradation with respect to the bulk. Then, by analyzing the information on the directionality of phonon suppression in this system, we identify a new structure of rectangular pores with the same porosity that enables a four-fold decrease in thermal transport with respect to the circular pores. Our results illustrate the utility of the directional phonon suppression function, enabling new avenues for systematic thermal conductivity minimization and potentially accelerating the engineering of next-generation thermoelectric devices

The investments in renewable energy sources: do low carbon economies better invest in green technologies?

The aim of this study is to analyse the driving of investment in renewable energy sources in low carbon and high carbon economies. To address these issues, a dynamic panel analysis of the renewable investment in a sample of 29 countries was proposed. Results demonstrate that the dynamic of investments in renewable sources is similar in the two panels, and depends by nuclear power generation, GDP and technological efficiency. Results show that countries try to reduce their environmental footprint, decreasing the CO2 intensity . Based on the estimation results, we think that energy sustainability passes through the use of renewable resources that can complement the nuclear technology on condition that both exceed their limits.CO2 intensity; Dynamic model; Nuclear Energy

Automatic Mode Switching in Atrial Fibrillation

Automatic mode switching (AMS) algorithms were designed to prevent tracking of atrial tachyarrhythmias (ATA) or other rapidly occurring signals sensed by atrial channels, thereby reducing the adverse hemodynamic and symptomatic consequences of a rapid ventricular response. The inclusion of an AMS function in most dual chamber pacemaker now provides optimal management of atrial arrhythmias and allows the benefit of atrioventricular synchrony to be extended to a population with existing atrial fibrillation. Appropriate AMS depends on several parameters: a) the programmed parameters; b) the characteristics of the arrhythmia; c) the characteristics of the AMS algorithm. Three qualifying aspects constitute an AMS algorithm: onset, AMS response, and resynchronization. Since AMS programs also provide data on the time of onset and duration of AMS episodes, AMS data may be interpreted as a surrogate marker of ATAs recurrence. Recently, stored electrograms corresponding to episodes of ATAs have been introduced, thus clarifying the accuracy of AMS in detecting ATAs Clinically this information may be used to assess the efficacy of an antiarrhythmic intervention or the risk of thromboembolic events, and it may serve as a valuable research tool for evaluating the natural history and burden of ATAs

Preferences, trust and willingness to pay for food information: An analysis of the Italian Market

Lack of consumer trust and communication strategies are probably the main determinants of information failure in modern food markets. This study attempts to tackle these aspects affecting the quality of food information by investigating questions related to what topics are more relevant to consumers, who should disseminate trustful food information, and how communication should be conveyed. Primary data were collected both through qualitative (in depth interviews and focus groups) and quantitative research. Quantitative research was conducted by means of a questionnaire administered in 2006-2007 to a sample of Italian respondents using both a web and a traditional mail survey. Reading preferences, willingness to pay and trust towards public and private sources conveying information through a hypothetical food magazine were assessed combining factor analysis, choice modelling and a criterion-based market segmentation. The study shows that reading preferences of Italian consumers can be summarized along three dimensions: agro-food system, enjoyment and wellness. Furthermore, willingness to pay for receiving food-related information is influenced by trust towards the type of publisher, which plays also a key role in market segmentation together with socio-demographic and economic variables such as gender, age, presence of children and income. Policy implications of these findings are discussed.food information, trust, preference heterogeneity, segmentation, Italy, Food Consumption/Nutrition/Food Safety, D12, D18, D89, Q18,

Big Data Analytics for QoS Prediction Through Probabilistic Model Checking

As competitiveness increases, being able to guaranting QoS of delivered services is key for business success. It is thus of paramount importance the ability to continuously monitor the workflow providing a service and to timely recognize breaches in the agreed QoS level. The ideal condition would be the possibility to anticipate, thus predict, a breach and operate to avoid it, or at least to mitigate its effects. In this paper we propose a model checking based approach to predict QoS of a formally described process. The continous model checking is enabled by the usage of a parametrized model of the monitored system, where the actual value of parameters is continuously evaluated and updated by means of big data tools. The paper also describes a prototype implementation of the approach and shows its usage in a case study.Comment: EDCC-2014, BIG4CIP-2014, Big Data Analytics, QoS Prediction, Model Checking, SLA compliance monitorin