Thermophysical properties of Fe-Cr-Ni melts are studied using electrostatic levitation and rapid solidification techniques. Six hypoeutectic FeCr Ni alloys with a Cr/Ni ratio of around 0.8 were melted and solidified at different degrees of undercooling. From the observed relationship between the undercooling and thermal plateau time, the hypercooling limit and heat of fusion of FeCr Ni melts are determined as a function of Cr mass fraction. A ratio of specific heat and total hemispherical emissivity of the Fe-Cr-Ni melts is calculated using the time-temperature profiles. A new method is presented to evaluate the temperature dependence of specific heat for undercooled melts and applied to this alloy family.
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http://dx.doi.org/10.1016/j.jct.2019.06.001 | DOI Listing |
Sci Rep
January 2025
College of Economics and Finance, Huaqiao University, Quanzhou, 362021, China.
High carbon sectors (agriculture, industry, construction, and transportation) contribute nearly 85% of carbon emissions, highlighting the urgent need for transitioning towards cleaner energy structures in these sectors. This study utilizes the undesirable SBM model to assess TFEE (total factor energy efficiency) across the total sector and high carbon sectors. It decomposes TFEE from an energy structural perspective into coal, oil, natural gas, and electric heat efficiencies.
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January 2025
Department of Computer Science, American International University-Bangladesh (AIUB), Dhaka, 1229, Bangladesh.
The transportation industry contributes significantly to climate change through carbon dioxide ( ) emissions, intensifying global warming and leading to more frequent and severe weather phenomena such as flooding, drought, heat waves, glacier melting, and rising sea levels. This study proposes a comprehensive approach for predicting emissions from vehicles using deep learning techniques enhanced by eXplainable Artificial Intelligence (XAI) methods. Utilizing a dataset from the Canadian government's official open data portal, we explored the impact of various vehicle attributes on emissions.
View Article and Find Full Text PDFPhys Rev Lett
December 2024
Duke University, Department of Physics, Durham, North Carolina 27708, USA.
The emergence of a quantum spin liquid (QSL), a state of matter that can result when electron spins are highly correlated but do not become ordered, has been the subject of a considerable body of research in condensed matter physics [1,2]. Spin liquid states have been proposed as hosts for high-temperature superconductivity [3] and can host topological properties with potential applications in quantum information science [4]. The excitations of most quantum spin liquids are not conventional spin waves but rather quasiparticles known as spinons, whose existence is well established experimentally only in one-dimensional systems; the unambiguous experimental realization of QSL behavior in higher dimensions remains challenging.
View Article and Find Full Text PDFJ Acoust Soc Am
January 2025
Key Laboratory of Modern Acoustics (MOE), School of Physics, Collaborative Innovation Centre of Advanced Microstructures, Nanjing University, Nanjing 210093, China.
In thermal therapies, accurate estimation of in-tissue power deposition density (PDD) is essential for predicting temperature distributions over time or regularizing temperature imaging. Based on our previous work on ultrasound thermometry, namely, multi-thread thermal strain imaging (MT-TSI), this work develops an in vivo PDD estimation method. Specifically, by combining the TSI model infinitesimal echo strain filter with the bio-heat transfer theory (the Pennes equation), a finite-difference time-domain model is established to allow online extraction of the PDD.
View Article and Find Full Text PDFLancet Reg Health West Pac
January 2025
National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Beijing, China.
Background: Due to global climate change, high temperature and heatwaves have become critical issues that pose a threat to human health. An effective early warning system is essential to mitigate the health risks associated with high temperature and heatwaves. However, most of the current heatwave early warning systems are not adequately developed based on the heat-health risk model, and the health impact of hot weather has not been well managed in most countries.
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