Through intricate calculations, the density functional theory (DFT) implemented in the Wien2k code was employed to comprehensively investigate a wide range of material characteristics. Our study encompasses an exhaustive analysis of structural stability, electronic properties, magnetic behaviors, transport phenomena, mechanical responses, and thermodynamic profiles of two notable instances of filled Skutterudites, namely, CeNiP and DyCoSb, which have been thoroughly explored. These computations were performed using the WIEN 2K code, combining local orbitals and the full-potential linearized augmented plane-wave approach. The findings provided insight into the wide range of properties of these materials. In this methodology, the exchange-correlation potential relies on the local-density approximation. We conducted the calculations with and without incorporating spin-orbit interactions. The results obtained provide information about the lattice constant, bulk modulus, and pressure derivative. The stability, as indicated by the P-V graphical plot, suggests that there are no structural phase transitions from the cubic symmetry structure. Notably, our work includes an examination of Curie temperatures, which are pivotal in understanding magnetic phase transitions. The validated elastic properties further support the material's stability and corroborate its ductile nature. These alloys should be considered for spintronic and thermoelectric applications due to their estimated transport characteristics and the observed ductile nature. To enhance our understanding of the thermal stability of antimony-based compounds, we have made reliable estimations of the thermophysical characteristics. By integrating theoretical insights with practical implications, we bridge the gap between fundamental understanding and material design applications. Using DFT in the Wien2k framework, we discover connections and patterns among different properties, showing how to create materials with specific functions and better performance. This approach not only advances our fundamental comprehension of materials but also promises innovation across various technological domains.
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http://dx.doi.org/10.1021/acsomega.3c06694 | DOI Listing |
Proc Natl Acad Sci U S A
January 2025
Applied Mathematics Laboratory, Courant Institute of Mathematical Sciences, Department of Mathematics, New York University, New York, NY 10012.
Mechanical systems with moving points of contact-including rolling, sliding, and impacts-are common in engineering applications and everyday experiences. The challenges in analyzing such systems are compounded when an object dynamically explores the complex surface shape of a moving structure, as arises in familiar but poorly understood contexts such as hula hooping. We study this activity as a unique form of mechanical levitation against gravity and identify the conditions required for the stable suspension of an object rolling around a gyrating body.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Political Science, Middlebury College, Middlebury, Vermont, United States of America.
Assessing whether texts are positive or negative-sentiment analysis-has wide-ranging applications across many disciplines. Automated approaches make it possible to code near unlimited quantities of texts rapidly, replicably, and with high accuracy. Compared to machine learning and large language model (LLM) approaches, lexicon-based methods may sacrifice some in performance, but in exchange they provide generalizability and domain independence, while crucially offering the possibility of identifying gradations in sentiment.
View Article and Find Full Text PDFJ Healthc Manag
January 2025
Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Goal: This study aimed to compare the value of tax exemptions and community benefits across various nonprofit hospitals and show how hospital and geographical characteristics can explain the values.
Methods: Data from 2017 to 2021 Internal Revenue Service Form 990s were used to evaluate 17 types of community benefits in nonprofit hospitals and assess six categories of tax benefits. Descriptive analyses compared charity care, community benefits, and estimated tax exemptions among nonprofit hospitals while considering variations in teaching status, location (rurality), and US region.
Elife
January 2025
Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.
Data-driven models of neurons and circuits are important for understanding how the properties of membrane conductances, synapses, dendrites, and the anatomical connectivity between neurons generate the complex dynamical behaviors of brain circuits in health and disease. However, the inherent complexity of these biological processes makes the construction and reuse of biologically detailed models challenging. A wide range of tools have been developed to aid their construction and simulation, but differences in design and internal representation act as technical barriers to those who wish to use data-driven models in their research workflows.
View Article and Find Full Text PDFAdv Skin Wound Care
January 2025
At the Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, United States, Adrian Chen, BS, Aleksandra Qilleri, BS, and Timothy Foster, BS, are Medical Students. Amit S. Rao, MD, is Project Manager, Department of Surgery, Wound Care Division, Northwell Wound Healing Center and Hyperbarics, Northwell Health, Hempstead. Sandeep Gopalakrishnan, PhD, MAPWCA, is Associate Professor and Director, Wound Healing and Tissue Repair Analytics Laboratory, School of Nursing, College of Health Professions, University of Wisconsin-Milwaukee. Jeffrey Niezgoda, MD, MAPWCA, is Founder and President Emeritus, AZH Wound Care and Hyperbaric Oxygen Therapy Center, Milwaukee, and President and Chief Medical Officer, WebCME, Greendale, Wisconsin. Alisha Oropallo, MD, is Professor of Surgery, Donald and Barbara Zucker School of Medicine and The Feinstein Institutes for Medical Research, Manhasset New York; Director, Comprehensive Wound Healing Center, Northwell Health; and Program Director, Wound and Burn Fellowship program, Northwell Health.
Generative artificial intelligence (AI) models are a new technological development with vast research use cases among medical subspecialties. These powerful large language models offer a wide range of possibilities in wound care, from personalized patient support to optimized treatment plans and improved scientific writing. They can also assist in efficiently navigating the literature and selecting and summarizing articles, enabling researchers to focus on impactful studies relevant to wound care management and enhancing response quality through prompt-learning iterations.
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