Two-dimensional (2D) 1T-VSe has prompted significant interest due to the discrepancies regarding alleged ferromagnetism (FM) at room temperature, charge density wave (CDW) states, and the interplay between the two. We employed a combined Diffusion Monte Carlo (DMC) and density functional theory (DFT) approach to accurately investigate the magnetic properties, CDW states, and their responses to strain in monolayer 1T-VSe. Our calculations show the delicate competition between various phases, revealing critical insights into the relationship between their energetic and structural properties. We performed classical Monte Carlo simulations informed by our DMC and DFT results and found the magnetic transition temperature () of the undistorted (non-CDW) FM phase to be 228 K and the distorted (CDW) phase to be 68 K. Additionally, we studied the response of biaxial strain on the energetic stability and magnetic properties of various phases of 2D 1T-VSe and found that small amounts of strain can increase the , suggesting a promising route for engineering and enhancing magnetic behavior. Finally, we synthesized 1T-VSe and performed Raman spectroscopy measurements, which were in close agreement with our calculated results, validating our computational approach. Our work emphasizes the role of highly accurate DMC methods in advancing the understanding of monolayer 1T-VSe and provides a robust framework for future studies of 2D magnetic materials.
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http://dx.doi.org/10.1021/acsnano.4c15914 | DOI Listing |
J Chem Theory Comput
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School of Science, Constructor University, Campus Ring 1, 28759 Bremen, Germany.
The estimation of accurate free energies for antibiotic permeation via the bacterial outer-membrane porins has proven to be challenging. Atomistic simulations of the process suffer from sampling issues that are typical of systems with complex and slow dynamics, even with the application of advanced sampling methods. Ultimately, the objective is to obtain accurate potential of mean force (PMF) for a large set of antibiotics and to predict permeation rates.
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Department of Materials Science and Tecnology, Federal University of Bahia, Salvador, Brazil.
The accurate estimation of methane generation in landfills is crucial for effective greenhouse gas management and energy recovery, requiring site-specific assessments due to the inherent variability in waste composition and properties before and after disposal. This study investigates the uncertainties associated with methane generation predictions by employing a combination of stoichiometric methods, Biochemical Methane Potential (BMP) assays, and Bayesian inference. Fresh and aged (1-year-old and 5-year-old) samples collected in the tropical Saravan dump site in Gilan, Iran, were used to evaluate the waste's methane generation potential and degradation rate in the field.
View Article and Find Full Text PDFNanomaterials (Basel)
March 2025
Faculty of Physics, St. Petersburg State University, Universitetskaya Emb. 13B, 199034 St. Petersburg, Russia.
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Facultad de Ciencias Básicas, Departamento de Física y Electrónica, Universidad de Córdoba, Monteria 230002, Colombia.
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April 2025
Department of Mathematics, University of Texas at Arlington, Arlington, Texas, USA.
The mean residual life (MRL) function plays an important role in the summary and analysis of survival data. The main advantage of this function is that it summarizes the information in units of time instead of a probability scale, which requires careful interpretation. Ranked set sampling (RSS) is a sampling technique designed for situations, where obtaining precise measurements of sample units is expensive or difficult, but ranking them without referring to their accurate values is cost-effective or easy.
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