We have performed numerical and experimental studies of the flow in a large aspect ratio Couette-Taylor system with a rotating inner cylinder and a fixed radial temperature gradient. The base flow state is a superposition of an azimuthal flow induced by rotation and an axial large convective cell induced by the temperature gradient. For a relatively large temperature gradient, the rotation rate of the inner cylinder destabilizes the convective cell to give rise to travelling wave pattern through a subcritical bifurcation. This wave pattern is associated with a temperature mode and it consists of helical vortices travelling in the annulus. In a small range of the rotation rate, helical vortices have longitudinal meandering leading to the formation of kinks randomly distributed, leading to spatio-temporal disordered patterns. The flow becomes regular for a large interval of rotation rate. The friction, the momentum and the heat transfer coefficients are computed and found to be independent of the heating direction. This article is part of the theme issue 'Taylor-Couette and related flows on the centennial of Taylor's seminal paper (part 1)'.
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http://dx.doi.org/10.1098/rsta.2022.0117 | DOI Listing |
J Mol Model
January 2025
Shanxi Jiangyang Chemical Limited Company, Taiyuan, 030041, Shanxi, China.
Context: DNAN/DNB cocrystals, as a newly developed type of energetic material, possess superior safety and thermal stability, making them a suitable alternative to traditional melt-cast explosives. Nonetheless, an exploration of the thermal degradation dynamics of the said cocrystal composite has heretofore remained uncharted. Consequently, we engaged the ReaxFF/lg force field modality to delve into the thermal dissociation processes of the DNAN/DNB cocrystal assembly across a spectrum of temperatures, encompassing 2500, 2750, 3000, 3250, and 3500 K.
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January 2025
Department of Biology, Colorado State University, Fort Collins, Colorado, USA.
Identifying populations at highest risk from climate change is a critical component of conservation efforts. However, vulnerability assessments are usually applied at the species level, even though intraspecific variation in exposure, sensitivity and adaptive capacity play a crucial role in determining vulnerability. Genomic data can inform intraspecific vulnerability by identifying signatures of local adaptation that reflect population-level variation in sensitivity and adaptive capacity.
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January 2025
Department of Oral & Maxillofacial Surgery and Diagnostic Sciences, Faculty of Dentistry, Taif University, 21944, Taif, Saudi Arabia.
This study investigates the use of machine learning models to predict solubility of rivaroxaban in binary solvents based on temperature (T), mass fraction (w), and solvent type. Using a dataset with over 250 data points and including solvents encoded with one-hot encoding, four models were compared: Gradient Boosting (GB), Light Gradient Boosting (LGB), Extra Trees (ET), and Random Forest (RF). The Jellyfish Optimizer (JO) algorithm was applied to tune hyperparameters, enhancing model performance.
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January 2025
National and Local United Engineering Laboratory of Flat Panel Display Technology, College of Physics and Information Engineering, Fuzhou University, 350108, Fuzhou, China.
Multifunctional materials have attracted tremendous attention in intelligent and interactive devices. However, achieving multi-dimensional sensing capabilities with the same perovskite quantum dot (PQD) material is still in its infancy, with some considering it currently challenging and even unattainable. Drawing inspiration from neurons, a novel multifunctional CsPbBr/PDMS nanosphere is devised to sense humidity, temperature, and pressure simultaneously with unique interactive responses.
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January 2025
Department of Geography, Faculty of Science, Environment and Economy, University of Exeter, Exeter, UK.
Understanding the effects of multiple stressors has become a major focus in ecology and evolution. While many studies have investigated the combined effects of stressors, revealing massive variability, a mechanistic understanding that reconciles the diversity of multiple stressor outcomes is lacking. Here, we show how performance curves can fill this gap by revealing mechanisms that shape multiple stressor outcomes.
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