In the present paper, a new type of micro-mechanically motivated chain network model for rubber-like materials is proposed. The model captures topological constraints of polymer network chains, in particular, entanglements. The model demonstrates how the local molecular packing constraints modify under deformation and shows the impact of these changes on the macroscopic elasticity of the material. To this end, we combine concepts of a confining tube and a slip-link (reptation) model. In these models, entanglements of polymer chains play an important role. The nature of entanglements is discussed, and relationships governing entanglements are formulated in terms of molecular physics. In the context of nonlinear elasticity, we apply a non-affine concept which captures the liquid-like behavior of polymer networks at smaller scales in a more realistic way. Model predictions show good agreement with experimental results from uniaxial and biaxial tension tests.
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http://dx.doi.org/10.1039/d0sm02055a | DOI Listing |
Sci Total Environ
January 2025
Center for Environmental Radioactivity (CERAD) CoE, Norwegian University of Life Sciences, P.O. Box 5003, N-1432 Ås, Norway; Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences (NMBU), P.O.Box 5003, NO-1432 Ås, Norway.
Numerical transport models are important tools for nuclear emergency decision makers in that they rapidly provide early predictions of dispersion of released radionuclides, which is key information to determine adequate emergency protective measures. They can also help us understand and describe environmental processes and can give a comprehensive assessment of transport and transfer of radionuclides in the environment. Transport of radionuclides in air and ocean is affected by a number of different physico-chemical processes.
View Article and Find Full Text PDFSci Total Environ
January 2025
University of São Paulo, Luiz de Queiroz College of Agriculture, Department of Soil Science, Brazil.
Phosphorus (P) movement in soils is influenced by flow velocities, diffusion rates, and several soil characteristics and properties. In acidic soils, P is tightly bound to soil particles, reducing its availability to plants. Organomineral fertilizers combine organic matter with mineral nutrients, enhancing P fertilization efficiency, and reducing environmental impacts.
View Article and Find Full Text PDFSci Total Environ
January 2025
CATIE, Centro Agronómico Tropical de Investigación y Enseñanza, Turrialba 30501, Costa Rica.
Agricultural systems are both emitters of greenhouse gases and have the potential to sequester carbon, especially agroforestry systems. Coffee agroforestry systems offer a wide range of intensities of use of agricultural inputs and densities and management of shade trees. We assessed the agronomic carbon footprint (up to farm gate) and modelled the carbon sequestration of a range of coffee agroforestry systems across 180 farms in Costa Rica and Guatemala.
View Article and Find Full Text PDFDev Cogn Neurosci
January 2025
Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA.
The pituitary gland (PG) plays a central role in the production and secretion of pubertal hormones, with documented links to the increase in mental health symptoms during adolescence. Although literature has largely focused on examining whole PG volume, recent findings have demonstrated associations among pubertal hormone levels, including dehydroepiandrosterone (DHEA), PG subregions, and mental health symptoms during adolescence. Despite the anterior PG's role in DHEA production, studies have not yet examined potential links with transdiagnostic symptomology (i.
View Article and Find Full Text PDFLung Cancer
January 2025
Dept. of Medical Oncology, Princess Margaret Cancer Center, Toronto, ON, Canada.
Background: Manual extraction of real-world clinical data for research can be time-consuming and prone to error. We assessed the feasibility of using natural language processing (NLP), an AI technique, to automate data extraction for patients with advanced lung cancer (aLC). We assessed the external validity of our NLP-extracted data by comparing our findings to those reported in the literature.
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