Hollow silica particles (HSPs) have become the focus of interest in many laboratories recently, because of their versatility, stemming from the ability to control their size and shape, as well as surface functionalization. Determining the mechanical stability of hollow particles is essential for their use, both in applications in which they need to retain their structure, as well as those in which they need to break down. We have synthesized a series of HSPs (inner diameter of 231 nm) with increasing wall thickness (7-25 nm), using a template approach. Their mechanical stability was measured using mercury intrusion porosimetry (MIP), which represents the novel application of the technique for these materials. The samples with complete shells break at progressively higher pressures, and samples with wall thickness ≥21 nm remain stable to the highest pressure applied (414 MPa). Other characterization methods, namely microscopy, gas adsorption, and small-angle X-ray scattering, shed light on the size parameters of the particles, as well as the porosity of the silica walls. By varying the amount of silica precursor used in the template coating step, we were able to produce hollow silicas with variable stability, thereby allowing for control of their mechanical properties.
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http://dx.doi.org/10.1021/acs.langmuir.7b00506 | DOI Listing |
Adv Sci (Weinh)
December 2024
Graduate School of Biomedical Engineering, Faculty of Engineering, and Tyree Institute of Health Engineering (IHealthE), UNSW Sydney, Kensington Campus, Sydney, NSW, 2052, Australia.
Hemodynamic stabilization is crucial in managing acute cardiac events, where compromised blood flow can lead to severe complications and increased mortality. Conditions like decompensated heart failure (HF) and cardiogenic shock require rapid and effective hemodynamic support. Current mechanical assistive devices, such as intra-aortic balloon pumps (IABP) and extracorporeal membrane oxygenation (ECMO), offer temporary stabilization but are limited to short-term use due to risks associated with prolonged blood contact.
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December 2024
School of Mechanical and Electrical Engineering, Qiqihar University, Qiqihar, 161006, China.
A prediction model of the pig house environment based on Bayesian optimization (BO), squeeze and excitation block (SE), convolutional neural network (CNN) and gated recurrent unit (GRU) is proposed to improve the prediction accuracy and animal welfare and take control measures in advance. To ensure the optimal model configuration, the model uses a BO algorithm to fine-tune hyper-parameters, such as the number of GRUs, initial learning rate and L2 normal form regularization factor. The environmental data are fed into the SE-CNN block, which extracts the local features of the data through convolutional operations.
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December 2024
Geotechnical Institute, TU Bergakademie Freiberg, Freiberg, Germany.
The development of new urban areas necessitates building on increasingly scarce land, often overlaid on weak soil layers. Furthermore, climate change has exacerbated the extent of global arid lands, making it imperative to find sustainable soil stabilization and erosion mitigation methods. Thus, scientists have strived to find a plant-based biopolymer that favors several agricultural waste sources and provides high strength and durability for sustainable soil stabilization.
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December 2024
Department of Civil, Environmental and Mechanical Engineering, University of Trento, Via Mesiano, 77, 38123, Trento, Italy.
In this study, DL-phenylalanine modified with a multiwall carbon nanotube paste electrode is used as advanced electrochemical sensor for analysing of 0.1 mM caffeic acid (CFA) with simultaneous detection of riboflavin (RFN). The developed sensors include electrochemically polymerized DL-phenylalanine (DL-PA) modified multiwall carbon nanotube paste electrode [DL-PAMMCNTPE] and bare multiwall carbon nanotube paste electrode [BMCNTPE].
View Article and Find Full Text PDFTo address the challenges of performing in-situ tests on riverbed overburden gravel, this study employs three scaling methods-equal mass substitution, similar gradation, and the mixed method-to investigate the original gradation of the gravel. Large-scale triaxial consolidated drained shear tests were conducted to evaluate the effects of the maximum particle size reduction ratio (M) and confining pressure on the stress-strain behavior, fractal dimension, particle breakage, and the parameters of the Duncan-Chang model (an elastic model describing nonlinear stress-strain relationships). The study explores how scaling, based on fractal dimension and particle breakage rate, impacts the strength and deformation characteristics of gravel materials.
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