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Mechanical properties of steel fiber-reinforced rubber concrete after elevated temperature
Neural Network Potential with Multiresolution Approach Enables Accurate Prediction of Reaction Free Energies in Solution
3D-printed gelled electrolytes for electroanalytical applications
Abstract In this work, several gelators were employed to formulate a conducive gel phase (ionic conductivity) compatible with direct ink writing/bioprinting/robocasting (different names in the literature describe the same printing technology). The main goal of this work was to evaluate gelled phases being a mixture of background electrolyte (NaCl), redox probe (Fe(CN)6 3−/4−), and gel precursor (guar gum, gelatine, agarose, and agar-agar). The studied concentration of gelators ranged from 0.1 to 4% depending on the employed system. Each gelator required a customized formulation protocol. We have found that guar gum exhibits the best printing properties (lack of aggregates blocking the printing nozzle) while giving the least reproducible electrochemical results (when a glassy carbon electrode was employed as the working electrode). The study of two other gelators (agarose and gelatin) indicated significant changes in the electrochemical properties of the investigated surface as their concentration and number of voltammetric scans were varied. The best electrochemical performance was obtained for agar-agar however, this was also a gelator causing the most problems during 3D printing. Finally, we have employed six screen-printed electrodes displaying approximate properties, that were further covered with a 3D-printed conductive gelled cube (direct printing over the electrode surface). We have found that such a system allowed for a surprisingly good electroanalytical response when the model redox probe (Fe(CN)6 3−/4−) was considered. This work is a prelude to 3D-printed gel-based detection devices we are currently developing in our team.
The impact of goat hair as a natural animal fiber on properties of the lightweight cement composite
Abstract The increasing demand for sustainable and eco-friendly construction materials has prompted the exploration of natural fibers as reinforcement in cement composites. This study investigates the potential of goat hair as a natural fiber reinforcement in lightweight cement composites to enhance mechanical properties and sustainability. The research evaluates goat-hair-reinforced composites’ flexural and compressive strengths at 7 and 28 days after mixing. The results show that the inclusion of goat hair at a rate of 0.4% of cement, as a reinforcing material, leads to a significant increase in flexural and compressive strength. Specifically, flexural strength increased by 2.5% and 21.8%, while compressive strength improved by 5.5% and 21.5% at water-to-cement ratios of 0.4 and 0.5, respectively, compared to the control mixture. The findings demonstrate the effectiveness of goat hair in improving mechanical performance while reducing the environmental footprint of construction materials. This study highlights the need for further exploration of natural fibers in sustainable construction practices, focusing on optimizing mechanical performance and eco-friendly materials for broader applications.
Molecular Distinction of Cell Wall and Capsular Polysaccharides in Encapsulated Pathogens by In Situ Magic-Angle Spinning NMR Techniques
Comparative study of cytochrome P450 expression in the kidneys of Lepus yarkandensis and Oryctolagus cuniculus
Synergistic Effects in Low-Temperature CO Oxidation on Cerium Oxide Surfaces
Transformer-based conditional generative transfer learning network for cross domain fault diagnosis under limited data
Assessment of quality in volatile oil from three basic sources of Xinyi from Hubei by anatomy, GC-MS, and chemometric methods
Chirality-Dependent Kinetics of Single-Walled Carbon Nanotubes from Machine-Learning Force Fields
Highly efficient polarization converter with wide angular stability
Choice
In Situ Probing the Anion-Widened Anodic Electric Double Layer for Enhanced Faradaic Efficiency of Chlorine-Involved Reactions
Association between serum vitamin A and bone mineral density in adolescents
Electrocatalytic Ammonia Oxidation by Pyridyl-Substituted Ferrocenes
Social and non-social risk-taking in adolescence
Abstract The Social Risk Hypothesis of Depression proposes that individuals who perceive themselves as low in value to their social groups are at risk of developing depression. Behaviourally, lower self-perceived social value is proposed to reduce individuals’ propensity to take social risks to avoid further lowering their social worth. This is in contrast with adolescent-typical behaviour, which is characterised by heightened risk-taking in social contexts. The current study aimed to investigate how low self-perceived social value influences risk-taking in social compared to non-social contexts during adolescence. 114 adolescents (aged 12–23 years) completed the Balloon Analogue Risk Task (BART) in individual and social contexts. The results showed that adolescents took more risks in social compared to individual contexts. Risk-taking across social and individual contexts also varied as a function of self-perceived social value. In older—but not younger—youth, lower self-perceived social value was associated with greater risk-taking in social compared to individual contexts. These findings suggest that self-perceived social value differentially influences social risk-taking across adolescence. In later youth, the heightened social risk-taking observed in individuals with low self-perceived social value aligns with developmental theories suggesting that risk-taking at this age serves to increase social rank and avoid social exclusion by peers.
Metal Doping Activation of Anion-Mediated Electron Transfer in Catalytic Reactions
MEMS vibrometer: Dynamic modeling of multimodal inertial transducers
Abstract Guided ultrasonic wave-based structural health monitoring utilizes propagating elastic waves to identify, locate, and characterize damage within aviation structures. Fiber metal laminates, which are composite materials made by layering metal sheets with fiber-reinforced polymers, combine the high strength of composites with the ductility and impact resistance of metals. However, structural health monitoring methods suitable for these materials have to be developed, allowing to monitor also the inner laminate layers. Therefore, laminate-embedded MEMS vibrometers have been introduced recently. Due to the quasi-free operation of these inertial sensors, they are directly sensitive to the displacement induced by propagating guided ultrasonic waves. However, the multimodal excitation of the sensor’s core resonator, when exposed to ultrasound bursts, leads to a pseudo-nonlinear sensor response, which is attributed to the spectrum of guided ultrasonic waves and their interference with higher harmonics of the continuum resonator. The transfer behavior of the sensor can be improved by implementing electrical mode suppression. This research involves analytically modeling the continuous resonator with multiple aggregated resonators, numerically simulating sensor responses to 100 kHz ultrasound bursts, and using a laser scanning micro vibrometer setup for experimental validation, providing a deeper understanding of MEMS vibrometer dynamics for ultrasonic monitoring and demonstrating their applicability.