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The extent to which a droplet pins on a textured substrate is determined by the dynamics of the contact line and the liquid-vapor interface. However, the synergistic contribution of contact line sliding and interface distortion to the droplet depinning force remains unknown. More strikingly, current models fail to predict the depinning force per unit length of droplets on soft pillar arrays. Therefore, we fabricate soft pillar arrays with varying geometrical dimensions and mechanical properties and measure the depinning forces per unit length by allowing droplets to evaporate on such substrates. We then analyze the decrease in excess Gibbs free energy of the apparent droplet caused by the detachment of the droplet boundary from the previously pinned pillars. In contrast to prior notions, based on the measured decreases in excess Gibbs free energy, we find that the coefficient, that governs the ratio of interface distortion's contribution to the depinning force to that of the sliding contact line, increases with a decrease in pillar packing density. By considering the combined contribution from contact line sliding, liquid-vapor interface distortion, and pillar deflection, we introduce an analytical model to predict the droplet depinning force per unit length and corroborate the model using experimental data reported in this and prior studies.
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As electrocatalysts, molecular catalysts with large aromatic systems (such as terpyridine, porphyrin, or phthalocyanine) have been widely applied in the CO2 reduction reaction (CO2RR). However, these monomeric catalysts tend to aggregate due to strong π-π interactions, resulting in limited accessibility of the active site. In light of these challenges, we present a novel strategy of active site isolation for enhancing the CO2RR. Six Ru(Tpy)2 were integrated into the skeleton of a metallo-organic supramolecule by stepwise self-assembly in order to form a rhombus-fused six-pointed star R1 with active site isolation. The turnover frequency (TOF) of R1 was as high as 10.73 s-1 at -0.6 V versus reversible hydrogen electrode (vs RHE), which is the best reported value so far at the same potential to our knowledge. Furthermore, by increasing the connector density on R1's skeleton, a more stable triangle-fused six-pointed star T1 was successfully synthesized. T1 exhibits exceptional stability up to 126 h at -0.4 V vs RHE and excellent TOF values of CO. The strategy of active site isolation and connector density increment significantly enhanced the catalytic activity by increasing the exposure of the active site. This work provides a starting point for the design of molecular catalysts and facilitates the development of a new generation of catalysts with a high catalytic performance.
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Interfacial electric field holds significant importance in determining both the polar molecular configuration and surface coverage during electrocatalysis. This study introduces a methodology leveraging the varying electric dipole moment of SO2 under distinct interfacial electric field strengths to enhance the selectivity of the SO2 electroreduction process. This approach presented the first attempt to utilize pulsed voltage application to the Au/PTFE membrane electrode for the control of the molecular configuration and coverage of SO2 on the electrode surface. Remarkably, the modulation of pulse duration resulted in a substantial inhibition of the hydrogen evolution reaction (HER) (FEH2 < 3%) under millisecond pulse conditions (ta = 10 ms, tc = 300 ms, Ea = -0.8 V (vs Hg/Hg2SO4), Ec = -1.8 V (vs Hg/Hg2SO4)), concomitant with a noteworthy enhancement in H2S selectivity (FEH2S > 97%). A comprehensive analysis, incorporating in situ Raman spectroscopy, electrochemical quartz crystal microbalance, COMSOL simulations, and DFT calculations, corroborated the increased selectivity of H2S products was primarily associated with the inherently large dipole moment of the SO2 molecule. The enhancement of the interfacial electric field induced by millisecond pulses was instrumental in amplifying SO2 coverage, activating SO2, facilitating the formation of the pivotal intermediate product *SOH, and effectively reducing the reaction energy barrier in the SO2 reduction process. These findings provide novel insights into the influences of ion and molecular transport dynamics, as well as the temporal intricacies of competitive pathways during the SO2 electroreduction process. Moreover, it underscores the intrinsic correlation between the electric dipole moment and surface-molecule interaction of the catalyst.
RESUMO
The electrocatalytic reduction of SO2 to produce H2S is a critical approach for achieving the efficient utilization of sulfur resources. At the core of this approach for commercial applications lies the imperative need to elevate current density. However, the challenges posed by high current density manifest in the rapid depletion of protons, leading to a decrease in SO2 partial pressure, consequently hampering the generation and separation of H2S. Here, we demonstrate an effective solution to alleviate the problem of insufficient supply of protons by employing Nafion polymer as the proton conductor to modified Cu catalysts surface, creating a proton-enriched layer to boost H2S generation. It was observed that Nafion shortens the hydrogen bonds with water molecules in the electrolyte via its sulfonic acid groups, benefiting the proton transfer and consequently increasing the proton density on the electrode surface by 5-fold. With the Nafion-modified catalyst, the H2S partial current density and separation efficiency reached 205.9 mA·cm-2 (1.01 mmol·cm-2·h-1) and 87.8%, which were 1.34 and 1.22 times that on unmodified Cu, respectively. This work highlights the practicality of fabricating a proton conductor via ionic polymer for the control over product selectivity in pH-sensitive reactions under high current density.
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Silicone elastomers have been widely used for biomedical applications. A variety of hyperelastic models have been proposed to describe this type of materials in the past few decades. The assessment of the quality of the proposed models is mostly based on stress-strain data obtained from uniform deformation, but very little work has been done to investigate model performances with heterogeneous deformation fields and full-field characterization methods. In this study, thirteen hyperelastic models are evaluated using the virtual fields method combined with full-field deformation data obtained from biaxial tests. The quality of these models is assessed by their capabilities to predict the mechanical responses of silicone elastomers, and the influences of the first and second invariants on modeling of elastomers are investigated through comparative studies between models. The results indicate that for elastomers under finite biaxial deformation, Yeoh model performs the best among selected models; the first invariant plays an important role in constitutive modeling; the second invariant does not have obvious influence on improving the fitting performance. This study provides a full-field method to calibrate and compare hyperelastic models of silicone elastomers under biaxial loading conditions.
Assuntos
Elastômeros , Elastômeros de Silicone , Fenômenos Biomecânicos , Estresse MecânicoRESUMO
We propose a point cloud and mesh generation algorithm, particle injection mesh generator (PIMesh), that can be used to generate optimized high-quality point clouds and unstructured meshes for domains in any shape with minimum (or even no) user intervention. The domains can be scanned images in OBJ format in 2D and 3D or just a line drawing in 2D. Mesh grading can also be easily controlled. The PIMesh is robust and easy to be implemented and is useful for a variety of applications, ranging from generating point clouds for meshless methods, mesh generation for finite element methods, computer graphics applications and surgical simulators. The core idea of the PIMesh is that a mesh domain is considered as an "airtight container" into which particles are "injected" at one or multiple selected interior points. The motion of the particles is controlled by a pseudo-molecular dynamics (PMD) formulation with a pairwise purely repelling "force" moderated by an absolute velocity dependent drag force. The particles repel each other and occupy the whole domain somewhat like blowing up a balloon. When the container is full of particles and the motion is stopped (the particles can be considered as a point cloud), a Delaunay triangulation algorithm is employed to link the particles together to generate an unstructured mesh. The performance of the PIMesh and the comparison with other unstructured mesh generation approaches are demonstrated through generating node distributions and meshes for several 2D and 3D object domains including a scanned image of bones and others.
Assuntos
Algoritmos , Simulação por Computador , Análise de Elementos Finitos , SoftwareRESUMO
In a centralized model of simulation-based education (Ce-SBE), students practice skills in simulation laboratories, while in a decentralized model (De-SBE), they practice skills outside of these laboratories. The cost of "take-home" simulators is a barrier that can be overcome with additive manufacturing (AM). Our objective was to develop and evaluate the quality of education when year one nursing students practiced clinical skills from home following normal curricular activities but in the De-SBE format. A group of expert educators, designers, and researchers followed a two-cycle, iterative design-to-cost approach to develop three simulators: wound care and urethral catheterization (male and female). The total cost of manufacturing all three simulators was USD 5,000. These were sent to all year one nursing students who followed an online curriculum. Twenty-nine students completed the survey, which indicated that the simulators supported the students' learning needs, and several changes were requested to improve the educational value. The results indicate that substituting traditional simulators with AM-simulators provided an acceptable alternative for nursing students to learn wound care and urethral catheterization off-campus in De-SBE. The feedback also provided suggestions to improve each of the simulators to make the experience more authentic.
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Three-dimensional (3D) printed splints are becoming more feasible in recent years, showing promising lightweight, waterproof, and hygienic designs. A typical procedure to create 3D printed splints is obtaining the geometry of a body segment using a 3D scanner, creating a 3D printable splint model based on the geometry of the body segment, and 3D printing the splint. As technologies of 3D scanning and 3D printing become mature gradually, the main challenge to fabricate 3D printed splint is to create 3D printable splint models. To solve this challenge, researchers have proposed various methods to design 3D splint models. However, most methods require extensive 3D modeling skills that medical professionals are lacking. In this work, a semi-automatic method is proposed to create a 3D printable model. Given the geometry of a body segment obtained through a 3D scanner, the method includes three key steps: (1) create a draft splint lattice structure, (2) optimize the splint structure, and (3) create a 3D printable model based on the optimized structure. All the software adopted for this method is free and readily available, and thus, there is no additional cost to convert from a scanned geometry of a body segment to a 3D printable splint model. Because the majority of the work is done automatically, with initial training, a medical professional should be able to create a 3D printable model using the proposed method, given the geometry of a body segment. The proposed method is demonstrated by creating a 3D printed wrist splint and the demo is uploaded into GitHub, a popular open-source platform.
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Recent surges in COVID-19 cases have generated an urgent global demand for ventilators. This demand has led to the development of numerous low-cost ventilation devices, but there has been less emphasis on training health professionals to use these new devices safely. The aim of this technical report is twofold: first, to describe the design and manufacturing process of the automated inflating resuscitator (AIR), a 3D-printed ventilator training device which operates on the principle of pushing a bag valve mask; second, to present a simulation scenario that can be used for training health professionals how to use this and similar, low-cost, 3D-printed ventilators in the context of ventilator shortages caused by COVID-19. To this end, the AIR was designed in an expedient manner in accordance with basic functionality established by the Medicines and Healthcare Products Regulatory Agency (United Kingdom) for provisional clinical use in light of COVID-19.