Single-walled carbon nanotubes (SWCNTs) were dispersed in water with the help of a combination of surfactants to achieve a high concentration SWCNT ink. Transparent conducting films (TCFs) were fabricated through a rod-coating method using the SWCNT ink. The addition of binders (polyacrylic acid or carboxymethyl cellulose) greatly enhanced the adhesion of SWCNT films to substrates and the cohesion between CNTs, which produced a uniform film of SWCNTs by preventing damage during the post-treatment process. The thickness of SWCNT films is controlled by the amount of SWCNTs in the solution and the diameter of the wire used. To test the film adhesion, Scotcht tape was used to detach some loosely bound SWCNTs. Then the SWCNT films were further post-treated with nitric acid to improve the conductivity. The addition of polyacrylic acid to the SWCNT dispersion improved the film adhesion obviously without decreasing its electrical conductivity. This rod-coating method demonstrates great potential for the scalable fabrication of flexible SWCNT-TCFs.
Background Studies have shown that a direct association exists between the diet and blood uric acid concentrations. However, works on the association of dietary patterns with blood uric acid concentrations and hyperuricemia remain limited. Objective This study aims to evaluate the association of dietary patterns with blood uric acid concentrations and hyperuricemia. Methods The relationship between dietary patterns and hyperuricemia was explored through a nutritional epidemiological survey in China (n = 4855). Three statistical methods, including principal component analysis, reduced rank regression (RRR), and partial least squares regression, were used to extract dietary patterns. General linear regression and logistic regression analyses were utilized to explore the relationship of dietary patterns with blood uric acid concentrations and hyperuricemia. Results After adjusting for potential confounding factors, the score for the plant-based dietary pattern was found to be negatively correlated with blood uric acid levels (β = − 3.225) and that for the animal dietary pattern was discovered to be directly correlated with blood uric acid levels (β = 3.645). The participants in the highest quartile of plant-based dietary pattern scores were at a low risk of hyperuricemia (OR = 0.699; 95% CI: 0.561–0.870, P < 0.05), whereas those in the highest quartile of animal dietary pattern scores were at a high risk of hyperuricemia (OR = 1.401; 95% CI: 1.129–1.739, P < 0.05). The participants in the third quartile of scores for the RRR dietary pattern, which was characterized by the relatively high intake of poultry, sugary beverages, and animal organs and the low intake of desserts and snacks, had a significantly higher risk of hyperuricemia than those in the first quartile of scores for the RRR dietary pattern (OR = 1.421; 95% CI: 1.146–1.763, P < 0.05). Conclusions Our research indicated that plant-based dietary pattern analyzed by PCA was negatively associated with blood uric acid concentrations, while animal-based dietary pattern was directly associated with blood uric acid concentrations. The RRR dietary pattern may have the potential to induce elevations in blood uric acid concentrations.
Y-junction carbon nanocoils (Y-CNCs) were synthesized by thermal chemical vapor deposition using Ni catalyst prepared by spray-coating method. According to the emerging morphologies of Y-CNCs, several growth models were advanced to elucidate their formation mechanisms. Regarding the Y-CNCs without metal catalyst in the Y-junctions, fusing of contiguous CNCs and a tip-growth mechanism are considered to be responsible for their formation. However, as for the Y-CNCs with catalyst presence in the Y-junctions, the formation can be ascribed to nanoscale soldering/welding and bottom-growth mechanism. It is found that increasing spray-coating time for catalyst preparation generates agglomerated larger nanoparticles strongly adhering to the substrate, resulting in bottom-growth of CNCs and appearance of the metal catalyst in the Y-junctions. In the contrary case, CNCs catalyzed by isolated smaller nanoparticles develop Y-junctions with an absence of metal catalyst by virtue of weaker adhesion of catalyst with the substrate and tip-growth of CNCs.
Ambient sounds arise from a massive superposition of chaotic events distributed over a large area or volume, such as waves breaking on a beach or rain hitting the ground. The directionality and loudness of these sounds as they propagate in complex 3D scenes vary with listener location, providing cues that distinguish indoors from outdoors and reveal portals and occluders. We show that ambient sources can be approximated using an ideal notion of spatio-temporal incoherence and develop a lightweight technique to capture their global propagation effects. Our approach precomputes a single FDTD simulation using a sustained source signal whose phase is randomized over frequency and source extent. It then extracts a spherical harmonic encoding of the resulting steady-state distribution of power over direction and position in the scene using an efficient flux density formulation. The resulting parameter fields are smooth and compressible, requiring only a few MB of memory per extended source. We also present a fast binaural rendering technique that exploits phase incoherence to reduce filtering cost.
Common acoustic sources, like voices or musical instruments, exhibit strong frequency and directional dependence. When transported through complex environments, their anisotropic radiated field undergoes scattering, diffraction, and occlusion before reaching a directionally-sensitive listener. We present the first wave-based interactive auralization system that encodes and renders a complete reciprocal description of acoustic wave fields in general scenes. Our method renders directional effects at freely moving and rotating sources and listeners and supports any tabulated source directivity function and head-related transfer function. We represent a static scene's global acoustic transfer as an 11-dimensional bidirectional impulse response (BIR) field, which we extract from a set of wave simulations. We parametrically encode the BIR as a pair of radiating and arriving directions for the perceptually-salient initial ( direct ) response, and a compact 6 × 6 reflections transfer matrix capturing indirect energy transfer with scene-dependent anisotropy. We render our encoded data with an efficient and scalable algorithm - integrated in the Unreal Engine ™ - whose CPU performance is agnostic to scene complexity and angular source/listener resolutions. We demonstrate convincing effects that depend on detailed scene geometry, for a variety of environments and source types.
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