The deterministic chaos and random noise in turbulent jet.

A turbulent flow is usually treated as a superposition of coherent structure and incoherent turbulence. In this paper, the largest Lyapunov exponent and the random noise in the near field of round jet and plane jet are estimated with our previously proposed method of chaotic time series analysis [T. L. Yao, et al., Chaos 22, 033102 (2012)]. The results show that the largest Lyapunov exponents of the round jet and plane jet are in direct proportion to the reciprocal of the integral time scale of turbulence, which is in accordance with the results of the dimensional analysis, and the proportionality coefficients are equal. In addition, the random noise of the round jet and plane jet has the same linear relation with the Kolmogorov velocity scale of turbulence. As a result, the random noise may well be from the incoherent disturbance in turbulence, and the coherent structure in turbulence may well follow the rule of chaotic motion.

Polymer-Surface-Mediated Mechanochemical Reaction for Rapid and Scalable Manufacture of Perovskite QD Phosphors.

Perovskite quantum dots (QDs) have been considered new-generation emitters for lighting and displays due to their high photoluminescence (PL) efficiency, and pure color. However, their commercialization process is currently hindered by the challenge of mass production in a quick and environmentally friendly manner. In this study, a polymer-surface-mediated mechanochemical reaction (PMR) is proposed to prepare perovskite QDs using a high-speed multifunction grinder for the first time. PMR possesses two distinctive features: i) The ultra-high rotating speed (>15 000 rpm) of the grinder facilitates the rapid conversion of the precursor to perovskite; ii) The surface-rich polymer particulate ensures QDs with high dispersity, avoiding QD aggregation-induced PL quenching. Therefore, PMR can successfully manufacture green perovskite QDs with a high PL quantum yield (PLQY) exceeding 90% in a highly material- (100% yield), time- (1 kg min-1), and effort- (solvent-free) efficient manner. Moreover, the PMR demonstrates remarkable versatility, including synthesizing by various polymers and producing diverse colored and Pb-free phosphors. Importantly, these phosphors featuring a combination of polymer and perovskite, are facilely processed into various solid emitters. The proposed rapid, green, and scalable approach has great potential to accelerate the commercialization of perovskite QDs.

Enhancing percutaneous coronary intervention with heuristic path planning and deep-learning-based vascular segmentation.

Percutaneous coronary intervention (PCI) is a minimally invasive technique for treating vascular diseases. PCI requires precise and real-time visualization and guidance to ensure surgical safety and efficiency. Existing mainstream guiding methods rely on hemodynamic parameters. However, these methods are less intuitive than images and pose some challenges to the decision-making of cardiologists. This paper proposes a novel PCI guiding assistance system by combining a novel vascular segmentation network and a heuristic intervention path planning algorithm, providing cardiologists with clear and visualized information. A dataset of 1077 DSA images from 288 patients is also collected in clinical practice. A Likert Scale is also designed to evaluate system performance in user experiments. Results of user experiments demonstrate that the system can generate satisfactory and reasonable paths for PCI. Our proposed method outperformed the state-of-the-art baselines based on three metrics (Jaccard: 0.4091, F1: 0.5626, Accuracy: 0.9583). The proposed system can effectively assist cardiologists in PCI by providing a clear segmentation of vascular structures and optimal real-time intervention paths, thus demonstrating great potential for robotic PCI autonomy.

Estimating the largest Lyapunov exponent and noise level from chaotic time series.

A novel method for estimating simultaneously the largest Lyapunov exponent (LLE) and noise level (NL) from a noisy chaotic time series is presented in this paper. We research the influence of noise on the average distance of different pairs of points in an embedding phase space and provide a rescaled formula for calculating the LLE when the time series is contaminated with noise. Our algorithm is proposed based on this formula and the invariant of the LLE in different dimensional embedding phase spaces. With numerical simulation, we find that the proposed method provides a reasonable estimate of the LLE and NL when the NL is less than 10% of the signal content. The comparison with Kantz algorithm shows that our method gives more accurate results of the LLE for the noisy time series. Furthermore, our method is not sensitive to the distribution of the noise.

Investigation of Fe-Ni Mixed-Oxide Catalysts for the Reduction of NO by CO: Physicochemical Properties and Catalytic Performance.

A series of Fe-Ni mixed-oxide catalysts were synthesized by using the sol-gel method for the reduction of NO by CO. These Fe-Ni mixed-oxide catalysts exhibited tremendously enhanced catalytic performance compared to monometallic catalysts that were prepared by using the same method. The effects of Fe/Ni molar ratio and calcination temperature on the catalytic activity were examined and the physicochemical properties of the catalysts were characterized by using XRD, Raman spectroscopy, N2 -adsorption/-desorption isotherms, temperature-programmed reduction with hydrogen (H2 -TPR), temperature-programmed desorption of nitric oxide (NO-TPD), and X-ray photoelectron spectroscopy (XPS). The results indicated that the reduction behavior, surface oxygen species, and surface chemical valence states of iron and nickel in the catalysts were the key factors in the NO elimination. Fe0.5 Ni0.5 Ox that was calcined at 250 °C exhibited excellent catalytic activity of 100 % NO conversion at 130 °C and a lifetime of more than 40 hours. A plausible mechanism for the reduction of NO by CO over the Fe-Ni mixed-oxide catalysts is proposed, based on XPS and in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) analyses.