Fluid dynamics of controllable synthesis of micro-fine powder particles using Taylor-Couette flow reactors

Synthesis of fine particles is widely encountered in many applications. Typical examples can be found in fabrication of pigments, ceramics, pharmaceuticals and bio-chemicals among others. During the whole process of particle synthesis, one particle will engage several periods such as nucleation, particle growth, aggregation and breakage. The reaction environment provided by chemical reactors plays a crucial role in particle synthesis. The control of particle properties such as size and morphology are mostly determined by the control of fluid dynamics in the reactors. Therefore, the purpose of this PhD research is to investigate the fluid dynamics in Taylor-Couette (TC) flow reactors for the application of controllable synthesis of micro-fine powder particles. The main work and outcomes can be summarised as: (1) In chapter 2, CFD modelling, flow visualization and conductivity experiment are performed to investigate the mixing behaviour with the adoption of non-circular cylinder. It shows that the use of non-circular inner cylinder can significantly improve macro-mixing throughout the reactor. Mass transfer is therefore enhanced and provides a better environment for micro-mixing between the embedded turbulent eddies in the Taylor vortices. As a result, the micro-mixing has been improved over the whole reactor. Such improvement on micro and macro-mixing behaviour implies that the production of micro particles can be effectively controlled when using a Taylor-Couette flow reactor for synthesis. (2) Following the work of Chapter 2, Chapter 3 is focused on the local fluid dynamics in a large Taylor Couette reactor. Particle Image Velocimetry (PIV) method is used to reveal the shear turbulence and hydrodynamics in the reactor. It is shown that centrifugal force has a larger influence in the flow patterns. In such cases, the instabilities are easily initiated so that the flow patterns experience huge changes. Gravity force due to vertical alignment of the reactor influences the flow both in its normal (radical) and parallel (axial) direction. The Taylor vortex structures tends to deform along the height as the spatial correlation coefficients along the axial direction still exhibit a regularly periodic pattern but gradually reduces. This change reflects the deformation of Taylor vortices. (3) In Chapter 4, by using PIV, the applications of rough surface and non-circular inner cylinder have very different influence on the vortex structures and shear turbulence generated in the Taylor Couette flow reactor. The adoption of the non-circular inner cylinder apparently changes the vortices in large scales. Turbulence is strongly enhanced using the non-circular inner cylinder but less enhancement was found for the use of the rough surface inner cylinder. The main effects of rough surface on the shear turbulence are that the spatial distribution of turbulence characters in the vicinity of the inner cylinder have changed their distribution. High turbulent kinetic energy (TKE) and high TKE dissipation rate region are not always to appear in the same locations due to strong convection. (4) Based on the basic understanding of fluid dynamics and mixing behaviour from Chapter 3 and Chapter 4, an example of the effect of fluid dynamics on synthesis of micro particles, barium sulphate particles are tracked using the Euler-Lagrange approach with consideration of the particle growth in the synthesis process with particle size changes with time. The particle trajectories change dramatically for particles when particle size changes with time. The particle trajectories tracked in the circular and non-circular inner cylinder Taylor-Couette flow reactors present helical movement but are entrapped and affected by the presence of Taylor vortices. The calculated dispersion coefficient for both types of inner cylinder Taylor-Couette flow reactors indicates that particle dispersion, especially in the axial direction, is not always improved by adoption of the non-circular inner cylinder. To sum up, this PhD work mainly provides a fundamental study focused on the characterization of fluid dynamics which affects particle synthesis process. Flow visualization, mixing experiment, PIV and CFD are used to study the key fluid dynamic characteristics in both circular and non-circular Taylor-Couette reactor. The main implication is that characters which affects particle synthesis process such as mixing, shear strain and particle dispersion can be better controlled by adopting non-circular inner cylinder Taylor Couette reactor. Meanwhile, various length scale turbulent eddies embedded in the Taylor vortices have is strongly affected by inner cylinder boundary conditions, thus influence the control and performance of the reactor. Focus should be placed on the key characters of flow which affects actual particle synthesis process when using the Taylor-Couette reactors

Self-assembly of 3D fennel-like Co3O4 with thirty-six surfaces for high performance supercapacitor

Three-dimensional (3D) fennel-like cobalt oxide (II,III) (Co3O4) particles with thirty-six surfaces on nickel foams were prepared via a simple hydrothermal synthesis method and its growth process was also researched. The crystalline structure and morphology were investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM), and Raman spectroscopy. The Brunauer-Emmett Teller (BET) analysis revealed that 3D fennel-like Co3O4 particles have high specific surface area. Therefore, the special structure with thirty-six surfaces indicates the good electrochemical performance of the micron-nanometer material as electrode material for supercapacitors. The cyclic voltammetry (CV), galvanostatic charge-discharge, and electrochemical impedance spectroscopy (EIS) were conducted to evaluate the electrochemical performances. Compared with other morphological materials of the similar sizes, the Co3O4 particles on nickel foam exhibit a high specific capacitance of 384.375 F.g(-1) at the current density of 3A.g(-1) and excellent cycling stability of a capacitance retention of 96.54% after 1500 galvanostatic charge-discharge cycles in 6M potassium hydroxide (KOH) electrolyte

Information Service System for Internet of Vehicles

This system is an Android mobile phone information service system for internet of vehicles. The information service system has four types of functions, including a login registration function, an information search function, a location function, and an information query function. The connection between cars and cars is gradually evolving into Internet of Vehicles from the traditional vehicle self-organizing network. The need for real-time service information for vehicles has also followed. Therefore, the research mainly designed an information service system for users of vehicles

Large Eddy Simulation of Bubble Column Bubbly Flow Considering Subgrid-Scale Turbulent Diffusion Effects and Bubble Oscillation

Through Euler/Euler large eddy simulation (LES) modeling, it is demonstrated that turbulent dispersion of bubbles can effectively indicate the impact of turbulent eddies on the bubble dynamics, i.e., the bubble oscillation behavior. This finding builds on previous work using the Euler/Lagrange LES modeling approach and leads to a significant improvement in predicting bubble lateral dispersion. Spatially filtered terms were proposed for the subgrid-scale (SGS) turbulent dispersion and added mass stress force models, with a modification made to the SGS eddy viscosity to reflect bubble turbulent dispersion and oscillations. The proposed model substantially improves the prediction of bubble volume fraction distribution, bubble and liquid phase velocity profiles, the turbulent kinetic energy spectrum, and mass transfer

Can regional integration narrow city-level energy efficiency gap in China?

Improving energy efficiency is essential for energy conservation, emissions reduction, and sustainable development. Prevalent huge efficiency gaps are not advantageous for the improvement of the region's overall energy efficiency. Although studies have analyzed the influencing factors of the regional energy efficiency gap, the impact of regional integration on the regional energy efficiency gap remains untested. This paper applies the extended stochastic frontier analysis (SFA) method that incorporates time-varying, time-invariant and city heterogeneous characteristics to estimate the city-level energy efficiency in China from 2005 to 2017. Building on the “center-periphery” framework, we further calculate the regional energy efficiency gap and investigate the impact of regional integration on the regional energy efficiency gap through the generalized moment method (GMM). The results show that 1) average city-level energy efficiency is 44.2%, ranging from 2.9% to 75.5%, indicating that China has a huge regional energy efficiency gap; 2) there is a U-shaped relationship between regional integration and the regional energy efficiency gap within city agglomeration. Improvement in regional integration can narrow the regional energy efficiency gap when the degree of regional integration is low, and expand the efficiency gap when regional integration level is high; 3) government intervention will smooth the impact of regional integration on the regional energy efficiency gap within city agglomeration. Practicable policies to mitigate the regional energy efficiency gap in China are suggested and applicable to other emerging economies, especially for those with a huge imbalance in regional energy efficiency

Interfacial Phenomena in the Synthesis Process of Barium Sulfate Particles Precipitated in a Lobed Inner Cylinder Taylor-Couette Flow Reactor: Effects of Fluid Dynamics

Three different kinds of morphology with various sizes of barium sulfate particles were produced by reactive precipitation in a Taylor-Couette flow reactor. It is found that particle morphology transition is strongly related to the hydrodynamics in the reactor, clearly indicating an interfacial interaction between feed solutions and aggregated particles. At low concentration, particle morphology transition is observed at the onset of turbulent Taylor-Couette flow. Such morphology transition also appears at the onset of turbulent Taylor vortex flow at high concentration. Based on different transition status, supersaturation is found to play an important role in nucleation and growth processes. In addition, it is revealed that the synthesized particle reduces its size as the consequence of the transition in particle morphology, indicating the effect of variation of the feeding rates. Experimental results have confirmed that controllable synthesis of barium sulfate particles with a particular morphology can be achieved through suitable selection of the controlling parameters such as the rotational speed of inner cylinder of Taylor-Couette flow reactor, reactant feeding rate and supersaturation ratio

Self-explaining Hierarchical Model for Intraoperative Time Series

Major postoperative complications are devastating to surgical patients. Some of these complications are potentially preventable via early predictions based on intraoperative data. However, intraoperative data comprise long and fine-grained multivariate time series, prohibiting the effective learning of accurate models. The large gaps associated with clinical events and protocols are usually ignored. Moreover, deep models generally lack transparency. Nevertheless, the interpretability is crucial to assist clinicians in planning for and delivering postoperative care and timely interventions. Towards this end, we propose a hierarchical model combining the strength of both attention and recurrent models for intraoperative time series. We further develop an explanation module for the hierarchical model to interpret the predictions by providing contributions of intraoperative data in a fine-grained manner. Experiments on a large dataset of 111,888 surgeries with multiple outcomes and an external high-resolution ICU dataset show that our model can achieve strong predictive performance (i.e., high accuracy) and offer robust interpretations (i.e., high transparency) for predicted outcomes based on intraoperative time series

Effect of zinc acetate concentration on optimization of photocatalytic activity of p-Co3O4/n-ZnO heterostructures

In this work, p-Co3O4/n-ZnO heterostructures were fabricated on Ni substrate by hydrothermal-decomposition method using cobaltous nitrate hexahydrate (Co(NO3)(2)center dot 6H(2)O) and zinc acetate dihydrate (Zn(CH3COO)(2)center dot 2H(2)O) as precursors with zinc acetate concentration varying from 5.0 to 55.0 mM. Structure and morphology of the developed samples were characterized by X-ray diffraction (XRD), Raman spectroscopy, and scanning electron microscopy (SEM). Effect of zinc acetate concentration on the photocatalytic activity of p-Co3O4/n-ZnO heterostructures was investigated by degradation of methyl orange (MO) under the UV light irradiation. The fabricated p-Co3O4/n-ZnO heterostructures exhibited higher photocatalytic activity than pure Co3O4 particles. In order to obtain the maximum photocatalytic activity, zinc acetate concentration was optimized. Specifically, at 35 mM of zinc acetate, the p-Co3O4/n-ZnO showed the highest photocatalytic activity with the degradation efficiency of MO reaching 89.38% after 72 h irradiation. The improvement of photocatalytic performance of p-Co3O4/n-ZnO heterostructures is due to the increased concentration of photo-generated holes on Co3O4 surface and the higher surface-to-volume ratio in the hierarchical structure formed by nano-lamellas

Preparation Method of Co 3

Co3O4 nanoparticles were fabricated by a novel, facile, and environment-friendly carbon-assisted method using degreasing cotton. Structural and morphological characterizations were performed using X-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The component of the sample obtained at different temperatures was measured by Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS). Nitrogen adsorption and desorption isotherms were utilized to reveal the specific surface areas. The formation mechanism of Co3O4 nanoparticles was also proposed, demonstrating that the additive degreasing cotton played an indispensable role in the process of synthesizing the sample. The resultant Co3O4 sample calcined at 600°C exhibited superior electrochemical performance with better specific capacitance and long-term cycling life, due to its high specific surface areas and pores structures. Additionally, it has been proved that this facile synthetic strategy can be extended to produce other metal oxide materials (e.g., Fe3O4). As a consequence, the carbon-assisted method using degreasing cotton accompanied a promising prospect for practical application

Assisting Clinical Decisions for Scarcely Available Treatment via Disentangled Latent Representation

Extracorporeal membrane oxygenation (ECMO) is an essential life-supporting modality for COVID-19 patients who are refractory to conventional therapies. However, the proper treatment decision has been the subject of significant debate and it remains controversial about who benefits from this scarcely available and technically complex treatment option. To support clinical decisions, it is a critical need to predict the treatment need and the potential treatment and no-treatment responses. Targeting this clinical challenge, we propose Treatment Variational AutoEncoder (TVAE), a novel approach for individualized treatment analysis. TVAE is specifically designed to address the modeling challenges like ECMO with strong treatment selection bias and scarce treatment cases. TVAE conceptualizes the treatment decision as a multi-scale problem. We model a patient's potential treatment assignment and the factual and counterfactual outcomes as part of their intrinsic characteristics that can be represented by a deep latent variable model. The factual and counterfactual prediction errors are alleviated via a reconstruction regularization scheme together with semi-supervision, and the selection bias and the scarcity of treatment cases are mitigated by the disentangled and distribution-matched latent space and the label-balancing generative strategy. We evaluate TVAE on two real-world COVID-19 datasets: an international dataset collected from 1651 hospitals across 63 countries, and a institutional dataset collected from 15 hospitals. The results show that TVAE outperforms state-of-the-art treatment effect models in predicting both the propensity scores and factual outcomes on heterogeneous COVID-19 datasets. Additional experiments also show TVAE outperforms the best existing models in individual treatment effect estimation on the synthesized IHDP benchmark dataset