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Dechlorination of coal-fired flue gas is a novel approach for realizing zero discharge of desulfurization wastewater. The core principle is to convert the HCl in the flue gas into chloride salt, which will migrate into the fly ash. Pilot-scale experiments were conducted to research the migration and agglomeration of chlorine in actual coal-fired flue gas in a power plant. The results indicate that the HCl removal efficiency in flue gas can rise to 70% at a Na/Cl molar ratio of 7.58 when using NaOH solution with clean water or a ratio of 8.93 when using NaOH solution with desulfurization wastewater. XPS shows that the characteristic peak of chloride in the dechlorinated ash is much more pronounced than that in the original ash. The content of inorganic chloride increases significantly with increasing Na/Cl or the utilization of desulfurization wastewater. SEM–EDS indicates that the various salts agglomerated on the fly ash surface notably increase after dechlorination. The contents of Na, Ca, Mg, Fe and S in the ash increase remarkably, especially with desulfurization wastewater. The chloride salts generated by flue gas dechlorination and the pollutants in the desulfurization wastewater are effectively agglomerated with the fly ash.

In practical operations, the carbon monoxide (CO) distribution in an opposite-wall-firing furnace (OWFF) is characterized by a high concentration near the side walls and a low concentration in the center, accompanied by a series of combustion-related issues. To find the reasons for the CO distribution, a numerical study was conducted on a 660 MWe OWFF. The CO concentration profiles, distribution coefficients of coal and air, mixing coefficients, and the aerodynamic characteristics were extracted for analysis. The CO distribution within the furnace greatly depends on the mixing of coal and air. A mismatch between the aerodynamic behaviors of coal and air causes the non-uniform distribution of CO. Taking into consideration that distinctive flow patterns exist within the different regions, the formation mechanisms of the CO distribution can be divided into two components: (1) In the burner region, the collision of opposite flows leads to the migration of gas and particles toward the side wall which, together with the vortexes formed at furnace corners, is responsible for unburned particles concentrated and oxygenized from the furnace center to the side wall. Thus, high CO concentrations appear in these areas. (2) As the over-fire air (OFA) jet is injected into the furnace, it occupies the central region of furnace and pushes the gas from the burner region outward to the side wall, which is disadvantageous for the mixing effect in the side wall region. As a consequence, a U-shaped distribution of CO concentration is formed. Our results contribute to a theoretical basis for facilitating the control of variation in CO concentration within the furnace.

Novel scaffolds are expected to treat Alzheimer’s disease, pyrazole-5-fluorosulfates were found as selective BuChE inhibitors. Compounds K1–K26 were assayed for ChE inhibitory activity, amongst them, compound K3 showed potent BuChE and hBuChE inhibition (IC50 = 0.79 μM and 6.59 μM). SAR analysis showed that 1-, 3-, 4-subtituent and 5-fluorosulfate of pyrazole ring affected BuChE inhibitory activity. Molecular docking showed that the fluorosulfate increased the binding affinity of hBuChE through π-sulphur interaction. Compound K3 was a reversible, mixed and non-competitive BuChE inhibitor (Ki = 0.77 μM) and showed remarkable neuroprotection, safe toxicological profile and BBB penetration. In vivo behavioural study showed that K3 treatment improved the Aβ1 − 42-induced cognitive impairment, and significantly prevented the effects of Aβ1 − 42 toxicity. Therefore, selective BuChE inhibitor K3 has potential to be further developed as AD therapeutics.

The thermodynamic and kinetic mechanisms of Taixi anthracite during its graphitization process were explored. To understand the variation trends of carbon arrangement order, microcrystal size, and graphitization degree against temperature during the graphitization process, a series of experiments were performed using Raman spectroscopy and X-ray diffraction (XRD). Subsequently, the influencing factors of the dominant reaction at different temperatures were analyzed using thermodynamics and kinetics. The results showed that the graphitization process of Taixi anthracite can be divided into three stages from the perspective of reaction thermodynamics and kinetics. Temperature played a crucial role in the formation and growth of a graphitic structure. Meanwhile, multivariate mechanisms coexisted in the graphitization process. At ultrahigh temperatures, the defects of synthetic graphite could not be completely eliminated and perfect graphite crystals could not be produced. At low temperatures, the reaction is mainly controlled by dynamics, while at high temperatures, thermodynamics dominates the direction of the reaction.

In order to effectively identify the stability degree of grinding and obtain better surface integrity of machined workpiece in grinding application, in this paper, a quantitative assessment...

Based on Hertzian theory and a theoretical model considering the flexibility of the carriage, this article established a model to describe how the vertical stiffness of preloaded linear rolling guides with cylinders changes.A method of iterative calculation is adopted to solve the problem.According to the results of finite element analysis, the deformation range of a double guide platform is predicted.

The resistive switching behavior in resistive random access memories (RRAMs) using atomic-layer-deposited Ga

Herein, synthetic graphite materials with hierarchical pores and large specific surface area were successfully prepared by one-step impregnation with lignite as the carbon source, sulfuric acid (H2SO4) as the oxidant, and phosphoric acid (H3PO4) as the activator. The microstructural characteristics of synthetic graphite were investigated via X-ray diffraction (XRD), Raman spectroscopy, scanning electron microscopy (SEM), and transmission electron microscopy (TEM). Moreover, the pore parameters were studied by nitrogen adsorption–desorption. The results showed that synthetic graphite had a perfect orderly layered structure with high graphitization degree and a well-developed multistage pore structure with pore sizes ranging from nanometer to micrometer. The specific surface area and pore volume were 415.29 m2 g−1 and 0.67 cm3 g−1, respectively. The results of Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) showed that the impregnation pretreatment provided polar groups containing oxygen to the surfaces. These unique characteristics make synthetic graphite possess good adsorption capacity for dye pollutants (the adsorption rate of the methyl orange solution was 99.9% within 60 min at 50 °C, and the pH value of the solution was 3). The effects of temperature and pH value on the adsorption capacity were studied. The repeatability of the adsorption performance was also tested, and the adsorption rate was 84.6% of the initial adsorption rate after five cycles.

On the basis of the grinding process experiments for SiC ceramic workpiece, grinding process parameters are measured on the multi-sensor fusion detection test platform and experimental results are analyzed. Lempel–Ziv complexity (LZC) is introduced to reflect the integrated grinding process stability due to kinds of factors such as vibration from grinding machine parts and noise from experimental platform. The greater the LZC is, the fewer period factors are in the grinding process, which reflect the nonlinear correlations in the grinding process impacting on grinding process. A method is given based on LZC for analyzing grinding process stability. Under consideration of experimental results, a predictive model for surface quality is given by the Kernel Principle Component Analysis and Modified Extreme learning machine method (KPCA-MELM), and grinding process parameters can be optimized too. KPCA-MELM predictive model overcomes disadvantages of MELM predictive model of the randomness of weight ω a...

HCl in coal-fired flue gas has adverse impact on the environment, equipment, and the flue gas desulfurization (FGD) system. The existence of HCl also increases the difficulty of the treatment of desulfurization waste water. Semi-dry dechlorination technology is put forward to attach chlorine to fly ash by spraying in alkaline solution. Simultaneously, desulphurization waste water is used as the solvent of alkali, and this could help realize the target of near-zero emission of desulfurization waste water. CHEMKIN is used to build a chemical kinetics model, which is based on the measured components of flue gas in a coal-fired power plant. NaOH is set as the alkali absorbent in the model. Both the competitive relationship of SO2 and HCl and the effects of different factors on HCl reaction efficiency are analyzed. SO2 with high concentration would compete for more NaOH, but when Na/Cl (ratio in mole) is 1, the reaction efficiency of HCl achieves 22.28%, and it is positively correlated with Na/Cl. When Na/Cl surpasses 5, the reaction efficiency of HCl increases to beyond 70%. As Na/Cl continues to increase, there is a slower growth of HCl reaction efficiency and it finally achieves 100% when Na/Cl reaches 12. With a fixed value of Na/Cl, a change of 1000 mg/m3 in SO2 concentration would change the reaction efficiency of HCl about 13%. The effect of flue temperature on HCl reaction efficiency is not significant. Acid gases in flue gas react with NaOH completely in 0.1 s and come to equilibrium after about 1 s.

Three kinds of cylindrical plunge-grinding experiments are conducted with CBN grinding wheel by single-factor method for the carburizing alloy steel 20CrMnTi to investigate surface quality parameters and grinding force with change of wheel speed, workpiece speed, and the depth of cut. It is clarified that how change trends and correlations among surface quality parameters, grinding force, and grinding process parameters are. Based on the experiment results, analytical models for surface roughness and grinding force are established, which make the multi-object grinding parameter optimization possible and can predict the roughness and grinding force. The alloy steel 20CrMnTi workpiece surface quality and grinding efficiency-oriented optimization are conducted by the Strengthen PARETO algorithm, which make the prediction error good enough with roughness error less than 2% and the removal rate per unit width $$ {Q}_W^{\prime } $$ 1% below. The Strengthen PARETO optimal predictive model proves to be effective and sufficient to solve the problem of surface quality and grinding efficiency-oriented optimization. The alloy steel grinding parameters meet the requirement of the roughness under the value 0.8 μm with high grinding efficiency in automobile industry for shaft parts and gear production.

By adding mixture of ZrO2 and carbon, a Zr-enhanced composite coating was produced onto an AISI 1045 substrate by laser cladding. The microstructure and phase formation, microhardness and wear resistance of the composite coating were studied. The experimental results indicate that the composite coating with metallurgical bonding to substrate consists of γ-Ni, massive ceramic particles of ZrC, NiZr2, Ni7Zr2, (Fe, Ni)23C6 and Fe3C. The in situ-synthesized ZrC particles are uniformly dispersed in composite coating, which refines the microstructure of composite coating. With different ZrO2 and carbon additions, the properties are improved differently. Finally, the fine in situ ZrC particles improve the microhardness of composite coating to HV0.2 650, which is nearly 2.7 times that of Ni25 coating. Also, the composite coating has an advantage in wear resistance; it offers better wear resistance when more mixture of ZrO2 and carbon was added in nickel alloys.

Ultra-precision micro machine tool (UPMMT) has always been a high-precision machine tool for microscale/mesoscale mechanical components. It has demonstrated many advantages in small footprint, low cost of energy, low operational cost, high machining precision, etc. However, developing UPMMT is always a complicated, labor-consuming work and lacks scientific approach and guidelines. This paper is devoted to introduce a detailed design method of a micro grinding machine tool used for flexible joint blade machining. The micro grinding machine tool was built up with a combined support structure of both advantages of gantry column and single column structure, allowing more work zone and better static stability. In order to improve the dynamic performance of the machine tool, an optimization design method based on sensitivity analysis was proposed. The weakest link of the machine tool structure was identified and selected as the optimization target, and an optimization equation was established with the nature frequency as the optimization goal, mass and size as the constraint condition. The results showed that the first six nature frequencies of the machine tool were increased with different degrees and the first nature frequency was increased by about 10%. The biggest resonance peak of the machine tool was reduced in the x direction by 8.6%, in the y direction by 6.4%, and in the z direction by 10.1%. Based on the optimization results, a prototype was built, and machining tests were carried out on flexible joint blade machining to evaluate the machining performance of this machine tool.

Bilayer structures composed of 5% Mg-doped LiNbO3 single-crystal films and ultrathin Al2O3 layers with thickness ranging from 2 to 6 nm have been fabricated by using ion slicing technique combined with atomic layer deposition method. The transient domain switching current measurement results reveal that the P-V hysteresis loops are symmetry in type II mode with single voltage pulse per cycle, which may be attributed to the built-in electric field formed by asymmetric electrodes and compensation of an internal imprint field. Besides, the inlaid Al2O3, as an ideal tunnel switch layer, turns on during ferroelectric switching, but closes during the post-switching or non-switching under the applied pulse voltage. The Al2O3 layer blocks the adverse effects such as by-electrode charge injection and improves the fatigue endurance properties of Mg-doped LiNbO3 ferroelectric capacitors. This study provides a possible way to improve the reliability properties of ferroelectric devices in the non-volatile memory application.

Understanding the effects of surface heterogeneities on wetting characteristics and contact line dynamics is significant for a number of applications. In this work, the advancing and receding contact angles on well-defined heterogeneous surfaces were measured using the captive bubble technique. Furthermore, contact line distortions were observed to clarify the origin of the changes in the contact angle. For heterogeneous surfaces with different hydrophilic area fractions but the same hydrophilic defect diameter, the defects had no restrictive effect on the retreating behavior of the contact line, resulting in a nearly constant advancing contact angle. Conversely, during receding contact angle measurements, the presence of a few hydrophilic defects caused three-phase contact line pinning. Increasing the number of hydrophilic defects led to more corrugations of the three-phase contact line, resulting in a decrease in the receding contact angle. For heterogeneous surfaces with the same hydrophilic area fraction but different hydrophilic defect diameters, the advancing contact angles were also nearly constant because in the hydrophilic region, no energy barrier prevented contact line movement. However, the greater energy barriers caused by larger hydrophilic defects led to a slight decrease in the receding contact angles. A comparison of the measured and calculated values for both the advancing and receding contact angles showed that the experimental contact angle results were consistent with the contact angles calculated using the line-fraction Cassie equation. These insights into the wetting behavior of heterogeneous surfaces under liquids are expected to lead to advanced practical applications of heterogeneous surfaces.

This paper presents a time-domain force analytical model of cylindrical grinding process, which focuses on the time-varying dynamic behaviors caused by unstable machining process. This model analyzes the dynamic behaviors between the wheel and workpiece as the contact length and the maximum undeformed chip thickness change. It contains the grinding force affected by spindle run-out and vibration and especially focuses on the variation of grinding force which is affected by grinding parameters. In order to ensure the accuracy and computational efficiency of this model, the on-line detection results of grinding process have been adopted into the force analytical model. Through this model, explanations of different grinding parameter combinations are provided for grinding mechanism observed from the simulated results. Therefore, this model is validated by comparing the simulated results with the experimental results.

Grinding of brittle materials is characterized by a complex removal mechanism of both ductile and brittle removal. Therefore, the traditional force models, which are mainly targeted to metallic materials, cannot be fully applied to the force prediction of brittle materials. This paper will propose a new grinding force model for brittle materials considering co-existing of ductile removal force and brittle removal force. The ductile removal force is mainly composed of rubbing force, ploughing force, and chipping force. However, the brittle removal force is more related to rubbing force and fracture chipping force. The proportional coefficient of ductile removal and crack size will be modeled through a series of experiments under different wheel speed and undeformed chip thickness. The working status for a single grit was separated based on the Hertz Theory and chip thickness modeling of Rayleigh probability density function. Grinding experiments have been undertaken by using a high speed diamond grinder on Silicon Carbide, and the results was compared to the force model predictions for validation. The predictive force model shows a reasonable agreement quantitatively with the experimental force data.

The wettability of solid surface is significant in a wide range of applications. The surface wettability would be affected by a number of factors, such as chemical composition, heterogeneity, surface roughness, and the properties of droplet/bubble. The variation of the contact angle with the size of bubble/droplet in a three phase contact system can be ascribed to the influence of the line tension. Understanding the evolution of contact angle and pseudo-line tension between a heterogeneous surface and bubble with different size is significant in guiding the applications of heterogeneous surfaces. In this work, heterogeneous surfaces with different hydrophobic area fractions were prepared. These surfaces consisted of discrete hydrophilic dots and interconnected hydrophobic background. The contact angles between the heterogeneous surface and bubble were measured at different bubble sizes and the pseudo-line tensions were calculated. Meanwhile, a model was developed to estimate the pseudo-line tension on the heterogeneous surface. The model predicted that the pseudo-line tension would increase with the increase of the hydrophobic area fraction and the vector would point to the liquid phase, which was consistent with the experimental results.

Bilayer structures composed of 5% Mg-doped LiNbO

Atomic scale control of the thickness of thin film makes atomic layer deposition highly advantageous in the preparation of high quality super-lattices. However, precisely controlling the film chemical stoichiometry is very challenging. In this study, we deposited SiOx film with different stoichiometry by plasma enhanced atomic layer deposition. After reviewing various deposition parameters like temperature, precursor pulse time, and gas flow, the silicon dioxides of stoichiometric (SiO2) and non-stoichiometric (SiO1.8 and SiO1.6) were successfully fabricated. X-ray photo-electron spectroscopy was first employed to analyze the element content and chemical bonding energy of these films. Then the morphology, structure, composition, and optical characteristics of SiOx film were systematically studied through atomic force microscope, transmission electron microscopy, X-ray reflection, and spectroscopic ellipsometry. The experimental results indicate that both the mass density and refractive index of SiO1.8 and SiO1.6 are less than SiO2 film. The energy band-gap is approved by spectroscopic ellipsometry data and X-ray photo-electron spectroscopy O 1s analysis. The results demonstrate that the energy band-gap decreases as the oxygen concentration decreases in SiOx film. After we obtained the Si-rich silicon oxide film deposition, the SiO1.6/SiO2 super-lattices was fabricated and its photoluminescence (PL) property was characterized by PL spectra. The weak PL intensity gives us greater awareness that more research is needed in order to decrease the x of SiOx film to a larger extent through further optimizing plasma-enhanced atomic layer deposition processes, and hence improve the photoluminescence properties of SiOx/SiO2 super-lattices.

Ischemia-reperfusion (I/R) injury often leads to myocardial apoptosis and necrosis. Studies have demonstrated the role microRNAs (miRs) played in myocardial I/R injury. Thus, we established a myocardial I/R injury model and a thoracic epidural anesthesia (TEA) model in mice to explore whether microRNA-374 (miR-374) affects myocardial I/R injury. We collected myocardial tissues to evaluate whether TEA exerts a protection effect on myocardial tissues. In addition, the levels of miR-374, dystrobrevin alpha (DTNA), and the statue of the Notch1 axis were detected. Subsequently, cardiomyocytes extracted from TEA mice were treated to regulate their levels of miR-374 and DTNA. After that, cell viability, cell cycle distribution, and apoptosis of cardiomyocytes were assessed. This was followed by the detection of the myocardial infarction area. The mice models of myocardial I/R injury were associated with poorly expressed miR-374 and highly expressed DTNA. TEA was found to protect myocardial tissues against myocardial I/R injury by elevating miR-374 and reducing DTNA. Dual-luciferase reporter assay validated that DTNA was the target gene of miR-374. Cardiomyocytes with overexpressed miR-374 were shown to have downregulated DTNA levels and blocked Notch1 axis. Overexpressed miR-374 was also found to promote the viability and inhibit the apoptosis of cardiomyocytes, as well as to increase the number of cells arrested in the S phase. In accordance with this, the myocardial infarction area was decreased with the upregulated miR-347 and downregulated DTNA. Collectively, these results demonstrated that, by inhibiting the activity of DTNA-mediated Notch1 axis, miR-374 could protect against myocardial I/R injury in mice after TEA.

The error control and distribution of multi-operational machining processes is an active and important research topic in manufacturing. Most of the recent studies focus on statistical methods and the robustness of the evaluating process. However, these studies mainly serve to provide a change prediction tool rather than a method to identify and control root causes of machining errors. In this paper, in order to effectively control and distribute products of high-quality precision, a method of integrating a stream of variations (SoV) and multi-objective optimization is proposed. First, a machining process decomposition method is introduced to identify the sources of error. The multi-operation machining process is divided into three levels: the operation level, the station level, and the key characteristics level. Second, the sensitivities of the machining operation are evaluated level by level based on the SoV model; results of this evaluation will be used to determine the maximum error sources affecting the quality of products. Third, a distribution technique for each quality precision is achieved by solving a multi-objective optimization problem to minimize the cost and error associated with the sensitivities. Finally, a machining instance containing four operations is presented to demonstrate the effectiveness of the methodology.

Machining-induced residual stress is important for the part performance. In the literature, various predictive models have been proposed for residual stress in one-pass machining without considering the multi-pass aspect. This study describes the regeneration of residual stress in multi-pass machining with thermo-mechanical loadings, in the full elasto-plastic state, captured using the Neumann-Duhamel principle. The residual stress is then analysed satisfying elastic-plastic relaxation in-between layers and at the boundaries. Large experimental data in milling of AA2121-T3 agreed well with model predictions, thus supporting the consideration of initial stress functions, materials cyclic plasticity and compatibility to allow for residual stress prediction in multi-pass machining.

The grinding process requires a high energy expenditure per unit volume of material removed. The high temperature generated in abrasive processes is the main factor responsible for thermal damage to a ground surface. An investigation was undertaken to explore the temperature characteristics in high speed grinding (HSG) of silicon carbide (SiC) with a vitrified diamond wheel. A grindable thermocouople technique including a NI-DAQ device will be used to measure the grinding temperature. This paper will discuss the temperature characteristics in high speed grinding of SiC in detail and give an experiment-based temperature distribution model for SiC. A molecular dynamics simulation will be used to illustrate the effect of a high loading rate on SiC material’s mechanical property, which will further elaborate its unique HSG temperature characteristics. The experimental investigation will provide more practical application support in utilizing HSG technology in a high quality ceramic grinding.

This paper deals with an intelligent multi-sensor monitoring system, which focus on the characteristic of transient occurrence in high speed grinding and its application to the machining of brittle and hard materials. Different sensors are used to collect workpiece vibration, acoustic emission, force and displacement signals, which are used to define the stability of grinding process and monitoring the fault in high speed machining. Although there is a lot of methods have been reported in recent literature for monitoring grinding process, they have not a systematic method which can totally reflect the characteristic of high speed grinding. On the other hand，no single sensor or feature has been shown to be successfully and precisely all grinding faults. This paper combined different feature selection including time-frequency domain or wavelet methods and sensor fusion based on clustering method to deal with the stability condition test in high-speed grinding. The validity of the proposed method and the excellent detection accuracy is demonstrated through tests with SiC machining in high-speed grinding.

Quality prediction is an important means of the quality management in modern spinning production. This paper proposed a yarn quality prediction model based on Genetic Algorithm and back propagation neural network to predict the yarn quality and optimize the process parameters. The main identification model parameters were optimized by using genetic algorithm, and the prediction performance of the model has been compared against that of the BP neural network model. The effectiveness and availability of the proposed model are verified with the use of actual production data.

Demands of automatic recognition of abnormal patterns in control charts have been increasing nowadays in manufacturing process. Control chart pattern recognition is an important statistical process control tool used to determine whether a process is run in its intended range or not and eliminate the potential attribution factors as far as possible according to the abnormal condition shown in the control chart. This paper uses the time domain features as input vector and genetic algorithm to obtain the optimal parameters of SVM in a self-adapted manner. Design anomaly detection model for dynamic process is made to realize control chart pattern recognition under the complex condition. The experimental results show that the proposed approach method has higher detection accuracy and stronger generalization ability than other methods, so it is more suitable for quality control in production field.