Fabrication of crescent-shaped ceramic microparticles based on single emulsion microfluidics

Ceramic microparticles have great potentials in various fields such as materials engineering, biotechnology, microelectromechanical systems, etc. Morphology of the microparticle performs an important role on their application. To date, it remains difficult to find an effective and controllable way for fabricating nonspherical ceramic microparticles with 3D features. This work demonstrates a method that combines UV light lithography and single emulsion opaque-droplet-templated microfluidic molding to prepare the crescent-shaped ceramic microparticles. By tailoring the intensity of UV light and flow rate of fluid, the shapes of microparticles are accordingly tuned. Therefore, varieties of crescent-shaped microparticles and their variations have been fabricated. After sintering, the crescent-shaped alumina ceramic microparticles were obtained. Benefitting from the light absorption and scattering behavior of most ceramic nanoparticles, this system can serve as a general platform to produce crescent-shaped microparticles made from different materials, and hold great potentials for applications in microrobotics, structural materials in MEMS, and biotechnology.     

北斗星历解析及实时卫星位置解算实现

利用 C 语言编程进行北斗卫星星历数据的实时读取，更新结构体的卫星轨道参数， 从而实现北斗卫星位置的解算，并与武汉大学数据中心提供的北斗精密星历作比较，对解算的卫星位置结果进行评估，最大误差不超过 3.5 米，满足实际应用需要。     

Solution-Synthesized Multifunctional Janus Nanotree Microswimmer

Synthetic active matters are perfect model systems for non-equilibrium thermodynamics and of great potential for novel biomedical and environmental applications. However, most applications are limited by the complicated and low-yield preparation, while a scalable synthesis for highly functional microswimmers is highly desired. In this paper, an all-solution synthesis method is developed where the gold-loaded titania-silica nanotree can be produced as a multi-functional self-propulsion microswimmer. By applying light, heat, and electric field, the Janus nanotree demonstrated multi-mode self-propulsion, including photochemical self-electrophoresis by UV and visible light radiation, thermophoresis by near-infrared light radiation, and induced-charge electrophoresis under AC electric field. Due to the scalable synthesis, the Janus nanotree is further demonstrated as a high-efficiency, low-cost, active adsorbent for water decontamination, where the toxic mercury ions can be reclaimed with enhanced efficiency.     

Hydrogeochemical Processes and Inverse Modeling for a Multilayer Aquifer System in the Yuaner Coal Mine,Huaibei Coalfield,China

Coal mining can dramatically change hydrogeological conditions and induce serious environmental problems. Fifty groundwater samples were collected from the main aquifers in the Yuaner coal mine (Anhui Province, China). The results show that the main hydrogeochemical processes in the mine include dissolution, precipitation, pyrite oxidation, desulfurization, and cation exchange. The Neogene porous aquifer is affected by groundwater flow conditions; its main hydrogeochemical processes are dissolution of carbonate minerals and gypsum, and cation exchange. The Permian coal measure’s fractured sandstone aquifer was confirmed to be controlled by the region’s geological structure; its main hydrogeochemical processes are desulfurization and cation exchange. The Carboniferous Taiyuan limestone aquifer was determined by both groundwater flow conditions and regional geological structure; its main hydrogeochemical processes are dissolution of carbonate minerals and gypsum, pyrite oxidation, and cation exchange. Additionally, hydrogeochemical inverse modeling of the groundwater flow path confirm the hydrochemistry results and principal component analysis.

     

Influence of CO2 inleakage on the slight-alkalization of generator internal cooling water

The slight-alkalization of generator internal cooling water (GICW) is widely used to inhibit the corrosion of hollow copper conductor and thereby ensure the safe operation of the generator. CO₂ inleakage is increasingly identified as a potential security risk for GICW system. In this paper, the influence of CO₂ inleakage on the slight-alkalization of GICW was theoretically discussed. Based on the equilibriums of the CO₂-NaOH-H₂O system, CO₂ inleakage saturation was derived to quantify the amount of the dissolved CO₂ in GICW. This parameter can be directly calculated with the measured conductivity and the [Na⁺] of GICW. The influence of CO₂ inleakage on the slight-alkalization conditioning of GICW and the measurement of its water quality parameters were then analyzed. The more severe the inleakage, the narrower the water quality operation ranges of GICW, resulting in the more difficult the slight-alkalization conditioning of GICW. The temperature calibrations of the conductivity and the pH value of GICW show non-linear correlations with the amount of CO₂ inleakage and the NaOH dosage. This study provides insights into the influence of CO₂ inleakage on the slight-alkalization of GICW, which can serve as the theoretical basis for the actual slight-alkalization when CO₂ inleakage occurs.     

A self-adaptive synthetic over-sampling technique for imbalanced classification

Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50%-80%) is used for training and the rest—for validation. In many problems, however, the data are highly imbalanced in regard to different classes or does not have good coverage of the feasible data space which, in turn, creates problems in validation and usage phase. In this paper, we propose a technique for synthesizing feasible and likely data to help balance the classes as well as to boost the performance in terms of confusion matrix as well as overall. The idea, in a nutshell, is to synthesize data samples in close vicinity to the actual data samples specifically for the less represented (minority) classes. This has also implications to the so-called fairness of machine learning. In this paper, we propose a specific method for synthesizing data in a way to balance the classes and boost the performance, especially of the minority classes. It is generic and can be applied to different base algorithms, for example, support vector machines, k-nearest neighbour classifiers deep neural, rule-based classifiers, decision trees, and so forth. The results demonstrated that (a) a significantly more balanced (and fair) classification results can be achieved and (b) that the overall performance as well as the performance per class measured by confusion matrix can be boosted. In addition, this approach can be very valuable for the cases when the number of actual available labelled data is small which itself is one of the problems of the contemporary machine learning.     

The formation of fibrous structure of polyamide 6 induced by the three-step forming process and its prominent reinforcement in nitrile rubber

Nitrile rubber (NBR) blends with excellent performance have always been a hot research topic in petroleum field. Due to the excellent performance and compatibility of polyamide 6 (PA6), it provides an opportunity for the preparation of high-performance NBR/PA6 blends. In this article, NBR/PA6 blends were prepared by the three-step molding process. Experimentally, it was found that PA6 has a prominent reinforcement effect in NBR matrix. The variation of this mechanical property was investigated from different aspects of the crystal structure, crystallinities, phase morphology, and so on. It can be cleared that the formation of fibrous structure of PA6 phase is the main factor for reinforcement of the polymer blends. Meanwhile, the formation mechanism of the special phase structure induced by the three-step process is deeply expounded and its structural evolution schematic is established. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47472.