Hydrophobic Cross-Linked Poly(dimethylsiloxane)-Based Sorbents for Oil Spill Applications

With the increase of industrialization and urbanization, humankind faces massive oil-based pollution due to tanker accidents, human error, and natural disasters. For this, hydrophobic sorbents are fabricated and their applications for the removal of oil from polluted water sources are investigated. These hydrophobic sorbents are prepared by the condensation reaction of poly(dimethylsiloxane) and tris[3-(trimethoxysilyl)propyl]isocyanurate cross-linker via bulk polymerization. The obtained sorbents exhibit high oil sorption capacity, fast absorption–desorption kinetics, and great reusability. Moreover, they can selectively absorb oil from the water surface, thus making them practical for water clean-up applications.     

Frequency response data-based peak filter design applied to MIMO large-scale high-precision scan stage

A large-scale high-precision scan stage is important equipment in the industrial productions of micro-fabrication such as flat panel display (FPD) lithography systems. Designing controllers for multi-input multi-output (MIMO) systems is time-consuming and needs experience because of the interaction between each axis and many controller tuning parameters. The aim of this study is to develop a peak filter design method based on frequency response data to reduce repetitive disturbance. This data-based approach does not use the model and only uses the frequency response data of the controlled system and the disturbance spectrum calculated from the scanning error data (Contribution 1). The peak filter is designed by convex optimization and satisfies robust stability conditions for six-degree-of-freedom systems (Contribution 2). The control performance of the designed peak filter is experimentally demonstrated with an industrial MIMO large-scale high-precision scan stage in reducing the scanning error of the main stroke of the translation along the $x$-axis (Contribution 3).     

Analysis of pressure and heat distribution in a dilating or contracting filter chamber with two outlets using multivariate spectral quasilinearization method

The development of efficient filters is an essential part of industrial machinery design, specifically to increase the lifespan of a machine. In the filter chamber design considered in this study, the magnetic material is placed along the horizontal surface of the filter chamber. The inside of the filter chamber is layered with a porous material to restrict the outflow of unwanted particles. This study aims to investigate the flow, pressure, and heat distribution in a dilating or contracting filter chamber with two outlets driven by injection through a permeable surface. The proposed model of the fluid dynamics within the filter chamber follows the conservation equations in the form of partial differential equations. The model equations are further reduced to a steady case through Lie's symmetry group of transformation. They are then solved using a multivariate spectral-based quasilinearization method on the Chebyshev–Gauss–Lobatto nodes. Insights and analyses of the thermophysical parameters that drive optimal outflow during the filtration process are provided through the graphs of the numerical solutions of the differential equations. We find, among other results, that expansion of the filter chamber leads to an overall decrease in internal pressure and an increase in heat distribution inside the filter chamber. The results also show that shrinking the filter chamber increases the internal momentum inside the filter, which leads to more outflow of filtrates.     

Finite-time adaptive fuzzy control for a class of output constrained nonlinear systems with dead-zone

The article investigates the finite-time adaptive fuzzy control for a class of nonlinear systems with output constraint and input dead-zone. First, by skillfully combining the barrier Lyapunov function, backstepping design method, and finite-time control theory, a novel adaptive state-feedback tracking controller is constructed, and the output constraint of the nonlinear system is not violated. Second, the fuzzy logic system is used to approximate unknown function in the nonlinear system. Third, the finite-time command filter is introduced to avoid the problem of “complexity explosion” caused by repeated differentiations of the virtual control signal in conventional backstepping control schemes. Meanwhile, a new saturation function is added in the compensating signal for filter error to improve control accuracy. Finally, based on Lyapunov stability analysis, all the signals of the closed-loop are proved to be semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood region of the origin in a finite time. A simulation example is presented to demonstrate the effectiveness for the proposed control scheme.     

Influence of pulse-jet cleaning pressure on performance of compact dust collector with pleated filter operated in clean-on-time mode

To operate a bag filter continuously, pulse-jet cleaning of dust particles from the filter medium is commonly required, and the pulse-jet pressure significantly affects the filter performance. In this study, the accumulation structure of residual dust particles inside and on the surface of a filter medium at different pulse-jet pressures was investigated by constructing a simple model, and the influence of the dust structure on the filter performance was clarified. Using a simple model, we determined the effective ratio of filtration area β, which represents the ratio of the filterable area to the total filtration area, the true resistance coefficient due to the primary dust layer ζ_p’ thinly deposited on the filter surface, and the true resistance coefficient inside the filter media itself ζ_f’_. The effective ratio of filtration area β decreased with operation time for all pulse-jet pressures; however, it maintained a high value when the pulse-jet pressure was high. The validity of β analyzed by the model was verified using two different methods, and the results showed good agreement, indicating that the model is effective in identifying real conditions. The true resistance coefficient due to the primary dust layer ζ_p’ decreased as the pulse-jet pressure increased; however, the true resistance coefficient inside the filter media itself ζ_f’ was the highest at 0.5 MPa. In addition, the dust collection efficiency was different at each pulse-jet pressure, which was considered to be caused by the difference in the dust particle accumulation structure.     

Understanding δ-Bi2O3 fluorite degradation mechanism and related solutions for promising applications in distributed multigeneration

Oxygen selective membrane on the base of cermet δ-Bi₂O₃/Ag with an interpenetrating structure has the maximum potential efficiency of air separation. However, the degradation processes, including the phase degradation of fluorite δ-Bi₂O₃, do not make it possible to create a membrane with the required perfection and durability. In this work, the ordering of oxygen vacancies with the transformation of fluorite into the rhombohedral phase (S.G. R-3) was studied by powder HT XRD in situ at 600 °C on dense Bi_0.78Er_0.2Hf_0.02O_1.51 ceramics. Fast regeneration of disordered fluorite occurs at T = 640–700 °C. The phase degradation of fluorite due to the segregation of dopants at the second stage leads into stable phases - sillenite, tetragonal or rhombohedral phase (S.G. R-3m), depending on the composition of δ-Bi₂O₃. Fast regeneration of fluorite occurs when heated to 820 °C, which is unacceptable for membranes. Analysis of all available data allows us to propose approaches to optimize the composition of δ-Bi₂O₃ and technical solutions for creating durable oxygen selective membranes with promising use in distributed multigeneration. As a result of the analysis, a new solid electrolyte with better parameters was obtained.     

Long-term performance analysis of chemical filters in clean rooms based on a prediction model

Chemical filters are the most important devices for removing gas-phase pollutants in clean rooms. However, the testing concentration of chemical filters is too high for reflecting their performance in a real clean room environment. This study tested the adsorption performance of chemical filters in the two most commonly used shapes at different concentrations. Then, the Langmuir equation and Wheeler-Jonas kinetic equation were combined to establish an adsorption performance prediction model of chemical filters under actual conditions. The predicted values of the model were in good agreement with the experimental results, which indicated the high accuracy of the prediction model. The model does not need to test the microscopic parameters of the adsorbent and can maintain high accuracy at low concentrations. A fast method for calculating the service life of chemical filters was also presented. Based on this model, the total cost of using a chemical filter with a high carbon content in microelectronic clean rooms could be decreased by 45% due to decreasing the number of filter replacements over 3 months. So a chemical filter with a high carbon content should be preferred over a filter with low resistance in microelectronic clean rooms.     

Reusable and durable electrostatic air filter based on hybrid metallized microfibers decorated with metal-organic-framework nanocrystals

As global air pollution becomes increasingly severe,various types of fibrous filters have been devel-oped to improve air filter performance.However,fibrous filters have limitations such as high packing density that generally causes high-pressure drop and ultimately deterioration in the filtration effi-ciency.High-pressure particulate matter precipitators are limited in terms of scope for commercialization because they require high voltage supplies and ozone generators.In this study,we develop fibrous fil-ters with enhanced durability and improved performance using metallized microfibers decorated with metal-organic-framework(MOF)nanocrystals.Not only does the efficiency of the developed filters remain at or above 97％for 0.50-1.5 μm PMs but the durability also significantly increases.In addi-tion,using the water purification ability of the MOF,we explore the dye degradation effect of the hybrid microfibers by immersing them into Rhodamine B aqueous solution.In such an experiment the Rho-damine B aqueous solution is completely purified by the presence of the hybrid microfibers under the UV irradiation.     

Remarkable Antibacterial Activity of Reduced Graphene Oxide Functionalized by Copper Ions

Despite long-term efforts for exploring antibacterial agents or drugs, potentiating antibacterial activity and meanwhile minimizing toxicity to the environment remains a challenge. Here, it is experimentally shown that the functionality of reduced graphene oxide (rGO) through copper ions displays selective antibacterial activity that is significantly stronger than that of rGO itself and no toxicity to mammalian cells. Remarkably, this antibacterial activity is two-orders-of-magnitude greater than the activity of its surrounding copper ions. It is demonstrated that rGO is functionalized through the cation–π interaction to massively adsorb copper ions to form a rGO–copper composite and result in an extremely low concentration level of surrounding copper ions (less than ≈0.5 µm ). These copper ions on rGO are positively charged and strongly interact with negatively charged bacterial cells to selectively achieve antibacterial activity, while rGO exhibits the functionality to not only actuate rapid delivery of copper ions and massive assembly onto bacterial cells but also result in the valence shift in the copper ions from Cu²⁺ into Cu⁺, which greatly enhances the antibacterial activity. Notably, this rGO functionality through cation–π interaction with copper ions can similarly achieve algaecidal activity but does not exert cytotoxicity against neutrally charged mammalian cells.     

DCNN深度特征与交替方向乘子的相关滤波跟踪

针对采用相关滤波的判别式目标跟踪遇到的瓶颈问题：由于目标快速移动引起边界效应，使得相关滤波器在学习与更新过程中可能会引入错误，最终错误的累积将导致跟踪失败。在采集深度学习特征与样本相似性度量的基础上，提出一种引入交替方向乘子方法的改进相关滤波目标跟踪算法，选择DCNN深度特征有效地表征待跟踪目标的初始状态，通过在线分类过程中样本相似性比对与半监督学习，辅助解决相关滤波器在学习过程中存在的自学习问题。所提目标跟踪算法特别适合训练样本为持续获得的、同时存储空间较小的机器学习过程，提高目标在快速运动与部分遮挡等复杂情况下的跟踪成功率，针对VOT2016标准测试视频的实验表明：当目标面临快速运动时，对比CN、SAMF、STC算法，所提DA-CFT跟踪算法将跟踪成功率分别由60.4%～73.4%、67.2%～82.9%、80.9%～88.1%提升至85.6%～91.0%。