Material encapsulation in poly(methyl methacrylate) shell: A review

Material encapsulation is a relatively new technique for coating a micro/nanosize particle or droplet with polymeric or inorganic shell. Encapsulation technology has many applications in various fields including drug delivery, cosmetic, agriculture, thermal energy storage, textile, and self-healing polymers. Poly(methyl methacrylate) (PMMA) is widely used as shell material in encapsulation due to its high chemical stability, biocompatibility, nontoxicity, and good mechanical properties. The main approach for micro/nanoencapsulation of materials using PMMA as shell comprises emulsion-based techniques such as emulsion polymerization and solvent evaporation from oil-in-water emulsion. In the present review, we first focus on the encapsulation techniques of liquid materials with PMMA shell by analyzing the effective processing parameters influencing the preparation of PMMA micro/nanocapsules. We then describe the morphology of PMMA capsules in emulsion systems according to thermodynamic relations. The techniques to investigation of mechanical properties of capsule shell and the release mechanisms of core material from PMMA capsules were also investigated. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48039.     

A PV installation framework concerning electricity variable rates

This paper assesses building integrated photovoltaic (BIPV) installation parameters based on the profit generated by a photovoltaic system. It takes into consideration a home building case study and it investigates its monthly energy demand based on a specific location and a typical occupancy. The capability of a photovoltaic (PV) system to generate more profit occurs when solar intensity is maximum while the electric energy price is at its highest rate. The paper traces a framework that encompasses different aspects such as energy demand, energy price, and solar intensity. This framework identifies profit alternatives according to different installation parameters. A tool that predicts a PV installation hourly electric energy production is developed. The profit generated is simulated for home buildings located in Beirut (Lebanon) and Xihua (China), both at 33.8° latitude north. The paper highlights a new approach for BIPV installations, taking into account weather conditions, energy demand, and electric energy utility rates.     

Longitudinal permeability determination of dual-scale fibrous materials

In this work, the longitudinal permeability of squarely packed dual-scale fiber preforms is studied theoretically. These fiber preforms are composed of aligned porous tows and the tows are tightly packed. The effective permeability is calculated as a parallel-like network of intra-tow permeability and inter-tow permeability, which are quantified by Darcy’s law and the inscribed radius between tows, respectively. The jump velocity at the interface between inter-tow fluids and porous tows is considered, as derived by substituting Beavers and Joseph’s correlation into Brinkman’s equation. We further examine the effects of intra-tow permeability on the effective permeability of the fibrous system with three interface conditions: (1) interface velocity = 0, (2) interface velocity = mean intra-tow velocity, and (3) interface velocity = jump velocity. The jump-velocity-based model is found to be closest to numerical data. The influence of the fiber volume fraction of tows on the effective permeability is also analyzed.     

Effects of Winding Attachment Positions on Output Characteristics of Flux‐Modulating Synchronous Machines

The flux‐modulating synchronous machine (FMSM) is a new type of multipole SM with nonoverlapping concentrated armature and field windings on the stator. This paper compares the output characteristics of two FMSMs through finite element analysis (FEA) and experiments. In both of the FMSMs, the attachment positions of the armature and field windings are swapped. To determine the reason for the discrepancies in their output characteristics, unsaturated inductances were calculated using a d‐‐q equivalent circuit. In addition, the calculated results of the inductances were confirmed through a visualization of the leakage fluxes using FEA. The results of the study show that the synchronous inductance can be reduced by attaching the armature winding to the air‐gap side of the stator teeth and that the reduction leads to an increase in output power.     

基于改进D?Lite遗传算法路径规划研究

针对遗传算法在移动机器人路径规划中易产生早熟现象和收敛速度慢的问题,提出了改进的D~* Lite遗传算法。该算法将D~* Lite算法和遗传算法相结合,通过引入碰撞系数和可视检测技术以提高路径安全性,寻找最短路径。在遗传算法设计中加入动态调整交叉与变异概率,以解决算法在路径规划中因陷入局部最优值而不能到达目标点的问题。最后,通过实验仿真可知:与蚁群算法和免疫遗传算法相比,改进的D~* Lite遗传算法执行效率高,可以快速规划出全局最优路径。     

Iron(II) Sulfate(VI) from Titania Production as a Raw Material for Preparation of Hydrogen Sulfide Sorbents

A hybrid sorbent material for removal of hydrogen sulfide from air was developed. The material is based on activated carbon and iron compounds obtained from waste iron(II) sulfate(VI) heptahydrate. The iron salt is deposited on the carbonaceous support and subjected to oxidation (Fe²⁺ to Fe³⁺) using atmospheric oxygen under alkaline conditions. An effect of H₂O₂ addition to the process on the composition of the resultant material was also examined. X-ray diffraction (XRD) analyses confirmed easy conversion of waste FeSO₄·7H₂O to iron oxides Fe₃O₄ and FeOOH. The activated carbon supporting iron oxides revealed a higher efficiency in H₂S elimination from air compared to the commercial activated carbon, without any modification.     

基于神经网络和遗传算法的锭子弹性管性能优化

为得到减振弹性管对下锭胆的支承弹性和锭子高速运动下的稳定性等性能的最优匹配效率,依据减振弹性管的等效抗弯刚度及底部等效刚度系数公式,利用MatLab数值分析软件构建弹性管抗弯刚度和底部挠度数学模型。首先,结合Isight优化软件基于径向基神经网络构建其近似模型,且使精度达到可接受水平,并以模型的关键结构参数弹性模量、螺距、槽宽、壁厚为设计变量,结合遗传算法对弹性管抗弯刚度和底部挠度进行多目标优化设计,得到Pareto最优解集和Pareto前沿图,确定出减振弹性管结构工艺参数的优化方案。通过对优化数据进行分析发现,该方案在保证减振弹性管弹性的同时,其底部振幅明显减弱。     

Effects of the film thickness and poling electric field on photovoltaic performances of (Pb,La)(Zr,Ti)O3 ferroelectric thin film-based devices

The ferroelectric photovoltaic (FPV) effect obtained in inorganic perovskite ferroelectric materials has received much attention because of its large potential in preparing FPV devices with superior stability, high open-circuit voltage (V_oc) and large short-circuit current density (J_sc). In order to obtain suitable thickness for the ferroelectric thin film as light absorption layer, in which, the sunlight can be fully absorbed and the photo-generated electrons and holes are recombined as few as possible, we prepare Pb_0.93La_0.07(Zr_0.6Ti_0.4)_0.9825O₃ (PLZT) ferroelectric thin films with different layer numbers by the sol-gel method and based on these thin films, obtain FPV devices with FTO/PLZT/Au structure. By measuring photovoltaic properties, it is found that the device with 4 layer-PLZT thin film (~300 nm thickness) exhibits the largest V_oc and J_sc and the photovoltaic effect obviously depends on the value and direction of the poling electric field. When the device is applied a negative poling electric field, both the V_oc and J_sc are significantly higher than those of the device applied the positive poling electric field, due to the depolarization field resulting from the remnant polarization in the same direction with the built-in electric field induced by the Schottky barrier, and the higher the negative poling electric field, the larger the V_oc and J_sc. At a -333 kV/cm poling electric field, the FPV device exhibits the most superior photovoltaic properties with a V_oc of as high as 0.73 V and J_sc of as large as 2.11 μA/cm². This work opens a new way for developing ferroelectric photovoltaic devices with good properties.     

{X,Y}-Cyclacene Graphs with Next Nearest Neighbor Interactions

Eigensolutions of {X( = C,B,N),Y( = C,B,N)}-cyclacene graphs with next nearest neighbor (nnn) interactions have been obtained in analytical forms by adapting n-fold rotational symmetry followed by two-fold rotational symmetry (or a plane of symmetry). Expressions of eigensolution indicate the subspectral relationship among such cyclacenes with an even number of hexagonal rings e.g., eigenvalues of {X,Y}-di-cyclacene are found in the eigenspectra of all such even cyclacenes. Total π-electron energies and highest occupied molecular orbital and lowest unoccupied molecular orbital (HOMO–LUMO) gaps are calculated using the analytical expressions obtained and are found to vary negligibly with the variation of nnn interactions in such cyclacenes. Total π-electron energy is found to increase due to increase in restriction intensity of nnn interactions, whereas the HOMO–LUMO gap of polyacenecs having the even number of hexagonal rings and with one electron at each site (atom) decreases with increase in the restriction intensity since such systems contain degenerate half-filled HOMO (bonding or nonbonding) that are much more vulnerable for perturbations imposed through nnn interactions.     

Flexible Distribution-Based Regression Models for Count Data: Application to Medical Diagnosis

Abstract

Data mining techniques have been successfully utilized in different applications of significant fields, including medical research. With the wealth of data available within the health-care systems, there is a lack of practical analysis tools to discover hidden relationships and trends in data. The complexity of medical data that is unfavorable for most models is a considerable challenge in prediction. The ability of a model to perform accurately and efficiently in disease diagnosis is extremely significant. Thus, the model must be selected to fit the data better, such that the learning from previous data is most efficient, and the diagnosis of the disease is highly accurate. This work is motivated by the limited number of regression analysis tools for multivariate counts in the literature. We propose two regression models for count data based on flexible distributions, namely, the multinomial Beta-Liouville and multinomial scaled Dirichlet, and evaluated the proposed models in the problem of disease diagnosis. The performance is evaluated based on the accuracy of the prediction which depends on the nature and complexity of the dataset. Our results show the efficiency of the two proposed regression models where the prediction performance of both models is competitive to other previously used regression models for count data and to the best results in the literature.