Evaluation of Non-Ambiguous Critical Micelle Concentration of Surfactants in Relation to Solution Behaviors of Pure and Mixed Surfactant Systems: A Physicochemical Documentary and Analysis

Critical micelle concentration (CMC) is a fundamental physical parameter of surfactant aggregation in solution. The CMC is determined by different methods, tensiometry, conductometry, microcalorimetry, fluorimetry, and so on. However, it is known that though CMC is reported as a single value, in reality, micelle formation occurs over a narrow range of concentration for different experimental procedures produce different results. We shall discuss about a unique procedure of measuring correct CMC applicable to all potential methods used in practice. This is essential for the evaluation of thermodynamic properties of the micelle forming process in pure and mixed states in terms of solution theories. As we in this short documentary want to deal with various aspects of Milton Rosen's research—wherein we have also worked—a few other facets of surfactant chemistry research, besides the micelle formation, are also briefly discussed. In mixed surfactant systems, synergistic effects in various surfactant properties like detergency, foaming, solubilization, and so on are found whereas in some others non-synergistic effects are observed. Dehydration of micelles with an increase in temperature or by the addition of hydrophilic substances may cause clouding to the system. Soluble amphiphilic systems produce Gibbs monolayer at the air/water interface; insoluble amphiphiles form Langmuir monolayers. A documentary of the above aspects will be herein presented and discussed. We mention that this article is neither an original research article nor a review article. This is a mixture of the two: a documentary of both original research and some review of our works presented in memory of Prof. Milton Rosen.     

低功耗高性能的全MOS电压基准源设计

设计了一种基于亚阈值技术的全MOS电压基准源,采用共源共栅结构来增大PSRR,使用MOS管代替电阻,优化温度特性,使电路中大部分MOS管工作于亚阈值区。基于0.18μm CMOS工艺进行设计、版图绘制、和前、后仿真,在后仿真中得出相关参数值。对各参数做出详细分析,包括:一定温度范围内的温度系数;常温下基准输出电压;不同电源电压条件下的线性调整率、基准源静态电流及功耗,并对不同频率下的电源电压抑制比进行了对比。实验结果表明达到了低功耗高性能的设计目标。     

Common Mode Voltage Reduction Using 3D-SVPWM for 3-level CI-NPC Inverter with Hybrid Energy System

This paper elucidates Common Mode Voltage (CMV) reduction in transformerless 3-phase 3-level Coupled Inductor Neutral Point (CI-NPC) Clamped Inverter with Hybrid Energy System. The three dimensional Space Vector Pulse Width Modulation (3D-SVPWM) with Nearest State Vector (NSV) is implemented to reduce the CMV by proper selection of medium, large and small vectors in 3D cubic space region. This NSV scheme in addition to CMV reduction, reduces the capacitor voltage balancing issues and minimizes switching losses. The proposed control provides full utilization of dc link voltage with reduced harmonics. This 3-level CI-NPC inverter is energized by hybrid energy source which includes photovoltaic system and wind energy system. The results obtained for the proposed scheme through simulation and experimental setup is compared with the conventional 2D-SVPWM and 3D-SVPWM scheme. From the compared results it is evident that the proposed scheme reduces CMV to a larger extent than 2D and 3D-SVPWM control. The simulation and experimental results are verified using matlab-simulink and FPGA-Spartan-6 controller respectively.     

The control of paracetamol particle size and surface morphology through crystallisation in a spray dryer

The parameters governing the crystallisation of paracetamol using various conventional techniques has been extensively studied, however the factors influencing the drug crystallisation using spray drying is not as well understood. The aim of this work was to investigate the crystallisation of an active pharmaceutical ingredient through evaporative crystallisation using a spray dryer to study the physicochemical properties of the drug and to use semi-empirical equations to gain insight into the morphology and particle size of the dried powder. Paracetamol solutions were spray dried at various inlet temperatures ranging from 60 °C to 120 °C and also from a series of inlet feed solvent compositions ranging from 50/50% v/v ethanol/water to 100% ethanol and solid-state characterisation was done. The size and morphology of the dried materials were altered with a change in spray drying parameters, with an increase in inlet temperature leading to an increase in particle Sauter mean diameter (from 3.0 to 4.4 µm) and a decrease in the particle size with an increase in ethanol concentration in the feed (from 4.6 to 4.4 µm) as a result of changes in particle density and atomised droplet size. The morphology of the dried particles consisted of agglomerates of individual crystallites bound together into larger semi-spherical agglomerates with a higher tendency for particles having crystalline ridges to form at higher ethanol concentrations of the feed.     

Study on the long-term behaviour of glass fibre in the tensile stress field

Glass fibre is a random network structure composed of [SiO₄] tetrahedra. The structure contains a large number of defects, which act as crack initiation points. Under tensile stress, cracks undergo crack initiation, stable propagation, failure propagation, and fracture, and the stress that begins after unstable propagation is called the critical fracture stress. When the stress is less than the critical value, the crack is subject to the force of chemical bonds during the crack propagation process, and crack arrest occurs. When the stress is greater than the critical value, the glass fibre will undergo destructive fracture. In this paper, long-term tensile tests were carried out on glass fibre and a glass fibre composite under different constant tensile stress conditions. The fracture times of the glass fibre and glass fibre composite under different tensile stresses were obtained, the critical fracture stress of glass fibre was inferred, and the fracture mechanism was explained.     

Prediction of mode I fracture toughness of rock using linear multiple regression and gene expression programming

Prediction of mode I fracture toughness (K_IC) of rock is of significant importance in rock engineering analyses. In this study, linear multiple regression (LMR) and gene expression programming (GEP) methods were used to provide a reliable relationship to determine mode I fracture toughness of rock. The presented model was developed based on 60 datasets taken from the previous literature. To predict fracture parameters, three mechanical parameters of rock mass including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and elastic modulus (E) have been selected as the input parameters. A cluster of data was collected and divided into two random groups of training and testing datasets. Then, different statistical linear and artificial intelligence based nonlinear analyses were conducted on the training data to provide a reliable prediction model of K_IC. These two predictive methods were then evaluated based on the testing data. To evaluate the efficiency of the proposed models for predicting the mode I fracture toughness of rock, various statistical indices including coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE) were utilized herein. In the case of testing datasets, the values of R², RMSE, and MAE for the GEP model were 0.87, 0.188, and 0.156, respectively, while they were 0.74, 0.473, and 0.223, respectively, for the LMR model. The results indicated that the selected GEP model delivered superior performance with a higher R² value and lower errors.     

Life-cycle assessment of hydrogen technologies with the focus on EU critical raw materials and end-of-life strategies

We present the results of a life-cycle assessment (LCA) for the manufacturing and end-of-life (EoL) phases of the following fuel-cell and hydrogen (FCH) technologies: alkaline water electrolyser (AWE), polymer-electrolyte-membrane water electrolyser (PEMWE), high-temperature (HT) and low-temperature (LT) polymer-electrolyte-membrane fuel cells (PEMFCs), together with the balance-of-plant components. New life-cycle inventories (LCIs), i.e., material inputs for the AWE, PEMWE and HT PEMFC are developed, whereas the existing LCI for the LT PEMFC is adopted from a previous EU-funded project. The LCA models for all four FCH technologies are created by modelling the manufacturing phase, followed by defining the EoL strategies and processes used and finally by assessing the effects of the EoL approach using environmental indicators. The effects are analysed with a stepwise approach, where the CML2001 assessment method is used to evaluate the environmental impacts. The results show that the environmental impacts of the manufacturing phase can be substantially reduced by using the proposed EoL strategies (i.e., recycled materials being used in the manufacturing phase and replacing some of the virgin materials). To point out the importance of critical materials (in this case, the platinum-group metals or PGMs) and their recycling strategies, further analyses were made. By comparing the EoL phase with and without the recycling of PGMs, an increase in the environmental impacts is observed, which is much greater in the case of both fuel-cell systems, because they contain a larger quantity of PGMs.     

Direct model-based predictive control scheme without cost function for voltage source inverters with reduced common-mode voltage

This paper presents a direct model-based predictive control scheme for voltage source inverters (VSIs) with reduced common-mode voltages (CMVs). The developed method directly finds optimal vectors without using repetitive calculation of a cost function. To adjust output currents with the CMVs in the range of –V_dc/6 to +V_dc/6, the developed method uses voltage vectors, as finite control resources, excluding zero voltage vectors which produce the CMVs in the VSI within ±V_dc/2. In a model-based predictive control (MPC), not using zero voltage vectors increases the output current ripples and the current errors. To alleviate these problems, the developed method uses two non-zero voltage vectors in one sampling step. In addition, the voltage vectors scheduled to be used are directly selected at every sampling step once the developed method calculates the future reference voltage vector, saving the efforts of repeatedly calculating the cost function. And the two non-zero voltage vectors are optimally allocated to make the output current approach the reference current as close as possible. Thus, low CMV, rapid current-following capability and sufficient output current ripple performance are attained by the developed method. The results of a simulation and an experiment verify the effectiveness of the developed method.