3-D profiles and surface topography of alumina compacts

A non-contacting laser scanning profilometer, with associated hardware and software, is used for the determination of the overall shape and surface topography of cylindrical alumina compacts. The change in the shape distortion of the cylinder, defined as (R_max-R_min)/R_min (R is the radius of the compact), was monitored, as a function of the ambient temperature, during sintering.During sintering, an increase in the diameteral distortion values were observed. Certain surface topographic characteristics , also obtained by the laser scanning of the surfaces of the green compacts, were used to characterise the agglomerate deformation and breakdown. The deformation of agglomerates starts at very low compaction pressures. However, the inter-agglomerate pores are not eliminated until a compaction pressure of 37 MPa.     

Electrical and interface state density properties of the 4H-nSiC/[6,6]-phenyl C61-butyric acid methyl ester/Au diode

The electrical and interface state density properties of the Ni/4H-nSiC/PCBM/Au diode have been investigated by current-voltage, capacitance-voltage and conductance-frequency methods. The ideality factor, barrier height and series resistance values of the diode were found to be 2.28, 1.10 eV and 3.76 × 10⁴ Ω, respectively. The diode shows a non-ideal I-V behaviour with an ideality factor greater than unity that could be ascribed to the interfacial layer, interface states and series resistance. The obtained barrier height (1.10 eV) of the Ni/4H-nSiC/PCBM/Au diode is lower than that of Ni/4H-nSiC diode (1.32 eV). This indicates that the PCBM organic layer induces a change of 160 meV in the barrier height of the Ni/4H-nSiC diode. The interface state density of the diode was determined from G_p/ω-f plots and was of order of 5.61 × 10¹² eV⁻¹ cm⁻².     

Spatial assessment of site suitability for solar desalination plants: a case study of the coastal regions of Turkey

Clean Technologies and Environmental Policy - Many countries, especially in arid and semiarid regions, suffer from water scarcity because of the decline in the existing freshwater reserves by...     

An agile production network enabled by reconfigurable manufacturing systems

Emergencies, and efforts to address them, create disruptions to local and global supply chains and surges in demand of emergency resources, which substantially affect global production. Reconfigurable manufacturing systems are promising solutions to improve flexibility and to reduce the effort needed to adapt supply chains and production networks to fit a perturbed environment. This paper proposes a method for coordination of reconfigurable manufacturing resources from multiple enterprises to structure ad-hoc production networks for critical products required in emergencies. Network optimization models and interaction algorithms are integrated to evolve the production network through synchronous machine-level and network-level reconfiguration driven by data.     

The Implementation of Optimization Methods for Contrast Enhancement

The performances of the multivariate techniques are directly related to the variable selection process, which is time consuming and requires resources for testing each possible parameter to achieve the best results. Therefore, optimization methods for variable selection process have been proposed in the literature to find the optimal solution in short time by using less system resources. Contrast enhancement is the one of the most important and the parameter dependent image enhancement technique. In this study, two optimization methods are employed for the variable selection for the contrast enhancement technique. Particle swarm optimization (PSO) and artificial bee colony (ABC) optimization methods are implemented to the histogram stretching technique in parameter selection process. The results of the optimized histogram stretching technique are compared with one of the parameter independent contrast enhancement technique; histogram equalization. The results show that the performance of the optimized histogram stretching is better not only in distorted images but also in original images. Histogram equalization degraded the original images while the optimized histogram stretching has no effect due to being an adaptive solution.     

Defect Passivation in Perovskite Solar Cells by Cyano‐Based π‐Conjugated Molecules for Improved Performance and Stability

Defects at the surface and grain boundaries of metal–halide perovskite films lead to performance losses of perovskite solar cells (PSCs). Here, organic cyano‐based π‐conjugated molecules composed of indacenodithieno[3,2‐b]thiophene (IDTT) are reported and it is found that their cyano group can effectively passivate such defects. To achieve a homogeneous distribution, these molecules are dissolved in the antisolvent, used to initiate the perovskite crystallization. It is found that these molecules are self‐anchored at the grain boundaries due to their strong binding to undercoordinated Pb²⁺. On a device level, this passivation scheme enhances the charge separation and transport at the grain boundaries due to the well‐matched energetic levels between the passivant and the perovskite. Consequently, these benefits contribute directly to the achievement of power conversion efficiencies as high as 21.2%, as well as the improved environmental and thermal stability of the PSCs. The surface treatment provides a new strategy to simultaneously passivate defects and enhance charge extraction/transport at the device interface by manipulating the anchoring groups of the molecules.     

Smartphone based sperm counting - an alternative way to the visual assessment technique in sperm concentration analysis

Sperm Counting is the first phase of the infertility diagnosis. Computer Aided Sperm Analysis (CASA) and Visual Assessment (VA) are two evaluation techniques employed in analyses. VA is carried out by observing sperm on counting chambers. Therefore, diagnosis strongly depends on the skills and experiences. CASA isolates the human factor by utilizing the computer based techniques. However, it is more costly than VA and requires exhausted parameter settings. In this study, we present a novel approach that uses smartphone and computer for sperm counting analysis. Smartphone is used to obtain images similar to VA technique. Then, sample videos are transferred to the computer side where we developed the Computerized Sperm Counting Software (CSCS) to count the sperm using counting chambers and eliminate human effects. CSCS consists of four modules: (1) Data Acquisition and Organization, (2) Regions of Interest (ROI) detection, (3) Motile/Immotile Sperm Detection, (4) Counting. Smartphone based data acquisition provided less costly design contrary to CASA systems. ROI extraction was realized by a combinational approach of line detection and segmentation methods. Background and Foreground extractions were employed in immotile and motile sperm detection process, respectively. Additionally, active contour was implemented to enhance the segmentation of immotile sperm. As the final step, detected sperms were counted by pixel based blob analysis. According to experimental results, the proposed smartphone based sperm concentration analysis can be adapted in laboratories due to its modularity, functionality, accuracy and cost when compare to CASA and VA based sperm counting analysis.

     

A new methodology for optimization and prediction of rate of penetration during drilling operations

Predictive models have been widely used in different engineering fields, as well as in petroleum engineering. Due to the development of high-performance computer systems, the accuracy and complexity of predictive models have been increased significantly. One of the common methods for prediction is artificial neural network (ANN). ANN models in combination with optimization algorithms provide a powerful and fast tool for the prediction and optimization of processes which take a large amount of time if they are simulated using common simulation technics. In the present paper, to predict penetration rate during drilling process, several ANN models were developed based on the data obtained from drilling of a gas well located in south of Iran. Regarding the R2 and RMSE values of the developed models, the best model was selected for prediction of penetration rate. In the next step, artificial bee colony algorithm was used for optimization of the parameters which are effective on rate of penetration (ROP). Results showed that the model is accurate enough for being used in the prediction and optimization of ROP in drilling operations.     

A comparative analysis of efficiency and reliability of capacitive micro-switches with initially curved electrodes

Enhancement of both efficiency and reliability of MEMS structures has always been an interesting and even essential issue for research community. This paper provides a comparative investigation in this field focusing on the role of initially curved electrodes of capacitive micro-switches. Four models have been introduced by appliance of curved microbeams as either upper or lower electrodes of a capacitive MEMS switch, as well as the conventional base model with straight both electrodes. By introducing a mathematical model and appropriate numerical procedure, the contact area between two electrodes, which has direct effect on the reliability has been estimated using Hertz relation for all models. The electromechanical coupling factor which is related to the efficiency of the switch has been calculated considering the stored mechanical and electrical energy of the system. The results have shown that by appliance of an initial curvature to the both electrodes, the estimated contact area can increase up to 279% compared to the conventional switches. Also, a switch with straight moveable electrode and curved substrate exhibits an increase in coupling factor up to 24% compared to the base model, while increasing the pull-in voltage of the switch.