Investigation of pillar thickness variation effect on oblique rotating implantation (ORI)-based vertical double gate MOSFET

The rapid scaling of integrated circuit requires further shrinkage of lateral device dimension, which correlates with pillar thickness in vertical structure. This paper investigates the effect of pillar thickness variation on vertical double gate MOSFET (VDGM) fabricated using oblique rotating ion implantation (ORI) method. For this purpose, several scenarios of silicon pillar thickness t_si were evaluated for 20–100 nm channel length. The source region was found to merge at pillar thickness below 75 nm, which results in floating body effect and creates isolated region in the middle of pillar. The vertical devices using ORI method show better performance than those with conventional implantation method for all pillar thickness, due to the elimination of corner effect that degrades the gate control. The presence of isolated depletion region in the middle of pillar at floating body increases parasitic effect for higher drain potential. By further reduction of pillar thickness towards fully depleted feature, the increase in gate-to gate charge coupling improves the performance of ORI-based vertical double gate MOSFET, as evident in near-ideal swing value and lower DIBL, compared to the partially depleted and body-tied device.     

Enhanced maximum curvature descriptors for finger vein verification

Multimedia Tools and Applications - Maximum Curvature Method (MCM) is one of the promising methods for finger vein verification. MCM scans the curvature of the vein image profiles within a finger...     

Applying variable precision rough set model for clustering student suffering study’s anxiety

Computational models of the artificial intelligence such as rough set theory have several applications. Data clustering under rough set theory can be considered as a technique for medical decision making. One possible application is the clustering of student suffering study’s anxiety. In this paper, we present the applicability of variable precision rough set model for clustering student suffering studies anxiety. The proposed technique is based on the mean of accuracy of approximation using variable precision of attributes. The datasets are taken from a survey aimed to identify of studies anxiety sources among students at Universiti Malaysia Pahang (UMP). At this stage of the research, we show how variable precision rough set model can be used to groups student in each study’s anxiety. The results may potentially contribute to give a recommendation how to design intervention, to conduct a treatment in order to reduce anxiety and further to improve student’s academic performance.     

Noble-free oxygen reduction reaction catalyst supported on Sengon wood (Paraserianthes falcataria L.) derived reduced graphene oxide for fuel cell application

Reduced graphene oxide (RGO) has progressed as one of key emerging carbon for catalyst support material. As an alternative to the conventional RGO precursor, biomass Sengon wood was converted into RGO for use as a noble metal free catalyst support in oxygen reduction reaction (ORR). This work intends to reveal the applicability of Sengon wood-derived RGO in anchoring/doping iron and nitrogen particles onto its surface and to study its ORR performance in a half-cell environment. Thin-sheet layer and highly defective (I_D/I_G) was gradually obtained at elevated pyrolysis temperature of Sengon wood graphene oxide (GO) at range 700°C to 900°C. As prepared RGO was further doped into catalyst (Fe/N/RGO) through the same pyrolysis procedure at a selected temperature after mixing the GO powder with iron chloride and different nitrogen precursors (urea, choline chloride, and polyaniline) at a fixed ratio. The ORR activity reached a current density up to 2.43 mA/cm², which in conjunction with smooth multilayer sheet morphology and high graphitic-N content as the active sites. Stability analysis indicated an 85% current efficiency and only 0.03 V reduction in onset potential on methanol resistant test for Fe/ChoCl/RGO catalyst. This study revealed that Sengon wood-derived RGO successfully supported Fe-N-C catalyst which showed comparable oxygen reduction activity to Pt/C.     

Vibration impact acoustic emission technique for identification and analysis of defects in carbon steel tubes: Part B Cluster analysis

Current steel tubes inspection techniques are invasive, and the interpretation and evaluation of inspection results are manually done by skilled personnel. Part A of this work details the methodology involved in the newly developed non-invasive, non-destructive tube inspection technique based on the integration of vibration impact (VI) and acoustic emission (AE) systems known as the vibration impact acoustic emission (VIAE) technique. AE signals have been introduced into a series of ASTM A179 seamless steel tubes using the impact hammer. Specifically, a good steel tube as the reference tube and four steel tubes with through-hole artificial defect at different locations were used in this study. The AEs propagation was captured using a high frequency sensor of AE systems. The present study explores the cluster analysis approach based on autoregressive (AR) coefficients to automatically interpret the AE signals. The results from the cluster analysis were graphically illustrated using a dendrogram that demonstrated the arrangement of the natural clusters of AE signals. The AR algorithm appears to be the more effective method in classifying the AE signals into natural groups. This approach has successfully classified AE signals for quick and confident interpretation of defects in carbon steel tubes.     

Microstructural investigations of XW-42 and M2 tool steels in semi-solid zones via direct partial remelting route

A suitable microstructure for thixoforming consists of spheroidal grains in a liquid matrix. In order to achieve this, some processing routes have been established. In this study, microstructural evolution of XW-42 and AISI M2 steels via direct partial remelting from the as-annealed condition was examined. Both steels were found to possess certain types of carbides that dissolved when subjected to heating inside the semi-solid zones. The types of carbides were MC-M₆C for AISI M2 steel (fully dissolved between 1280 and 1300 °C) and M₇C₃ for XW-42 steel (fully dissolved between 1250 and 1270 °C). The dissolution of these grain boundary carbides during partial remelting helps with the grain spheroidisation and also with providing grain lubrication for the forming process through solid–liquid particle contact. In addition, solid–solid contacts were also observed (in 2D as well as 3D microstructural observation) and considered useful to provide structural integrity prior to forming. However, these contacts also must also be weak enough to be sheared easily. Compression test results for AISI M2 steel showed that thixotropic behaviour and complete mould filling were observed starting from 35 liquid percent. The same behaviour is also expected to occur for XW-42 steel due to its similarity in microstructural evolution with AISI M2 steel.     

Carrier transport in high-efficiency ZnO/SiO2/Si solar cells

Carrier transport in ZnO/SiO₂/n-Si solar cell has been theoretically analyzed with a consideration that the photo-carrier transport from silicon to ZnO layer through the barrier is dominated by quantum mechanical tunneling process of minority carrier. It was found that the highest efficiency of the cell could be achieved at SiO₂ layer thickness of around 20 Å. The efficiency of the cells decreases as the surface states density Q_ss becomes higher. Moreover, the efficiency increases as the electron concentration of ZnO layer is increased due to the decrease of work function of ZnO. It was also found that the lower transmittance of the high carrier concentration ZnO due to the free-carrier absorption at infrared wavelength region does not give any significant effect to the cell performance. The efficiency of higher than 25% is achievable by optimizing the involved device parameters.     

Hybrid genetic algorithm for multi-time period production/distribution planning

In this paper, we deal with a production/distribution problem to determine an efficient integration of production, distribution and inventory system so that products are produced and distributed at the right quantities, to the right customers, and at the right time, in order to minimize system wide costs while satisfying all demand required. This problem can be viewed as an optimization model that integrates facility location decisions, distribution costs, and inventory management for multi-products and multi-time periods. To solve the problem, we propose a new technique called spanning tree-based genetic algorithm (hst-GA). In order to improve its efficiency, the proposed method is hybridized with the fuzzy logic controller (FLC) concept for auto-tuning the GA parameters. The proposed method is compared with traditional spanning tree-based genetic algorithm approach. This comparison shows that the proposed method gives better results.     

Solving exclusionary side constrained transportation problem by using a hybrid spanning tree-based genetic algorithm

In real life applications we often have the following problem: How to find the reasonable assignment strategy to satisfy the source and destination requirement without shipping goods from any pairs of prohibited sources simultaneously to the same destination so that the total cost can be minimized. This kind of problem is known as the transportation problem with exclusionary side constraint (escTP). Since this problem is one of nonlinear programming models, it is impossible to solve this problem using a traditional linear programming software package (i.e., LINDO). In this paper, an evolutionary algorithm based on a genetic algorithm approach is proposed to solve it. We adopt a Prüfer number to represent the candidate solution to the problem and design the feasibility of the chromosome. Moreover, to handle the infeasible chromosome, here we also propose the repairing procedure. In order to improve the performance of the genetic algorithm, the fuzzy logic controller (FLC) is used to dynamically control the genetic operators. Comparisons with other conventional methods and the spanning tree-based genetic algorithm (st-GA) are presented and the results show the proposed approach to be better as a whole.