Morphological defects and uniformity issues of 4H-SiC homoepitaxial layers grown on off-oriented (0001)Si faces

The morphological defects and uniformity of 4H-SiC epilayers grown by hot wall CVD at 1500 degrees C on off-oriented (0001) Si faces are characterized by atomic force microscope, Nomarski optical microscopy, and Micro-Raman spectroscopy. Typical morphological defects including triangular defects, wavy steps, round pits, and groove defects are observed in mirror-like SiC epilayers. The preparation of the substrate surface is necessary for the growth of high-quality 4H-SiC epitaxial layers with low-surface defect density under optimized growth conditions. (c) 2006 Elsevier Ltd. All rights reserved.

Phase-locked ring-defect photonic crystal vertical-cavity surface-emitting laser

Phase-locked oxide-confined ring-defect photonic crystal vertical-cavity surface-emitting laser is presented. The coupled-mode theory is employed to illustrate the two supermodes of the device, in-phase and out-of-phase supermode. Experimental results verify the two supermodes by the characteristics of the spectra and the far field patterns. At the lower current, only the out-of-phase supermode is excited, whereas under the higher current, the in-phase supermode also appears at the shorter wavelength range. In addition, the measured spectral separation between the two supermodes agrees well with the theoretical result.

NEW TYPE OF SILICON MATERIAL WITH VERY HIGH-QUALITY SURFACE-LAYER ON INSULATING DEFECT LAYER

A new-type silicon material, silicon on defect layer (SODL) was proved to have a very high quality surface microstructure which is necessary for commercially feasible high-density very large scale integrated circuits (VLSI). The structure of the SODL material was viewed by transmission electron microscopy. The SODL material was also proved to have a buried defect layer with an insulating resistivity of 5.7 x 10(10) OMEGA-cm.

A computational model for defect prediction in shape castings based on the interaction of free surface flow, heat transfer, and solidification phenomena

High-integrity castings require sophisticated design and manufacturing procedures to ensure they are essentially macrodefect free. Unfortunately, an important class of such defects—macroporosity, misruns, and pipe shrinkage—are all functions of the interactions of free surface flow, heat transfer, and solidication in complex geometries. Because these defects arise as an interaction of the preceding continuum phenomena, genuinely predictive models of these defects must represent these interactions explicitly. This work describes an attempt to model the formation of macrodefects explicitly as a function of the interacting continuum phenomena in arbitrarily complex three-dimensional geometries. The computational approach exploits a compatible set of finite volume procedures extended to unstructured meshes. The implementation of the model is described together with its testing and a measure of validation. The model demonstrates the potential to predict reliably shrinkage macroporosity, misruns, and pipe shrinkage directly as a result of interactions among free-surface fluid flow, heat transfer, and solidification.

Modulation of surface charge, particle size and morphological properties of chitosan-TPP nanoparticles intended for gene delivery

This work investigates the polyanion initiated gelation process in fabricating chitosan-TPP (tripolyphosphate) nanoparticles in the size range of 100-250 nm intended to be used as carriers for the delivery of gene or protein macromolecules. It demonstrates that ionic gelation of cationic chitosan molecules offers a flexible and easily controllable process for systematically and predictably manipulating particle size and surface charge which are important properties in determining gene transfection efficacy if the nanoparticles are used as non-viral vectors for gene delivery, or as delivery carriers for protein molecules. Variations in chitosan molecular weight, chitosan concentration, chitosan to TPP weight ratio and solution pH value were examined systematically for their effects on nanoparticle size, intensity of surface charge, and tendency of particle aggregation so as to enable speedy fabrication of chitosan nanoparticles with predetermined properties. The chitosan-TPP nanoparticles exhibited a high positive surface charge across a wide pH range, and the isoelectric point (IEP) of the nanoparticles was found to be at pH 9.0. Detailed imaging analysis of the particle morphology revealed that the nanoparticles possess typical shapes of polyhedrons (e.g., pentagon and hexagon), indicating a similar crystallisation mechanism during the particle formation and growth process. This study demonstrates that systematic design and modulation of the surface charge and particle size of chitosan-TPP nanoparticles can be readily achieved with the right control of critical processing parameters, especially the chitosan to TPP weight ratio. (c) 2005 Elsevier B.V. All rights reserved.

The development of a surface defect machining method for hard turning processes

Hard turning (HT) is a material removal process employing a combination of a single point cutting tool and high speeds to machine hard ferrous alloys which exhibit hardness values over 45 HRC. In this paper, a surface defect machining (SDM) method for HT is proposed which harnesses the combined advantages of porosity machining and pulsed laser pre-treatment processing. From previous experimental work, this was shown to provide better controllability of the process and improved quality of the machined surface. While the experiments showed promising results, a comprehensive understanding of this new technique could only be achieved through a rigorous, in depth theoretical analysis. Therefore, an assessment of the SDM technique was carried out using both finite element method (FEM) and molecular dynamics (MD) simulations.
FEM modelling was used to compare the conventional HT of AISI 4340 steel (52 HRC) using an Al2O3 insert with the proposed SDM method. The simulations showed very good agreement with the previously published experimental results. Compared to conventional HT, SDM provided favourable machining outcomes, such as reduced shear plane angle, reduced average cutting forces, improved surface roughness, lower residual stresses on the machined surface, reduced tool–chip interface contact length and increased chip flow velocity. Furthermore, a scientific explanation of the improved surface finish was revealed using a state-of-the-art MD simulation model which suggested that during SDM, a combination of both the cutting action and rough polishing action help improve the machined surface finish.

A sparse representation based fast detection method for surface defect detection of bottle caps

A practical machine-vision-based system is developed for fast detection of defects occurring on the surface of bottle caps. This system can be used to extract the circular region as the region of interests (ROI) from the surface of a bottle cap, and then use the circular region projection histogram (CRPH) as the matching features. We establish two dictionaries for the template and possible defect, respectively. Due to the requirements of high-speed production as well as detecting quality, a fast algorithm based on a sparse representation is proposed to speed up the searching. In the sparse representation, non-zero elements in the sparse factors indicate the defect's size and position. Experimental results in industrial trials show that the proposed method outperforms the orientation code method (OCM) and is able to produce promising results for detecting defects on the surface of bottle caps.

A theoretical assessment of surface defect machining and hot machining of nanocrystalline silicon carbide

In this paper, a newly proposed machining method named “surface defect machining” (SDM) [Wear, 302, 2013 (1124-1135)] was explored for machining of nanocrystalline beta silicon carbide (3C-SiC) at 300K using MD simulation. The results were compared with isothermal high temperature machining at 1200K under the same machining parameters, emulating ductile mode micro laser assisted machining (µ-LAM) and with conventional cutting at 300 K. In the MD simulation, surface defects were generated on the top of the (010) surface of the 3C-SiC work piece prior to cutting, and the workpiece was then cut along the <100> direction using a single point diamond tool at a cutting speed of 10 m/sec. Cutting forces, sub-surface deformation layer depth, temperature in the shear zone, shear plane angle and friction coefficient were used to characterize the response of the workpiece. Simulation results showed that SDM provides a unique advantage of decreased shear plane angle which eases the shearing action. This in turn causes an increased value of average coefficient of friction in contrast to the isothermal cutting (carried at 1200 K) and normal cutting (carried at 300K). The increase of friction coefficient however was found to aid the cutting action of the tool due to an intermittent dropping in the cutting forces, lowering stresses on the cutting tool and reducing operational temperature. Analysis shows that the introduction of surface defects prior to conventional machining can be a viable choice for machining a wide range of ceramics, hard steels and composites compared to hot machining.

Enabling ultra high precision on hard steels using surface defect machining

This paper is an extension to an idea coined during the 13th EUSPEN Conference (P6.23) named "surface defect machining" (SDM). The objective of this work was to demonstrate how a conventional CNC turret lathe can be used to obtain ultra high precision machined surface finish on hard steels without recourse to a sophisticated ultra precision machine tool. An AISI 4340 hard steel (69 HRC) workpiece was machined using a CBN cutting tool with and without SDM. Post-machining measurements by a Form Talysurf and a Scanning Electron Microscope (FEI Quanta 3D) revealed that SDM culminates to several key advantages (i) provides better quality of the machined surface integrity and offers (ii) lowering feed rate to 5μm/rev to obtain a machined surface roughness of 30 nm (optical quality).

Advances in the surface defect machining (SDM) of hard steels

This paper reports the realisation of precision surface finish (Ra 30 nm) on AISI 4340 steel using a conventional turret lathe by adapting and incorporating a surface defect machining (SDM) method [Wear, 302, 2013 (1124-1135)]. Conventional ways of machining materials are limited by the use of a critical feed rate, experimentally determined as 0.02 mm/rev, beyond which no appreciable improvement in the machined quality of the surface is obtained. However, in this research, the novel application of an SDM method was used to overcome this minimum feed rate limitation ultimately reducing it to 0.005 mm/rev and attaining an average machined surface roughness of 30 nm. From an application point of view, such a smooth finish is well within the values recommended in the ASTM standards for total knee joint prosthesis. Further analysis was done using SEM imaging, white light interferometry and numerical simulations to verify that adapting SDM method provides improved surface integrity by reducing the extent of side flow, microchips and weldments during the hard turning process.

Machine vision system for automatic inspection of surface defects in aluminum die casting

A camera based machine vision system for the automatic inspection of surface defects in aluminum die casting is presented. The system uses a hybrid image processing algorithm based on mathematic morphology to detect defects with different sizes and shapes. The defect inspection algorithm consists of two parts. One is a parameter learning algorithm, in which a genetic algorithm is used to extract optimal structuring element parameters, and segmentation and noise removal thresholds. The second part is a defect detection algorithm, in which the parameters obtained by a genetic algorithm are used for morphological operations. The machine vision system has been applied in an industrial setting to detect two types of casting defects: parts mix-up and any defects on the surface of castings. The system performs with a 99% or higher accuracy for both part mix-up and defect detection and is currently used in industry as part of normal production.