Photopolymerizable liquid encapsulants for microelectronic devices: Thermal and mechanical properties of systems with reduced in‐mold cure times

Photopolymerizable liquid encapsulants (PLEs) for microelectronic devices may offer important advantages over traditional transfer molding compounds, including reduced in‐mold cure times, lower thermal stresses, and reduced wire sweep. In this contribution, we discuss an encapsulation process based upon a low viscosity resin that cures rapidly upon exposure to UV light. These highly filled PLEs are comprised of an epoxy novolac‐based vinyl ester resin (～25 wt %), fused silica filler (70–74 wt %), photoinitiator, silane coupling agent, and, in some cases, a thermal initiator. We have characterized the material properties (flexural strength and modulus, coefficient of thermal expansion, glass transition temperature, and thermal stress parameter) of PLEs cured with UV illumination times of 60, 90, and 120 s, as well as, the thermal conductivity and adhesive peel strength of PLEs photocured for 90 s. In addition, we investigated the effect of the fused silica loading and the initiation scheme on these properties. The results indicate that the PLEs are very promising for microelectronic encapsulation. These liquid encapsulants cure (to an ejectable hardness) in 1 min for an initiating light intensity of 200 mW/cm², and exhibit appropriate values for the thermal and mechanical properties listed above. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 81: 3449–3461, 2001     

Magnetic resonance image denoising using nonlocal maximum likelihood paradigm in DCT‐framework

The data acquired by magnetic resonance (MR) imaging system are inherently degraded by noise that has its origin in the thermal Brownian motion of electrons. Denoising can enhance the quality (by improving the SNR) of the acquired MR image, which is important for both visual analysis and other post processing operations. Recent works on maximum likelihood (ML) based denoising shows that ML methods are very effective in denoising MR images and has an edge over the other state‐of‐the‐art methods for MRI denoising. Among the ML based approaches, the Nonlocal maximum likelihood (NLML) method is commonly used. In the conventional NLML method, the samples for the ML estimation of the unknown true pixel are chosen in a nonlocal fashion based on the intensity similarity of the pixel neighborhoods. Euclidean distance is generally used to measure this similarity. It has been recently shown that computing similarity measure is more robust in discrete cosine transform (DCT) subspace, compared with Euclidean image subspace. Motivated by this observation, we integrated DCT into NLML to produce an improved MRI filtration process. Other than improving the SNR, the time complexity of the conventional NLML can also be significantly reduced through the proposed approach. On synthetic MR brain image, an average improvement of 5% in PSNR and 86%reduction in execution time is achieved with a search window size of 91 × 91 after incorporating the improvements in the existing NLML method. On an experimental kiwi fruit image an improvement of 10% in PSNR is achieved. We did experiments on both simulated and real data sets to validate and to demonstrate the effectiveness of the proposed method. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 256–264, 2015     

Combined permeable pavement and photocatalytic titanium dioxide oxidation system for urban run‐off treatment and disinfection

Permeable pavement systems (PPS) are frequently associated with high removal efficiencies for water quality parameters. Their effluent can, therefore, be recycled, for example, for sprinkling onto gardens. Nevertheless, some stakeholders fear that potentially pathogenic organisms within the treated run‐off could be too high, and therefore they request disinfection before recycling. The aim of this paper is, therefore, to assess the efficiency of a batch flow combined titanium dioxide (TiO₂) and ultraviolet (UV) light photocatalytic reactor in removing water‐borne microbial contaminants from the effluent of PPS. Combined TiO₂ and UV photocatalytic reaction times between 80 and 100 min were required for the complete removal of Escherichia coli, total coliforms and faecal Streptococci, which had mean initial counts of 1.5 × 10⁷, 4.4 × 10⁶ and 6.9 × 10⁵ colony‐forming units (CFU) per 100 mL, respectively. In comparison, UV disinfection alone resulted in insignificant microbial removal. Suspended TiO₂ powder was more effective than small immobilised TiO₂ crystals.     

The Change of X‐ray Diffraction Peak Width During in situ Conventional Sintering of Nanoscale Powders

Diffraction peaks of nanoscale particles of 3 mol% yttria‐stabilized zirconia become sharper as the powder sinters. The reduction in the peak width is correlated with the increase in density. The sharpening of the peak agrees reasonably well with the remaining free surface area as the sample sinters. Therefore, high curvature of the free surface of the pores is assumed to lead to peak broadening (the grain boundaries that grow at the expense of the free surfaces of the pores do not have this curvature). The change in the grain size during sintering does not make a significant contribution to peak width.     

An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach

Melanoma is the deadliest type of skin cancer with highest mortality rate. However, the annihilation in early stage implies a high survival rate therefore, it demands early diagnosis. The accustomed diagnosis methods are costly and cumbersome due to the involvement of experienced experts as well as the requirements for highly equipped environment. The recent advancements in computerized solutions for these diagnoses are highly promising with improved accuracy and efficiency. In this article, we proposed a method for the classification of melanoma and benign skin lesions. Our approach integrates preprocessing, lesion segmentation, features extraction, features selection, and classification. Preprocessing is executed in the context of hair removal by DullRazor, whereas lesion texture and color information are utilized to enhance the lesion contrast. In lesion segmentation, a hybrid technique has been implemented and results are fused using additive law of probability. Serial based method is applied subsequently that extracts and fuses the traits such as color, texture, and HOG (shape). The fused features are selected afterwards by implementing a novel Boltzman Entropy method. Finally, the selected features are classified by Support Vector Machine. The proposed method is evaluated on publically available data set PH2. Our approach has provided promising results of sensitivity 97.7%, specificity 96.7%, accuracy 97.5%, and F‐score 97.5%, which are significantly better than the results of existing methods available on the same data set. The proposed method detects and classifies melanoma significantly good as compared to existing methods.     

Production of aromatics by catalytic fast pyrolysis of cellulose in a bubbling fluidized bed reactor

Catalytic fast pyrolysis of cellulose was studied at 500°C using a ZSM‐5 catalyst in a bubbling fluidized bed reactor constructed from a 4.92‐cm ID pipe. Inert gas was fed from below through the distributor plate and from above through a vertical feed tube along with cellulose. Flowing 34% of the total fluidization gas through the feed tube led to the optimal mixing of the pyrolysis vapors into the catalyst bed, which experimentally corresponded to 29.5% carbon aromatic yield. Aromatic yield reached a maximum of 31.6% carbon with increasing gas residence time by changing the catalyst bed height. Increasing the hole‐spacing in the distributor plate was shown to have negligible effect on average bubble diameter and hence did not change the product distribution. Aromatic yields of up to 39.5% carbon were obtained when all studied parameters were optimized. © 2014 American Institute of Chemical Engineers AIChE J, 60: 1320–1335, 2014     

Conventional and Non-conventional Edible Oils: An Indian Perspective

The Indian dietary pattern has undergone major changes over the past 40 years. Many of these changes involve modification in dietary intake of fats and oils. In developing countries like India, vegetable oils are replacing animal fats because of the cost and health concerns. A wide range of vegetable oils are available in the market but the choice of healthy cooking oil has been a controversial subject since ideas keep on changing as new evidence accumulates. One of the factors holding back the increased use of value-added healthy oils in India is that most potential consumers are genuinely not aware of their health benefits. Edible oil consumption is primarily a community-driven phenomenon in India. The purpose of this paper is to highlight the current scenario of edible oils in India, their composition, health benefits, food applications, stability issues and future aspects as buying the right oil for health has become of great importance.     

Adsorption and penetration of hydrogen in W: A first principles study

In BCC crystals, such as Tungsten (W), slippage has been observed on the (1 1 0) and (1 1 2) planes. In this work, hydrogen diffusion paths from three different W surfaces ((1 0 0), (1 1 0) and (1 1 2)) have been calculated using first principles density functional theory. Equilibrium sites for H at the surfaces are identified. The energetics for H penetration from the surfaces to the solute site in the bulk is calculated. It is found that for our low surface coverage of H (3.4 × 10¹⁴ H/cm²), approximately 2 eV is required for an H atom to penetrate any of the W surfaces considered in this study.     

Identification and extraction of brain tumor from MRI using local statistics of Zernike moments

In this article, a novel method is proposed for the detection of brain tumor in magnetic resonance images (MRIs). The features of Zernike moments are used to analyze the MRIs. The image is divided into two parts from the center of the image based on the average value of the pixel located at the center boundary, and new image vectors are formed to extract the tumor. The local statistics values obtained from the low and high order Zernike moments are used to calculate the appropriate threshold value for efficient tumor extraction. The proposed method successfully analyzes the tumor part of the image on testing with different MRIs.     

A theoretical study of the performance of sub-micron MOSFET devices in the presence of edge potential

In the present communication we have presented a detailed theoretical analysis of the performance of the sub-micron device in the presence of the discontinuity at the Si–SiO₂ interface. It is assumed that due to interface discontinuity a potential develops at the edges (Source/Drain) in addition to the built-in-potential. This potential, called Edge Potential, measures directly the extent of the interface roughness. The effect of this potential is more critical in the case of short channel device where drain and source are in close proximity. Our analysis shows that the discontinuity is dominant at the edges but not in the channel. Drive current as well as saturation transconductance decreases in the presence of edge potential. These results suggest that the performance of the device degrades due to the interface roughness. Effect of interface roughness near the edges can be reduced at high gate voltage but it will result more interface roughness scattering.