Study of nano-crystalline silicon deposited by VHF-PE CVD for solar cell devices

Nanocrystalline Silicon (nc-Si: H) is an important material for photovoltaic energy conversion devices and for thin film transistors. The material consists of small grains of Si, of the order of 10-20 rim, with a significant amorphous phase and bonded Hydrogen (H) interspersed between the grains which through passivation leads to good electronic transport in the device;In this work, a systematic study is carried out of midgap defect densities and minority carrier diffusion lengths in Nanocrystalline p+nn+ devices by changing the doping and defect densities with different techniques. The devices and films were deposited in a VHF diode plasma discharge with varying deposition parameters. Defect densities were measured and the energetic location of the traps was found to be ~0.5 to 0.35 eV below the conduction band. A surprising finding was that there was a 1:1 correlation between the deep defect states which were responsible for carrier capture, and the donor density. The diffusion length and its excellent correlation with the deep defect density, verified SRH recombination model;Excellent hole and electron mobilities from n+nn + devices using SCLC technique were obtained (some measurements by other students) with good lifetimes from reverse recovery technique. Linear relationship between hole lifetimes against the inverse of the defect densities measured showed approximate linear correlation, thus verifying the SRH recombination model for very first time;Also Dark I-V current studies were done and their relationship with crystallinity was studied, backed by QE measurements. Two techniques of graded TMB and H 2 were used to improve hole transport in these devices. A final device innovation was the use of a thin a-Si: H buffer layer at n-p+ interface which significantly improved the Voc, presumably by reducing the recombination at the interface states;Thus, important fundamental material properties, electron and hole mobility, defect density, minority carrier lifetime and minority carrier diffusion length, capture coefficients were all measured in the same or very similar samples. This is the first time ever that such systematic measurements have been made in this material system

Literary review on etiopathology and principal management of Udarda

In Ayurveda, Udarda has been described along with treatment in classical texts for benefit of human kind. The description of Udarda along with treatment as single chapter is not found in Charak and Sushruta Samhita. The details of Udarda as a separate chapter are given Madhavnidana, Chakradutta and various other texts. Udarda has Kapha dominance and can be treated with various Kapha Shamak Yoga given by Acharyas

Modeling Bottom-Up Visual Attention Using Dihedral Group D4

Published version. Source at http://dx.doi.org/10.3390/sym8080079 In this paper, first, we briefly describe the dihedral group D4 that serves as the basis for calculating saliency in our proposed model. Second, our saliency model makes two major changes in a latest state-of-the-art model known as group-based asymmetry. First, based on the properties of the dihedral group D4, we simplify the asymmetry calculations associated with the measurement of saliency. This results is an algorithm that reduces the number of calculations by at least half that makes it the fastest among the six best algorithms used in this research article. Second, in order to maximize the information across different chromatic and multi-resolution features, the color image space is de-correlated. We evaluate our algorithm against 10 state-of-the-art saliency models. Our results show that by using optimal parameters for a given dataset, our proposed model can outperform the best saliency algorithm in the literature. However, as the differences among the (few) best saliency models are small, we would like to suggest that our proposed model is among the best and the fastest among the best. Finally, as a part of future work, we suggest that our proposed approach on saliency can be extended to include three-dimensional image data