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{userid:"ijtsrd", "refid":1706,"repocollections":"","attachment":"","_thumb":"","articletype":"article","sectionheading":"","title":"Synthesis and Characterisation of CDSE Nanoparticles by Chemical Precipitation Method\r\n","year":"2018","author":"A. Jesper Anandhi | R. Kanagadurai | A. Mercy | B. Milton Boaz\r\n","journal":"International Journal of Trend in Scientific Research and Development","volume":"2","number":"3","pages":"","month":"","doi":"","pubmed":"","pdflink":"http:\/\/www.ijtsrd.com\/papers\/ijtsrd12820.pdf","urllink":"http:\/\/www.ijtsrd.com\/physics\/nanotechnology\/12820\/synthesis-and-characterisation-of-cdse-nanoparticles-by-chemical-precipitation-method\/a-jesper-anandhi","abstract":"CdSe nanoparticles were synthesized using a simple chemical precipitation method at room temperature in different Cd:Se ratios. The nanoparticles were characterized using x-ray diffraction(XRD),high resolution scanning electron microscopy (HRSEM),energy dispersive X-ray analysis (EDAX). XRD pattern reveals that the nanoparticles are in well crystalline Hexagonal phase.The broadening of diffraction peaks indicated the formation of particles in the nanometer size regime.HRSEM images of Cdse nanoparticles of CdSe in different Cd:Se ratios shows different morphologies. The elemental analysis from EDAX shows that the prepared samples are exactly stoichiometric. A. Jesper Anandhi | R. Kanagadurai | A. Mercy | B. Milton Boaz\"Synthesis and Characterisation of CDSE Nanoparticles by Chemical Precipitation Method\" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http:\/\/www.ijtsrd.com\/papers\/ijtsrd12820.pdf  http:\/\/www.ijtsrd.com\/physics\/nanotechnology\/12820\/synthesis-and-characterisation-of-cdse-nanoparticles-by-chemical-precipitation-method\/a-jesper-anandhi\r\n","note":"","tags":"CdSe nanoparticles, x-ray diffraction, nanocrystals, sem image","weight":1706}
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{userid:"sridhar_hariharaputran", "refid":"6","attachment":"","articletype":"article","sectionheading":"","title":"BioSuite: A comprehensive bioinformatics software package (A unique industry\u2013academia collaboration)","year":"2007","author":"M. Vidyasagar, S, Mande, S. Rajgopal, B. Gopalkrishnan, S. T. P. T. Srinivas, C. Uma,Maheswara Rao, T. Kathiravan, K. Mastanarao, S. Narendranath, S.Rohini, A. Irshad, T. Murali, C. Subrahmanyam, T. Mona, S. Sankha,\r\nV. Priya, D. Suman, V. V. Raja Rao, P. Nageswara Rao, R. Issaac, H. Yashodeep, B. Arundhoti, G. Nishant, S Jignesh, K. S. Chaitanya, S. P.V. Prasad Reddy;  P. Chakraborty;  S. E. Hasnain, S. Mande, A. Nagarajaram, A. Ranjan, M. S. Acharya, M. Anwaruddin, S. K. Arun, Gyanrajkumar,D. Kumar, S. Priya, S. Ranjan, B. R. Reddi, J. Seshadri, P. SravanKumar, S. Swaminathan, P. Umadevi, V. Vindal, S. Vijaykrishnan; A. K. Saxena, A. Dixit, P. Prathipati,S. K. Kashaw;  C. Mandal, S.Bag; N. Balakrishnan, M. Bansal, N. R.Chandra, M. R. N. Murthy, S. Ramakumar, K. Sekar, N. Srinivasan,K. Suguna, S. Vishveshwara, R. Anandhi, Bhadra, S. Das, P. Hansia,S. Hariharaputran, J. Jeyakani, R. Karthikeyan, R. K. Pandey, C. S.Swamy, B. Vasanthakumar, P. V. Balaji, R. Y. Patel, B. Jayaram, S. A. Shaikh,P. P. Chakrabarti, A. Banerjee, A. Chakrabarti,R. L. Karandikar, P. Chaudhuri, G. P. S. Raghava, A. Ghosh,  M. Bansal, N. Paramsivam, S. K. Brahmachari, D.Dash, C. Balasubramaniam, A. Basu, P. Biswas, M. Hariharan, R.Mathur, K. S. Sandhu, V. Scaria, R. Shankar, P. J. Narayanan, V. Jain, Nirnimesh,  S. Krishnaswamy, V. Alaguraj, R. Marikkannu, A. V. S. K. Mohan Katta, N. Krishnan, K. V. Srividhya, P. J. Eswari,  P. V. Bharatam, P. Iqbal, D. Bhattacharyya, G. R. Desiraju, J. J. Kumar, M. Ravikumar;  M. Gautham, P. A. Prasad, D. Bharanidharan ","journal":"Current science","volume":" Vol. 92","number":" NO. 1, ","pages":"29 - 38","month":"Jan","doi":"","pubmed":"","pdflink":"","urllink":"http:\/\/www.ias.ac.in\/currsci\/jan102007\/29.pdf","abstract":"","note":"","tags":""}
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{userid:"satra", "articletype":"article","pages":"645-653","author":"Genevera I Allen, Nicola Amoroso, Catalina Anghel, Venkat Balagurusamy, Christopher J Bare, Derek Beaton, Roberto Bellotti, David A Bennett, Kevin L Boehme, Paul C Boutros, Laura Caberlotto, Cristian Caloian, Frederick Campbell, Elias Chaibub Neto, Yu-Chuan Chang, Beibei Chen, Chien-Yu Chen, Ting-Ying Chien, Tim Clark, Sudeshna Das, Christos Davatzikos, Jieyao Deng, Donna Dillenberger, Richard J B Dobson, Qilin Dong, Jimit Doshi, Denise Duma, Rosangela Errico, Guray Erus, Evan Everett, David W Fardo, Stephen H Friend, Holger Fr\u00f6hlich, Jessica Gan, Peter St George-Hyslop, Satrajit S Ghosh, Enrico Glaab, Robert C Green, Yuanfang Guan, Ming-Yi Hong, Chao Huang, Jinseub Hwang, Joseph Ibrahim, Paolo Inglese, Anandhi Iyappan, Qijia Jiang, Yuriko Katsumata, John S K Kauwe, Arno Klein, Dehan Kong, Roland Krause, Emilie Lalonde, Mario Lauria, Eunjee Lee, Xihui Lin, Zhandong Liu, Julie Livingstone, Benjamin A Logsdon, Simon Lovestone, Tsung-Wei Ma, Ashutosh Malhotra, Lara M Mangravite, Taylor J Maxwell, Emily Merrill, John Nagorski, Aishwarya Namasivayam, Manjari Narayan, Mufassra Naz, Stephen J Newhouse, Thea C Norman, Ramil N Nurtdinov, Yen-Jen Oyang, Yudi Pawitan, Shengwen Peng, Mette A Peters, Stephen R Piccolo, Paurush Praveen, Corrado Priami, Veronica Y Sabelnykova, Philipp Senger, Xia Shen, Andrew Simmons, Aristeidis Sotiras, Gustavo Stolovitzky, Sabina Tangaro, Andrea Tateo, Yi-An Tung, Nicholas J Tustison, Erdem Varol, George Vradenburg, Michael W Weiner, Guanghua Xiao, Lei Xie, Yang Xie, Jia Xu, Hojin Yang, Xiaowei Zhan, Yunyun Zhou, Fan Zhu, Hongtu Zhu, Shanfeng Zhu,  ","year":"2016","title":"Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease.","month":"Jun","journal":"Alzheimer's & dementia : the journal of the Alzheimer's Association","publisher":"","volume":"12","number":"6","note":"","tags":"","booktitle":"","editor":"","abstract":"Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.","address":"","school":"","issn":"1552-5279","doi":"10.1016\/j.jalz.2016.02.006","isi":"","pubmed":"27079753","key":"Allen2016","howpublished":"","urllink":"","refid":38,"weight":38}
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