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Institution

Indian Institute of Technology Guwahati

EducationGuwahati, Assam, India
About: Indian Institute of Technology Guwahati is a education organization based out in Guwahati, Assam, India. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 6933 authors who have published 17102 publications receiving 257351 citations.


Papers
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Journal ArticleDOI
TL;DR: A more viable method to solve the design of rolling element bearings using genetic algorithms (GAs) is presented, which weakens the chances of getting trapped in local maxima or minima.
Abstract: The design of rolling element bearings has been a challenging task in the field of mechanical engineering. While most of the real aspects of the design are never disclosed by bearing manufacturers, the common engineer is left with no other alternative than to refer to standard tables and charts containing the bearing performance characteristics. This paper presents a more viable method to solve this problem using genetic algorithms (GAs). Since the algorithm is basically a guided random search, it weakens the chances of getting trapped in local maxima or minima. The method used has yielded improved performance parameters than those catalogued in standard tables. *Indraneel Chakraborty is currently with Massachusetts Institute of Technology and can be reached at indranil@mit.edu †Vinay Kumar is currently with Mindtree Consulting, India and can be reached at vinayk@mindtree.com

71 citations

Journal ArticleDOI
TL;DR: In this article, the authors have discussed various nanoporous heterogeneous catalysts investigated for biodiesel production and mainly focused on the mechanism involved in transesterification using heterogenous catalysts.

71 citations

Journal ArticleDOI
TL;DR: In this article, a neural network model was trained and tested for predicting the flow stress by taking data available in the literature for 99.99% pure aluminum, which was found that the trained neural network could predict flow stress for unseen data quite reliably.

71 citations

Journal ArticleDOI
TL;DR: The results hint toward an epitaxial growth of aligned ZnO NRs on graphene by a vapor-liquid-solid mechanism and establish the importance of defect engineering in graphene for controlled fabrication of graphene-semiconductor NW hybrids with improved optoelectronic functionalities.
Abstract: We demonstrate graphene-assisted controlled fabrication of various ZnO 1D nanostructures on the SiO2/graphene substrate at a low temperature (540 °C) and elucidate the growth mechanism. Monolayer and a few layer graphene prepared by chemical vapor deposition (CVD) and subsequently coated with a thin Au layer followed by rapid thermal annealing is shown to result in highly aligned wurtzite ZnO nanorods (NRs) with clear hexagonal facets. On the other hand, direct growth on CVD graphene without a Au catalyst layer resulted in a randomly oriented growth of dense ZnO nanoribbons (NRBs). The role of in-plane defects and preferential clustering of Au atoms on the defect sites of graphene on the growth of highly aligned ZnO NRs/nanowires (NWs) on graphene was established from micro-Raman and high-resolution transmission electron microscopy analyses. Further, we demonstrate strong UV and visible photoluminescence (PL) from the as-grown and post-growth annealed ZnO NRs, NWs, and NRBs, and the origin of the PL emiss...

71 citations

Journal ArticleDOI
TL;DR: Current findings strongly indicate that the employment of 3,5-dinitrosalicylic acid assay for quantifying the reducing sugars in the presence of furans is not appropriate.

71 citations


Authors

Showing all 7128 results

NameH-indexPapersCitations
Jasvinder A. Singh1762382223370
Dipanwita Dutta1431651103866
Sanjay Gupta9990235039
Santosh Kumar80119629391
Subrata Ghosh7884132147
Rishi Raj7856922423
B. Bhuyan7365821275
Ravi Shankar6667219326
Ashutosh Sharma6657016100
Gautam Biswas6372116146
Sam P. de Visser6225613820
Surendra Nadh Somala6114428273
Manish Kumar61142521762
Mihir Kumar Purkait572679812
Ajaikumar B. Kunnumakkara5720120025
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023118
2022365
20212,032
20201,947
20191,866
20181,647