Institution
Indian Institute of Technology Guwahati
Education•Guwahati, 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: Adsorption & Catalysis. The organization has 6933 authors who have published 17102 publications receiving 257351 citations.
Topics: Adsorption, Catalysis, Heat transfer, Finite element method, Membrane
Papers published on a yearly basis
Papers
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TL;DR: The yeast Candida bombicola produces biosurfactant with properties akin to those of sophorolipid (SL) group of compounds when grown on a cheap fermentative medium containing sugarcane molasses, yeast extract, urea, and soybean oil.
Abstract: The yeast Candida bombicola produces biosurfactant with properties akin to those of sophorolipid (SL) group of compounds. In the present work, the yeast was shown to produce 63.7 g l−1 SL when grown on a cheap fermentative medium containing sugarcane molasses, yeast extract, urea, and soybean oil. The partially purified SL was characterized and confirmed by Fourier-transform infrared (FT-IR) spectroscopy, 1H and 13C nuclear magnetic resonance (NMR) and liquid chromatography–mass spectroscopy (LC-MS) analysis. The critical micelle concentration (CMC) and minimum surface tension of the produced SL in aqueous solution were found to be 59.43 mg l−1 and 34.15 m Nm−1, respectively. The emulsification activity and stability with kerosene oil and organic solvents viz. xylene, benzene, and hexadecane were also tested using the produced SL, which yielded better results compared to those reported in the literature.
132 citations
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TL;DR: In this article, a stream function-velocity formulation of the two-dimensional steady-state Navier-Stokes equations representing incompressible fluid flows in 2D domains is proposed.
132 citations
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TL;DR: A knowledge-based system is developed for the prediction of surface roughness in turning process using neural networks and fuzzy set theory, which helps the user in understanding the behavior of the cutting process and to assess the effectiveness of the model.
Abstract: In the present work, a knowledge-based system is developed for the prediction of surface roughness in turning process. Neural networks and fuzzy set theory are used for this purpose. Knowledge acquired from the shop floor is used to train the neural network. The trained network provides a number of data sets, which are fed to a fuzzy-set-based rule generation module. A large number of IF–THEN rules are generated, which can be reduced to a smaller set of rules by using Boolean operations. The developed rule base may be used for predicting surface roughness for given process variables as well as for the prediction of process variables for a given surface roughness. The concise set of rules helps the user in understanding the behavior of the cutting process and to assess the effectiveness of the model. The performance of the developed knowledge-based system is studied with the experimental data of dry and wet turning of mild steel with HSS and carbide tools.
132 citations
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TL;DR: In this paper, green synthesis of metallic nanoparticles (NPs) using rosemary (Rosmarinus officinalis Linn.) leaf extract was confirmed by some thoughtful techniques like as UV-visible, FT-IR, SEM & TEM, and XRD.
132 citations
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TL;DR: In this article, the authors report the results of a study of the exclusive semileptonic decays in a hadronic decay model, where the events are tagged by fully reconstructing a second $B$ meson in the event.
Abstract: We report the results of a study of the exclusive semileptonic decays ${B}^{\ensuremath{-}}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{0}{\ensuremath{\ell}}^{\ensuremath{-}}{\overline{\ensuremath{
u}}}_{\ensuremath{\ell}}$, ${\overline{B}}^{0}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{+}{\ensuremath{\ell}}^{\ensuremath{-}}{\overline{\ensuremath{
u}}}_{\ensuremath{\ell}}$, ${B}^{\ensuremath{-}}\ensuremath{\rightarrow}{\ensuremath{\rho}}^{0}{\ensuremath{\ell}}^{\ensuremath{-}}{\overline{\ensuremath{
u}}}_{\ensuremath{\ell}}$, ${\overline{B}}^{0}\ensuremath{\rightarrow}{\ensuremath{\rho}}^{+}{\ensuremath{\ell}}^{\ensuremath{-}}{\overline{\ensuremath{
u}}}_{\ensuremath{\ell}}$ and ${B}^{\ensuremath{-}}\ensuremath{\rightarrow}\ensuremath{\omega}{\ensuremath{\ell}}^{\ensuremath{-}}{\overline{\ensuremath{
u}}}_{\ensuremath{\ell}}$, where $\ensuremath{\ell}$ represents an electron or a muon. The events are tagged by fully reconstructing a second $B$ meson in the event in a hadronic decay mode. The measured branching fractions are $\mathcal{B}({B}^{\ensuremath{-}}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{0}{\ensuremath{\ell}}^{\ensuremath{-}}{\overline{\ensuremath{
u}}}_{\ensuremath{\ell}})=(0.80\ifmmode\pm\else\textpm\fi{}0.08\ifmmode\pm\else\textpm\fi{}0.04)\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}4}$, $\mathcal{B}({\overline{B}}^{0}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{+}{\ensuremath{\ell}}^{\ensuremath{-}}{\overline{\ensuremath{
u}}}_{\ensuremath{\ell}})=(1.49\ifmmode\pm\else\textpm\fi{}0.09\ifmmode\pm\else\textpm\fi{}0.07)\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}4}$, $\mathcal{B}({B}^{\ensuremath{-}}\ensuremath{\rightarrow}{\ensuremath{\rho}}^{0}{\ensuremath{\ell}}^{\ensuremath{-}}{\overline{\ensuremath{
u}}}_{\ensuremath{\ell}})=(1.83\ifmmode\pm\else\textpm\fi{}0.10\ifmmode\pm\else\textpm\fi{}0.10)\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}4}$, $\mathcal{B}({\overline{B}}^{0}\ensuremath{\rightarrow}{\ensuremath{\rho}}^{+}{\ensuremath{\ell}}^{\ensuremath{-}}{\overline{\ensuremath{
u}}}_{\ensuremath{\ell}})=(3.22\ifmmode\pm\else\textpm\fi{}0.27\ifmmode\pm\else\textpm\fi{}0.24)\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}4}$, and $\mathcal{B}({B}^{\ensuremath{-}}\ensuremath{\rightarrow}\ensuremath{\omega}{\ensuremath{\ell}}^{\ensuremath{-}}{\overline{\ensuremath{
u}}}_{\ensuremath{\ell}})=(1.07\ifmmode\pm\else\textpm\fi{}0.16\ifmmode\pm\else\textpm\fi{}0.07)\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}4}$, where the first error is statistical and the second one is systematic. The obtained branching fractions are inclusive of soft photon emission. We also determine the branching fractions as a function of the 4-momentum transfer squared to the leptonic system ${q}^{2}=({p}_{\ensuremath{\ell}}+{p}_{\ensuremath{
u}}{)}^{2}$, where ${p}_{\ensuremath{\ell}}$ and ${p}_{\ensuremath{
u}}$ are the lepton and neutrino 4-momenta, respectively. Using the pion modes, a recent light cone sum rule calculation, lattice QCD results and a model-independent description of the hadronic form factor, a value of the Cabibbo-Kobayashi-Maskawa matrix element $|{V}_{ub}|=(3.52\ifmmode\pm\else\textpm\fi{}0.29)\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}3}$ is extracted. A structure in the two-pion invariant mass distribution near $1.3\text{ }\text{ }\mathrm{GeV}/{c}^{2}$, which might be dominated by the decay ${B}^{\ensuremath{-}}\ensuremath{\rightarrow}{f}_{2}(1270){\ensuremath{\ell}}^{\ensuremath{-}}{\overline{\ensuremath{
u}}}_{\ensuremath{\ell}}$, ${f}_{2}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}$, is seen. These results are obtained from a $711\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$ data sample that contains $772\ifmmode\times\else\texttimes\fi{}{10}^{6}$ $B\overline{B}$ pairs, collected near the $\ensuremath{\Upsilon}(4S)$ resonance with the Belle detector at the KEKB asymmetric-energy ${e}^{+}{e}^{\ensuremath{-}}$ collider.
132 citations
Authors
Showing all 7128 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jasvinder A. Singh | 176 | 2382 | 223370 |
Dipanwita Dutta | 143 | 1651 | 103866 |
Sanjay Gupta | 99 | 902 | 35039 |
Santosh Kumar | 80 | 1196 | 29391 |
Subrata Ghosh | 78 | 841 | 32147 |
Rishi Raj | 78 | 569 | 22423 |
B. Bhuyan | 73 | 658 | 21275 |
Ravi Shankar | 66 | 672 | 19326 |
Ashutosh Sharma | 66 | 570 | 16100 |
Gautam Biswas | 63 | 721 | 16146 |
Sam P. de Visser | 62 | 256 | 13820 |
Surendra Nadh Somala | 61 | 144 | 28273 |
Manish Kumar | 61 | 1425 | 21762 |
Mihir Kumar Purkait | 57 | 267 | 9812 |
Ajaikumar B. Kunnumakkara | 57 | 201 | 20025 |