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T

T. Swaminathan

Researcher at Indian Institute of Technology Madras

Publications -  29
Citations -  1512

T. Swaminathan is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Response surface methodology & Adsorption. The author has an hindex of 18, co-authored 29 publications receiving 1402 citations. Previous affiliations of T. Swaminathan include Indian Institutes of Technology.

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Optimization of batch process parameters using response surface methodology for dye removal by a novel adsorbent

TL;DR: In this paper, a hybrid adsorbent that was prepared by pyrolysing a mixture of carbon and fly ash in 1:1 ratio was successfully employed for experimental design and analysis.
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Response surface modeling and optimization to elucidate and analyze the effects of inoculum age and size on surfactin production

TL;DR: In this article, a computer aided response surface modeling, optimization and analysis of the age and size of the two-stage inocula was carried out in batch reactor studies and the optimal values were obtained including primary inoculum age and density = 56h and 5.5h, respectively.
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Application of response-surface methodology to evaluate the optimum environmental conditions for the enhanced production of surfactin

TL;DR: In this paper, the effect of fermentation process conditions, namely pH, temperature, rates of agitation and aeration, on surfactin production was extensively studied to optimize the process conditions for the maximum production of surfactins.
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Effect of DO concentration on biofilm structure and membrane filterability in submerged membrane bioreactor.

TL;DR: Different in biofilm characteristics as a result of different DO level was main factor affecting biofouling for both MBRs, and reduced porosity of LDO biofilm resulted in lower filterability than the HDO.
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Characterization of concentration and purification parameters and operating conditions for the small-scale recovery of surfactin

TL;DR: An understanding of ultrafiltration characteristics and operating conditions from the analyses of the present study constitutes a very important milestone for process optimization and scale-up.