@article { ISI:000254672800002, title = {Modeling of a fluidized bed propylene polymerization reactor operated in condensed mode}, journal = {Journal of Applied Polymer Science}, volume = {108}, number = {4}, year = {2008}, month = {MAY}, pages = {2067-2076}, publisher = {JOHN WILEY \& SONS INC}, type = {Article}, address = {111 RIVER ST, HOBOKEN, NJ 07030 USA}, abstract = {

The gas-phase polymerization of propylene is one of the most widely accepted and commercially used processes for the manufacture of polypropylene (PP). Because of the highly exothermic nature of polymerization reactions, temperature runaway and subsequent polymer melting and agglomeration may occur, and the reactor has to be operated in a small operating window for safety. The addition of liquid monomer for heat removal (condensed mode) broadens the operating window and can substantially increase (by 50-100\%) the capacity of given reactor hardware. This article describes the extension of a comprehensive mathematical model for the simulation of fluidized bed PP reactors to include the condensed mode of operations. The model is used to determine the influence of the operating parameters on the polymer properties and particle size distribution. The model is also used to determine the effects of two active sites and the reaction kinetics on macroscopic variables. The developed framework is useful for simulating multimonomer, multisite Ziegler-Natta-type olefin fluidized bed polymerization reactors operated under condensed mode. (C) 2008 Wiley Periodicals, Inc. J Appl Polym Sci 108: 2067-2076, 2008.

}, keywords = {Modeling, Polyolefins, Ziegler-Natta polymerization}, issn = {0021-8995}, doi = {10.1002/app.27748}, author = {Utikar, Ranjeet P. and Harshe, Yogesh M. and Mehra, Anurag and Ranade, Vivek V.} } @article { ISI:000257228100019, title = {Optimal xylanase production using Penicilium janthinellum NCIM 1169: a model based approach}, journal = {Biochemical Engineering Journal}, volume = {40}, number = {2}, year = {2008}, month = {JUN}, pages = {348-356}, publisher = {ELSEVIER SCIENCE SA}, address = {PO BOX 564, 1001 LAUSANNE, SWITZERLAND}, abstract = {

Xylanases are an industrially important class of hydrolytic enzymes that degrade xylans. Production of xylanase from a fungal culture by submerged fermentation and optimization of the operating conditions for maximum activity are the two aims of the present study. Penicillium janthinellum NCIM 1169 with Mandels-Weber medium, sugarcane bagassse (40\#) as a carbon source and beef extract as a nitrogen source were used in the experiments. We did 41 experiments to see the effect of variations in carbon, nitrogen source, pH, and inoculum on xylanase activity. This data was then used to build an input/output model using multiple linear regression, back propagation neural network and lazy learning algorithm. It was found that lazy learning model correlated well in mapping input/output data. This model was then utilized as an objective function in genetic algorithm to find the optimal combination of the operating conditions to get the maximum xylanase activity. It was observed that with carbon source, 1.63\%, nitrogen source, 0.16\%, pH, 4.1, and inoculum, 5.5\%, maximum xylanase activity of 28.98 +/- 1.73 U/ml was achieved. (C) 2008 Elsevier B.V. All rights reserved.

}, keywords = {Artificial intelligence, Enzyme activity, Fermentation, Modeling, Optimization, Xylanase}, issn = {1369-703X}, doi = {10.1016/j.bej.2008.01.003}, author = {Meshram, Mukesh and Kulkarni, Abhijit and Jayaraman, Valadi K. and Kulkarni, B. D. and Lele, S. S.} } @article { ISI:000283759400011, title = {Polyethersulfone-expanded graphite nanocomposites: charge transport and impedance characteristics}, journal = {Composites Science and Technology}, volume = {70}, number = {14}, year = {2010}, month = {NOV0}, pages = {2111-2116}, publisher = {ELSEVIER SCI LTD}, address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}, abstract = {

Polyethersulfone (PES)-expanded graphite nanocomposites have been prepared by solution blending route after sonicating expanded graphite in dichloromethane. It has been observed that ultrasonication results in nanosheets formation leading to a low percolation threshold of 3 wt.\%. At 5 wt.\% filler loading the conductivity is of the order of 10(-2) S/cm. Hopping type of charge transport occurs at 3.2 wt.\% expanded graphite in PES below which capacitive effects couple. The effective dielectric constant at low frequency increases with filler concentration. Impedance measurement has been carried out to evaluate interfacial capacitance which, for 3.2 wt.\% expanded graphite addition in PES, increases to 110 pF from 32 pF for 1 wt.\% expanded graphite in the polymer. DSC analysis shows an increment of 12 C in the T(g) of PES with 3 wt.\% expanded graphite suggesting interaction between the polymer and filler. (C) 2010 Elsevier Ltd. All rights reserved.

}, keywords = {Differential scanning calorimetry (DSC), Electrical properties, Modeling, Polymers, Scanning/transmission electron microscopy (STEM)}, issn = {0266-3538}, doi = {10.1016/j.compscitech.2010.08.008}, author = {Ramanujam, B. T. S. and Mahale, Rajashree Y. and Radhakrishnan, S.} } @article { ISI:000340517700011, title = {Photopolymerization kinetics of block polyether based terminal urethane methacrylate with/without cross-linker}, journal = {Advances in Polymer Technology}, volume = {33}, number = {3}, year = {2014}, month = {FEB}, pages = {21418}, publisher = {WILEY-BLACKWELL}, address = {111 RIVER ST, HOBOKEN 07030-5774, NJ USA}, abstract = {

The present work deals with the photopolymerization of difunctional macromonomer with a polyether chain and urethane methacrylate terminations. Macromonomeric formulations were prepared by mixing macromonomer with two different concentrations of photoinitiator. Formulations were also prepared by the addition of 10 wt\% of soft-segmented difunctional cross-linker to the abovementioned macromonomic formulations. All formulations were then subjected to photopolymerization studies and the effects of light intensity on the photopolymerization kinetics were studied at two different isothermal conditions using photo differential scanning calorimetry (Photo DSC) with polychromatic radiation. The isothermal heat flow against time was recorded for all formulations and the kinetic parameters were noted. It was observed that the rate of maximum polymerization as well as peak maximum time showed a general trend. However, the ultimate conversion as well as the conversion at maximum rate did not show any trend due to diffusional restrictions imparted by the increase in viscosity with conversion. The photopolymerization of the formulations and curing kinetics including evaluation of autocatalytic model are discussed. (C) 2014 Wiley Periodicals, Inc.

}, keywords = {kinetics, Macromonomers, Modeling, Photo DSC, Photopolymerization}, issn = {0730-6679}, doi = {10.1002/adv.21418}, author = {Reghunathan, Harikrishna} } @article { ISI:000334141800011, title = {Soft-sensor development for biochemical systems using genetic programming}, journal = {Biochemical Engineering Journal}, volume = {85}, year = {2014}, month = {APR}, pages = {89-100}, publisher = {ELSEVIER SCIENCE BV}, address = {PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}, abstract = {

Soft-sensors are software based process monitoring systems/models. In real-time they estimate those process variables, which are difficult to measure online or whose measurement by analytical procedures is tedious and time-consuming. In this study, the genetic programming (GP), an artificial intelligence based data-driven modeling formalism, has been introduced for the development of soft-sensors for biochemical processes. The novelty of the GP is that given example input-output data, it searches and optimizes both the form (structure) and parameters of an appropriate linear/nonlinear data-fitting model. In this study, GP-based soft-sensors have been developed for two bioprocesses, namely extracellular production of lipase enzyme and bacterial production of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) copolymer. While in case study-I, the soft-sensor predicts the time-dependent lipase activity (U/ml), in case study-II it predicts the amount of accumulated polyhydroxyalkanoates (\% dcw). The prediction and generalization performance of the GP-based soft-sensors was compared with the corresponding multi-layer perceptron (MLP) neural network and support vector regression (SVR) based soft-sensors. This comparison indicates that in the first case study the GP-based soft-sensor with the training and test set correlation coefficient (root-mean-squared-error) magnitudes of \>0.96 (approximate to 0.962 U/ml) has clearly outperformed the two other soft-sensors. In case study-II involving bacterial copolymer production, the GP and SVR based soft-sensors have performed equally well (correlation coefficient approximate to 0.98) while the MLP based soft-sensor{\textquoteright}s performance was relatively inferior (correlation coefficient approximate to 0.94). (C) 2014 Elsevier B.V. All rights reserved.

}, keywords = {Artificial intelligence, Batch processing, Bioprocess monitoring, Lipase, Modeling, sensors}, issn = {1369-703X}, doi = {10.1016/j.bej.2014.02.007}, author = {Sharma, Suraj and Tambe, Sanjeev S.} } @article {46188, title = {Web-gLV: a web based platform for lotka-volterra based modeling and simulation of microbial populations}, journal = {Frontiers in Microbiology}, volume = {10}, year = {2019}, month = {FEB }, pages = {288}, type = {Article}, abstract = {

The affordability of high throughput DNA sequencing has allowed us to explore the dynamics of microbial populations in various ecosystems. Mathematical modeling and simulation of such microbiome time series data can help in getting better understanding of bacterial communities. In this paper; we present Web-gLV- a GUI based interactive platform for generalized Lotka-Volterra (gLV) based modeling and simulation of microbial populations. The tool can be used to generate the mathematical models with automatic estimation of parameters and use them to predict future trajectories using numerical simulations. We also demonstrate the utility of our tool on few publicly available datasets. The case studies demonstrate the ease with which the current tool can be used by biologists to model bacterial populations and simulate their dynamics to get biological insights. We expect Web-gLV to be a valuable contribution in the field of ecological modeling and metagenomic systems biology.

}, keywords = {lotka-volterra, microbial population, Microbiome, Modeling, numerical-simulation, time-series, visualization, web-server}, issn = {1664-302X}, doi = {10.3389/fmicb.2019.00288}, author = {Kuntal, Bhusan K. and Gadgil, Chetan and Mande, Sharmila S.} } @article {47112, title = {Web-gLV: a web based platform for lotka-volterra based modeling and simulation of microbial populations (vol 10, 288, 2019)}, journal = {Frontiers in Microbiology}, volume = {11}, year = {2021}, month = {JAN }, pages = {605308}, type = {Correction}, keywords = {lotka-volterra, microbial population, Microbiome, Modeling, numerical-simulation, time-series, visualization, web-server}, issn = {1664-302X}, doi = {10.3389/fmicb.2020.605308}, author = {Kuntal, Bhusan K. and Gadgil, Chetan and Mande, Sharmila S.} }