IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Water Alternate Gas (WAG) injection methods are the derivative of gas injection methods, wherein water and gas are injected intermittently. WAG injection can lead to improved oil recovery by combining better mobility control and contacting upswept zones and by leading to improved microscopic displacement. Gas trapping in the reservoir after WAG process is an important parameter that affects the recovery of oil. Trapped gas refers to the immobile gas saturation remaining after the rock is flooded with oil or water. Trapped gas creates significant hysteresis effect (during drainage and imbibition) and reduces the relative permeability of water in the mixed wet or oil wet reservoirs. In this work, gas trapping phenomena is presented for different WAG methods for a Indian Brownfield, namely, single, five cycle WAG, tapered WAG, five cycle WAG with Hydrocarbon gas (HC) and CO 2 gas. Experiments are carried out on the recombined fluid in the core flooding apparatus at the reservoir conditions. The crude oil and gas is obtained from the separator at separator conditions and recombined at the reservoir conditions of 120°C and 230 kg/cm 2 at reservoir gas-oil ratio (GOR) to become representative of the reservoir fluid. The actual core sample is obtained from the field and is used for the study. The water and gas injection rate used for this study are 20 and 10 cc/hr, respectively, for all the experimental studies. Two types of gases are used for WAG method, namely, hydrocarbon gas (collected from the field and having about 90 % methane by composition in mole %) and CO 2 gas. The results on the saturation of phases and Land's trapping constant have been calculated for several cases of production life cycle and for different WAG methods.

Department Of Chemical Engineering

Society of Petroleum Engineers - International Petroleum Technology Conference 2012, IPTC 2012

Investigations on gas trapping phenomena for different EOR-water alternate gas injection methodologies

Semiclathrate hydrates of tetra-n-butyl ammonium bromide (TBAB) offer potential solution for gas storage, transportation, separation of flue gases and CO 2 sequestration. Models for phase equilibria for these systems have not yet been developed in open literatures and thus require urgent attention. In this work, the first attempt has been made to model phase equilibria of semiclathrate hydrates of CH 4, CO 2 and N 2 in aqueous solution of TBAB. A thermodynamic model for gas hydrate system as proposed by Chen and Guo has been extended for semiclathrate hydrates of gases in aqueous solution of TBAB. A correlation for the activity of water relating to the system temperature, concentration of TBAB in the system and the nature of guest gas molecule has been proposed. The model results have been validated against available experimental data on phase equilibria of semiclathrate hydrate systems of aqueous TBAB with different gases as guest molecule. The extended Chen and Guo's model is found to be suitable to explain the promotion effect of TBAB for the studied gaseous system such as, methane, carbon dioxide and nitrogen as a guest molecule. Additionally, a correlation for the increase in equilibrium formation temperature (hydrate promotion temperature, ΔT p) of semiclathrate hydrate system with respect to pure gas hydrate system has been developed and applied to semiclathrate hydrate of TBAB with several gases as guest molecules. The developed correlation is found to predict the promotion effect satisfactorily for the system studied. © 2012 CAS/DICP.

World University root node

GENERAL

Journal of Natural Gas Chemistry

Modeling phase equilibria of semiclathrate hydrates of CH 4, CO 2 and N 2 in aqueous solution of tetra-n-butyl ammonium bromide

The performance of biosensors, i.e. the sensitivity, specificity, linearity, reusability, chemical stability, and reproducibility is critically dependent on the biofunctionalization of the sensor platform. The type(s) of linkers used for the immobilization of the capture probes and the exact immobilization protocol play a vital role in the overall performance of sensors. A variety of linker molecules have been used to biofunctionalize technologically important substrates (glass, gold, mica etc.). Amongst the different linkers, researchers have paid more attention to two dimensional architectures, e.g.silanes, polyaniline (PANI), alkanethiols, poly-L-lysine (PLL), etc. Despite extensive research and a large number of reports, researchers still face problems related to limited loading efficiency, limited accessibility of the probes, poor control over uniform spacing among the probes and a loss of functionality due to irregular orientation of the probes, all of which cause variability in the responses. Three dimensional gel based matrices have proved to be a better choice, except for the fact that the leaching of entrapped probe molecules has limited their use in developing sensor platforms. Taking into account the limitations of the two dimensional linker arrays and three dimensional gel matrices, supramolecular dendritic architectures have shown immense potential in designing and developing the sensor platforms. Dendrimers are well-defined, monodispersed, globular macromolecules constructed around a core unit. Different properties of dendrimers, i.e. their structural uniformity, globular shape, monodispersity, the existence of dendritic crevices, high functional group density, hydrophilicity, versatility to design dendrimer of different composition and their nanometric size can be exploited while developing high sensitivity biosensors. Researchers have demonstrated that these hyperbranched 3D molecules show enhanced sensitivity, reduced nonspecific binding, greater accessibility of the probe for the target analyte, high stability and low variability in their response. Hence, designing a sensor with a dendrimer as a linker is a successful approach to obtain superior sensor performance and minimize the overall cost of a sensor. In this article, we discuss various aspects of dendrimers from the point of view of sensor design, hoping that this review will excite more researchers into exploiting the exceptional properties of dendrimers in biosensor development.

Department of Applied Mechanics

Fulltext

Dendrimers in biosensors: Concept and applications

This paper presents for the first time a full 32nm CMOS technology for high data rate and low operating power applications using a conventional high-k with single metal gate stack. High speed digital transistors are demonstrated 22% delay reduction for ring oscillator (RO) at same power versus previous SiON technology. Significant matching factor (AVT) improvement (Avt∼2.8mV.um) and low 1/f noise aligned with poly SiON are reported. Excellent Static Noise Margin (SNM) of 213mV has been achieved at low voltage for a high density 0.157um2 SRAM cell. Hierarchical BEOL based on Extreme Low k (ELK) dielectric (k∼2.4) is presented allowing high density wiring with low RC delay. Reliability criteria have been met for hot carrier injection (HCI), gate dielectric break-down (TDDB) and bias temperature instability (BTI) extracted at 125°C.

Department of Electrical Engineering

Department Of Physics

Technical Digest - International Electron Devices Meeting, IEDM

32nm general purpose bulk CMOS technology for high performance applications at low voltage

Dynamic viscoelastic moduli of an example polymerizing system namely the free radical bulk polymerization of methyl methacrylate (MMA), is studied using a Haake® rheometer-reactor assembly and an adapted Haake® HV-DIN cup-and-bob assembly. A series of experiments on the bulk polymerization of MMA under different temperature histories (isothermal, step-increase and step-decrease) and at two different initiator [2, 2′-azoisobutyronitrile (AIBN)] concentrations, have been carried out. The data on the storage modulus, G′, the loss modulus, G″, and the phase shift, δ, are measured during the course of polymerization, well into the gel effect region. A new correlation is developed for these properties. The kinetic model and the correlation for the zero-shear viscosity, presented in our earlier studies, are used in this generalized correlation. The correlation so developed is observed to represent experimental data quite well for a variety of temperature histories. The characteristic relaxation time, τi, representing the bulk polymerization of MMA is observed to be larger than the Rouse value, τR, by a factor of about seven. The findings are observed to be in agreement with several other studies for entangled non-polymerizing systems. © Springer-Verlag 2006.

Rheologica Acta

Dynamic viscoelastic properties of free radical bulk polymerizing systems under near-isothermal and non-isothermal conditions

An experimental study on the on-line optimizing control of a sample free radical bulk polymerization system, namely, methyl methacrylate (MMA), is carried out in a rheometer–reactor assembly. Two initiator loadings and three cases involving external disturbances (power failure) are studied. The disturbances are assumed to be of two kinds: one that leads to a sudden increase in the temperature of the reaction mass (cooling water pump failure) over the planned temperature history,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><mi is="true">T</mi><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>, and one leading to a sudden drop in the temperature (heater failure). The temperature and the viscosity,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><mi is="true">η</mi></math>, histories are used to describe the ‘state’ (conversion,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"><mi is="true">x</mi></mrow><mrow is="true"><mi is="true">m</mi></mrow></msub></math>, and weight-average molecular weight,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"><mi is="true">M</mi></mrow><mrow is="true"><mi is="true">w</mi></mrow></msub></math>) of the polymerizing mass. The polymerization is first carried out under an off-line computed optimal temperature history,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"><mi is="true">T</mi></mrow><mrow is="true"><mi is="true">op</mi></mrow></msub><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>, obtained using the adapted jumping gene version of the elitist genetic algorithm (GA-II-aJG). A planned disturbance is introduced after the start of polymerization and continues for a pre-specified duration. A new optimal temperature history,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"><mi is="true">T</mi></mrow><mrow is="true"><mi is="true">reop</mi></mrow></msub><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>, is calculated on-line (in about 3&nbsp;min of real time) using GA-II-aJG. This is implemented as soon as the disturbance is rectified. Experimental values of&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"><mi is="true">x</mi></mrow><mrow is="true"><mi is="true">m</mi></mrow></msub><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"><mi is="true">M</mi></mrow><mrow is="true"><mi is="true">w</mi></mrow></msub><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>&nbsp;and&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><mi is="true">η</mi><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>&nbsp;are also measured. These are observed to be in good agreement with model predictions for all the cases. It is found that the information on the viscosity of the reaction mass can be used effectively for on-line optimizing control. This can help ‘save’ the batch (give a product having the desired values of the average molecular weights) optimally, in as short a reaction time as possible. The effect of re-tuning of the model parameters using experimental data on the temperature,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"><mi is="true">T</mi></mrow><mrow is="true"><mi is="true">exp</mi></mrow></msub><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>, and the viscosity,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><mi is="true">η</mi><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>, is also demonstrated.An experimental study on the on-line optimizing control of a sample free radical bulk polymerization system, namely, methyl methacrylate (MMA), is carried out in a rheometer–reactor assembly. Two initiator loadings and three cases involving external disturbances (power failure) are studied. The disturbances are assumed to be of two kinds: one that leads to a sudden increase in the temperature of the reaction mass (cooling water pump failure) over the planned temperature history,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><mi is="true">T</mi><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>, and one leading to a sudden drop in the temperature (heater failure). The temperature and the viscosity,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><mi is="true">η</mi></math>, histories are used to describe the ‘state’ (conversion,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"><mi is="true">x</mi></mrow><mrow is="true"><mi is="true">m</mi></mrow></msub></math>, and weight-average molecular weight,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"><mi is="true">M</mi></mrow><mrow is="true"><mi is="true">w</mi></mrow></msub></math>) of the polymerizing mass. The polymerization is first carried out under an off-line computed optimal temperature history,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"><mi is="true">T</mi></mrow><mrow is="true"><mi is="true">op</mi></mrow></msub><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>, obtained using the adapted jumping gene version of the elitist genetic algorithm (GA-II-aJG). A planned disturbance is introduced after the start of polymerization and continues for a pre-specified duration. A new optimal temperature history,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"><mi is="true">T</mi></mrow><mrow is="true"><mi is="true">reop</mi></mrow></msub><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>, is calculated on-line (in about 3&nbsp;min of real time) using GA-II-aJG. This is implemented as soon as the disturbance is rectified. Experimental values of&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"><mi is="true">x</mi></mrow><mrow is="true"><mi is="true">m</mi></mrow></msub><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"><mi is="true">M</mi></mrow><mrow is="true"><mi is="true">w</mi></mrow></msub><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>&nbsp;and&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><mi is="true">η</mi><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>&nbsp;are also measured. These are observed to be in good agreement with model predictions for all the cases. It is found that the information on the viscosity of the reaction mass can be used effectively for on-line optimizing control. This can help ‘save’ the batch (give a product having the desired values of the average molecular weights) optimally, in as short a reaction time as possible. The effect of re-tuning of the model parameters using experimental data on the temperature,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"><mi is="true">T</mi></mrow><mrow is="true"><mi is="true">exp</mi></mrow></msub><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>, and the viscosity,&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><mi is="true">η</mi><mo stretchy="false" is="true">(</mo><mi is="true">t</mi><mo stretchy="false" is="true">)</mo></math>, is also demonstrated.

Chemical Engineering Science

An experimental study on on-line optimizing control of free radical bulk polymerization in a rheometer–reactor assembly under conditions of power failure

A viscometer-reactor assembly is used to generate data on the viscosity, η(t), of an example polymerizing system exhibiting the Trommsdorff effect, namely, the bulk free radical polymerization of methyl methacrylate (MMA), at different temperature conditions [near-isothermal and non-isothermal (near-step increase and near-step decrease in temperature)] and at two different initiator, 2,2′-azoisobutyronitrile (AIBN), concentrations. Two types of cup and bob assemblies, viz., the Haake® SV-2 and the Haake® HV-DIN, have been used to measure η(t) of the reaction mass, until reasonably high values of viscosity, well into the gel effect region. Only three sets of experimental data on xm(t), Mw(t) and η(t) under near-isothermal conditions, are used to develop general correlations for the viscosity. These tuned correlations predict the values of the viscosity for a whole variety of other experimental conditions, including non-isothermal cases, reflecting that the physics of the system is well represented by them. Hence, these correlations can be used for other systems after tuning their parameters. The feasibility of on-line soft sensing is demonstrated for a few cases. © 2006 Elsevier Ltd. All rights reserved.

Polymer

Viscosity of bulk free radical polymerizing systems under near-isothermal and non-isothermal conditions

Experimental data on the monomer conversion, xm, and the weight average molecular weight, Mw, have been generated under several isothermal and non-isothermal conditions for the polymerization of methyl methacrylate in a rheometer-reactor assembly. The non-isothermal results, in particular, can be used to provide more stringent tests of kinetic models than isothermal data alone. A simple empirical model has been used to describe this system that accounts for the gel (Trommsdorff) and glass effects. The model involves only xm and the temperature, and is quite general. The model parameters are tuned using only three sets of isothermal data. Good agreement is found between the experimental results and model predictions for a whole variety of experimental conditions, including non-isothermal operation and with intermediate addition of initiator. Because of its generality, this model is quite suitable for use for on-line optimizing control as well as for describing industrial reactors. © 2005 Published by Elsevier Ltd.

Bulk free radical polymerizations of methyl methacrylateunder non-isothermal conditions and with intermediate additionof initiator: Experiments and modeling