Preeti Aghalayam

Bio: Preeti Aghalayam is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Underground coal gasification & Catalysis. The author has an hindex of 22, co-authored 59 publications receiving 1360 citations. Previous affiliations of Preeti Aghalayam include University of Delaware & University of Massachusetts Amherst.

Improving efficiency of CCS-enabled IGCC power plant through the use of recycle flue gas for coal gasification

Abstract: CO2 capture from coal-fired power plants is necessary for continued use of coal as a fuel. Proven CO2 capture techniques such as amine absorption and oxyfuel combustion entail significant energy penalty leading to considerable decrease in the net thermal efficiency of the power plant. Recent studies of high-ash Indian coals show that CO2 has sufficient reactivity for coal gasification in temperature ranges of interest to IGCC. Against this background, we analyse in the present study, a new power plant layout which uses part of the sequestered flue gas stream for high-pressure gasification of the coal within the framework of an IGCC power plant with CO2 capture. Detailed thermodynamic calculations of the new plant layout, referred to here as Oxy-RFG-IGCC-CC, using commercial power plant simulation software show that the optimized Oxy-RFG-IGCC-CC plant with CO2 capture produces power at an overall thermal efficiency of 34.2%, which is nearly the same as that of current generation of pulverized coal boiler-based power plants without CO2 capture or that of a conventional IGCC with post-combustion capture. The proposed simpler layout is also 1.9% more efficient than a comparable CO2-capture-enabled IGCC plant that uses steam for coal gasification.

Global Kinetic Modeling and Analysis of Lean NOx Traps (LNT) Catalysts

Abstract: Lean NOx traps (LNT) is an after-treatment technique that is used for NOx abatement in lean-burn engines. The objective of this work is to develop a generic kinetic model applicable to various LNT catalyst formulations and to apply it to the design and analysis of the LNT reactor. The kinetic model of 16 reactions is proposed using Langmuir–Hinshelwood kinetics. It is validated against experiments reported in the literature, performed for a family of catalyst formulations that use Pt-group metals as the active catalyst and barium-based NOx storage, and is capable of predicting the performance with minimal modification of parameters. A kinetic analysis highlights the contribution of each reaction to the overall kinetic scheme in order to determine the important steps and qualitatively validate the model. A reactor-level analysis is done by varying the operating conditions and the time scales of the lean and rich phases are optimized.

Understanding NO emissions in diesel and biodiesel based engines

Abstract: Formation of nitrogen oxide pollutants is investigated using a homogeneous combustion model for diesel and biodiesel surrogates including-n-heptane, methyl decanoate, methyl-9-decenoate and other oxygenated fuels. The investigations are carried out in a series of detailed simulation studies-ignition and combustion characteristics unique to the fuel are chosen such that comparable engine performance is obtained, and the results compared in terms of emissions. This is followed by an analysis of the NOX formation pathways for the various fuels in a model HCCI engine, operated at conditions where similar temperature profiles are obtained. Different fuel-oxygen ratios including fuel-lean, stoichiometric, and fuel-rich inlet conditions are examined in detail from viewpoint of NOX emissions. Significant NO variations are observed among the fuels at stoichiometric fuel-air ratio, with the oxygenated fuels demonstrating high NO compared to n-heptane. In particular, the NO emissions for MD9D was found to be 2.6 times that for n-heptane, at stoichiometric conditions at practically significant operating conditions. Thermal, prompt, and other pathways for NO formation are evaluated at fuel-lean, stoichiometric, and fuel-rich conditions, for different imposed temperature trends. The thermal pathway is found to contribute >60% of the NO in case of stoichiometric & fuel-lean mixtures. The contribution of the prompt pathway, on the other hand, can be as high as 50% in case of fuel-rich mixtures. Significant insight into the formation of NO in diesel and biodiesel engines is obtained from our studies.

A methodology for structure dependent global kinetic models: Application to the selective catalytic reduction of NO by hydrocarbons

Abstract: Global kinetic models capable of capturing experimentally observed features of catalytic reactions are vital in design and optimization studies. In this work, a detailed analysis of the selective catalytic reduction of NO and NO2, particularly in automotive exhaust control is undertaken. The prominent metal based catalysts for this reaction range from Pt, Au & Rh to cheaper options including Cu, Ag & Co supported on Al2O3, SiO2, and occasionally, zeolites. Here, we focus on Ag & Co supported on Al2O3 catalysts, and propose a computationally tractable kinetic model capable of capturing the observed SCR features across a range of catalyst synthesis and reactor operating conditions. In particular, the effects of metal loading on catalyst performance are closely examined. In SCR, an important aspect is the catalytic activity at higher inlet O2 concentrations. The global kinetic model proposed here is shown to predict the trends with respect to reactor temperature and inlet feed compositions (including O2), well, for both catalysts.

A review of catalytic partial oxidation of methane to synthesis gas with emphasis on reaction mechanisms over transition metal catalysts

Abstract: Catalytic partial oxidation of methane has been reviewed with an emphasis on the reaction mechanisms over transition metal catalysts. The thermodynamics and aspects related to heat and mass transport is also evaluated, and an extensive table on research contributions to methane partial oxidation over transition metal catalysts in the literature is provided. Presented are both theoretical and experimental evidence pointing to inherent differences in the reaction mechanism over transition metals. These differences are related to methane dissociation, binding site preferences, the stability of OH surface species, surface residence times of active species and contributions from lattice oxygen atoms and support species. Methane dissociation requires a reduced metal surface, but at elevated temperatures oxides of active species may be reduced by direct interaction with methane or from the reaction with H, H2, C or CO. The comparison of elementary reaction steps on Pt and Rh illustrates that a key factor to produce hydrogen as a primary product is a high activation energy barrier to the formation of OH. Another essential property for the formation of H2 and CO as primary products is a low surface coverage of intermediates, such that the probability of O–H, OH–H and CO–O interactions are reduced. The local concentrations of reactants and products change rapidly through the catalyst bed. This influences the reaction mechanisms, but the product composition is typically close to equilibrated at the bed exit temperature.

An overview of spatial microscopic and accelerated kinetic Monte Carlo methods

Abstract: The microscopic spatial kinetic Monte Carlo (KMC) method has been employed extensively in materials modeling. In this review paper, we focus on different traditional and multiscale KMC algorithms, challenges associated with their implementation, and methods developed to overcome these challenges. In the first part of the paper, we compare the implementation and computational cost of the null-event and rejection-free microscopic KMC algorithms. A firmer and more general foundation of the null-event KMC algorithm is presented. Statistical equivalence between the null-event and rejection-free KMC algorithms is also demonstrated. Implementation and efficiency of various search and update algorithms, which are at the heart of all spatial KMC simulations, are outlined and compared via numerical examples. In the second half of the paper, we review various spatial and temporal multiscale KMC methods, namely, the coarse-grained Monte Carlo (CGMC), the stochastic singular perturbation approximation, and the τ-leap methods, introduced recently to overcome the disparity of length and time scales and the one-at-a time execution of events. The concepts of the CGMC and the τ-leap methods, stochastic closures, multigrid methods, error associated with coarse-graining, a posteriori error estimates for generating spatially adaptive coarse-grained lattices, and computational speed-up upon coarse-graining are illustrated through simple examples from crystal growth, defect dynamics, adsorption–desorption, surface diffusion, and phase transitions.