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.

Parameter Optimization of Molecular Models: Application to Surface Kinetics

Abstract: A multistep methodology is explored for the optimization of the parameters of molecular models. This methodology is based on response surface methods and circumvents the practically impossible rigorous parameter fitting of computationally intensive molecular models. The approach is demonstrated for the parameters of the catalytic oxidation reaction of CO on platinum modeled by kinetic Monte Carlo simulations. After implementation of an initial reaction mechanism, sensitivity analysis is carried out to determine the key (active) reaction parameters for selected experimental points. Next, solution mapping is used to parametrize the model responses as low-degree polynomials of the active parameters. Finally, optimization of the active parameters is performed using simulated annealing. The optimized parameters are contrasted to those of a continuum-type mean-field model. The effect of surface diffusion in determining intrinsic kinetic parameters is also addressed, and the possibility of bridging the pressure ...

Experiments and Kinetic Modeling for CO2 Gasification of Indian Coal Chars in the Context of Underground Coal Gasification

Abstract: Gasification of four Indian coals is carried out in a CO2 atmosphere, using a thermogravimetric analyzer (TGA) to determine the intrinsic kinetics over a temperature range of 800–1050 °C with different partial pressures of CO2. The applicability of three models, viz., the volumetric reaction model, the shrinking core model and the random pore model, is evaluated. Of these three models, the random pore model is found to be the most suitable for all the coals considered in the current study. The dependence of the reaction rate on the gas-phase partial pressures is explained by the Langmuir–Hinshelwood model, and the parameters for the inhibition due to CO and CO2 are determined by performing experiments at different partial pressures. In underground coal gasification, the reaction takes place on reasonably large sized coal particles, wherein diffusion effects are significant. A one-dimensional reaction diffusion model is therefore developed in order to determine the diffusional resistance in the coal partic...

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.