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Anurag Mehra

Publications and source records attributed to Anurag Mehra.

4 recordsLinked to original sources

Modeling shell formation in core-shell nanocrystals in reverse micelle systems.

The mechanisms responsible for the formation of the shell in core-shell nanocrystals are ion-displacement and heterogeneous nucleation. In the ion-displacement mechanism, the shell is formed by the displacement reaction at the surface of the core nanoparticle whereas in heterogeneous nucleation the core particle induces the nucleation (or direct deposition) of shell material on its surface. The formation of core-shell nanocrystals via the post-core route has been examined in the current investigation. A purely probabilistic Monte Carlo scheme for the formation of the shell has been developed to predict the experimental results of Hota et al. (Hota, G.; Jain, S.; Khilar, K. C. Colloids Surf., A 2004, 232, 119) for the precipitation of Ag2S-coated CdS (Ag2S@CdS) nanoparticles. The simulation procedure involves two stages. In the first stage, shell formation takes place as a result of the consumption of supersaturation, ion displacement, and reaction between Ag+ and excess sulfide ions. The growth in the second stage is driven by the coagulation of nanoparticles. The results indicate that the fraction of shell deposited by the ion-displacement mechanism increases with increasing ion ratio and decreases with increasing water-to-surfactant molar ratio.

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Coagulation of nanoparticles in reverse micellar systems: a Monte Carlo model.

The process of formation of nanoparticles obtained by mixing two micellized, aqueous solutions has been simulated using the Monte Carlo technique. The model includes the phenomena of finite nucleation, growth via intermicellar exchange, and coagulation of nanoparticles after their formation. Using the model, an exploratory study has been conducted to analyze whether the coagulation of nanoparticles is the reason for the formation of nanoparticles whose sizes are comparable to the size of the reverse micelles. The model explains the possible mechanism of coagulation of semiconductor nanoparticles formed within reverse micelles and its effect on the evolution of their size with time. The model is predictive in nature, and the simulation results compare well with those observed experimentally.

Journal Article↗

Monte Carlo models for nanoparticle formation in two microemulsion systems.

The process of formation of nanoparticles obtained by mixing two micellized, aqueous solutions has been simulated using the Monte Carlo technique. The model includes the phenomena of finite reaction, nucleation, and growth via intermicellar exchange. This exploratory study examines the characteristic particle size distributions (PSDs) that result from using combinations of different initial reactant distributions (Poissonian and geometric) and different types of intermicellar exchange protocols (random, cooperative, and binomial). It is observed that the PSDs obtained using an initial Poissonian distribution of reactants and random exchange rules are similar to reported experimental results for CdS nanoparticles. The effect of exchange efficiency and reaction rate has also been studied. It is seen that a high exchange efficiency leads to relatively larger particle sizes. Also, a slow reaction rate has been shown to lead to the formation of larger nanoparticles.

Journal Article↗

Mathematical analysis of solid-liquid mass transfer in a batch reactor for the enzymatic transformation of testosterone to 4AD.

A previous mathematical analysis of mass transfer in a two-phase (solid-liquid) batch reactor for enzymatic transformation of testosterone to 4AD (Pereira et al., 1987) is extended to incorporate the effect of convective mixing. The results of the analysis showed that for a given enzyme loading, the mass transfer resistance in the solid (a function of the bead size) and the intensity of convective mixing (as embodied in the mass transfer coefficient) are two parameters that can be varied such that the overall mass transfer rate from the solid to the liquid phase ensures optimal reactor performance.

17-Hydroxysteroid Dehydrogenases↗