Computational chemistry predictions of reaction processes in organometallic vapor phase epitaxy

Quantitative understanding of reaction mechanisms in organometallic vapor phase epitaxy (OMVPE) is critical for selection of precursors, design of equipment, and optimization of process conditions. Progress has been made in the simulation of fluid flow as well as heat and mass transfer, but predictions of growth rates, alloy composition, and dopant incorporation are limited by the availability of thermodynamic and kinetic data for OMVPE precursors. Chemical kinetic experiments are expensive and difficult to perform, and the organometallic compounds being toxic and/or pyrophoric further complicates the situation. It is therefore desirable to study OMVPE reactions from first principles, quantum chemistry computations. We describe current quantum chemistry methods, Hartree-Fock and post-Hartree-Fock ab initio molecular orbital techniques and density functional theory (DFT) methods, with emphasis on issues related to OMVPE applications. The primary examples in this review are drawn from OMVPE applications, but studies on silicon chemistry are also included to illustrate important elements in simulation of vapor phase growth processes. Molecular structure and energy are reported for trialkyl group III species and group V hydrides by ab initio molecular orbital and density functional theory. The results are evaluated against experimental data. Vibrational frequencies needed for calculation of thermochemical properties (e.g., ΔH and ΔS) at process temperatures are also computed and compared to experimental data. The bimolecular reaction of methyl with arsine exemplifies the combined use of quantum chemistry and transition state theory to predict a reaction rate. A reaction mechanism for thermal decomposition of phosphine further demonstrates the use of these techniques. Lewis-acid-base adduct reactions of group III and V precursors exemplifies the use of quantum chemistry to evaluate adduct bond strengths and potential alkane elimination reaction pathways. A study of thermochemical properties of bridging organometallic aluminum compounds serves to illustrate variations in accuracy among different first principle methods. Overall, the selected examples demonstrate that computational chemistry techniques can provide useful insight into OMVPE chemical processes, but also that additional investigations are needed to establish which methods would be best for particular subsets of OMVPE chemistry.     

Menadione-γ-cyclodextrin inclusion complex

A stable, nonsublimable -cyclodextrin inclusion complex of menadione (Vitamin K₃) of 11.7% menadione content (molar ratio 1:1) was prepared in solution, in suspension, and by kneading. The physicalchemical properties of the complex formed were studied by X-ray diffraction, by thermal analysis (DTG, TG, DSC, TEA), and by chiroptical studies. The biological activity of the complex was tested on baby chickens by prothrombin time determination. Reduced prothrombin times showed an enhanced bioavailability of menadione in complexed form. The stability of vitamin K₃ is greatly improved in pharmaceuticals or in veterinary products prepared with a menadione--CD inclusion complex.     

α-Lactams (Aziridinones)

α-Lactams have often been postulated as intermediates in numerous processes. The isolation of the first α-lactam, N-tert-butyl-3-phenylaziridinone, was accomplished in 1962. Since then, further N- and C-3-substituted α-lactams have been synthesized. Most of these very reactive compounds undergo easy thermal decomposition; remarkable is the relative stability of 1,3-di-tert-butylaziridinone, which does not start to decompose below 140°C. The α-lactam ring is opened by nucleophilic reagents. — The correlation of stability and substituents is discussed in the last section. An acyclic, planar or almost planar, charge-delocalized intermediate is suggested to explain the observed effects.     

Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter

Data assimilation is an iterative approach to the problem of estimating the state of a dynamical system using both current and past observations of the system together with a model for the system’s time evolution. Rather than solving the problem from scratch each time new observations become available, one uses the model to “forecast” the current state, using a prior state estimate (which incorporates information from past data) as the initial condition, then uses current data to correct the prior forecast to a current state estimate. This Bayesian approach is most effective when the uncertainty in both the observations and in the state estimate, as it evolves over time, are accurately quantified. In this article, we describe a practical method for data assimilation in large, spatiotemporally chaotic systems. The method is a type of “ensemble Kalman filter”, in which the state estimate and its approximate uncertainty are represented at any given time by an ensemble of system states. We discuss both the mathematical basis of this approach and its implementation; our primary emphasis is on ease of use and computational speed rather than improving accuracy over previously published approaches to ensemble Kalman filtering. We include some numerical results demonstrating the efficiency and accuracy of our implementation for assimilating real atmospheric data with the global forecast model used by the US National Weather Service.     

Compaction of poly(dimethylsiloxane) (PDMS) due to proton beam irradiation

This work is about the detailed investigation of the changes of the surface topography, the degree of compaction/shrinkage and its relation to the irradiation fluence and the structure spacing in poly(dimethylsiloxane) (PDMS) patterned with 2 MeV proton microbeam. The irradiated periodic structures consisted of parallel lines with different widths and spacing. To achieve different degrees of compaction, each structure was irradiated with more different fluences. At the irradiated areas the surface topography, the adhesion, the wettability and the rigidity of the surface also changes due to the chemical/structural change of the basic poly(dimethylsiloxane) polymer. The surface topography, the phase modification of the surface, and the connection between them was revealed with using an atomic force microscope (AFM).     

Alkali Carbonate Effects on N‐(2‐Hydroxyethyl)urea Cyclization: Application to a 2‐Imidazolidinone Scale‐Up

An imidazolidinone intermediate ( 3 ) used in the synthesis of novel HIV‐entry inhibitors was prepared on multihundred gram scales in four steps and 40% overall yield. The penultimate step in the synthesis involved regioselective N‐cyclization of N‐(2‐hydroxylethyl)urea ( 11 ) by in situ activation of the terminal hydroxyl group with p‐TsCl in the presence of base. The ratio of N‐cyclized to O‐cyclized products followed a group IA periodic trend relative to the alkali carbonate base employed. The use of Cs₂CO₃ as base effected the desired N‐cyclization with a high degree of regiocontrol (>98%).     

Integration of ground aerogel particles as chromatographic stationary phase into microchip

C16 modified and ground monolithic silica aerogel particles in submicrometer size, as a new type of stationary phase was prepared and integrated in polydimethylsiloxane (PDMS) microchip. The aerogel particles were packed into the microfluidic channel using a simple procedure, which does not require any special frit or fabrication step to retain the particles. The subnanoliter volume of samples can be transported through the porous, short length of packing with low pressure (< 3 bar). Food dyes as test components could be separated using low pressure within 6s. A 50-fold preconcentration could be achieved by retaining 100 nL volume of sample on the packing and elution with methanol.