Abstract: A method for predicting the formation of silicon nanocrystals in an oxide matrix is disclosed. Initially, fundamental data for a set of microscopic processes that can occur during one or more material processing operations are obtained. Kinetic models are then built by utilizing the fundamental data for a set of reactions that can contribute substantially to the formation of silicon nanocrystals in a silicon oxide matrix. Finally, the kinetic models are applied to predict shape, size distribution, spatial arrangements of silicon nanocrystals.

Abstract: A thermoelectric device includes: a first region; a second region; and a thermoelectric body disposed between the first region and the second region, where the thermoelectric body includes a vacancy.

Abstract: A method for predicting the contribution of silicon interstitials to n-type dopant transient enhanced diffusion during a pn junction formation is disclosed. Initially, fundamental data for a set of microscopic processes that can occur during one or more material processing operations are obtained. The fundamental data are then utilized to build kinetic models for a set of reactions that contribute substantially to an evolution of n-type dopant concentration and electrical activities. The kinetic models are subsequently applied to a simulator to predict temporal and spatial evolutions of concentration and electrical activity profiles of the n-type dopants.

Abstract: Techniques for predicting the behavior of dopant and defect components in a substrate lattice formed from a substrate material can be implemented in hardware or software. Fundamental data for a set of microscopic processes that can occur during one or more material processing operations is obtained. Such data can include data representing the kinetics of processes in the set of microscopic processes and the energetics and structure of possible states in the material processing operations. From the fundamental data and a set of external conditions, distributions of dopant and defect components in the substrate lattice are predicted.

Abstract: Computer programs and computer-implemented methods for predicting from first principles the behavior of dopants and defects in the processing of electronic materials. The distribution of dopant and defect components in a substrate lattice is predicted based on external conditions and fundamental data for a set of microscopic processes that can occur during material processing operations. The concentration behavior of one or more fast components is calculated in two stages, by solving a first relationship for a time period before the fast component reaches a pseudo steady state at which the concentration of the fast component is determined by concentrations of one or more second components, and by solving a second relationship for a time period after the first component reaches the pseudo steady state. Application of these methods to modeling ultrashallow junction processing is also described.

Abstract: Computer programs and computer-implemented methods for predicting from first principles the behavior of dopants and defects in the processing of electronic materials. The distribution of dopant and defect components in a substrate lattice is predicted based on external conditions and fundamental data for a set of microscopic processes that can occur during material processing operations. The concentration behavior of one or more fast components is calculated in two stages, by solving a first relationship for a time period before the fast component reaches a pseudo steady state at which the concentration of the fast component is determined by concentrations of one or more second components, and by solving a second relationship for a time period after the first component reaches the pseudo steady state. Application of these methods to modeling ultrashallow junction processing is also described.