Garnett W. Bryant

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This is the second in a series of articles describing a wide variety of projects at NIST that synergistically combine physical science and information science. It describes, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing, visualization, and machine learning to(More)
Many-body levels of optically excited and multiply charged InAs nanocrystals are studied with the semi-empirical tight-binding model. Single-particle levels of unstrained spherical InAs nanocrystals are described by the sp 3 d 5 s* nearest-neighbor tight-binding model including spin-orbit coupling. For optically excited InAs nanocrystals, first-order(More)
The electron-hole states of semiconductor quantum dots are investigated within the framework of empirical tight-binding descriptions for Si, as an example of an indirect-gap material, and InAs and CdSe as examples of typical III-V and II-VI direct-gap materials. We significantly improve the energies of the single-particle states by optimizing tight-binding(More)
This is the third in a series of articles that describe, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing, visualization, and machine learning to accelerate scientific discovery. In this article we focus on the use of high performance computing and visualization for(More)
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