GaP/Si: Studying Semiconductor Growth Characteristics with Realistic Quantum-Chemical Models
Andreas Stegmüller and
Ralf Tonner ()
Additional contact information
Andreas Stegmüller: Philipps-Universität Marburg, Fachbereich Chemie
Ralf Tonner: Philipps-Universität Marburg, Fachbereich Chemie
A chapter in High Performance Computing in Science and Engineering ‘14, 2015, pp 205-218 from Springer
Abstract:
Abstract The understanding of microscopic processes and properties is crucial for the development and efficient production of inorganic III/V semiconductor materials. Those materials are grown in chemical vapour deposition procedures where elementary steps have not yet been thoroughly understood. Ab initio calculations are capable to investigate those atomic and electronic properties. Modern implementations of Density Functional Theory were applied to study layered bulk structures, periodic surface properties and adatom transport on Si(001) and GaP-Si(001) materials. By increasing cell sizes and number of atoms to scales that only supercomputing facilities can handle, a realistic chemical environment can be modeled with increased structural degrees of freedom. Bulk supercells were constructed in order to model realistic interfaces between two thin films in the nanometer scale. Supercell models in slab geometry were set up and converged with respect to the volume of vacuum and number of relaxed atoms for an accurate description of slab surfaces. These studies enable a direct comparison to experimental studies on these materials.
Keywords: Density Functional Theory; Surface Reconstruction; Vacuum Region; Hessian Matrice; Kinetic Monte Carlo Simulation (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-10810-0_15
Ordering information: This item can be ordered from
http://www.springer.com/9783319108100
DOI: 10.1007/978-3-319-10810-0_15
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().