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The Gaussian Approximation Potential [electronic resource] : An Interatomic Potential Derived from First Principles Quantum Mechanics / by Albert Bartk-Prtay.

Por: Tipo de material: TextoTextoSeries Springer Theses, Recognizing Outstanding Ph.D. Research | Springer Theses, Recognizing Outstanding Ph.D. ResearchEditor: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010Descripción: XIV, 90 p. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • online resource
ISBN:
  • 9783642140679
Trabajos contenidos:
  • SpringerLink (Online service)
Tema(s): Formatos físicos adicionales: Sin títuloClasificación CDD:
  • 530.41 23
Clasificación LoC:
  • Libro electrónico
Recursos en línea:
Contenidos:
Springer eBooksResumen: Simulation of materials at the atomistic level is an important tool in studying microscopic structures and processes. The atomic interactions necessary for the simulations are correctly described by Quantum Mechanics, but the size of systems and the length of processes that can be modelled are still limited. The framework of Gaussian Approximation Potentials that is developed in this thesis allows us to generate interatomic potentials automatically, based on quantum mechanical data. The resulting potentials offer several orders of magnitude faster computations, while maintaining quantum mechanical accuracy. The method has already been successfully applied for semiconductors and metals.
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Representation of Atomic Environments -- Gaussian Process -- Interatomic Potentials -- Computational Methods -- Results -- Conclusion and Further Work -- Appendices.

Simulation of materials at the atomistic level is an important tool in studying microscopic structures and processes. The atomic interactions necessary for the simulations are correctly described by Quantum Mechanics, but the size of systems and the length of processes that can be modelled are still limited. The framework of Gaussian Approximation Potentials that is developed in this thesis allows us to generate interatomic potentials automatically, based on quantum mechanical data. The resulting potentials offer several orders of magnitude faster computations, while maintaining quantum mechanical accuracy. The method has already been successfully applied for semiconductors and metals.

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