RT info:eu-repo/semantics/masterThesis
T1 Characterization and dynamics of Si self-interstitial clusters by self-learning kinetic Monte Carlo simulations
A1 Calvo Ruiz, Diego
A2 Universidad de Valladolid. Facultad de Ciencias
K1 Semiconductores - Propiedades
AB Si is a semiconductor material whose relevance in the industry is undeniable, beingimplemented in every generation of the transistor scaling over the last decades thanksto their excellent properties and easy production. During the fabrication process it iscommon to deal with the diffusion of impurity atoms in Si, which is critically influencedby intrinsic defects such as self-interstitials and vacancies. Point defects tend to aggregateforming small clusters and extended defects and therefore, the dopant diffusivity isenhanced and leakage currents are increased in the  final device.The aim of this work is to study the energetic characteristics of small Si interstitialsclusters from an atomistic point of view, determining their formation enthalpies andenergy barriers for each cluster size. To do so, we have run simulations with the kineticActivation-Relaxation Technique. We have characterized each geometrical configurationbased on energetic and visual criteria, classifying the small clusters in chainlike, compactor (111) configurations. The transition barriers between these structures have been alsodetermined. This information is useful to understand the behaviour of small clusters incrystal and how they can evolve to extended defects. This study can also be applied toother semiconductor materials.
YR 2016
FD 2016
LK http://uvadoc.uva.es/handle/10324/20512
UL http://uvadoc.uva.es/handle/10324/20512
LA eng
NO Departamento de Química Física y Química Inorgánica
DS UVaDOC
RD 27-nov-2024