Modeling equilibrium concentrations of Bjerrum and molecular point defects and their complexes in ice Ih

2008 ◽  
Vol 128 (16) ◽  
pp. 164502 ◽  
Author(s):  
Maurice de Koning ◽  
Alex Antonelli
Keyword(s):  
Point Defects ◽  
Equilibrium Concentrations

Atomistic Simulations of Point Defect Properties in Silicon

1992 ◽  
Vol 278 ◽  
Author(s):  
Dimitrios Maroudas ◽  
Robert A. Brown
Keyword(s):  
Distribution Function ◽  
Point Defects ◽  
Thermal Equilibrium ◽  
Harmonic Approximation ◽  
Reference State ◽  
Atomistic Simulations ◽  
Free Energies ◽  
Systematic Analysis ◽  
Equilibrium Concentrations ◽  
Cumulant Analysis

AbstractA systematic analysis based on atomistic simulations is presented for the calculation of energies and equilibrium concentrations of intrinsic point defects in silicon. Calculation of Gibbs free energies is based on the quasi-harmonic approximation for the reference state and the cumulant analysis of the enthalpy distribution function from Monte Carlo simulations in the reference state. Results are presented for the temperature dependence of enthalpies, volumes, and free energies of formation and thermal equilibrium concentrations of vacancies and self-interstitials.

scholarly journals Diffusion Engineering by Carbon in Silicon

2000 ◽  
Vol 610 ◽  
Author(s):  
Ulrich Goesele ◽  
Pierre Laveant ◽  
Rene Scholz ◽  
Norbert Engler ◽  
Peter Werner
Keyword(s):  
Point Defects ◽  
Crystalline Silicon ◽  
Bipolar Transistor ◽  
Precipitation Behavior ◽  
High Concentration ◽  
Intrinsic Point Defects ◽  
Influence Diffusion ◽  
Carbon Precipitation ◽  
Equilibrium Concentrations ◽  
Diffusion Mechanisms

AbstractThe possibility to suppress undesirable diffusion of the base dopant boron in siliconbased bipolar transistor structures by the incorporation of a high concentration of carbon has lead to renewed interest in the behavior of carbon in crystalline silicon. The present paper will review essential features of carbon in silicon including solubility, diffusion mechanisms and precipitation behavior. Based on this information the possibilities to use carbon to influence diffusion of dopants in silicon by the introduction of non-equilibrium concentrations of intrinsic point defects will be discussed as well as the reason for the relatively high resilience against carbon precipitation. Interactions between carbon and oxygen will be mentioned, especially in the context of an as yet unexplained fast out-diffusion of carbon close to the surface.

Diffusion in the AlMo3 Ordered Intermetallic

2008 ◽  
Vol 272 ◽  
pp. 51-60
Author(s):  
M.I. Pascuet ◽  
Julián R. Fernández ◽  
A.M. Monti
Keyword(s):  
Monte Carlo ◽  
Point Defects ◽  
Interatomic Potential ◽  
Kinetic Monte Carlo ◽  
Statistical Thermodynamics ◽  
Monte Carlo Technique ◽  
Vacancy Mechanism ◽  
Ordered Intermetallic ◽  
Equilibrium Concentrations

An EAM interatomic potential for the ordered AlMo3 intermetallic is developed and applied to the study of point defects in the AlMo3. The equilibrium concentrations of vacancies and antisites are calculated using statistical thermodynamics. Results show that antisites are the most abundant type of defect in a range of temperatures and compositions close to stoichiometry. Finally, the diffusion by vacancy mechanism in the same structure is studied through the kinetic Monte Carlo technique. Possible atomic mechanisms of diffusion are suggested and analyzed in some detail.

Diffusion and Point Defects in Elemental Semiconductors

2018 ◽  
Vol 17 ◽  
pp. 1-28 ◽  
Author(s):  
Helmut Mehrer
Keyword(s):  
Point Defects ◽  
Base Material ◽  
Good Deal ◽  
Radiation Detectors ◽  
Electronic Band ◽  
Self Diffusion ◽  
Electronic Band Gap ◽  
Equilibrium Concentrations ◽  
Elemental Semiconductors ◽  
Silicon And Germanium

Elemental semiconductors play an important role in high-technology equipment used in industry and everyday life. The first transistors were made in the 1950ies of germanium. Later silicon took over because its electronic band-gap is larger. Nowadays, germanium is the base material mainly for γ-radiation detectors. Silicon is the most important semiconductor for the fabrication of solid-state electronic devices (memory chips, processors chips, ...) in computers, cellphones, smartphones. Silicon is also important for photovoltaic devices of energy production.Diffusion is a key process in the fabrication of semiconductor devices. This chapter deals with diffusion and point defects in silicon and germanium. It aims at making the reader familiar with the present understanding rather than painstakingly presenting all diffusion data available a good deal of which may be found in a data collection by Stolwijk and Bracht [1], in the author’s textbook [2], and in recent review papers by Bracht [3, 4]. We mainly review self-diffusion, diffusion of doping elements, oxygen diffusion, and diffusion modes of hybrid foreign elements in elemental semiconductors.Self-diffusion in elemental semiconductors is a very slow process compared to metals. One of the reasons is that the equilibrium concentrations of vacancies and self-interstitials are low. In contrast to metals, point defects in semiconductors exist in neutral and in charged states. The concentrations of charged point defects are therefore affected by doping [2 - 4].

The Influence of Point Defects on Diffusion and Gettering in Silicon

1984 ◽  
Vol 36 ◽  
Author(s):  
U. Gösele ◽  
T. Y. Tan
Keyword(s):  
Point Defects ◽  
Thermal Equilibrium ◽  
Nucleation And Growth ◽  
Impurity Diffusion ◽  
Intrinsic Point Defects ◽  
Different Types ◽  
Equilibrium Concentrations ◽  
Metallic Impurities

ABSTRACTIn a first part, we deal with the influence of intrinsic point defects (vacancies and self-interstitials) on self- and impurity diffusion in silicon. Estimates of the diffusivities and thermal equilibrium concentrations of vacancies and self-interstitials are given. In a second partwe discuss the influence of point defects on the diffusion and precipitation of different types of metallic impurities in various gettering schemes as well as on the nucleation and growth of SiO2 precipitates.

Properties of Point-Defects in Si for Process Modeling

1995 ◽  
Vol 389 ◽  
Author(s):  
H.-J. Gossmann ◽  
C. S. Rafferty ◽  
P. A. Stolk ◽  
D. J. Eaglesham ◽  
G. H. Gilmer ◽  
...  
Keyword(s):  
Point Defects ◽  
Quantitative Information ◽  
Recombination Coefficient ◽  
Native Point Defects ◽  
Front End ◽  
Atomistic Calculations ◽  
Equilibrium Concentrations ◽  
Dopant Atoms ◽  
Physical Phenomena ◽  
Impurity Profiles

ABSTRACTThe development of future Si device technologies will rely extensively on modeling, requiring truly predictive tools. Here we focus on the front-end processes, during which ion-implantation and annealing create 3-D impurity profiles that determine crucial electrical device parameters. The final configuration is the result of a complex interaction of dopant atoms with Si self-interstitials and vacancies, which themselves interact with each other as well as with the implantation-induced damage and interfaces. Predictive modeling requires for all these processes a solid understanding of the physical phenomena as well as accurate quantitative information. Si self-interstitials and vacancies are not observable directly in an experiment, but only via their interactions with some other physical quantity of the sample. We review our work employing dopant atoms in δ-doping superlattices (δ-DSL) that yield directly the time averaged depth profiles of Si native point defects during a particular processing sequence. This approach is uniquely suited for giving insights into the interplay of point defects in Si, providing crosschecks for atomistic calculations as well as parameters for process simulators. We describe experiments to extract interstitial and vacancy parameters and discuss the influence of intrinsic and extrinsic interstitial traps, as well as of the annealing environment, on the native point defect population. The latter allows to place certain bounds on the interstitial vacancy recombination coefficient as well as the ratio of interstitial and vacancy equilibrium concentrations.

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