Elastic-energy relaxation in heterostructures with strained nanoinclusions

Kolesnikova, A. L.; Романов, А. Е.; Chaldyshev, V. V.

doi:10.1134/s1063783407040117

Cited by 18 publications

(36 citation statements)

References 19 publications

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“…Interstitial atoms form an interstitial dislocation loop near to the precipitate. At the same time, a mismatch dislocation loop is formed on the very precipitate (Kolesnikova et al, 2007). At the same time, the critical sizes of precipitates, at which formation of dislocations is energy favorable, have the same order as the critical size of dislocation loops (Kolesnikova et al, 2007).…”

Section: Kinetic Model For the Formation And Growth Of Dislocation Loopsmentioning

confidence: 69%

“…There can be found analytical solutions in respect of spherical precipitates (Kolesnikova & Romanov, 2004). Let us take the theoretical and experimental researches of stress relaxation at volume quantum dots as initial model (Chaldyshev et al, 2002;Kolesnikova & Romanov, 2004;Chaldyshev et al, 2005;Kolesnikova et al, 2007). According to these representations, as far as the precipitate grows, its elastic field induces the formation of a circular interstitial dislocation loop of mismatch.…”

Section: Kinetic Model For the Formation And Growth Of Dislocation Loopsmentioning

confidence: 99%

“…In the volume of silicon the precipitate produces a stress field caused by mismatch between the lattice parameters of precipitate () 1 a and the surrounding matrix () 2 a (Kolesnikova et al, 2007). Then, the intrinsic deformation of the precipitate is defined as described bellow …”

Section: Kinetic Model For the Formation And Growth Of Dislocation Loopsmentioning

confidence: 99%

See 2 more Smart Citations

The Diffusion Model of Grown-In Microdefects Formation During Crystallization of Dislocation-Free Silicon Single Crystals

Talanin¹,

Talanin²

2012

Advances in Crystallization Processes

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Advances in Crystallization Processes 612 microvoids as a result of aggregation of vacancies (Goethem et al., 2008;Kulkarni, 2008a). In this physical model, the interaction between the impurities and intrinsic point defects is not considered (Kulkarni et. al., 2004). R e c e n t v e r s i o n s o f t h i s m o d e l h a v e s u g g e s t e d t h a t p a r t o f t h e v a c a n c i e s ( v ) i n t h e temperature range 1683 ... 1373 K, due to the interaction with oxygen (O) and nitrogen (N) impurities, are bound into complexes of the vO, vO 2 , and vN types (Kulkarni 2007;2008b). After the formation of microvoids, the aforementioned complexes grow and take up vacancies. This model has ignored the growth of the complexes by means of the injection of intrinsic interstitial silicon atoms and the interaction of an impurity with intrinsic interstitial silicon atoms (Kulkarni 2007;2008b).In the general case recombination-diffusion model assumes that the process of defect formation in dislocation-free silicon single crystals occurs in four stages: (i) fast recombination of intrinsic point defects near the crystallization front; (ii) the formation in the narrow temperature range 1423...1223 K depending on the value of V g /G microvoids or interstitial dislocation loops; (iii) the formation of oxygen clusters in the temperature range 1223...1023 K; (iv) growth of precipitates as a result of subsequent heat treatments.Recombination-diffusion model is the physical basis for models of the dynamics of point defects. The mathematical model of point defect dynamics in silicon quantitatively explains the homogeneous mechanism of formation of microvoids and dislocation loops. It should be noted that, in the general case, the model of point defect dynamics includes three approximations: rigorous, simplified, and discrete-continuum approaches (Sinno, 1999;Dornberger et. al., 2001;Wang & Brown, 2001;Kulkarni et. al., 2004;Kulkarni, 2005;Prostomolotov & Verezub, 2009). The rigorous model requires the solution to integrodifferential equations for point defect concentration fields, and the distribution of grown-in microdefects in this model is a function of the coordinates, the time, and the time of evolution of the size distribution of microdefects. A high consumption of time and cost for the performance of calculations required the development of a simplified model in which the average defect radius is approximated by the square root of the average defect area. This approximation is taken into account in the additional variable, which is proportional to the total area of the defect surface. The simplified model is effective for calculating the twodimensional distribution of grown-in microdefects. Both models use the classical nucleation theory and suggest the calculation of the formation of stable nuclei and the kinetics of diffusion-limited growth of defects. The discrete-continuum approximation suggests a complex approach: the solution to discrete equations for the smallest defects and the solution to the Fokker-Planck equation for...

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Section: Kinetic Model For the Formation And Growth Of Dislocation Loopsmentioning

confidence: 69%

Section: Kinetic Model For the Formation And Growth Of Dislocation Loopsmentioning

confidence: 99%

See 1 more Smart Citation

The Diffusion Model of Grown-In Microdefects Formation During Crystallization of Dislocation-Free Silicon Single Crystals

Talanin¹,

Talanin²

2012

Advances in Crystallization Processes

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“…relaxation by precipitate results in occurrence of one or more dislocation loops [25]. The critical radiuses of precipitates which are energy favorable to the nucleation of dislocation loop shall be crit R = 3,028 µm (SiO 2 ) and crit R = 3,402 µm (SiC).…”

Section: Algorithm For the Formation Of Dislocation Loopsmentioning

confidence: 99%

“…In the volume of silicon the precipitate produces a stress field caused by mismatch between the lattice parameters of precipitate ( ) 1 a and surrounding matrix ( ) 2 a [25]. Then, the intrinsic deformation of the precipitate is defined as described bellow …”

Section: Algorithm For the Formation Of Dislocation Loopsmentioning

confidence: 99%

Algorithm for Calculating the Initial Defect Structure of Semiconductor Silicon

Talanin¹

2017

EAS

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An algorithm for calculating the defect structure of semiconductor silicon crystals was proposed. The proposed approach makes it possible to calculate the sizes, distribution densities of grown-in microdefects at any point of the crystal. Calculations are performed by using and analyzing the thermal conditions of crystal growth in the temperature range from 1683 K to 300 K. The algorithm flowchart is given.

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