Ion beam induced defects in crystalline silicon

Cristiano, Fuccio; Cherkashin, Nikolay; Hebras, Xavier; Calvo, P.; Lamrani, Y.; Scheid, E.; Mauduit, B. de; Colombeau, B.; Lerch, W.; Paul, S.; Claverie, A.

doi:10.1016/j.nimb.2003.11.019

Cited by 42 publications

(26 citation statements)

References 25 publications

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“…Both of these results are consistent with the experimental observation that self-interstitial clusters eventually tend to coarsen into FDLs and then PDLs under most anneal-ing conditions. 3,[24][25][26][27][28][29] On the other hand, the absence of ͕100͖ planar defects in silicon wafer annealing experiments cannot be explained on the basis of simple energetics as these are found to possess formation energies that are very similar to the various configurations of ͕113͖ defects. For example, Goss 5 employed DFT within the local density approximation to compute the formation energies of infinite ͕100͖ and ͕113͖ defects, and found that the ͕100͖ defect was in fact slightly favored over the ͕113͖.…”

Section: Formation Thermodynamics For Self-interstitial Clusters-prevmentioning

confidence: 99%

Detailed microscopic analysis of self-interstitial aggregation in silicon. II. Thermodynamic analysis of single clusters

2010

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We analyze results generated by large-scale molecular-dynamics simulations of self-interstitial clusters in crystalline silicon using a recently developed computational method for probing the thermodynamics of defects in solids. In this approach, the potential-energy landscape is sampled with lengthy moleculardynamics simulations and repeated energy minimizations in order to build distribution functions that quantitatively describe the formation thermodynamics of a particular defect cluster. Using this method, a comprehensive picture for interstitial aggregation is proposed. In particular, we find that both vibrational and configuration entropic factors play important roles in determining self-interstitial cluster morphology. In addition to the expected role of temperature, we also find that applied (hydrostatic) pressure and the commensurate lattice strain greatly influence the resulting aggregation pathways. Interestingly, the effect of pressure appears to manifest not by altering the thermodynamics of individual defect configurations but rather by changing the overall energy landscape associated with the defect. These effects appear to be general and are predicted using multiple, well-tested, empirical interatomic potentials for silicon. Our results suggest that internal stress environments within a silicon wafer (e.g., created by ion implantation) could have profound effects on the observed selfinterstitial cluster morphology. We analyze results generated by large-scale molecular-dynamics simulations of self-interstitial clusters in crystalline silicon using a recently developed computational method for probing the thermodynamics of defects in solids. In this approach, the potential-energy landscape is sampled with lengthy molecular-dynamics simulations and repeated energy minimizations in order to build distribution functions that quantitatively describe the formation thermodynamics of a particular defect cluster. Using this method, a comprehensive picture for interstitial aggregation is proposed. In particular, we find that both vibrational and configuration entropic factors play important roles in determining self-interstitial cluster morphology. In addition to the expected role of temperature, we also find that applied ͑hydrostatic͒ pressure and the commensurate lattice strain greatly influence the resulting aggregation pathways. Interestingly, the effect of pressure appears to manifest not by altering the thermodynamics of individual defect configurations but rather by changing the overall energy landscape associated with the defect. These effects appear to be general and are predicted using multiple, well-tested, empirical interatomic potentials for silicon. Our results suggest that internal stress environments within a silicon wafer ͑e.g., created by ion implantation͒ could have profound effects on the observed selfinterstitial cluster morphology. Disciplines Biochemical and Biomolecular Engineering | Chemical Engineering | Engineering

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Section: Formation Thermodynamics For Self-interstitial Clusters-prevmentioning

confidence: 99%

Detailed microscopic analysis of self-interstitial aggregation in silicon. II. Thermodynamic analysis of single clusters

2010

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“…In both cases it was concluded that nucleation of PDLs and FDLs is the result of an unfaulting process of the ͕113͖ defects. [7][8][9] In this letter, we report a detailed study of the defect evolution after a preamorphizing implant, in which we show that an "intermediate" rodlike defect forms during the transformation of ͕113͖'s into DLs.…”

Section: Evidences Of An Intermediate Rodlike Defect During the Transmentioning

confidence: 90%

“…However, if the total interstitial population is sufficiently high, additional thermal budgets allow the ͕113͖'s to transform into PDLs and FDLs, which, in turn, engage a competitive ripening mechanism among themselves, depending on the different experimental conditions. [5][6][7] A particular attention has been paid to the evolution kinetics of extended defects, resulting from nonamorphizing 8,9 and amorphizing 6-10 implants. In both cases it was concluded that nucleation of PDLs and FDLs is the result of an unfaulting process of the ͕113͖ defects.…”

Section: Evidences Of An Intermediate Rodlike Defect During the Transmentioning

confidence: 99%

Evidences of an intermediate rodlike defect during the transformation of {113} defects into dislocation loops

Boninelli

Cherkashin

Claverie

et al. 2006

Applied Physics Letters

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A detailed study of the transformation of the {113} defects into dislocation loops has been carried out in Ge preamorphized silicon (30keV, 1×1015Ge+∕cm2) and annealed at 800°C for time ranging from 15to2700s. The presence of a stable defect, along the ⟨110⟩ directions, formed during the transformation from {113}’s into Frank dislocation loops (FDLs), has been revealed and studied. Performing a detailed transmission electron microscopy analysis in nonconventional zone axes, a 1∕3 [111]-type Burgers vector has been found. These defects are shown to be more stable than {113}’s but less than FDLs.

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“…For bigger sizes we rearrange them into the {311} defects and/or faulted DLs according to the crystalline geometry data. The experimental transition size between small clusters and {311} defects is not well known, and the literature establishes a size of n = 10 as a minimum [4], [12] and n = 40 as a maximum [11].…”

Section: A Shapementioning

confidence: 99%

“…DL are expected to be more stable than {311} defects beyond a size of about ≈ 350 atoms. However, {311} defects of much larger sizes have been observed [1], [5], [11], [18]. For a {311} defect population distribution (at a given temperature), only the large {311} defects are observed to transform into DLs.…”

Section: A Shapementioning

confidence: 99%

From point defects to dislocation loops: A comprehensive TCAD model for self-interstitial defects in silicon

Martín-Bragado

Avci

Zographos

et al. 2007

ESSDERC 2007 - 37th European Solid State Device Research Conference

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Abstract-An atomistic model for self-interstitial extended defects is presented in this work. Using a limited set of assumptions about the shape and emission frequency of extended defects, and taking as parameters the interstitial binding energies of extended defects versus their size, this model is able to predict a wide variety of experimental results. The model accounts for the whole extended defect evolution, from the initial small irregular clusters to the {311} defects and to the more stable dislocation loops. The model predicts the extended defect dissolution, supersaturation and defect size evolution with time, and it takes into account the thermally activated transformation of {311} defects into dislocation. The model is also used to explore a two-phase exponential decay observed in the dissolution of {311} defects.

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Ion beam induced defects in crystalline silicon

Cited by 42 publications

References 25 publications

Detailed microscopic analysis of self-interstitial aggregation in silicon. II. Thermodynamic analysis of single clusters

Detailed microscopic analysis of self-interstitial aggregation in silicon. II. Thermodynamic analysis of single clusters

Evidences of an intermediate rodlike defect during the transformation of {113} defects into dislocation loops

From point defects to dislocation loops: A comprehensive TCAD model for self-interstitial defects in silicon

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