Energetics of Self-Interstitial Clusters in Si

Cowern, N.E.B.; Mannino, Giovanni; Stolk, P. A.; Roozeboom, F.; Huizing, H.G.A.; Berkum, J. G. M. van; Cristiano, Fuccio; Claverie, A.; Jaraı́z, M.

doi:10.1103/physrevlett.82.4460

Cited by 318 publications

(227 citation statements)

References 16 publications

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“…The various predicted structures were found to be in excellent structural agreement with microscopy observations and electronic-structure calculations. [2][3][4][5][6][7] Overall, the three different potentials employed, namely, the environment-dependent interatomic potential ͑EDIP͒, 8 Tersoff, 9 and Stillinger-Weber ͑SW͒, 10 all predicted consistent overall trends, leading to a qualitatively coherent picture for some aspects of selfinterstitial clustering in silicon. In particular, it was found that cluster morphology is sensitively dependent on both the temperature and stress within the lattice.…”

Section: Introductionmentioning

confidence: 99%

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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: Introductionmentioning

confidence: 99%

“…2, which was based on comparisons of cluster concentrations measured as a function of time, generates estimates for effective formation free energies, rather than just energies. In other words, our previous results suggest that the reason why the model regression in Ref.…”

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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“…they are formed with extra Si atoms precipitated as clusters. A study about the smaller precursor clusters that nucleate and grow into {311}'s was reported by Cowern et al [4]. Based on experimental observations [5], the unfaulting of the {311} defects is the source of the subthreshold DLs in non-amorphized ion-implanted silicon, i.e.…”

Section: Introductionmentioning

confidence: 99%

“…A considerable effort, using both continuum [4], [7]- [13] and atomistic [14]- [16] approaches, has been devoted to the understanding of the physical mechanisms that control the nucleation, growth and dissolution of such defects. The continuum method however, is limited by the number of equations that can be solved without running into prohibitive CPU demands and/or convergence instabilities.…”

Section: Introductionmentioning

confidence: 99%

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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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An improved model for boron diffusion and activation in silicon

et al. 2009

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Technologies such as solid-phase epitaxial regrowth and millisecond annealing techniques have led to a wide range of maximum temperatures and heating rates for activating dopants and eliminating ion implantation damage for transistor junction formation. Developing suitable annealing strategies depends on mathematical models that incorporate accurate defect physics. The present work describes a model that includes a newly discovered representation of defect annihilation at surfaces and of near-surface band bending, together with an improved representation of interstitial clustering. Key parameters are determined by maximum likelihood (ML) estimation and maximum a posteriori (MAP) estimation. The model yields a substantially improved ability to model the behavior of implanted boron over a wide range of annealing conditions.

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Energetics of Self-Interstitial Clusters in Si

Cited by 318 publications

References 16 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

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

An improved model for boron diffusion and activation in silicon

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