Energy dependence of transient enhanced diffusion and defect kinetics

Saleh, Hugo; Law, Mark E.; Bharatan, S.; Jones, K. S.; Krishnamoorthy, V.; Büyüklimanli, Temel

doi:10.1063/1.126894

Cited by 12 publications

(7 citation statements)

References 6 publications

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“…As stated in [1], the calibration of the model for small interstitial clusters and {311} defects is based on the interstitial supersaturation evolution data extracted from boron marker layers experiments [10,11] and on the data of interstitial concentration in {311} defects as well as {311} density extracted from TEM measurements [12][13][14][15][16]. For experiments with relatively low interstitial dose and small thermal budget, no dislocation loops can nucleate.…”

Section: Resultsmentioning

confidence: 99%

Efficient TCAD Model for the Evolution of Interstitial Clusters, {311} Defects, and Dislocation Loops in Silicon

2007

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The simulation of deep-submicron silicon-device manufacturing processes relies on predictive models for extended defect clusters. For submicroscopic interstitial clusters and {311} defects, an efficient and highly accurate model for process simulation has been developed and calibrated recently [1]. This model combines equations for three small interstitial clusters and two moments for {311} defects. In this work, we extend this model to include dislocation loops and to reproduce a greatly increased range of experimental data, including thermal annealing of end-of-range defects after amorphizing implants.

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Section: Resultsmentioning

confidence: 99%

Efficient TCAD Model for the Evolution of Interstitial Clusters, {311} Defects, and Dislocation Loops in Silicon

2007

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“…This may be expected due to the projected range ͑100 Å͒ being furthest from the interface. [12][13][14] The presence of a higher supersaturation of excess interstitials may be the reason fewer extended defects are observed. 4.…”

Section: Discussionmentioning

confidence: 99%

Influence of the surface Si/buried oxide interface on extended defect evolution in silicon-on-insulator scaled to 300 Å

Saavedra

Frazer

Jones

et al. 2002

Journal of Vacuum Science &Amp; Technology B: Microelectronics and Nanometer Structures Processing, Measurement, and Phenomena

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As device dimensions continue to be scaled, incorporation of silicon-on-insulator ͑SOI͒ as mainstream complementary metal-oxide-semiconductor technology also increases. This experiment set out to further investigate the effect of the surface Si/buried oxide ͑BOX͒ interface on the formation and dissolution of extended defects in SOI. UNIBOND® wafers were thinned to 300, 700, and 1600 Å. Si ϩ ion implantation was performed from 5 to 40 keV with a constant, nonamorphizing dose of 2ϫ10 14 cm Ϫ2 . Inert ambient furnace anneals were performed at 750°C for times of 5 min up to 8 h. Transmission electron microscopy was used to study the evolution of extended defects, as well as to quantify the number of trapped interstitials. It is observed that the surface Si/BOX interface does not enhance the dissolution rate of extended defects unless у15% of the dose is truncated by the BOX. Further, no reduction in the trapped interstitial concentration is seen unless у6% of the dose is truncated. It is concluded that the surface Si/BOX interface does not serve as a significant sink for interstitial recombination, as long as the interstitial profile is mostly confined to the surface Si layer.

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“…Saleh et al 13 varied the distance to the surface, with implantation energies from 20 to 160 keV, and measured the characteristic time constants for TED ͑by measuring the junction depth broadening of a boron marker layer and assuming an exponential decay in diffusivity with time͒ and ͕113͖ defect dissolution ͑measured from the slope of the fast decay region of the Si interstitial dose in ͕113͖ defects versus time͒. They observed that while the characteristic time for TED clearly increases with the implanted energy-distance to the surface, the characteristic time for ͕113͖ defect dissolution varies very weakly with the implanted energy.…”

Section: A Spatial and Temporal Evolution Of A Layer Ofˆ113‰ Defectsmentioning

confidence: 98%

“…They showed that the ͕113͖ defects dissolve uniformly across the layer, and the width of the layer does not change until the ͕113͖ defects nearly completely dissolve. Saleh et al 13 claimed no correlation between TED and ͕113͖ dissolution since TED depends strongly on implant energy but the ͕113͖ dissolution is weakly dependent.…”

Section: Introductionmentioning

confidence: 98%

“…However, even in those cases in which ͕113͖ defects are observed, many controversies are found in the literature about the role of the surface in the interstitial removal from ͕113͖ defects and about the correlation between TED and ͕113͖ defects. [9][10][11][12][13] The role of the silicon surface in the removal of point defects has been investigated by Lim et al 9 These authors have shifted the position of the surface in relation to the damage by the use of chemical etching. Their results indicated that surface proximity reduces TED and the surface behaves as an efficient sink for Si interstitials.…”

Section: Introductionmentioning

confidence: 99%

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Atomistic analysis of defect evolution and transient enhanced diffusion in silicon

Aboy

Pelaz

Marqués

et al. 2003

Journal of Applied Physics

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Kinetic Monte Carlo simulations are used to analyze the ripening and dissolution of small Si interstitial clusters and {113} defects, and its influence on transient enhanced diffusion of dopants in silicon. The evolution of Si interstitial defects is studied in terms of the probabilities of emitted Si interstitials being recaptured by other defects or in turn being annihilated at the surface. These two probabilities are related to the average distance among defects and their distance to the surface, respectively. During the initial stages of the defect ripening, when the defect concentration is high enough and the distance among them is small, Si interstitials are mostly exchanged among defects with a minimal loss of them to the surface. Only when defects grow to large sizes and their concentration decreases, the loss of Si interstitials through diffusion to the surface prevails, causing their dissolution. The presence of large and stable defects near the surface is also possible when the implant energy is low—small distance to the surface—but the dose is high enough—even smaller distance among defects. The exchange of Si interstitials among defects sets a interstitial supersaturation responsible for the temporary enhancement of the diffusivity of interstitial diffusing dopants. The transitory feature of the enhancement is well correlated to the extinction of the Si interstitial defects.

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Energy dependence of transient enhanced diffusion and defect kinetics

Cited by 12 publications

References 6 publications

Efficient TCAD Model for the Evolution of Interstitial Clusters, {311} Defects, and Dislocation Loops in Silicon

Efficient TCAD Model for the Evolution of Interstitial Clusters, {311} Defects, and Dislocation Loops in Silicon

Influence of the surface Si/buried oxide interface on extended defect evolution in silicon-on-insulator scaled to 300 Å

Atomistic analysis of defect evolution and transient enhanced diffusion in silicon

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