The fabrication of ultra large-scale integrated (ULSI) circuits with ever shrinking feature size requires a continued reduction of diffusion lengths of dopants in Si. However, boron implants undergo an “anomalous” diffusion upon annealing, which is detrimental to the ultra-shallow junction formation. Over the last decade, boron transient diffusion has been much better understood. This implantation-induced transient-enhanced diffusion is known to be driven by the large supersaturation of self-interstitial silicon atoms emitted from the extended defects. The form and evolution of implantation-induced defects with respect to implant species, energy, dose, and annealing temperature have been systematically studied. The improved understanding has led to the development of new doping techniques, such as carbon co-implant, multiple step annealing and point defect engineering (PDE) using co-implantation of high-energy ions. In the PDE approach, high-energy ion bombardments inject vacancies near the surface region and create excessive interstitials near the end of projected range deep inside the substrate. Such manipulation of point defects can retard boron diffusion and enhance the activation of boron. The control of boron diffusion could be used to form ultra-shallow junctions for next generation Si device. In this article, we review the history and recent progress in PDE.

Boron diffusion in silicon: the anomalies and control by point defect engineering

In this work the Si self-interstitial--carbon interaction has been experimentally investigated and modeled. The interactions between self-interstitials, produced by 20-keV silicon implantation, and substitutional carbon in silicon have been studied using a ${\mathrm{Si}}_{1\ensuremath{-}y}{\mathrm{C}}_{y}$ layer grown by molecular beam epitaxy (MBE) and interposed between the near-surface self-interstitial source and a deeper B spike used as a marker for the Si-interstitial concentration. The C atoms, all incorporated in substitutional sites and with a C-dose range of $7\ifmmode\times\else\texttimes\fi{}{10}^{12}--4\ifmmode\times\else\texttimes\fi{}{10}^{14}{\mathrm{a}\mathrm{t}\mathrm{o}\mathrm{m}\mathrm{s}/\mathrm{c}\mathrm{m}}^{2},$ trap the self-interstitials in such a manner that the ${\mathrm{Si}}_{1\ensuremath{-}y}{\mathrm{C}}_{y}$ layer behaves as a filtering membrane for the interstitials flowing towards the bulk and, consequently, strongly reduces the boron-enhanced diffusion. This trapping ability is related to the total C dose in the ${\mathrm{Si}}_{1\ensuremath{-}y}{\mathrm{C}}_{y}$ membrane. Substitutional carbon atoms interacting with self-interstitials are shown to trap Si interstitials, to be removed from their substitutional sites, and to precipitate into the C-rich region. After precipitation, C atoms are not able to further trap injected self-interstitials, and the interstitials generated in the surface region can freely pass through the C-rich region and produce B-enhanced diffusion. The atomistic mechanism leading to Si-interstitial trapping has been investigated by developing a simulation code describing the migration of injected interstitials. The simulation takes into account the surface recombination, the interstitial diffusion in our MBE-grown material, and C traps. Since the model calculates the amount of interstitials that actually react with C atoms, by a comparison with the experimental data it is possible to derive quantitative indications of the trapping mechanism. It is shown that one Si interstitial is able to deactivate about two C traps by means of interstitial trapping and C clustering reactions. The reaction causing trapping and deactivation is tentatively described.

Interaction between self-interstitials and substitutional C in silicon: Interstitial trapping and C clustering mechanism

The reduction of transient enhanced diffusion (TED) with reduced implantation energy has been investigated and quantified. A fixed dose of 1×1014 cm−2 Si+ was implanted at energies ranging from 0.5 to 20 keV into boron doping superlattices and enhanced diffusion of the buried boron marker layers was measured for anneals at 810, 950, and 1050 °C. A linearly decreasing dependence of diffusivity enhancement on decreasing Si+ ion range is observed at all temperatures, extrapolating to ∼1 for 0 keV. This is consistent with our expectation that at zero implantation energy there would be no excess interstitials from the implantation and hence no TED. Monte Carlo modeling and continuum simulations are used to fit the experimental data. The results are consistent with a surface recombination length for interstitials of <10 nm. The data presented here demonstrate that in the range of annealing temperatures of interest for p-n junction formation, TED is reduced at smaller ion implantation energies and that this is due to increased interstitial annihilation at the surface.

Reduction of transient diffusion from 1–5 keV Si+ ion implantation due to surface annihilation of interstitials

The implant species and dose effects of ion implantation, including crossing the amorphization threshold, on the transient enhanced diffusion (TED) behavior of a boron marker layer in silicon have been studied. It has been found that for lower implant doses, TED is species independent. However, for higher implanted doses, the dependence of TED on species becomes very significant. It has been found that at these higher doses, including amorphizing doses, P implants cause more TED than either Si or As implants. This result is explained based on the fully coupled diffusion mechanism of the impurity dopants where dopants diffuse by temporarily pairing with point defects. Additionally, both point defect clusters and extended defects such as dislocations significantly affect the dopant profile evolution of both the implanted profile and the buried marker layer. By modeling these effects, the experimental results have been simulated and a consistent parameter set has been found to fit the data to a reasonable ex...

Species and dose dependence of ion implantation damage induced transient enhanced diffusion

A physically motivated model that accounts for the spatial and temporal evolution of self-interstitial agglomerates in ion-implanted Si is presented. For the calibration of the model, a genetic algorithm is used to find the optimum set of physical parameters from experimental data. Mean-size evolution of {113} defects obtained by transmission electron microscopy and self-interstitial oversaturation results measured in the vicinity of extended defects are combined in the same fitting procedure. The calibration of parameters shows that binding energies of small self-interstitial clusters exhibit strong maxima, as reported in other investigations. Results of the calibrated model are compared to experimental data obtained in complementary investigations. It is demonstrated that the model is able to predict a wide variety of physical phenomena, from the oversaturation of self-interstitials via the mean-size evolution of {113} defects to the depth distribution of the density of the latter.

A physically based model for the spatial and temporal evolution of self-interstitial agglomerates in ion-implanted silicon

The enhanced diffusion of impurities that is seen following ion implantation is rapidly quenched, hence, the name transient enhanced diffusion (TED). The quenching of TED is associated with the annealing of implant damage, either by the diffusion of point defects to the bulk or to the surface. It is variously assumed that either the surface or the bulk is the predominant annealing site. In this work, we explore these assumptions by observing the reduction of TED in a buried marker, when the surface is etched to bring it closer to implanted damage. The results show a considerable reduction in TED with surface etching, demonstrating that the surface plays a key role in annealing implant damage. Numerical modeling allows extraction of the surface recombination length of interstitials at 800 °C. Only a value of 0.1 μm is consistent with the data. All but a very small fraction of implanted interstitials are recombined at the surface with this value.

The role of the surface in transient enhanced diffusion

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The role of the surface in transient enhanced diffusion