Phosphorus vacancy cluster model for phosphorus diffusion gettering of metals in Si

Chen, Renyu; Trzynadlowski, Bart C.; Dunham, Scott T.

doi:10.1063/1.4864377

Cited by 27 publications

(28 citation statements)

References 27 publications

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“…Consequently, the formation enthalpy of the P 4 V complex, where the vacancy is surrounded on all sides by a P atom, is found to be negative (À0.31 eV), indicating that its formation is a spontaneous process from a thermodynamic perspective. (A similar behavior for the formation of P 4 V complex is also reported by Chen et al 14 in their studies on gettering.) The question arises whether two such P n V clusters can co-exist next to each other forming a divacancy configuration.…”

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confidence: 85%

On the manifestation of phosphorus-vacancy complexes in epitaxial Si:P films

Dhayalan

Kujala

Slotte

et al. 2016

Applied Physics Letters

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In situ doped epitaxial Si:P films with P concentrations >1 × 1021 at./cm3 are suitable for source-drain stressors of n-FinFETs. These films combine the advantages of high conductivity derived from the high P doping with the creation of tensile strain in the Si channel. It has been suggested that the tensile strain developed in the Si:P films is due to the presence of local Si3P4 clusters, which however do not contribute to the electrical conductivity. During laser annealing, the Si3P4 clusters are expected to disperse resulting in an increased conductivity while the strain reduces slightly. However, the existence of Si3P4 is not proven. Based on first-principles simulations, we demonstrate that the formation of vacancy centered Si3P4 clusters, in the form of four P atoms bonded to a Si vacancy, is thermodynamically favorable at such high P concentrations. We suggest that during post epi-growth annealing, a fraction of the P atoms from these clusters are activated, while the remaining part goes into interstitial sites, thereby reducing strain. We corroborate our conjecture experimentally using positron annihilation spectroscopy, electron spin resonance, and Rutherford backscattering ion channeling studies.

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confidence: 85%

On the manifestation of phosphorus-vacancy complexes in epitaxial Si:P films

Dhayalan

Kujala

Slotte

et al. 2016

Applied Physics Letters

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“…As proposed in the model by Chen et al, 15 we assume a complex of P 4 V-Fe with a binding energy of 1.52 eV. In our model, P 4 V is the only complex for clustered phosphorus.…”

Section: Gettering Mechanismsmentioning

confidence: 99%

Main defect reactions behind phosphorus diffusion gettering of iron

Schön

Vähänissi

Haarahiltunen

et al. 2014

Journal of Applied Physics

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Phosphorus diffusion is well known to getter effectively metal impurities during silicon solar cell processing. However, the main mechanisms behind phosphorus diffusion gettering are still unclear. Here, we analyze the impact of oxygen, phosphosilicate glass as well as active and clustered phosphorus on the gettering efficiency of iron. The results indicate that two different mechanisms dominate the gettering process. First, segregation of iron through active phosphorus seems to correlate well with the gettered iron profile. Secondly, immobile oxygen appears to act as an effective gettering sink for iron further enhancing the segregation effect. Based on these findings, we present a unifying gettering model that can be used to predict the measured iron concentrations in the bulk and in the heavily phosphorus doped layers and explains the previous discrepancies reported in the literature

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“…At least eight research groups have developed tools to simulate the evolution of iron during solar cell processing [21][22][23][24][25][26][27][28]. These Simulators differ in two significant ways: (1) physics: they make different assumptions regarding the governing physics of nucleation, precipitation, growth, and dissolution of iron-silicide precipitates, and (2) implementation: they use different coding environments, with unique mesh assumptions and numerical solvers.…”

Section: Introductionmentioning

confidence: 99%

Building intuition of iron evolution during solar cell processing through analysis of different process models

et al. 2015

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An important aspect of Process Simulators for photovoltaics is prediction of defect evolution during device fabrication. Over the last twenty years, these tools have accelerated process optimization, and several Process Simulators for iron, a ubiquitous and deleterious impurity in silicon, have been developed. The diversity of these tools can make it difficult to build intuition about the physics governing iron behavior during processing. Thus, in one unified software environment and using self-consistent terminology, we combine and describe three of these Simulators. We vary structural defect distribution and iron precipitation equations to create eight distinct Models, which we then use to simulate different stages of processing. We find that the structural defect distribution influences the final interstitial iron concentration ([Fe,]) more strongly than the iron precipitation equations. We identify two regimes of iron behavior: (1) diffusivity-limited, in which iron evolution is kinetic ally limited and bulk [Fe,] predictions can vary by an order of magnitude or more, and (2) solubility-limited, in which iron evolution is near thermodynamic equilibrium and the Models yield similar results. This rigorous analysis provides new intuition that can inform Process Simulation, material, and process development, and it enables scientists and engineers to choose an appropriate level of Model complexity based on wafer type and quality, processing conditions, and available computation time.

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Phosphorus vacancy cluster model for phosphorus diffusion gettering of metals in Si

Cited by 27 publications

References 27 publications

On the manifestation of phosphorus-vacancy complexes in epitaxial Si:P films

On the manifestation of phosphorus-vacancy complexes in epitaxial Si:P films

Main defect reactions behind phosphorus diffusion gettering of iron

Building intuition of iron evolution during solar cell processing through analysis of different process models

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