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Diffusion of Phosphorus and Boron from Atomic Layer Deposition Oxides into Silicon
Author(s) -
Beljakowa Svetlana,
Pichler Peter,
Kalkofen Bodo,
Hübner René
Publication year - 2019
Publication title -
physica status solidi (a)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.532
H-Index - 104
eISSN - 1862-6319
pISSN - 1862-6300
DOI - 10.1002/pssa.201900306
Subject(s) - x ray photoelectron spectroscopy , silicon , secondary ion mass spectrometry , dopant , atomic layer deposition , boron , materials science , analytical chemistry (journal) , annealing (glass) , oxide , silicon oxide , doping , transmission electron microscopy , inorganic chemistry , chemical engineering , layer (electronics) , chemistry , nanotechnology , ion , metallurgy , optoelectronics , silicon nitride , organic chemistry , chromatography , engineering
Oxides containing group III or group V elements (B 2 O 3 /Sb 2 O 5 and P 2 O 5 /Sb 2 O 5 ) are grown by plasma‐assisted atomic layer deposition (ALD) on single‐crystalline silicon and serve as dopant sources for conformal and shallow doping. Transport phenomena in ALD‐oxide–Si structures during rapid thermal annealing (RTA) are investigated subsequently by X‐ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), and secondary ion mass spectrometry (SIMS). The XPS and TEM analyses of the annealed ALD‐oxide–Si structures demonstrate that the ALD oxide converts to a silicon oxide and partially evaporates during annealing. In addition, dopant‐containing, spherical, and partially crystalline particles form in the oxide, and Si‐P precipitates at the oxide–Si interface. After diffusion annealing at 1000 °C, the SIMS analyses reveal phosphorus and boron concentration profiles in the silicon substrate with maximum concentrations exceeding their solid solubility limits by roughly one order of magnitude. Experimental doping profiles of phosphorus and boron in silicon are compared with simulation results, considering a slight injection of self‐interstitials and dynamical defect clustering.