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Comparison of Different Characterization Techniques for Plasma Implanted Samples Having Highly Doped and Shallow Implanted Layers: Dose Measurement, Profile, Etching or Deposition Characterizations

AIP conference proceedings(2011)

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摘要
Plasma doping has been accepted into semiconductor manufacturing for low energy, high dose implant applications. As a consequence, plasma implanted samples often have very high concentration doped layers (> 1 x 10(21)/cm(3)) of very thin depth (<10 nm). Thus, well-known characterization techniques, such as SIMS, to measure dose and implantation thickness must be used carefully because of high matrix effects. Another problem is due to the fact that plasma-surface interactions can lead to parasitic etching (mainly with halide precursors) or deposition (mainly with hydride precursors). The aim of this study is to compare different characterization methods and to determine the best one to use depending on implantation conditions and desired parameter (dose, profile, surface chemistry ...). In this study, 300 mm and 200 mm Si wafers were implanted using PULSION (Plasma doping tool from IBS) using several precursors (BF3, B2H6) at low and high doses and under different conditions to promote etching or deposition. As-implanted surface characterization was performed using SIMS comparing several protocols: low energy SIMS using standard and MCs modes and PCOR-SIMS from EAG. Results are compared with XPS measurements and TEM analysis for deposition and etching determination. Some samples were characterized using the Shallow Probe from CAMECA. The Shallow Probe tool is based on LEXES, a specialized EPMA technique to study thin layers and shallow implants. It is a surface technique ideally suited to analyze highly doped USJ, and the tool is widely used to monitor dose. In this work, dose and depth information (in the form of the depth at the critical concentration similar to 5 x 10(18)at/cm(3)) are compared to 'reference' techniques such as SIMS.
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关键词
Plasma doping,ion implantation,SIMS,LEXES,Uniformity mapping
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