Paper
1 June 1992 Application of statistical models to decomposition of systematic and random error in low-voltage SEM metrology
Kevin M. Monahan, Sadri Khalessi
Author Affiliations +
Abstract
Site-to-site LVSEM measurement data on insulating samples are affected in a systematic way by the number of measurements per site. The problem stems from the fact that repeated imaging at the same site does not produce true statistical replicates since the electron dose is cumulative. Indeed, the measurement values tend to grow or shrink in direct proportion to the total dose applied. The data support a model for linewidth as a function of electron dose that includes a linear term for systematic error and a reciprocal square root term as a scaling parameter for random error. We show that charging samples such a resist on oxide, where measurements are dominated by site-to-site variation in the systematic error, should be measured at low electron dose. Conversely, conducting samples such as polysilicon on oxide, where the measurements are dominated by random error, should be measured at relatively high electron dose.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kevin M. Monahan and Sadri Khalessi "Application of statistical models to decomposition of systematic and random error in low-voltage SEM metrology", Proc. SPIE 1673, Integrated Circuit Metrology, Inspection, and Process Control VI, (1 June 1992); https://doi.org/10.1117/12.59783
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Cited by 1 scholarly publication.
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KEYWORDS
Error analysis

Oxides

Data modeling

Metrology

Imaging systems

Statistical analysis

Scanning electron microscopy

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