Maximum a posteriori estimation for high-throughput peak fitting in X-ray photoelectron spectroscopy

Abstract

We introduce a peak fitting method to estimate the model parameters and the number of peaks without using the conventional trial-and-error approach. The proposed method automatically removes excess peaks using maximum a posteriori estimation. The computation is performed efficiently by the spectrum-adapted expectation–conditional maximisation algorithm with deterministic annealing. We apply the proposed method to synthetic and experimental data from a tunnel field-effect transistor. The proposed method identified two peak components in the experimental data from a [Formula: see text] sheet, which are interpreted to be the Mo [Formula: see text] and Mo [Formula: see text] peaks. No peaks were detected on the [Formula: see text]-[Formula: see text] sheet and hexagonal boron nitride ([Formula: see text]-BN) within the measured binding energy range.

Keywords

• Peak fitting
• X-ray photoelectron spectroscopy
• maximum a posteriori estimation
• expectation–conditional maximisation algorithm
• high-throughput analysis
• Methodology, apparatus, and experimental design