Journal Article

Spectrum adapted expectation-maximization algorithm for high-throughput peak shift analysis

Nagata, Kenji, Ando, Yasunobu, Akaho, Shotaro, Matsumura, Tarojiro, Nagamura, Naoka

2019

Overview

We introduce a spectrum-adapted expectation-maximization (EM) algorithm for high-throughput analysis of a large number of spectral datasets by considering the weight of the intensity corresponding to the measurement energy steps. Proposed method was applied to synthetic data in order to evaluate the performance of the analysis accuracy and calculation time. Moreover, the proposed method was performed to the spectral data collected from graphene and MoS 2 field-effect transistors devices. The calculation completed in less than 13.4 s per set and successfully detected systematic peak shifts of the C 1s in graphene and S 2p in MoS 2 peaks. This result suggests that the proposed method can support the investigation of peak shift with two advantages: (1) a large amount of data can be processed at high speed; and (2) stable and automatic calculation can be easily performed.

• Publisher: Taylor & Francis,Taylor & Francis Ltd,Taylor & Francis Group
• Subject: 502 Electron spectroscopy / 60 New topics / Others / Algorithms / EM algorithm / Field effect transistors / Graphene / Ions / machine learning / Mathematical analysis / Maximization / Molybdenum disulfide / New Topics/Others / Optimization / Other / peak separation / Semiconductor devices / spectral data / XPS analysis