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Spectrum adapted the expectation-maximization algorithm for high-throughput peak shift analysis.
Matsumura, Tarojiro; Nagamura, Naoka; Akaho, Shotaro; Nagata, Kenji; Ando, Yasunobu.
Afiliação
  • Matsumura T; Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology, Tsukuba, Japan.
  • Nagamura N; Research Center for Advanced Measurement and Characterization, National Institute for Materials Science (NIMS), Tsukuba, Japan.
  • Akaho S; Japan Science and Technology Agency, PRESTO, Saitama, Japan.
  • Nagata K; Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology, Tokyo, Japan.
  • Ando Y; Japan Science and Technology Agency, PRESTO, Saitama, Japan.
Sci Technol Adv Mater ; 20(1): 733-745, 2019.
Article em En | MEDLINE | ID: mdl-31275463
ABSTRACT
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 MoS2 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 MoS2 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.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article