計測インフォマティクスを応用したX線顕微分光によるナノ表界面分析

抄録

Informatics techniques support improving the efficiency of data analysis in spectral imaging measurements. Applications of informatics to the measurement technique are categorized as the measurement informatics, which is growing parallel alongside with materials informatics. Recently, we introduced a spectrum-adapted expectation-maximization (EM) algorithm for high-throughput analysis of a large number of spectral datasets obtained by synchrotron soft X-ray scanning photoelectron microscopy. The advantage of the proposed method is that high-speed peak fitting can be performed with stable behavior of calculation compared to previous methods. We performed the proposed method to the series of spectra collected from graphene field-effect transistors devices. The calculation completed in less than 10 minute per set and successfully detected systematic peak shifts of the C 1s core level spectra in graphene. In contrast, the calculation time was 1day when manually performing the peak fitting by using a nonlinear least-squares method with commercial software. Moreover, we improve the spectrum-adapted EM algorithm by adopting Expectation–Conditional Maximization (ECM) algorithm to use various fitting functions and background functions. This method enables us to conduct the high-through put analysis of peak shift using various fitting functions.