SAMURAI - NIMS Researchers Database

HOME > プロフィール > 達 博

研究内容

Keywords

Nanomaterial, Surface analysis, Background signal, Secondary electron

Dr Bo Da has been engaged in developing novel measurement-analysis methods to extract more information from measured spectra by surface analysis techniques. For instance, he developed the reverse Monte Carlo method to extract optical constant of bulk material from measured surface electron spectra, and the extended Mermin method to determine low energy electron mean free path of bulk material. Most recently, Da’s research focus has been largely related to development of new measurement-analysis method for nanomaterial samples. The virtual substrate method developed by him represents a benchmark for surface analysis to provide “free-standing” information about supported nanomaterials, and brought him President’s Prize awarded by NIMS. He has had ten first-author papers related to these new methods published in various journals, including Nature Communications, Physical Review Letters and Journal of Applied Physics, among others.

researchPicture

Characterization techniques available for bulk or thin-film solid-state materials have been extended to substrate-supported nanomaterials, but generally non-quantitatively. This is because the nanomaterial signals are inevitably buried in the signals from the underlying substrate in common reflection-configuration techniques. Here, we propose a virtual substrate method, inspired by the four-point probe technique for resistance measurement as well as the chop-nod method in infrared astronomy, to characterize nanomaterials without the influence of underlying substrate signals from four interrelated measurements. This method in secondary electron (SE) microscopy, a SE spectrum (white electrons) associated with the reflectivity difference between two different substrates can be tracked and controlled. The SE spectrum is used to quantitatively investigate the covering nanomaterial based on subtle changes in the transmission of the nanomaterial with high efficiency rivaling that of conventional core-level electrons. The virtual substrate method represents a benchmark for surface analysis to provide “free-standing” information about supported nanomaterials.

所属学会

日本表面真空学会

受賞履歴

  • 倉田奨励金 (2023)
  • 花王科学奨励賞 (2020)
  • Best Poster Award, by the Executive Committee of Joint Symposium on Materials Integration and Advanced Materials Characterization, Japan (Tsukuba). (2018)
  • President’s Prize for Advances in Science and Technology for Young Scientists, by National Institute for Materials Science, Japan (Tsukuba). (2017)
  • Best Poster Award, by the Executive Committee of Joint Symposium on Intercommunity and Measurement, Japan (Tsukuba). (2016)
  • Best Poster Award, by the Executive Committee of Joint Symposium on Intercommunity and Measurement, Japan (Tsukuba). (2014)
  • Student Award, by The 141st Committee on Microbeam Analysis of Japan Society for the Promotion of Science, Korea (Seoul). (2011)
  • Best Poster Award, by The Surface Science Society of Japan, Japan (Tokyo). (2011)
マテリアル基盤研究センター
タイトル

Heuristic data-driven spectral analysis for nanomaterial information embed in the background

キーワード

Nanomaterial, Surface analysis, Background signal, Secondary electron

概要

Low energy electron–electron interactions in nanomaterial, low energy electron transport properties of nanomaterial, electronic properties of nanomaterial at low energies. Extracting meaningful information from the background and characterizing material using energy-filtered scanning electron microscopy.

新規性・独創性

1. finding proper AD descriptors that meet the actual requirement according to the experience learned from many measurements under different experimental conditions
2. an extension of the traditional data-driven analysis approach
3. holds immense potential to become a new benchmark method in data processing

内容

image

Firstly, the proposed heuristic data-driven analysis method represents a benchmark to extract meaningful information from background data, which, in principle, can be easily implemented in many more reflection-configuration techniques than surface analysis techniques and does not demand extra investment in equipment. Therefore, such technique will generate broad interest from numerous fields that use reflection-onfiguration techniques for ultrathin material characterization.

Secondly, implemented in SE spectra, this method expands the energy scale of analysis down to several electron volts and thus allows one to quantitatively probe the e–e interactions of a nanomaterial and hold to potential to observe ‘hidden’ electronic energy transfer to and from a nanomaterial on a substrate.

Finally, with the exploit of SE signals, the heuristic data-driven analysis method can be extended to energy-filtered SEM for material characterization, and rival conventional techniques based on core-level signals in signal-to-noise ratio by orders of magnitude, holding great potential for manufacture monitoring and quality control. This new technique is of particularly importance for steel industry because the nanometer-thick passive films on stainless steel could be automatically characterized without any additional procedures other than processing scanning energy-filtered SEM images.

まとめ

The virtual substrate method represents a benchmark for surface analysis to provide “free-standing” information about supported nanomaterials.

この機能は所内限定です。
この機能は所内限定です。

▲ページトップへ移動