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DA, Bo
Address
305-0044 1-1 Namiki Tsukuba Ibaraki JAPAN [Access]

Research

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.

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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.

PublicationsNIMS affiliated publications since 2004.

Research papers
Patents
  • No. 6796858 3次元ラマン分光方法 (2020)
  • No. 6677943 顕微分光データ測定装置および方法 (2020)
  • No: 2017181192 顕微分光データ測定装置および方法 (2017)
  • No: 2018146410 3次元ラマン分光方法 (2018)
  • No: 2021071287 被測定細胞の弾性特性分布を解析する方法及び装置、並びに原子間力顕微鏡の探針の形状パラメータを定める方法及び装置 (2021)

Awards

  • 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)
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