Virtual substrate method for nanomaterials characterization

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 reflectio...

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Bibliographic Details
Published in:Nature communications 2017-05, Vol.8 (1), p.15629-15629, Article 15629
Main Authors: Da, Bo, Liu, Jiangwei, Yamamoto, Mahito, Ueda, Yoshihiro, Watanabe, Kazuyuki, Cuong, Nguyen Thanh, Li, Songlin, Tsukagoshi, Kazuhito, Yoshikawa, Hideki, Iwai, Hideo, Tanuma, Shigeo, Guo, Hongxuan, Gao, Zhaoshun, Sun, Xia, Ding, Zejun
Format: Article
Language:English
Subjects:
119/118
140/133
639/301/357
639/301/357/918
639/766/930/12
Astronomy
Humanities and Social Sciences
multidisciplinary
Nanotechnology
Science
Science (multidisciplinary)
Substrates
Thin films
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Summary: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. By implementing 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 rivalling that of conventional core-level electrons. The virtual substrate method represents a benchmark for surface analysis to provide ‘free-standing’ information about supported nanomaterials. Quantitative characterization of supported nanomaterials is challenging, because the nanomaterial signals cannot easily be deconvoluted from those of the substrate. Here, the authors introduce an inventive approach to overcome this problem for electron-based surface analysis techniques.
ISSN:2041-1723
2041-1723
DOI:10.1038/ncomms15629