Nanoscale C–H/C–D mapping of organic materials using electron spectroscopy
Distinguishing hydrogen from deuterium using atomic-scale imaging and spectroscopy is crucial for identifying microscopic structures and the origins of the properties of organic materials. However, conventional structural analysis techniques for materials containing both isotopes, such as neutron scattering, provide only averaged information across the beam area. Here we utilize vibrational spectroscopy using a monochromated transmission electron microscope to discretely image hydrogen and deuterium in organic polymers at single-nanometre resolution. This technique allowed carbon-hydrogen and carbon-deuterium stretches to be mapped, which uncovered the surface segregation of the deuterated polystyrene component within a block copolymer film composed of deuterated polystyrene and poly(2-vinylpyridine). Moreover, it enabled clear visualization of the spatial distribution of hydrogenated and deuterated polystyrene on a molecular scale in a bulk block copolymer specimen containing both components. This method, integrated with coarse-grained molecular dynamics simulations, revealed a localized feature of polymer chains corresponding to the reptation tube, which could not be identified using conventional scattering techniques.
Authors
- Tomohiro Miyata (ORCID: https://orcid.org/0000-0001-7352-9640)
- Koichi Mayumi (ORCID: https://orcid.org/0000-0002-1976-3791)
- Katsumi Hagita (ORCID: https://orcid.org/0000-0002-6708-7468)
- Hsiao‐Fang Wang (ORCID: https://orcid.org/0000-0002-5884-4316)
- Hiroshi Jinnai (ORCID: https://orcid.org/0000-0003-3400-1928)
- Ryosuke Senga (ORCID: https://orcid.org/0000-0001-9225-4144)
- Kazu Suenaga (ORCID: https://orcid.org/0000-0002-6107-1123)
Institutions
- Tohoku University (JP)
- National Central University (TW)
- Osaka Research Institute of Industrial Science and Technology (JP)
- National Defense Academy of Japan (JP)
- National Institute of Advanced Industrial Science and Technology (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- Nature Nanotechnology
- Published
- 2025-03-24
- DOI
- https://doi.org/10.1038/s41565-025-01893-5
- Citations
- 6
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 3.11
Funders
- Japan Society for the Promotion of Science
- Core Research for Evolutional Science and Technology
- Precursory Research for Embryonic Science and Technology