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Cited by 295

The DOI matches its Crossref record; 115 of the 115 references it cites were found in a registry or an index.

Infrared Imaging and Spectroscopy Beyond the Diffraction Limit

Open access
Centrone, Andrea·2015·Annual Review of Analytical Chemistry

Abstract

Progress in nanotechnology is enabled by and dependent on the availability of measurement methods with spatial resolution commensurate with nanomaterials' length scales. Chemical imaging techniques, such as scattering scanning near-field optical microscopy (s-SNOM) and photothermal-induced resonance (PTIR), have provided scientists with means of extracting rich chemical and structural information with nanoscale resolution. This review presents some basics of infrared spectroscopy and microscopy, followed by detailed descriptions of s-SNOM and PTIR working principles. Nanoscale spectra are compared with far-field macroscale spectra, which are widely used for chemical identification. Selected examples illustrate either technical aspects of the measurements or applications in materials science. Central to this review is the ability to record nanoscale infrared spectra because, although chemical maps enable immediate visualization, the spectra provide information to interpret the images and characterize the sample. The growing breadth of nanomaterials and biological applications suggest rapid growth for this field.

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Crossref · 10.1146/annurev-anchem-071114-040435

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Metadata

Authors
Centrone, A.
Venue
Annual Review of Analytical Chemistry
Published
2015-07-22
Volume
8
Issue
1
Pages
101-126
ISSN
  • 1936-1327 (ISSN-L)
  • 1936-1335
OpenAlex
W2168807202
Cited by
295
References
115
FWCI
1.75
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Infrared Imaging and Spectroscopy Beyond the Diffraction Limit. https://app.cochat.ai/papers/10.1146/annurev-anchem-071114-040435
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Centrone, A. (2015). Infrared Imaging and Spectroscopy Beyond the Diffraction Limit. Annual Review of Analytical Chemistry. https://doi.org/10.1146/annurev-anchem-071114-040435

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.