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An efficient solution for correlative microscopy and co-localized observations based on multiscale multimodal machine-readable nanoGPS tags

Abstract : For a long time, investigating the same regions of interest of a sample with different instruments has been recognized as a very useful approach in various scientific fields. This paper presents an original solution for spotting the same points of interest with a high degree of accuracy and simplicity using different microscopes. It is based on small patterned tags fixed to the samples or their substrates. The patterns include an image-based position-sensing technology, for which an image of a small part of the tag can be automatically converted to absolute coordinates and angular orientation. Taking a single snapshot of the tag with an imaging instrument provides a correspondence between the sample and the coordinates of the moving stage. Co-localized observations performed with scanning electron microscopes, optical microscopes, and Raman microscopes are presented. The accuracy is in the range of a few µm up to 20 µm, which is generally sufficient to remove any ambiguity between the observed objects. The different contributions to colocalization errors are investigated experimentally and it is shown that errors related to the tags are negligible and that the main source of error is related to the accuracy of the moving stages integrated into the microscopes. A straightforward estimation of the relocalization error can be performed. It is believed that this solution will save researchers time and facilitate cooperation between laboratories.
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https://hal.archives-ouvertes.fr/hal-03229789
Contributor : Matthieu Leroy <>
Submitted on : Wednesday, May 19, 2021 - 11:38:31 AM
Last modification on : Friday, July 2, 2021 - 1:26:01 PM
Long-term archiving on: : Friday, August 20, 2021 - 6:25:09 PM

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Olivier Acher, Thanh-Liêm Nguyên, Alexander Podzorov, Matthieu Leroy, Pierre-Alix Carles, et al.. An efficient solution for correlative microscopy and co-localized observations based on multiscale multimodal machine-readable nanoGPS tags. Measurement Science and Technology, IOP Publishing, 2021, 32 (4), pp.045402. ⟨10.1088/1361-6501/abce39⟩. ⟨hal-03229789⟩

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