Precise Nanosizing with High Dynamic Range Holography

Unai Ortiz-Orruño, Ala Jo, Hakho Lee, Niek F. Van Hulst, Matz Liebel

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Optical sensing is one of the key enablers of modern diagnostics. Especially label-free imaging modalities hold great promise as they eliminate labeling procedures prior to analysis. However, scattering signals of nanometric particles scale with their volume square. This unfavorable scaling makes it extremely difficult to quantitatively characterize intrinsically heterogeneous clinical samples, such as extracellular vesicles, as their signal variation easily exceeds the dynamic range of currently available cameras. Here, we introduce off-axis k-space holography that circumvents this limitation. By imaging the back-focal plane of our microscope, we project the scattering signal of all particles onto all camera pixels, thus dramatically boosting the achievable dynamic range to up to 110 dB. We validate our platform by detecting and quantitatively sizing metallic and dielectric particles over a 200 × 200 μm field of view and demonstrate that independently performed signal calibrations allow correctly sizing particles made from different materials. Finally, we present quantitative size distributions of extracellular vesicle samples.
Original languageEnglish
Pages (from-to)317-322
JournalNano Letters
Volume21
Issue number1
DOIs
Publication statusPublished - 13 Jan 2021
Externally publishedYes

Funding

Authors acknowledge support by the Ministry of Science, Innovation, and Universities (MCIU/AEI: RTI2018-099957-J-I00 and PGC2018-096875-B-I00). N.F.v.H. acknowledges the financial support by the European Commission (ERC Advanced Grant 670949-LightNet, ERC Proof-of-Concept Grant 755196-IBIS), Ministry of Science & Innovations (“Severo Ochoa” program for Centers of Excellence in R&D CEX2019-000910-S), the Catalan AGAUR (2017SGR1369), Fundacio; Privada Cellex, Fundacio; Privada Mir-Puig, the Generalitat de Catalunya through the CERCA program and the NVIDIA Corporation Titan Xp GPU grant. H.L. was partly supported by NIH grants (R01CA229777, U01CA233360, R21DA049577) and DoD awards (W81XWH-19-1-0199, W81XWH-19-1-0194).

FundersFunder number
NVIDIA Corporation Titan Xp GPU
National Institutes of HealthU01CA233360, R01CA229777
U.S. Department of DefenseW81XWH-19-1-0199, W81XWH-19-1-0194
National Institute on Drug AbuseR21DA049577
Ministerio de Ciencia, Innovación y UniversidadesPGC2018-096875-B-I00, RTI2018-099957-J-I00
European Commission
European Research Council755196-IBIS, 670949-LightNet
Generalitat de Catalunya
Agència de Gestió d'Ajuts Universitaris i de Recerca2017SGR1369
Ministerio de Ciencia e InnovaciónCEX2019-000910-S

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