Wide-field optical detection of nanoparticles using on-chip microscopy and self-assembled nanolenses

Journal name:
Nature Photonics
Volume:
7,
Pages:
247–254
Year published:
DOI:
doi:10.1038/nphoton.2012.337
Received
Accepted
Published online
Corrected online

Abstract

The direct observation of nanoscale objects is a challenging task for optical microscopy because the scattering from an individual nanoparticle is typically weak at optical wavelengths. Electron microscopy therefore remains one of the gold standard visualization methods for nanoparticles, despite its high cost, limited throughput and restricted field-of-view. Here, we describe a high-throughput, on-chip detection scheme that uses biocompatible wetting films to self-assemble aspheric liquid nanolenses around individual nanoparticles to enhance the contrast between the scattered and background light. We model the effect of the nanolens as a spatial phase mask centred on the particle and show that the holographic diffraction pattern of this effective phase mask allows detection of sub-100 nm particles across a large field-of-view of >20 mm2. As a proof-of-concept demonstration, we report on-chip detection of individual polystyrene nanoparticles, adenoviruses and influenza A (H1N1) viral particles.

At a glance

Figures

  1. Experimental setup, numerical model and sample preparation.
    Figure 1: Experimental setup, numerical model and sample preparation.

    a, Lensfree pixel super-resolution holography schematic (Z1  8–12 cm, Z2  300 µm). Discrete lateral shifts of the fibre-coupled source create sub-pixel (<1.12 µm) image shifts on the detector plane, which are used to generate a pixel super-resolved holographic image. b, Self-assembled liquid nanolens (meniscus) shapes for different substrate (θs) and particle (θp) contact angles (iiii), and SEM images of beads with (iv) and without (v) desiccated residue from a nanolens. Inset to iv: three-dimensional model used in the optical simulations. c, Overview of the sample preparation technique.

  2. Large-FOV lensfree holographic microscopy of nanoparticles.
    Figure 2: Large-FOV lensfree holographic microscopy of nanoparticles.

    a,b, Full FOV of the CMOS chip (a) and a zoomed-in region (b). The large black marks in a facilitate registration with the SEM images. The green square in a is also shown, expanded, in Fig. 3. c,d, Raw lensfree Bayer-pattern RGB images (c) are converted into high-resolution monochrome holograms (d) via pixel super-resolution. e, Reconstructing the super-resolved holographic images enables the detection of single nanoparticles. f, This is verified by SEM. Various other SEM FOVs and their lensfree reconstruction comparisons are included in Fig. 3 and Supplementary Figs S3–S6. Scale bars, 5 µm.

  3. Lensfree holographic reconstructions of nanoparticles.
    Figure 3: Lensfree holographic reconstructions of nanoparticles.

    ag, Similar to Fig. 2b–f, the green square region from Fig. 2a is reconstructed to demonstrate the robustness of nanolens formation and lensfree holography across a large FOV (verified by SEM images). hn, Demonstration of improvement in contrast and SNR of 95 nm particles using pixel super-resolution. With ≥16 sub-pixel-shifted lensfree frames (ik), individual nanoparticles are detectable using nanolenses. SNR values correspond to the 95 nm particle within the red square. For comparison (h), a bright-field, oil-immersion ×100 objective lens (NA = 1.25) image of the same sample is shown with intensity cross-sections. Scale bars, 5 µm (bd,g); images in eg have the same scale.

  4. Lensfree holographic detection of 198 nm and 95 nm polystyrene beads with and without self-assembled nanolenses.
    Figure 4: Lensfree holographic detection of 198 nm and 95 nm polystyrene beads with and without self-assembled nanolenses.

    Using lensfree microscopy, neither 198 nm (ad) nor 95 nm beads (il) can be detected using regular smears without nanolenses. In contrast, the formation of liquid nanolenses enables holographic detection of both bead sizes via amplitude and phase images (eg,mo). Nanolens-based lensfree holographic images (f,g,n,o) (cropped from a much larger FOV of >20 mm2) are in good agreement with ×100 oil-immersion objective lens (NA = 1.25) images of the same samples (h,p), although the contrast is relatively poor in these bright-field images.

  5. Simulated digital holographic reconstructions illustrating how liquid nanolenses enable the detection of otherwise undetectable 95 nm particles.
    Figure 5: Simulated digital holographic reconstructions illustrating how liquid nanolenses enable the detection of otherwise undetectable 95 nm particles.

    a, The results of an FDTD simulation are holographically propagated and then reconstructed. b, The thin lens model is used to generate the holograms. In these simulations a super-resolved pixel size of 0.28 µm is used. Both amplitude and phase reconstructions are shown in each case, with the nanoparticle located at the centre of the frame. The standard deviation of the Gaussian noise added to the lensfree holograms is 1% of the mean hologram intensity.

  6. Detection of viruses.
    Figure 6: Detection of viruses.

    Lensfree pixel super-resolved holographic detection of individual influenza A (H1N1) viruses (ac,eg,ik) and adenoviruses (mo). Holographic fringes for adenoviruses are weak due to their smaller size (<100 nm). Bright-field oil-immersion objective lens (×100, NA = 1.25) images of H1N1 samples are shown for comparison (d,h,l). p, Because adenoviruses could not be observed under bright-field microscopy, SEM was instead used for their verification. q,r, A tilted SEM image of a single H1N1 virus surrounded by a liquid nanolens desiccated by SEM sample preparation is shown (q), as is a normal-incidence SEM image of a single adenovirus (r).

Change history

Corrected online 13 February 2013
In the version of this Article originally published online, the particle contact angle θp in Fig. 1b,ii should have been labelled as 50°. This has now been corrected in the HTML and PDF versions of the Article.

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Author information

  1. These authors contributed equally to this work

    • Onur Mudanyali &
    • Euan McLeod

Affiliations

  1. Electrical Engineering Department, University of California, Los Angeles, California 90095, USA

    • Onur Mudanyali,
    • Euan McLeod,
    • Wei Luo,
    • Alon Greenbaum,
    • Ahmet F. Coskun &
    • Aydogan Ozcan
  2. Bioengineering Department, University of California, Los Angeles, California 90095, USA

    • Onur Mudanyali,
    • Euan McLeod,
    • Wei Luo,
    • Alon Greenbaum,
    • Ahmet F. Coskun &
    • Aydogan Ozcan
  3. CEA, LETI, MINATEC, 17 rue des Martyrs, 38054 Grenoble cedex 9, France

    • Yves Hennequin &
    • Cédric P. Allier
  4. California NanoSystems Institute, University of California, Los Angeles, California 90095, USA

    • Aydogan Ozcan
  5. Department of Surgery, David Geffen School of Medicine, University of California, Los Angeles, California 90095, USA

    • Aydogan Ozcan

Contributions

O.M. performed the experiments and processed the resulting data. E.M. developed the theory and conducted numerical simulations and the related analysis. E.M., W.L., A.G and A.F.C. assisted in conducting the experiments and data analysis. O.M., E.M., Y.H., C.P.A. and A.O. planned the research and O.M., E.M. and A.O. wrote the manuscript. A.O. supervised the project.

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