The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Nanomanipulation Using Silicon Photonic Crystal Resonators
Abstract
Optical tweezers have enabled a number of microscale processes such as single cell handling, flow-cytometry, directed assembly, and optical chromatography. To extend this functionality to the nanoscale, a number of near-field approaches have been developed that yield much higher optical forces by confining light to subwavelength volumes. At present, these techniques are limited in both the complexity and precision with which handling can be performed. Here, we present a new class of nanoscale optical trap exploiting optical resonance in one-dimensional silicon photonic crystals. The trapping of 48 nm and 62 nm dielectric nanoparticles is demonstrated along with the ability to transport, trap, and manipulate larger nanoparticles by simultaneously exploiting the propagating nature of the light in a coupling waveguide and its stationary nature within the resonator. Field amplification within the resonator is shown to produce a trap several orders of magnitude stronger than conventional tweezers and an order of magnitude stiffer than other near-field techniques. Our approach lays the groundwork for a new class of optical trapping platforms that could eventually enable complex all-optical single molecule manipulation and directed assembly of nanoscale material.
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Citations
Cites
Ultra-high-Q toroid microcavity on a chip
Armani, D. K., Kippenberg, T. J., Spillane, S. M., & Vahala, K. J. (2003) · Nature · doi:10.1038/nature01371 · Cited by 2,214
Cited by
Optical Trapping of a Single Protein
Pang, Y., & Gordon, R. (2012) · Nano Letters · doi:10.1021/nl203719v · Cited by 503
Metadata
- Authors
- Mandal, S., Serey, X., & Erickson, D.
- Venue
- Nano Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2009-12-02
- Volume
- 10
- Issue
- 1
- Pages
- 99-104
- ISSN
- 1530-6984 (ISSN-L)
- 1530-6992
- OpenAlex
- W2093698359
- Cited by
- 301
- References
- 1
- FWCI
- 11.52
- Type
- journal article
- Language
- en
- Open access
- closed
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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.