Journal
NANO LETTERS
Volume 21, Issue 19, Pages 7921-7928Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.nanolett.1c01808
Keywords
hyperlens; hyperbolic media; reconstruction algorithm; super-resolution
Categories
Funding
- Vannevar Bush Faculty Fellowship [ONR-VB: N00014-19-1-2630, NSF/EFRI-1741660]
- Programmable Quantum Materials, an Energy Frontier Research Center - U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences (BES) [DE-SC0019443]
- Quantum Materials EPIQS [9455]
- ASEE fellowship
- Office of Naval Research through the Nanoscience Institute
- Air Force Office of Scientific Research (AFOSR) [FA9550-18-1-029]
- Office of Naval Research [N00014-20-1-2427]
- National Science Foundation, Division of Materials Research [1904793]
- [ONR-N00014-18-1-2107]
- Direct For Mathematical & Physical Scien
- Division Of Materials Research [1904793] Funding Source: National Science Foundation
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This research explores the use of hyperbolic phonon polaritons in hexagonal boron nitride for super-resolution imaging, making significant advances in the field. By improving spatial resolution and developing an image reconstruction algorithm, the study successfully overcomes challenges in hyperlens imaging and offers insights for achieving far-field imaging modalities.
The hyperbolic phonon polaritons supported in hexagonal boron nitride (hBN) with long scattering lifetimes are advantageous for applications such as super-resolution imaging via hyperlensing. Yet, hyperlens imaging is challenging for distinguishing individual and closely spaced objects and for correlating the complicated hyperlens fields with the structure of an unknown object underneath. Here, we make significant strides to overcome each of these challenges. First, we demonstrate that monoisotopic h(11)BN provides significant improvements in spatial resolution, experimentally resolving structures as small as 44 nm and those with sub 25 nm spacings at 6.76 mu m free-space wavelength. We also present an image reconstruction algorithm that provides a structurally accurate, visual representation of the embedded objects from the complex hyperlens field. Further, we offer additional insights into optimizing hyperlens performance on the basis of material properties, with an eye toward realizing far-field imaging modalities. Thus, our results significantly advance label-free, high-resolution, spectrally selective hyperlens imaging and image reconstruction methodologies.
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