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Abstract
Linear optical methods of determining the chirality of organic and inorganic materials have relied on weak chiral optical (chiroptical) effects. Nonlinear chiroptical characterization holds the potential of much greater sensitivity and smaller interaction volumes. However, suitable materials on which to perform measurements have been lacking for decades. Here, we present the first nonlinear chiroptical characterization of crystallographic chirality in gold helicoids (≈150 nm size) and core/shell helicoids with the newly discovered hyper-Rayleigh scattering optical activity (HRS OA) technique. The observed chiroptical signal is, on average, originating from between ≈0.05 and ≈0.13 helicoids, i.e., less than a single nanoparticle. The measured HRS OA ellipticities reach ≈3°, for a concentration ≈109 times smaller than that of chiral molecules with similar nonlinear chiroptical response. These huge values indicate that the helicoids are excellent candidates for future nonlinear chiroptical materials and applications.
Original language | English |
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Pages (from-to) | 5792-5798 |
Number of pages | 7 |
Journal | Nano Letters |
Volume | 20 |
Issue number | 8 |
Early online date | 24 Jun 2020 |
DOIs | |
Publication status | Published - 12 Aug 2020 |
Fingerprint Dive into the research topics of 'Single nanoparticle chiroptics in a liquid: optical activity in hyper-Rayleigh scattering from Au helicoids'. Together they form a unique fingerprint.
Projects
- 1 Active
Profiles
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Ventsislav Valev
- Department of Physics - Royal Society University Research Fellow & Professor of Physics
- Centre for Photonics and Photonic Materials
- Condensed Matter Physics CDT
- Centre for Nanoscience and Nanotechnology
Person: Research & Teaching
Datasets
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Dataset for "Single nanoparticle chiroptics in a liquid: optical activity in hyper-Rayleigh scattering from Au helicoids"
Ohnoutek, L. (Creator), Murphy, A. (Creator), Rasadean, D. (Creator), Pantos, D. (Creator) & Valev, V. (Creator), University of Bath, 26 Jun 2020
DOI: 10.15125/BATH-00862
Dataset