Predicting Dielectric Function from Scattering-Type Scanning-Near-Field Optical Microscopy (s-SNOM)

When and Where

Nov 29, 2023
2:00pm - 2:15pm

Hynes, Level 3, Room 303

Presenter

Tom Vincent

Xinyun Liu

Daniel Johnson

Lars Mester

Nathaniel Huang

Olga Kazakova

Jessica Boland

Co-Author(s)

Tom Vincent¹,Xinyun Liu¹,Daniel Johnson^1,2,Lars Mester³,Nathaniel Huang²,Olga Kazakova²,Jessica Boland^1,2

Photon Science Institute, University of Manchester¹,National Physical Laboratory²,Attocube Systems AG³

Abstract

Tom Vincent¹,Xinyun Liu¹,Daniel Johnson^1,2,Lars Mester³,Nathaniel Huang²,Olga Kazakova²,Jessica Boland^1,2

Photon Science Institute, University of Manchester¹,National Physical Laboratory²,Attocube Systems AG³

Scattering-type scanning near-field optical microscopy (s-SNOM) is a powerful tool that enables optical microscopy and spectroscopy with extreme sub-wavelength spatial resolution [1]. It is used heavily to characterise optical metamaterials, low-dimensional materials, and surface states in topological insulators, which may have nanoscale dimensions that can’t be detected by traditional optical microscopy. But relating material dielectric function to the observed optical contrast requires modelling the interaction between a SNOM tip and the sample, which can be both conceptually and computationally challenging. The finite dipole model (FDM) has shown excellent agreement between experimental and modelled data based on known dielectric functions [2]–[4]. However to date there are only a few works that fit the FDM to experimental SNOM data to retrieve unknown dielectric functions [5]–[7]. In this work, we investigate in-detail how the FDM relates the dielectric function to the observed optical contrast. We demonstrate its application on real SNOM spectra from topological insulator thin films and InN nanoparticles, with reference to measurements simulated by our soon-to-be-released modelling package, pysnom. We identify the key challenges involved in fitting to the FDM, including non-unique solutions and finite size effects, and we present the strategies we’ve developed to overcome them. By following the steps outlined in this presentation, and taking advantage of our optimised code library, we hope that extracting quantitative measurements of dielectric function from SNOM experiments will become more achievable for the wider scientific community. [1] F. Keilmann and R. Hillenbrand, “Near-field microscopy by elastic light scattering from a tip,” Philos. Trans. R. Soc. London. Ser. A Math. Phys. Eng. Sci., vol. 362, no. 1817, pp. 787–805, Apr. 2004, doi: 10.1098/rsta.2003.1347. [2] A. Cvitkovic, N. Ocelic, and R. Hillenbrand, “Analytical model for quantitative prediction of material contrasts in scattering-type near-field optical microscopy,” Opt. Express, vol. 15, no. 14, p. 8550, 2007, doi: 10.1364/oe.15.008550. [3] B. Hauer, A. P. Engelhardt, and T. Taubner, “Quasi-analytical model for scattering infrared near-field microscopy on layered systems,” Opt. Express, vol. 20, no. 12, p. 13173, Jun. 2012, doi: 10.1364/OE.20.013173. [4] L. Mester, A. A. Govyadinov, S. Chen, M. Goikoetxea, and R. Hillenbrand, “Subsurface chemical nanoidentification by nano-FTIR spectroscopy,” Nat. Commun., vol. 11, no. 1, p. 3359, Dec. 2020, doi: 10.1038/s41467-020-17034-6. [5] F. Mooshammer et al., “Nanoscale Near-Field Tomography of Surface States on (Bi 0.5 Sb 0.5 ) 2 Te 3,” Nano Lett., vol. 18, no. 12, pp. 7515–7523, Dec. 2018, doi: 10.1021/acs.nanolett.8b03008. [6] C. Lupo et al., “Quantitative infrared near-field imaging of suspended topological insulator nanostructures,” pp. 1–23, Dec. 2021, [Online]. Available: http://arxiv.org/abs/2112.10104 [7] A. A. Govyadinov, S. Mastel, F. Golmar, A. Chuvilin, P. S. Carney, and R. Hillenbrand, “Recovery of Permittivity and Depth from Near-Field Data as a Step toward Infrared Nanotomography,” ACS Nano, vol. 8, no. 7, pp. 6911–6921, Jul. 2014, doi: 10.1021/nn5016314.