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Research data supporting "Tailoring ultrahigh index plasmonic combinatorial metamaterials for SEIRA and SERS by tuning the fill fraction"

Repository URI

https://www.repository.cam.ac.uk/handle/1810/387668

Repository DOI

https://doi.org/10.17863/CAM.120356
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Files

Tunable_MLagg_Optica_Open_Data_Final.zip (2.83 MB)

Type

Dataset

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Authors

Description

This dataset contains raw spectral data for each main and supplementary figure of a publication showing tunable high refractive index combinatorial metamaterials for surface-enhanced infrared absorption (SEIRA) and Raman spectroscopy (SERS). The SEIRA and IR data are all referenced to a gold mirror and measured in reflection mode, using 200 scans per measurement. The dark field (DF) scattering data is referenced to a white light scattering target and has been background subtracted to remove dark counts. Simulations are carried out with COMSOL and their results tabulated. The dataset includes simulations of the metamaterial as an effective medium with changing geometrical parameters, SEIRA, SERS and DF characterisation of the metamaterial using different fill factors and the substrate's application for enhanced sensing of polystyrene nanoparticles.

Version

Software / Usage instructions

All files are in csv format, graphs can be plotted using excel, open office or other data visualisation tool.

Keywords

Metamaterial, Mid-infrared, Nanoparticles, Plasmonics, SEIRA, Self-assembly, Sensing

Publisher

Rights and licensing

Attribution 4.0 International (CC BY 4.0)
Except where otherwised noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)
Sponsorship
European Commission Horizon 2020 (H2020) ERC (883703)
Engineering and Physical Sciences Research Council (EP/L015978/1)
EPSRC (EP/X037770/1)
EPSRC (EP/Y008162/1)
Engineering and Physical Sciences Research Council (EP/L015889/1)
Engineering and Physical Sciences Research Council (EP/S022953/1)
The authors acknowledge financial support from the European Research Council (ERC) under Horizon 2020 research and innovation programme PICOFORCE (Grant Agreement No. 883703), and from the EPSRC (Cambridge NanoDTC EP/L015978/1, EP/X037770/1, EP/Y008162/1). N.S. acknowledges support from EPSRC Grant EP/L015889/1 for the EPSRC Centre for Doctoral Training in Sensor Technologies and Applications, and from AstraZeneca (MedImmune Ltd). C.T. is supported by a Gates Cambridge fellowship (OPP1144). R.A. acknowledges support from the Winton Programme for the Physics of Sustainability and from St. John’s College Cambridge. R.D. acknowledges support from from EPSRC grant EP/S022953/1 for the EPSRC Centre for Doctoral Training in Integrated Functional Nano. A.D. and Z.S. wish to acknowledge support from the Royal Society University Research Fellowship URF/R1/180097 and URF/R/231024, Royal Society Research Fellows Enhancement Award RGF /EA/181038, funding from ESPRC grants EP/Y008774/1 and EP/X012689/1 from EPSRC for the CDT in Topological Design EP/S02297X/1.

Relationships

Supplements:
https://www.repository.cam.ac.uk/handle/1810/387590
https://doi.org/10.1364/OPTICA.567324

Collections

Research Data - Physics