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Research data supporting “Tracking and Controlling Monolayer Water in Gold Nanogaps using Extreme Plasmonic Spectroscopy.”


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Description

This dataset contains raw spectral data associated with the main and supplementary figures of a publication detailing how surface water monolayers in sub-nm gaps between gold nanoparticle surfaces can be observed using surface-enhanced Raman spectroscopy (SERS). SERS data were collected at 5-10 positions on a multi-layer gold nanoparticle aggregate (MLagg) substrate in a range of conditions, and are normalised for laser power and integration time. All measurements are taken at room temperature unless otherwise specified and Raman shifts are calibrated with respect to Si. The SERS dataset characterises the MLagg substrate in air, water, and DMSO, demonstrates how the surface water changes with deuteration and subsequent drying in nitrogen flow, and the effects of an applied potential.

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All data are provided in comma-separated values (.csv) format, which can be plotted with any standard spreadsheet program as well as scientific software and programming languages (e.g. Python).

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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)
Engineering and Physical Sciences Research Council (EP/L027151/1)
EPSRC (EP/X037770/1)
Engineering and Physical Sciences Research Council (EP/L015889/1)
Royal Society (URF\R1\211162)
EPSRC (EP/Y008294/1)
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/L027151/1, EP/X037770/1). S.M.S.-T. was supported by the University of Cambridge Harding Distinguished Postgraduate Scholars Programme. S.M.S.-T. acknowledges further support from EPSRC Grant EP/L015889/1 for the EPSRC Centre for Doctoral Training in Sensor Technologies and Applications. R.A. acknowledges support from St. John's College Cambridge. M.N. was supported by a Gates Cambridge fellowship (OPP1144). B.d.N. acknowledges support from the Royal Society (URF∖R1∖211162) and the EPSRC (EP/Y008294/1).