Issue 37, 2020

Through-bottle whisky sensing and classification using Raman spectroscopy in an axicon-based backscattering configuration

Abstract

Non-intrusive detection systems have the potential to characterise materials through various transparent glass and plastic containers. Food and drink adulteration is increasingly problematic, representing a serious health risk as well as an economic issue. This is of particular concern for alcoholic spirits such as Scotch whisky which are often targeted for fraudulent activity. We have developed a Raman system with a novel geometry of excitation and collection, exploiting the beam propagation from an axicon lens, which results in an annular beam at the bottle surface before focusing within the sample. This facilitates the efficient acquisition of Raman signals from the alcoholic spirit contained inside the bottle, while avoiding the collection of auto-fluorescence signals generated by the bottle wall. Therefore, this technique provides a way of non-destructive and non-contact detection to precisely analyse the contents without the requirement to open the bottle.

Graphical abstract: Through-bottle whisky sensing and classification using Raman spectroscopy in an axicon-based backscattering configuration

Article information

Article type
Paper
Submitted
01 Jun 2020
Accepted
18 Aug 2020
First published
19 Aug 2020
This article is Open Access
Creative Commons BY license

Anal. Methods, 2020,12, 4572-4578

Through-bottle whisky sensing and classification using Raman spectroscopy in an axicon-based backscattering configuration

H. Fleming, M. Chen, G. D. Bruce and K. Dholakia, Anal. Methods, 2020, 12, 4572 DOI: 10.1039/D0AY01101K

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements