Literature DB >> 27216667

Water monitoring by optofluidic Raman spectroscopy for in situ applications.

Gianluca Persichetti1, Romeo Bernini2.   

Abstract

The feasibility of water monitoring by Raman spectroscopy with a portable optofluidic system for in-situ applications has been successfully demonstrated. In the proposed approach, the sample under analysis is injected into a capillary nozzle in order to produce a liquid jet that acts as an optical waveguide. This jet waveguide provides an effective strategy to excite and collect the Raman signals arising from water contaminants due to the high refractive index difference between air and water. The proposed approach avoids any necessity of liquid container or flow cell and removes any background signal coming from the sample container commonly affects Raman measurements. Furthermore, this absence is a significant advantage for in situ measurements where fouling problems can be relevant and cleaning procedures are troublesome. The extreme simplicity and efficiency of the optical scheme adopted in our approach result in highly sensitive and rapid measurements that have been performed on different representative water pollutants. The experimental results demonstrate the high potentiality of our device in water quality monitoring and analysis. In particular, nitrate and sulfate are detected below the maximum contamination level allowed for drinking water, whereas a limit of detection of 40mg/l has been found for benzene.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Jet waveguide sensor; Portable sensor; Raman spectroscopy; Water monitoring

Mesh:

Substances:

Year:  2016        PMID: 27216667     DOI: 10.1016/j.talanta.2016.03.102

Source DB:  PubMed          Journal:  Talanta        ISSN: 0039-9140            Impact factor:   6.057


  1 in total

1.  Application of Laser-Induced, Deep UV Raman Spectroscopy and Artificial Intelligence in Real-Time Environmental Monitoring-Solutions and First Results.

Authors:  Claudia Post; Simon Brülisauer; Kryss Waldschläger; William Hug; Luis Grüneis; Niklas Heyden; Sebastian Schmor; Aaron Förderer; Ray Reid; Michael Reid; Rohit Bhartia; Quoc Nguyen; Holger Schüttrumpf; Florian Amann
Journal:  Sensors (Basel)       Date:  2021-06-05       Impact factor: 3.576

  1 in total

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