Optical Spectroscopy for Sensing, Monitoring and Analysis: 2nd Edition
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Optical Sensors".
Deadline for manuscript submissions: 31 July 2025 | Viewed by 621
Special Issue Editors
Interests: real-time monitoring; laser-induced breakdown spectroscopy; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: optical spectroscopy; spectroelectrochemistry; separations; design of experiments; chemometrics; machine learning
Special Issue Information
Dear Colleagues,
Based on the positive turnout of our previous issue we are happy to announce a 2nd Special issue on “Optical Spectroscopy for Sensing, Monitoring, and Analysis”. You can view the original Special Issue here: https://www.mdpi.com/journal/sensors/special_issues/14NLO90B2H .
There is a growing need for sensors that are capable of monitoring a plethora of analytes in complex and hazardous environments in real time. Optical spectroscopy is an ideal candidate for these sensor applications due to the intrinsic ability to send light to and from a measurement point using optics or fibers, thereby protecting expensive equipment from exposure. These applications of optical spectroscopy have seen rapid growth in their capabilities due to advances in equipment, modeling techniques, and sensor fusion. Outside of in situ analysis, similar advances have been made to enable the use of optical spectroscopy for further sample characterization.
This Special Issue therefore aims to put together original research and review articles on recent advances, technologies, solutions, applications, and new challenges in the field of optical spectroscopy for sensing, monitoring, and analysis.
Dr. Hunter B. Andrews
Dr. Luke R. Sadergaski
Dr. Kyle C. Hartig
Guest Editors
Manuscript Submission Information
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Keywords
- optical spectroscopy
- laser spectroscopy
- laser-induced breakdown spectroscopy
- Raman spectroscopy
- spectrophotometry
- fluorescence spectroscopy
- online monitoring
- sensor fusion
- chemometrics
- machine learning
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