Special Issue "Chemical Sensors based on In Situ Spectroscopy"
Deadline for manuscript submissions: closed (31 July 2015).
Interests: Noninvasive glucose measurements in human subjects; real-time bioreactor monitoring and control; near infrared spectroscopy; terahertz spectroscopy; dielectric spectroscopy
Interests: IR and Raman spectroscopy for biomedical diagnosis; sensors based on surface enhanced Raman spectroscopy; chemometrics
Analytical measurements via in situ spectroscopy represent a challenging area of chemical sensor development. Such measurements involve passing a selected band of radiation through a sample and extracting the desired chemical information from the resulting spectrum. Approaches include, but are not limited to, near infrared, mid-infrared, Raman scattering, magnetic resonance, impedance, terahertz, and dielectric spectroscopies. Typically, multivariate analysis methods are required to properly extract the desired analytical information from the in situ spectra, owing to the complexity of the sample matrix. This approach offers several attractive features, including the ability to quantify multiple analytes simultaneously within the sample matrix. In addition, this spectroscopic approach is both reagentless and nondestructive, thereby enabling real-time measurements without perturbing the system under investigation. These features promise rapid, real-time analytical measurements that are well suited for in situ control of critical processes, as well as monitoring quality of supply-chain materials. For these reasons, spectroscopic sensors have been developed for a variety of applications, including those in food sciences, petroleum refining, bioprocessing, biomedical sciences, environmental monitoring, and others. Still, longstanding analytical issues remain that limit the implementation of this approach, including selectivity in complex sample matrixes, poor calibration robustness over time, sensitivity, and limits of detection.
This Special Issue of Sensors will be dedicated to advances in the contemporary development of spectroscopic chemical sensors with an emphasis on overcoming these longstanding issues as well as their applications to novel processes. Both original research reports and reviews are welcome. Research reports must advance analytical science by expanding our overall understanding of in situ measurements. Reviews must provide a critical assessment of a selected element of the field.
Prof. Dr. Mark A. Arnold
Prof. Dr. Hoeil Chung
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- spectroscopic sensors
- noninvasive sensing
- real-time monitoring
- near-infrared spectroscopy
- mid-infrared spectroscopy
- Raman scattering spectroscopy