Adaptive Method for Quantitative Estimation of Glucose and Fructose Concentrations in Aqueous Solutions Based on Infrared Nanoantenna Optics
Clicks: 338
ID: 66643
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Popular Article
81.2
/100
338 views
198 readers
Trending
AI Quality Assessment
Not analyzed
Readership in this journal
PopularRanked #290 of 1,694 articles by views in sensors
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 1,694 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
In life science and health research one observes a continuous need for new concepts and methods to detect and quantify the presence and concentration of certain biomolecules—preferably even in vivo or aqueous solutions. One prominent example, among many others, is the blood glucose level, which is highly important in the treatment of, e.g., diabetes mellitus. Detecting and, in particular, quantifying the amount of such molecular species in a complex sensing environment, such as human body fluids, constitutes a significant challenge. Surface-enhanced infrared absorption (SEIRA) spectroscopy has proven to be uniquely able to differentiate even very similar molecular species in very small concentrations. We are thus employing SEIRA to gather the vibrational response of aqueous glucose and fructose solutions in the mid-infrared spectral range with varying concentration levels down to 10 g/l. In contrast to previous work, we further demonstrate that it is possible to not only extract the presence of the analyte molecules but to determine the quantitative concentrations in a reliable and automated way. For this, a baseline correction method is applied to pre-process the measurement data in order to extract the characteristic vibrational information. Afterwards, a set of basis functions is fitted to capture the characteristic features of the two examined monosaccharides and a potential contribution of the solvent itself. The reconstruction of the actual concentration levels is then performed by superposition of the different basis functions to approximate the measured data. This software-based enhancement of the employed optical sensors leads to an accurate quantitative estimate of glucose and fructose concentrations in aqueous solutions.
| Reference Key |
schuler2019adaptivesensors
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Schuler, Benjamin;Kühner, Lucca;Hentschel, Mario;Giessen, Harald;Tarín, Cristina; |
| Journal | sensors |
| Year | 2019 |
| DOI |
DOI not found
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.