| Autor: |
Kalinichev AV; Aarhus University Centre for Water Technology, Department of Biology - Microbiology, Ny Munkegade 116, 8000 Aarhus C, Denmark. klaus.koren@bio.au.dk., Zieger SE; Aarhus University Centre for Water Technology, Department of Biology - Microbiology, Ny Munkegade 116, 8000 Aarhus C, Denmark. klaus.koren@bio.au.dk., Koren K; Aarhus University Centre for Water Technology, Department of Biology - Microbiology, Ny Munkegade 116, 8000 Aarhus C, Denmark. klaus.koren@bio.au.dk. |
| Jazyk: |
angličtina |
| Zdroj: |
The Analyst [Analyst] 2023 Dec 18; Vol. 149 (1), pp. 29-45. Date of Electronic Publication: 2023 Dec 18. |
| DOI: |
10.1039/d3an01661g |
| Abstrakt: |
Chemical gradients and uneven distribution of analytes are common in natural and artificial systems. As a result, the ability to visualize chemical distributions in two or more dimensions has gained significant importance in recent years. This has led to the integration of chemical imaging techniques into all domains of analytical chemistry. In this review, we focus on the use of optical sensors, so-called optodes, to obtain real-time and multidimensional images of two or more parameters simultaneously. It is important to emphasize that multiparameter imaging in this context is not confined solely to multiple chemical parameters (analytes) but also encompasses physical ( e.g. , temperature or flow) or biological ( e.g. , metabolic activity) parameters. First, we discuss the technological milestones that have paved the way for chemical imaging using optodes. Later, we delve into various strategies that can be taken to enable multiparameter imaging. The latter spans from developing novel receptors that enable the recognition of multiple parameters to chemometrics and machine learning-based techniques for data analysis. We also explore ongoing trends, challenges, and prospects for future developments in this field. Optode-based multiparameter imaging is a rapidly expanding field that is being fueled by cutting-edge technologies. Chemical imaging possesses the potential to provide novel insights into complex samples, bridging not only across various scientific disciplines but also between research and society. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
|
