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Related Concept Videos

Photoluminescence: Applications01:14

Photoluminescence: Applications

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Photoluminescence offers a wide range of applications due to its inherent sensitivity and selectivity. This technique allows for both direct and indirect analyses of the analyte. Direct quantitative analysis is possible when the analyte exhibits a favorable quantum yield for fluorescence or phosphorescence. However, an indirect analysis may be feasible if the analyte is not fluorescent or phosphorescent, or if the quantum yield is unfavorable. Indirect methods include reacting the analyte with...
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DNA probes are fragments of DNA labeled with a reporter tag to enable their detection or purification. The resulting labeled DNA probes can then hybridize to target nucleic acid sequences through complementary base-pairing, and may be used to recover or identify these regions.
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Photoluminescence: Fluorescence and Phosphorescence01:23

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Photoluminescence is a process where a molecule absorbs light energy and re-emits it in the form of light. This phenomenon occurs when a substance absorbs photons, promoting its electrons to higher energy level excited states, followed by a relaxation process in which the electrons return to their original ground state energy levels and emit light. Photoluminescence is widely observed in various materials, including semiconductors, and organic and inorganic compounds.
A pair of electrons in a...
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Fluorescence and Phosphorescence: Instrumentation01:25

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Fluorometers and spectrofluorometers are two types of instruments used for measuring molecular fluorescence. These instruments differ in how they select excitation and emission wavelengths and the type of light sources they utilize. Fluorometers use absorption interference filters to choose excitation and emission wavelengths. The excitation source in a fluorometer is typically a low-pressure mercury vapor lamp that emits intense lines distributed throughout the ultraviolet and visible regions.
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Photoluminescence Probes in Data-Enabled Sensing.

Claudia Von Suskil1, Micaih J Murray1, Dipak B Sanap1

  • 1Department of Chemistry and Biochemistry, University of Delaware, Newark, Delaware, USA;

Annual Review of Analytical Chemistry (Palo Alto, Calif.)
|May 1, 2023
PubMed
Summary

This review covers advancements in photoluminescent probes and multidimensional detection, highlighting how multivariate analysis of complex data enhances analyte identification. Key trends include probe arrays and deep learning for improved pattern recognition.

Keywords:
(photo)luminescent probesN-way analysisimage analysismultidimensional fluorescencemultidimensional phosphorescencemultivariate analysis

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Area of Science:

  • Analytical Chemistry
  • Spectroscopy
  • Chemometrics

Background:

  • Photoluminescent probes offer sensitive detection but often yield complex data.
  • Multidimensional photoluminescence detection generates rich datasets.
  • Multivariate data analysis (MVA) is crucial for extracting meaningful information from complex spectral data.

Purpose of the Study:

  • To review the development of photoluminescent probes, multidimensional detection, and MVA methods.
  • To highlight recent advancements (2015-2022) in MVA of multidimensional photoluminescence measurements.
  • To identify key trends and future directions in the field.

Main Methods:

  • Literature review focusing on publications from June 2015 to June 2022.
  • Analysis of trends in probe array development.
  • Examination of machine learning (neural networks, deep learning) applications.
  • Review of multiway MVA applied to higher-order spectral and lifetime data.

Main Results:

  • Probe arrays enable fingerprint-like responses for complex sample analysis.
  • Neural networks and deep learning improve pattern recognition in photoluminescence images.
  • Multiway MVA effectively analyzes mining matrices and higher-order data, including hyperspectral images.
  • Combining multidimensional measurements with MVA significantly increases information extraction.

Conclusions:

  • The integration of multidimensional photoluminescence measurements and MVA is a powerful approach for enhanced analytical performance.
  • Emerging trends like probe arrays and advanced computational methods are driving innovation in chemical sensing.
  • Future research will likely focus on further developing these integrated strategies for increasingly complex analytical challenges.