Laser fluorimetry of mixtures of polyatomic organic compounds using artificial neural networks
- D.V. Skobel'tsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow (Russian Federation)
- Department of Physics, M.V. Lomonosov Moscow State University, Moscow (Russian Federation)
New possibilities of laser fluorimetry offered by the use of algorithms for solving inverse problems based on artificial neural networks are demonstrated. A two-component mixture of polyatomic organic compounds is analysed by three methods of laser fluorimetry: a direct analysis of the fluorescence band, the kinetic fluorimetry (when durations of the laser pulse and the detector gate pulse are comparable with the fluorescence lifetimes or exceed them), and the saturation fluorimetry. The numerical experiments showed that the use of artificial neural networks in these methods provides a high practical stability of the solution of inverse problems and ensures a high sensitivity and a high accuracy of determining the contribution of components to fluorescence and of measuring molecular photophysical parameters, which can be used for the identification of components. (laser applications and other topics in quantum electronics)
- OSTI ID:
- 21496536
- Journal Information:
- Quantum Electronics (Woodbury, N.Y.), Vol. 31, Issue 9; Other Information: DOI: 10.1070/QE2001v031n09ABEH002056; ISSN 1063-7818
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
ORGANIC
PHYSICAL AND ANALYTICAL CHEMISTRY
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY
ACCURACY
ALGORITHMS
FLUORESCENCE
FLUORESCENCE SPECTROSCOPY
LASERS
MATHEMATICAL SOLUTIONS
NEURAL NETWORKS
ORGANIC COMPOUNDS
PULSES
SENSITIVITY
EMISSION
EMISSION SPECTROSCOPY
LUMINESCENCE
MATHEMATICAL LOGIC
PHOTON EMISSION
SPECTROSCOPY