Paper
14 August 1992 Luminescent sensors: modeling of microheterogeneous systems and model differentiation
James N. Demas, Benjamin A. DeGraff Jr.
Author Affiliations +
Proceedings Volume 1681, Optically Based Methods for Process Analysis; (1992) https://doi.org/10.1117/12.142555
Event: SPIE's 1992 Symposium on Process Control and Monitoring, 1992, Somerset, NJ, United States
Abstract
Many recent advances in remote optical sensors of O2, pH, and pCO2 have been based on luminescence species as the reporter molecule. Both organic probes and, more recently, transition metal complexes are being used on inorganic or organic polymer supports. Polymer supported systems are highly microheterogeneous. However, heterogeneity has an enormous effect on luminescence, quenching, and photochemistry, which has led to considerable difficulty in properly interpreting and correcting sensor behavior. An intimate understanding of the detailed interactions between the complexes and their environment is necessary before the rational design of new high performance sensors and probes can be achieved. Key to such understanding is developing reliable models for the nature of this heterogeneity and its consequences in sensor performance. While several different models for heterogeneity have evolved, it is not widely appreciated that these models are not unique and that proof of such models is extraordinarily difficult. We outline some different models, demonstrate their effect on sensor response, spell out the magnitude of the uniqueness problem, and indicate what types of measurement are necessary to differentiate between models.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
James N. Demas and Benjamin A. DeGraff Jr. "Luminescent sensors: modeling of microheterogeneous systems and model differentiation", Proc. SPIE 1681, Optically Based Methods for Process Analysis, (14 August 1992); https://doi.org/10.1117/12.142555
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Cited by 5 scholarly publications.
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KEYWORDS
Sensors

Systems modeling

Data modeling

Luminescence

Polymers

Environmental sensing

Molecules

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