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Coupled turbidity and spectroscopy problems: a simple algorithm for the volumetric analysis of optically thin or
Paul Dent1, Bin Deng, Jerry Goodisman
1Department of Chemistry, Syracuse University, Syracuse, NY 13244-4100 USA.
Applied Spectroscopy
|February 10, 2015
Summary
This study presents a new algorithm to measure phase volume and solute concentration in two-phase systems using elastic (EE) and inelastic (IE) light scattering. The method offers a linear approach for analyzing optically thin or dilute homogeneous systems.
Area of Science:
- Optical Physics
- Biophysical Measurement
- Spectroscopy
Background:
- Accurate measurement of phase volume fraction and solute concentration is crucial in various scientific fields.
- Existing methods may have limitations in optically thin or dilute systems.
- Noninvasive in vivo probing requires robust analytical techniques.
Purpose of the Study:
- To develop and validate a novel algorithm for quantifying phase volume fraction and solute concentration in two-phase systems.
- To establish a method applicable to optically thin or dilute, spatially homogeneous systems.
- To explore the algorithm's performance under non-ideal conditions like spatial inhomogeneity and photochemistry.
Main Methods:
- An algorithm based on radiation transfer theory was developed.
- The method utilizes measurements of elastically scattered light (EE) and inelastically scattered light (IE) from probing light.
- Parameters for the algorithm are derived from a training set of measurements.
Main Results:
- The algorithm demonstrates that phase volume and concentration are linear functions of EE and IE signals.
- The study validates the algorithm's applicability to optically thin or dilute homogeneous systems.
- Performance was assessed under conditions of spatial inhomogeneity and light-induced photochemistry.
Conclusions:
- The developed algorithm provides a reliable method for measuring phase volume fraction and solute concentration.
- The linearity of phase volume and concentration with EE and IE signals is a key finding.
- The algorithm shows potential for applications in noninvasive in vivo analysis, such as human skin and tissue analysis.
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