Multiway Decomposition Followed by Reconvolution of Fluorescence Time Decay Data.

Area of Science:

• Analytical Chemistry
• Spectroscopy

Background:

• Time-resolved emission spectroscopy (TRES) is becoming more accessible due to decreasing instrument costs and the advent of LED light sources.
• Accurate analysis of TRES data is crucial for understanding complex fluorescent systems.

Purpose of the Study:

• To introduce and validate a novel methodology for analyzing TRES data by integrating PARallel FACtor analysis (PARAFAC) and reconvolution.
• To compare the performance of the proposed method against established techniques like global reconvolution, tail fitting, and the SLICING method.

Main Methods:

• The proposed method combines PARAFAC, a soft modeling technique, with reconvolution, a standard TRES fitting approach.
• Performance was evaluated using a measured TRES dataset of three fluorophores and simulated datasets with up to four fluorophores.

Main Results:

• Global fitting is effective only at high signal-to-noise ratios (SNR > 15 dB).
• The SLICING method showed limitations in estimating time decay due to difficulties in defining spectral tails.
• The novel PARAFAC-reconvolution method demonstrated robust and accurate results, outperforming other techniques, especially under high noise (SNR down to 5 dB) and broad instrument response functions.

Conclusions:

• The integrated PARAFAC-reconvolution method provides a superior approach for analyzing complex TRES data, particularly in challenging conditions.
• This technique enhances the reliability and accuracy of fluorophore characterization from TRES measurements.