Sub-Nanosecond Digital Signal Processing of Photomultiplier Tube Response Enabling Multiphoton Counting in Raman Spectroscopy. Issue 10 (October 2022)

• Record Type: Journal Article
• Authors: Lin, Yu-Chung; Sinfield, Joseph V.
• Is Part Of: Applied spectroscopy. Volume 76:Issue 10(2022)
• Page Start: 1174
• Page End: 1190
• Publication Date: 2022-10
• Subjects: Multiphoton -- photon counting -- Raman spectroscopy -- digital signal processing -- DSP -- photomultiplier tube; Spectrum analysis -- Periodicals; 543.505
• DOI: 10.1177/00037028221095878
• Languages: English
• ISSNs: 0003-7028

Abstract

This paper introduces a novel approach to achieve multiple photon counting for Raman spectroscopy. The multiphoton counting process is made possible by recording and analyzing the photomultiplier tube response to each pulse of a pulsed laser in a time-resolved Raman spectroscopy system. Conventional Raman spectroscopy typically considers photon arrivals as binary events assessed by a single threshold. Hence, the conventional algorithm ignores the fact that multiple photons could arrive within the same response, sacrificing potential signal gain. In this work, a high-speed data acquisition system and multiple threshold digital signal processing counting algorithm are employed to facilitate multiphoton counting, a data processing approach that differentiates photon arrival events by amplitude and time and contributes to improved Raman detection sensitivity. The multiphoton counting algorithm enables lower concentration detection, greater sensitivity, shortens experiment duration, and improves noise rejection. Results from analyses of aqueous solutions of nitrate, isopropanol, and rhodamine 6G demonstrate the versatility and effectiveness of this algorithm. The algorithm increased system sensitivity by ∼ 2.0-, 2.0-, and 3.1-fold, compared to traditional single-threshold analyses of the same data for tests performed on nitrate, isopropanol, and rhodamine 6G, respectively. Results also demonstrated that the multiphoton counting algorithm increases the upper analysis limit for high Raman-yield compounds, shifting the saturation threshold to a higher concentration in typical concentration versus intensity calibration curves. Graphical Abstract