Paper
26 February 1999 Near-IR diode-laser-based sensor for parts-per-billion-level water vapor in industrial gases
William J. Kessler, Mark G. Allen, Steven J. Davis, Phillip A. Mulhall, Jan A. Polex
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Abstract
The verification of low water vapor impurity levels in semiconductor manufacturing feed gas supplies is becoming critically important for the development of advanced electronic devices. Ammonia is one of the important precursor gases for electronic manufacturing. In this paper, we present data from a water vapor absorption spectroscopy sensor designed to continuously measure ppb water impurities in pure ammonia gas with a 1 Hz bandwidth. The sensor is built using a near-IR diode laser, commercial fiber optic components, room-temperature InGaAs photodiodes, an ultra- sensitive balanced radiometric detection circuit, and a modified commercially available multipass cell. We present water vapor collisional broadening data by ammonia used to determine the optimal operating pressure for maximum system sensitivity. The commercial multipass cell was modified for ease of alignment, a nearly continuously variable pathlength, and to minimize the atmospheric air pathlength outside of the cell. The computer- controlled sensor is applicable to making water impurity measurements in a number of additional commercially important gases, such as hydrogen chloride, hydrogen fluoride, hydrogen bromide, silane, etc. The sensor is also applicable to moisture measurements in natural gas, and manufacturing dryer applications, such as those found in the plastics industry or the pharmaceutical industry, where in-line process control is critical.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
William J. Kessler, Mark G. Allen, Steven J. Davis, Phillip A. Mulhall, and Jan A. Polex "Near-IR diode-laser-based sensor for parts-per-billion-level water vapor in industrial gases", Proc. SPIE 3537, Electro-Optic, Integrated Optic, and Electronic Technologies for Online Chemical Process Monitoring, (26 February 1999); https://doi.org/10.1117/12.341026
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Cited by 4 scholarly publications.
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