Autonomous Real Time, Multi Species Monitoring System for In-line Commodity Purity Analysis

In NASA and commercial aerospace processes involving hydrogen, oxygen, methane, air, nitrogen, and helium, real-time in-line analysis of gas purity is critical for ensuring product quality, process efficiency, and compliance with stringent standards for mission success. Current standard methods like GC/MS require significant downtime, labor, and sample distribution to labs for analysis, struggle with real-time monitoring, and do not allow for sampling in the process stream. There is a need for innovative gas/fluid composition monitoring technologies capable of achieving real-time in-line analysis of hydrogen, oxygen, methane, air, nitrogen, and helium process streams, with a focus on detecting and quantifying impurities such as hydrocarbons, moisture, and total impurities per NASA purity standards. The long-term objective of the proposed effort is to leverage Sporian’s prior work on machine learning-enabled spectroscopy-based sensing systems to realize an intelligent, real-time, cost-effective process gas stream composition monitoring system focused on detecting and quantifying both composition and impurities per NASA purity standards. This initial effort will focus on methane process streams and their specific needs and technical requirements, as sensing contaminants in high-concentration methane gas traditionally presents many challenges for conventional in-line sensor types. Phase I efforts will include: 1) working with stakeholders to define system requirements; 2) evaluating revised hardware/electronics architectures and designs; and 3) proof of principle testing and demonstration using benchtop-scale prototype hardware. If successful, Sporian will be well-positioned for the Phase II efforts focused on full system prototyping and relevant environmental testing/demonstration. Work will be done through a collaboration between Sporian Microsystems and the University of Central Florida.