HYDROGEN DETECTION USING AN INTELLIGENT OPTICAL SENSOR (HyDIOS)
The objective of this effort was to demonstrate the feasibility of a hydrogen sensor capable of detecting and monitoring hydrogen concentrations in real-time. The sensor could be standalone or part of a more comprehensive set of sensing capabilities compatible with existing pipeline monitoring systems. These studies determined the range and resolution of an intelligent optical hydrogen sensor. The project demonstrates strong feasibility and significant value for supporting the Nation’s incentives for a hydrogen economy and improving pipeline systems' safety and efficiency that carry natural gas/hydrogen blends. The project's goals were achieved by designing and producing an advanced optical sensor interface, surface characterization, sensor performance validation, and prototype planning. For this sensor surface interface, various metal organic frameworks (MOFs) with a large surface-to-volume ratio and high affinity towards hydrogen were utilized. The MOFs are synthesized from metal ions and organic building blocks. The MOF framework topology, pore size, and surface area could be readily tuned. Based on optical modeling and simulation, a composite nanostructure interface with specific chemical geometries and optical properties was designed. A sensor prototype was engineered to produce an intelligent sensor system. The sensitivity range and resolution were characterized. Various chemical deposition techniques were refined to improve the surface interface stability and repeatability. A commercially available benchtop gas-phase surface plasmon resonance (SPR) instrument was employed to test experimental sensor surfaces in various gas environments and configurations. Various pressures were applied to the sensor’s interfaces, investigated, and measured the change in the stress response. An intelligent hydrogen sensor was engineered and designed for pipeline compatibility and durability, and sensor components were ordered. The fundamentals of Oceanit’s intelligent optical sensor for detecting natural gas/hydrogen blends were demonstrated in Phase I. MOF selection, and deposition techniques were used to successfully create an optical sensor that allowed precise detection of hydrogen in a buffer gas when hydrogen was introduced to the sensor interface. Multiple surface interfaces were investigated, and stability tests with a wide range of candidate MOFs guided optimization of the sensor interface. The reflectivity curve features of the sensor indicated not only the unique presence of hydrogen but also pressure and temperature conditions. Furthermore, repeatability tests were performed, demonstrating the reusability of a sensor surface. Edge computing techniques were developed to detect natural gas/hydrogen blends. The algorithms allow for advanced data analytics and mapping of hydrogen concentrations through optical detection. Together, these technologies combine to provide a versatile system for real-time, low-cost pipeline diagnostics. Oceanit has created an intelligent sensor platform capable of identifying and quantifying natural gas/hydrogen blends throughout transport and has the potential to forecast maintenance for repairing pipeline damage without disruption to service. The natural gas/hydrogen blend monitoring capabilities developed in this project can be applied to a wide variety of gas and liquid monitoring related projects, including gas turbine power plants, wastewater, oil & petrochemical, and biological, to name a few. Increased understanding of natural gas/hydrogen blend transportation, storage and consumption conditions will minimize methane and hydrogen emissions. Knowledge obtained from this technology will improve pipeline mitigation technologies and create a predictive maintenance schedule that will increase the lifetime of the current natural gas pipeline.
- Research Organization:
- Oceanit Laboratories, Inc.
- Sponsoring Organization:
- USDOE Office of Science (SC)
- Contributing Organization:
- University of California, Riverside
- DOE Contract Number:
- SC0021945
- OSTI ID:
- 1860456
- Type / Phase:
- SBIR (Phase I)
- Report Number(s):
- DE-SC0021945
- Country of Publication:
- United States
- Language:
- English
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