Timothy P. Griffin

Real-time quantitative analysis of H2, He, O2, and ar by quadrupole ion trap mass spectrometry

The use of a quadrupole ion trap mass spectrometer (QITMS) for quantitative analysis of hydrogen and helium as well as of other permanent gases is demonstrated. Like commercial instruments, the customized QITMS uses mass selective instability; however, this instrument operates at a greater trapping frequency and without a buffer gas. Thus, a useable mass range from 2 to over 50 daltons (Da) is achieved. The performance of the ion trap is evaluated using part-per-million (ppm) concentrations of hydrogen, helium, oxygen, and argon mixed into a nitrogen gas stream, as outlined by the National Aeronautics and Space Administration (NASA), which is interested in monitoring for cryogenic fuel leaks within the Space Shuttle during launch preparations. When quantitating the four analytes, relative accuracy and precision were better than the NASA-required minimum of 10% error and 5% deviation, respectively. Limits of detection were below the NASA requirement of 25-ppm hydrogen and 100-ppm helium; those for oxygen and argon were within the same order of magnitude as the requirements. These results were achieved at a fast data recording rate, and demonstrate the utility of the QITMS as a real-time quantitative monitoring device for permanent gas analysis.

Evaluation of small mass spectrometer systems for permanent gas analysis

This work is aimed at understanding the aspects of designing a miniature mass spectrometer (MS) system. Several types of small MS systems are evaluated and discussed, including linear quadrupole, quadrupole ion trap, time of flight, and sector. Analysis of hydrogen, helium, oxygen, and argon in a nitrogen background with the concentrations of the components of interest ranging from 0 to 5000 parts per million (ppm). The performance of each system in terms of accuracy, precision, limits of detection, response time, recovery time, scan rate, size, and weight is assessed. The relative accuracies of the systems varied from <1% to ∼40% with an average below 10%. Relative precisions varied from 1% to 20%, with an average below 5%. The detection limits had a large distribution, ranging from 0.2 to 170 ppm. The systems had a diverse response time ranging from 4 to 210 s, as did the recovery time with a 6-to-210-s distribution. Most instruments had scan times near 1 s; however, one instrument exceeded 13 s. System weights varied from 9 to 52 kg and sizes ranged from 15 × 103 cm3 to 110 × 103 cm3. A performance scale is set up to rank each system, and an overall performance score is given to each system.

Three-dimensional concentration mapping of gases using a portable mass spectrometer system

The visualization of hazardous gaseous emissions at volcanoes using in-situ mass spectrometry (MS) is a key step towards a better comprehension of the geophysical phenomena surrounding eruptive activity. In-situ data consisting of helium, carbon dioxide, sulfur dioxide, and other gas species, were acquired with a quadrupole based MS system. Global position systems (GPS) and MS data were plotted on ground imagery, topography, and remote sensing data collected by a host of instruments during the second Costa Rica Airborne Research and Technology Applications (CARTA) mission. This combination of gas and imaging data allowed three-dimensional (3D) visualization of the volcanic plume and the mapping of gas concentration at several volcanic structures and urban areas. This combined set of data has demonstrated a better tool to assess hazardous conditions by visualizing and modeling of possible scenarios of volcanic activity. The MS system is used for in-situ measurement of 3D gas concentrations at different volcanic locations with three different transportation platforms: aircraft, auto, and hand-carried. The demonstration for urban contamination mapping is also presented as another possible use for the MS system.

Application of support vector machines to vapor detection and classification for environmental monitoring of spacecraft

Electronic noses (E-nose) have gained popularity in various applications such as food inspection, cosmetics quality control [1], toxic vapor detection to counter terrorism, detection of Improvised Explosive Devices (IED), narcotics detection, etc. In the paper, we summarized our results on the application of Support Vector Machines (SVM) to gas detection and classification using E-nose. First, based on experimental data from Jet Propulsion Lab. (JPL), we created three different data sets based on different pre-processing techniques. Second, we used SVM to detect gas sample data from non-gas background data, and used three sensor selection methods to improve the detection rate. We were able to achieve 85% correct detection of gases. Third, SVM gas classifier was developed to classify 15 different single gases and mixtures. Different sensor selection methods were applied and FSS & BSS feature selection method yielded the best performance.