KEYWORDS: Diffusion, Physics, Chemical species, Data modeling, Chemical analysis, Temperature metrology, Standards development, Mass spectrometry, Epoxies, Data processing
Progress was performed recently on the separation and characterization of the chemical species outgassed by space materials, relying on the assessment of thermogravimetric analysis (TGA) peaks by mass spectrometry (MS). A companion communication reports on this experimental technique and the first level processing of these MS data, which often allows determining which are the outgassed species, and their MS spectra. This communication focusses more on the second analysis step, i.e. the study of the MS data acquired during the initial outgassing phase. Ancient simpler outgassing analyses based on total mass measurements only, most of the time on quartz crystal microbalances (QCMs), cannot realistically determine the separate contribution of different species, even though some models consider the contribution of several species, which are indeed more “mathematical species” than physical ones. In contrast, this new approach, also taking into account the MS measurements during the outgassing, and known species spectra (from the TGA/MS analysis done previously), allows a more realistic determination of the contribution of each real chemical species to the total outgassing. Even though results are not yet final and perfect, measured outgassing fluxes from several species and materials are presented. Their physical analysis, through comparison and fit by diffusion or other possible outgassing laws are also presented. At this level, they clearly point to diffusion laws, rather than to any other outgassing law, although not necessarily always Fickian diffusion. This method was applied to typical US or European outgassing approaches, with either isothermal ASTM-1559 outgassing tests or multi-temperature VBQC-type tests.
Well-established procedures for the characterization of contamination during outgassing usually involve total mass measurements through quartz crystal microbalance (QCM). Recently, the addition of mass spectrometry (MS) measurements to these data has become more common. The combination of both high sensitivity QCM and MS data may lead to a better understanding of the physics taking place during outgassing contamination processes. The way to do so is to complement the basic measurements of total mass loss on QCMs by the identification of each species and the quantitative determination of each species contribution. In a first characterization step, the thermogravimetric analysis of contaminants deposited on QCMs allows a partial species separation that helps exploiting mass spectrometry data. In return, these data permit a finer species separation. The key to these measurements is to obtain sufficient signal to noise ratio in the mass spectrometer. Though outgassing of space materials is not done the same way in Europe (multi-temperature steps, ECSS-Q-TM-70-52A) and in the US (isothermal, ASTM E-1559-09), both tests could be used to perform a first species separation, as reported here. Most species outgassed by a few common materials were identified (and quantified) through TGA and MS coupling. As reported in a companion paper, the knowledge of these species’ spectra then allows the analysis of the MS data during the initial outgassing phase, determining the quantitative outgassing of each species and leading to the improved comprehension of the physical laws ruling outgassing.
KEYWORDS: Contamination, Analytical research, Monte Carlo methods, Chemical analysis, Computer simulations, Contamination control, Space operations, Atmospheric sciences, Particles, Aerospace engineering
The Jet Propulsion Laboratory (JPL) has pursued a multi-disciplinary effort to experimentally characterize and computationally simulate the effects of powered descent onto the Europan surface. As part of the proposed Europa Lander technology development and maturation activities, JPL Contamination Control and the German Aerospace Center (DLR) are conducting a test program to characterize monopropellant plume-induced contamination, the preliminary results of which are showcased in this presentation. These measurements have been used in the further development of JPL’s computational physics simulations of descent engine plumes interacting with the Europan surface with direct simulation Monte Carlo (DSMC) techniques, and in broader support of contamination control strategies for the proposed Europa Lander mission.
One of the Mars 2020 mission’s primary science objectives is to seek out traces of past life on Mars – the rover’s sample caching system (SCS) will collect and store rock cores and regolith samples for possible return to Earth for analysis by a future mission. These samples must be contaminated with fewer than 10 parts-per-billion (PPB) total organic carbon (TOC) of terrestrial origin to permit an unambiguous detection of Martian organic signatures; this 10 PPB threshold translates to less than a monolayer of adsorbed contaminant molecules on the inside surfaces of sample tubes. Achieving such a stringent requirement has necessitated some of the strictest contamination control protocols ever enacted in NASA’s history. Throughout all phases of the mission, sources of terrestrial organic carbon can contaminate samples and sample caching hardware through a variety of transport mechanisms in free-molecular and continuum flow regimes. Predicting and mitigating the contamination of future returned samples requires a comprehensive understanding and cataloging of contaminant sources, transport mechanisms, and adsorption characteristics. Therefore, JPL Contamination Control has developed a novel multispecies model based on experimental measurements of Mars 2020 flight hardware, which has been applied in characterizing organic carbon contaminant sources, species compositions, and outgassing rate dependences on temperature. These are the boundary conditions for an end-to-end modeling framework in which the transport and deposition of contaminant species are calculated for each mission phase, culminating in a prediction of the total quantity of terrestrial organic carbon within future returned samples.
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