Response of QIT-MS to Noble Gas Isotopic Ratios in a Simulated Venus Flyby

The primary objective of the present study is to investigate the science return of future Venus atmosphere probe mission concepts using the Quadrupole Ion Trap (QIT) Mass Spectrometer (MS) Instrument (QIT-MS-I). We demonstrate the use of Monte-Carlo simulations in determining the optimal ion trappin...

Full description

Saved in:
Bibliographic Details
Published in:Atmosphere 2019-05, Vol.10 (5), p.232
Main Authors: Nikolić, Dragan, Madzunkov, Stojan M., Darrach, Murray R.
Format: Article
Language:English
Subjects:
Algorithms
Atmosphere
Carbon dioxide
Computer simulation
Flyby missions
Gases
Gettering
Handbooks
Isotope ratios
Isotopes
Mass spectrometry
Monte Carlo simulation
Nitrogen
noble gases
Organic chemistry
Quadrupoles
Random walk
Rare gases
Ratios
Sensors
Solar system
Vacuum
Vacuum chambers
Vacuum technology
Venus
Venus atmosphere
Viscosity
VOCs
Volatile organic compounds
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The primary objective of the present study is to investigate the science return of future Venus atmosphere probe mission concepts using the Quadrupole Ion Trap (QIT) Mass Spectrometer (MS) Instrument (QIT-MS-I). We demonstrate the use of Monte-Carlo simulations in determining the optimal ion trapping conditions and focus the analysis on retrieving isotope ratios of noble gases in the model sample of the Venus atmosphere. Sampling takes place at a constant velocity of ~10 km/s between 112–110 km altitude and involves the use of getter pumps to remove all chemically-active species, retaining inert noble gases. The enriched sample is leaked into passively pumped vacuum chamber where it is analyzed by the QIT-MS sensor (QIT-MS-S) for 40 minutes. The simulated mass spectrum, as recorded by the QIT-MS-S, is deconvoluted using random walk algorithm to reveal relative abundances of noble gas isotopes. The required precision and accuracy of the deconvolution method is benchmarked against the a priori known model composition of the atmospheric sample.
ISSN:2073-4433
2073-4433
DOI:10.3390/atmos10050232