Lyne CT, Liu MF, Rovey JL. A simple retarding-potential time-of-flight mass spectrometer for electrospray propulsion diagnostics.
J Elect Propuls 2023;
2:13. [PMID:
37016724 PMCID:
PMC10066156 DOI:
10.1007/s44205-023-00045-y]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 03/13/2023] [Indexed: 04/06/2023]
Abstract
The time-of-flight mass spectrometer (ToF-MS) is a useful tool for quantifying the performance of electrospray thrusters and characterizing their plumes. ToF-MS data can be used to calculate the mass-to-charge distribution in the plume, but the kinetic-energy-to-charge (i.e., the potential) distribution must be known first. Here we use a ToF-MS in tandem with a retarding potential (RP) analyzer. By sweeping the retarding potential through the range of potentials present in the plume, both the mass-to-charge distribution and the potential distribution can be measured independently. We demonstrate this technique in a case study using a capillary electrospray emitter and the ionic liquid propellant 1-Ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, abbreviated EMI-Im. We report a linear correlation between retarding potential and mass-to-charge ratio that agrees with published data from more complex orthogonal RP/ToF-MS instruments. Calculated values for the jet velocity and jet breakup potential match within 2% and 12%, respectively. Using conventional ToF-MS, we estimated the propellant flow rate and compared those estimates to direct flow rate measurements. For flow rates between 233 pL/s and 565 pL/s, the error in ToF-based flow rate estimates ranged from -16% to -13% when the plume potential was assumed to be a function of mass-to-charge. Assuming a constant plume potential yielded mixed results. However, using the average stopping potential measured by a retarding potential analyzer resulted in higher errors, ranging from -26% to -30%. Data and MATLAB code are included as supplemental materials so that readers can easily apply the techniques described here.
Supplementary Information
The online version contains supplementary material available at 10.1007/s44205-023-00045-y.
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