Invited article: Characterization of background sources in space-based time-of-flight mass spectrometers.

Invited Article: Characterization of background sources in space-based time-of-flight mass spectrometers J. A. Gilbert, D. J. Gershman, G. Gloeckler, R. A. Lundgren, T. H. Zurbuchen, T. M. Orlando, J. McLain, and R. von Steiger Citation: Review of Scientific Instruments 85, 091301 (2014); doi: 10.1063/1.4894694 View online: http://dx.doi.org/10.1063/1.4894694 View Table of Contents: http://scitation.aip.org/content/aip/journal/rsi/85/9?ver=pdfcov Published by the AIP Publishing Articles you may be interested in Inverted time-of-flight spectrometer for mass-to-charge analysis of plasmaa) Rev. Sci. Instrum. 85, 02A738 (2014); 10.1063/1.4861393 A new magnetron based gas aggregation source of metal nanoclusters coupled to a double time-of-flight mass spectrometer system Rev. Sci. Instrum. 81, 075110 (2010); 10.1063/1.3465304 Development of a compact electron ion coincidence analyzer using a coaxially symmetric mirror electron energy analyzer and a miniature polar-angle-resolved time-of-flight ion mass spectrometer with four concentric anodes Rev. Sci. Instrum. 80, 043303 (2009); 10.1063/1.3116442 Time-of-flight neutral mass and velocity spectrometer for atmospheric research Rev. Sci. Instrum. 73, 190 (2002); 10.1063/1.1424903 Characterization of a Hadamard transform time-of-flight mass spectrometer Rev. Sci. Instrum. 71, 1306 (2000); 10.1063/1.1150456

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REVIEW OF SCIENTIFIC INSTRUMENTS 85, 091301 (2014)

Invited Article: Characterization of background sources in space-based time-of-flight mass spectrometers J. A. Gilbert,1 D. J. Gershman,1 G. Gloeckler,1 R. A. Lundgren,1 T. H. Zurbuchen,1 T. M. Orlando,2 J. McLain,2 and R. von Steiger3 1 Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, 2455 Hayward St, Ann Arbor, Michigan 48109, USA 2 Georgia Institute of Technology, 225 North Ave NW, Atlanta, Georgia 30332, USA 3 International Space Science Institute, Hallerstrasse 6, CH-3012 Bern, Switzerland and Physikalisches Institut, Universität Bern, Sidlerstrasse 5, CH-3012 Bern, Switzerland

(Received 20 March 2013; accepted 28 July 2014; published online 17 September 2014) For instruments that use time-of-flight techniques to measure space plasma, there are common sources of background signals that evidence themselves in the data. The background from these sources may increase the complexity of data analysis and reduce the signal-to-noise response of the instrument, thereby diminishing the science value or usefulness of the data. This paper reviews several sources of background commonly found in time-of-flight mass spectrometers and illustrates their effect in actual data using examples from ACE-SWICS and MESSENGER-FIPS. Sources include penetrating particles and radiation, UV photons, energy straggling and angular scattering, electron stimulated desorption of ions, ion-induced electron emission, accidental coincidence events, and noise signatures from instrument electronics. Data signatures of these sources are shown, as well as mitigation strategies and design considerations for future instruments. © 2014 AIP Publishing LLC. [http://dx.doi.org/10.1063/1.4894694] I. INTRODUCTION

Measurements of space plasma have provided valuable data for understanding physical processes that occur in the Heliosphere and the environments of planetary bodies. The instruments designed to measure this plasma vary in their form and capabilities, and are often optimized to detect a certain type of material in a specific environment. Before these data can be analyzed, however, unwanted artifacts due to the hardware or the environment need to be accounted for and, if possible, removed from the raw data. This review discusses some of the more common sources of background and noise that affect the data of a variety of instruments, with a focus on mass spectrometers that utilize carbon foil time-offlight (TOF) techniques. Several sources of background are discussed, with examples provided from flight data and suggested strategies for mitigation. Early measurements of the upper atmosphere and ionosphere were made by instruments such as Geiger-Müller counters and Langmuir probes, which were used to determine energetic particle fluxes and plasma densities. Later, retarding potential analyzers (RPA) were developed not only for use in ionospheric and magnetospheric measurements, but also for interplanetary measurements. The Voyager missions, which are currently at the edge of the Heliosphere, possess RPAs in the form of Faraday cups with several parallel grids, whose voltage potentials create a filter for energyper-charge (E/q) selection.11 Curved-plate electrostatic analyzers (ESAs) with electrodes shaped as cylinders,94 spherical surfaces,6 top-hats,13 and other designs, have been commonly used for E/q selection and are able to deflect particles with less applied voltage potential than the more direct RPA designs.109 In contrast, spectrographs that use 0034-6748/2014/85(9)/091301/19/$30.00

static magnetic fields for charged particle deflection96 avoid the necessity of sweeping voltage potentials and can separate ions and electrons over a range of energies simultaneously, at the expense of the additional mass for the magnetic material as well as the effects that the fields may have on neighboring spacecraft instrumentation.107 For measurements that require the identification of the mass-per-charge of plasma components, several instrument designs have been used, sometimes in conjunction with ESAs. Sensors that use both electric and magnetic fields, such as Wien filters, include the mass-energy spectrometer onboard the Interplanetary Monitoring Platform IMP-F and IMP-G,76 which measured the solar wind, and the lowenergy ion mass spectrometer (IMS-LO) onboard the Combined Release and Radiation Effects Satellite (CRRES),16 which examined the plasma composition within Earth’s magnetosphere and radiation belts. Quadrupole mass spectrometers use the oscillation of ions between parallel rods to filter ions by their mass-per-charge (M/q), and are often used in neutral mass spectrometers, such as the Neutral Gas Mass Spectrometer (NGMS) on the Pioneer Venus Orbiter75 and the Ion Neutral Mass Spectrometer (INMS) on Cassini.100 Neutral particle sensors can have many design similarities with ion sensors, sometimes with the addition of electrostatic or magnetic fields for charged particle deflection at the entrance. Devices such as a conversion surface, carbon foil, or electron bombardment are used to create charged particles from the neutral atoms so they can be guided through the sensor.24,23, 100 Time-of-flight (TOF) techniques are often used in collaboration with ESAs to make separate measurements of the speed and the E/q of an ion, and thereby derive the M/q34 or, when combined with an energy detector, to measure the

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mass and charge separately.35 Sensors of this type have been used to measure the mass composition of ions up to MeV energies. Variations to the TOF design, such as the energyisochronous designs that measure a M/q-dependent TOF that is independent of the initial energy of the particle, have led to improved mass resolution in flight instruments such as the Mass Time-of-Flight (MTOF) sensor on the Solar and Heliospheric Observatory (SOHO),52 the Ion Mass Spectrometer (IMS) on Cassini,111 and the Rosetta Orbiter Spectrometer for Ion and Neutral Analysis (ROSINA) on Rosetta.5 The composition of plasmas in the heliosphere is often measured in situ using TOF mass spectrometers. Key discoveries from these instruments include the composition of pickup ions, which are neutral atoms that become ionized and “picked up” by the solar wind,40, 56 and of atomic ions in the solar wind heavier than the predominant Hydrogen and Helium ions,98 which will herein be referred to as “heavy ions.” The elemental composition of domains such as the interstellar medium, planetary atmospheres, comets, and interplanetary gas and dust can be studied in their pickup ions. The heavy ions reveal information about the origin of the solar wind and the formation and evolution of coronal mass ejections, powerful events that expel energetic radiation and plasma from the photosphere and lower corona out into the heliosphere. The isotopic and elemental composition measured by these instruments gives clues about the origin of the solar system and the physical processes governing the Sun. Furthermore, the composition and velocity distributions of the plasma environment around various planets, comets, and moons can provide insights into their origin, key physical processes, and evolution. A review of TOF sensors, including a chronicle of their history, a discussion of their respective limitations, and a list of instruments and the missions on which they have flown, can be found in Ref. 106, with additional discussion on the history and types of plasma mass spectrometers in Refs. 109, 110, 50, and 107. Often, the answers to important science questions are found in measurement regimes where the signal of interest is obscured by fluxes of background events that complicate data analysis. The term “background” typically refers to measured signals that were not the intended measurement target, and “noise” often refer to artifacts of the instrument electronics. While electronics noise will be mentioned briefly, this review will focus on background signals, which are herein defined as any measured event that would be eliminated or correctly identified in a perfect instrument. By identifying and characterizing some of the common sources of background in TOF spectrometers, as well as their physical and statistical behaviors, the effects of these sources can be corrected for and mitigated in future instruments with simple design considerations. This in turn will greatly increase the accuracy of such instruments, enabling new scientific discoveries. Because some of these sources can also affect data from instruments that do not rely on TOF systems for particle identification, such as electron analyzers, the principles described herein may be beneficial to such sensors as well. This paper will discuss some of the most common sources of background in the data of spaceborne TOF mass spectrometers, and discuss design guidelines to mitigate their

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effects before, or even during, flight operation. Two example TOF sensors are introduced in Sec. II: the Solar Wind Ion Composition Spectrometer (SWICS) onboard the Advanced Composition Explorer (ACE)41 and the Ulysses36 spacecraft, and the Fast Imaging Plasma Spectrometer (FIPS), which is part of the Energetic Particle and Plasma Spectrometer (EPPS) instrument4 on the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft.91 In Sec. III, each source of background is described, along with the effects on the measured in-flight data, with additional discussion in Sec. IV. II. DESCRIPTION OF EXAMPLE TOF SENSORS

In the most general sense, spaceborne TOF sensors consist of detectors to measure the start and stop signals of incident ions or neutrals, and electronics to calculate the valid TOF values from these detectors. Other sections of the instrument, e.g., an electrostatic analyzer, neutralizing surfaces, retarding potentials, shutters, etc., are tailored to meet the demands of the intended measurement species. Many of the background sources detailed in this paper affect a variety of instrument designs. Here, we focus on designs that utilize secondary electron emission from thin carbon foils for TOF “start” triggers.86,66 The discussion can also be applied to carbon in the graphene state, which can be used to make foils of only a few atomic layers in thickness. Initial experiments on the angular scattering and charge exchange properties of graphene foils have shown them to be excellent candidates to replace the thin, amorphous carbon foils presently in use in space instruments.3, 18 To facilitate the discussion, two specific TOF system designs are used here as examples: (1) linear grid-free TOF systems (e.g., Refs. 34 and 36) and (2) TOF systems that use electrostatic mirrors or grids (e.g., Refs. 104 and 4). Other designs, such as the isochronous linear-electric-field TOF (e.g., Refs. 48, 65, 5, and 30) may be affected by some of these background signatures as well. In an electrostatic-grid design, wire is often wound in a pattern of parallel lines similar to a harp. Voltage applied to this harp will create a uniform potential (accounting for the effects of field penetration in the gaps) while still possessing a large open area for particle transmission. Designs that utilize electrostatic grids within the TOF chamber are able to create fields with the necessary shape for ion or electron guidance; however, ions can impact the grid causing angular deflection or secondary electron emission. Grid-free designs avoid this, but are not always able to create the desired field shape with the same degree of accuracy. A. SWICS: A grid-free TOF mass spectrometer

The SWICS sensors have discovered most of the known heliospheric pickup ion species (e.g., Refs. 37, 26, 27, 39, and 42), as well as elucidated the compositional differences between the steady (usually fast, compositionally like the photosphere) and unsteady (compositionally like the corona) solar wind.98 The sensor, shown schematically in Fig. 1, is mounted on a spinning platform to sweep over a large field of view, and consists of a collimator, a small-angle deflection ESA to


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FIG. 1. Schematic representation of the SWICS ESA and TOF sections. Ion and secondary electron trajectories are shown, as well as the three detectors used for triple-coincidence measurements: microchannel plate detectors for (1) start and (2) stop time-of-flight signals, and (3) solid state detectors for measurement of ion energy. Some sources of background are also illustrated: (A) penetrating particles and radiation, (B) UV photons, and (C) energy straggling. Adapted c ESO. from Ref. 36, reproduced with permission

select the ion energy-per-charge (E/q), and a grid-free TOFEnergy analyzer that records both the time of flight and the total ion energy (E). Light traps and serrated, black coated surfaces on the deflection plates within the ESA serve to attenuate incident photons. The grid-free design also avoids the intrinsic issues, such as ion energy losses, reduction in ion transmission, and secondary electron emission,104 that come from having wire grids or harps in the ion path. SWICS is modeled after the low-background triple-coincidence design for sensors that measure the mass composition and energy spectra32, 33 of ions in space. After ions pass through the electrostatic deflection of the ESA, they enter a region of post-deflection acceleration,102 often abbreviated as post-acceleration. There, the ions are accelerated in proportion to their charge state, typically by voltages of 10-30 kV (e.g., Refs. 33, 36, 25, and 4). This acceleration reduces the amount of energy straggling and angular scattering that the ions experience as they pass through a thin carbon foil and enter the TOF section. In many cases, this acceleration also allows the ions to register measurements above the energy threshold of the solid state detector (SSD).54, 98 Ions that pass through the foil cause secondary electrons to be ejected from both the entrance and exit surfaces of the foil.83,1 The electrons that accompany an ion into the TOF system are electrostatically deflected toward a microchannel plate (MCP) detection assembly, where they trigger a start signal for the flight time. The original ion continues with a straight trajectory and impacts the SSD. Secondary electrons are released from the SSD and guided toward a MCP assembly where they trigger the stop signal for the ion flight time, and the residual energy (E) of the ion is recorded by the SSD. A schematic diagram showing voltage values for electrodes within the TOF system can be found in Ref. 36. The start (1), stop (2), and energy (3) detectors shown in Fig. 1 all must be triggered within a set measurement time for a valid “triple-coincidence” event to be recorded. The measured TOF (τ ), the E/q setting of the ESA, and the measured

energy (Emeas ) can be used to calculate the mass (M), massper-charge ratio (M/q), and the incident energy (E0 ) of the ion as shown in Eq. (1) through Eq. (4). Other parameters in these equations include the distance that the ion travels within the TOF chamber (d), the post-acceleration voltage (VA ), the nuclear defect of the solid state detectors (α), and the energy loss that the ion experiences when passing through the carbon foil (Eloss ) 2 1 d Emeas = M , (1) α 2 τ 2 1 M d E E + VA − loss = , (2) q q 2 q τ q=

Emeas /α , (E/q + VA − Eloss /q) q E0 = . E/q

(3) (4)

If the SSD is not triggered during an ion measurement, which is common for heavy ions with low charge states such as pickup ions, the start and stop TOF signals can still create a “double-coincidence” event from which the M/q can be calculated,36 as shown in Eq. (2). For later reference, some sources of background events are marked in the figure: (A) penetrating particles and radiation, (B) UV photons, and (C) energy straggling at the carbon foil. B. FIPS: A TOF mass spectrometer with deflection grids

The FIPS sensor, mounted on a three-axis stabilized platform, consists of an ESA with an annular aperture, a post-acceleration region, and a double-coincidence (start and stop detectors are both triggered during a measurement) TOF section with electrostatic mirror harps12 used for secondary electron deflection. The 45◦ angle between the harps and the


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FIG. 2. The FIPS sensor. Ions are guided through an ESA that is optimized for UV reduction, through a post-acceleration region, carbon foil, and into an electrostatic mirror TOF system. Some sources of background are marked: (D) electron-stimulated desorption, (E) ion-induced electron emission, and (F) accidental-coincidence detections. Adapted from Ref. 4, reproduced with kind permission from Springer Science and Business Media.

carbon foil ensures that the incident positions of ions passing through the foil, including their incident angles, will be mirror-imaged by secondary electrons onto the start anode. The inner surfaces of the ESA deflection plates are serrated and treated to improve the photon attenuation. In addition, the detailed design of the ESA ensures that any incident photon will undergo at least three surface reflections before arriving at the carbon foil. Fig. 2 shows a schematic of the FIPS sensor, with examples of three potential sources of background marked. Electrons emitted from high-voltage wires, such as the mirror harps or wire grids, can strike surfaces within the TOF chamber and cause electron-stimulated desorption (ESD) of ions (D). These electrons can also strike the MCP detectors directly, affecting the calculations of flight times. Ions, including those that are incident from space and those generated by ESD processes, can strike grids or other surfaces within the instrument and generate secondary electrons (E); a process called ion-induced electron emission (IIEE). The secondary electrons produced by this effect may trigger signals on the start or stop MCPs. Finally, accidental-coincidence measurements (F) can occur when the start and stop timing signals are triggered by two different ions. For reference, the carbon foil and the central mirror harp are both set to the negative postacceleration voltage VA , while the other harps and the TOF housing are set to 14/15 VA . The MCPs on FIPS are arranged in stacks of 3, or z-stacks, to increase the electron multiplication and create a strong signal on the detection anode.95 The total voltage drop across each stack is the negative voltage VMCP , with the front (TOF side) of the MCP stack set to 3.5/15 VA + VMCP , the back of the MCP stack set to 3.5/15 VA , and the detection anodes at 2.5/15 VA . One known source of background on the FIPS sensor involves a combination of processes (D) and (E). Electrons that strike the start MCP may desorb positive ions from the surface in addition to triggering start timing signals, and these desorbed ions are accelerated away from the MCP surface toward the TOF chamber. These ions can strike the harps, grids,

or any other surface within the TOF chamber, and may cause secondary electrons to be emitted. If the desorbed ions impact specific areas of the FIPS TOF chamber, the resulting secondary electrons are pulled toward the stop MCP, triggering stop signals and registering TOF events. The initial electron that initiates this process could be a secondary electron generated at the carbon foil by a passing ion, or it could be field emission from high voltage wires within the chamber. Ion optics modeling of this process, and comparison with flight data, are discussed in Appendix A. III. SOURCES OF BACKGROUND EVENTS

The concept of background in a data set can apply to a broad range of topics. This paper will focus on some of the most common contributors to background, including their causes and techniques for mitigating their effects. Common background sources that will be discussed in Subsections III A–III G include radiation and high-energy particles that penetrate the housing of an instrument, and photons, particularly UV, which can reflect off of surfaces and eventually traverse the ESA,113,28 stimulating emission in the carbon foil53 or triggering channel electron multipliers or microchannel plate detectors directly.62 Unless specifically indicated, for purposes of this discussion the general term “particles” refers to electrons, ions, or neutrals regardless of their source. Also included are ions initiating from the ESD of instrument surfaces and electrons from IIEE,49 which can increase detector background event rates. While these can be independent of the ESA voltage settings, high incident flux during specific voltage steps can increase background signals during those steps due to a higher chance of ESD or IIEE occurring. ESD will release low-energy particles, both ionized and neutral, that can trigger detectors and create a clear signature in the distribution of measured events. IIEE can create measured signals either by impacting the detectors directly or by subsequent ESD of ions.


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Some background signals can be associated with a specific E/q range of incident ions. For example, ions experience energy straggling as they pass through the thin carbon foil. This energy loss process has been characterized extensively55,2, 112,31 and causes the ions to have lower energies and longer measured TOF values than what is typical for their species, which potentially leads to a misclassification of mass and M/q. As another example, accidental coincidence measurements will appear at the E/q step of incident ions with times of flight that do not correspond to their true M/q. Ions that are misidentified due to energy straggling or accidental coincidences will contribute to the level of background in the data. Finally, noise signatures can be caused by instrument electronics. These sources may be highly instrument-specific, but an illustrative example demonstrating the impact of such noise will be discussed in Subsection III G. Some instrumental effects, such as events that are missed due to detector efficiencies, recovery time in the detectors or TOF electronics, or particles excluded due to limited field of view or analyzer stepping sequences, are outside the scope of this paper as they would not produce a background signal in the data. During data recovery, these and other effects can be accounted for using metrics such as the geometric duty cycle or the geometric factor.43, 44, 108

A. Penetrating particles and radiation

High-energy particles such as cosmic rays, as well as energetic protons and electrons, have energies sufficient to penetrate the housing of an instrument. Penetrating radiation can also be created by energetic electrons, which can generate Bremsstrahlung radiation upon impact.97 Mass constraints on space instruments limit the amount of physical shielding that can be used, making penetrating particles and radiation a common source of background.

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1. Signatures of penetrating particles and radiation

For a TOF spectrometer, penetrating radiation will be detected independent of the ESA voltage setting, i.e., counts will appear in the measured data at all E/q steps, and can generate events at all TOF values. In some cases, a penetrating particle or photon will trigger either a start or stop signal coincident with another detection – whether that be a penetrating particle, an ion, or electron emitted within the instrument, or one that is filtered by the ESA as intended – and generate a valid TOF measurement. As an example, Fig. 3 shows detector count rates (s−1 ) from the ACE-SWICS main ion channel during the Bastille Day event of 2000, a series of solar flares and interplanetary coronal mass ejections in which measured energetic proton fluxes surpassed 104 (MeV cm2 sr s)−1 .90 The top panel shows the count rates in one of the E/q channels (65 keV/e) for each type of measurement: start rate, double-coincidence event rate, and triple-coincidence event rate. In the remaining panels, the vertical axes indicate the E/q value of the incident ions, and span the entire E/q range of SWICS. Data are collected in each of the 60 E/q steps for 12 s, and thus a full scan requires 12 min of measurement time. The count rates are shown for the start MCP, double-coincidence (both start and stop MCPs are triggered), and triple-coincidence (both MCPs and the SSD are triggered). The proton track, seen as the lower E/q of the two ion tracks (He2+ being the higher E/q track), is intentionally truncated in the main channel of the triple-coincidence data. To better isolate the low-flux signal of heavier ions in the main channel, SWICS has an auxiliary channel (see Fig. 1) dedicated to the energy range and flux rates of proton measurements. During the event, the level of background increased by several orders of magnitude and remained high for more than one day. Although the levels of background events were quite high during this event, the triple-coincidence measurement provided the best background suppression and had the shortest

FIG. 3. ACE-SWICS count rates during the Bastille Day event in 2000. The count rates of ions with E/q = 65 keV/e are shown (top) to illustrate the background level, which, in the triple-coincidence rate, is significantly lower and has a shorter recovery time than the background level in the start rate or doublecoincidence rate. The count rates of the start MCP, the double-coincidence events, and triple-coincidence events increase in all E/q channels from penetrating particles.


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recovery time, and ion composition measurements were successful.90 2. Mitigation strategies for penetrating particles and radiation

For data sets that contain background events from penetrating particles and radiation, a standard removal procedure is to estimate the particle flux in E/q steps that normally do not have any real events, and subtract this background level from the data. A successful approach used by several instruments is to incorporate “anti-coincidence” techniques, which are particularly useful if a low-flux signal is being measured. An anti-coincidence detector would be placed behind the detector used for particle measurement. If a particle is energetic enough to penetrate through the particle detector and also trigger the anti-coincidence detector, it can be discarded as penetrating radiation, substantially improving the signal-tonoise ratio of the data set. These were originally used in space to reduce the background events in instruments such as the Electrostatic Energy-Charge Analyzer (EECA)19 on IMP-7 and IMP-8, and the Solar Energetic Particle Ionic Charge Analyzer (SEPICA)72 on ACE. Triple-coincidence measurements are also highly effective in mitigating the contributions of penetrating radiation, as illustrated in Fig. 3. B. UV photons

MCP detectors have a considerable history of measuring photons in space and have been used in missions that examine wavelengths ranging from visible to X-ray.88, 89 They can be triggered by direct photon impact when photon energies are ≥4 eV,78 or by photoelectrons released from the carbon foil or other surfaces. The hydrogen emission line of 121.6 nm, Lyman-α, is strongly emitted by the Sun, and has energy sufficient to create MCP signals that are indistinguishable to those of particles.103, 113 A light leak in a TOF instrument will raise the floor level of background at all E/q steps and in all TOF channels. These background events from UV/EUV can overwhelm any real signal due to the extremely high solar photon flux, particularly in sensors that have an aperture facing the Sun. During solar maximum, for example, the Lyman-α flux at 1 AU can be over 4 × 1011 photons cm−2 s−1 ,60 so a rejection rate of >1:1010 is desirable for particle sensors with apertures exposed to direct solar UV.74 1. Signatures of UV events

UV photons can be absorbed by the carbon foil, liberating an electron that may trigger a start signal.53 If the photon itself traverses the foil, it may trigger a stop signal directly.46 A single photon is therefore not able to trigger a doublecoincidence event on its own. It can, however, contribute to accidental coincidence events, as described in Sec. III F. Gaps or other openings in the sensor housing may permit light to enter the instrument. Such light leaks will cause a raised level of background on photodiodes or will trigger counts on MCPs if the photons have a path to the detectors. On spinning spacecraft, a UV leak into the detector area will manifest itself as a spin-synchronous signal.

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2. Mitigation strategies for UV

A study by Gershman and Zurbuchen28 used ray tracing simulations along with models for scattering and reflection off of various surfaces to calculate UV transmission through a model of the high-resolution MASS spectrometer (MASS) on the Wind spacecraft.38 They found that UV transmission is a strong function of the material selection and coating used within the instrument, as well as the number of surface reflections the photons experience prior to reaching the detector. Significant photon flux was found to transmit through the modeled sensor even after several reflections, underscoring the importance of incorporating photon attenuation into sensor design, such as the traditional minimum “3-bounce rule.”73, 107 Historically, light traps and optical baffles have proven highly effective in reducing UV flux, as have serrated plates and black surface coatings (e.g., Refs. 34 and 68). By creating serrated, or scalloped surfaces, specular reflections of photons are hindered and the scattering efficiency reduces by about a factor of three.14 Blackened coatings have varying degrees of reflectivity depending on the material used. Analysis by Zurbuchen et al.113 shows excellent low-reflection properties for surface coatings of CuO and Cu2 S, and the review of about 2 dozen black surfaces by Persky79 characterizes the reflectance and outgassing properties of flight-tested coatings including Martin Black and Chemglaze Z306, both of which were used on the Hubble Space Telescope. The SWICS instrument, which uses a combination of light traps, serrated plates, and black coatings, has UV background suppression better than 1:1012 .28 Some foil-based designs for energetic neutral atom detectors46, 71 or high-energy ion detectors,4 allow the foil to be directly exposed to incoming UV photons. In these cases, solar UV has been suppressed by using thicker foils, foils with specialized coatings,52 or nanoscale transmission gratings.87,45 While increasing the thickness of the foil will result in a reduced UV transmission, it will also reduce the particle transmission and increase the degree of scattering. In addition, developments in nanotechnology are advancing the light-suppression capabilities of spaceflight hardware. For example, the use of nanogratings to suppress UV photons but permit neutral atoms to pass unimpeded has been tested successfully in flight80,67 and offers the possibility of lighter instrumentation, free from the necessity of mechanical light traps or baffles.57 As an alternative surface treatment, multiwalled carbon nanotubes have been found to provide superior absorbance of UV; up to an order of magnitude over Z306 paint.47

C. Electron stimulated desorption

Desorption induced by electronic transitions (DIET) refers to non-thermal desorption of atoms, molecules, and ions from surfaces. Although many reviews exist on this topic,81,64 the general phenomenon is not well known in the space science community. Some general comments are therefore presented that are specifically relevant to the stimulated desorption of ions as a source of background in space-based


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TOF mass spectrometers. When electrons are the primary excitation source, DIET is more specifically referred to as ESD. An important aspect of ESD is that forces leading to desorption are due to the repulsive nature of the excited electronic states. This is in contrast with typical elastic ion sputtering, which relies on the momentum exchange between ejecta and an incoming particle.7 In ESD, the original incident highenergy electron triggers the production of a cascade of low energy secondary electrons over the penetration distance within the target material.63 These secondary electrons undergo inelastic scattering prior to trapping or release. The inelastic scattering can excite the surface or adsorbate-substrate complex via direct ionization, direct electronic excitation, and resonant attachment processes. These lead to desorption of cations, neutrals, and anions, respectively. Substances such as organic contaminants and water that are adsorbed onto the surface of a material, or to the terminal surface sites, can undergo DIET or ESD. This occurs from oxides,59 minerals,69 as well as adsorbate-covered metal surfaces.10 The overall ESD cross sections are higher for oxides and minerals due to the effective screening and quenching typical of metal substrates. For the case of space instruments, ESD is relevant for both insulating and conducting surfaces. In the case of an insulator, such as parylene coating, incident electrons can readily desorb both neutral and ion species from the adsorbed contaminant monolayers. An insulating or high-band-gap material releases cations and neutrals from the lattice by an Augerstimulated multi-electron process. Adsorbates on insulators or high-band-gap materials also undergo ESD with high cross section due to longer excited-state lifetimes. For conducting material, the electron density at the Fermi level significantly enhances the probability that a desorbed ion from a metal will neutralize.70 In TOF systems, there are several sources of electrons suitable to cause desorption of instrument surface material, such as IIEE from surfaces, forward and backward secondary electron emission from the carbon foil,83 or field emission of electrons from high potential wire grids or sharp corners in the instrument.20 These secondary electrons are created with only 1-2 eV with respect to their surface potential, but can be accelerated within the instrument to energies that are sufficient for ESD. In fact, most ESD processes have an ion energy threshold on the order of 10 eV.81,69 However, to be a source of background, the ions desorbed by ESD must trigger a double-coincidence event. Such a process is most likely to originate in two areas of an instrument: the post-acceleration region, discussed in conjunction with IIEE in Sec. III D, and the surface of the start MCP, discussed here. The background events produced by this process will have TOF values that correspond to the velocities of ions or neutrals desorbed from surfaces within the instrument and accelerated by local fields, and will be independent of the E/q settings of the ESA.

1. ESD and MCPs

The MCPs commonly used in start and stop detector assemblies contain arrays of angled channels with high lengthto-diameter ratios. These channels are composed of leaded

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glass treated to be semiconducting and to have a high secondary electron emission.105 The MCP surfaces are covered with a conductive coating to allow a potential to be applied across each plate. An incident particle or photon initiates a cascade of secondary electrons in one of the channels which, due to the electric field across the plate, accumulates and accelerates out of the other side of the MCP as a charge cloud that can readily be measured. The initial particle as well as cascaded secondary electrons can desorb ions from the MCP channels and surface.93,58 Just as electrons are accelerated toward the MCP, newly created ions are accelerated away—toward the original particle’s direction of incidence. This effect is well known for photon detection applications, and is called ion-feedback or ion-poisoning as desorbed glass ions from the MCP channel walls cause damage to the input photocathode.77 For TOF applications, if the start and stop MCP assemblies are located directly across from each other, the ions or neutrals desorbed from the start MCP could impact the stop detector directly, creating a TOF measurement in the data. In order to determine the types of desorbates expected to be observed in flight, laboratory ESD analysis was performed on a flight-spare MCP from FIPS using the experimental setup of Ref. 69. Prior to these lab experiments, the MCP had been cleaned and stored in a nitrogen-purged cabinet to insulate it from humidity. Fig. 4 shows the M/q spectra of ions desorbed from the MCP surface by incident 1-keV electrons at a vacuum pressure of 5 × 10−10 Torr. The majority of the desorbed ions are from organic contaminants (C, H) and water group ions, with H+ being the desorbate with the strongest measured signal. Only trace amounts of MCP glass material (SiO2 ) were observed, with small peaks at M/q = 16 amu/e for O+ and M/q = 28 amu/e for Si+ . While the measured O+ may also be a daughter product of the adsorbed water or organic compounds, the peak at 28 amu/e is very likely Si+ from the MCP glass and not a compound with similar M/q values such as CO+ or N2 + . Molecular Nitrogen does not adsorb strongly to glass, and is efficiently pumped by the vacuum system. While CO is difficult to remove from ultra-high vacuum (UHV) systems due to its large affinity for metals, the M/q = 28 amu/e peak was not observed until higher e− energies were used, consistent with previous ESD experiments on the desorption of Silicon from glass surfaces.101 The relative strength of ESD for electron energies from 10 to 1000 eV is also shown in Fig. 4. Above ∼300 eV, ion desorption yields of all species remain relatively constant. Unlike ion sputtering processes, higher energy incident electrons are still expected to deposit significant energy near the surface of the sample, and therefore similar mass spectra are expected even at incident energies of several keV. The process of ESD is very sensitive to monolayer coverage of adsorbates, but is not very sensitive to gas-phase species due to the low number densities and cross sections. Most volatiles produced by a spacecraft are water and organic hydrocarbons,85 the same volatiles that are present in minute quantities in a UHV system. The organics that were present on the MCP tested here, however, likely adsorbed to the MCP surface during exposure to Earth’s atmosphere. The ions shown in the mass spectrum of Fig. 4 are H+ (mostly


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FIG. 4. The mass spectra of desorbed ions from a FIPS flight-spare MCP using 1-keV incident electrons show trace amounts of MCP glass ions and a variety of hydrocarbons desorbed from the surface. The energy dependence of desorbed ion yields is shown for various ion species.

from –OH and –Cx Hy groups) and the most stable –Cx Hy + fragments from larger hydrocarbons. Larger mass fragments also desorb from the MCP during ESD but mostly as neutrals, rather than as ions, due to the desorption kinetics. These are therefore not an important component of the background ion spectrum. Due to the formation of water or hydrocarbon monolayers when exposed to air, all instrument surfaces will be coated by them until they are removed through some means, such as in-flight high-temperature bake-outs, desorption by incident electrons or photons, or ion sputtering. Since the majority of the measured desorbates are from adsorbed monolayers rather than surface material, a M/q spectra similar to that shown in Fig. 4 is expected not only from ions desorbed from MCPs, but from other instrument materials and surfaces as well. 2. Signatures of ESD background

An example of background events from ESD processes can be observed in flight data from FIPS. The wire harps used to establish a controlled potential within the TOF region, and to form the electrostatic mirror harps, are held at high volt-

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age potentials and therefore emit electrons at room temperature. Additionally, field emission electrons can come from sharp points on the ends of the high voltage cables, where bare metal wire or fasteners are used to make contact. Although the TOF chamber is nominally a field-free region,4 field penetration through the harps creates a small attractive potential that draws low-energy secondary electrons toward the start MCP, as shown in D of Fig. 2. These two sources of electrons, the wire harps and the high voltage cables, create two distinct groupings of ESD-based background events in the FIPS data, both of which have been characterized and removed in post-processing.29 For the first group, electrons emitted from the carbon foil during an ion passage, or from the wire harps due to field emission, are guided toward the start MCP. These desorb ions and neutrals from the channels and surface of the MCP while also triggering a start signal. Desorbed ions are accelerated to energies of ∼5 keV toward the roof of the FIPS TOF chamber, where they cause secondary electrons to be emitted, as shown in E of Fig. 2. Field penetration through the mirror harps in the “stop” half of the TOF system guides secondary electrons toward the stop MCP, resulting in a correlated start-stop pair, i.e., an ESD-based event. In the second group, beams of electrons emitted from nearby high voltage cables outside of the TOF chamber can reach the edges of the start MCP on FIPS. This field emission creates a “hotspot” of ESD-based background events. Ions desorbed from the MCP by this field emission are subject to fringing field effects such that their trajectories may not reach the top of the TOF chamber, but rather strike the sides. Similar to the first group, secondary electrons are emitted and trigger a stop signal, generating a valid TOF event. For these TOF events, the travel distance to the sides of the TOF chamber is shorter than that of the first group, which must travel to the top of the TOF chamber. The ESD-based events in this second group are therefore found with a fraction of the TOF as those of the first group. These effects create two sets of ESD-based events, a higher-TOF group of desorbed ions that hit the roof of the FIPS TOF chamber, and a lowerTOF group of desorbed ions that strike the sides of the TOF chamber. During periods of high incidence flux, there will be an increase in secondary electron emission from the foil at the TOF system entrance. In the E/q steps that correspond to the high flux, the rate of ESD background events will be enhanced as more secondary electrons strike the start MCP and desorb ions from its surface. To characterize these ESD-based background events in flight, measurements were taken with a variety of voltage settings in the TOF section, while the ESA was set to reject incoming ions. The two groups of ESD-based background events are apparent in the solid black line of Fig. 5, which had a MCP high voltage setting of VMCP = −2600 V. The shaded region shows three peaks in the lower-TOF group of ions that are desorbed mainly from the hotspot of electron emission visible near the edge of the MCP position image. The locations of the higher-TOF peaks match the travel times of the desorbates from the surface of the start MCP to the roof of the TOF chamber, as determined using a three-dimensional


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FIG. 5. Significant reduction of localized ESD events was achieved by modifying the stray electric fields near the edge of the start detector assembly by lowering the VMCP bias. (Left) The TOF spectra show sets of peaks from the hotspot area (shaded) and from the wire harp electron emission. Certain voltage settings reduced the occurrence of hotspot events. The spatial location of the TOF start signal for two voltage settings indicates when background events were (center) and were not (right) generated from the ESD hotspot.

ion-optics model of FIPS in SIMION software,17 described in Appendix A. The locations of the lower-TOF peaks appear at a constant fraction of the higher-TOF peaks, indicating that they originate from identical ion species following different flight paths. With an adjustment of onboard VMCP settings to −2500 V, the hotspot was eliminated from the MCP image and the background peaks in the shaded region disappeared, as shown with the red dashed line.

3. Mitigation strategies for ESD

The high voltage wire that supplies the FIPS start VMCP is in close proximity to the location of the ESD hotspot. When the VMCP was adjusted by only 100 V (from −2.6 kV to −2.5 kV across the 3-MCP stack), the signature of these hotspot events disappeared. This may have been due to a change in the fringe fields, causing the electron beam to be directed away from the MCP active area. During flight tests, prior to orbital insertion at the planet Mercury, the ESA voltages were set to prevent any incident ions from entering the FIPS aperture, VA was held constant at −10.5 kV, and the VMCP was sequentially adjusted to find an optimal setting for background reduction. The adjustment of the VMCP was the only change to the sensor during this time period and stands as an example of a successful in-flight mitigation strategy of ESD background. Reducing the surface contamination from organic compounds and water molecules can also help reduce the effects of ESD. However, this reduction is extremely difficult to accomplish. In order to release adsorbed molecules from surfaces, the instrument must be baked at high temperatures. While this is possible in a laboratory setting, it is usually impractical during flight, and contaminant monolayers will quickly accumulate on the surface once removed from vacuum on Earth. Therefore, potential remedies to minimize these contaminants include backfilling the system with pure nitrogen gas until launch or purging with a clean gas and then hermetically sealing the system for cleanliness and humidity control. These precautions will not prevent the adsorption of monolayers, however. For example, the MCPs used in flight on FIPS were baked and cleaned, then stored in a nitrogenpurged cabinet until integration and testing. FIPS was then

stored under high vacuum until its final integration with the spacecraft, and the instrument was purged with nitrogen up until launch. Even with these precautions, adsorbed contaminants can still be seen by an experienced examination of the raw flight data. During design and simulation, potential sources of electrons in the instrument should be identified and modeled. Wire harps, grids, or electrostatic lenses can be added to prevent electrons from backscattering from the carbon foil, and the front of the MCPs can be set at a small negative potential with respect to the surrounding TOF chamber to prevent desorbed ions from accelerating away from the MCP. Simulations of electron and desorbed ion trajectories (Appendix A) can be invaluable in predicting significant ESD background in instruments. Finally, during calibration, instrument data should be accumulated in the absence of incident particles to best characterize any internal sources of electrons and desorbed ions. Because ions are emitted from the front surface of MCPs, it is possible for ions to be desorbed from one MCP and trigger a signal on the other, creating a spurious TOF signal. Design considerations such as offset MCP locations, iondeflecting electrodes, or a physical barrier should be put in place to prevent ion feedback between the MCPs, as exemplified on each of the three SWICS instruments.36, 38, 41 D. Ion-induced electron emission

Ions can initiate background events when combined with electron stimulated desorption. For instruments that use postacceleration, there may be a clear background signature in the data that is attributable to a combination of IIEE and ESD. Improved mass resolution is achieved by floating the entire TOF chamber at VA . Ions desorbed from surfaces outside of the TOF region can be accelerated into the TOF region by VA . The possibility of increased background from these desorbed ions is a known tradeoff for the improved mass resolution attained by the use of post acceleration. A sketch of a sample post-acceleration region from SWICS is shown in Fig. 6 with key events numbered. (1) An ion exiting the ESA is post-accelerated to raise the ion energy above any SSD energy threshold, with the


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FIG. 6. Trajectories of desorbed protons in the SWICS post-acceleration region. (1) Incident ions can strike a wire harp whose purpose is to suppress secondary electrons back-scattered from the carbon foil. (2) Ion-induced electrons from the harp are accelerated back toward the ESA, where they may strike the ESA housing and desorb ions from its surface. (3) These desorbed ions are accelerated and may enter the TOF system, where they trigger a measurement.

added benefit of a reduction in the amount of energy straggling and angular scattering at the carbon foil. The resolution of the instrument therefore typically increases with higher VA , which is about −25 kV on ACE-SWICS, for example. The carbon foil is held at VA , and a wire harp between the carbon foil and the high voltage housing is biased slightly negative (−13 V) with respect to the foil. Secondary electrons back-scattered from the foil during ion transit are prevented from entering the postacceleration region by this harp. While the open area of the harp allows the majority of ions to pass freely through, some incident ions will strike it, leading to IIEE. These secondary electrons will be repelled by the harp and guided into the post-acceleration region, where they will be accelerated back toward the ESA. (2) If the secondary electrons strike the grounded surface of the ESA housing, they can desorb ions via ESD. Positive ions that are desorbed from the surface will immediately be accelerated toward the carbon foil by VA . This effect can be exacerbated if the impact surface has insulative properties, such as a Parylene coating. (3) These ions are carried through the post-acceleration region into the time-of-flight system where they can trigger a real TOF signal. 1. Signatures of ion-induced electron emission

In the data, these events will be characterized by their highly specific TOF values, independent of the E/q settings of the ESA. For ions created near the entrance of the postacceleration region, the dominant charge is q = 1, and hence they will look exactly like space ions at rest (i.e., 0 eV). Their flight time will correspond to the speed gained in the postacceleration region, accounting for any losses experienced during the transit of the carbon foil, and their count rate will be largely proportional to the count rate of real ions in every E/q step. The proportionality is not exact since highly charged ions extract more electrons from the foil and thus lead to more

FIG. 7. SWICS data from 2004, with the total number of counts during the year indicated by the color scale, and modeled tracks for several ions in E/q-TOF space shown in black. SWICS double-coincidence data show the E/q-independent desorbed H+ track centered on 48 ns and rising vertically through the entire E/q range. Due to the energy threshold of the SSD, the desorbed proton background is not clearly apparent in the SWICS triplecoincidence data for the same time period.

such 0 eV events. For ions created inside of the TOF system, such as those desorbed from a MCP, the TOF will relate to the distance and speed the ion travels before triggering the stop signal, either directly or by inducing a secondary electron that triggers the stop MCP (source E in Fig. 2). ACE-SWICS double-coincidence and triple-coincidence counts from all of 2004 are histogrammed in Fig. 7. The color scale indicates the total number of counts during the year, and the modeled tracks for several ions in E/q-TOF space are traced with solid black lines. In the double-coincidence data, a vertical streak is present at TOF values around 48 ns, which corresponds to measurements of desorbed H+ that possess only the energy gained from post-acceleration. This signal is enhanced during times of increased incident ion flux, as expected for an induced desorption process. This same time period is shown for triple-coincidence data, and the vertical proton streak is virtually absent, as expected. The energy gained in post-acceleration alone is usually not sufficient for most H+ ions, real or desorbed, to overcome the SSD energy threshold. A comparison between the two data sets indicates


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the TOF section. These are likely caused by ions or electrons being ejected from surfaces within the TOF chamber (such as the 60-ns peak), or due to electronics hardware (such as the spike at 50 ns) as discussed in Sec. III G.

2. Mitigation strategies for ion-induced electron emission

Similar mitigation strategies to those described for ESD also apply to reducing background events caused by IIEE. If a PAHV is used, a triple-coincidence measurement combined with the energy threshold of a solid state detector can filter out ions desorbed in the post-acceleration region. Also, as shown in Fig. 6, a wire harp can be used to prevent backscattered electrons from the carbon foil from reaching the post-acceleration region.

E. Energy straggling

FIG. 8. The TOF of a proton peak shifted from ∼51 ns to ∼48 ns after the PAHV of ACE-SWICS was increased. These protons possessed only the energy gained by the PAHV, and were independent of the E/q setting. Smaller peaks that remained stationary across the voltage increase were caused by other sources such as ions or electrons being ejected from surfaces within the TOF region, and electronics noise.

that only about 1% of the “real” protons seen in double coincidence trigger a SSD signal, and because the desorbed protons have one to a few keV less energy than the real protons, they are suppressed even more. An experimental verification of this background source can be made by adjusting VA and measuring the associated TOF shift in the desorbed peak. In ACE-SWICS, prior to 4 May 2000, a proton with only the energy gained from VA had a theoretical time of flight of 52 ns. After that date, VA was increased by 3 kV, speeding up the theoretical proton time of flight to 48.5 ns. Fig. 8 shows one-year accumulations of ACE-SWICS data for the years 1999 and 2007, covering preand post-voltage ramp-up. To eliminate the signal of the solar wind and most pickup ions, only data with E/q > 40 keV/e were used. A comparison between the two years shows one TOF peak that shifts from ∼51 ns to ∼48 ns, indicating a faster speed and thus an increased energy of the incident ion. The TOF values of this shifting peak coincide with those of a proton possessing only the energy gained by VA used during each of the respective years. The other peaks in Fig. 8 did not shift when the voltage was changed, eliminating the possibility that they were caused by ions originating from outside of

The energy lost by ions as they pass through the carbon foil can be derived from experimental data,55,2 or can be calculated using software such as the Stopping and Range of Ions in Matter (SRIM).112 The distribution of energy loss that an ion experiences can be seen in the data points of Fig. 9, which shows results from a SRIM Monte Carlo simulation of 275 keV iron atoms going through a carbon foil 2.5 μg cm−2 thick. Such is the energy that a typical solar wind iron charge state, Fe9+ , would have after gaining energy in an instrument’s 25-kV post-acceleration region. The ions will lose energy in the carbon foil, with the majority of ions fitting into a Gaussian distribution of energy loss, as indicated by the ideal Gaussian overlaid as a solid line. For some of the ions, however, collisions in the foil will de-energize and therefore decelerate them to form a tail of high energy loss with a falloff proportional to e−x . These straggled ions will pass through the TOF system with a range of measured flight times, corresponding to their decreased speeds. Since they pass through the ESA as intended, these decelerated ions will be assigned to their correct E/q values in the data, but the range of measured times of flight and energies may lead to calculated M or M/q values that are different than that of the original ion.

FIG. 9. Simulated energy loss for a mono-energetic beam of 275-keV iron atoms that pass through a 2.5 μg cm−2 carbon foil. An exponentially decreasing tail of energy loss due to straggling in the carbon foil is visible in the distribution.


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straggling will therefore have minimal effect on the mass resolution. However, ions whose trajectories are not reversed by the linear electric field, such as those who exit the carbon foil with neutral or negative charges, will still suffer reduced mass resolution from energy straggling. F. Accidental coincidence FIG. 10. An E vs. TOF histogram of ACE-SWICS triple-coincidence counts accumulated in a single E/q step during the year 2004. As He2+ gains or loses energy, it will move in E-TOF space along the modeled track, shown in black. Energy straggling of He2+ can be seen by counts found at lower energies and longer times of flight than the main peak.

In addition to energy straggling, ions that traverse carbon foils may experience a degree of angular scattering that causes deviations in their trajectories.51,21 These ions may therefore travel along slightly longer flight paths before reaching the detector, creating a broadening of the measured TOF distribution. The effects of energy straggling and angular scattering combine with other effects such as uncertainty in the timing electronics or the energy spread in the solid state detector to decrease the mass resolution of the instrument.32, 66 If the angular scattering is sufficient that an ion is deflected into a surface within the instrument, it can cause secondary electrons to be emitted that may increase the level of background. 1. Signature of energy straggling

Accidental coincidence events, also called “false” coincidences, occur when two different particles coincidentally trigger the start and stop signals for a single TOF measurement within a specified timing window. These accidental coincidences are more prominent when the incident particle flux is high, as shown in Appendix B, but high flux is not a requirement. While increased-flux events sometimes contain penetrating radiation (Sec. III A), the particles can also pass through the ESA as designed, thereby limiting the background signatures to specific E/q steps. 1. Signatures of accidental coincidence

Shown in Fig. 11 is a one-day accumulation of ACESWICS double-coincidence data from 11 August 2009. The color scale indicates the counts that fall in each E/q-TOF bin, and calculated E/q vs. TOF tracks for several ions are shown with solid black lines. In this 2D histogram, accidental coincidence events are evident as horizontal tracks that cover a range of TOF values within the expected E/q steps for a given ion, and that overlap the calculated curved tracks of all

The effects of energy straggling can be seen when the data are histogrammed by energy and TOF; two parameters that are directly affected by deceleration. In this parameter space, ion species are found along curved tracks, and can reliably be found in consistent locations along these tracks based on their initial energy. Shown in Fig. 10 is a one-year accumulation of ACE-SWICS triple-coincidence data in a single E/q step (7.5 keV/e) from 2004. The number of counts in each ETOF bin is indicated by color, with a modeled track for He2+ traced with a solid black line. In this 2D histogram, the effects of energy straggling are evident as some of the He2+ ions have decelerated to longer times of flight and lower energies along the modeled track. 2. Mitigation strategies for energy straggling

The use of carbon foils for secondary electron generation in straight-through TOF systems leads to an expected and unavoidable background signal due to energy straggling. The effect can, however, be modeled, quantified, and reduced when post-processing the data. Further, straggling can be reduced in the instrument with increased Post-Acceleration High Voltage (PAHV) ahead of the foil. The energy straggling issue can be avoided altogether, however, by using an energy-isochronous design (e.g., Refs. 48, 65, and 30) in which ion trajectories undergo half of a harmonic oscillation in the linear electric field of the TOF system. For ions that exit the carbon foil with a positive charge and experience a trajectory oscillation, the times of flight are independent of the ion energy, and energy

FIG. 11. An E/q vs. TOF histogram of ACE-SWICS double-coincidence counts during one day in 2009. The color scale indicates the number of counts that fall in each E/q-TOF bin, and the solid black lines are calculated traces of specific ion tracks in E/q vs. TOF space. Accidental coincidences of H+ and He2+ are indicated by horizontal streaks at consistent E/q values, with longer times of flight than the bulk of the species. The lower panel shows, in faded color, which counts are eliminated when an 85% solar wind speed threshold is applied.


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heavier M/q values. Ions that possess solar wind energies will be found in a diagonal region extending from the lower left to the upper right of the figure. Pickup ions and energetic particles are found above this region. The horizontal ion tracks of H+ and He2+ due to accidental coincidences are indicated with arrows. This accidental coincidence effect is possible for any ion, and is also seen in triple-coincidence data. Also apparent in Fig. 11 is a discontinuity in the accidental proton track near TOF = 83 ns, corresponding to M/q = 3.27 amu/e. This discontinuity is unrelated to the dead time of the coincidence measurements, as the rate of incident ions is much lower. It is a built-in feature of the instrument, reflecting a change in the onboard priority scheme for data telemetry that separates the channels dominated by protons and alpha particles from those containing the heavy ions, and ensures that the few measured heavy solar wind ions have a higher probability of being telemetered from the spacecraft. The different transmission probabilities are accounted for during data analysis.

2. Probabilities of accidental coincidence

Accidental coincidence events follow an exponential decay in the probability of an event occurring versus the TOF. Appendix B contains a detailed derivation of accidental coincidence probabilities for single-start/single-stop TOF measurements, accounting for detector efficiencies and contrasting the probability distributions of real and accidental coincidence measurements as a function of the incident flux rate. Accidental coincidences affect data not only by adding spurious counts in TOF bins, but also by preventing real counts from being recorded. Such an absence of counts does not create visible background and is outside the scope of this paper, but statistical treatments that include formulae for restoring real counts that are lost due to accidental coincidences, correcting for dead time in the timing electronics, or treating single-start/multiple-stop and multiple-start/multiplestop systems can be found in Refs. 15, 61, and 8.

3. Mitigation strategies for accidental coincidence

Several design considerations can be employed to reduce the incident flux, and therefore the occurrence of accidental coincidences during routine measurements. For example, if measurements of solar wind heavy elements (e.g., M > 4 amu) are desired, the E/q stepping of the instrument can be adjusted to avoid the high density proton peak36 and therefore preclude accidental coincidences of a rare heavy ion with a frequently incident proton. Similarly, the geometric factor, which characterizes an instrument’s sensitivity and gathering power,92 could be made adjustable (e.g., Ref. 84), which would allow a reduction in the number of ions reaching the TOF section during times of high incident flux. In addition to the use of anti-coincidence detectors, as described in Sec. III A 2, the likelihood of accidental coincidence events drowning out the signal in the data is greatly

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decreased when the requirement of triple coincidence is put in place. For measurement regimes in which the bulk speed of the incident plasma is known, a simple minimum speed threshold set at some fraction of the bulk speed will eliminate the much slower accidental-coincidence counts from the data. Fig. 11 demonstrates this technique, with the counts eliminated by a minimum speed threshold of 85% of the solar wind speed displayed with faded color.

G. Electronics

Noise events in the data can also be caused by issues with the flight electronics. It is not possible to list all of the sources of noise events in the electronics, as many are instrumentspecific. An example from SWICS will serve here as an illustration of how noise events from electronics can affect an accurate interpretation of the data when not properly characterized.

1. Signatures of electronics noise

Noise from onboard electronics can show up as periodic or recurrent signals. These are highly instrument specific and can include such processes as data rate saturation, data spillover into neighboring channels, or shifting data into improper measurement bins. These can have a significant effect on data analysis, particularly when species with low fluxes are studied. An example can be seen in histograms of SWICS E/q vs. TOF data, where periodic vertical streaks are visible. Fourier analysis of these noise events indicates a peak in TOF channels numbered 2n (n = 1:9) and at linear combinations of 2n . The largest disturbances occur at channels 28 , 29 , and (28 + 29 ), corresponding to TOF values of 50, 100, and 150 ns, respectively, with peaks at 26 and lower hardly discernible. Double-coincidence data from days 210 to 240 in 2009 are shown in Fig. 12, where an ion-to-solar wind speed filter of Vion > 0.85 Vsw was used to remove accidental coincidence measurements from the data. In the E/q vs. TOF histogram, an artificial peak at 100 ns can be seen at all E/q steps, accompanied by a trough a few channels wide immediately to its left. This peak is a feature of the analog-to-digital conversion, which releases counts into a 2n channel that were accumulated in the channels immediately below it. The calculated trace of O+ pickup ions crosses this peak between E/q = 6575 keV/e. When the O+ data are ordered by their E/q step, there is an apparent increase in high-energy ions, when in fact the peak is an artifact of the analog-to-digital conversion. The elimination of electronics noise in-flight is difficult and instrument- or even circuit-specific. One possible strategy to mitigate the condition discussed here is to artificially map some of the 2n peaks to the channels just below based on a scheme obtained from a calibration run under carefully controlled conditions. In general, any such issues are best addressed in the design, testing, and calibration of instruments in a controlled laboratory setting. When these signatures are found in flight data, care must be taken to process them properly during analysis.


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dent ions independently, as opposed to E/q in electrostatic sensors, or M/q in magnetostatic or TOF sensors only. Combining such measurements in coincidence has enabled sensors such as SWICS to provide extremely sensitive data sets of low-flux solar wind heavy ions. Using a small form factor design without triplecoincidence capabilities, such as for FIPS, can lead to additional sources of background, some of which are only revealed post-launch. Mass constraints, for example, may necessitate the use of materials with higher outgassing rates than otherwise. Without sufficient venting the increased pressure will cause counts to trigger on MCPs. It is not feasible, nor is it necessary, to eliminate all background sources in the design and flight stages of the instrument. Background removal techniques are necessary during post-processing of flight data. For example, Ref. 29 applies background removal methods to data from the FIPS sensor on MESSENGER, demonstrating that background removal from the data can reveal valuable science measured with a compact, double-coincidence instrument. Although FIPS is used as a case study, the framework and processing techniques discussed are completely generalizable and can be applied to any TOF instrument to assist with background forward modeling, and in some cases, removal. ACKNOWLEDGMENTS

FIG. 12. An example from 30 days of ACE-SWICS ion composition data from 2009 that illustrates how electronic noise events will skew data for lowcount studies. The strong peak at TOF = 100 ns crosses the O+ calculation (solid black line) near E/q = 65 keV/e. When the O+ measurements are ordered according to their E/q, a large electronic noise peak between E/q = 65-75 keV/e is revealed.

The authors would like to acknowledge J. M. Raines, J. Thomas, and P. Shearer of the University of Michigan for assistance with the processing of raw SWICS and FIPS data and for helpful discussions, the paper reviewers for their insightful comments, and C. C. Nowak for creating the issue cover artwork. This work was supported in part by National Aeronautics and Space Administration (NASA) Grant Nos. DTM3250-04, NNX08AI11G, NNX13AH66G, NNX11AD84G, and the NASA GSRP Grant No. NNX09AL50H.

IV. CONCLUSIONS

APPENDIX A: ION OPTICS MODEL OF ESD ON FIPS

The key mechanisms behind a number of background sources in TOF spectrometers have been identified, as well as their corresponding signatures in instrument measurements. The variety, subtlety, and complexity of these processes illustrate that the design of an effective spaceborne TOF sensor is far from trivial. Not only must the instrument accurately analyze incident ions, but it must be designed to withstand a harsh and unpredictable space environment that is a unique and often overpowering source of measurement contamination. Most of the sources of background events discussed in this paper can be expected in any TOF spectrometer, and many of them apply to other types of particle detecting instruments as well, such as electron detectors or bulk plasma sensors. Careful design principles such as UV suppression and the avoidance of direct paths for MCP-to-MCP ion feedback can reduce the background level seen in the data. However, one of the greatest background suppression techniques is the use of triple-coincidence detection of ions. This technique was invented to measure mass, charge, and energy of inci-

Understanding the trajectories of ions that create background events in the FIPS data enables the prediction of background rates and, consequently, estimates of instrument signal-to-noise. These signal-to-noise estimates, along with a probabilistic background removal algorithm, are discussed in detail in Ref. 29. Here, an accurate time-of-flight spectrum of ESD-based background is generated using the proposed harp emission mechanism for event creation. A three-dimensional ion optics model of the FIPS TOF chamber was created in SIMION17 and used to simulate the trajectories of ions desorbed by electrons emitted from the wire harps. Flight voltage potentials were used in the model, and the effective potentials of the field control harps in front of the start and stop MCP assemblies were modeled according to work by Read et al.82 on field penetration through wire grids. Ions were initialized at rest uniformly over the front surface of the start MCP and quickly accelerated to ∼5 keV/e due to internal voltages. When the ions struck the top of the TOF housing, a secondary electron was emitted. The instrumentmeasured TOF corresponds to the time for an ion to travel


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FIG. 13. Comparison of FIPS flight data (top row) and SIMION simulations of desorbed hydrocarbons from the start MCP (bottom row) for VA of (left) −10.5 kV and (right) −8.5 kV. The simulated TOF values of ions that travel from the start MCP to the top of the TOF chamber match closely with peaks from the flight data. The shaded region in the flight data contains peaks from ions that follow trajectories that collide with the side wall of the TOF chamber instead of the top, resulting in a set of peaks created by the same hydrocarbon groups, but at TOF values that are a constant fraction (56%) of the higher-TOF peaks.

from the front of the start MCP to the top of the TOF housing, and the time for the subsequent ion-induced secondary electron to be measured by the stop MCP assembly. The mass spectra from the lab measurements of Fig. 4 were used to determine the relative ratios of desorbed ion masses, with the exception of H+ , whose abundance was scaled down by a factor of 30 in order to enable better comparison with the peak shapes of other simulated masses. The true relative desorbed mass spectra are expected to vary with electron energy. Fig. 13 compares the simulations of desorbed ions that are repelled from the MCP surface (bottom row) with FIPS in-flight measurements of background made at two different PAHVs (top row). Note that not only are the simulated times of flight in good agreement with those of the in-flight data in terms of the TOF value, peak shape, and relative counts, but the spectra shifts as expected for different values of the PAHV. The constant offset error in TOF value is likely due in part to errors in the field penetration model surrounding the mirror harp and other wire grids. The overall lower flight times of the simulation may also be due to an underestimation of the flight path that the desorbed ions take from the MCP surface to the location within the curved TOF chamber where they eventually strike; a TOF error that scales in proportion to the square root of the ion mass. The shaded region indicates ESD background events caused by electron emission onto a local area near the edge of the MCP. Such electrons desorbs ions that, instead of traveling to the roof of the chamber, strike side walls inside the TOF chamber creating secondary electrons that trigger stop signals as discussed previously. These events were not simulated due to the difficulties in accurately modeling fringing field effects. APPENDIX B: QUANTIFICATION OF ACCIDENTAL COINCIDENCE PROBABILITIES 1. Probability distributions

Accidental coincidence events have a higher probability of occurring during times of high incident particle flux. The probability of recording an accidental coincidence signal in

a timing window decreases exponentially with time, and is highly dependent on the incident particle rate. The following discussion is based on a derivation outlined in Ref. 9. Assume that an incident ion penetrates the carbon foil and the resulting secondary electrons are guided toward the start MCP assembly. The detection efficiency of the start MCP assembly leads to a probability p1 that the electrons will trigger a start signal. After a time τ , the ion will trigger a signal on the stop MCP assembly with some probability p2 , either by direct impact in the case of a double-coincidence design, or by secondary electron emission from the target SSD in the case of a triple-coincidence design. These probabilities, when combined with the probabilities that a particle will experience successful transmission through the foil and any grids or harps, make up the absolute detection efficiency of the sensor, and can be monitored over the duration of a mission to analyze the changes in performance and gain of MCP detectors.22 If many ions of the same species pass through the system, a Gaussian distribution of flight times, f(τ ), is expected due to energy straggling in the carbon foil, deviations in ion trajectory, the energy passband of the ESA, differences in secondary electron flight time, and variations due to electronics. Techniques for resolving different ions with overlapping distributions are beyond the scope of this discussion, but can be found in the literature.98, 99 Certain instrument-dependent timing limitations are assumed to be in place for this derivation. For example, on SWICS a start signal opens a timing window, the first stop signal in the timing window is used to determine the TOF value, and the timing window closes at time Tmax . Other timing configurations, including setups that involve single-start/multiple-stop or multiple-start/multiple-stop are discussed by Bodi et al.8 For a single-start/single-stop setup, the probabilities must be found for whether this stop signal is a real signal or an accidental coincidence. For any τ , the probability of a real stop signal being detected within the interval [τ , τ + dτ ] is f(τ )dτ , as shown in the left panel of Fig. 14. The total probability of detecting a real stop signal is found by integrating f(τ ) to measure the area under the probability curve. For the purpose of this derivation, f(τ ) will be


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FIG. 14. (Left) The probability distribution of flight times, given by f(τ ), is normalized to p2 . For τ = τ i , the probability that the real stop signal will be found in the shaded area is f(τ i )dτ . (Center) The probability density of real stop signals can be partially integrated to find F(τ 0 ), the total probability of a signal being measured within time τ 0 . (Right) The cumulative probability illustrates that at some time τ , the probability of not having the stop signal is 1 − F(τ ).

normalized to p2 , the total probability that a stop signal will be measured ∞ f (τ )dτ = p2 .

(B1)

where n is the number of successful accidental coincident events. From Eq. (B3), the probability that there will be no successful accidental coincident signals within [0, τ ] can be found, i.e., the probability for n = 0 Pp

−∞

If the stop detector assembly was perfectly efficient, then every incident particle would result in a measurement, i.e., p2 = 100%. In practice, however, the detector efficiency reduces this value. Also, the limits of integration can be restricted to the timing window range [0, Tmax ]. While signals may trigger on the detectors outside of the timing window, they will not be recorded as a time-of-flight event. The cumulative probability F(τ 0 ) of detecting a real stop signal within some time interval [0, τ 0 ] is F (τ0 ) =

f (τ )dτ,

(B2)

and the probability of not having a real stop signal in that interval is 1 − F(τ ), as shown in Fig. 14. For any τ , the accidental coincidence stop signals that occur randomly within the time interval [0, τ ] are independent of one another, with only a small probability that an event will occur at any given τ , and can therefore be described by Poisson statistics. With an incident ion rate of J0 , the total number of events that occur within that interval is J0 τ , and the mean number of accidental signals is p2 J0 τ . The Poisson distribution for these accidental events is J τ (n) 2 0

=

fr (τ )dτ = e−p2 J0 τ (f (τ )dτ ).

(p2 J0 τ )n e−p2 J0 τ , n!

(B3)

FIG. 15. Illustration of the probability of finding the real stop signal within the interval [τ , τ + dτ ], with no accidental signals occurring beforehand.

(B4)

(B5)

Similarly, the Poisson distribution can be written for the small time interval [τ , τ + dτ ], which has a measurement duration of dτ (p2 J0 dτ )n e−p2 J0 dτ . (B6) n! From this, the probability can be found that there will be exactly one successful accidental coincident signal within the interval [τ , τ + dτ ] J dτ (n) 2 0

0

= e−p2 J0 τ .

With this, the probability distribution of the real stop signal being measured within the interval [τ , τ + dτ ], with no accidental coincidence signal occurring in the time leading up to that interval (Fig. 15), is

Pp

τ0

Pp

J τ (0)

2 0

Pp

J dτ (1)

2 0

=

= (p2 J0 dτ )e−p2 J0 dτ ≈ p2 J0 dτ.

(B7)

The probability distribution of the accidental stop signal being measured within the interval [τ , τ + dτ ], with no other accidental coincidence or real signal being detected before time τ , is fa (τ )dτ = e−p2 J0 τ (1 − F (τ ))(p2 J0 dτ ).

(B8)

This is illustrated in Fig. 16. If an approximation is made of an infinitely small TOF resolution, the distribution f(τ ) can be replaced by a delta

FIG. 16. Illustration of the probability of finding the accidental stop signal within the interval [τ , τ + dτ ], with no accidental or real signals occurring beforehand.


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function p2 δ(τ − τ 0 ). The cumulative probability of detecting a real stop signal from Eq. (B2) now becomes τ0 0 if τ < τ0 F (τ ) = p2 δ(τ − τ0 )dτ = . (B9) p2 if τ = τ0 0

If the timing electronics are set so that only the first detected stop signal will trigger the time-of-flight measurement, and that a real signal will trigger the detector with a probability of p2 at time τ 0 , then the cumulative probability at time τ 0 will be F(τ 0 ). The probability that no real signal will be detected at time τ 0 is 1 − F(τ 0 ), or equivalently, 1 − p2 . Since f(τ ) is normalized to p2 , the total probability cannot go higher than p2 and the cumulative probability F(τ ) by definition will not decrease. Therefore, F(τ ) = p2 for all τ ≥ τ 0 . The infinite TOF resolution will simplify Eqs. (B5) and (B8) for the real and accidental probability distributions to fr (τ ) = p2 δ(τ − τ0 )e−p2 J0 τ and fa (τ ) = e

−p2 J0 τ

F (τ ) = 0 if (1 − F (τ ))(p2 J0 ), F (τ ) = p2 if

(B10)

τ < τ0

. τ ≥ τ0 (B11) Equation (B11) gives the probability density that the accidental coincidence signal will occur anytime within the timing window [0, TMAX ], and the real signal will not be detected at the expected time τ 0 due to the imperfect detection efficiency of the stop detector. For a high incident count rate J0 , the probability of an accidental coincidence occurring decreases exponentially with τ . When J0 is low, as is usually the case in space-based TOF instruments due to the geometric factor and the limits of the detector electronics, the exponential term in Eqs. (B10) and (B11) can be approximated as 1, and the probability of accidental coincidences becomes nearly constant. The real and accidental coincidence probability distributions, Eq. (B5) and Eq. (B11), are plotted for the case of low incident ion flux and high incident ion flux in Fig. 17. The real event occurs with probability p2 at a mean value of τ 0 = 90 ns, with a standard deviation of σ = 2 ns. During times of low flux (J0 = 104 ions s−1 ), the background level due to accidental coincidence is nearly constant, as is typically seen in instrument data. When the flux through the instrument is extremely high (J0 = 60 × 106 ions s−1 ) the exponential term in the accidental coincidence probability distribution has a stronger effect. There is a drop in the accidental probability density after time τ 0 . Since this derivation uses the assumption that a timing measurement is completed with the first detected signal, an accidental coincidence signal after time τ 0 is only possible if the real signal fails to trigger at time τ 0 , i.e., the probability that no real signal is detected, 1 − p2 , will hold for all τ ≥ τ 0 , while prior to τ 0 the probability of no real signal is 100%. A stop detector with perfect efficiency would eliminate the possibility that an accidental coincidence could occur after the real signal triggered at time τ 0 , and the accidental probability density would drop to zero after τ = τ 0 . The step down in the accidental probability distribution is therefore a result of the imperfect efficiency of the stop detector.

FIG. 17. Modeled time-of-flight distribution of accidental coincidences for a low incident flux shows a near-constant accidental background level, while during high incident flux the accidental coincidence probability takes an exponential form.

2. Total probabilities

To find the total probabilities, the probability density Eqs. (B10) and (B11) must be integrated over the duration of the measurement timing window [0, TMAX ]. In addition to pr , the total probability for getting a real signal at time τ 0 , and pa , the total probability for getting an accidental stop signal at time τ 0 , the total probability p0 for not detecting any signal at all within the interval can be found pr = p2 e−p2 J0 τ0 ,

(B12)

pa = 1 − p2 e−p2 J0 τ0 − (1 − p2 )e−p2 J0 TMAX , p0 = 1 − pr − pa = (1 − p2 )e

−p2 J0 TMAX

.

(B13) (B14)

1 F.

Allegrini, R. F. Wimmer-Schweingruber, P. Wurz, and P. Bochsler, Nucl. Instrum. Methods B 211, 487–494 (2003). 2 F. Allegrini, D. J. McComas, D. T. Young, J.-J. Berthelier, J. Covinhes, J.-M. Illiano, J.-F. Riou, H. O. Funsten, and R. W. Harper, Rev. Sci. Instrum. 77, 044501 (2006). 3 F. Allegrini, R. W. Ebert, S. A. Fuselier, G. Nicolaou, P. Bedworth, S. Sinton, and K. J. Trattner, Opt. Eng. 53, 024101 (2014). 4 G. B. Andrews, T. H. Zurbuchen, B. H. Mauk, H. Malcom, L. A. Fisk, G. Gloeckler, G. C. Ho, J. S. Kelley, P. L. Koehn, T. W. LeFevere, S. S. Livi, R. A. Lundgren, and J. M. Raines, Space Sci. Rev. 131, 523–556 (2007).


091301-18 5 H.

Gilbert et al.

Balsiger, K. Altwegg, P. Bochsler, P. Eberhardt, J. Fischer, S. Graf, A. Jäckel, E. Kopp, U. Langer, M. Mildner, J. Müller, T. Riesen, M. Rubin, S. Scherer, P. Wurz, S. Wüthrich, E. Arijs, S. Delanoye, J. De Keyser, E. Neefs, D. Nevejans, H. Rème, C. Aoustin, C. Mazelle, J.-L. Médale, J. A. Sauvaud, J.-J. Berthelier, J.-L. Bertaux, L. Duvet, J.-M. Illiano, S. A. Fuselier, A. G. Ghielmetti, T. Magoncelli, E. G. Shelley, A. Korth, K. Heerlein, H. Lauche, S. Livi, A. Loose, U. Mall, B. Wilken, F. Gliem, B. Fiethe, T. I. Gombosi, B. Block, G. R. Carignan, L. A. Fisk, J. H. Waite, D. T. Young, and H. Wollnik, Space Sci. Rev. 128, 745–801 (2007). 6 S. J. Bame, D. J. McComas, B. L. Barraclough, J. L. Phillips, K. J. Sofaly, J. C. Chavez, B. E. Goldstein, and R. K. Sakurai, Astron. Astrophys. Suppl. Ser. 92, 237–265 (1992), see http://adsabs.harvard.edu/ abs/1992A%26AS...92..237B. 7 P. Sigmund, Top. Appl. Phys. 47, 9–71 (1981). 8 A. Bodi, B. Sztáray, T. Baer, M. Johnson, and T. Gerber, Rev. Sci. Instrum. 78, 084102 (2007). 9 R. Bodmer, Ph.D. dissertation, University of Bern, 1996. 10 A. R. Burns, E. B. Stechel, D. R. Jennison, and T. M. Orlando, Phys. Rev. B 45, 1373–1385 (1992). 11 H. S. Bridge, J. W. Belcher, R. J. Butler, A. J. Lazarus, A. M. Mavretic, J. D. Sullivan, G. L. Siscoe, and V. M. Vasyliunas, Space Sci. Rev. 21, 259–287 (1977). 12 F. Busch, W. Pfeffer, B. Kohlmeyer, D. Schüll, and F. Pühlhoffer, Nucl. Instrum. Methods 171, 71–74 (1980). 13 C. W. Carlson, D. W. Curtis, G. Paschmann, and W. Michael, Adv. Space Res. 2, 67–70 (1983). 14 C. W. Carlson and J. P. McFadden, Geophys. Monogr. Ser. 102, 125–140 (1998). 15 P. B. Coates, Rev. Sci. Instrum. 63, 2084–2088 (1992). 16 H. H. Collin, J. M. Quinn, G. R. Smith, E. Hertzberg, S. Roselle, and S. J. Battel, J. Spacecraft Rockets 29, 617–620 (1992). 17 D. A. Dahl, Int. J. Mass Spectrom. 200, 3–25 (2000). 18 R. W. Ebert, F. Allegrini, S. A. Fuselier, G. Nicolaou, P. Bedworth, S. Sinton, and K. J. Trattner, Rev. Sci. Instrum. 85, 033302 (2014). 19 C. Y. Fan, G. Gloeckler, and E. Tums, Proc. Int. Cosmic Ray Conf. 4, 1602–1607 (1971), available online at http://inis.iaea.org/search/ search.aspx?orig_q=RN:4051560. 20 R. H. Fowler and L. Nordheim, Proc. R. Soc. London, Ser. A 119, 173–181 (1928). 21 H. O. Funsten, D. J. McComas, and B. L. Barraclough, Opt. Eng. 32, 3090–3095 (1993). 22 H. O. Funsten, R. W. Harper, and D. J. McComas, Rev. Sci. Instrum. 76, 053301 (2005). 23 H. O. Funsten, F. Allegrini, P. Bochsler, G. Dunn, S. Ellis, D. Everett, M. J. Fagan, S. A. Fuselier, M. Granoff, M. Gruntman, A. A. Guthrie, J. Hanley, R. W. Harper, D. Heirtzler, P. Janzen, K. H. Kihara, B. King, H. Kucharek, M. P. Manzo, M. Maple, K. Mashburn, D. J. McComas, E. Möbius, J. Nolin, D. Piazza, S. Pope, D. B. Reisenfeld, B. Rodriguez, E. C. Roelof, L. Saul, S. Turco, P. Valek, S. Weidner, P. Wurz, and S. Zaffke, Space Sci. Rev. 146, 75–103 (2009). 24 S. A. Fuselier, P. Bochsler, D. Chornay, G. Clark, G. B. Crew, G. Dunn, S. Ellis, T. Friedmann, H. O. Funsten, A. G. Ghielmetti, J. Googins, M. S. Granoff, J. W. Hamilton, J. Hanley, D. Heirtzler, E. Hertzberg, D. Isaac, B. King, U. Knauss, H. Kucharek, F. Kudirka, S. Livi, J. Lobell, S. Longworth, K. Mashburn, D. J. McComas, E. Möbius, A. S. Moore, T. E. Moore, R. J. Nemanich, J. Nolin, M. O’Neal, D. Piazza, L. Peterson, S. E. Pope, P. Rosmarynowski, L. A. Saul, J. R. Scherrer, J. A. Scheer, C. Schlemm, N. A. Schwadron, C. Tillier, S. Turco, J. Tyler, M. Vosbury, M. Wieser, P. Wurz, and S. Zaffke, Space Sci. Rev. 146, 117–147 (2009). 25 A. B. Galvin, L. M. Kistler, M. A. Popecki, C. J. Farrugia, K. D. C. Simunac, L. Ellis, E. Möbius, M. A. Lee, M. Boehm, J. Carroll, A. Crawshaw, M. Conti, P. Demaine, S. Ellis, J. A. Gaidos, J. Googins, M. Granoff, A. Gustafson, D. Heirtzler, B. King, U. Knauss, J. Levasseur, S. Longworth, K. Singer, S. Turco, P. Vachon, M. Vosbury, M. Widholm, L. M. Blush, R. Karrer, P. Bochsler, H. Daoudi, A. Etter, J. Fischer, J. Jost, A. Opitz, M. Sigrist, P. Wurz, B. Klecker, M. Ertl, E. Seidenschwang, R. F. Wimmer-Schweingruber, M. Koeten, B. Thompson, and D. Steinfeld, Space Sci. Rev. 136, 437–486 (2008). 26 J. Geiss, G. Gloeckler, U. Mall, R. von Steiger, A. B. Galvin, and K. W. Ogilvie, Astron. Astrophys. 282, 924–933 (1994), see http://adsabs.harvard.edu/abs/1994A%26A...282..924G. 27 J. Geiss, G. Gloeckler, L. A. Fisk, and R. von Steiger, J. Geophys. Res. 100, 23373–23377, doi:10.1029/95JA03051 (1995).

Rev. Sci. Instrum. 85, 091301 (2014) 28 D.

J. Gershman and T. H. Zurbuchen, Rev. Sci. Instrum. 81, 045111 (2010). 29 D. J. Gershman, J. A. Gilbert, J. M. Raines, G. Gloeckler, P. Tracy, and T. H. Zurbuchen, Report No. 1 (Department of Atmospheric, Oceanic, and Space Sciences, University of Michigan, 2013), pp. 1–31, see http://hdl.handle.net/2027.42/100358. 30 J. A. Gilbert, R. A. Lundgren, M. H. Panning, S. Rogacki, and T. H. Zurbuchen, Rev. Sci. Instrum. 81, 053302 (2010). 31 J. A. Gilbert, S. T. Lepri, E. Landi, and T. H. Zurbuchen, Astrophys. J. 751, 20 (2012). 32 G. Gloeckler, University of Maryland Technical Report No. TR77-043 (University of Maryland, College Park, MD, 1977). 33 G. Gloeckler and K. C. Hsieh, Nucl. Instrum. Methods 165, 537–544 (1979). 34 G. Gloeckler, F. M. Ipavich, W. Stüdemann, B. Wilken, D. C. Hamilton, G. Kremser, D. Hovestadt, F. Gliem, R. A. Lundgren, W. Rieck, E. O. Tums, J. C. Cain, L. S. Masung, W. Weiss, and P. Winterhof, IEEE Trans. Geosci. Remote Sens. GE-23, 234–240 (1985). 35 G. Gloeckler, Rev. Sci. Instrum. 61, 3613–3620 (1990). 36 G. Gloeckler, J. Geiss, H. Balsiger, P. Bedini, J. C. Cain, J. Fischer, L. A. Fisk, A. B. Galvin, F. Gliem, D. C. Hamilton, J. V. Hollweg, F. M. Ipavich, R. Joos, S. Livi, R. A. Lundgren, U. Mall, J. F. McKenzie, K. W. Ogilvie, F. Ottens, W. Rieck, E. O. Tums, R. von Steiger, W. Weiss, and B. Wilken, Astron. Astrophys. Suppl. Ser. 92, 267–289 (1992), see http://adsabs.harvard.edu/abs/1992A%26AS...92..267G. 37 G. Gloeckler, J. Geiss, H. Balsiger, L. A. Fisk, A. B. Galvin, F. M. Ipavich, K. W. Ogilvie, R. von Steiger, and B. Wilken, Science 261, 70–73 (1993). 38 G. Gloeckler, H. Balsiger, A. Bürgi, P. Bochsler, L. A. Fisk, A. B. Galvin, J. Geiss, F. Gliem, D. C. Hamilton, T. E. Holzer, D. Hovestadt, F. M. Ipavich, E. Kirsch, R. A. Lundgren, K. W. Ogilvie, R. B. Sheldon, and B. Wilken, Space Sci. Rev. 71, 79–124 (1995). 39 G. Gloeckler and J. Geiss, Nature (London) 381, 210–212 (1996). 40 G. Gloeckler and J. Geiss, Space Sci. Rev. 86, 127–159 (1998). 41 G. Gloeckler, J. Cain, F. M. Ipavich, E. O. Tums, P. Bedini, L. A. Fisk, T. H. Zurbuchen, P. Bochsler, J. Fischer, R. F. Wimmer-Schweingruber, J. Geiss, and R. Kallenbach, Space Sci. Rev. 86, 497–539 (1998). 42 G. Gloeckler, L. A. Fisk, J. Geiss, N. A. Schwadron, and T. H. Zurbuchen, J. Geophys. Res. 105, 7459–7463, doi:10.1029/1999JA000224 (2000). 43 J. T. Gosling, J. R. Asbridge, S. J. Bame, and W. C. Feldman, Rev. Sci. Instrum. 49, 1260–1268 (1978). 44 J. T. Gosling, M. F. Thomsen, and R. C. Anderson, “A cookbook for determining essential transmission characteristics of spherical section electrostatic analyzers,” Report No. LA-10147-M (Los Alamos National Laboratory, 1984). 45 M. Gruntman, Appl. Opt. 34, 5732–5737 (1995). 46 M. Gruntman, Rev. Sci. Instrum. 68, 3617–3656 (1997). 47 J. G. Hagopian, S. A. Getty, M. Quijada, J. Tveekrem, R. Shiri, P. Roman, J. Butler, G. Georgiev, J. Livas, C. Hunt, A. Maldonado, S. Talapatra, X. Zhang, S. J. Papadakis, A. H. Monica, and D. Deglau, Proc. SPIE 7761, 77610F (2010). 48 D. C. Hamilton, G. Gloeckler, F. M. Ipavich, R. A. Lundgren, R. B. Sheldon, and D. Hovestadt, Rev. Sci. Instrum. 61, 3104–3106 (1990). 49 D. Hasselkamp, K. G. Lang, A. Scharmann, and N. Stiller, Nucl. Instrum. Methods 180, 349–356 (1981). 50 M. Hilchenbach, Int. J. Mass Spectrom. 215, 113–129 (2002). 51 G. Högberg, H. Nordén, and H. G. Berry, Nucl. Instrum. Methods 90, 283–288 (1970). 52 D. Hovestadt, M. Hilchenbach, A. Bürgi, B. Klecker, P. Laeverenz, M. Scholer, H. Grünwaldt, W. I. Axford, S. Livi, E. Marsch, B. Wilken, H. P. Winterhoff, F. M. Ipavich, P. Bedini, M. A. Coplan, A. B. Galvin, G. Gloeckler, P. Bochsler, H. Balsiger, J. Fischer, J. Geiss, R. Kallenbach, P. Wurz, K.-U. Reiche, F. Gliem, D. L. Judge, H. S. Ogawa, K. C. Hsieh, E. Möbius, M. A. Lee, G. G. Managadze, M. I. Verigin, and M. Neugebauer, Sol. Phys. 162, 441–481 (1995). 53 K. C. Hsieh, E. Keppler, and G. Schmidtke, J. Appl. Phys. 51, 2242–2246 (1980). 54 F. M. Ipavich, R. A. Lundgren, B. A. Lambird, and G. Gloeckler, Nucl. Instrum. Methods 154, 291–294 (1978). 55 F. M. Ipavich, L. S. Ma Sung, and G. Gloeckler, University of Maryland Technical Report No. 82-172 (University of Maryland, College Park, MD, 1982). 56 R. Kallenbach, J. Geiss, G. Gloeckler, and R. von Steiger, Astrophys. Space Sci. 274, 97–114 (2000).


091301-19 57 A.

Gilbert et al.

F. Kaplan, J. A. Gilbert, R. Trabert, T. H. Zurbuchen, and L. J. Guo, ACS Photon. 1(7), 554–559 (2014). 58 S. K. Kulov, S. A. Kesaev, I. R. Bugulova, Ju. L. Pergamentsev, V. Ju. Boyadjidy, N. V. Berishvili, K. Ju. Ahpolov, and S. G. Manukov, Proc. SPIE 5834, 203–206 (2005). 59 C. D. Lane, N. G. Petrik, T. M. Orlando, and G. A. Kimmel, J. Chem. Phys. 127, 224706 (2007). 60 J. Lean, Rev. Geophys. 29, 505–535, doi:10.1029/91RG01895 (1991). 61 T. Luhmann, Rev. Sci. Instrum. 68, 2347–2356 (1997). 62 J. E. Mack, F. Paresce, and S. Bowyer, Appl. Opt. 15, 861–862 (1976). 63 T. E. Madey and J. T. Yates, Jr., J. Vac. Sci. Technol. 8, 525–555 (1971). 64 T. E. Madey, Surf. Sci. 299–300, 824–836 (1994). 65 D. J. McComas and J. E. Nordholt, Rev. Sci. Instrum. 61, 3095–3097 (1990). 66 D. J. McComas, F. Allegrini, C. J. Pollock, H. O. Funsten, S. Ritzau, and G. Gloeckler, Rev. Sci. Instrum. 75, 4863–4870 (2004). 67 D. J. McComas, F. Allegrini, J. Baldonado, B. Blake, P. C. Brandt, J. Burch, J. Clemmons, W. Crain, D. Delapp, R. DeMajistre, D. Everett, H. Fahr, L. Friesen, H. O. Funsten, J. Goldstein, M. Gruntman, R. Harbaugh, R. Harper, H. Henkel, C. Holmlund, G. Lay, D. Mabry, D. Mitchell, U. Nass, C. Pollock, S. Pope, M. Reno, S. Ritzau, E. Roelof, E. Scime, M. Sivjee, R. Skoug, T. S. Sotirelis, M. Thomsen, C. Urdiales, P. Valek, K. Viherkanto, S. Weidner, T. Ylikorpi, M. Young, and J. Zoennchen, Space Sci. Rev. 142, 157–231 (2009). 68 J. P. McFadden, D. S. Evans, W. T. Kasprzak, L. H. Brace, D. J. Chornay, A. J. Coates, B. K. Dichter, W. R. Hoegy, E. Holeman, K. Kadinsky-Cade, J. C. Kasper, D. Kataria, L. Kistler, D. Larson, A. J. Lazarus, F. Mozer, T. Mukai, K. W. Ogilvie, G. Paschmann, F. Rich, Y. Saito, J. D. Scudder, J. T. Steinberg, M. Wüest, and P. Wurz, ISSI Sci. Rep. Ser. 7, 277–385 (2007), available online at http://adsabs.harvard.edu/abs/2007ISSIR...7..277M. 69 J. L. McLain, A. L. Sprague, G. A. Grieves, D. Schriver, P. Trainicek, and T. M. Orlando, J. Geophys. Res. 116, E03007, doi:10.1029/2010JE003714 (2011). 70 D. Menzel and R. Gomer, J. Chem. Phys. 41, 3311–3328 (1964). 71 D. G. Mitchell, S. E. Jaskulek, C. E. Schlemm, E. P. Keath, R. E. Thompson, B. E. Tossman, J. D. Boldt, J. R. Hayes, G. B. Andrews, N. Paschalidis, D. C. Hamilton, R. A. Lundgren, E. O. Tums, P. Wilson IV, H. D. Voss, D. Prentice, K. C. Hsieh, C. C. Curtis, and F. R. Powell, Space Sci. Rev. 91, 67–112 (2000). 72 E. Möbius, L. M. Kistler, M. A. Popecki, K. N. Crocker, M. Granoff, S. Turco, A. Anderson, P. Demain, J. Distelbrink, I. Dors, P. Dunphy, S. Ellis, J. Gaidos, J. Googins, R. Hayes, G. Humphrey, H. Kästle, J. Lavasseur, E. J. Lund, R. Miller, E. Sartori, M. Shappirio, S. Taylor, P. Vachon, M. Vosbury, V. Ye, D. Hovestadt, B. Klecker, H. Arbinger, E. Künneth, E. Pfeffermann, E. Seidenschwang, F. Gliem, K.-U. Reiche, K. Stöckner, W. Wiewesiek, A. Harasim, J. Schimpfle, S. Battell, J. Cravens, and G. Murphy, Space Sci. Rev. 86, 449–495 (1998). 73 T. E. Moore, D. J. Chornay, M. R. Collier, F. A. Herrero, J. Johnson, M. A. Johnson, J. W. Keller, J. F. Laudadio, J. F. Lobell, K. W. Ogilvie, P. Rozmarynowski, S. A. Fuselier, A. G. Ghielmetti, E. Hertzberg, D. C. Hamilton, R. Lundgren, P. Wilson, P. Walpole, T. M. Stephen, B. L. Peko, B. van Zyl, P. Wurz, J. M. Quinn, and G. R. Wilson, Space Sci. Rev. 91, 155–195 (2000). 74 P. Mukherjee, M.-G. Kang, T. H. Zurbuchen, L. J. Guo, and F. A. Herrero, J. Vac. Sci. Technol. B 25, 2645–2648 (2007). 75 H. B. Niemann, J. R. Booth, J. E. Cooley, R. E. Hartle, W. T. Kasprzak, N. W. Spencer, S. H. Way, D. M. Hunten, and G. R. Carignan, IEEE Trans. Geosci. Remote Sens. GE-18, 60–65 (1980). 76 K. W. Ogilvie, N. McIlwraith, and T. D. Wilkerson, Rev. Sci. Instrum. 39, 441–451 (1968). 77 J. Pan, J. Lü, Z. Zhang, J. Sun, and D. Su, Chin. J. Electron. 19, 757–762 (2010), available online at http://www.ejournal.org.cn/ Jweb_cje/EN/volumn/volumn_1172.shtml. 78 F. Paresce, Appl. Opt. 14, 2823–2824 (1975). 79 M. J. Persky, Rev. Sci. Instrum. 70, 2193–2217 (1999). 80 C. J. Pollock, K. Asamura, J. Baldonado, M. M. Balkey, P. Barker, J. L. Burch, E. J. Korpela, J. Cravens, G. Dirks, M.-C. Fok, H. O. Funsten, M. Grande, M. Gruntman, J. Hanley, J.-M. Jahn, M. Jenkins, M. Lampton, M. Marckwordt, D. J. McComas, T. Mukai, G. Penegor, S. Pope, S. Ritzau, M. L. Schattenburg, E. Scime, R. Skoug, W. Spurgeon, T. Stecklein, S. Storms, C. Urdiales, P. Valek, J. T. M. van Beek, S. E. Weidner, M. Wüest, M. K. Young, and C. Zinsmeyer, Space Sci. Rev. 91, 113–154 (2000). 81 R. D. Ramsier and J. T. Yates, Jr., Surf. Sci. Rep. 12, 243–378 (1991).

Rev. Sci. Instrum. 85, 091301 (2014) 82 F.

H. Read, L. A. Baranova, N. J. Bowring, J. Lambourne, and T. C. Whitwell, Rev. Sci. Instrum. 69, 84–90 (1998). 83 S. M. Ritzau and R. A. Baragiola, Phys. Rev. B 58, 2529–2538 (1998). 84 U. Rohner, L. Saul, P. Wurz, F. Allegrini, J. Scheer, and D. J. McComas, Meas. Sci. Technol. 23, 025901 (2012). 85 B. Schläppi, K. Altwegg, H. Balsiger, M. Hässig, A. Jäckel, P. Wurz, B. Fiethe, M. Rubin, S. A. Fuselier, J. J. Berthelier, J. De Keyser, H. Rème, and U. Mall, J. Geophys. Res. 115, A12313, doi:10.1029/2010JA015734 (2010). 86 W. F. W. Schneider, B. Kohlmeyer, and R. Bock, Nucl. Instrum. Methods 87, 253–259 (1970). 87 E. E. Scime, E. H. Anderson, D. J. McComas, and M. L. Schattenburg, Appl. Opt. 34, 648–654 (1995). 88 O. H. W. Siegmund, R. F. Malina, K. Coburn, and D. Werthimer, IEEE Trans. Nucl. Sci. 31, 776–779 (1984). 89 O. H. W. Siegmund, J. Vallerga, A. Tremsin, and J. McPhate, Proc. SPIE 6686, 66860W (2007). 90 C. W. Smith, N. F. Ness, L. F. Burlaga, R. M. Skoug, D. J. McComas, T. H. Zurbuchen, G. Gloeckler, D. K. Haggerty, R. E. Gold, M. I. Desai, G. M. Mason, J. E. Mazur, J. R. Dwyer, M. A. Popecki, E. Möbius, C. M. S. Cohen, and R. A. Leske, Sol. Phys. 204, 229–254 (2001). 91 S. C. Solomon, R. L. McNutt, Jr., R. E. Gold, and D. L. Domingue, Space Sci. Rev. 131, 3–39 (2007). 92 J. D. Sullivan, Nucl. Instrum. Methods 95, 5–11 (1971). 93 A. M. Then and C. G. Pantano, J. Non-Cryst. Solids 120, 178–187 (1990). 94 G. C. Theodoridis and F. R. Paolini, Rev. Sci. Instrum. 39, 326–330 (1968). 95 J. G. Timothy, ISSI Sci. Rep. Ser. 9, 391–421 (2013). 96 A. L. Vampola, J. V. Osborn, and B. M. Johnson, J. Spacecraft Rockets 29, 592–595 (1992). 97 A. L. Vampola, Geophys. Monogr. Ser. 102, 339–355 (1998). 98 R. von Steiger, N. A. Schwadron, L. A. Fisk, J. Geiss, G. Gloeckler, S. Hefti, B. Wilken, R. F. Wimmer-Schweingruber, and T. H. Zurbuchen, J. Geophys. Res. 105, 27217–27238, doi:10.1029/1999JA000358 (2000). 99 R. von Steiger and T. H. Zurbuchen, J. Geophys. Res. 116, A01105, doi:10.1029/2010JA015835 (2011). 100 J. H. Waite, Jr., W. S. Lewis, W. T. Kasprzak, V. G. Anicich, B. P. Block, T. E. Cravens, G. G. Fletcher, W.-H. Ip, J. G. Luhmann, R. L. McNutt, H. B. Niemann, J. K. Parejko, J. E. Richards, R. L. Thorpe, E. M. Walter, and R. V. Yelle, Space Sci. Rev. 114, 113–231 (2004). 101 Y. X. Wang, F. Ohuchi, and P. H. Holloway, J. Vac. Sci. Technol. A 2, 732–737 (1984). 102 W. G. White, Electron. Eng. 21, 75–79 (1949). 103 K. Wilhelm, W. Curdt, E. Marsch, U. Schühle, P. Lemaire, A. Gabriel, J.-C. Vial, M. Grewing, M. C. E. Huber, S. D. Jordan, A. I. Poland, R. J. Thomas, M. Kühne, J. G. Timothy, D. M. Hassler, and O. H. W. Siegmund, Sol. Phys. 162, 189–231 (1995). 104 B. Wilken and W. Stüdemann, Nucl. Instrum. Methods 222, 587–600 (1984). 105 J. L. Wiza, Nucl. Instrum. Methods 162, 587–601 (1979). 106 M. Wüest, Geophys. Monogr. Ser. 102, 141–155 (1998). 107 M. Wüest, D. S. Evans, J. P. McFadden, W. T. Kasprzak, L. H. Brace, B. K. Dichter, W. R. Hoegy, A. J. Lazarus, A. Masson, and O. Vaisberg, ISSI Sci. Rep. Ser. 7, 11–116 (2007), available online at http://adsabs.harvard.edu/abs/2007ISSIR...7...11W. 108 D. T. Young, S. J. Bame, M. F. Thomsen, R. H. Martin, J. L. Burch, J. A. Marshall, and B. Reinhard, Rev. Sci. Instrum. 59, 743–751 (1988). 109 D. T. Young, Geophys. Monogr. Ser. 102, 1–16 (1998). 110 D. T. Young, Geophys. Monogr. Ser. 130, 353–365 (2002). 111 D. T. Young, J. J. Berthelier, M. Blanc, J. L. Burch, A. J. Coates, R. Goldstein, M. Grande, T. W. Hill, R. E. Johnson, V. Kelha, D. J. McComas, E. C. Sittler, K. R. Svenes, K. Szegö, P. Tanskanen, K. Ahola, D. Anderson, S. Bakshi, R. A. Baragiola, B. L. Barraclough, R. K. Black, S. Bolton, T. Booker, R. Bowman, P. Casey, F. J. Crary, D. Delapp, G. Dirks, N. Eaker, H. O. Funsten, J. D. Furman, J. T. Gosling, H. Hannula, C. Holmlund, H. Huomo, J. M. Illiano, P. Jensen, M. A. Johnson, D. R. Linder, T. Luntama, S. Maurice, K. P. McCabe, K. Mursula, B. T. Narheim, J. E. Nordholt, A. Preece, J. Rudzki, A. Ruitberg, K. Smith, S. Szalai, M. F. Thomsen, K. Viherkanto, J. Vilppola, T. Vollmer, T. E. Wahl, M. Wüest, T. Ylikorpi, and C. Zinsmeyer, Space Sci. Rev. 114, 1–112 (2004). 112 J. F. Ziegler, M. D. Ziegler, and J. P. Biersack, Nucl. Instrum. Methods B 268, 1818–1823 (2010). 113 T. H. Zurbuchen, P. Bochsler, and F. Scholze, Opt. Eng. 34, 1303–1315 (1995).


Hybrid tandem mass spectrometers in biological research.

Miniature and Fieldable Mass Spectrometers: Recent Advances.

Invited Review Article: Pump-probe microscopy.

Ion sources for ion implantation technology (invited).

Building mass spectrometers and a philosophy of research.

An electrospray ion source for magnetic sector mass spectrometers.

Invited article: Richard D. Turk Memorial Lecture--parasites' progress.

Invited review article: The Chandra X-ray Observatory.

Invited review article: Advanced light microscopy for biological space research.

Invited commentary: Body mass index and mortality.

Surface-induced dissociation in tandem quadrupole mass spectrometers: A comparison of three designs.

Invited article: in situ comparison of passive radon-thoron discriminative monitors at subsurface workplaces in Hungary.

Efficient injection of low-mass ions into high magnetic field Fourier transform ion cyclotron resonance mass spectrometers.

Characterisation of deuterium spectra from laser driven multi-species sources by employing differentially filtered image plate detectors in Thomson spectrometers.

Untargeted, spectral library-free analysis of data-independent acquisition proteomics data generated using Orbitrap mass spectrometers.

Invited Review Article: Error and uncertainty in Raman thermal conductivity measurements.

Kinetic modeling of particle dynamics in H(-) negative ion sources (invited).

Pediatric Anterior Mediastinal Mass: A Review Article.

Invited Article: Autonomous assembly of atomically perfect nanostructures using a scanning tunneling microscope.

Invited Frontiers Commentary. Tier Climbing Article: Redefining Neuromarketing as an Integrated Science of Influence.

Invited article: Expanded and improved traceability of vibration measurements by laser interferometry.

Accurate label-free protein quantitation with high- and low-resolution mass spectrometers.

depth profiling mass spectrometers.

A pulsed-leak valve for use with ion trapping mass spectrometers.