Arnaud
Delcorte
*,
Vincent
Delmez
,
Christine
Dupont-Gillain
,
Clément
Lauzin
,
Hannah
Jefford
,
Mykhailo
Chundak
,
Claude
Poleunis
and
Konstantin
Moshkunov
Université Catholique de Louvain, Institute of Condensed Matter and Nanoscience, 1 Place Louis Pasteur, 1348 Louvain-la-Neuve, Belgium. E-mail: arnaud.delcorte@uclouvain.be
First published on 16th June 2020
Ionised cluster beams have been produced and employed for thin film deposition and surface processing for half a century. In the last two decades, kiloelectronvolt cluster ions have also proved to be outstanding for surface characterisation by secondary ion mass spectrometry (SIMS), because their sputter and ion yields are enhanced in a non-linear fashion with respect to monoatomic projectiles, with a resulting step change of sensitivity for analysis and imaging. In particular, large gas cluster ion beams, or GCIB, have now become a reference in organic surface and thin film analysis using SIMS and X-ray photoelectron spectroscopy (XPS). The reason is that they induce soft molecular desorption and offer the opportunity to conduct damageless depth-profiling and 3D molecular imaging of the most sensitive organic electronics and biological samples, with a nanoscale depth resolution. In line with these recent developments, the present review focuses on rather weakly-bound, light-element cluster ions, such as noble or other gas clusters, and water or alcohol nanodroplets (excluding clusters made of metals, inorganic salts or ionic liquids) and their interaction with surfaces (essentially, but not exclusively, organic). The scope of this article encompasses three aspects. The first one is the fundamentals of large cluster impacts with surfaces, using the wealth of information provided by molecular dynamics simulations and experimental observations. The second focus is on recent applications of large cluster ion beams in surface characterisation, including mass spectrometric analysis and 2D localisation of large molecules, molecular depth-profiling and 3D molecular imaging. Finally, the perspective explores cutting edge developments, involving (i) new types of clusters with a chemistry designed to enhance performance for mass spectrometry imaging, (ii) the use of cluster fragment ion backscattering to locally retrieve physical surface properties and (iii) the fabrication of new biosurface and thin film architectures, where large cluster ion beams are used as tools to transfer biomolecules in vacuo from a target reservoir to any collector substrate.
In a typical secondary ion mass spectrometry (SIMS) experiment, the primary ion beam, single atoms or clusters, is raster scanned over the surface to analyse, and the sputtered secondary ions are collected and separated in a mass spectrometer (quadrupole analyser, magnetic sector or time-of-flight – ToF analyser). ToF analysers generally require a pulsed primary ion beam while the other analysers function with a continuous (DC) primary ion beam.7 The ion images are then reconstructed by associating the measured secondary ion distributions to the x and y deflections of the incident beam. In this common configuration, the quality of the images depends on the primary beam focus, which defines the ultimate lateral resolution, but also on the efficiency of the sputtering process to turn surface molecules into detectable diagnostic ions. With the continued improvement of the primary ion beam focus, the attainable pixel size decreases, and so does the number of emitted ions per pixel. Therefore, developers constantly strive to enhance the ionisation efficiency, so that increasingly smaller areas and ultimately nanoscale objects can be analysed.8–10
The scope of this review encompasses rather weakly-bound, light-element cluster ions, such as noble or other gas clusters, water or glycerol nanodroplets, excluding clusters made of metals, inorganic salts or ionic liquids. Large cluster ions (n > 500) have been embraced by the surface analysis community (essentially SIMS and X-ray photoelectron spectroscopy – XPS) in the last decade. Light-element cluster ions are naturally formed in the gas phase in the solar system and in the planetary atmospheres. In Titan's atmosphere, ions with m/z ratio up to 10000 were detected by mass spectrometry,11 with a tentative assignment of part of the observed ion signal.12 Ionic clusters were also found in the E-ring of Saturn with m/z ion signals corresponding to large solvation of sodium cations by water.13 Water and other clusters are also naturally present in the Earth's atmosphere.14,15 In the laboratory, large light-element cluster ions can be produced either by supersonic, adiabatic expansion of a gas (gas cluster ion beams – GCIB) or by electrospraying a liquid solution. The first method leads to clusters with a maximum size of thousands of atoms while the second produces nano and microdroplets containing thousands to millions of atoms. For both methods, the pioneering experiments date back to the very beginning of the 1990's.2,16 By electrospraying a solution with 70% water and 30% glycerol, Mahoney et al. formed a beam of multicharged ions with a calculated average cluster mass of 8 × 106 Da (massive cluster impact or MCI).16,17 The mass spectrum resulting from the bombardment of a solid thin layer of a peptide of molecular weight (MW) 2395 by such a beam is shown in Fig. 1a (top), together with the spectrum of the same sample acquired using an atomic ion beam (bottom). Though absolute intensities were not compared in this seminal article, the relatively larger abundance of quasi-molecular ions (i.e. molecules ±1 proton), and the comparatively smaller abundance of fragments (i.e. products of dissociation of the molecules), in the mass spectrum obtained with large clusters are striking. Using this technique with an electrosprayed solution of 2 M ammonium acetate in 100% glycerol, Fenselau et al. reported the detection of multiply charged molecular ions of bovine carbonic anhydrase (MW: 29
021) and horse heart myoglobin (MW: 16
952).18 A similar approach using 1 M acetic acid water solution to form the beam was coined electrospray droplet impact (EDI) mass spectrometry.19,20 The beam diameter on the sample was estimated to be ∼3 mm. Parent ions of biomolecules such as gramicidin S (MW: 1141), insulin (MW: 5808), cytochrome C (MW: 12
327) and lysozyme (MW: 14
300) could be detected by this method.
![]() | ||
Fig. 1 Mass spectrometry with large clusters. (a) Negative-ion spectrum of a peptide sample (MW: 2395) obtained using (top) a massive-cluster ion beam and (bottom) a xenon primary atom beam (∼5 keV). Reproduced from ref. 16 with permission from John Wiley & Sons, copyright 1991. (b) Positive ion mass spectrum of a spin-coated insulin (MW: 5808) thin film measured with (top) 10 keV Ar3000+ and (bottom) 30 keV Bi3+. |
Noble gas cluster ion beams were initially developed by Yamada and co-workers for surface modification, involving shallow implantation, surface etching, ultra-shallow junction formation and doping, surface smoothing or cluster-assisted thin film deposition.21–23 GCIB were coupled later to mass spectrometers for solid sample analysis. The mass spectrum resulting from the bombardment of a film of insulin by 10 keV Ar3000+ clusters is shown in Fig. 1b (top). Similar results were obtained by other authors.24 Again, comparison with SIMS spectra obtained with monoatomic or small cluster ion projectiles, such as 30 keV Bi3+ in Fig. 1b (bottom), demonstrates that the relative fraction of molecular versus fragment ions is maximised using large cluster ions. The initial distribution of Ar cluster ions produced in an adiabatic expansion is rather broad and strongly dependent on the backing pressure and the base pressure in the expansion chamber, as illustrated by Yamada.22 It extends from a few hundreds to a few thousands of atoms for a backing pressure of 20 to 40 bars. A rough mass selection can be operated by a Wien filter, possibly followed by a finer time-of-flight selection, when a pulsed beam is desired for sample analysis with a well-defined cluster size (Fig. 1b and Kayser et al.25).
For small-scale analysis and imaging, cluster ions produced by adiabatic expansion in the vacuum are superior to electrosprayed liquids because their beams can be much better focused (currently ∼μm in DC mode26). However, alternative approaches not relying on the beam focus, but on the microscope capabilities of the spectrometer may be competitive in certain cases, as will be discussed further. On the other hand, the nano and microdroplets formed by electrospray are large enough to withstand atmospheric pressure, leading to powerful complementary and lower-cost ambient analytical methods (desorption electrospray ionisation – DESI,27 desorption ionisation by charge exchange – DICE28).
Early on, the experimental development was accompanied by a theoretical effort to understand the physics of large clusters impinging on solid materials, both organic and inorganic. In addition to analytical models involving spikes, shock waves and hydrodynamic flow,29–33 computer simulations and, in particular, classical molecular dynamics (MD) helped unravel the mechanisms of energetic cluster impacts and induced desorption.34–36Fig. 2 provides illustrative examples of such MD simulations, in which the impacts of large kiloelectronvolt argon clusters form nanocraters in various surfaces and cause the emission of large amounts of molecular material and even nanoparticles. In the upcoming section, we show how these simulations shed light on the complex processes induced by large cluster impacts, and provide us with a very detailed microscopic view of the resulting emission processes. The following sections review cutting edge applications in organic and bio sample characterisation with GCIB, followed by new developments in materials analysis and molecular transfer to create novel (bio)surfaces.
![]() | ||
Fig. 2 Microscopic view of large cluster impacts. (a) 90 keV Ar9000 on silver covered by a polystyrene tetramer monolayer (10 eV per atom). Reproduced from ref. 37 with permission from The American Chemical Society, copyright 2008. (b) 15 keV Ar250 on a fullerite crystal (60 eV per atom). (c) 5 keV Ar2000 on crystalline polyethylene decorated with Au nanoparticles (2.5 eV per atom). Reproduced from ref. 40 with permission from The American Chemical Society, copyright 2013. (d) 10 keV Ar5000 on a polystyrene molecule adsorbed on amorphous polyethylene (2 eV per atom). |
In classical MD simulations such as those illustrated in Fig. 2, Newton's equations of motion are numerically integrated over a given time interval, providing the researcher with the positions and velocities of all the particles at each timestep. The forces among the atoms or particles in the system are derived from empirical interaction potentials, either mimicking more accurate first principle calculations and/or fit to the properties of the described materials. Therefore, MD simulations, unlike computer codes based on the binary collision approximation (BCA),41 calculate the interactions between all the atoms of the system, so that many body effects can be reasonably described. They consume much more computer time than BCA codes, but are obviously required for the investigation of cluster impacts and polyatomic species emission. Systems with 105–107 atoms are routinely modelled for times spanning between 10 and 103 ps. In order to correctly treat high energy collisions, a purely repulsive, spherical, diatomic potential (Molière, ZBL) is appended to the more sophisticated potentials describing the atom behaviours at low energy. Also, a thermal bath governed by Langevin dynamics42 is often implemented around the impact region to compensate for the finite size of the simulation cells. That region absorbs the excess energy and pressure waves that would otherwise be reflected towards the centre of the cell, causing spurious effects. Classical MD simulations have developed in parallel with the field of ion–surface collisions, starting with the seminal works of Harrison and co-workers.43,44 With the concomitant development of new interaction potentials and force fields, they have been applied to a multitude of material and projectile types including, recently, very large clusters and complex molecular materials.45
![]() | ||
Fig. 3 Molecular dynamics of Ar cluster impacts. (a) Crater volume (the inset shows that the craters can be modelled by ellipsoids), reproduced from ref. 50 with permission from The American Vacuum Society, copyright 2018. (b) Sputtered mass for 0° (blue) and 45° (red) incidence; the dashed gray line indicates the experimental sputtered mass for Irganox 1010 targets (the inset shows the fraction of molecules sputtered intact), reproduced from ref. 53 with permission from The American Chemical Society, copyright 2015. (c) Absolute pressure wave velocity (black symbols) and pressure wave velocity divided by the projectile speed (red triangles), reproduced from ref. 59 with permission from The American Chemical Society, copyright 2019. (d) Number of new intra- (Ni) and intermolecular (Nc) bonds. Reproduced from ref. 39 with permission from The American Chemical Society, copyright 2013. All the quantities are represented as a function of the energy per atom in the projectile (x-axis). The y-values are also scaled by the number of atoms, except for the pressure wave velocities in (c). |
Experimentally, the sputter yields (Y) generated by Ar clusters, scaled with the number of atoms in the cluster Y/n, were found to follow so-called universal curves as a function of the scaled energy E/n for all tested materials, that is, the different projectile energies and sizes assemble on a single line for a given material and impact angle.51,52 This behaviour is also observed in the MD simulations, as shown in Fig. 3b for polyethylene surfaces, with a linear evolution of the scaled sputtered mass at high E/n and a transition to a non-linear region below 10–50 eV, depending on the incidence angle (0° and 45° from normal in Fig. 3b).53 Similar curves are also predicted for methane53 and other large (hydro)carbon clusters54 bombarding polymers, and for various targets,55,56 so that they appear to be a general feature in the dynamics of light-element cluster interactions with organic surfaces. The concept of universality of the sputtering curves was discussed and criticised by Paruch et al.57 The dependence on the incidence angle was explained by two concomitant effects: (i) the angular dependence of the maximum energy deposited in the topmost surface layers53 and (ii) the increased blocking of the emission induced by large clusters when the incidence becomes close to normal.58 The experimental sputtering curves indicate that the position of the transition from the non-linear to the linear sputtering region is material dependent, with higher E/n values of the transition for harder and more cohesive inorganic materials than for polymers and other organic molecules. In the example of Fig. 3a–c, the transition to the non-linear region is accompanied by a change in the sputtered material flux, with about 50% of fragments at high E/n and almost no fragments below 5–10 eV per atom, where the energy becomes too small to break covalent bonds (inset of Fig. 3b). Important implications of this effect for molecular analysis and organic material depth profiling will be discussed in Section 3.
The MD simulation data provide some more insights into the mechanisms at play. Plotting the sputtered mass divided by the projectile energy as a function of velocity or E/n, the aforementioned linear region essentially becomes a plateau, while the non-linear region shows a pronounced variation from almost zero to the plateau value.53 Such a plot indicates how efficiently the projectile energy is used for sputtering when varying the cluster impact conditions. For a large range of E/n, corresponding to the linear evolution in Fig. 3b, the sputtering per atom and per energy unit remains constant, while it decreases gradually in the non-linear region (small E/n). At very high E/n, the efficiency also starts to decrease, when the projectile implants deep in the solid and its energy is used to create subsurface damage. The lateral and vertical velocities of the pressure waves developing in an amorphous icosane solid upon impact were estimated from the MD data (Fig. 3c).59 The pressure wave velocities first increase with E/n, from ∼2 to ∼5 km s−1 around 10 eV per atom, then decrease after a broad maximum. Hence, the pressure wave velocities also show a clear transition region around 10–50 eV per atom, indicating two different physical situations of cluster impact.
The measured speed of sound in n-hexadecane is ∼1.3 km s−1 and for polyethylene, ∼2 km s−1, so that the pressure wave velocities measured for slow projectile impacts are close to the speed of sound in the solid. With increasing projectile velocity, they become highly supersonic. The maximum of the pressure wave velocities corresponds roughly to the region of saturation of the sputtered mass per unit of energy of the projectile. It is also the region where fragmentation starts to increase. For low velocity impacts, the material is able to accompany the motion induced by the projectile penetration. Note that a proportionality between the crater edge motion and the projectile velocity was also observed for Ar cluster impacts in silicon below 40 eV per atom.48 In Fig. 3c, beyond the wave velocity maximum, one enters the region of fast cluster impacts, where the projectile and wave velocities decouple, meaning that the wave velocity decreases while the projectile speed upon impact continues to increase.
Sputtering simulations of coarse-grained polyethylene samples with various size chains allowed us to describe a generic behaviour of cratering, fragmentation and emission induced by Ar clusters in organic sample. Detailed chemistry and specific reaction pathways, however, require atomistic simulations and more computer intensive potentials (AIREBO,60 ReaxFF61), with a higher constraint on simulation cell size, time and/or statistics. ReaxFF has been used recently to explain some differences in the sputtering of hydrocarbon and oxygen-containing polymers by 20 keV C60 projectiles.62 In particular, the simulations show that longer chain segments are emitted from the hydrocarbons while the oxygen-containing molecules fragment in smaller pieces. With the aim to explain the chemistry induced in polymers like polystyrene and polycarbonate, notoriously difficult to depth profile with fullerene projectiles, a series of investigations compared the bombardment of fullerite and polystyrene by C60 and a range of Ar clusters.39,63,64 For these simulations, the AIREBO potential was selected, because it associates reactivity of H and C atoms (covalent bond breaking and creation) with a long-range part describing non-bonding interactions (intermolecular cohesion). AIREBO was recognised as the potential of choice for sputtering of hydrocarbons. Indeed, it provides similar results as ReaxFF and computes two times faster.65 A detailed discussion about the reactivity of the different hydrocarbon potentials is also provided by Zarshenas et al.66 in the case of acetylene molecules and radicals. The numbers of new intermolecular (Nc) and intramolecular (Ni) bonds generated by the normal impact of Ar clusters in a fullerite sample are shown in Fig. 3d. The general trend is reminiscent of the sputtering curves of Fig. 3b, with an asymptotical tendency towards a linear behaviour at high energy for each Ar cluster size. An example of crosslinked fullerite network, obtained under 2.5 keV Ar18 bombardment, is shown as an inset. Crosslinking, leading to a chemically degraded and more resistant organic surface, was recognised as the main obstacle to molecular depth profiling with SF5+ and C60+ keV projectiles.67 In addition to the trend of new bond creation identified for Ar clusters, the simulations indicate that C60 create much more crosslinking than similar size Ar clusters (Fig. 3d), because the fragmentation of the buckminsterfullerene molecule provides up to sixty highly reactive C radicals which take active part in the induced reactions.
![]() | ||
Fig. 4 Energy of the desorbed molecular ions. (a) FWHM of the axial kinetic energy distributions of (M − H)− sputtered from Irganox 1010 by 30 keV Mn+, Bi+, Bi5+, and by a series of Arn+ cluster projectiles, as a function of the scaled energy E/n. Inset: Image of the molecular dynamics showing the change of emission angle with varying Ar cluster energy per atom, in red and blue; green and yellow indicate the backscattered Ar atoms for the 278 and 1 eV per atom cases, respectively. Reproduced from ref. 59 with permission from The American Chemical Society, copyright 2019. (b) Mean internal energy of the secondary ions as a function of E/n for 20 keV Ar cluster impacts. Inset: internal energy distributions for different cluster sizes. Reproduced from ref. 68 with permission from The American Society for Mass Spectrometry, copyright 2019. |
The mass spectra of organic surfaces obtained upon Ar cluster bombardment with varying E/n support these considerations. Fig. 5a shows the case of P-pPDA benzoxazine μm thick films upon various conditions of Ar cluster ion bombardment. Biosourced benzoxazine molecular coatings form a thermoset polymer upon curing at high temperature, considered for the replacement of chromium-containing coatings for the protection of environmentally exposed aircraft parts.72 In Fig. 5a, the relative intensity of the quasi-molecular ion of benzoxazine, (M − H)+, increases with decreasing E/n, up to a maximum value reached around 2–3 eV, while the non-covalent dimer ion intensity continues to increase strongly below 3 eV, a good indication of the mildness of the desorption process. In parallel, the intensities of fragment ions such as C7H7+ go down to almost nought at 2 eV per atom. The overlapping of the data obtained with clusters having 10 and 20 keV of acceleration energy confirms that E/n is the relevant parameter governing fragmentation, not the total cluster energy.
The effects of repeated Ar cluster bombardment on Ag substrates have been studied using MD simulations by Rzeznik et al.73 They show that, starting from a flat Ag(111) surface, continuous bombardment with 20 and 40 keV Ar872 at normal incidence leads to root-mean-square (RMS) roughness of <1 nm and >2 nm, respectively. Changing the incidence to 70° off normal results in reduced roughness. Our atomic force microscopy (AFM) measurements on flat benzoxazine molecular coatings bombarded by 10 keV Ar3000+ cluster projectiles at 45° incidence also indicate an increase of RMS roughness up to ∼4 nm after 3 × 1013 ions per cm2 (Fig. 5b). Larger induced roughness is expected for organic than for silver surfaces, since the craters created by single cluster impacts in organic materials are significantly deeper and wider. For polymers, topography creation by the Ar cluster beam could be measured ex situ within the time of the experiment only for samples in the glassy state at room temperature (polystyrene and (poly)benzoxazine). Polymers which are above their glass transition (Tg) at room temperature seem to recover their initial surface state within the time of the experiment.
Many of the reviewed results indicate a predominant dependence of the measured quantities (crater size, sputtered mass, fragmentation and damage, topography development) on the energy per atom E/n of the Ar cluster projectiles. The incidence angle constitutes a secondary source of variation. Interestingly, by using large clusters with a low E/n such as 10 keV Ar5000+, organic sample emission with minimal covalent bond scissions and surface damage could be attained, which paved the way to new applications in organic material and biological sample characterisation, as will be discussed in the following section.
The fundamentals of cluster ion–surface interaction, including sputtering, are summarised in Fig. 6.
![]() | ||
Fig. 6 Schematics of the different regimes of cluster–surface interactions, as a function of the projectile energy per atom. |
![]() | ||
Fig. 7 Molecular depth-profiling with Ar clusters. (a) 5.5 keV Ar700+ single-beam depth profile of a PS film (C7H7+; m/z 91). Reproduced from ref. 88 with permission from John Wiley and Sons, copyright 2009. (b) 2.5 keV Ar1700+ dual-beam depth profile of an evaporated amino-acid multilayer alternating three phenylalanine layers of 7 nm thickness each, sandwiched between four evaporated tyrosine layers of 75 nm thickness each (analysis beam: 30 keV Bi3+). Reproduced from ref. 96 with permission from Springer, copyright 2014. (c) 10 keV Ar1700+ dual-beam depth profile of an OPV heterojunction P3HT:PCBM/PEDOT:PSS/ITO (analysis beam: 30 keV Bi3+). (d) Ibidem with 15 and 20 keV Ar1700+ etching (c and d are reproduced from ref. 100 with permission from The Royal Society of Chemistry, copyright 2013). |
The experiments of Ninomiya were performed with Ar clusters for both sample erosion and ToF-SIMS analysis, using a secondary ion chopper in the spectrometer column to provide the start signal of the time-of-flight measurement. In close collaboration with the University of Manchester, Ionoptika also developed an instrument using a continuous high energy Ar beam for both erosion and analysis (“single beam” experiment), in order to achieve the best possible focus.90,91 A secondary ion beam bunching unit and a harmonic reflectron spectrometer provide the necessary performance for mass analysis.
In other instruments, and typically the ION-TOF machines,92 depth profiling and 3D imaging experiments alternate an erosion beam (Ar clusters) and an analysis beam (Bi clusters), in the so-called “dual beam mode”, which has several consequences: (i) nanoscale lateral resolution is provided by the excellent focus of the pulsed Bi cluster beam; (ii) the mass spectra are rather fragmented given the high energy per atom of Bi clusters; (iii) a large quantity of material, sputtered by the erosion beam, is unavailable for the analysis; (iv) depth resolution results from a combination of both beam effects. It is also possible to use pulsed Ar cluster ions for analysis, but the lateral resolution is much reduced.
The depth resolution in Ar cluster organic depth profiling can be assessed using reference molecular samples such as the evaporated Irganox multilayers developed at the British National Physical Laboratory.93 The best depth resolution obtained in an interlaboratory study was ∼5 nm, with 2.5 keV Ar1700+ clusters.93 Similar values were also attained using OLED materials for 2.5 keV cluster ions, with the resolution generally degrading for higher energy beams.94 In another study, comparable values were demonstrated using evaporated amino acid delta layers.95 As shown in Fig. 7b, the up-slope of the 3rd “delta” (i.e. ultrathin) layer of tyrosine, buried at a depth of ∼280 nm, remains close to 4–5 nm using 2.5 keV Ar1700+, while the profile quality degrades strongly with C60+ projectiles at all tested energies, (3rd delta layer up-slope of ∼16 nm for 20 keV C60+ and no 3rd layer detected with 10 keV C60+).96 In a detailed study of polymer surface modification by plasmas, shallow depth profiles using 10 keV Ar5000+ clusters were obtained from polyethylene treated by an atmospheric Ar–D2O radio-frequency plasma torch (post-discharge region).97,98 They indicate a reduction of deuteration by a factor of 3, over the top 3 nm of the surface, and an almost complete disappearance of oxidation products within the same depth, providing us with a lower limit of depth resolution in Ar cluster depth profiling. Reference multilayers of Irganox and amino acids can be depth profiled with higher energy Ar clusters and even, to some extent, with C60+ projectiles. However, as was explained in the previous section, samples that are more prone to crosslinking under irradiation, such as certain classes of polymers and materials containing fullerene molecules, turn out to be more difficult. Pure fullerite layers couldn’t be satisfactorily depth profiled with >10 keV Ar1000+ clusters.99 The case of organic photovoltaic (OPV) layer assemblies of PCBM:P3HT/PEDOT:PSS, Fig. 7c, clearly shows the superiority of low E/n Ar clusters over 30 keV C60+ and also 500 eV Cs+ for sensitive organic sample depth profiling.100 The depth profiles obtained with an assembly devoid of PCBM also indicated that the fullerene-containing molecule was the most problematic in those experiments. However, if the Ar cluster depth profiling of PCBM:P3HT/PEDOT:PSS heterojunctions is successful at low E/n, a slight increase of the Ar1700+ beam energy, from 10 to 15 keV, suffices to degrade the profile quality, and both the molecular ion of PCBM and the P3HT characteristic signal are quickly lost at 20 keV (Fig. 7d).
Another significant issue concerns the molecular depth profiling of hybrid samples containing organic and inorganic phases, in the form of multilayers or of nanoparticles embedded in a matrix.101 Even though a universal solution is still missing, recent studies indicate that, for complex multilayer devices including inorganic or hybrid layers, using a low energy Cs+ beam is competitive with the use of Arn+ clusters with rather large E/n (40 eV), while for Arn+ clusters with small E/n, the strong preferential erosion of the organic part leads to failure of the depth profile.102
![]() | ||
Fig. 8 2D and 3D imaging with Ar clusters. (a) Mass spectrum and image of cholesterol trimers, (C27H46O)3H+ (m/z 1160.07) obtained from the surface of a rat brain using the delayed extraction mode. Reproduced from ref. 107 with permission from The American Vacuum Society, copyright 2016. (b) Overlay ion images of intact phosphatidylcholine (PC) phospholipid (32![]() ![]() |
For 3D molecular imaging, as for depth profiling, both the “single beam” and the “dual beam” approaches have been used in a number of studies, depending on the available instruments. In Fig. 8c, the 3D molecular image of a single pixel of a portable media player OLED display was reconstructed from a dual beam experiment alternating sequences of continuous bombardment by GCIB and analysis using a pulsed Bi cluster ion source.114 The colours represent single molecular masses in the range of m/z 500–800, characteristic of the different functional layers of the organic display. This case study shows that, like molecular depth profiling, 3D imaging finds an important application field in organic electronics (OPV, OLED, organic memories, etc.), whenever 3D architectures have to be assessed,115 defects identified116 or effects of aging and molecular diffusion understood and mitigated.117
One major issue in analyses involving complex organic blends with a large number of high mass compounds, as is typically the case of cells and tissues in biology, is the precise identification of the compounds. In mass spectrometry, identification relies on accurate mass determination that can then be matched against compound libraries and/or structural investigation using MS/MS. The latter involves fragmentation of the molecular ion after its selection by a first mass spectrometer, giving rise to a daughter ion mass spectrum that is characteristic of the isolated molecule. With a limited mass accuracy and a resolving power M/ΔM not exceeding several thousands, ToF mass spectrometers are unable to provide an unambiguous peak identification in biologically and pharmaceutically relevant samples, as was discussed by Gilmore et al.118 One recently developed strategy consists in coupling a state-of-the-art ToF-SIMS with an Orbitrap analyser, able to deliver mass accuracy in the sub-p.p.m. range with a resolving power in the 105.119 The proposed instrument functions in the dual beam mode, with high lateral, low mass resolution images provided by the ToF spectrometer coupled with the Bi cluster ion analysis sequences, while high mass accuracy and resolution are ensured by the Orbitrap spectrometer, which is fed by the beam of secondary ions produced during the continuous GCIB erosion sequences. Fig. 8d shows the reconstructed 3D image of a single macrophage cell incubated with a drug, amiodarone, where isosurfaces with different colours represent the distribution of three ions selected in the general ToF mass spectrum, a cell membrane marker in grey, a marker of the cell nucleus in magenta and the protonated molecular ion (M + H)+ of amiodarone in green (m/z 646). The ∼300 nm spatial resolution provided by the Bi cluster ion beam in the ToF image is complemented by the separate peak annotation of the Orbitrap spectrometer. Recent commercial ToF-SIMS instruments also propose molecular imaging with additional MS/MS capabilities to facilitate data interpretation.120
Experiments with a range of large clusters were conducted, including other rare gas (Kr133) and molecular clusters (O2, CO2,134 CH4,133 H2O,135etc.) In some cases, their interaction with surfaces has also been modelled using MD simulations (Ne, Kr,136 CO2,137 CH453). However, an accurate description of the induced chemistry, and in particular ionisation effects, remains out of reach of the models. Therefore, experimental investigations are expected to lead the way in this area. The comparison between Ar2500+ and Kr2500+ cluster bombardment of insulin films at the same E/n = 2 eV does not indicate a significant difference of molecular ion yield.133 The same authors show that 5 keV (CH4)1500+ clusters (3.3 eV per molecule), Fig. 9a, produce about half the insulin yield with respect to isoenergetic Ar1500+ clusters. They reasonably explain the difference by the lower sputtering yield of the methane cluster, due to its lower mass and momentum (16 amu for CH4 against 40 for Ar). Our MD simulations comparing argon and methane clusters impinging on kilodalton molecules53 also indicate a smaller yield for CH4 clusters with the same E/n (n being Ar atoms or CH4 molecules), about a factor of 2 above 10 eV and slightly less below that value. However, they point to a combination of effects to explain the lower sputtering yield of methane clusters. Indeed, even in the low energy range, where individual CH4 molecules do not break, the impact transfers significant energy in their ro-vibrational modes, in addition to breaking stronger intermolecular bonds than in argon.
![]() | ||
Fig. 9 Development of alternative cluster beams for SIMS. (a) SIMS spectrum of an insulin film obtained with 5 keV (CH4)1500+ clusters. Reproduced from ref. 133 with permission from Elsevier, copyright 2013. (b) Projectile mass dependence of the internal energy increase at the end of the MD simulation of 5 keV (CH4)n impacts on 1.4 kDa polyethylene oligomers (45° incidence). The total potential energy (PE) gained upon impact, green, is separated from the ro-vibrational kinetic energy (ro-vib KE) of the CH4 molecules, red. For comparison, the total (initial) potential energy of the Arn clusters, is signified by the dashed black line (atomisation energy). Reproduced from ref. 53 with permission from The American Chemical Society, copyright 2015. (c) Relative ion yield of [M + H]+ ions obtained upon 20 keV Arn+ and (H2O)n+ bombardment of an Angiotensin film. Reproduced from ref. 141 with permission from The American Chemical Society, copyright 2015. (d) 20 keV Ar–CH4 binary cluster bombardment of evaporated trehalose films. Signal of molecular ions [M + Na]+ (m/z 365), [M + H]+ (m/z 343) and characteristic fragment ions [M − OH]+ (m/z 325) and [M − X]+ (m/z 203) normalized to the primary ion current vs. CH4 concentration in the gas mix. Reproduced from ref. 145 with permission from John Wiley and Sons, copyright 2014. |
Fig. 9b shows that for the largest clusters at 5 keV, 1.1 keV is spent to break the methane cluster and heat its molecules (blue curve), i.e. about 20% of the initial cluster energy. In this respect, it should be noted that the vibrational energy is probably overestimated in the classical MD model.138 In real methane, the vibrational energy levels are quantized, so that transfer of energy quantities that are smaller than the energy of the first vibrationally excited level (0.16 eV) would be impossible. So the simulations give us estimates rather than accurate values. In contrast, the quantification of the rotational levels should never be limiting (0.001 eV). In addition, the simulations show that the cumulated translational kinetic energy of the methane molecules after impact is also 500 eV larger than that of Ar atoms for the same initial cluster mass and momentum, another factor suggesting that methane clusters transfer their energy less efficiently to the surface molecules.53 They also penetrate less in the organic surface. The effects are thus complex, and we speculate that both the larger size of the methane clusters for a same total mass (smaller momentum per unit area)139,140 and the small atomic mass of hydrogen contribute to explain the differences. As was explained in the article of Moritani et al., the idea behind the use of methane clusters was to provide a source of hydrogen that could form protons upon impact and hence improve molecular ionisation by protonation. However, the results indicate no enhancement, probably because the energy required to form a free proton from a methane molecule is still far from reach in a cluster impact where the energy per molecule is around 3 eV. Experiments conducted with CO2 clusters on phospholipids and sugar films do not indicate significant ion yield enhancements with respect to Ar.134,137 Nevertheless, the use of CO2 clusters improves the lateral resolution of 2D imaging by more than a factor of two. Another technical advantage of CO2versus Ar clusters is related to their higher binding energy which allows to operate the system with a lower backing pressure.
Promising results in terms of molecular ionisation were reported by the group of Manchester using a water cluster beam also produced by adiabatic expansion in a similar column as the argon cluster beam.135,141,142Fig. 9c compares the yields of protonated molecular ion (M + H)+ of angiotensin measured upon 20 keV (H2O)n+ and Arn+ bombardment, for different cluster constituent numbers n and, thereby, different E/n (note that in Fig. 9c, n represents the number of Ar atoms or the number of H2O molecules). Unlike the argon data, the protonated molecular ion yield measured using water clusters shows a sharp maximum around 3 eV per molecule. The enhancement factor between argon and water at that value of E/n is larger than 10. For many biomolecules, the enhancement gained with water GCIB is around one order of magnitude, either in “static” bombardment conditions or for the consumption of all the available material per unit of surface area.135
To qualitatively understand the drastic difference between the effect of water and methane clusters on sample protonation, one must rely on the specific properties of water in the condensed phase. Indeed, the energetics of proton formation from isolated methane and water molecules are similar, while they differ strongly in the liquid phase, making protonation much easier in water because of its polarity, binding and amphoteric properties. The solvation properties of water and its acid–base properties already develop with a small number of water molecules. For instance, the smallest acid droplet was claimed to be formed in a helium droplet containing four water units and one HCl molecule.143 One can then speculate that the spreading of a large (H2O)n cluster on the molecular surface over the few picoseconds of their interaction144 suffices to produce the solvation environment where proton transfer to the analyte can occur. These considerations hold for EDI MS as well, where larger water nanodroplets are used to interrogate the samples.19,20
In addition to unary clusters, made of a single type of atom or molecule, using binary clusters could provide a supplementary degree of freedom to induce or control specific ionisation reactions upon cluster impact. First attempts at sputtering trehalose sugar thin films with 20 keV clusters formed from argon doped with a few percents of methane show interesting enhancements of the protonated molecular ion (M + H)+ and of the fragment (M − OH)+ by a factor of ∼4 (Fig. 9d).145 The data are difficult to rationalise given the previous observations made with pure Ar and pure CH4 clusters.133 In these binary Ar–CH4 cluster measurements, the gas composition in the source is assessed by residual gas analysis, while the total cluster mass distribution is measured by time-of-flight after beam pulsing. However, the average percentage of methane in the formed clusters is not known (much less its distribution) and, since one Ar atom is 2.5 times heavier than one CH4, this introduces a strong uncertainty on the cluster sizes.
One important factor determining cluster formation in adiabatic expansions is the intermolecular binding energy of the constituents (Hagena parameter146). Because of their stronger binding energy, methane clusters are expected to form at the expense of argon clusters in an expansion of the mixed gas. However, the details of binary cluster formation in realistic conditions are not well known. To obtain a better microscopic view of Ar–CH4 binary cluster formation as in Moritani et al.133 and Wucher et al.,145 we performed MD simulations, using the grand-canonical NVE ensemble. It is important to stress that MD studies of cluster formation (unary or binary) often use NVT conditions, which is correct if the nucleation is slow enough compared to thermostat effectiveness or medium heat capacity, for instance, to determine nucleation rates (as critical clusters are few to tens of monomers in size) or if the medium is liquid. However, in the supersonic expansion modelled here, large clusters grow adiabatically, the gas heat capacity is low and the nucleation changes drastically during the run, as temperature rises and density decreases. Therefore, the NVE ensemble constituted a strict requirement.
In a first series of simulations, cluster formation and growth were studied in randomly distributed argon–methane gas blends with three initial compositions (1%, 3% and 10% CH4 in Ar), for a total duration of 50 ns. Fig. 10a presents the averaged ratio of the methane to argon constituent numbers in the clusters as a function of simulation time for the three selected gas compositions. In all cases, the CH4/Ar ratio quickly rises after an initial nucleation stage (<5 ns) and switches to a steady and slower rise for all methane concentrations. The composition of the resulting clusters deviates strongly from the one of the initial mix. It is always highly enriched in methane. For instance, the multiplication factors are 15 and 7 times for the 1% and the 10% methane mix, respectively.
To better understand the cluster nucleation and growth, the graph in Fig. 10b plots the time of the first encounter of a cluster of a given size (first passage time) for a single simulation with 3% of CH4. The scattering of points is not the noise, but the signatures of each individual cluster evolution in the simulation. At the beginning the data points generally follow a monotonous progression, but at 25 ns, points start to drop out. For example, the cluster composed of 46 monomers is encountered before 40 to 45 monomer-sized clusters are (these jumps are marked by the black line). Two striking features become obvious. Firstly, the curve switches at a size of 25 from single monomer addition to the addition of multimers. Secondly, the cluster size progression becomes much faster at the same point as the slope of the curve becomes closer to horizontal. This coincidence indicates that after some threshold size, clusters tend to grow mostly by consumption of smaller clusters instead of monomers.
The mechanism of cluster growth by cluster coalescence, after a first stage of nucleation and growth by monomer addition, is supported by other studies, for both metal147,148 and molecular clusters (water149). In a real supersonic expansion, the gas supersaturation would drop substantially after reaching a maximum, as the beam expands inside the nozzle. In this regime, the existing clusters are even more unlikely to grow by addition of gas monomers, having to merge in order to grow further. Therefore, after the first set of 6 parallel simulations was completed (Fig. 10c, black squares), all the monomers were removed from the system and all the clusters were placed in new empty cells with random orientations. After that, the simulations were restarted, with clusters merging actively, which resulted in the formation of significantly larger clusters (Fig. 10c, red dots). After 20 ns, the resulting clusters had reached a size of ∼200 constituents. Then they were extracted once again and combined into new cells. In the third run (Fig. 10c, blue triangles), cluster sizes of 400 and more were obtained. In those subsequent two series of simulations, the increase of the CH4/Ar ratio is due to the energy released upon aggregation of the clusters, which induces the preferential evaporation of Ar. The mechanism of cluster coalescence is illustrated in Fig. 10d. The two clusters first connect with a liquid-like interface before forming an elongated rotating “bean” that finally relaxes into a more spherical shape.
The predicted increase in methane content with respect to the composition of the initial gas was observed experimentally by Moritani et al.133 From the absence of backscattered Arn+ ions in the obtained mass spectra, they deduced that a mix of 10% methane and 90% argon in the GCIB source results in pure methane cluster ions. The example of the Ar–CH4 clusters demonstrates that beam diagnostic is paramount prior to any fundamental study of ionisation enhancement with binary clusters. This can be done by mass spectrometric analysis of the beam itself.150,151 However, the high resolution mass analysis of the GCIB required for a detailed diagnostic is usually absent from the experimental setups used for SIMS.
Applying a similar methodology as the one described above, we measured the intensity variations of the backscattered Arn+ clusters as a function of temperature for several amorphous polymer surfaces including polyisobutylene, polybutadiene, polystyrene (PS) and polymethyl methacrylate (PMMA).155 The clusters used in this study were 10 keV Ar3000+, that is the same E/n as the work of the Japanese team. For all the investigated polymers, our results show a clear transition of the Ar cluster fragment ratio I(Ar2+)/∑I(Arn+) (n = 2–3) when the temperature is scanned from −120 °C to +125 °C (the exact limits depend on the studied polymer). The case of low-molecular weight homodisperse PS (MW: 4000) is illustrated in Fig. 11a, with a transition temperature of 65 °C. The observed transition generally spans over a few tens of degrees and the temperature of the inflection point of the curves is always slightly lower than the bulk glass transition temperature (Tg) measured for the considered polymer (83 °C for the PS of Fig. 11a). Such a difference between bulk (Tg) and surface transition temperature was already observed by Fu et al. for PS156 and PMMA,157 using a different protocol based on a principal component analysis of the secondary ion intensities.
![]() | ||
Fig. 11 Nanophysics with backscattered Ar cluster ions. Temperature dependence of the backscattered Ar cluster fragment ratio I(Ar2+)/∑I(Arn+) (n = 2–3) (a) for homodisperse PS oligomers (MW: 4000) (reproduced from ref. 155 with permission from The American Society for Mass Spectrometry, copyright 2018) and (b) for uncured (orange), partly cured (blue) and fully cured (red) benzoxazine thin films. (c) Secondary ion image of fingerprint hydrocarbon secondary ions, first column, and of the backscattered Ar cluster fragment ratio I(Ar2+)/∑I(Arn+) (n = 2–3), second column, at the edge of a PS (MW: 4000) drop cast on a film of high MW polyethylene. In all cases, the analysis beam is 10 keV Ar3000+. |
Another example involving benzoxazine thermoset thin films is presented in Fig. 11b, where the same Ar cluster breaking ratio is plotted as a function of temperature for uncured (∼0% polymerization, orange), partly cured (∼60% polymerisation, light blue) and fully cured (∼100% polymerisation, red) samples. These molecules polymerise via the benzoxazine ring opening so that 4 reactive sites per molecule are able to bridge with neighbouring benzoxazines, eventually leading to a dense crosslinked network.72 The protocol used for the experiment is the same as in Poleunis et al.155 The initial benzoxazine molecular sample, might be slightly polymerised already (the reaction may already start at room temperature, though very slowly), so that the surface transition observed around 80 °C might be intermediate between a melting and a glass transition. After curing, the transition temperature increases significantly, and monotonically with the polymerisation degree. Finally, a second thermal cycle with the partly cured sample shows a shift of the transition towards higher temperature, indicating that the temperature cycle used to measure the first transition allowed the polymerisation reactions to proceed further, leading to a more crosslinked network with a higher transition temperature. This experiment illustrates the interest and the limits of the procedure for dynamic systems that evolve with temperature and time. Indeed, the stabilisation times required for a precise temperature control may allow the systems to change during the measurement. Optimising the design of the heating/sample holder system and the measurement protocol should help reduce this effect.
Finally, the imaging possibilities provided by backscattered Ar cluster fragment ions are illustrated in Fig. 11c. For this experiment, a drop of polystyrene was cast from a toluene solution on a polyethylene (PE) film. Polyethylene is rubbery, above its Tg, while polystyrene is glassy, below its Tg, at room temperature (20 °C, first image row). Chemical contrast at the edge of the droplet is indicated by the most characteristic ions of the two hydrocarbon polymers (C3H7+ for PE and C7H7+ for PS, first image column). When the temperature is lowered to −150 °C (second image row), the chemical contrast remains essentially unchanged, but the image of the Ar cluster breaking ratio changes drastically (second image column). The PE region becomes much brighter, demonstrating a change of the polymer surface properties. The polymer transition temperature is indeed between −110 and −125 °C, so that it is definitely glassy at −150 °C. This pronounced change and the very weak contrast of the PS vs. PE regions at −150 °C demonstrates the sensitivity of the Ar cluster ion fragmentation with respect to the surface physics or mechanics. The possibility of adding relevant physical information to the local chemical and molecular analysis by SIMS is exciting. One important feature of this protocol is that the correlated physical and chemical information may be resolved in 2 dimensions, such as AFM, via 2D ion beam imaging but also along the 3rd dimension (μm lateral resolution; nm vertical resolution) through molecular depth profiles, providing access to buried structures (multilayers, composites, nano-objects).
Mechanistically, it can be intuitively understood that harder, more cohesive and more crystalline material surfaces induce more fragmentation of the impinging clusters, which is confirmed by MD simulations. In the experiments involving Ar cluster ions and polymers, it is interesting to note that the Ar cluster fragment ratio I(Ar2+)/∑I(Arn+) (n = 2–3) always varies in a similar range of values (from 0.2 to 0.6, Fig. 11 and Poleunis et al.155), indicating a relative insensitivity to the polymer specific chemistry, polarity, etc., and therefore, unbiased sensitivity to mechanical and structural effects. For other types of clusters, specific chemical interactions between the cluster constituents and the surfaces may also influence their fragmentation, as was predicted with water nanodroplets.144 A detailed investigation of the physics underlying the observed effects, and their dependence on the cluster nature and energy, is currently underway in our laboratory.
Recently, Lorenz et al. reported a detailed investigation of the angular dependence of the emission of antioxidant molecular ions (Irganox 1010, MW: 1176) sputtered by 10 keV Ar2000+ clusters, using a specially designed sample holder with a collector plate.69 By analysing the material deposited on the collector, they demonstrated that the emission angle was very off-normal and forward directed, as soon as the incidence angle exceeded 15° away from the normal. This is in general agreement with experiments and MD simulations of large Ar cluster induced sputtering of molecular surfaces, such as those discussed in Section 2.53,58 The same study also showed that the SIMS spectra measured on the target and the collector were identical, suggesting that the material transferred to the collector was essentially intact, which is also consistent with other observations for low E/n. Encouraged by these results, we devised a molecular transfer experiment in our ToF-SIMS instrument, using a custom-made sample holder (Fig. 12).
After successful preliminary attempts with PS oligomer samples (MW: 2000), angiotensin (MW: 1046) was successfully transferred from a dried droplet target (22 μm-thick) to a clean silicon wafer using Arn+ clusters (1500 ≤ n ≤ 5000), as shown in Fig. 12a. The ToF-SIMS spectra recorded on the collector with 30 keV Bi5+ primary ions are similar to the ones recorded on a freshly spin-coated thin film of angiotensin. Fig. 12b indicates that insulin (MW: 5808) can also be found intact after transfer onto the collector, as demonstrated by the presence of the molecular ion in the mass spectrum obtained with 10 keV Ar3000+ projectiles. Nevertheless, the molecular peak is rather small in comparison with Fig. 1b, suggesting that even milder transfer conditions might be desirable. For lysozyme (MW: 14k), we couldn’t detect any molecular ions from either the target or the collector, only fragments, an indication of the limits of the SIMS analysis for massive molecules, even with GCIB as primary ions.
The transfer of larger proteins and complexes is under investigation, as well as the control of their bioactivity and their direct detection by other mass spectrometric methods. The possibility to transfer non-covalent complexes made of large biomolecules is suggested by mass spectra such as Fig. 12d, showing a rather intense peak of insulin dimer ions, which was recorded upon 10 keV Ar3000+ bombardment of a spin-coated insulin thin film. In the aforementioned transfer experiments, the quantity of molecular material is directly proportional to the primary ion dose and, therefore, it can be precisely controlled from the submonolayer to the multilayer regime. Strategies are also envisioned to obtain more uniform thicknesses over the collector. These promising experiments suggest the possibility of well controlled protein transfer irrespective of the substrate nature and open the door to the design of more complex multilayered architectures.
Finally, MD simulations help us analyse the first requirement for successful transfer and mass spectrometry of large (bio)molecules, that is, the conditions in which such molecules can be desorbed intact from surfaces. In a previous study, we chose globular polystyrene oligomers (MW: 7.5k) as model molecules to test desorption induced by large hydrocarbon clusters made of small polystyrene oligomers (4 monomer units each).162 The impinging cluster contained 197 polystyrene molecules for a total mass of 110 kDa, the total cluster energy was 10 keV and both the impact point and angle were varied. Recently, we conducted similar simulations with a significantly larger polystyrene molecule (MW: 60k) as target, comparable in size to proteins like bovine serum albumin (Fig. 2d). This time, 10 keV Ar5000 clusters were used as projectiles. The main results obtained in these studies are summarised in Table 1. The simulations indicate that both molecules can be desorbed without fragmentation from hard and soft substrates, provided that the energy per atom does not exceed a few eV. However, desorption is not successful from a soft substrate with normal incidence, only with oblique incidence (45°–75°). Mechanistically, the emission is the result of the combined action of the expanding rim pushing the molecule outward and the side jetting Ar atoms which entrain the molecule in their flux (“washing” mechanism) (Fig. 2d). For 75° incidence, the 60 kDa polystyrene molecule unfolds along the flat polyethylene surface, and though its upward momentum finally leads to desorption, it is not clear that the same would happen from a more corrugated surface. Overall, emission is easier from a hard substrate, because at the considered cluster energy per atom, it deforms mainly elastically and backscatters much of the deposited energy, helping the desorption process, while a soft substrate consumes a lot of the projectile energy in plastic deformation. This is, however, the case encountered in molecular transfer from a relatively thick organic target.
Cluster type | Energy (E/n) | Geometry | Molecule mass (kDa) | Intact desorption | Mechanism |
---|---|---|---|---|---|
a Adapted from Delcorte and Garrison.162 | |||||
Au substrate | |||||
Hydrocarbona | 0.65 | Top hit, 0°–30° | 7.5 | Yes | Spring |
Hydrocarbona | 0.65 | Top hit, 45°–60° | 7.5 | No | Deformation/sliding |
Hydrocarbona | 0.65 | Side hit, 0° | 7.5 | Yes | Washing |
Ar1000 | 10 | Side hit, 45° | 60 | No | Fragmentation |
Ar5000 | 2 | Side hit, 45° | 60 | Yes | Washing/lifting |
Ar5000 | 2 | Side hit, 75° | 60 | Yes | Washing |
Polyethylene substrate | |||||
Hydrocarbona | 0.65 | Top hit, 0° | 7.5 | No | Pushing down |
Hydrocarbona | 0.65 | Side hit, 0° | 7.5 | No | Lifting |
Hydrocarbona | 0.65 | Top hit, 60° | 7.5 | No | Pushing down |
Hydrocarbona | 0.65 | Side hit, 60° | 7.5 | Yes | Rim/washing |
Ar5000 | 2 | Side hit, 45° | 60 | Yes | Rim/washing |
Ar5000 | 2 | Side hit, 75° | 60 | Yes | Washing |
This journal is © the Owner Societies 2020 |