Ultramicroscopy 132 (2013) 239–247
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Understanding the detection of carbon in austenitic high-Mn steel using atom probe tomography R.K.W. Marceau n, P. Choi, D. Raabe Max-Planck-Institut f¨ ur Eisenforschung, Max-Planck-Straße 1, 40237 D¨ usseldorf, Germany
a r t i c l e i n f o
abstract
Available online 17 February 2013
A high-Mn TWIP steel having composition Fe–22Mn–0.6C (wt%) is considered in this study, where the need for accurate and quantitative analysis of clustering and short-range ordering by atom probe analysis requires a better understanding of the detection of carbon in this system. Experimental measurements reveal that a high percentage of carbon atoms are detected as molecular ion species and on multiple hit events, which is discussed with respect to issues such as optimal experimental parameters, correlated field evaporation and directional walk/migration of carbon atoms at the surface of the specimen tip during analysis. These phenomena impact the compositional and spatial accuracy of the atom probe measurement and thus require careful consideration for further cluster-finding analysis. & 2013 Elsevier B.V. All rights reserved.
Keywords: Atom probe Fe–Mn–C TWIP steel Carbon detection Cluster-finding analysis Short-range order
1. Introduction High-Mn austenitic TWIP (Twinning Induced Plasticity) steels exhibit high strength and exceptional energy absorption properties due to extensive twin formation under mechanical load, making them very attractive for application in the automotive industry. These materials have low stacking-fault energy (SFE), where this parameter is highly sensitive to composition and is regarded as the governing criterion for the active plasticity mode. In a recent study using density-functional theory-based total-energy calculations, possible local atomic ordering effects have been discovered due to a thermodynamic driving force that should lead to manganese enrichment of the immediate proximity of carbon atoms [1]. Other works in the literature employing mechanical testing, modelling and simulation, also refer to the coupling of C and Mn atoms as the product of dynamic strain aging and contribute to the remarkably rapid work hardening behaviour [2,3]. Whilst the solute architecture within this solid solution alloy is increasingly recognised as a key factor in engineering the evolution of deformation microstructure, the challenge is that characterising atomistic-level structures pushes the limits of resolution and detection of most microscopy and characterisation techniques. Atom probe tomography (APT) provides a unique combination of highly resolved atomistic information, both chemically and spatially in three dimensions, which can be data-
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mined for quantitative nanostructural information. It is therefore the experimental tool required to quantitatively assess atomic-scale fluctuations in local chemistry by applying state-of-the-art data analysis techniques to discern clustering phenomena. These fluctuations in local composition include short-range ordering (SRO); reputed to affect the local SFE of the material and thus also local and global deformation pathways. Despite the relative ease of access to the experimental, atomic-scale data by APT, there are various analysis difficulties that need to be overcome in order to produce accurate information. This is particularly the case in the Fe–Mn–C system where the interstitial C atoms in Fe can be subject to correlated field evaporation [4], directional walk [5], and are often detected as molecular ion species on multiple hits [6,7]. These issues, in addition to quantitative carbon content analysis [6,8], are discussed. The aim of this work is to better understand the detection of carbon in steel with particular reference to how this will influence the cluster-finding/SRO analysis, using Fe–Mn–C steel as an example.
2. Material and methods High-Mn TWIP steel was used in this study, with nominal composition of Fe–22Mn–0.6C (wt%). The actual bulk chemical composition measured by metallurgical analysis methods is shown in Table 1. The material was melted in an induction furnace under an Ar atmosphere and cast into round bars of 25 mm diameter. To avoid Mn segregation [9], samples were swaged to 20% area reduction at 1000 1C and subsequently solution-treated for 4 h at 1100 1C under Ar. Thereafter, samples were hot-rolled to 75% engineering thickness at 1000 1C followed by air-cooling. The hot-rolled material has been
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Table 1 Chemical composition of the Fe–Mn–C alloy.
wt% at.%
Fe
Mn
C
S
N
O
P
Al
Bal. Bal.
21.3a 21.1
0.68b 3.07
0.0028b 0.0047
0.0013c 0.0050
o 0.002d o 0.007
o 0.002a o 0.004
o 0.002 o 0.004
Si a
o0.002 o0.004
Cr a
o0.002 o0.002
Mo a
o 0.002 o 0.001
a
a
Inductively coupled plasma optical emission spectroscopy (ICP-OES). Infrared absorption, measurement after combustion. Thermal conductivity, decomposition in graphite crucible. d Infrared absorption, reduction fusion under helium. b c
shown to have a fully austenitic structure with an average grain size of 50 mm, which remains stable during room temperature tensile testing carried out at an initial strain rate of 5 10 4 s 1 [10]. The microstructure of the tensile deformed TWIP steel was also examined [10] using scanning electron microscopy techniques, namely, electron backscatter diffraction (EBSD) to evaluate the local crystallographic texture and electron channelling contrast imaging (ECCI) [11,12] to analyse the dislocation and twin substructure. Needle-like specimens for APT study were prepared from the gauge length of a tensile-deformed sample interrupted at a true strain of e ¼0.30. The APT work was performed on sharp needles prepared by site-specific, in-situ lift out technique [13] using a FEI Helios NanoLab 600TM dual beam FIB/SEM instrument, in order to capture specific grain orientations identified by EBSD, having specific deformation substructures as characterised by ECCI [10]. Atom probe microscopy was conducted using a LEAP 3000X HR instrument (Cameca) operating in voltage mode under ultra-high vacuum with a pulse fraction of 20%, pulse repetition rate of 200 kHz and at a detection rate of 0.005 atoms/pulse. The total voltage during probing was in the range of 3.5–7.6 kV. Measurements containing 5 million atoms each were carried out at setpoint temperatures of 20, 40 and 60 K to test the effect of temperature on the apparent concentration of carbon. Tomographic reconstruction was performed with the IVAS 3.6.0 software using shank angles and tip radii ( 20–60 nm) measured from SEM after site-specific preparation.
3. Results and discussion
Fig. 1. Atom probe mass spectra of single-hit and multiple-hit ions for the Fe–22Mn–0.6C (wt%) steel measured at a set-point temperature of 60 K.
Table 2 Measured number of counts (background corrected) of Fe, Mn and C (monomer and molecular species) ions arriving on single and multiple hits, corresponding directly with the mass spectra in Fig. 1 measured at a set-point temperature of 60 K. Ion species
Single hits
Multiple hits
Ratio of multiples/singles
56
687 212,557 3,598,994 78,951 11,096 103 996,244 3280 7673 4917 793 5705 143
898 131,326 748,930 45,601 8676 862 474,571 27,003 49,563 20,742 5417 17,888 410
1.31 0.62 0.21 0.58 0.78 8.37 0.48 8.23 6.46 4.22 6.83 3.14 2.87
Fe Fe2 þ 56 Fe2 þ 57 Fe2 þ 58 Fe2 þ 56 Fe3 þ Mn2 þ Cþ C2 þ C2þ C3þ C23 þ C24 þ 54
3.1. APT mass spectra Fig. 1 shows the atom probe mass spectra of single and multiple hit ions between 5 and 37 Da for the Fe–Mn–C steel, with peak assignments labelled directly on the plots. Peaks also occur at 56 and 69 Da, not shown in this figure, corresponding to Fe þ and Ga þ , respectively. Peaks at 18.7, 27, 28, 28.5 and 29 Da were assigned to Fe ions, whilst Mn is completely contained with the peak at 27.5 Da. Ga ions are also detected in the second charge state at 34.5 Da, and O in the first charge state at 16 Da. The peak at 14 Da is assigned to nitrogen (N þ and/or N22 þ ) given the results of the metallurgical analysis (Table 1) and interestingly only occurs as multiple-hit ions. In the absence of any other significant amounts of trace elements detected by metallurgical analysis, the remaining peaks in the mass spectra correspond to carbon and its molecular species. 3.2. Single hits and multiple hits of carbon The occurrence of carbon and its molecular species is quite curious as to whether it is detected as single hit ions or multiple hit ions. Comparing the single-hit and multiple-hit mass spectra in Fig. 1 it is clear that carbon is much more common in multiple events, and also in relative comparison to the other elements (Table 2). The same trend was observed by Thuvander et al. [14] in a Ti(C,N) system. The 12C isotope (in its first and second charge states) of monomer
þ
carbon is detected in both the single-hit and multiple-hit mass spectra (Fig. 1), but the 13C isotope ions are only detected as multiple hits. The peaks at 18 and 36 Da, assigned to 12C23 þ and 12C3þ , respectively, and also the peak at 24 Da, are all occurring as both single and multiple hits. These are all simple molecular species of carbon. The complex molecular species on the other hand, i.e. (12C213C)2 þ RC23 þ , (12C313C)2þ RC24 þ and (12C13C) þ RC2þ occurring at 18.5, 24.5 and 25 Da, respectively, have peaks predominantly in the multiple-hit mass spectrum. As per Takahashi et al. [8], the peak at 24 Da has been assigned to the 12C2þ molecular species, which as a result produces a value of the apparent concentration of carbon closer to the nominal concentration (Fig. 2(a)), whereas if it were to be assigned completely to the 12C24 þ molecular ion the total carbon concentration is well
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changed by pulse fraction; however at a lower value (e.g. 15%) there is an increase in the background noise level due to DC evaporation. In the current study, the pulse fraction was set to 20% so as to keep the background noise relatively low but also reduce the possibility of reaching maximum capacity of the pulser as the standing voltage on the specimen increased during the experiment. Fig. 2(a) shows the apparent concentration of carbon in total, as monomer (C1) ions, dimer (C2) ions, trimer (C3) ions and tetramer (C4) ions, as a function of temperature. The corresponding concentrations of Fe and Mn are shown in Fig. 2(b). Note that these values have been corrected by subtracting the background noise from the mass spectrum using the IVAS software. The respective concentrations of all the elements were best achieved by atom probe measurement at 60 K, as indicated in Fig. 2(a) and (b) given minimal deviation from the actual concentration values plotted as dashed lines. Subsequent experiments were therefore carried out at this temperature. Looking at Fig. 2(a) it can be seen that molecular carbon species with an odd number of atoms, i.e. C3, were found to be more abundant than those having an even number of atoms (e.g. C2 and C4) per molecule. This is in accord with theoretical ab initio calculations by Raghavachari and Binkley (1987) [17] and pulsed-laser field evaporation experiments by Liu and Tsong (1988) [18], and also observed by atom probe in the work of Sha et al. [6]. 3.4. Significance of molecular ion species of carbon
Fig. 2. Apparent concentration (background corrected) of (a) carbon and its molecular species and (b) Fe (including individual isotopes of the second chargestate) and Mn, as a function of temperature during the atom probe experiment. The dashed horizontal lines indicate the total concentrations of Fe, Mn and C (from Table 1). The percentage of carbon hits as multiples are also given in (a).
overestimated. Peak decomposition based on the natural abundance of the isotopes [6] indicates that there should be a roughly equal contribution of each of the 12C2þ and 12C24 þ molecular ions to the peak at 24 Da, confirmed in the present work using the deconvolution algorithm provided in the IVAS software. There are also recent studies in the literature on carbide-forming systems that highlight a peak correction method based on the occurrence of single/multiple events to make more accurate quantification of the carbon concentration [14–16]. However in the current work, for the purpose of later making a cluster-finding analysis, there needs to be an either/or assignment of ions (each having specific spatial coordinates) for each peak. Thus, a practical approach has been taken where the peak at 24 Da has been assigned to only 12 þ C2 molecular ions for the reason outlined earlier. Similarly, the peaks at 25 and 26 have been assigned to (12C13C) þ and 13C2þ , respectively, rather than (12C213C2)2 þ and 13C24 þ . 3.3. Temperature dependence of the apparent concentration of carbon In addition to correct assignment of peaks in the total mass spectrum, optimum experimental parameters are required during the atom probe measurement in order to determine the composition of the steel as accurately as possible. It has been previously shown by Takahashi et al. [8] that the measured concentration of carbon is not
A high percentage (62%) of the carbon atoms belong to molecular ion species (where 39% of the detector hits attributed to carbon come from individual carbon molecular ions – Table 2). For the formation of molecular ions to occur, it seems a necessary criterion for the atoms concerned to be in close proximity to each other near the specimen surface – a view that suggests that a high percentage of carbon atoms detected as molecular species could already indicate a degree of clustering of these atoms in the microstructure [19], notwithstanding the effect of surface migration [5]. Also, as observed in the current study, the smallest doubly charged carbon cluster ion (molecular ion) observed is C23 þ (Fig. 1), which means that three carbon atoms is the critical number to resist Coulomb explosion [20]; a phenomenon whereby highly charged molecules or clusters become unstable due to the repulsive Coulomb forces of the constituent atoms. Given that carbon ions with an odd number of atoms are more stable regardless of charge state [18], and the fact that larger cluster ions are easier to ionise than smaller ones [17]; these factors could bear influence on the charge-state distribution observed in the mass spectrum if splitting of molecular ions were to occur during post-ionisation. So far, due to a lack of evidence of molecular ion dissociation observed in data acquired using the LEAP 3000X HR [21]; it is inconclusive as to whether this is affected by the energy compensating action of the wide-angle reflectron. 3.5. Consideration of other factors that affect atom probe measurement of carbon The question remains however; why is the measured concentration of carbon by atom probe too high when peak decomposition is employed in this case, and especially at lower atom probe temperatures? In fact, previous studies in the literature display a mix of trends – either the nominal concentration of carbon is reached when peak decomposition is or is not employed. This is complicated by the fact that carbon is not always homogeneously distributed in steel but rather tends to segregate to microstructural features (e.g. grain and phase boundaries, defects such as dislocations, etc.) depending on its mobility in a certain phase. Additionally, carbon distribution from atom probe measurement can be influenced by the underlying
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crystallographic nature of the steel material [5,7,22,23] and these artifacts need to be considered carefully before making an assessment of the bulk composition. Nevertheless, atom probe measurements on martensitic steel show that the carbon concentration is often underestimated without deconvolution of the peak at 24 Da (12C24 þ and 12C2þ ) [6,24], as is also the case for a range of carbide materials [14]. However, the opposite is generally true for measurements of carbon in cementite [8,25,26] and also in the case of the present work for austenitic steel, where the carbon concentration becomes or would become overestimated when accounting for both 12 2 þ C4 and 12C2þ at 24 Da peak in the mass spectrum. The reasons for this difference are due to the field evaporation behaviour of carbon in steel, which is a complex combination of the experimental conditions (as previously discussed), composition of the material (and the relative field evaporation potentials of the elements) and the resultant local electric field environment of the carbon atom site in relation to its neighbours (Fe in particular) in the lattice. Carbon occupies an octahedral interstitial site within face-centred cubic (fcc) austenite (g), body-centred cubic (bcc) ferrite (a), bcc or bodycentred tetragonal (bct) martensite (a0 ) [27], but its location is further complicated with respect to the formation of martensite depending on the degree of supersaturation of carbon in solid solution, where an intermediate hexagonal close-packed (hcp) martensite can be present [28]. The cementite (y) phase, referred to as a Fe3C compound, is significantly different from the interstitial solid solutions, having an orthorhombic D011 crystal structure [27]. The anomalous spatial detection and compositional measurement of carbon in steel by atom probe has been widely reported. Recent work by Felfer at al. [29] and the references therein summarise relevant effects that contribute in general to this well-recognised phenomenon. Positional accuracy of carbon may be compromised by field-induced surface migration of the atoms on the specimen tip prior to field evaporation (see [5] and references therein), which is related to the specimen crystallography [7], but has also been described as being the result of trajectory aberrations, specifically related to the difference in trajectories of C and Fe ions [22]. Preferential retention is another effect that has received a lot attention, where carbon as a highevaporation-field solute element [30] may be retained longer on the tip of the Fe-based specimen; thus appearing later in the sequence of detected events and hence reconstructed at a deeper position in the tomogram. Takahashi et al. [8] ruled out that preferential retention of C and preferential evaporation of Fe caused their discrepancy in measured carbon concentration in cementite since the carbon concentration was unchanged with decreasing pulse fraction and increased standing voltage (and therefore increased potential for DC evaporation of Fe). However, it still does not rule out the possibility that preferential retention of C will affect the positional accuracy of these atoms in the reconstructed data. This effect has been measured for C present at grain boundaries in Fe [29], but the magnitude of this effect in bulk solid solution material (i.e. within the interior grain matrix) is more difficult to determine. From the point of view of compositional accuracy; minimal pile-up of Fe ions might be expected on the detector because only a low fraction of multiple hits from Fe ions are observed (Table 2). Hence one might also expect a negligible effect from counting loss of Fe (and artificial increase of C) as a result of detector saturation [31,32] from the dead time of the delay-line detector (about 3 ns [14]). This is the argument from Takahashi et al. [8] as a result of analysis of the ratios of isotopes of Fe. Also as per [8], there is no indication in the current study that peaks occur in the mass spectra as a result of Fe dimer ions (Fe22 þ ), at 56.5 Da (56Fe57Fe2 þ ) and/or 28.25 Da (56Fe57Fe4 þ ), which therefore means that all the Fe was detected as monomer ions. In the current work, as temperature decreases the apparent concentration of Fe decreases
(Fig. 2b), concurrent with an increase in that of C (Fig. 2a) – also shown by Takahashi et al. [8]. The decrease in measured concentration of Fe is due to the decrease in 56Fe2 þ ions (Fig. 2b), which have the highest number of counts in the mass spectrum ( 65–68 at%). This trend is despite the measured increase in concentration of 54Fe2 þ ions, which have a much lower concentration ( 5–6 at%). Also, the percentage of all ions detected on multiple hits increases as the temperature decreases (21%, 24% and 28% at 60, 40 and 20 K), as reflected by that of C in Fig. 2(a). So therefore, the reason for the measured increase in carbon concentration at lower temperature can actually be explained by
Fig. 3. Distribution of frequency of (a) Fe2 þ , (b) Fe þ and (c) Fe3 þ ions on the atom probe detector (legends refer to number of hits).
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a preferential loss of Fe due to the effect of multiple hit events on detector saturation (dead time). Although C is much more common in the multiple hits than in the single hits on a relative basis, Fe has the most counts (in particular 56Fe2 þ ) in the multiple events (Table 2); so if ions are lost due to the dead time it would affect the concentration of Fe the most. Whilst it is possible to
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correct for this effect based on the natural abundances of the isotopes [33], as previously mentioned in Section 3.2, there needs to be an either/or assignment of ions (each having specific spatial coordinates) for the purpose of later making a cluster-finding analysis.
Fig. 4. Distribution of single-hit ions of (a) Fe, (b) Mn, (c) C1, (d) C2, (e) C3 and (f) C4 on the atom probe detector (legends refer to number of hits).
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3.6. Impact of correlated detection of carbon on cluster-finding/SRO analysis Correlated field evaporation is the process of co-evaporation of atoms such that when they are detected they are correlated both spatially and temporally, and occurs because the field evaporation of one atom increases the probability of field evaporation of
neighbouring atoms by increasing the local electric field [4], i.e. the field at evaporation [34]. The extent of correlated field evaporation is therefore manifest in the measurement of multiple hits in the atom probe experiment. In this work, a very high percentage of multiple hits of carbon are detected. In fact, 84% of the carbon hits are detected as multiple hits and after decomposition of the molecular species, 82% of all carbon atoms are
Fig. 5. Distribution of multiple-hit ions of (a) Fe, (b) Mn, (c) C1, (d) C2, (e) C3 and (f) C4 on the atom probe detector (legends refer to number of hits).
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detected as multiples (calculated from Table 2). Also, the percentage of multiple hits increases as the temperature decreases (Fig. 2a)—a trend seen in the current work for all ion species. In order to obtain an appreciation of the spatial correlation of multiple hits as compared to single hits, it is pertinent to map the electric field distribution at the specimen tip. For a given temperature in voltage-mode APT multiple hits are more likely to occur at regions of higher field strength, which are well-known to be caused by faceting of the specimen surface, e.g. atom kink sites and the edges of atomic terraces, forming patterns of crystallographic poles and zone lines [35–37]. The ionisation charge state of an atom during field evaporation is heavily dependent on the electric field [38]. Additionally, ions formed by field evaporation can be subsequently post-ionised in the vicinity of the tip whereby an ion being accelerated away from the surface in a strong electric field loses one or more electrons by tunnelling into the substrate [39]. Thus, the relative abundance of charge states of a species provides a good indication of the electric field strength at the tip surface [40,41]. In Fig. 3 the first, second and third charge states of Fe have been mapped from detector hits in the experiment; using the raw delay line position coordinates rather than the reconstructed data so as to exclude the influence of any possible artifacts introduced during tomographic reconstruction. Whilst quantitative estimation of the actual electric field strength at the tip surface is possible (e.g. [5]) using the data curves published by Kingham [38], because the distributions of Fe þ and Fe3 þ are homogeneous (Fig. 3b and c, respectively) in this case, the distribution of Fe2 þ (Fig. 3a) ions arriving on the detector directly indicates the variation in electric field. For example, the Fe2 þ /Fe þ ratio is higher on the left side of the detector hit map where there are more hits from Fe2 þ ions, indicating higher electric field from the Kingham curves for Fe [38]. This holds true except for the crystallographic pole region, which as mentioned earlier is a highly faceted location, thus influencing the ion trajectories and accordingly having a lower density of Fe2 þ hits as seen in Fig. 3(a). In this region the Fe3 þ /Fe2 þ ratio is relatively higher than neighbouring regions and thus indicates a higher electric field. Fig. 4 shows the distribution of single-hit ions of Fe, Mn, monomer C ions and also the molecular species of carbon; mapped using the detector coordinates. Whilst the single-hit distributions of Fe and Mn (Fig. 4a and b) follow similar detection behaviour, representative of the crystallographic nature of the specimen during field evaporation, the distribution of single hits of carbon and its molecular species (Fig. 4c–f) is homogeneous across the detector. Fig. 5 shows the equivalent information of Fig. 4 but for the multiple-hit ions. In this case, multiple hits of Fe and Mn ions (Fig. 5a and b) are clearly influenced by the electric field distribution, showing a similar distribution to that of Fig. 3(a), but detection is also influenced by crystallography-induced ion trajectory effects given the lower density of hits at the pole region. Multiple hits of monomer carbon ions are also influenced by the higher electric field measured on the left hand side of the detector (Fig. 5c), but there is also a higher number of multiple hits at the crystallographic pole. This could mean either that the trajectory paths of monomer C ions after field evaporation at the pole are not as much influenced by the underlying crystallography as compared to Fe and Mn ions (possibly due to the higher field required for evaporation of carbon atoms [30] and because they reside at interstitial lattice sites); or, that surface migration (also termed directional walk [5]) of the C monomer ions occurs as a result of the electric field gradient. It is also possible that both these effects occur in parallel. The observed inhomogeneous detection of carbon tapers off with the molecular species,
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where only 31% of the carbon ions are detected as molecular species on multiple-hit events (from Table 2), and this effect is observed to also decrease as the number of carbon atoms per molecule increases (Fig. 5d–f). This could be an indicator of molecular ion dissociation, since monomers are more commonly detected as multiples and carbon molecules as singles. Fig. 6 shows the distribution of multiple-hit ions as a function of their degree of multiplicity, where both the size and grey scale of the markers represent the number of atoms per multiple-hit event. It can be seen that in all cases, the high-field regions at the surface of the tip (at both the pole region and also as measured on the left side of the detector) attract a higher number density of multiple hits with a higher degree of multiplicity. The effect becomes decreasingly obvious however for the molecular species as the number of carbon atoms per molecule increases. For example, there is almost an absence of detection of high-multiplicity C3 multiple hits (Fig. 6e) compared to C2 multiple hits Fig. 6d) at the crystallographic pole region. So on the one hand, molecular carbon species possibly represent clusters of carbon atoms in the microstructure due to the supposed requirement of close spatial proximity for their formation during field ionisation and evaporation; but on the other hand, their detection on multiple-hit events and with a high degree of multiplicity, decreases with the number of carbon atoms per molecular ion. The latter is related to the effect of artifacts – i.e. correlated field evaporation and the influence of electric field gradients (as determined by crystallography) on directional migration of carbon atoms at the specimen tip surface – whereas the former concerns actual microstructural information. This balance of signal to noise and how it impacts clusterfinding/SRO analysis involving C, Mn and Fe atoms, needs to be investigated further as a function of the size and abundance of the molecular carbon species detected on multiple hits and whether the data should be filtered based on fiducial selection from the detector hit map. Indeed, decomposition of the molecular species of carbon is important to properly account for the participation of carbon during the assessment of SRO/ clustering phenomena.
4. Summary and conclusions This study is motivated by the need for a better understanding of the detection of carbon in Fe–Mn–C TWIP steel for accurate and quantitative analysis of clustering and short-range ordering in this system. Optimal experimental parameters for compositional accuracy (60 K, 20% pulse fraction) require minimisation of multiple hit events so as not to artificially increase the concentration of carbon due to preferential loss of Fe because of detector saturation (dead time). Correlated field evaporation and directional walk/migration of carbon atoms at the surface of the specimen tip during field evaporation are discussed with respect to detection of carbon as monomer or molecular ion species and as single or multiple hit events. These phenomena impact the spatial accuracy of the atom probe measurement and importantly require careful consideration for further cluster-finding/SRO analysis.
Acknowledgements RKWM gratefully acknowledges the support of the Alexander von Humboldt Foundation through the award of a Humboldt Postdoctoral Fellowship. PC and DR acknowledge financial support by the German Research Foundation in the framework of SFB 761 ‘‘steel ab initio’’.
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Fig. 6. Distribution on detector of multiple hits of (a) Fe, (b) Mn, (c) C1, (d) C2, (e) C3 and (f) C4 ions according to degree of multiplicity (legends refer to number of hits per detection event).
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