Applications of Time-of-Flight Secondary Ion Mass Spectrometry

Heng-Yong Nie
Surface Science Western
Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is extremely surface sensitive and has superior chemical selectivity, making this surface analytical technique powerful and often unique in identifying chemical structures and exploring surface chemistry. With its imaging capability, ToF-SIMS is especially useful in materials failure analyses where both identification of chemicals and pinpointing their localities are required. Assisted with a sputter ion beam, ToF-SIMS is also capable of depth profiling both organic and inorganic materials, which allows exploring chemical variability in the depth direction without a priori knowledge of the sample under investigation due to its parallel detection of all ions generated.
  • probing the 1-3 nm outermost surface
  • identifying organic molecules
  • imaging and depth profiling
It is my hope that the examples presented here will help you appreciate as how ToF-SIMS can be used to assist your research on surface chemistry, solve your surface-associated problems, or develop analytical approaches to understanding materials failure mechanisms.

How ToF-SIMS works?

ToF-SIMS such as an IONTOF TOF-SIMS IV at Surface Science Western, a pulsed (~1 ns) primary ion beam (e.g., 25 keV Bi3+) is used to bombard the sample surface, which generates secondary particles including ions, electrons and neutral particles carrying chemical information of the surface. Either positive or negative ions (determined by the polarity of the electric field applied between the extractor and the sample stage), each at a time, are extracted by an electric field (e.g., 2 kV). The extracted ions gain energy of 2 keV (assuming that they are singly charged). Then the energetic ions are let fly through a flight tube (2 m in length). The lighter ions will fly faster and thus arrive at the detector than the heavier ones. The basic concept of ToF-SIMS is illustrated below (in the case of extraction of positive ions; the polarity of the extraction electric field will be reversed for the extraction of negative ions).

The ions arrive at the detector according to their flight times that are determined by their mass to charge ratio (m/z). As shown in the following figure, the measured time events of the ions striking the detector are converted to m/z via calibration of known species such as hydrogen, carbon and hydrocarbons, as well as any known ions detected. Though dependent on the size of a scanned area, mass resolutions (mass dependent as it is defined as the center of a peak divided by its full width at half maximum of the peak) can be as high as 10,000.

After the extraction of the secondary ions is finished a low energy (18 eV) electron beam is flooded on the scanned area for charge compensation until the next pulse of the primary ion beam is shot (this is the reason ToF-SIMS can be applied to highly insulating materials). All these events are done within the cycle time. Within each cycle time, the first one to arrive at the detector is a hydrogen ion and the heaviest one will arrive at last, which is determined by the time the system allows the ions to be detected. For example, with a cycle time of 100 μs (or a repetition rate of 10 kHz), the cutoff is around m/z 900 - anything heavier than this has no chance to reach the detector before the system start the next cycle. Therefore, in order to catch higher mass species, the cycle time has to be increased (e.g., m/z up to 1600 will be covered by a cycle time of >140 μs). The base pressure of the analysis chamber of a ToF-SIMS instrument can be as good as 1×10-9 mbar. However, it will work with no problems even if at pressures around 1×10-5 mbar.

  • parallel detection: all ions generated are recorded.
  • high mass resolution: up to 10,000.

Because the primary beam rasters the sample surface pixel by pixel (e.g., 128 pixel × 128 pixel) over the scanned area (e.g., 500 μm × 500 μm), each pixel has a mass spectrum, which enables ion imaging when the intensities of selected ions are plotted against the pixels. Ion images show spatial distributions of chemicals over the scanned area. The spatial resolution is a couple of microns in high mass resolution mode (in the so called high current bunched mode). The primary ion fluence is usually controlled at ~1011 ions/cm2, which is much less than the static limit of ~1013 ions/cm2. This is the reason why ToF-SIMS is called static SIMS, meaning that the surface is not significantly altered after the measurement so that the same surface can be subjected to other analyses. Moreover, with a sputter ion beam (e.g., Cs+ and C60+) used to remove a controllable portion of materials, ToF-SIMS is also capable of elemental and molecular depth profiling.

ToF-SIMS is surface sensitive, probing only 1-3 nm of the topmost surface. Because ion yields for different species are different and can even change according to the chemical environment they are in (matrix effect), ToF-SIMS is not a quantitative technique. A reference is needed for quantification of specific elements. Therefore, it is not practical to compare different species from the same sample. However, ToF-SIMS results, meaning ion intensities, can be conveniently used to compare the same species from different samples. For example, one may find that sodium (Na+) is several times more in a sample than another one.

ToF-SIMS spectra are rich in chemical information as they capture all ions that are created in the process of bombardment (by the primary ion beam). It often provides unique chemical selectivity for organic materials via the characteristic ions (in many cases molecular ions). This allows one to explore/develop unique analytical approaches to reveal surface chemistry and/or identify chemical structures.

ToF-SIMS is also referred to as static SIMS because it collects chemical information from the surface while only sputtering off 1% or less of the topmost layer of the specimen (thus leaving the surface chemistry essentially undiminished). To put it in context, the "static" term is meant to compare with the dynamic SIMS, which was developed prior to static SIMS. In dynamic SIMS the primary ion beam sputters through the specimen while detecting the chemical constituents of the specimen, leading to its applications in depth profiling elements (e.g., dopants in semiconductors and precious metals in ores).

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Ion mass spectra

Surface sensitivity and chemical selectivity of ToF-SIMS

ToF-SIMS is characterized by its surface sensitivity and chemical selectivity. For example, if there is only a monolayer of some molecules, many other techniques may lack either surface sensitive or chemical selectivity, or both. By contrast, a monolayer of a substance is more than enough to be detected by ToF-SIMS. As an example, shown below are negative (upper panel) and positive (lower panel) ion mass spectra obtained on a stain which was visible on a metal substrate and only showed slightly increased carbon levels as detected by other two techniques. ToF-SIMS helped identifying the stain as due to the presence of diacylglycerides (also called diglycerides). The fatty acid chains are seen as negative ions corresponding to fatty acids, such as palmitate C16H31O2¯ at m/z 255 and myristate C14H27O2¯ at m/z 227. With the removal of a hydroxyl group (OH)  from the glyceryl link, the glyceryl dipalmitate (C16H31O2)2C3H5+ is detected as a positive ion at m/z 552. As can be seen in the spectra, other combinations with different fatty acids are also detected.

Another example for identification of Cyanox 1790, whose molecular formula is [M=C3O3N3(C13H19O)3], is shown below. Molecular ions of M+ and [M-H]¯ are detected at m/z 699 and 698, respectively, both of which are rather weak. Abundant ions are C13H19O+ and C3O3N3(C13H19O)2¯ at m/z 191 and 508, respectively. This and the above example demonstrate the superior chemical selectivity of ToF-SIMS.

  • extremely surface sensitive
  • superb chemical selectivity

Vancomycin, M=C66H75Cl2N9O24, a Gram-positive bacteria antibiotic, is studied. Shown below are negative and positive ion mass spectra for a vancomycin layer spin-coating on a cleaved mica substrate. There are an abundant negative and an abundant positive peak at m/z 155 and 100, respectively. These two peaks have been identified as C7H4O2Cl¯ and C6H14N +, respectively.

These two ions are fragmented from the two structural moieties of the vancomycin molecule illustrated below. In addition, though in much lower intensities, the protonated molecular ion [M+H]+ (m/z 1448) and decarboxylated molecular ion [M-COOH]¯ (m/z 1402) were also detected.

Other chemicals such as pigments, antibiotics and surfactants have been examined. Their molecular ions are often detected using ToF-SIMS. They usually also have diagnostic fragmented ions. To reiterate, the superior chemical selectivity and surface sensitivity of ToF-SIMS often make it powerful in investigating surface contaminants, which may be as thin as a couple of nanometers, yet are either visible and/or impact the surface chemistry of the contaminated substrate.

Isotopes of elements

ToF-SIMS is also useful in detecting isotopes of elements and molecules containing them. For substances that are not isotope enriched the ion mass spectra show the natural abundance of the isotopes. In fact, isotope distribution pattern of an element is a useful property for identification of elements and molecules/fragments. Shown below are ion mass spectra for tin, copper and a fragment ion AuCl2.

Shown below is the negative ion mass spectrum of Pigment Yellow 110 (M=C22H6Cl8N4O2). The pigment molecule has eight chlorine atoms, each of which has two isotopes at m/z 35 and 37, making the deprotonated molecular ion a complicated group of peaks. The most abundant peak is called monoisotopic peak (which in this case is at m/z 641). Those isotope patterns can be checked using the Isotope Distribution Calculator and Mass Spec Plotter provided by Scientific Instrument Services.

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Ion mass spectra of silicones

Silicones are widely used in plastic industry as a release agent and paint systems as a wetting agent. They are also used in many personal cosmetic products. Therefore, via plastic packaging and handling this chemical is often found on the surface of many objects as a contaminant. Due to their low surface energy nature (~24 mJ/m2), silicones tend to cause failures in adhesion and create paint defects. To make things worse, even trace amounts of silicones are enough to alert the surface energy of the contaminated substrate. ToF-SIMS is especially powerful in identifying siloaxane contamination, thanks to its superior surface sensitivity and chemical selectivity.

Shown below are negative secondary ion mass spectra of different silicones. They both have the identical ions, but the ion intensity ratios between some of the ions are different for the two different silicones. This is a piece of important chemical information because one often encounters situations where two or more molecules all have the same elements so that they are not differentiated by fragmented ions, rather, they may be only differentiated by the relationships between the intensities of some of their ions detected in ToF-SIMS. For example, for the two different silicones, one can see that the ion intensity ratios for ions at m/z 89 (SiC3H9O¯) and 91 (SiC2H7O2¯), as well as those at m/z 163 (Si2C5H15O2¯) and 165 (Si2C4H13O3¯) are reversed. This difference is indeed a reflection of the abundance and lack of the Si(CH3)3 in polydimethylsiloxanes and cyclosiloxane, respectively. This trend is also observed for Sylgard 184, a silicone elastomer kit from Dow Corning, with different degrees of cross-linking.

Shown below are a list of the major negative and positive ions (and their m/z) fragmented from silicones and the fragmentation patterns based on the molecular formula of poly(dimethyl siloxane), PDMS, which is a silicone oil.

    Negative ions

  • Si¯ (m/z 27.977)
  • SiCH3O¯ (58.995)
  • SiC2H5O¯ (73.011)
  • SiCH3O2¯ (74.991)
  • SiC3H9O¯ (89.043)
  • SiC2H7O2¯ (91.021)
  • Si2C3H9O3¯ (149.009)
  • Si2C5H15O2¯ (163.061)
  • Si2C4H13O3¯ (165.041)
  • Si3C5H15O4¯ (223.027)
  • Si3C7H21O3¯ (237.081)

    Positive ions

  • Si+ (m/z 27.977)
  • SiC3H9+ (73.047)
  • Si2C5H15O+ (147.065)
  • Si3C5H15O3+ (207.033)
  • Si3C7H21O2+ (221.086)
  • Si4C7H21O4+ (281.051)
  • Si5C7H21O5+ (325.024)
  • Si5C9H27O5+ (355.070)

  • Silicones, due to their low surface energy, are widely used as wettability enhancers and release agents.
  • This very surface property, however, is responsible for failures when silicones contaminate a substrate subjected to adhesion or painting applications.
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Ion images

Paint craters

ToF-SIMS imaging is useful in studying the localization of chemicals on a surface. This is especially useful in cases where the presence of a chemical is critical but may be ignored because the intensities of its ions are rather weak due to its (minimal) size when one only looks at the ion mass spectra collected over the scanned area. For example, paint craters may well be caused by the presence of a tiny perfluorocarbon particle (due to its low surface energy, approximately 18 mJ/m2, that obstructs the wetting of the paint whose contribution to the mass spectrum collected on a rather large area may be buried (or hardly noticeable). If one maps the scanned area, say 500 μm × 500 μm, even a perfluorocarbon particle of a size only a couple of microns across will be detected because of its contrast. This approach is thus a must in ToF-SIMS studies on the causes of paint craters. Shown below are positive ion images for an automotive paint crater caused by a perfluorocarbon particle. Perfluorocarbons are characterized by C+, CF+, CF3+ and C3F5+, as well as other CxFy+.

  • imaging critical in finding tiny low-surface-energy particles causing paint craters.

Other agents causing paint cratering include silicones, fatty acids and detergents. The common property of those agents lies in their low surface energy, perhaps ranging in 20-25 mJ/m2. It is worth noting that silicones are also used as an ingredient in some paint systems to enhance their wettability. In this case, the same principle is used, that is, silicones are used to lower the surface tension (in unit mN/m, which is numerically equivalent to surface energy in unit mJ/m2) of the paint so that it can better wet a substrate that does not necessarily have a high surface energy. In fact, most plastics, if not derivatized for gaining a large surface energy, is characterized by a rather small surface energy, perhaps in the range of 25-35 mJ/m2. Paint craters form when the paint applied on the substrate to be painted cannot wet the spot due to its lower surface energy, which may be caused by the presence of a particle having a lower-than-the-substrate surface energy. Therefore, it is possible that aggregates of silicones in the paint system, as well as contamination by foreign silicones could both cause paint craters. Sometimes, one needs to figure out as which is the case (when silicone was found to cause the crater). In this case, comparisons of negative silicone ions at m/z 89 and 91 and at m/z 163 and 165, as described before , become quite helpful.

Automotive painting process (including primer, basecoat and clearcoat) occupies roughly one third of the cost for manufacturing vehicles. It is also believed that the appearance of affects customers' choice in purchasing cars. Paint cratering may lead to a shutdown of the production line. ToF-SIMS is the most useful technique in identifying the cause(s) of paint cratering, due to the fact that in many cases paint cratering is related to a tiny particle or an extremely thin layer of materials having a low surface energy. Detection of these defects demand the kind of surface sensitivity and chemical selectivity only ToF-SIMS can provide.

Differentiating fatty acids and their salts

Shown here is a composite image of Si+ (shown in blue), C16H33O2+ (green) and C16H33O2Na2+ (red). This image shows the excellent chemical selectivity of ToF-SIMS, that is, palmitic acid is differentiated from its salt (sodium palmitate) because when in the salt form, there is almost no C16H33O2+ detected. Of course, both the acid and its salt have abundant negative ion C16H31O2¯ (not shown). Thus, the chemical selectivity for this acid and its salt lies in the positive ions, rather than the negative counterpart. This also applies to other fatty acids and their salts. This observation may be explained by the fact that for a fatty acid to become a protonated molecular ion, it only needs to grab one hydrogen atom or proton. By contrast, for the salt of a fatty acid to become a protonated molecular ion, it has to grab two hydrogen atoms or protons. This ion formation process is obviously blocked by the presence of the cation (e.g., Na+). The ToF-SIMS results suggest that it is rather easier for the salt to grab one more cation to become a positive ion of the salt with an extra cation than to capture two hydrogen atoms or protons.

Phase separation

Phase separation of an antibiotic vancomycin and its polymeric matrix poly(lactide-co-glycolide) (PLGA) was observed when dimethyl sulfoxide (DMSO) was used as the solvent. The sample was made by placing the solution on a cleaved mica substrate. The phase separation is shown in the ion images of C7H4O2Cl¯ (at m/z 155, representing vancomycin) and C6H7O5¯ (representing PLGA). For the vancomycin molecule, C7H4O2Cl¯ is a diagnostic ion that is abundant and a structural entity of the molecule. It was also found that sulfur species were present in the vancomycin phase, suggesting that there might be an interaction between vancomycin and DMSO.

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Depth profiling

Metal oxides

Assisted with a sputter ion beam, ToF-SIMS can be used to depth profile both inorganic and organic materials. In practice, an area is sputtered for a pre-determined period followed by analyzing the newly generated surface within the sputtered area, which provides a data point in the depth profile. Repeating this sputter/analysis cycle until the desired depth is profiled. In most cases, the depth of the crater generated as a result of the depth profiling is measured using a profilometer (either a mecahnical stylus one or an optical one) so that the depth can be calibrated (otherwise the depth information is expressed by sputter time). The depth resolution can be as high as 1 nm. Shown below are an optical image (top left corner) of the crater after depth profiling and depth profiles (right) of a layered structure of ZnO/In2O3/Si using a 3 keV Cs+ sputter beam and a 25 keV Bi3+ analysis beam. The zinc oxide layer is expressed by ZnO¯, indium by InO¯ and silicon by Si¯, respectively. Also shown is a cross section image of the profiled depth. Note that the vertical dimension is for the profiled depth and the lateral dimension for the scanned area.

  • dual beam approach for depth profiling
  • depth resolution on the order of 1 nm
  • powerful for investigating deposited thin films and native oxide layers
Shown here are depth profiles for a structure of alternating layers of different oxides of metals M1, M2 and M3. Also shown are carbon and carbon related ions. A peak of carbon is seen in the middle of the film, suggesting increased carbon levels due to an interruption during the deposition process (i.e., accumulation of hydrocarbons in vacuum). Therefore, ToF-SIMS depth profiling is powerful in investigation the quality/integrity of layered structures.

Layered organics

Depth profiling organic materials often requires appropriate sputter ion beam that will not significantly degrade the molecules. C60+ is a good sputter beam for many organic materials. Vancomycin is used to showcase the ability of ToF-SIMS to perform three-dimensional molecular imaging. Shown below are the depth profiles of C7H4O2Cl¯and C3H3O3¯, representing vancomycin and PLGA, respectively. The ion intensities for a single depth are the sums of those over the scanned area. Since each pixel has a full spectrum over the scanned area for all probed depths, ToF-SIMS provides a three-dimensional distribution of chemical information. For example, shown on the right-hand side in the following figure is a cross section, i.e., an x - z plane cut from the profiled depth. Note that the vertical direction represents the depth (z, 290 nm) and its scale is different from the dimension (x, 200 μm) of the scanned area.

Quantifying cross-linking degrees of PMMA

An approach based on ToF-SIMS was developed to determine the degree of cross-linking on the surface and its variations in a nanometer-scale depth of organic materials. ToF-SIMS is extremely surface sensitive and capable of depth profiling with the use of a sputter ion beam to remove controllable amounts of substance. Poly(methyl methacrylate) (PMMA) films spin-coated on a Si substrate were cross-linked using a recently developed, surface sensitive, hyperthermal hydrogen projectile bombardment technique. The ion intensity ratio between two ubiquitous hydrocarbon species C6H¯ and C4H¯ detected in ToF-SIMS, denoted as ρ, was used to assess the degree of cross-linking of the PMMA films. The cross-linking depth of the PMMA films was revealed by depth profiling ρ into the polymer films using the C60+ sputter beam. The control PMMA film spin-coated on a Si substrate was characterized by ρ=32% on its surface when using a 25 keV Bi3+ primary ion beam. This parameter on the PMMA films subjected to HHIC treatment for 10, 100 and 500 s increased to 45%, 56% and 65%, respectively. The depth profiles of ρ obtained using a 10 keV C60+ ion beam resembled an exponential decay, from which the cross-linking depth was estimated to be 3, 15 and 39 nm, respectively, for the three cross-linked PMMA films. As shown in panel (a) of the figure, the characteristic PMMA ion C4H5O2¯ indicates the variation of cross-linking degree of PMMA. Panel (b) shows that the ion intensity ratio ρ between C6H¯ to C4H¯ detected in ToF-SIMS provides a unique and simple means to assess the degree of cross-linking of the surface of PMMA films cross-linked by the surface sensitive hyperthermal hydrogen projectile bombardment technique. The ToF-SIMS approach is capable of depth profiling ultra thin organic films with nanometer resolutions.
  • opportunities to developing new analytical approaches
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Principal component analysis of CnH¯ ions

The rich chemical information provided by ToF-SIMS ion mass spectra lies in the form of fragmented ions, which often amount to hundreds, leading to the possibility of identifying chemicals and exploring surface chemistry. Facing such a daunting number of ions (i.e., variables) detected in ToF-SIMS, dimensionality reduction techniques such as principal component analysis (PCA), a multivariate data analysis method, have proven useful in revealing similarities or differences of ions in terms of the variability of their intensities and can be used to differentiate a polymer with different molecular weights or different polymers. The original variables (i.e., ions in the ToF-SIMS case) are transformed to a much smaller number of new orthogonal variables (i.e., PCs), which are linear combinations of the original variables. The PCs are transformed from the original data under the condition that the first PC accounts for as much of the variance in the original data as possible, with the following PCs picking up the remaining maximum variances subsequently. Although there are as many PCs as the original variables, one can discard the higher PCs without losing much information as the first two (or several) PCs explain the vast majority of the variance (thus dimensionality reduction). However, PCA represents only a mathematic transformation of the original data -- one still needs to figure out as what the first PCs capture, which is apparently data- or problem-oriented.

  • A dimensionality reduction technique, PCA offers visualization of clustering (or lack of it) among observations, contributions of variables to clustering and relationships among variables.

PCA allows one to compare numerous observations (data) over multiple variables in a biplot, which is constructed by a plot of the scores of the observations on two PCs (often the first two PCs) overlapped with a plot of loadings of the variables on the same two PCs. A biplot visualizes the similarities and differences among the multivariate observations, their relationships with the variables and the correlations between the variables. Shown in the biplot below is a covariance biplot for the scores of the observations as points and loadings of the variables as arrowed lines, both on PC1 and PC2, for polyethylene (PE), polypropylene (PP), polyisoprene (PIP) and polystyrene (PS). The PCA results were obtained from a data set of 39 observations for the four polymers against the 10 CnH¯ (n=1 to 10) ions, using the prcomp() function in the open source R language. The function is actually based on singular value decomposition , svd() function in R, returning scores of observations, loadings of variables and eigenvalues (i.e., variances of PCs). The score of an observation on a PC is the sum of the individual ion intensity of each variable multiplied by the loading of the corresponding variable on the PC. In other words, it is the projection of all the CnH¯ intensities of an observation on a PC, or how an observation is expressed as a single point on the PC axis. A score plot is used to determine similarities or differences among observations. The score plot in the figure shows that the four polymers are separated into four groups.

An arrowed line of a variable may be called a "variable vector", serving to point the direction of the variable in the PCs coordinates. The smaller an angle between two variable vectors of two CnH¯, the more similarly the two variables behave in terms of their variability in their ion intensities. In other words, two variables are positively or negatively correlated if the angle between their variable vectors is close to 0 or 180°, respectively. On the other hand, an angle close to 90° indicates that the two variables are not correlated at all. The loading plot in the figure shows clearly the similarities among C6H¯ to C10H¯ for their significant contributions to PC1. By contrast, the variable vectors of C2H¯ and C3H¯ point to (approximately) the opposite direction and with increased loadings on PC2. This indicates that the intensities of the two groups of ions vary in opposite directions, that is, when the ion intensities of one group measured on a polymer sample increase, those of the other group decrease.

  • PC1 captures the variability of "carbon density" of the four polymers.

Assisted by the PCA results, we confirmed that lower and higher "carbon density" polymers favor the formation of smaller (e.g., C2H¯ and C3H¯ and larger (i.e., C6H¯ to C10H¯) CnH¯, respectively. Moreover, we found that the variability of the C4H¯ intensity against different polymers is relatively small in comparison with other CnH¯ intensities. The PCA results shown in the figure verified our argument that with increased "carbon density", ion intensities of larger CnH¯ increase while those of smaller CnH¯ decrease. Therefore, it is the "carbon density" of polymers that dictates the variability of CnH¯ captured by PC1.

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Heng-Yong Nie

Surface Science Western
Department of Physics and Astronomy Western University

Last modified October 14, 2023
Since January 31, 2018 © Heng-Yong Nie