Calculating Oxygen Content from Adventitious Carbon 1s Spectra

Adventitious carbon (AdC) is commonly detected in X-ray photoelectron spectroscopy (XPS) analyses of most samples. While AdC can be beneficial in some cases, such as for charge correction purposes during the analysis of insulators, its associated C–O functionalities can complicate the interpretation of O 1s spectra. Accurately accounting for AdC’s contribution within the O 1s spectrum is essential but challenging due to significant spectral overlap and poorly resolved components in the high-resolution O 1s spectrum.

Rather than assigning multiple components without clear physical meaning—potentially leading to misinterpretations—incorporating stoichiometry offers a more reliable approach to improving data accuracy. However, applying stoichiometry can be tedious and challenging, particularly for novice users.

A recently published article [1] describes an approximation to enhance oxygen spectra interpretation by estimating oxygen linked to AdC. This publication provides background information, key assumptions, and an easy-to-use Excel calculator to assist XPS researchers in analyzing their own O 1s spectra.

This approach is particularly useful for accurately quantifying survey spectra when AdC influence must be minimized and for modelling high-binding-energy components in the oxygen 1s spectrum. The latter example is important to many transition metal oxides which have overlapping hydroxide and/or defect oxide components in the same binding energy window. Detailed examples of these applications are presented and discussed in reference [1]. These types of calculations were originally introduced in [2].

This Excel based calculator (also available at supplementary material in [1]) takes information from the survey and high resolution carbon 1s spectra and determines the amount of oxygen that is present from adventitious carbon species. This amount can then be deducted from the overall oxygen concentration.
(Note: you must download the file to Excel to use it - it is locked in Google Docs).

XPS Reference Pages

This site contains information gained from decades of X-ray photoelectron spectroscopy (XPS) analyses of an enormous variety of samples analyzed at Surface Science Western laboratories located at the Western University (London, Ontario). Originally this site was designed as a place for students and our clients to access valuable tips and information. It has since been opened to all those interested in the XPS technique. Summaries of literature data, relevant references and unpublished data taken of well characterized standard samples are presented. Also curve-fitting tips, instrument set-up tips (specifically for the Kratos AXIS Supra, Ultra and Nova), and CasaXPS tips pertaining to questions we normally get from our students and clients, and other odd bits of information are presented.




The fine print:
Surface Science Western and the University of Western Ontario does not warranty any of the information shown at this site. Any use of this data in scientific publications or other forms should include referencing to the originally published data referenced herein.

Sulphur

Table 1. S 2p3/2 binding energies compiled from the NIST database [1] and other sources.



Notes: 2p3/2 - 2p1/2 doublet separation = 1.18eV, peaks constrained to a 2:1 area ratio (2p3/2 : 2p1/2), generally one sets both peaks to an equal FWHM for ease of use although in pure samples this may not be the case.

Smart et al. [9] and Pratt et al. [10] give an excellent overview of binding energy ranges for the study of mineral surfaces. These ranges can be used with other sulphur containing systems as well. Of particular interest is the assignment for polysulphides eg. (S4)2- = 162.0-163.0 eV, (S5)2- = 161.9 - 163.2 eV, (Sx)2-) = 163.7 eV. Surface species can also play a role in XPS, especially for in-situ fractured sulphide mineral species [11].

[a] Nesbitt et al. [12] give a value of 162.2 eV for the disulphide in arsenopyrite.
[b] A more detailed look at organic sulphur species can be found here.

In a recent paper from Sarah Harmer's group at Flinders University, synchrotron XPS is used to convincingly elucidate surface 3-coordinate, bulk and surface 4-coordinate and bulk 5-coordinate sulfur in the chalcogenide (Fe,Ni)9S8.  This work shows that sulfide coordination changes can be seen by XPS [13].

A Na2S2O3.5H2O (sodium thiosulphite cooled to -130C during analysis) reference sample gave S 2p3/2 peak positions of 162.1 eV and 168.1 eV for S*SO3 and SS*O3 moieties, respectively.

There is a lot of confusion in the literature when presenting the data for sulphur. Some papers mention S 2p when they really mean S 2p3/2, these are not interchangeable! Please remember to be specific about the exact peak you are referring to.  

A recent paper from Clark et al. [14] highlights how widespread the issue of erroneous peak fitting of S 2p is.  Section B within this paper is worth a look as it highlights some of the common errors that should be avoided, these include:
1) Lack of spin–orbit splitting. Doublets (2p3/2 and 2p1/2 peaks) in their appropriate 2:1 ratios, respectively, should be used to represent each chemical state in the material.
2) Inconsistent and widely varying peak widths/full widths at half maximum (FWHMs).
3) Questionable assignments of the peaks to chemical species or oxidation states.
4) Backgrounds that cut through and then extend above the data on the high and low binding energy sides of the peak envelopes. 
5) Relatively large range of peak binding energy positions or fit components that are assigned as the same chemical states and should have well defined positions.
6) Noisy spectra, insufficient S/N.

References:
[1] C.D. Wagner, A.V. Naumkin, A. Kraut-Vass, J.W. Allison, C.J. Powell, J.R.Jr. Rumble, NIST Standard Reference Database 20, Version 3.4 (web version) (http:/srdata.nist.gov/xps/) 2003.
[2][2] Z.E. Pettifer, J.S. Quinton, S.L. Harmer, Minerals Engineering, 184 (2022) 107666.
[3] A.N. Buckley, W.M. Skinner, S.L. Harmer, A. Pring, L-J. Fan, Geochimica et Cosmochimica Acta, 73 (2009) 4452-4467.
[4] A.N. Buckley, W.M. Skinner, S.L. Harmer, A. Pring, R.N. Lamb, L.J. Fan, Y. Yang, Canadian Journal of Chemistry, 85 (2007) 767- 781.
[5] S.L. Harmer, A.R. Pratt, H.W. Nesbitt, M.E. Fleet, Canadian Mineralogist, 43 (5) (2005) 1619-1630.
[6] M.E. Fleet, X. Liu, S.L. Harmer, H.W. Nesbitt, Surface Science, 584 (2005) 133-145.
[7] V.P. Zakaznova-Iakovleva, S.L. Harmer, H.W. Nesbitt, G.M. Bancroft, A.R. Pratt, R. Flemming, Surface Science, 600(2) (2006) 348-356.
[8] A.R. Pratt, H.W. Nesbitt, American Mineralogist, 85 (2000) 619-622.
[9] R.St.C. Smart, W.M. Skinner and A.R. Gerson, Surface and Interface Analysis, 28 (1999) 101-105.
[10] A.R. Pratt, I.J. Muir and H.W. Nesbitt, Geochimica et Cosmochimica Acta, 58 (2) (1994) 827-841.
[11] H.W. Nesbitt, M. Scaini, H. Hochst, G.M. Bancroft, A.G. Schaufuss and R. Szargan, American Mineralogist, 85 (2000) 850-857, 
[12] H.W. Nesbitt, I.J. Muir, A.R. Pratt, Geochimica et Cosmochimica Acta, 59 (9) (1995) 1773-1786,
[13] Z.E. Pettifer, J.S. Quinton, W.M. Skinner, S.L. Harmer, Applied Surface Science, 504 (2020) 144458. 
[14] B.M. Clark, G.H. Major, J.W. Pinder, D.E. Austin, D.R. Baer, M.C. Biesinger, C.D. Easton, S.L. Harmer, A. Herrera-Gomez, A.E. Hughes, W.M. Skinner, M.R. Linford, Journal of Vacuum Science and Technology A, 42 (2024) 063213.

Advanced Analysis of Indium

Analysing indium and indium-based compounds using X-ray Photoelectron Spectroscopy is challenging due to only slight shifts in the binding energies of the commonly used In 3d5/2 core line. A recent paper shares a comprehensive set of reference data for indium and its compounds, covering the In 3d, 3p, and 4d core lines, the In MNN Auger signal, as well as relevant counter ion signals [1]. Valuable tools, such as the modified Auger parameter and chemical state (Wagner) plots, which aid in differentiating indium species are also discussed.

Figure 1 and Table 1 present average literature values for the In 3d5/2 core line, highlighting both the average and standard deviations. These values illustrate the apparent challenge in distinguishing between various indium compounds. Factors like natural line widths, line shapes, and potential errors in charge correction add further complexity to accurate speciation.

Figure 1. Average In 3d5/2 literature values for indium compounds. 

Table 1. Average In 3d5/2 literature values for indium compounds.

Experimental data (Figure 2 and Table 2) presents a similar trend, underscoring that the In 3d5/2 core line alone is not enough to reliably distinguish between indium species. Notably, the In 3d5/2 core line of indium oxides shows variable asymmetry in line shape, which has led to differing interpretations in the literature. Some researchers attribute the high binding energy component to hydroxide or oxy-hydroxide species, while others suggest that it reflects electronic properties (screening effects). The current experiments [1] support the view that screening effects play an important role in this asymmetry. Excellent studies on these screening effects have been conducted by Körber [2] and Harvey [3].

Figure 2 In 3d spectra from [1].

Table 2. Experimental In 3d5/2 values from [1].

The In M4,5N4,5N4,5 transitions show a broader range of binding energy than the In 3d5/2 core level, making it better suited for accurate speciation, particularly by making use of the modified Auger parameter (Figure 3 and Table 3). In mixed-system analysis, i.e., a system containing multiple indium species, both the position and shape of the In M4,5N4,5N4,5 Auger electron signal can useful for speciation. Béchu and Fairley have provided an excellent discussion on the application of nonlinear and linear least-squares fitting methods to the In M4,5N4,5N4,5 signal, specifically for the oxidation of InSb [4]. Table 4 presents the fitting parameters needed to reproduce the M4,5N4,5N4,5 line shapes in order to fit complex experimental envelopes.

Figure 3. In MNN spectra for various indium compounds [1]. For reference, vertical lines indicating the kinetic energy (MNN) for metallic indium have been overlaid in each tile. Note that the additional signal present for InPO4 at 414.7 eV was due to Na contamination.

Table 3. In M4N4,5N4,5 and modified Auger parameter values [1]. 

Table 4. In MNN Auger peak fitting parameters [1].

Considering the information presented above, a comprehensive interpretation of XPS data involving indium and its compounds should involve a combination of the available data, including survey spectra (i.e., stoichiometry), the In 3d5/2 and In M4N4,5N4,5 Auger spectra, as well as the relevant counterion spectra (see [1]). For systems containing multiple indium compounds, the position and shape of the M4,5N4,5N4,5 transition can offer a more accurate approach than using the 3d5/2 core line alone.

References:
[1] J.D. Henderson, L.P. Pearson, H-Y. Nie, M.C. Biesinger, Surf. Interface Anal. 57 (2024) 81. https://doi.org/10.1002/sia.7356 
[2] C. Körber (et al.), Phys. Rev. B, 81 (2010) 165207
[3] S.P. Harvey (et al.), J. Phys. D Appl. Phys., 39 (2006) 3959.
[4] S. Béchu and N. Fairley, J. Vac. Sci. Technol. A, 42 (2024) 013202.

Iron

For the analysis of photoelectron spectra of relatively pure iron oxides, one can use peak shape and peak binding energy comparisons to standard compounds to derive oxide composition. McIntyre and Zetaruk’s [1] paper is widely cited and is still an excellent starting point for qualitative iron oxide determination. Pratt et al. [2] used a series of multiplet peaks to curve fit oxidized iron sulfide (pyrrhotite) surfaces.

Grosvenor et al.[3] fitted the various iron oxide, hydroxide and halide peak shapes with a close approximation of the Gupta and Sen[4] multiplet structure. Multiplet FWHM, splittings and weightings are presented. An analysis of satellite to main peak separation is also given. All Fe(II) (high spin only as low spin Fe(II) does not exhibit multiplet splitting) and Fe(III) species can be fitted with Gupta and Sen multiplet structure. Variation in peak spacing and intensity occur for different ligands. Broad satellite peaks of varying intensities at binding energies above the main Fe 2p3/2 structure are present in the spectra for all high spin compounds. However paper [3] only presents the main multiplet lines, excluding the details needed to fit the broader higher binding energy satellite structures.

Table 1 [5] presents full fitting parameters including the multiplet and satellite structure. FWHM values are reported for 10 eV pass energy only. To accommodate lower resolution settings slightly broader peaks would be necessary for best fit values. For these fits a Shirley background encompassing only the 2p3/2 portion of the spectrum is used. Also included in this Table are new spectral fitting parameters for FeCr2O4 and NiFe2O4, species that are important for the examination of oxide films on Fe-Cr-Ni alloys, as well as data for new analyses of α-Fe2O3 and γ-Fe2O3[5]. Fitting parameters for FeCO3, which has been noted in certain corrosion products, are also presented in Table 1. These analyses were collected from a mineral sample of siderite (cleaved in vacuum). Carbon 1s binding energy for FeCO3 is at 290.1 eV. The many spectra are best viewed in the original papers - see links in reference section.

New! Modified/updated fitting parameters for FeO, FeOOH and Fe3O4 are now included in Table 1 from work presented in reference [6]. In particular the analysis and fitting of FeO is improved substantially as the new FeO standard, sputter cleaned with a GCIS (not available during the original work in [3,5]), is free of low levels of surface Fe2O3/Fe3O4 contamination.


Table 1. Fe 2p3/2 spectral fitting parameters: binding energy (eV), percentage of total area, FWHM value (eV) and spectral component separation (eV) [5,6].

While these values [5] and reference spectra [1,3,5] will be useful for identification of pure oxide or oxy-hydroxide species, curve fitting of mixed systems quickly becomes complicated due to spectral overlaps. For example, it can be seen that various Fe(III) compounds have a similar range of Fe 2p binding energies and vary mostly in peak shape and satellite intensities. Any attempt at fitting two or more Fe(III) species to a spectrum will consequently contain an inherent degree of error. As well, overlap of the Fe(III) satellite structure with the Fe(0) and Fe(II) Fe 2p1/2 portion of the spectrum will result in setting the higher binding energy background endpoint placement at a point that will not cover the satellite structure of the Fe(III) species. This will require any fitting of mixed chemical state systems containing Fe(III) species to omit the higher binding energy Fe(III) satellite (e.g. Fe2O3, FeOOH) from the envelope of peaks. This will again increase the error associated with the curve fitting.  Finally, determination of the Fe species present, especially in a mix of Fe(III) species, should include corroborating evidence from O 1s analysis and even other analytical techniques such as Raman spectroscopy or, for thin crystalline films, grazing angle XRD. Some examples of fittings in mixed species samples are presented in [5].

Compared to the other transition metal species, the complex multiple species fitting of Fe is the most problematic. With so many possible species having overlapping binding energies erroneous interpretation can result. A sample with two distinct species can likely be fitted accurately, three species much less so, while four or more species must be looked at as indicative but unreliable. 

New! Recent work [6,7] has demonstrated the utility of these methodologies, with extremely good chemical state speciation achieved for oxide/hydroxide mixtures.  For metal/oxide/hydroxide mixtures, good success was found for low levels of metal content.  As the amount of metal grows (particularly above 25%) the amount of Fe(II) species tends to be underestimated. Results from the original curve-fittings from [5] were improved, particularly for FeO.  This work again emphasizes that the better the pure compound spectrum is, the better the final curve-fitting results!

References:
[1] N.S. McIntyre, D.G. Zetaruk, Anal. Chem. 49 (1977) 1521.
[2] A.R. Pratt, I.J. Muir, H.W. Nesbitt, Geochim. Cosmochim. Acta 58 (1994) 827.
[3] A.P. Grosvenor, B.A. Kobe, M.C. Biesinger, N.S. McIntyre, Surf. Interface Anal. 36 (2004) 1564.
[4] R.P. Gupta, S.K. Sen, Phys Rev. B 12 (1975) 15.
[5] M.C. Biesinger, B.P. Payne, A.P. Grosvenor, L.W.M. Lau, A.R. Gerson, R.St.C. Smart, Appl. Surf. Sci. 257 (2011) 2717.
[6] A.E. Hughes, C.D. Easton, T.R. Gengenbach, M.C. Biesinger, M. Laleh, (2024) JVST A, 42 (2024) 053205.
[7] A.E. Hughes, C.D. Easton, T.R. Gengenbach, M.C. Biesinger, M. Laleh, (2024) JVST A, 42 (2024) 053206.

What is Adventitious Carbon?

A thin layer of carbonaceous material is usually found on the surface of most air exposed samples, this layer is generally known as adventitious carbon. Even small exposures to atmosphere can produce these films. Adventitious carbon is generally comprised of a variety of (relatively short chain [1]) hydrocarbons species with small amounts of both singly and doubly bound oxygen functionality. The source of this carbon has been debated over the years. It does not appear to be graphitic in nature and in most modern high vacuum systems vacuum oils are not readily present (as they have been in the past) [1,2,3,4]. There may be some evidence that CO or CO2 species may play a role in the gradual appearance of carbon on pristine surfaces within the vacuum of the XPS chamber [3].

It’s presence on insulating surfaces provides for a convenient charge reference by setting the main line of the C 1s spectrum to 284.8 eV (although values ranging from 285.0 eV to 284.5 eV have been used in some cases, remember to check for this value when looking for binding energy references in the literature). The error in this value (284.8 eV) is, for most systems, on the order of +/-0.2 eV to 0.3 eV.  An in-depth look at the effectiveness of using AdC for charge correction purposes, including standardized fitting procedures, is presented in [5].
  
Work by Grey et al. [6] has explored the nature of adventitious carbon by XPS and time-of-flight secondary ion mass spectrometry (ToF-SIMS).  XPS D-parameter and ToF-SIMS analyses confirms that AdC is not graphitic in nature. An average C 1s spectrum for AdC (Figure 1, Table 1) was derived and shows that, on average, ~ 25 % of the carbon species in AdC is directly associated with oxygen functionality.  Similarly, ToF-SIMS analyses show that AdC is comprised of mainly short chain hydrocarbons with some oxygen functionality.

An advanced method for curve-fitting of the C 1s envelope for AdC (Table 2) was developed that included the effects of beta carbons (in this context, the alpha carbon is the carbon directly attached to the oxygen, and the beta carbon is attached to the alpha carbon) and were informed by the configurations of possible volatile organic compounds (VOC) that are the source of most AdC [6]. Using this method in combination with the dataset from [5], the average C–C/C–H AdC aliphatic peak position was shown to be 284.81 eV (+/- 0.25 eV) via verification with a secondary internal reference.

Figure 1. Average of 80 adventitious carbon C 1s XPS spectra.

Table 1. Average adventitious carbon C 1s fitting parameters from an average of 80 AdC spectra.

Table 2. Curve-fitting parameters for AdC C 1s including shifted beta peaks (*) (peaks E, F and G). Areas for peaks A, B, C, and D should be left unconstrained. # If peak-shape for peak D is well-defined the FWHM constraint can be removed.
References:
[1] T.L. Barr, S. Seal, J. Vac. Sci. Technol. A 13(3) (1995) 1239.
[2] P. Swift, Surf. Interface Anal. 4 (1982) 47.
[3] D.J. Miller, M.C. Biesinger, N.S. McIntyre, Surf. Interface Anal. 33 (2002) 299.
[4] H. Piao, N.S. McIntyre, Surf. Interface Anal. 33 (2002) 591.

Using Adventitious Carbon for Charge Correcting


The C 1s spectrum for adventitious carbon can be fit as follows.  A single peak, ascribed to alkyl type carbon (C-C, C-H), is fit to the main peak of the C 1s spectrum.  A second peak is added that is constrained to be 1.5 eV above the main peak, of equal FWHM to the main peak (C-C, C-H). This higher binding energy peak is ascribed to alcohol and/or ester functionality (C-OH, C-O-C). Further high binding energy components can be added if required. For example: C=O at approximately 3 eV above the main peak and O-C=O at 3.8 to 4.3 eV above the main peak. One or both of these peaks may also have to be constrained to the FWHM of the main peak if they are poorly resolved.  Reference [1] and the table below outline standard starting fitting parameters for adventitious carbon. 
Adventitious carbon C 1s curve-fitting parameters [1].
Spectra from insulating samples can then be charge corrected by shifting all peaks to the adventitious C 1s spectral component (C-C, C-H) binding energy set to 284.8 eV. There is certainly error associated with this assignment. Swift [2] lists a number of studies showing errors ranging from ±0.1eV to ±0.4 eV.  “Newer” studies (late 1970's) range from ±0.1 to ±0.3 eV. “Older” studies (late 1960's to early 1970's) were in the ±0.4eV range - however, reproducibility and resolution of the spectrometers of the time may have played a role.  Barr's [3] work from 1995 states that error in using adventitious carbon is ±0.2 eV.  Our work [4] in 2002 also suggests error in the ±0.2eV to  ±0.3eV range.  Experience with numerous conducting samples (1995 to present) and a routinely calibrated instrument have shown that the C 1s signal generally ranges from 284.7 eV to as high as 285.2 eV [5].  Reference [1] presents a detailed assessment of the analysis of insulating samples from a multi-user facility from over a 5-year period that showed an adventitious C 1s (C-C, C-H) binding of 284.91 eV ±0.25eV.  A similar study confirming the utility of the adventitious carbon technique with a similar multi-user facility analysis has been published by Morgan [6].

For organic systems, especially polymers, it is convenient to charge correct to the C-C, C-H signal set to 285.0 eV. This makes for easier comparison to the polymer handbook [7] which uses this number for charge correction.

References:
[1] M.C. Biesinger, Appl. Surf. Sci, 597 (2022) 153681.
[2] T.L. Barr, S. Seal, J. Vac. Sci. Technol. A 13(3) (1995) 1239.
[3] P. Swift, Surf. Interface Anal. 4 (1982) 47.
[4] D.J. Miller, M.C. Biesinger, N.S. McIntyre, Surf. Interface Anal. 33 (2002) 299.
[5] M.C. Biesinger, unpublished results
[6] D.J. Morgan, Surf. Interface Anal. (2024) https://doi.org/10.1002/sia.7360. 
[7] G. Beamson, D. Briggs, High Resolution XPS of Organic Polymers - The Scienta ESCA300 Database Wiley Interscience, 1992.

Graphitic/Graphene/Carbon Nanotube C 1s Curve-Fitting

Materials of a graphitic nature (e.g., graphite, graphene, carbon nanotubes etc.) will have a C 1s main peak, attributed to C=C, which can be used as a charge reference set to 284.5 eV. An average of values for graphite from 21 references from the NIST database [1] is 284.46 eV with a standard deviation of 0.14 eV. Note that the well characterized value of 284.5 eV for graphitic carbon is also a strong indicator that this value is not appropriate as a value to use for AdC charge referencing. While these types of samples are generally conductive and if they can be mounted in a manor (in electrical contact with the sample stage) to take advantage of this one should do so. However, many of these types of samples come as a small volume of powders or flakes which are very difficult to mount. Usually, we mount these on a double-sided adhesive which works well but electrically isolates the sample. Oxidation of these types of samples (e.g., graphene oxide) or their functionalization (e.g., functionalized CNTs) can result in them behaving less conductively or as a mixed conductive/insulating material.  Samples where these materials are mixed with other conducting or insulating compounds can also result in a mixed conductive/insulating sample. For most of these types of samples we now electrically isolate the sample and charge reference to C 1s at 284.5 eV for the graphitic (C=C) peak.[2]

Table 1 from [2] presents general fitting parameters for graphitic, graphene and carbon nanotube type materials. These starting fitting parameters include the main peak asymmetry (defined using an asymmetric Lorentzian (LA) line shape) and π to π* shake-up satellite from a pure graphite standard sample. These fitting parameters are similar to the approach taken by Morgan (Fig. 5, Table 2) [3],  Moeini et al. (Table 1) [4],  and Gengenbach et al.[5]  It is always best to run your own standard (pure graphite, graphene, CNT etc.) to get fitting parameters appropriate for your sample type, instrument and conditions used. Slight differences in the main peak asymmetry and differing shake-up satellite position, shape and intensities are possible for differing classes of graphitic materials. See for example from Morgan[3] where HOPG and nano-onion C 1s spectra show peak-shape differences, likely due to hydrogenation of the sample. However, with this caveat stated, the parameters used based on a graphite standard have worked very well for variety of samples (134) analyzed in the five-year data survey from [2]. Figure 1(A) presents the standard graphite spectrum used to obtain the parameters presented in Table 1. The spectra from Figure 1(B, C and D) show the use of these fitting parameters from Table 1 to effectively model a variety of graphitic component containing materials. 


Table 1. General fitting parameters for graphitic/graphene/carbon nanotube type materials. #Line-shape details for CasaXPS. Define asymmetric peak-shape in other software using pure graphite/graphene or CNT sample related your specimens. ##Gaussian/Lorentzian product formula, GL(30) is 30% Lorentzian 70% Gaussian.[2]


Figure 1.  Examples of curve-fitting of graphitic type systems using the parameters from Table 1.  A) pure graphite, B) carbon nanotube-based material modified in caustic solution, C) oxidized graphene and D) acid modified graphene and organic compound mixture.[2]

References:
[1] C.D. Wagner, A.V. Naumkin, A. Kraut-Vass, J.W. Allison, C.J. Powell, J.R.Jr. Rumble, NIST Standard Reference Database 20, Version 3.4 (web version) (http:/srdata.nist.gov/xps/) 2003.
[2] M.C. Biesinger, Appl. Surf. Sci. 597 (2022) 153681.
[3] D.J. Morgan, J. Carbon. Res. 7 (2021) 51.
[4] B. Moeini, M.R. Linford, N. Fairley, A. Barlow, P. Cumpson, D. Morgan, V. Fernandez, J. Baltrusaitis. Surf. Interface Anal. 54 (2022) 67.
[5] T.R. Gengenbach, G.H. Major, M.R. Linford, C.D. Easton, J. Vac. Sci. Technol. A, 39 (2021) 013204.