The XPS peak intensity and its background of inelastically scattered electrons varies strongly with the depth distribution of atoms. This phenomenon is the basis for a widely used method for nano-structure analysis.¹ With the rapid increase in the application of XPS, there is a growing need for automated XPS analysis. To meet this demand, a modified simpler and less accurate algorithm, which however is suitable for automation was developed.² For each XPS peak, this algorithm determines just two numbers: the total amount of atoms within the outermost ~ 10 nm and the approximate depth of the atoms. The validity of the algorithm was demonstrated experimentally by comparison to more elaborate quantification methods.² The algorithm is thus of interest for automated XPS analysis. Another application of the algorithm is in XPS imaging, where thousands of spectra must be analyzed. Here automatic data-handling procedures are crucial. Software that can automatically analyze thousands of spectra corresponding to the situation in XPS imaging is now being developed. The method produces nondestructively a 3-D image of the surface with nanometer depth resolution. The practical applicability of this to XPS imaging was recently demonstrated.^3-4

In ref ³ the algorithms ability to produce images of Ag taken from a series of samples with increasing thicknesses of plasma patterned Octadiene (2, 4, 6 and 8nm) on Ag substrates was demonstrated. The obtained images of the amount of Ag atoms in the outermost few nano-meters were in good agreement with the nominal thicknesses. Produced images of atoms at different depths clearly proved the potentials of the method for quantitative and nondestructive 3-D characterization of nano-structures. Spectral noise is a major limitation in imaging because the time allowed to acquire the spectrum at each pixel is typically ~1 sec. Different procedures for noise reduction were studied in ref⁴ and principal component analysis (PCA) was found to significantly improve the 3D images of a thermally patterned oxidized silicon where detailed 3-D images of the Si, O, and C atoms were determined on the nano-meter depth scale.

In the talk we will summarize the technique and discuss its limitations and potentials for both automation of conventional XPS data analysis and for 3D XPS imaging.

¹ S. Tougaard, Surf. Interf. Anal. 26 (1998) 249

² S. Tougaard, J. Vac. Sci. Technol., A21 ( 2003) 1081; A23(2005) 741

³ S. Hajati, S. Coultas, C. Blomfield and S. Tougaard, Surf. Interf. Anal. 40 (2008) 688

Information about the layer structure of surfaces at the angstrom level can be probed through X-ray Photoelectron Spectroscopy (XPS) by analyzing the structure of the entire spectrum, including the inelastic background. Model samples were prepared through a unique magnetron sputtering system to create thin film gradients ranging from two angstroms to hundreds of angstroms thick across a distance of seven centimeters. The system studied consisted of a titania wedge on a gold substrate. The samples were characterized using Variable Angle Spectroscopic Ellipsometry (VASE) to measure the thickness of the wedge along the sample at many points along the gradient. The thickness values from the XPS and VASE modeling were shown to have excellent linearity from two angstroms until the XPS photoelectron peak was extinguished. The effective attenuation lengths of the titania at the kinetic energies of the various gold photoelectron peaks were also measured and compared to theoretical values for inelastic mean free path. The values were within 29% of each other.

The backscattering factor (BF) has long been recognized as an important matrix-correction factor for quantitative AES. The BF definition (“fractional increase in the Auger current due to backscattered electrons” [1]) has been shown to be unsatisfactory since the “fractional increase” can be negative at low primary energies and more grazing-incidence of the primary electrons [2]. ISO/TC 201 is considering the definition of a new term, the backscattering correction factor (BCF), as a “factor equal to the ratio of the total Auger-electron current arising from ionizations in the sample caused by both the primary electrons and the backscattered electrons to the Auger-electron current arising directly from the primary electrons.” NIST recently released a new BCF Database [3] for AES. This database provides BCFs from Monte Carlo simulations for two models, a simplified model based on the previous BF definition which is relatively rapid and an advanced model based on the proposed BCF definition which is more accurate but slower. BCFs can be determined for a solid of arbitrary composition, a user-specified instrumental configuration, and primary energies up to 30 keV.

Examples will be given of the dependence of the BCF for Pd M₅N₄₅N₄₅ Auger electrons on various instrumental conditions (primary energy, primary-beam angle of incidence (θ₀), and analyzer acceptance solid angle) [4]. BCFs calculated from the advanced model of electron transport in the surface region of the Pd sample varied weakly with analyzer half-cone angle for θ₀ = 0° but more strongly for θ₀ = 80° where there were BCF differences varying between 19% at a primary energy of 1 keV and 6% at a primary energy of 5 keV. These BCF differences are due partly to variations of the density of inner-shell ionizations within the information depth for the detected Auger electrons. The latter variations are responsible for differences larger than 10% between BCFs from the widely used simplified BCF model and those from the more accurate advanced model for primary energies less than about 5 keV for θ₀ = 80°. These and other BCF differences indicate that the simplified model can provide only approximate BCF values. In addition, the simplified model does not provide any BCF dependence on Auger-electron emission angle or analyzer acceptance angle. Comparisons will also be made with measured BCFs for elemental solids.

[1] ASTM E 673-03, “Standard Terminology Relating to Surface Analysis,” in Annual Book of ASTM Standards, Vol. 3.06, 2010, p. 655.

[2] A. Jablonski, Surf. Science 499, 219 (2002).

[3] http://www.nist.gov/srd/nist154.cfm .

[4] A. Jablonski and C. J. Powell, Surf. Science 604, 1928 (2010).

We have recently developed a technique for recording the shifts in the positions of the XPS peaks in response to different waveforms of electrical and/or optical stimuli for probing the dynamics of the developed electrical potentials originating from intrinsic or extrinsic (like doping) properties of semiconductive materials such as charging/discharging, photoconductivity, surface photovoltage, band-bending/flatting/inversion, etc.^1-6 We have also shown that fast data acquisition (in the snapshot mode) and laterally spatial resolved XPS analysis (an area mapping mode) helps us to compare and align extracted electrical behaviors and chemical information from the sample. For a better understanding of a realistic performance (or failure) of a device during operation, we have extended our measurements to a CdS based photoresistor, where we have mapped the position of the Cd3d peak over an area of 5 mm x 5mm while the device is under operation without and under photoillumination. This method allows us to detect defects and malfunctioning sites/domains. We will present our methodology with experimental results and an electrical circuit model.

(1) Sezen H., Suzer, S. Surface Science, 2010, 604, L59.

(2) Suzer, S., Sezen, H., Ertas, G., Dâna, A. Journal of Electron Spectroscopy and Related Phenomena 2010, 176, 52.

(3) Sezen, H., Ertas, G., Suzer, S. Journal of Electron Spectroscopy and Related Phenomena, 2010, 178-9, 373.

(4) Sezen H., Suzer, S. Journal of Vacuum Science and Technology A, 2010, 28, 639.

(5) Sezen, H., Ozbay, E., Aktas, O., Suzer, S. Applied Physics Letters 2011, 98, 111901.

(6) Sezen, H., Suzer, S. Journal of Spectroscopy and Dynamics (in press).

XPS has long been a primary technique for the analysis of material surfaces, providing quantitative analysis of elemental atomic concentrations and chemical bonding states. When combined with ion sputter etching, it has provided a similar level of detail in depth profiling of metals, semiconductors, and inorganic compounds; however, the damage produced by ion bombardment precluded the depth profiling of organic and polymeric specimens. More recently it has been shown that sputter etching by carbon cluster ions significantly reduces the apparent damage to such materials, presumably the result of a combination of a reduced damage layer thickness and efficient removal of the damaged material. In this work we have used a coronene (C₂₄H₁₂⁺) ion source to sputter etch a series of organic compounds and polymers, including trehalose, poly(amide), poly(glycolic acid), poly(lactic acid), poly(ethylene glycol), poly(methyl methacrylate), poly(acrylonitrile), poly(ethylene terephalate), poly(vinyl chloride), and poly(tetrafluoroethylene). Specimens were sputtered to a steady-state condition and analyzed by XPS. Elemental composition and chemical bonding were compared to the original surface and the theoretical values. These data will be used to refine our understanding of cluster ion bombardment effects in polymers, and to interpret data from the analysis of future materials and devices.

The traditional approach when employing XPS for this application has been to acquire a number of small area spectra at different points. The advent of quantitative parallel XPS imaging introduced the possibility of faster acquisition times and higher spatial resolution than the traditional small XPS probe approach.

Here we present an alternative approach whereby multiple features are simultaneously analysed over a large area using XPS imaging. Acquisition conditions and post acquisition data treatment to optimise this approach on a range of samples will be discussed

This approach provides both a faster and more easily interpreted graphical method for multiple feature analysis.

We present examples of this approach on a variety of samples.