On line shape analysis in X-ray photoelectron spectroscopy

The partial-intensity approach for simulating electron scattering is outlined, and relevant algorithms that were introduced in the past decade are presented. This is important for understanding the signal generation and surface sensitivity for a wide variety of techniques such as X-ray photoelectron spectroscopy (XPS), Auger electron spectroscopy (AES), Auger-photoelectron coincidence spectroscopy (APECS), elastic peak electron spectroscopy (EPES), reflection electron energy loss spectroscopy (REELS), electron probe microanalysis (EPMA), total electron yield (TEY) and the like. In particular, the so-called trajectory-reversal algorithm is discussed, both for emission problems (relevant for XPS, AES, and APECS) as well as for reflection problems (relevant for EPES and REELS), as this algorithm allows one to achieve enhanced efficiencies in simulations of many orders of magnitude compared to a conventional simulation. It is then shown that the simulation of the partial intensities (i.e. the number of n-fold inelastically scattered electrons) is not only useful for simulation of model spectra but is also essential for truly quantitative interpretation of experimental spectra. Finally, the stochastic process for multiple scattering beyond the constant cross-section approximation is treated. Using the generalized stochastic process, the above approaches can be extended to techniques such as EPMA, TEY and the like in a straightforward way. Illustrative examples are given for the topics mentioned above.

“…This difference can also be clearly distinguished in the experimental data shown in Fig. 6, 26 both for the 4f and the 4d peak (upper curves). Using the proper partial intensities (Fig.…”

Section: X-ray Photoelectron Spectroscopy (Xps)mentioning

confidence: 68%

Simulation of electron spectra for surface analysis using the partial‐intensity approach (PIA)

Werner

2005

“…26 The bulk density value D 3.58 g/cm 3 for MgO and 3.99 g/cm 3 for Al 2 O 3 are indicated in Ref. 23.…”

Section: Spectrometers and The Samplesmentioning

confidence: 99%

“…It affects the inelastic mean free path (IMFP) of electrons, 1 determined by elastic peak electron spectroscopy (EPES). 2 Surface losses reduce the intensity of the photoelectron and Auger electron, 3 and of the elastic peak as well. 2,4 They affect reflection electron energy loss (REELS) spectra.…”

Section: Introductionmentioning

confidence: 99%

Experimental determination of the inelastic mean free path (IMFP) of electrons in selected oxide films applying surface excitation correction

Gurban

Gergely

Tóth

et al. 2006

The inelastic mean free path (IMFP) of electrons was determined using elastic peak electron spectroscopy (EPES) with Cu, Si, Ag, Ni and Au reference samples.Systematic differences occurred between the experimental and calculated (TPP-2M) (Tanuma, Powell, Penn) IMFPs, which can be ascribed partly to surface losses. The experimental IMFP was deduced from the integrated elastic peak ratio of the sample and the reference. Experiments were made with the ESA 31 (ATOMKI) and DESA 100 (Staib) electron spectrometers, and covered the E = 0.2-2 keV energy range. The results were evaluated applying Monte Carlo (MC) simulation based on the NIST SRD 64/3.1 database and using the EPESWIN software of Jablonski. The surface excitation correction (surface excitation parameter (SEP)) for SiO 2 , MgO and Al 2 O 3 was determined using our new procedure applying the model of Chen and Tanuma. This correction reduced the difference between uncorrected, experimentally determined and calculated IMFPs by nearly 50%, which proves the importance of the contribution of surface excitation. The oxide layers studied are insulators. Their surface potential was determined by the energy of the Auger peak. We observed an energy shift of 1-3 eV of the Auger peak positions due to charging. The SEP material parameter resulted in a ch = 1.2 for SiO 2 and a ch = 4 for MgO and Al 2 O 3 .

“…The total P set E of the sample is denoted by P ses E and by P ser E for the reference sample. Surface excitation reduces the intensity of the elastic peak, 2,5,6 (and the intensity of Auger and XPS peaks 9 ) by a factor exp P ses E and can affect the IMFP.…”

Section: Introductionmentioning

confidence: 99%

Experimental measurements of the surface excitation parameters of Cu, Au, Ni, Ag, Ge and Pd based on Si and other reference standard materials

Gergely

Menyhárd

Gurban

et al. 2004

Surface excitation in electron spectroscopy is characterized by the surface excitation parameter P se . In electron spectroscopy, the total surface excitation is observed for electrons impinging and reflected elastically (elastic peak electron spectroscopy, EPES) or for backscattered (REELS) electrons. Surface excitation reduces the intensity of the elastic peak and affects the REELS spectra. Experimental determination of the total P se from EPES spectra is made by measuring the ratio of integrated elastic peak intensities for the sample I ese and reference material I ere . This paper presents further development of Tanuma's work for this ratio. P ser of the reference was calculated with the formula and material parameters of Chen. Monte Carlo simulations were based on the NIST elastic scattering and Tanuma's IMFPs database for the reference samples. This work deals with Cu, Au, Ag, Ni and Pd metals and Ge, used also as standards for electron spectroscopy. Experiments were made with a high-energy resolution spectrometer (HSA), and with a DESA 100 spectrometer (Staib Ltd) with large solid angle for E = 0.2-2 keV. Surface excitation correction factors have been developed for the above metals and Ge, used for reference samples. Their application reduced the differences in IMFPs from Tanuma's values for the uncorrected rms errors 1l u (% values) to 1l c (corrected) data for Si/Ag (from 21.2 to 6.7%), for Si/Ni (11.4 to 9.8%), and for Si/Cu (13.5 to 5%). A similar improvement was found for Si/Au, Ag/Ni, Ag/Cu and Ag/Au experimental results, using surface excitation correction.