Mixing Roughness Information Research Articles

Deconvolution of high-resolution depth profiling data with sputtering induced roughness for reconstruction of nano-layer structure

In this paper, a deconvolution method is proposed to obtain the original nano-layer structure directly from measured high-resolution depth profiling data with sputtering induced roughness. This method combines the Mixing-Roughness-Information (MRI) depth resolution function and the Total Variation (TV)-Tikhonov regularization. The regularization parameter of α that influences strongly the error and stability of the deconvolution result is optimized based on the L-curve criterion by the simulated annealing algorithm. The simulation results show that this method can be used to effectively obtain the original nano-layer structure even if the depth profiling data contains noise and/or sputtering induced roughness. Subsequently, as an example, the original multilayer structure of 4 × Si(15 nm)/Al (15 nm) is obtained directly from measured AES depth profiling data and the obtained roughness values accordingly at the depths of the middle of the first Al sublayer and of the last Al sublayer agree well with the ones measured by AFM.

Restoration of the Initial In-Depth Distribution of an Element from a Profile Measured by SIMS

Some advantages of the roughness–mixing–recoil (RMR) implantation model over the popular mixing–roughness–information (MRI) depth model proposed by Hoffman and with the Dowsett response function describing the depth resolution function for depth-profiling analysis by secondary-ion mass spectrometry are briefly reviewed. The problem of delta-layer shifts relative to the initial position in the process of depth-profiling analysis is also examined in detail.

Deconvolution method for obtaining directly the original in-depth distribution of composition from measured sputter depth profile

A new method is proposed to determine the original in-depth distribution of composition directly by the deconvolution of measured depth profiling data using the MRI (Mixing-Roughness-Information) depth resolution function. To overcome the ill-conditioned problem that is often experienced in the deconvolution procedure, the regularization method and the TV-Tikhonov algorithm are employed. The method is applied for the case that the original depth-concentration distribution is either a smooth function or a square wave function and the corresponding arithmetic mean errors are determined accordingly. The noise effects from “measured” data on the deconvoluted profile are also quantitatively evaluated.

Preferential sputtering and mass conservation in AES and SIMS depth profiling

The preferential sputtering and the mass conservation upon AES and SIMS depth profiling have been evaluated quantitatively based on the Mixing-Roughness-Information (MRI) model. The simulation results demonstrated that (a) the preferential sputtering plays an important role in the reconstruction of the true concentration-depth profile; (b) the mass conservation is a nature consequence in SIMS depth profiling but it is not fulfilled in AES depth profiling; (c) the layer thickness can be determined by applying the mass conservation law in AES depth profiling if the atoms preferentially sputtered out from the mixing zone are taken into account.

Reconstruction of GaAs/AlAs supperlattice multilayer structure by quantification of AES and SIMS sputter depth profiles

The GaAs/AlAs superlattice multilayer structures were deposited on GaAs (100) substrates by molecular beam epitaxial (MBE) technique. The as-prepared samples were characterized respectively by Auger Electron Spectroscopy (AES) and Secondary Ion Mass Spectroscopy (SIMS) depth profiling techniques. The measured depth profiles were then fitted by the Mixing-Roughness-Information (MRI) model. The depth resolution values for both depth profiling techniques were evaluated quantitatively from the fitted MRI parameters and the as-prepared GaAs/AlAs multilayer structure was determined accordingly.

A new approach to express ToF SIMS depth profiling

We propose a new approach to express SIMS depth profiling on a TOF.SIMS‐5 time‐of‐flight mass spectrometer. The approach is based on the instrument capability to independently perform raster scans of sputter and probe ion beams. The probed area can be much smaller than the diameter of a sputter ion beam, like in the AES depth profiling method. This circumstance alleviates limitations on the sputter beam–raster size relation, which are critical in other types of SIMS, and enables analysis on a curved‐bottomed sputter crater. By considerably reducing the raster size, it is possible to increase the depth profiling speed by an order of magnitude without radically degrading the depth resolution. A technique is proposed for successive improvement of depth resolution through profile recovery with account for the developing curvature of the sputtered crater bottom in the probed area. Experimental study of the crater bottom form resulted in implementing a method to include contribution of the instrumental artifacts in a nonstationary depth resolution function within the Hofmann's mixing–roughness–information depth model. The real‐structure experiment has shown that the analysis technique combining reduction of a raster size with a successive nonstationary recovery ensures high speed of profiling at ~100 µm/h while maintaining the depth resolution of about 30 nm at a 5 µm depth. Copyright © 2015 John Wiley & Sons, Ltd.

Single and multiple profile fitting of AES and XPS intensity‐depth profiles for analysis of interdiffusion in thin films

Simultaneous fitting of independently measured sputter‐depth profiles of intensities of Auger electrons or photoelectrons from different Auger transitions (AES) or core levels (XPS) is shown to increase the reliability of the thus determined concentration‐depth profiles in diffusion‐annealed thin‐film systems, as compared with the usually applied single profile fitting. In this context, an extension of the Mixing‐Roughness‐Information (MRI) depth model is presented, which includes the concentration dependence of the MRI parameters for mixing and information depth, as well as of the backscattering correction factor and the sputter rate. The thus proposed procedure is applicable for diffusion lengths as small as a few nanometre and was applied to determine the concentration‐dependent self‐diffusion coefficients from measured AES and XPS sputter‐depth profiles recorded from diffusion‐annealed amorphous‐Si/polycrystalline Ge bilayers. Copyright © 2014 John Wiley & Sons, Ltd.

Sharp interfaces for diamond delta-doping and SIMS profile modelling

Boron delta-doping of diamond has appeared as a promising viable approach for the fabrication of high performance RF power transistors taking advantage of diamond properties. Here structures based on p−/p+/p− multilayers were synthesized on (100) HPHT Ib substrates using MPCVD. An original gas injector system was developed enabling to significantly improve the sharpness of both interfaces between p+ and p− layers with a good reproducibility. SIMS profiles recorded on the doping transients still demonstrate an asymmetry of the interface sharpness from 7nm/decade to 2nm/dec on the p−/p+ and the p+/p− interfaces, respectively. The observed differences are here explained and confirmed experimentally, and result from the combination of ion mixing with the effect of the surface roughness, thus limiting the SIMS resolution in depth. The Mixing Roughness Information (MRI) model then allows to evaluate the real value of the delta thickness achievable using this technique to 7nm and the negative and positive gradients to identical values, namely of 1.4nm/dec.

An analytical depth resolution function for the MRI model

The mixing roughness information depth model is frequently used for the quantification of sputter depth profiles. In general, the solution of the convolution integral for any kind of in‐depth distributions is achieved by numerical methods. For a thin delta layer, an analytical depth resolution function is presented, which enables a simple and user‐friendly quantification of measured delta layer profiles in AES, XPS and SIMS. Copyright © 2013 John Wiley & Sons, Ltd.

Influence of non-Gaussian roughness on sputter depth profiles

Surface/interface roughness has a significant influence on the shape of the depth profile measured by any depth profiling technique. Such an influence is particularly significant for thin delta layers and at sharp interfaces of single- and multilayers. In the mixing-roughness-information (MRI) model for quantification of measured depth profiles, the influence of roughness is usually taken into account by a Gaussian height distribution function (HDF). If the roughness cannot be represented by a Gaussian HDF, a non-Gaussian HDF has to be implemented into the MRI model. Deviations of simulated depth profiles using the MRI model with Gaussian and with several well-defined non-Gaussian HDFs are evaluated quantitatively. The results indicate that a realistic non-Gaussian HDF has to be taken into account if high accuracy in quantification of sputter depth profiles is required. Of particular importance is the case of a roughness given by an asymmetrical HDF. Application of an asymmetrical triangle height distribution function in the MRI model yields an excellent fit for the measured AES depth profiling data of a polycrystalline Al film.

Measuring the roughness of buried interfaces by sputter depth profiling

We report results of high-resolution sputter depth profiling of an alternating MgO/ZnO nanolayer stack grown by atomic layer deposition (ALD) of ≈5.5 nm per layer. We used an improved dual beam time-of-flight secondary ion mass spectrometer to measure 24Mg+ and 64Zn+ intensities as a function of sample depth. Analysis of depth profiles by the mixing–roughness–information model yields a 1.5 nm nanolayer interfacial roughness within the MgO/ZnO multilayer. This finding was cross-validated using specular x-ray reflectivity. Such an analysis further suggested that the 1.5 nm roughness corresponds to native/jig-sawed interfacial roughness rather than interfacial interdiffusion during the ALD growth.

Determination of Coated Substrate Roughness by Quantification of Measured Depth Profiles

The glow discharge optical emission spectroscopy (GDOES) depth profiles of zinc-coated copper substrates polished by different mesh size sandpapers are well fitted with the mixing-roughness-information (MRI) model. Based on the MRI fits, the copper substrate roughness parameters and the coating layer thickness values are extracted. Using the so-called 84% to 16% method, the depth resolution values of the measured GDOES depth profiles are obtained, thereby the respective roughness parameters are determined. The obtained zinc-coated copper substrate roughness values are correlated with the experimental measurements.

Quantification of N<sub>2</sub><sup>+</sup> Implanted AES Depth Profiling Data in Al

The nitrogen implanted profile in aluminum generated by 60keV N2+ bombardment is simulated numerically by the Stopping and Range of Ions in Matter (SRIM) program and is fitted analytically by the Schulz-Wittmaack expression. Taking the SRIM simulated profile as true concentration-depth profile of implanted nitrogen in aluminum matrix, the corresponding measured AES depth profiling data of implanted nitrogen are well fitted by the Mixing-Roughness-Information (MRI) model.

Extracting interdiffusion parameters from Ni/Cu thin films by means of profile reconstruction with the MRI model

AbstractThin film diffusion studies often involve a surface‐sensitive analysis technique combined with ion erosion to produce a depth profile of a sample. Such studies compare the depth profile of a reference sample to the depth profiles of samples that were annealed at different temperatures and times. The extent to which atoms of one layer diffuse into an adjacent layer, for a particular temperature and time, yields information on the diffusion process involved and allows quantification of the diffusion coefficient. The drawback to using an erosion‐type system is the effect of the incident ions on the surface being probed. The Mixing‐Roughness‐Information model attempts to compensate for this effect and is often employed as a means of quantification of measured depth profiles by means of profile reconstruction. Used in conjunction with Auger electron spectroscopy, the Mixing‐Roughness‐Information (MRI) model is a useful tool to reconstruct the ion erosion depth profiles as well as extracting interdiffusion parameters from these depth profiles. This study focuses on the extraction of the diffusion coefficient of Ni in Cu from Ni/Cu depth profiles obtained from ion erosion Auger electron spectroscopy. The resultant depth profiles were reconstructed with the MRI model. The diffusion coefficient for Ni diffusing in Cu was obtained from the MRI fit and it compared well to values available in literature. Copyright © 2010 John Wiley & Sons, Ltd.

Film thickness determining method of the silicon isotope superlattices by SIMS

It is becoming important to evaluate silicon self-diffusion with progress of a silicon semiconductor industry. In order to evaluate the self-diffusion of silicon, silicon isotope superlattices (SLs) is the only marker. For this reason, it is important to correctly evaluate a film thickness and a depth distribution of isotope SLs by secondary ion mass spectrometry (SIMS). As for film thickness, it is difficult to estimate the thicknesses correctly if the cycles of SLs are short. In this work, first, we report the determination of the film thickness for short-period SLs using mixing roughness-information (MRI) analysis to SIMS profile. Next, the uncertainty of the conventional method to determine the film thicknesses of SLs is determined. It was found that the conventional methods cannot correctly determine film thickness of short-period-isotope SLs where film thickness differs for every layer.

Factorial analysis of cluster-SIMS depth profiling using metal-cluster-complex ion beams

A Ir 4(CO) 7 + primary ion beam, at energies from 2.5 keV to 10 keV, was used to profile boron-delta layers in Si to investigate the influences of atomic mixing and surface roughness on the degradation of depth resolution. Factorial analyses using the mixing-roughness-information (MRI) model indicated that the influence of the mixing increased as beam energy was reduced below 5 keV in the case of oxygen flooding. It was confirmed that the magnitude of the MRI surface roughness was different from that of the AFM surface roughness. The discrepancy in the magnitude of roughness was examined by considering the difference in sputtering depth as well as the definition of the MRI surface roughness.

AES depth profiling with a tilted sample in front of a cylindrical mirror analyzer: quantification and profile shape changes according to an extension of the conventional MRI model

AbstractThe influence of the tilt angle of a sample in front of a cylindrical mirror analyzer (CMA) on AES depth profiles is calculated with the conventional mixing‐roughness‐information (MRI) depth model and an extended MRI model. While the conventional model works with an average electron escape depth value, the extended model takes into account the intensity from different segments along the azimuth angle corresponding to different escape depth values before summing up for the total, measured intensity. The deviation between both approaches is generally less than 4%, even for the worst case at 47.7° tilt angle. The shape of the profile is slightly different for both approaches. Because, for a CMA with coaxial gun, the sample tilt angle varies as the electron beam incidence angle, the influence of the latter has to be additionally taken into account for quantification of AES. In reasonable agreement with experimental results it is shown that above 45° the Auger peak intensity of Cu (914 eV) increases up to about a factor of two for an incidence angle of 85°. Copyright © 2006 John Wiley & Sons, Ltd.

Characterization of nanolayers by sputter depth profiling

Sputter depth profiling of nanostructures requires quantitative thin film analysis with high accuracy and with optimum resolution. More recently, powerful quantification models, such as the so-called mixing roughness information depth (MRI) model, have increased the accuracy of depth profiling to the sub-monolayer region. Using the MRI model, interdiffusion coefficients at nanolayer interfaces can be determined based on a mean diffusion path length of the order of 1 nm. After summarizing the progress to date, focus is on new developments with respect to experimental improvements such as ultra-low ion energy and glancing incidence, cluster ion sputtering, and improvements in theoretical modeling and quantification of nonlinearities with respect to the intensity scale and to the time scale of a depth profile, and the change of important quantification parameters such as electron escape depth in AES and XPS, mixing length and roughness during profiling, particularly when sputtering through interfaces. Today, the accuracy of quantification of sputter depth profiles of layered nanostructures is typically about 20% of a monolayer, or 0.06 nm on the elemental layer thickness scale.

Quantitative evaluation of contributions to interface broadening in metal/silicon multilayers

AbstractAuger electron spectroscopy (AES) depth profiling is a widely used technique to study buried interfaces in thin‐film structures. It involves a sputtering process that may cause topographical and compositional changes in the surface region of the ion‐bombarded sample. In order to reveal the original in‐depth elemental distribution, it is important to know the influence of the sputtering process.AES depth profiling of Si/Ti, Si/Ni, Si/Nb and Si/W layered structures was performed with 1 and 3 keV Ar+ ions at an incidence angle of 47°. The mixing–roughness–information depth (MRI) model was used to estimate different contributions to the interface broadening. A stronger broadening of the metal/Si interfaces than that of the Si/metal interfaces can be explained by ion bombardment induced roughening and mixing of metallic atoms with the silicon ones. Copyright © 2004 John Wiley & Sons, Ltd.

Sputter-depth profiling for thin-film analysis.

Following a brief historical background, the concepts and the present state of sputter-depth profiling for thin-film analysis are outlined. There are two main branches: either the removed matter (as in mass- or optical-spectroscopy-based secondary-ion mass spectrometry or glow-discharge optical emission spectroscopy), or the remaining surface (as in Auger electron spectroscopy and X-ray photoelectron spectroscopy) is characterized. These complementary methods show the same result if there is no preferential sputtering of a component. The common root of both is the fundamental ion-solid interaction. Understanding of how the latter influences the depth resolution has led to important improvements in experimental profiling conditions such as sample rotation and the use of low-energy ions at glancing incidence. Modern surface-analysis instruments can provide high-resolution depth profiles on the nanometre scale. Mathematical models of different sophistication were developed to allow deconvolution of the measured profile or quantification by reconstruction of the in-depth distribution of composition. For the latter purpose, the usefulness of the so-called mixing-roughness-information (MRI) depth model is outlined on several thin-film structures (e.g. AlAs/GaAs and Si/Ge), including its extension to quantification of sputter-depth profiles in layer structures with preferential sputtering of one component (Ta/Si). Using the MRI model, diffusion coefficients at interfaces as low as 10(-22) m(2) s(-1) can be determined. Fundamental limitations of sputter-depth profiling are mainly traced back to the stochastic nature of primary-particle energy transfer to the sputtered particle, promoting atomic mixing and the development of surface roughness. Owing to more sophisticated experimental methods, such as low-energy cluster ion bombardment, glancing ion incidence or 'backside' sputtering, these ultimate limitations can be reduced to the atomic monolayer scale.