Time-of-flight Secondary Ion Mass Spectrometry Depth Profile Research Articles

Analyzing 3D hyperspectral TOF-SIMS depth profile data using self-organizing map-relational perspective mapping.

The advantages of applying multivariate analysis to mass spectrometry imaging (MSI) data have been thoroughly demonstrated in recent decades. The identification and visualization of complex relationships between pixels in a hyperspectral data set can provide unique insights into the underlying surface chemistry. It is now recognized that most MSI data contain nonlinear relationships, which has led to increased application of machine learning approaches. Previously, we exemplified the use of the self-organizing map (SOM), a type of artificial neural network, for analyzing time-of-flight secondary ion mass spectrometry (TOF-SIMS) hyperspectral images. Recently, we developed a novel methodology, SOM-relational perspective mapping (RPM), which incorporates the algorithm RPM to improve visualization of the SOM for 2D TOF-SIMS images. Here, we use SOM-RPM to characterize and interpret 3D TOF-SIMS depth profile data, voxel-by-voxel. An organic Irganox™ multilayer standard sample was depth profiled using TOF-SIMS, and SOM-RPM was used to create 3D similarity maps of the depth-profiled sample, in which the mass spectral similarity of individual voxels is modeled with color similarity. We used this similarity map to segment the data into spatial features, demonstrating that the unsupervised method meaningfully differentiated between Irganox-3114 and Irganox-1010 nanometer-thin multilayer films. The method also identified unique clusters at the surface associated with environmental exposure and sample degradation. Key fragment ions characteristic of each cluster were identified, tying clusters to their underlying chemistries. SOM-RPM has the demonstrable ability to reduce vast data sets to simple 3D visualizations that can be used for clustering data and visualizing the complex relationships within.

Time-of-flight secondary ion mass spectrometry analysis of hair samples using unsupervised artificial neural network.

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) is extensively employed for the structural analysis of the outermost surfaces of organic materials, including biological materials, because it provides detailed compositional information and enables high-spatial-resolution chemical mapping. In this study, a combination of TOF-SIMS and data analysis was employed to evaluate biological materials composed of numerous proteins, including unknown ones. To interpret complicated TOF-SIMS data of human hair, an autoencoder, a dimensionality reduction method based on artificial neural networks, was applied. Autoencoders can be used to perform nonlinear analysis; therefore, they are more suitable than principal component analysis (PCA) for analyzing TOF-SIMS data, which are influenced by the matrix effect. As a model sample data, the TOF-SIMS depth profile of human hair, acquired via argon gas cluster ion beam sputtering and Bi3 2+ primary ion beam, was employed. Useful information, including the characteristic distributions of amino acids and permeated surfactants on the outermost surface of the hair, was extracted from the results obtained from the autoencoder. Furthermore, the autoencoder extracted more detailed features than did PCA. Therefore, autoencoders can become a powerful tool for TOF-SIMS data analysis.

Surface chemistry of Pb-activated sphalerite

Activation of sphalerite flotation by lead ions (Pb) is an important aspect of selective separation of sphalerite and galena, but its molecular mechanism remains poorly understood. In this paper, the surface chemistry of sphalerite in the Pb activation process at pHs 4 and 9 was investigated using inductively coupled plasma-atomic mission spectrometry (ICP-AES), time of flight secondary ion mass spectrometry (ToF-SIMS) and X-ray photoelectron spectroscopy (XPS). ICP results showed that the ion exchange ratio of Pb:Zn is not 1:1 during the activation at both acidic and alkaline pHs, indicating multiple adsorption mechanisms. ToF-SIMS results showed that three kinds of Pb secondary ion fragments, i.e., Pb+, PbOH+ and PbS+ were determined on the Pb-activated sphalerite surface, which provided direct evidence for the possible mixed activation mechanisms. In addition, ToF-SIMS depth profile results exposed that the Pb species not only distribute on the outermost sphalerite surface but also diffuse into the crystal structure of the mineral. XPS studies revealed the formation of PbS and PbSO3 at pH 4 and PbS, PbO with Pb(OH)2 at pH 9. It was also revealed that Pb uptake was higher at pH 9 than pH 4. Furthermore, XPS depth profile results showed the formation of PbSO3, Pb(OH)2 and PbO have not exceeded 2 nm depth, representing chemical bonding on the mineral surface, while PbS diffusion took place down to around 10 nm depth through ion exchange mechanism. All these details have established that the activation of sphalerite by Pb involves a mixed activation mechanism of ion exchange and Pb-oxide as activating sites. The PbS species formed by the ion exchange not only distribute on the outermost layer of sphalerite surface but also penetrate the surface and diffuse into the bulkphase of sphalerite.

A perspective on two chemometrics tools: PCA and MCR, and introduction of a new one: Pattern recognition entropy (PRE), as applied to XPS and ToF-SIMS depth profiles of organic and inorganic materials

X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) are much used analytical techniques that provide information about the outermost atomic and molecular layers of materials. In this work, we discuss the application of multivariate spectral techniques, including principal component analysis (PCA) and multivariate curve resolution (MCR), to the analysis of XPS and ToF-SIMS depth profiles. Multivariate analyses often provide insight into data sets that is not easily obtained in a univariate fashion. Pattern recognition entropy (PRE), which has its roots in Shannon’s information theory, is also introduced. This approach is not the same as the mutual information/entropy approaches sometimes used in data processing. A discussion of the theory of each technique is presented. PCA, MCR, and PRE are applied to four different data sets obtained from: a ToF-SIMS depth profile through ca. 100 nm of plasma polymerized C3F6 on Si, a ToF-SIMS depth profile through ca. 100 nm of plasma polymerized PNIPAM (poly (N-isopropylacrylamide)) on Si, an XPS depth profile through a film of SiO2 on Si, and an XPS depth profile through a film of Ta2O5 on Ta. PCA, MCR, and PRE reveal the presence of interfaces in the films, and often indicate that the first few scans in the depth profiles are different from those that follow. PRE and backward difference PRE provide this information in a straightforward fashion. Rises in the PRE signals at interfaces suggest greater complexity to the corresponding spectra. Results from PCA, especially for the higher principal components, were sometimes difficult to understand. MCR analyses were generally more interpretable.

Evaluation of depth distribution and characterization of nanoscale Ta/Si multilayer thin film structures

A multilayer thin film structure of ten alternate Ta and Si layers with approximately 18nm thickness for the combined (Ta+Si) layer, was evaluated to explore the individual layer thickness and the interface mixing behavior using different surface characterization techniques like Time-of-Flight Secondary Ion Mass Spectrometry (TOFSIMS), X-ray Reflectometry (XRR) and Kelvin Probe Force Microscopy (KPFM). These results were compared with measurements performed earlier using cross section Transmission Electron Microscopy (TEM). The TOFSIMS depth profile results indicate the individual thickness of Si and Ta layers to be 8.1nm and 5.9nm respectively which are less than the corresponding actual thickness measured by cross section TEM as 10.5nm and 7.5nm. The difference in thickness measurement has been explained in the light of ion bombardment induced atomic mixing in the interface during sputter depth profiling. A scanning electron micrograph shows the actual crater and its edges created due to the sputtering including the multilayer for real view of the structure. The XRR observations however reveal better agreement with the cross section TEM data, both being non-destructive in nature. Attempts were made to characterize the multilayer using KPFM technique which clearly elucidated the grating type cross section of the structure.

Nanoindentation, TEM and ToF-SIMS studies of the tribological layer system of cylindrical roller thrust bearings lubricated with different oil additive formulations

The chemical composition and microstructure of reaction layers formed under the presence of lubricants with different wear and fatigue protection properties on cylindrical roller thrust bearings made of SAE 52100 (100Cr6) steel were analysed by transmission electron microscopy (TEM) and time-of-flight secondary ion mass spectrometry (ToF-SIMS). In the TEM investigations, thin cross-sections prepared by focused ion beam (FIB) techniques showed pores inside the reaction layers for the tribological systems lubricated with mineral oil. ToF-SIMS studies revealed that both the reaction and the tribomutation layers contain atomic incorporations of the oil additive formulations used. The nanomechanical properties of the different tribological layers were also analysed by static and dynamic nanoindentation. The results show that the nanomechanical properties vary strongly with the base oil and the specific additives and that these variations can also be correlated with the ToF-SIMS depth profile distributions. Our investigations reveal that wear protection not only relies on the lubricant-induced formation of a reaction layer, but even more on the properties of the combined protection layer system of a reaction layer and an underlying fine crystalline tribomutation layer. The properties of both parts of the tribological layer system are influenced by the lubricant additive formulation used.

Surface chemistry of II–VI semiconductor ZnSe studied by time of flight secondary ion mass spectrometry and x-ray photoelectron spectroscopy

The composition and chemical state of the native oxide of single-crystalline ZnSe and the effect of HCl (18.5%)/H2O wet etching have been studied by time of flight secondary ion mass spectrometry (TOF-SIMS) and x-ray photoelectron spectroscopy (XPS). TOF-SIMS depth profile measurements show that the oxide layer of ZnSe is removed by etching in this solution for one minute, followed by a subsequent one minute rinse in deionized H2O. XPS depth profile measurements of the untreated ZnSe surface show that Se oxide only exists at the topmost surface (within the top 10% of the oxide layer). The change of Zn Auger parameter with depth of the untreated ZnSe specimen indicates that the remaining oxygen is chemically associated to Zn. High resolution XPS measurements of the etched ZnSe show no detectable Se oxide at the surface. Meanwhile, the Zn Auger parameter is similar to that of the unetched ZnSe after its oxide layer being removed by Ar+ sputtering. Both experiments show longer wet etching times result in Zn deficiency and more Cl contamination at the sample surface.