Fusion of 2-D SIMS Images Using the Wavelet Transform

 Secondary ion mass spectroscopy (SIMS) is a powerful method for element distribution examination of conducting and semi-conducting surfaces at high spatial resolution and with a high sensitivity. Routine surface analysis produces about 8 to 15 images in a short time, each of which displays the intensity distribution of one mass, thus generating a multispectral SIMS image. Formation of occlusions, segregations, and the overall location of the elements relative to each other, are difficult to recognise when looking at n separate 2-D images. Image fusion is a process whereby images obtained from various sensors, or at different moments of time, or under different conditions, are combined together to provide a more complete picture of the object under investigation. The process of combining SIMS images may be viewed as an attempt to compensate for the inherent effect of SIMS to channel the information obtained from the sample into different images, corresponding to different element phases. The wavelet transform is a powerful method for fusion of images. This work covers the use of wavelet based fusion algorithms on multispectral SIMS images, evaluating the performance of different wavelet based fusion rules on different type of image systems and comparing the results to conventional fusion techniques. An aim of this study is to increase the information, i.e. the number of masses, which can be merged into one image in order to enhance the perception and interpretation of the SIMS surface images.     

Denoising and multivariate analysis of time‐of‐flight SIMS images

Time‐of‐flight SIMS (ToF‐SIMS) imaging offers a modality for simultaneously visualizing the spatial distribution of different surface species. However, the utility of ToF‐SIMS datasets may be limited by their large size, degraded mass resolution and low ion counts per pixel. Through denoising and multivariate image analysis, regions of similar chemistries may be differentiated more readily in ToF‐SIMS image data. Three established denoising algorithms—down‐binning, boxcar and wavelet filtering—were applied to ToF‐SIMS images of different surface geometries and chemistries. The effect of these filters on the performance of principal component analysis (PCA) was evaluated in terms of the capture of important chemical image features in the principal component score images, the quality of the principal component score images and the ability of the principal components to explain the chemistries responsible for the image contrast. All filtering methods were found to improve the performance of PCA for all image datasets studied by improving capture of image features and producing principal component score images of higher quality than the unfiltered ion images. The loadings for filtered and unfiltered PCA models described the regions of chemical contrast by identifying peaks defining the regions of different surface chemistry. Down‐binning the images to increase pixel size and signal was the most effective technique to improve PCA performance. Copyright © 2003 John Wiley & Sons, Ltd.     

Extraction of hidden information of ToF‐SIMS data using different multivariate analyses

Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) is a powerful tool for determining surface information of complex systems such as polymers and biological materials. However, the interpretation of ToF‐SIMS raw data is often difficult. Multivariate analysis has become effective methods for the interpretation of ToF‐SIMS data. Some of multivariate analysis methods such as principal component analysis and multivariate curve resolution are useful for simplifying ToF‐SIMS data consisting of many components to that explained by a smaller number of components. In this study, the ToF‐SIMS data of four layers of three polymers was analyzed using these analysis methods. The information acquired by using each method was compared in terms of the spatial distribution of the polymers and identification. Moreover, in order to investigate the influence of surface contamination, the ToF‐SIMS data before and after Ar cluster ion beam sputtering was compared. As a result, materials in the sample of multiple components, including unknown contaminants, were distinguished. Copyright © 2014 John Wiley & Sons, Ltd.     

Mitigating dead‐time effects during multivariate analysis of ToF‐SIMS spectral images

ToF‐SIMS spectra are formed by bombarding a surface with a pulse of primary ions and detecting the resultant ionized surface species using a time‐of‐flight mass spectrometer. Typically, the detector is a time‐to‐digital converter. Once an ion is detected using such detectors, the detector becomes insensitive to the arrival of additional ions for a period termed as the (detector) dead‐time. Under commonly used ToF‐SIMS data acquisition conditions, the time interval over which ions arising from a single chemical species reach the detector is on the order of the detector dead‐time. Thus, only the first ion reaching the detector at any given mass is counted. The event registered by the data acquisition system, then, is the arrival of one or more ions at the detector. This behavior causes ToF‐SIMS data to violate, in the general case, the assumption of linear additivity that underlies many multivariate statistical analysis techniques. In this article, we show that high‐mass‐resolution ToF‐SIMS spectral‐image data follow a generalized linear model, and we propose a data transformation and scaling procedure that enables such data sets to be successfully analyzed using standard methods of multivariate image analysis. Copyright © 2008 John Wiley & Sons, Ltd.     

The accuracy and precision of the advanced Poisson dead‐time correction and its importance for multivariate analysis of high mass resolution ToF‐SIMS data

Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) data collected in single ion counting mode suffers from dead‐time effects that lead to potentially confusing artefacts when common multivariate analysis (MVA) methods are applied to the data. These artefacts can be eliminated by applying an advanced Poisson dead‐time correction that accounts for the signal intensity in the dead‐time window preceding each time channel. Because this correction is nonlinear, it changes the noise distribution in the data. In this work, the accuracy of this dead‐time correction and the noise characteristics of the corrected data have been analysed for spectra with small numbers of primary ion pulses. A simple but accurate equation for estimating the standard deviation in the advanced dead‐time corrected data has been developed. Based on these results, a scaling procedure to enable successful MVA of advanced dead‐time corrected ToF‐SIMS data has been developed. The improvements made possible by using the advanced dead‐time correction and our recommended scaling are presented for principal components analysis of a ToF‐SIMS image of aerosol particles on polytetrafluoroethylene. Recommendations are made for using the advanced dead time correction and scaling ToF‐SIMS data in order optimize the outcomes of MVA. Copyright © 2014 John Wiley & Sons, Ltd.     

A coded support for use in analysis of aerosols by different spectroscopic methods

A device used for localization of solid atmospheric microparticles on silicon wafers is described. Dimensions of the device are 5.04 mm × 5.0809 mm. This support facilitates the analysis by other instruments of particles previously located by scanning electron microscopy (SEM). The area of the wafer is divided into tables and cells identified by microlithographic alphanumeric characters. These characters are made of an alloy of aluminium, silicon and copper which can be visualized by imaging secondary-ion mass spectrometry (SIMS). The quality of the image produced by SIMS is worse than that obtained with SEM, mainly because of the bigger diameter of the SIMS ion beam, but the symbols and patterns used are still easily legible. Examples are given of images obtained from SEM, SIMS and secondary electron ion-induced microscopy (SEIIM).     

二次离子质谱生物成像

二次离子质谱作为目前空间分辨率最高的质谱成像技术,以其免标记、高灵敏、多组分检测优势和亚微米级高空间分辨成像优势为诸多生命科学问题的研究提供了全新的分析手段,在基础细胞生物学、组织生理病理学、生物医药与临床医学等领域的研究中得到了广泛应用.本文综述了二次离子质谱在生物组织、细胞、仿生生物膜等体系中的质谱成像研究进展.     

How does soaking wood in various pH buffers impact ToF‐SIMS spectra?

During the production of biofuels and/or bioproducts, wood and other lignocellulosic materials are frequently exposed to buffers during enzyme treatments. Buffer pH varies according to the activity profiles of the enzyme(s) used. Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) is an increasingly valuable analytical tool for the surface analysis of lignocellulosic solids, allowing for characterization of the lignin and polysaccharides at the surface, along with other components such as protein and inorganic salts. Despite the use of ToF‐SIMS to characterize dilute acid and alkali pretreatments of wood, the exposure of wood to buffers of intermediate pH range has not been studied as it relates to ToF‐SIMS analysis. This leads to the question: “How does soaking wood in various pH buffers impact ToF‐SIMS spectra?” Accordingly, a softwood (spruce) and hardwood (birch) were soaked in universal buffers ranging from pH 5 to 10, and then positive ion ToF‐SIMS spectra were acquired from the washed wood. Deacetylation was evident for both wood species above pH 8. Additionally, at higher pH, birch ToF‐SIMS spectra revealed a relative loss in polysaccharide peaks attributed to hemicellulose and an increase in lignin peaks. This study provides a basis for understanding the pH‐dependent alteration of wood solids in aqueous solution, which is important for understanding the controls in enzyme treatments.     

Multivariate analysis of extremely large ToFSIMS imaging datasets by a rapid PCA method

Principal component analysis (PCA) and other multivariate analysis methods have been used increasingly to analyse and understand depth profiles in X‐ray photoelectron spectroscopy (XPS), Auger electron spectroscopy (AES) and secondary ion mass spectrometry (SIMS). These methods have proved equally useful in fundamental studies as in applied work where speed of interpretation is very valuable. Until now these methods have been difficult to apply to very large datasets such as spectra associated with 2D images or 3D depth‐profiles. Existing algorithms for computing PCA matrices have been either too slow or demanded more memory than is available on desktop PCs. This often forces analysts to ‘bin’ spectra on much more coarse a grid than they would like, perhaps even to unity mass bins even though much higher resolution is available, or select only part of an image for PCA analysis, even though PCA of the full data would be preferred. We apply the new ‘random vectors’ method of singular value decomposition proposed by Halko and co‐authors to time‐of‐flight (ToF)SIMS data for the first time. This increases the speed of calculation by a factor of several hundred, making PCA of these datasets practical on desktop PCs for the first time. For large images or 3D depth profiles we have implemented a version of this algorithm which minimises memory needs, so that even datasets too large to store in memory can be processed into PCA results on an ordinary PC with a few gigabytes of memory in a few hours. We present results from ToFSIMS imaging of a citrate crystal and a basalt rock sample, the largest of which is 134GB in file size corresponding to 67 111 mass values at each of 512 × 512 pixels. This was processed into 100 PCA components in six hours on a conventional Windows desktop PC. © 2015 The Authors. Surface and Interface Analysis published by John Wiley & Sons Ltd.     

SIMS depth profiling of vertical p-channel Si-MOS transistor structures

SIMS depth profiling during O₂ ⁺ bombardment has been performed to analyse epitaxially grown Si p-n-p layers, which define the p-channel region in vertical Si-p MOS transistors, as well as to establish “on-chip” depth profiling of the functional vertical device. The SIMS detection limit of ³¹P in Si, phosphorus used as n-type dopant in the transistor, has been optimised as a function of the residual gas pressure in the SIMS analysis chamber and of the sputter erosion rate. We demonstrate that good vacuum during SIMS analysis combined with high erosion rates allows the simultaneous quantitative SIMS depth profiling of n- and p-type dopant concentrations in the vertical transistor. Small area “on-chip” SIMS depth profiling through the layered structure of Al-contact/TiSi₂/Si(p-n-p)/Si-substrate has been performed. Factors influencing the depth resolution during “on-chip” analysis of the transistor are discussed especially in terms of sputtering induced ripple formation at the erosion crater bottom, which has been imaged with atomic force microscopy. Received: 15 August 1996 / Revised: 17 January 1997 / Accepted: 21 January 1997     

A comparison between secondary-ion mass-spectrometry and spark-source mass-spectrometry for the quantitative analysis of steel wire

A comparison has been made between the results of the matrix-ion species ratio (MISR) method for quantification of secondary-ion mass-spectrometry data and spark-source mass-spectrometry analysis using photoplate detection for analysis of the steel basis of AlZn coated wire products. For SIMS quantification a suitable set of sensitivity factors, corrected for the actual surface sampling condition, was used. The results of both methods compare well. The SIMS results were, for most elements, within 25% of the concentration determined by SSMS. This could indicate that reasonably accurate results can be obtained by using the matrix-ion species ratio method for SIMS.     

Correlated Secondary Ion Mass Spectrometry-Laser Scanning Confocal Microscopy Imaging for Single Cell-Principles and Applications

Secondary ion mass spectrometry (SIMS) as a powerful surface analysis technique has been widely applied in semiconductor industry and geology research. Recently, with the development of instrumental technology, SIMS is attracting more and more attention in life sciences. SIMS can provide surface MS spectra, 2D/3D chemical images and depth profiling of substances simultaneously. The minimal lateral resolution of 2D SIMS imaging is 80–100 nm, and the longitudinal resolution of 3D SIMS imaging is about 1–5 nm. However, owing to lack of specific ions to render the structures of organelles, SIMS imaging for single cells still have great challenges. Optical microscopy, in particular laser scanning confocal microscopy (LSCM), has been emerged to be an indispensable technique for single cell imaging and can obtain high spatial 2D/3D imaging to visualize the structures of organelles. Thus, the combinational use of SIMS and LSCM, which takes advantages of SIMS for molecular imaging and LSCM for morphological imaging, has greatly extended the application of SIMS imaging and ensured its accuracy at single cells level, providing novel insights into better understanding of the biological events inside cells. In this review, we focus on the development and application of SIMS imaging and the correlated SIMS and LSCM imaging in the research of cell biology and drug discovery. We anticipate that the combinational use of SIMS and LSCM imaging has promising future in biomedicine and life sciences.     

Comparison of a new dead‐time correction method and conventional models for SIMS analysis

Recently, secondary ion mass spectrometry (SIMS) has been used in the analysis of not only impurities but also matrix elements, thus requiring a wide dynamic range for SIMS analysis. However, SIMS detectors, which are mostly used in pulse counting systems, have difficulties with detector saturation. In this paper, we investigate whether a dead‐time model that was developed for X‐ray measurement is applicable for SIMS analysis. We then compare a new correction method with conventional correction methods for detector saturation in SIMS analysis. We report that the new method can better correct the intensity in regions of higher intensity than that achieved by conventional methods. Copyright © 2012 John Wiley & Sons, Ltd.     

Simple statistically based alternatives to MAF for ToF‐SIMS spectral image analysis

The maximum autocorrelation factors technique (MAF) is becoming increasingly popular for the multivariate analysis of spectral images acquired with time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) instruments. In this article, we review the conditions under which the underlying chemical information can be separated from the large‐scale, non‐uniform noise characteristic of ToF‐SIMS data. Central to this pursuit is the ability to assess the covariance structure of the noise. Given a set of replicate images, the noise covariance matrix can be estimated in a straightforward way using standard statistical tools. Acquiring replicate images, however, is not always possible, and MAF solves a subtly different problem, namely, how to approximate the noise covariance matrix from a single image when replicates are not available. This distinction is important; the MAF approximation is not an unbiased statistical estimate of the noise covariance matrix, and it differs in a highly significant way from a true estimate for ToF‐SIMS data. Here, we draw attention to the fact that replicate measurements are made during the normal course of acquiring a ToF‐SIMS spectral image, rendering the MAF procedure unnecessary. Furthermore, in the common case that detector dead‐time effects permit no more than one ion of any specific species to be detected on a single primary ion shot, the noise covariance matrix can be estimated in a particularly simple way, which will be reported. Copyright © 2011 John Wiley & Sons, Ltd.     

Reduction of matrix effects in TOF‐SIMS analysis by metal‐assisted SIMS (MetA‐SIMS)

We investigated reduction of the matrix effect in time‐of‐flight secondary ion mass spectrometry (TOF‐SIMS) analysis by the deposition of a small amount of metal on the sample surfaces (metal‐assisted SIMS or MetA‐SIMS). The metal used was silver, and the substrates used were silicon wafers as electroconductive substrates and polypropylene (PP) plates as nonelectroconductive substrates. Irganox 1010 and silicone oil on these substrates were analyzed by TOF‐SIMS before and after silver deposition. Before silver deposition, the secondary ion yields from the substances on the silicon wafer and PP plate were quite different due to the matrix effect from each substrate. After silver deposition, however, both ion yields were enhanced, particularly the sample on the PP plate, and little difference was seen between the two substrates. It was therefore found that the deposition of a small amount of metal on the sample surface is useful for reduction of the matrix effect. By reducing the matrix effect using this technique, it is possible to evaluate from the ion intensities the order of magnitude of the quantities of organic materials on different substrates. In addition, this reduction technique has clear utility for the imaging of organic materials on nonuniform substrates such as metals and polymers. MetA‐SIMS is thus a useful analysis tool for solving problems with real‐world samples. Copyright © 2005 John Wiley & Sons, Ltd.     

Inverse velocities of sputtered monatomic ions: Systematics and quantification

The emission of secondary ions of about fifteen different elements, sputtered from Ti-base metal specimens, has been studied by SIMS. Both positive and negative ion yields have been measured at different exit energies up to ca 350 eV. It is found that when the logarithm of ionizability is plotted versus the inverse of the exit velocity, each element suggests a straight line behavior at energies above ca 20 eV. The gradient of the straight line is related to the respective 1st ionization potential (for positive ions) or electron affinity (negative ions). This behavior gives considerable support to the premises of modern theory of ionization in sputtering. Furthermore, the straight line plots for different elements are seen to converge as exit velocity increases; the intercepts at zero inverse velocity are found to be proportional to the respective element concentrations. This in principle offers a means of quantification in elemental analysis by SIMS, a method that does not require any external standards. The usefulness of the new method is demonstrated for ten elements sputtered from two specified titanium-base alloy standards from NIST.Dedicated to Professor Dr. rer. nat. Dr. h.c. Hubertus Nickel on the occasion of his 65th birthday     

An effect of residual gas component on detected secondary ions during TOF‐SIMS depth profiling and a method to estimate contained component

With regard to Secondary Ion Mass Spectroscopy (SIMS) measurement of atmospheric gas elements, a problem occurs that the detected signal includes background components caused by residual gas along with contained components. Relating to this issue, an available method to quantify the contained components by separating the background ones had been established for Dynamic SIMS. Time‐of‐Flight SIMS with sputtering ion gun has also applied for depth profiling as well as Dynamic SIMS. However, few studies have attempted to investigate the secondary ion behavior of the atmospheric gas elements for depth profiling by Time‐of‐flight SIMS, especially for low concentration levels. In this study, experimental examinations of the secondary ions of the atmospheric gas elements, such as oxygen, hydrogen, and carbon in the silicon substrate, has been conducted in various analytical conditions of TOF‐SIMS depth profiling mode. Under the analytical conditions of our study, it has been proved that the background intensity of these elements was correlated to the sputtering rate. For the analysis of Floating Zone Silicon substrate, the oxygen intensity of the background component was proportional to the inverse number of the sputtering rate. Based on these facts, the total detected intensity of the atmospheric gas elements was able to be separated into the contained components and background ones by changing the sputtering rate during TOF‐SIMS measurement. An experimental result has shown that the contained oxygen concentration in the Czochralsk Silicon substrate estimated by the “TOF‐SIMS Raster Change Method” has successfully agreed with the result by the Dynamic SIMS.     

Installation of a Shielded SIMS for the Analysis of Irradiated Nuclear Fuels

A CAMECA IMS 6F secondary ion mass spectrometer (SIMS) for the analysis of irradiated nuclear fuel has been installed in the Microbeam Analysis Laboratory of the Institute for Transuranium Elements (ITU). This device is specially equipped with heavy metal shielding to enable the safe examination of irradiated nuclear fuel samples with activities up to 75 GBq. At ITU the shielded SIMS will be used in conjunction with EPMA taking advantage of the complementary nature of the two techniques and will make important contributions to ongoing research programmes such as the safety of nuclear fuels, the partitioning and transmutation programme and the characterisation of spent fuels. The paper describes the shielded SIMS installation and presents a selection of results from the commissioning tests.     

Image fusion combining SEM and ToF‐SIMS images

Image fusion allows for the combination of an image containing chemical information but low spatial resolution with a high‐spatial resolution image having little to no chemical information. The resulting hybrid image retains all the information from the chemically relevant original image, with improved spatial resolution allowing for visual inspection of the spatial correlations. In this research, images were obtained from two sample test grids: one of a copper electron microscope grid with a letter ‘A’ in the center (referred to below as the ‘A‐grid’), and the other a Tantalum and Silicon test grid from Cameca that had an inscribed letter ‘C’ (referred to below as the ‘Cameca grid’). These were obtained using scanning electron microscopy (SEM) and time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS). Image fusion was implemented with the Munechika algorithm. The edge resolution of the resulting hybrid image was calculated compared with the edge resolution obtained for both the individual ToF‐SIMS and SEM images. The challenges of combining complimentary datasets from different instrumental analytical methods are discussed as well as the advantages of having a hybrid image. The distance across the edge for hybrid images of the A‐Grid and the Cameca grid were determined to be 21 µm and 8 µm, respectively. When these values were compared to the original ToF‐SIMS, SEM and optical microscopy measurements, the fused image had a spatial resolution nearly equal to that obtained in the SEM image for both samples. Copyright © 2014 John Wiley & Sons, Ltd.     

Differentiating diterpene resin acids using ToF‐SIMS and principal component analysis: new tools for assessing the geochemistry of amber

Amber is a polymerized plant resin having remarkable preservation potential in the geological record. Numerous analytical techniques have been applied to the study of amber organic chemistry in order to extract paleobotanical information. However, only exploratory work has been conducted using time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS), despite its immense potential due to the high mass resolution and range that can be analyzed concurrently. Detailed assessments of ion fragmentation patterns are prerequisite, given that amber is comprised of a challenging range of terpenoids, carboxylic acids, alcohols, and associated esters. In recent work, we demonstrated the applicability and efficiency of ToF‐SIMS as a tool to investigate amber chemical composition. However, only two diterpene resin acid standards were considered in this preliminary study, namely abietic acid and communic acid. We now extend this work by documenting the ToF‐SIMS spectra of ten additional diterpene resin acids and ask whether ToF‐SIMS analysis can distinguish subtle differences within a larger set of diterpenoids. Both positive and negative ToF‐SIMS spectra were produced, although negative polarity appears particularly promising for differentiating diterpene resin acids. Principal component analysis (PCA) was used to distill the data and verified that purified diterpenes have distinct ToF‐SIMS spectra that can be applied to amber chemotaxonomy as well as to the analysis of modern resins of known botanical origin. While this work is pertinent to the study of the composition and histories of ambers, the mass spectra of the 12 diterpene standards could prove valuable to any system where diterpenoid chemistry plays a role. Copyright © 2014 John Wiley & Sons, Ltd.