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.     

Chemical properties investigation of commercial cigarettes by a “pseudo” targeted method using GC‐MS‐selected ions monitoring

A “ppseudo” targeted method using GC‐MS‐selected ions monitoring was applied to investigate the chemical characteristics of commercial cigarettes made in China and foreign countries. To identify the components and define the quantative ions for SIM acquisition, a quality control sample was analyzed using GC‐MS full scan. Acquired data were treated with a homemade software. A peak table with 312 components and their related quantitation ions was achieved for SIM acquisition. Structure elucidation was performed using library searching, retention index, standard compounds, and fitted retention time. The fitted retention time was calculated by a linear correction curve obtained using measured and library retention time to verify compounds. A total of 90 compounds were elucidated. Chemical characteristics of different cigarette brands were investigated. The data acquisition was carried out in SIM mode. The principal component and the hierarchical clustering analyses showed that the Chinese domestic flue‐cured cigarettes were significantly different from the domestic blended, the foreign flue‐cured, and blended cigarettes. Sixty‐seven differential compounds were defined using the nonparametric Mann–Whitney test and the group blending samples comparison. Chinese domestic flue‐cured cigarettes have higher concentration of saccharides and lower concentration of organic acids and amino acids.     

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.     

Searching ultimate nanometrology for AlOx thickness in magnetic tunnel junction by analytical electron microscopy and X-ray reflectometry.

Practical analyses of the structures of ultrathin multilayers in tunneling magneto resistance (TMR) and Magnetic Random Access Memory (MRAM) devices have been a challenging task because layers are very thin, just 1-2 nm thick. Particularly, the thinness (approximately 1 nm) and chemical properties of the AlOx barrier layer are critical to its magnetic tunneling property. We focused on evaluating the current TEM analytical methods by measuring the thickness and composition of an AlOx layer using several TEM instruments, that is, a round robin test, and cross-checked the thickness results with an X-ray reflectometry (XRR) method. The thickness measured by using HRTEM, HAADF-STEM, and zero-loss images was 1.1 nm, which agreed with the results from the XRR method. On the other hand, TEM-EELS measurements showed 1.8 nm for an oxygen 2D-EELS image and 3.0 nm for an oxygen spatially resolved EELS image, whereas the STEM-EDS line profile showed 2.5 nm in thickness. However, after improving the TEM-EELS measurements by acquiring time-resolved images, the measured thickness of the AlOx layer was improved from 1.8 nm to 1.4 nm for the oxygen 2D-EELS image and from 3.0 nm to 2.0 nm for the spatially resolved EELS image, respectively. Also the observed thickness from the EDS line profile was improved to 1.4 nm after more careful optimization of the experimental parameters. We found that EELS and EDS of one-dimensional line scans or two-dimensional elemental mapping gave a larger AlOx thickness even though much care was taken. The reasons for larger measured values can be found from several factors such as sample drift, beam damage, probe size, beam delocalization, and multiple scattering for the EDS images, and chromatic aberration, diffraction limit due to the aperture, delocalization, alignment between layered direction in samples, and energy dispersion direction in the EELS instrument for EELS images. In the case of STEM-EDS mapping with focused nanoprobes, it is always necessary to reduce beam damage and sample drift while trying to maintain the signal-to-noise (S/N) ratio as high as possible. Also we confirmed that the time-resolved TEM-EELS acquisition technique improves S/N ratios of elemental maps without blurring the images.     

Multiplex mass spectrometry imaging for latent fingerprints

We have previously developed in‐parallel data acquisition of orbitrap mass spectrometry (MS) and ion trap MS and/or MS/MS scans for matrix‐assisted laser desorption/ionization MS imaging (MSI) to obtain rich chemical information in less data acquisition time. In the present study, we demonstrate a novel application of this multiplex MSI methodology for latent fingerprints. In a single imaging experiment, we could obtain chemical images of various endogenous and exogenous compounds, along with simultaneous MS/MS images of a few selected compounds. This work confirms the usefulness of multiplex MSI to explore chemical markers when the sample specimen is very limited. Copyright © 2013 John Wiley & Sons, Ltd.     

XPS analysis of bio‐organic systems

A survey of the literature is made for the XPS analysis of food products (mainly spray‐dried powders, which reveal a considerable surface enrichment in lipids) and of microorganisms and related systems (extracellular polymer substances and biofilms). This survey is used as a background for discussions and recommendations regarding methodology. Sample preparation methods reviewed are freeze drying, analysis of frozen hydrated specimens and adsorption of surface‐active biocompounds on model substrates. Peak decomposition is a way to increase the wealth of information provided by the XPS spectra. It should be performed after a check that sample charge stabilization is satisfactory. Moreover, ensuring the precision needed to make comparisons within sets of samples may involve a trade‐off between imposing constraints and generating information. The examination of correlations between spectral data in the light of chemical guidelines is useful to validate or improve peak decomposition and component assignment, and may also upgrade the chemical information regarding speciation. Further upgrading may be achieved by expressing marker XPS data in terms of concentrations of compounds of interest. Different methods of computation are discussed, providing a composition in terms of ingredients, classes of biochemical compounds, or various organic and inorganic compounds. As an alternative or complement to this deterministic approach, multivariate analysis of suitable spectral windows provides spectral components, which may be used for comparing samples, and which may have a direct chemical relevance or be used to identify features of interest. Copyright © 2011 John Wiley & Sons, Ltd.     

Fast Determination of Phenanthrene in Soil by Gas Chromatography-Mass Spectrometry Using Chemometric Resolution and Standard Addition Method

A method for fast determination of the component in complex samples by using gas chromatography‐mass spectrometry (GC‐MS) was developed and used for quantitative analysis of phenanthrene in soils. In the method, window independent component analysis (WICA) was used for resolving the mass spectrum and non‐negative immune algorithm (NNIA) was employed for obtaining the chromatographic profile. Therefore, spectral and chromatographic information of a specific component can be obtained from the measured GC‐MS data of overlapping and high background. Six soil samples collected from different places were analyzed. The tedious pretreatments in preparing the samples and the elution in the separation were simplified for speeding up the analysis. Due to the complexity of the matrix, standard addition method was adopted for the final quantification. The applicability of the method was validated with a spiked sample and the results of the six samples are reasonable.     

Understanding delamination in microelectronic devices using AES,XPS and chemometrics

The recent development of XPS instrumentation with near‐micron spatial resolution has advanced the capability of elemental and chemical‐state imaging accompanied by small‐area analysis (down to 15 µm). In this paper, the combined use of X‐ray photoelectron spectroscopy (XPS) and Auger electron spectroscopy (AES) at enhanced spatial resolution is shown to have significantly improved the understanding of interfacial delamination and related problems encountered in the production of electronic devices in the field of microelectronics. An example of the application of surface analysis for ITO/Mo adhesion problems will be presented. The mathematical procedure using principal component analysis (PCA) in the reduction of noise in XPS images will also be described. The dramatic improvements in the image contrast and chemical component determination from multispectral image data sets will be presented. This study is intended to explore the contributions given by advanced surface analysis tools to solve real‐world problems. Copyright © 2007 John Wiley & Sons, Ltd.     

Use of local rank‐based spatial information for resolution of spectroscopic images

Spectroscopic images are singular chemical measurements that enclose chemical and spatial information about samples. Resolution of spectroscopic images is focused on the recovery of the pure spectra and distribution maps of the image constituents from the sole raw spectroscopic measurement. In image resolution, constraints are generally limited to non‐negativity and the spatial information is generally not used. Local rank analysis methods have been adapted to describe the local spatial complexity of an image, providing specific pixel information. This local rank information combined with reference spectral information allows the identification of absent compounds in pixels with low compound overlap. The introduction of this information in the resolution process under the form of constraints helps to increase the performance of the resolution method and to decrease the ambiguity linked to the final solutions. Copyright © 2008 John Wiley & Sons, Ltd.     

Automated mass spectrometry imaging with a matrix-assisted laser desorption ionization time-of-flight instrument

The automated use of a matrix-assisted laser desorption ionization (MALDI) mass spectrometer (MS) is described for image analysis of samples through implementation of new software for instrument control, data acquisition, and data analysis. The software permits automated acquisition of MS MALDI spectra to form an ordered data array and contains display features to provide images at one or more mass-to-charge ratio values. The technique can be used to scan tissue samples, blotted samples, gels, or other sample surfaces where the image analysis of that sample is required. The program achieves a time of typically 1 s per image point, permitting an analysis made up of large numbers of points with high spatial resolution up to 850 dpi. The features of the software are demonstrated in this paper with samples of printed images, where visible images can be compared to those obtained by mass spectrometry. Quantitative aspects are introduced by analyzing a series of sample spots containing different amounts of several proteins.     

Evaluation of the chemical consistency of Yin‐Chen‐Hao‐Tang prepared by combined and separated decoction methods using high‐performance liquid chromatography and quadrupole time‐of‐flight mass spectrometry coupled with multivariate statistical analysis

In this study, Yin‐Chen‐Hao‐Tang prepared by two decoction methods, namely, combined decoction (modern decoction method) and separated decoction (traditional decoction method), was analyzed by high‐performance liquid chromatography with quadrupole time‐of‐flight mass spectrometry. The acquired datasets containing sample codes, t_R‐m/z pairs and ion intensities were processed with multivariate statistical analyses, such as principal component analysis and an orthogonal partial least squared discriminant analysis model, to globally compare the chemical differences between the different decoction samples. Then, the chemical differences between the combined and separated decoctions were screened out by S‐plots generated from the orthogonal partial least squared discriminant analysis model and compared with chemical information from an established in‐house library. The six components that contributed the most to the chemical differences were identified as chlorogenic acid, caffeic acid, geniposide, genipin, scopoletin, and 3,5‐dicaffeoylquinic acid. The concentrations of genipin and caffeic acid from the separated decoction were higher than those from the combined decoction, indicating that the separated decoction may present a stronger hepatoprotective effect. However, the results still require further investigation through pharmacological and clinical studies. Our findings not only establish a strategy to evaluate chemical consistency of Yin‐Chen‐Hao‐Tang but also provide the scientific basis for using traditional separated decoction method.     

Super-resolution and Raman chemical imaging: from multiple low resolution images to a high resolution image

Imaging in Raman spectroscopy is a valuable tool for analytical chemistry. Although molecular characterization at micron level is achieved for many applications, it usually fails producing chemical images of micron size samples as expected in chemical, environmental and biological analysis. The aim of the work is to introduce the potential of super-resolution in vibrational spectroscopic imaging. This original chemometrics approach uses several low resolution images of the same sample in order to retrieve a higher resolution chemical image. It is thus possible to overcome in a certain way some physical and instrumentals limitations. To illustrate the methodology, sub-micronic details of a Si/Au sample are retrieved from low resolution images with different super-resolution algorithms. The better results are obtained with Iterative L2/Bilateral Total Variation regularization method. The use of a regularization procedure gives also better results since its first property is to preserve edges during the reconstruction of the super-resolved image. This concept of chemical image data processing should open new analytical opportunities.     

On the implementation of spatial constraints in multivariate curve resolution alternating least squares for hyperspectral image analysis

Hyperspectral imaging (HSI) is a method for exploring spatial and spectral information associated with the distribution of the different compounds in a chemical or biological sample. Amongst the multivariate image analysis tools utilized to decompose the raw data into a bilinear model, multivariate curve resolution alternating least squares (MCR‐ALS) can be applied to obtain the distribution maps and pure spectra of the components of the sample image. However, a requirement is to have the data in a two‐way matrix. Thus, a preliminary step consists of unfolding the raw HSI data into a single‐pixel direction. Consequently, through this data manipulation, the information regarding pixel neighboring is lost, and spatial information cannot directly be constrained on the component profiles in the current MCR‐ALS algorithm. In this short communication, we propose an adaptation of the MCR‐ALS framework, enabling the potential implementation of any variation of spatial constraint. This can be achieved by adding, at each least‐squares step, refolding/unfolding of the distribution maps for the components. The implementation of segmentation, shape smoothness, and image modeling as spatial constraints is proposed as a proof of concept. Copyright © 2015 John Wiley & Sons, Ltd.     

Rapid parameter optimization of low signal‐to‐noise samples in NMR spectroscopy using rapid CPMG pulsing during acquisition: application to recycle delays

A method is presented that combines Carr–Purcell–Meiboom–Gill (CPMG) during acquisition with either selective or nonselective excitation to produce a considerable intensity enhancement and a simultaneous loss in chemical shift information. A range of parameters can theoretically be optimized very rapidly on the basis of the signal from the entire sample (hard excitation) or spectral subregion (soft excitation) and should prove useful for biological, environmental, and polymer samples that often exhibit highly dispersed and broad spectral profiles. To demonstrate the concept, we focus on the application of our method to T₁ determination, specifically for the slowest relaxing components in a sample, which ultimately determines the optimal recycle delay in quantitative NMR. The traditional inversion recovery (IR) pulse program is combined with a CPMG sequence during acquisition. The slowest relaxing components are selected with a shaped pulse, and then, low‐power CPMG echoes are applied during acquisition with intervals shorter than chemical shift evolution (RCPMG) thus producing a single peak with an SNR commensurate with the sum of the signal integrals in the selected region. A traditional ¹³C IR experiment is compared with the selective ¹³C IR‐RCPMG sequence and yields the same T₁ values for samples of lysozyme and riverine dissolved organic matter within error. For lysozyme, the RCPMG approach is ~70 times faster, and in the case of dissolved organic matter is over 600 times faster. This approach can be adapted for the optimization of a host of parameters where chemical shift information is not necessary, such as cross‐polarization/mixing times and pulse lengths. Copyright © 2013 John Wiley & Sons, Ltd.     

Low‐bandwidth space/frequency component separation for quantitative imaging

Quantitative MRI is often used to analyse multicomponent systems. The analysis requires the contributions from different species to be isolated. Species with distinct chemical shifts can be separated by using a low acquisition bandwidth, which is easy to achieve in common quantitative imaging protocols. The bandwidth reduction leads to separation of NMR contributions from different species in the image space. This new method was implemented and tested on two multicomponent systems containing several spectrally and spatially unresolved components with both distinctly different and similar diffusion coefficients and relaxation times. Separation was achieved with routine MRI diffusion and relaxation measurement pulse sequences in a microimaging environment for water/polyethylene glycol solution and for chloroform/TMS/polyethylene glycol solution. Conventional monoexponential fitting was used to determine diffusion coefficients and relaxation times from the spectrally separated data, whereas biexponential or triexponential fitting was required in the unseparated reference experiments. In the two‐component sample, the variation in the determined fast diffusing components was on the same order of magnitude for all experiments, while the variation in the slow diffusing polyethylene glycol was larger when no separation was present. The separation technique provided lower variability for all the determined diffusion coefficients and relaxation times in the three‐component sample. The low‐bandwidth separation method can provide separation of multicomponent systems based on the chemical shift difference between the species. The accuracy of the technique is comparable with the commonly used methods for bicomponent system analysis and surpasses those when there are more than two components in the sample. Copyright © 2016 John Wiley & Sons, Ltd.     

Application of SEM/EDX and metallographic techniques to the diachronic study (6th–18th century) of metallurgical materials found in archaeological excavations on the island of Ibiza (Spain)

This work is the archaeometric study of the different types of materials recovered in the same excavation or archaeological dig (which makes it possible to accurately date the remains found) on the island of Ibiza (Spain). The samples found belong only to the phase of iron forging and span a very wide historical period from the 6th to the 18th century, including the Islamic period. Scanning Electron Microscopy (SEM) is proposed to observe the images obtained of the surfaces of the samples, in order to study the topographical, morphological and microstructural characteristics providing information on the materials contained in the samples. It also permits chemical analysis of the elements in the sample using X-ray Microanalysis (SEM/EDX), which provides both qualitative and semi-quantitative information on the elements in the sample. The archaeometric results suggest that the sole use of the area studied was as a forge workshop over a long period of time. The slag studied show that no reduction or refining activities took place in the area. However, in this forge, pieces of other metals were also produced, especially bronze alloys, polymetallism being a common characteristic throughout history.     

Investigation of element distribution and homogeneity of TXRF samples using SR-micro-XRF to validate the use of an internal standard and improve external standard quantification

Total reflection X-ray fluorescence analysis (TXRF) offers a nondestructive qualitative and quantitative analysis of trace elements. Due to its outstanding properties TXRF is widely used in the semiconductor industry for the analysis of silicon wafer surfaces and in the chemical analysis of liquid samples. Two problems occur in quantification: the large statistical uncertainty in wafer surface analysis and the validity of using an internal standard in chemical analysis. In general TXRF is known to allow for linear calibration. For small sample amounts (low nanogram (ng) region) the thin film approximation is valid neglecting absorption effects of the exciting and the detected radiation. For higher total amounts of samples deviations from the linear relation between fluorescence intensity and sample amount can be observed. This could be caused by the sample itself because inhomogeneities and different sample shapes can lead to differences of the emitted fluorescence intensities and high statistical errors. The aim of the study was to investigate the elemental distribution inside a sample. Single and multi-element samples were investigated with Synchrotron-radiation-induced micro X-ray Fluorescence Analysis (SR-μ-XRF) and with an optical microscope. It could be proven that the microscope images are all based on the investigated elements. This allows the determination of the sample shape and potential inhomogeneities using only light microscope images. For the multi-element samples, it was furthermore shown that the elemental distribution inside the samples is homogeneous. This justifies internal standard quantification.