E.H. van Veen

On the use of line intensity ratios and power adjustments to control matrix effects in inductively coupled plasma optical emission spectrometry

In inductively coupled plasma optical emission spectrometry, matrix effects can be substantially reduced by applying robust operating conditions, i.e. a high rf power level and a low nebulizer gas flow. However, dissimilar line intensity changes are still observed, in particular with varying salt matrices. Calcium and, to a lesser extent, Mg induce stronger effects than Na and K. In 0.1, 0.3 and 1.0% Ca matrices, signal changes for 29 atomic as well as ionic lines have been determined with respect to the Ca-free solution. The changes range from –5 to –30% for the 1.0% Ca matrix. Starting from robust conditions in radial viewing, the rf power has been adjusted until the Cr ion-to-atom line ratio measured for the calcium solutions equalled the ratio determined during the calibration (0% Ca). By this power adjustment, the changes are within ±4%. No matrix effects originating from the sample introduction system are observed, probably due to the high acid concentrations used. The practical application of power adjustments is illustrated with results for certified sediment samples and with multiple line analysis for qualitative and semiquantitative analysis. The approach is an attractive alternative to matrix matching or standard additions. Internal standardization based on one atomic and one ionic line of the same element is indicated as another possibility.

Application of mathematical procedures to background correction and multivariate analysis in inductively coupled plasma-optical emission spectrometry

In inductively coupled plasma-optical emission spectrometry, continuous progress is made in acquiring and processing more spectral information than one gross analyte line intensity and two background intensities measured at both sides of the line. Compared to direct readers and slew-scan spectrometers, the recently introduced systems with echelle optics and charge transfer device detection provide more signals at a time, not only with respect to line and background, but also with respect to multiple lines for multiple elements. PC systems are increasingly powerful to apply more sophisticated mathematics for data reduction. Procedures developed over the last decade, based on convolution, differentiation, Fourier transforms, correlation, expert systems, neural networks, principal component analysis, projection methods, Kalman filtering, multiple linear regression and generalised standard additions are reviewed. The first four procedures aim at continuum or structured background correction in every spectral window measured, without prior knowledge about the appearance of the background and the composition of the sample. The other procedures utilise the information that is present for the sample and readily available in the spectrum. In addition to background correction, they allow signal averaging, noise separation, multiple line and multiple element analysis. Multiple line procedures concentrate on qualitative analysis and line selection, whereas multicomponent analysis allows quantitative analysis. Based on the characteristics of ICP-OES, the multicomponent analysis procedures are preferred.

Spectral interpretation and interference correction in inductively coupled plasma mass spectrometry

Abstract To tackle the several problematic polyatomic interferences in inductively coupled plasma mass spectrometry (ICP-MS), we have developed a software approach based on data reduction of the measured total mass spectrum through multicomponent analysis (MCA). The approach leans on a working knowledge of interferents that are likely to be encountered in a sample matrix, which composition is known by virtue of the total mass spectrum and knowledge of applied solvents. The full isotopic patterns for all elements and expected interferents are used in the modelling MCA matrix of 250 masses × 105 species at maximum. Polyatomic abundances are calculated by the software. Since all species are modelled fundamentally through their known natural abundances, the MCA matrix can be manipulated and reprocessed until interpretation of the mass spectrum and, hence, interference correction are optimal. The optimum is attained by use of the bar graph and calculation modes of the PC software and criteria for properly found isotopic patterns. With optimized models stored in the data base, the user may routinely process samples in one go, and operate the ICP-MS system in a true all-element mode. Use of elemental equations or measurement of large multivariate calibration sets and pure component solutions are superfluous. Data reduction is solely based on the information about the isotopic patterns, present in the measured mass spectrum itself. As a result, in the case of interferences, detection limits may be lowered by one to two orders of magnitude. The approach is illustrated with an industrial example of Hf determined in NdFeB, and with an environmental example. Here, a suite of elements over the 50–82 amu mass range has been determined in different salt matrices in ground water.

Kalman filtering of data from overlapping lines in inductively coupled plasma-atomic emission spectrometry

Abstract In inductively coupled plasma-atomic emission spectrometry (ICP-AES) spectral interferences give rise to severe problems. Detection limits worsen considerably, and line selection depends on matrix composition. It is investigated whether the detection limits can be reduced towards values obtained from isolated lines by use of a multicomponent analysis method, such as the Kalman filter. Our Kalman filter approach uses as many data as are readily available prior to analysis. The flatness of the innovations sequence is shown to be a criterion for correction of the optical instability of the monochromator. Spectral scans have intentionally been taken from a medium resolution monochromator in a fast scanning mode. The spectral scans do not require background correction in advance. The filter can handle structured as well as unstructured background and allows for noise averaging. Detection limits are obtained which are even lower than those based on pure component solutions. This is illustrated by the measurement of Nd in the presence of Pr, P in the presence of Cu, Cd in the presence of Fe and In in the presence of Mo and W. These measurements give examples of overlapping lines with identical shape, with large or small peak separations and/or with large intensity differences. The results suggest that line selection is almost independent of matrix composition. The approach is fast, deals with multicomponent systems and with one-component systems, and yields accurate concentration values in all cases. Data reduction in ICP-AES can be fully based on Kalman filtering.

Some spectral interference studies using Kalman filtering in inductively coupled plasma-atomic emission spectrometry

Abstract This paper continues the studies on the potential of Kalman filtering for data reduction in inductively coupled plasma-atomic emission spectrometry (ICP-AES). Two topics with respect to spectral interferences are discussed: line selection in dependence of the magnitude of the interfering signal; and the minimum peak separation required for quantitative resolution of analyte and interfering signals. In the presence of interferences, line selection is compulsory and depends on matrix composition. In many instances the interfering signal is of the same order of magnitude as the other contributions to the total background signal. With Kalman filtering line selection is not necessary, unless the interfering signal is substantially higher than the other background contributions. The minimum peak separation depends on the integration time per step in the spectral scan, the step size in the scan, and the number of lines in the spectral window. Two sets of filtering conditions for an analyte to interferent intensity ratio of 0.1 are given: a practical set leading to a minimum required separation of 3 pm; and an ultimate set for which the peaks may be separated down to only 1 pm at a spectral bandwidth of the monochromator of 17 pm. All results are illustrated with practical examples.

Practical implementation of survey analysis in inductively coupled plasma optical emission spectrometry

Abstract The combination of an echelle/charge coupled device detector based spectrometer with software for multicomponent analysis (MCA) allows practical implementation of survey analysis in inductively coupled plasma-optical emission spectrometry (ICP-OES). MCA requires models for the pure components. A procedure is described for how to obtain the models for 67 pure elements detectable in ICP-OES. In fact, each element is represented by two model vectors. Measurements at low analyte concentration provide the sensitivities for the prominent lines used in trace analysis, whereas weak lines and continuum emission are modelled with high concentration measurements. This modelling allows proper calibration for trace and major levels, and strongly reduces noise contributions. The model library is prepared once and a monitor solution, containing seven specific elements, is used to achieve a daily link with this once-only calibration (wavelength axis and sensitivity). To control the efficiency of atomization and ionization the Cr ii 267 nm to Cr i 357 nm ratio is used. The MCA calculations are repeated at different intensity levels in order to cover the dynamic range in intensity and, hence, concentration for all the elements present in the sample solution. Matrix-matching of the monitor solution was studied in order to overcome matrix effects owing to high acid or salt contents. Some certified reference materials were analysed. The results for most elements are found within 20% of the certified values.

Quantitative survey analysis by using the full inductively coupled plasma emission spectra taken from a segmented charge coupled device detector : feasibility study

Abstract Full emission spectra over 160–800 nm are taken from the segmented CCD detector (SCD) of the Perkin-Elmer Optima 3000 system. The spectra are processed by multicomponent analysis (MCA). This feasibility study indicates that fast and simultaneous quantitative analysis of all elements is within reach. It is essential to control the daily variations in sensitivity, RF power and wavelength axis, for which procedures have been developed. The combination of the SCD data and MCA eliminates the need for prior knowledge about the sample composition, for analyzing restricted suites of elements, and for selection of lines or background correction points. Processing the full spectrum improves the precision in the concentration.

Precision-based optimization of multicomponent analysis in inductively coupled plasma mass spectrometry

Abstract To arrive at rapid, precise and automated survey analysis in inductively coupled plasma mass spectrometry (ICP-MS), the measurement and data reduction of full-range mass scans ( m z = 6−238 ) have been investigated. The way mass spectra are scanned has been optimized with respect to short- and long-term precision. Three internal standards are needed to correct for changes in mass bias. An expression for the precision or relative standard deviation (RSD) as a function of the measured mass intensity has been derived in terms of source flicker and ion shot noise. Our formerly introduced multicomponent analysis approach has been optimized with respect to the construction of the modelling matrix. An automated interpretation system with a data base of interferents has been incorporated in the software. The optimization procedures use criteria based on the RSD function. Detection limits for Hf in solutions for the pure component and for the magnetic material NdFeB characterize the final approach. By only using the information available in the full-range mass scan, the approach results in concentrations and true detection limits in the sample solution for all elements.

Quantitative line selection with the Kalman filter approach for inductively coupled plasma atomic emission spectrometry

Abstract With the Kalman filter approach, the true detection limit (i.e. the detection limit in the sample solution) only depends on the height of the total background signal, and is not determined by the uncertainties in interfering background signals. Based on the background equivalent interferent concentration, the true detection limit can be directly estimated in sample solutions containing various amounts of interferent. This eases the application of the true detection limit as quantitative criterion for line selection. Following this approach, quantitative line selection is demonstrated for Pb and Cd determinations in river sediments (Fe interferences).

The Kalman filter approach to inductively coupled plasma atomic emission spectrometry

Abstract This article is an electronic publication in Spectrochimica Acta Electronica (SAE), the electronic section of Spectrochimica Acta Part B (SAB). The hardcopy text, comprising the main article and two appendices, is accompanied by a disk containing the compiled program, a reference manual and data files. The work deals with data handling in inductively coupled plasma atomic emission spectrometry (ICP-AES). With this technique, the analyte signal is superimposed on a background signal. When separating the signals by manual or automated three-point background correction, there are many instances in which the data reduction fails. Based on scans recorded in a fast-scanning mode and on a library of pure-component scans, the Kaiman filter approach models the emission in the spectral window (about 100 pm) of the analyte and mathematically solves the problem of background correction. By using a criterion-based algorithm to correct for optical instability, the uncertainty in the determination of the interferent line signal is eliminated. Therefore, the present filter implementation yields more accurate and precise results, especially in the case of line overlap. The Kalman filter Approach to Atomic Spectrometry (KAAS) software automatically processes Perkin-Elmer Plasma 1000 2000 text files, but can also handle ASCII data files. Practical and comprehensive examples are given to evoke the “Kalman filter feeling” in the crucial step of creating the emission model.