Robert L. Watters

Dissolution problems with botanical reference materials

SummaryAs part of the analytical research leading to the certification of the new Apple and Peach Leaves Standard Reference Materials (SRMs), a study was undertaken to evaluate different sample dissolution techniques for losses of analyte species. Possible loss mechanisms include absorption or adsorption of analyte elements at the walls of the sample decomposition vessels, and the formation or persistence of insoluble particulate material during sample dissolution. Results of this study indicated that significant fractions of some elements were present on particles after acid dissolution, despite visual indications that dissolution was complete. In addition, large amounts of some elements remained in the platinum crucibles used to fuse samples with lithium metaborate.

Comparison of reflux and microwave oven digestion for the determination of arsenic and selenium in sludge reference material using flow injection hydride generation and atomic absorption spectrometry

A microwave oven digestion procedure was developed for rapid dissolution of sludge samples (NIST SRM 2781) for the determination of As and Se. Microwave oven digestion with HNO3 and H2SO4 provides results comparable to those obtained by reflux column digestion using HNO3, H2SO4 and HClO4. The experimental details for sample preparation and the flow injection hydride generation atomic absorption spectrometric method are discussed. The effects of matrix and various acid concentrations on the extraction and absorbance were also studied. The proposed method has detection limits of 0.15 and 0.17 ng ml–1 for As and Se, respectively.

Determination of arsenic, selenium and mercury in an estuarine sediment standard reference material using flow injection and atomic absorption spectrometry

A flow-injection analysis atomic absorption spectrometric (FIA-AAS) method was developed for the determination of trace amounts of arsenic, selenium and mercury in a proposed estuarine sediment standard reference material (SRM 1646a). The samples were prepared in two manners: a) A wet digestion procedure with HNO3, H2SO4, and HClO4 using a reflux column and b) A microwave-oven digestion procedure utilizing HNO3, H2SO4, and HCl for As and Se, and HNO3 for Hg. Microwave-oven digestion provides results comparable to those found by reflux column digestion and reduces the sample preparation time by a factor of 10. The proposed method employing the microwave-oven digestion procedure coupled with FIA-AAS for As and Se, and FIA-CVAAS for Hg, has detection limits of 0.15 ng As/ml, O.17 ng Se/ml and 0.15 ng Hg/ml.

Laser-Induced Ionization of Atoms in a Power-Modulated Inductively Coupled Plasma

Laser-induced ionization of atoms has been detected in a power-modulated inductively coupled plasma. The measurement is made 1.4 ms after complete interruption of the 40-MHz power to a 400-W plasma. Electrical conductivity measurements between probe electrodes in the plasma during the power-off cycle have been made, demonstrating the decay in plasma background ion/electron concentrations which makes detection of laser-induced ionization possible. Radio-frequency interference from the ICP on the ionization detection electronics is also avoided by this approach. The primary mode of laser-induced ionization was photoionization of the laser-excited atoms, i.e., resonance ionization spectroscopy (RIS). Detection limits of 80 µg Fe/L and 20 µg Ga/L were achieved.

The use of standard reference materials for quality assurance in inductively coupled plasma optical emission and atomic absorption spectrometry

Abstract To ensure that a chemical measurement process yields accurate results, well characterized control materials such as Standard Reference Materials (SRMs) should be analysed. For inductively coupled plasma optical emission spectrometry (ICP-OES) and atomic absorption spectrometry (AAS) methods, the SRM should be similar in chemical matrix to the unknown test material of interest so that the SRM provides similar sources of potential systematic error. Such sources of error may include incomplete dissolution, loss of volatile analyte, and chemical matrix interferences in the plasma, flame or electrothermal atomizer. In addition, the SRM should be chosen so that the analyte levels match the corresponding estimated levels in the unknown and so that the uncertainties in the certified values are small enough to provide a useful test for accuracy. The measurement process itself must be designed so that sources of random error can be evaluated. Each potential source of random error should be replicated to provide for a test of its significance. The resulting data will yield estimates for these components of variance, and the overall standard error can then be calculated. Examples of experimental designs and typical results from an ICP analysis of an SRM are described. Procedures using commonly available software for evaluating components of variance and calculating the mean, standard error, and the effective number of degrees of complex variance component designs are also presented. The results of such an approach are then applied to ascertaining whether or not bias in the analytical results is detected.

A statistical method for calibrating flame emission spectrometry which takes account of errors in the calibration standards

Abstract Spiegelman, C.H., Watters, R.L. and Hungwu, L., 1991. A statistical method for calibrating flame emission spectrometry which takes account of errors in the calibration standards. Chemometrics and Intelligent Laboratory Systems , 11: 121–130. The determination of potassium in sample solutions using flame emission spectrometry (FES) requires that the calibration function be estimated. Calibration standard solutions of potassium are made in the laboratory and nebulized into the FES instrument. A total of 240 data points were collected from chemical analyses. However the data come from only eight different values of the standards and are highly correlated within each standard. In the final analysis a sample size of eight was chosen to estimate the calibration curve. The main goal of this paper is to estimate the calibration function based on these data and then measure the amount of potassium in samples using this calibration function. The secondary goal is to show some of the important exploratory data analysis that should be done in any calibration. Since both the underlying theory of emission spectrometry and the scatter plot of data points suggest a linear relationship between the emission intensity and potassium concentration, a linear regression model is applied to fit these data and the residuals are examined based on regression assumptions. Data transformation is then attempted to stabilize the nonconstant variance of the residuals due to the fact that residuals fail to meet the assumptions. However, because the suggested transformation of taking the logarithm or 1/4 power of both x and y is hard to interpret, and because the log transformation would require an addition of an arbitrary constant to the standard values, we proceeded with the untransformed data. Outlier detection was used to find possible outliers. Ten consecutive observations (obs. 201–210) in the data set are potential outliers for they have absolute studentized residuals bigger than 2.7. However, influential observation techniques indicate that their effect on the estimation of the calibration curve is not great. In order to help compensate for the error in the calibration standards, we expand the calibration interval estimates. This compensation is important and helps to avoid the rather ad-hoc deletion of unusually influential data from the analysis. We think that a plausible explanation for the outliers is error in the calibration standards. In recognition of the heterogeneity of variance indicated by our data, we perform a weighted least squares type of confidence interval estimation for our calibration curve. The coefficient and standard error estimates are quite close for all weighted cases; in contrast, the unweighted case yields different values for the standard errors. If heteroscedasticity (nonconstant variance of the observations) is ignored, confidence intervals will be too wide at the low end and too narrow at the high end of the calibration curve. At both ends of the calibration curve, each resulting multiple-use calibration confidence interval is somewhat wider than the corresponding single-use calibration confidence interval. Finally, since the measurement errors that have a known finite bound in working standards have been taken into account, the increase in confidence intervals relative to presumed exact standards is about 0.1%.

Trace detection in conducting solids using laser-induced fluorescence in a cathodic sputtering cell

A cathodic sputtering atom reservoir designed for atomic absorption spectrometry of conducting solid samples is examined as a potential sampling device for trace and ultra-trace detection using laser-induced fluorescence (LIF) spectrometry. The analytical results are promising, with sub-µg g–1 sensitivity for the model analyte (Fe) in brass samples, and with reasonable precision and accuracy (±15%) for the pulsed laser system used, but with far less sensitivity than might be predicted. Noise studies clearly indicate that laser-induced background fluorescence is the principal limiting noise source. Fundamental material transport studies indicate that diffusional loss of atomic number density to the walls is of much less importance than the background fluorescence in determining the sensitivity of the system. Extrapolations based on cell–experiment design to maximize number density and minimize background emission and fluorescence promise ng g–1 sensitivities for future implementations.