Sample Analysis Tables

A table of all runs that includes the instrument IDs and analysis dates should be provided. In addition to the runs that 

Calibration curve data should be assessed to determine the appropriate mathematical regression that describes the instrument s response over the range of thecalibration curve (Section8.5). The report should include the back-calculated concentration values, accuracies, slopes, y-intercepts and correlation coefficients (R) and the coefficients of determination (R ) (Equation[8.18] in Section 8.3.1) for aU curves used in the validation. The value should be 0.98 for each calibration curve. The R value (if used) must be 0.99 for each calibration curve. An example table used to summarize the calibration curve statistics for each run used for method validation is shown as Table 10.2. 

If matrix effects are evaluated during validation, a table that summarizes the response data and the calculated matrix effect (ME, Section 9.6.1) should also be provided. An example table for demonstration of ME data is shown in Table 10.7. 

Additional tables that summarize any other experiments conducted during method vahdation should also be included in the final report. 

---

Suppose we have two methods of preparing some product and we wish to see which treatment is best. When there are only two treatments, then the sampling analysis discussed in the section Two-Population Test of Hypothesis for Means can be used to deduce if the means of the two treatments differ significantly. When there are more treatments, the analysis is more detailed. Suppose the experimental results are arranged as shown in the table several measurements for each treatment. The goal is to see if the treatments differ significantly from each other that is, whether their means are different when the samples have the same variance. The hypothesis is that the treatments are all the same, and the null hypothesis is that they are different. The statistical validity of the hypothesis is determined by an analysis of variance. 

The modified FMEA approach has been used by the API to develop RP14C. In this document ten different process components have been analyzed and a Safety Analysis Table (SAT) has been developed for each component. A sample SAT for a pressure vessel is shown in Table 14-4. The fact that Tables 14-3 and 14-4 are not identical is due to both the subjective natures of a Hazard Analysis and FMEA, and to the fact that RP14C is a consensus standard. However, although the rationale differs somewhat, the devices required are identical. (The gas make-up system in Table 14-4 is not really required by RP14C, as we shall see.)... 

Purification of the radioactive tracer was modified to include a fractional sublimation before a single extraction—recrystallization cycle to conserve the tracer material. Microgram samples were prepared in melting point capillaries for assay by mass spectroscopic analysis (Table III), made by direct probe injection of the sample into the ion source (18). The probe was heated rapidly to 200°C, and mass spectra were obtained during vaporization of the sample. Tri-, tetra-, and pentachlorodibenzo-p-dioxins vaporized simultaneously with no observed fractionation. 

Figure 3. Histogram of Monte Carlo simulation for a synthetic alpha-spectrometric analysis (Table 1) of a sample with near-secular equilibrium No age can be calculated for the measured ...

Table 3.4 summarises the main characteristics of a variety of sample preparation modes for in-polymer additive analysis. Table 3.5 is a short literature evaluation of various extraction techniques. Majors [91] has recently reviewed the changing role of extraction in preparation of solid samples. Vandenburg and Clifford [4] and others [6,91-95] have reviewed several sample preparation techniques, including polymer dissolution, LSE and SEE, microwave dissolution, ultra-sonication and accelerated solvent extraction. 

Applications Specific applications of the direct spectrometric analysis methods of solid samples of Table 8.36 are given under the specific headings. One investigation that is practically only possible by direct solids analysis is checking the homogeneity of polymers [136,137] this is of significance for reference materials and for quality control. A method for the assessment of microhomogeneity should meet various requirements [223] ... 

Crompton [21] has reviewed the use of electrochemical methods in the determination of phenolic and amine antioxidants, organic peroxides, organotin heat stabilisers, metallic stearates and some inorganic anions (such as bromide, iodide and thiocyanate) in the 1950s/1960s (Table 8.75). The electrochemical detector is generally operated in tandem with a universal, nonselective detector, so that a more general sample analysis can be obtained than is possible with the electrochemical detector alone. 

The mass losses for all samples are in a good agreement with values of water and hydroxide group content obtained by chemical analysis (Table 1). Thus, for electrochemical testing of Li- intercalation activity each sample was heated at 350°C to remove all types of bound water. 

Table 34-3 Individual sample analysis precision for hypothetical production samples...

Table 34-5 Individual sample analysis estimated accuracy using grand mean calculation...

Table 34-6 Individual sample analysis accuracy using Spiked Recovery study...

Sample size and matrix Your choice of analytical method will also be dependent on the amount of sample you have, especially if the amount is limited and some of the methods under consideration are destructive to the sample. In the Bulging Drum Problem, sample size was not an issue. However, sampling the gas in the drum was challenging, since loss and contamination were quite likely. Getting the samples to the lab presented other challenges. Sample matrix is another important factor in method choice. As you know, some methods and instrumental techniques are not suitable for analysis of solids, without sample preparation. Table 21.8 lists some of the issues that must be considered for different sample matrices. 

Uchiyama [11] applied this method to the determination of fluorescent whitening agents and alkyl benzenesulphonates and also methylene blue active substances in bottom sediment samples taken in a lake. The muds were filtered off with a suction filter and frozen until analyzed. About 20g of wet bottom mud was extracted three times with a methanol-benzene (1 1) mixture. After the solvent was evaporated using a water bath, the residue was dissolved in hot water and this solution used for analysis. Table 10.2 shows the analytical results for methylene blue active substances (MBAS), alkyl benzene-sulphonate (ABS), and fluorescent whitening agent (FWA) in bottom sediments. 

When the merged stream flows through the detector, transient peaks are recorded in proportion to analyte concentration. Excessive dispersion of the sample zone into the carrier stream is reduced by the use of small sample volumes, narrow bore tubing and short residence times in the system. Rapid analysis and easy starting up procedures make this technique particularly useful for single samples which arrive infrequently and require immediate analysis (Table 6.1). 

The overall method includes sample collection and storage, extraction, and analysis steps. Sampling strategy is an important step in the overall process. Care must be taken to assure that the samples collected are representative of the environmental medium and that they are collected without contamination. There is an extensive list of test methods for water analysis (Tables 8.2, 8.3, and 8.4), which includes numerous modifications of the original methods, but most involve alternative extraction methods developed to improve overall method performance for the analysis. Solvent extraction methods with hexane are also in use. 

The samples from the plot receiving the granulated formulation (Table I) revealed a different situation. The overall variability was much larger with a coefficient of variation of 395, with increased variability both between and within the five samples. Analysis of variance gave components of 140 between field samples, and 264 between laboratory subsamples. Since the analytical procedures were identical with those used in the EC plot samples, where reproducibility was good, these results clearly indicate a much greater irregularity of the distribution of the herbicide in... 

The data modeled are from gas chromatograms obtained for Aroclors 1242, 1248, 1254 and 1260. The unknown samples are from the anaysis of used transformer oil obtained from a waste dump in New Jersey. The concentration of individual isomers in selected Aroclor and transformer oil samples are given in Appendix I. The data are organized in a matrix in which the first four data entries for each sample in row 1 of the data array (Table 2, Apendix I) designate the composition of the sample. For standards, these four variables represent the fractional parts of Aroclor 1242, 1248, 1254, or 1260, respectively, that were combined. Results from the analysis of transformer oil (samples 21-23) are of unknown fractional composition and variables 1 through 4 are null entries. In the examples that follow data from samples analyzed (Table 1, Appendix I) were used in part or in total to illustrate the PLS method. 

Table V lists the detection limits for several semi-volatile brominated organics by glc/ms/comp, glc/ecd and tlc/sd. By far the greatest sensitivity to TRIS is attainable with glc/ecd. However, the versatility and identification capabilities of glc/ms/comp make it the method of choice for sample analysis. Consequently, the majority of the samples were analyzed by glc/ms/comp.

In order to study he Lewis acidity of the samples, the intensity of the 1450 cm pyridine band was also measured. Sample HYUS-8 shows a high amount of Lewis centers (Fig. 4d), relative thf HYD-400 sampl (Fig. 5c). This agrees with the absence of A1 as observed by A1 MAS-NMR for HYD samples. However, chemical analysis (Table I) indicates that there is more aluminum in this sample than in that from the unit cell constant m i urements. These differences cculd be explained considering that A1 MAS-NMR does not detect octahedral EFAL because of the low symmetry of its environment (i ). If this is so, it is remarkable that this EFAL does not show Lewis acidity as measured by pyridine ad y ption. On the other hand, if indeed thej is a small amount of A1, then the EFAL should be present as Al" outside the zeolite framework. In this case it should be present as amorphous silica-alumina. 

The presence of Pr in apatite samples, up to 424.4 ppm in the blue apatite sample, was confirmed by induced-coupled plasma analysis (Table 1.3). The luminescence spectrum of apatite with a broad gate width of 9 ms is shown in Fig. 4.2a where the delay time of500 ns is used in order to quench the short-lived luminescence of Ce + and Eu +. The broad yellow band is connected with Mn " " luminescence, while the narrow lines at 485 and 579 nm are usually ascribed to Dy and the fines at 604 and 652 nm, to Sm +. Only those luminescence centers are detected by steady-state spectroscopy. Nevertheless, with a shorter gate width of 100 ps, when the relative contribution of the short lived centers is larger, the characteristic fines of Sm " at 652 nm and Dy + at 579 nm disappear while the fines at 485 and 607 nm remain (Fig. 4.2b). It is known that such luminescence is characteristic of Pr in apatite, which was proved by the study of synthetic apatite artificially activated by Pr (Gaft et al. 1997a Gaft... 

In order to check the possibility of ci -ions luminescence in the barite lattice, activation by Ag was accomplished (Gaft et al. 2001 a). The main reason was that in all natural barite samples the Ag and Cu impurities have been determined by ICP analysis (Table 4.11). Besides that, weak orange luminescence on the tail of the strong UV band was detected in BaS04 Ag under X-ray excitation (Prokic 1979). 

---