V. LAB REPORT. PART I. ICP-AES (section IVA)

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V. LAB REPORT The lab report should include an abstract and responses to the following items. All materials should be submitted by each individual, not one copy for the group. The goal for this part of the report is for each person to take the large amount of raw data generated by the commercial instruments, sort through it, and organize it into a tabulated form that is easy to reference and use. That is exactly what you would do if you were using a modern instrument on an research project. Use the table numbers and column letters given below to identify the information and give each table a title. Include a table of contents as a first page when you have completed the tables for your report, and please number all pages of your report at the center bottom position of each page. Show sample calculations for one element in each case where called for. Use units and proper significant figures in reporting values. You should be able to copy and paste much of the information called for in the tables using the data reports from the instruments, either as ASCII format (text), or Excel directly. If Text you can open in Excel and select text to columns and Excel can help interpret what data goes in what column but sometimes you still have to edit in excel to make this useful. You should not be typing values into tables by hand except occassionally. PART I. ICP-AES (section IVA) 1. Raw data generated by ICP-AES. Each group member will have a copy of the Excel files generated during the run. Cut and paste as required from these spreadsheets to create the requested tables below. Table 1. Instrumental Method Parameters. Include the following parameters which are found in the spreadsheets, except where noted, for each element in your method. Use the following six column designators in Table 1: A. wavelength for the analytical line B. wavelength for the background correction C. peak integration time (from method setup-acquisition) D. slit widths (from method setup-acquisition) E. PMT bias voltage F. PMT electronic gain Table 2. Calibration Method Information. Note that the program automatically determines the best calibration curve equation and that it may be a higher order polynomial fit. Include the following parameters which are found in the spreadsheets, except where noted, for each element in your method. Use the following five column headers in Table 2: A. element B. nominal concentration of standard C. net intensity for standard D. calculated concentration for standard (obtained from printed output for calibration) E. calibration equation (e.g., slope, coefficients, intercept values) for each element (in both printed output from calibration run, and in each spreadsheet for each sample analysis) Nov 8/2013; EXP_4_13 updated for report_last.wpd Ingle, Pastorek, Westall 1

Table 3. Analysis Results for each real sample and for each element in your method that you analyzed for. Use the following six column headers in Table 3: A. sample name B. element name C. average net intensity for element (NetInt.) D. average calculated concentration for element in ng/ml(conc) E. standard deviation for conc for element (SD) F. relative standard deviation for conc for element (RSD) Table 4. Detection Limits. This is based on the standard deviation for each element as determined using the 2% HNO 3 blank run with 15 replicates for each element in your method. For the JY ICP, the software reports the blank standard deviation in concentration units. The stdev blank is already divided by the slope and this means that in the report, stdev bk is already given in conc units. Hence, DL = 3 X stdev bk in this ICP case. Include a sample calculation as a footnote to the table for one element. Use the following three column headers for Table 4: A. element name B. SD in ng/ml C. DL in ng/ml 2. Presentation of Analysis Calculations. Table 5. For each type of sample, report the information specified in the Table 5 template below from the ICP-AES analysis. If the measured value for the concentration of a particular element in a test solution is below the calculated detection limit, report the concentration as not detected or write ND for that element. This includes negative numbers - they are negative due to deviations around zero - so any reported concentration that is negative is listed as 0" and obviously below the DL. Use the proper number of significant figures. For example, the number of significant figures is rarely ever greater than 3 for concentration data, and only 2 significant figures should be reported for SD, RSD, and the DL. 2

Table 5. Detection Limits and Elemental Concentrations in ng/ml for Test Solutions including % RSD from ICPAES. Elements Tested DL (ng/ml) Syn Unk Ca Cu continue with Al,Fe, Pb, Zn and your group s element of choice Conc STD RSD Conc STD RSD Mixed Std- 1 μg/ml you made Tap water Multimineral tablet 1 Multimineral tablet 2 Clam or Oyster Yogurt SRM 3. Final Sample Results. Prepare Tables 6-8 as described below. Back-calculate to relate your results to the values listed on the original containers or given on the USDA web page. As footnote to Table 6, give one sample calculation all the way through for one element for each type of sample in Table 6. Use proper units and significant figures. 3

Table 6. Mass in a Typical Serving or Tablet found from your data. Include at least the following nine columns: Sample Name Original Sample Mass, g Test Solution Total Volume, ml Dilution Factor Element Name Test Solution Conc., ng/ml mg Element/ g Sample Typical Sample Serving Size, g mg Element /Serving Yogurt (make separate row for each element) Multi vitamin 1 powder: whole tablet: (make separate row for each element) Multi vitamin 2 powder: whole tablet: (make separate row for each element) Oyster or Clam (make separate row for each element) 4

Table 7. Comparison to expected mass values for Vitamin Tablet. Report in Table 7 for each of the eight elements (Al, Ca, Cu, Fe, Zn, Pb, + element of your choice), the mass (mg/tablet) found for multivitamin 1 and multivitamin 2 (from Table 6), the average of these two values, the absolute value of the range between these two values, the percent deviation from the mean in duplicate measurements (% deviation = (range / 2) / average x 100), the expected value for mg element/tablet listed on the container, and the percent difference between the average value you determined and the expected value for mg element/tablet on the container. Show a complete sample calculation with units and proper significant figures for one element listed in Table 7. Briefly discuss how well the observed mass agrees with the expected mass for each element. Offer some explanation for any elements that do not agree very well. Consider the differences between observed and expected mg/tablet to the % deviation in replicate measurements, as appropriate. Table 8. Comparison to %Daily Value or %DV. Report in Table 8 the sample name, name of element measured, the value for %DV for that element based on your results, %DV for that element listed on the sample container, and % difference between your measured value and the container value. Use the same samples as those in Table 6. If the element is not listed on the container show NA (not available) in the table entry. If there is no Food Labeling Guide Reference Value (FLGRV) for the element, show NA in the table entry. The FLGRV values are daily values recommended by the FDA. Turn to Appendix F.: http://www.fda.gov/food/guidanceregulation/guidancedocumentsregulatoryinformation/labelingnutrition/ucm064928.htm Calculate the Percent Daily Value (DV) for the Appropriate Nutrients in your study. Based on your results for mass per serving (in mg) listed in Table 6, calculate your experimental values for the %DV for each element as follows: %DV = mass per serving (mg) / FLGRV daily value (mg) x 100 Show a complete sample calculation with units and proper significant figures for one element listed in Table 8. Briefly discuss how well the results for each of the real samples compares to what is expected for each element Offer some explanation for any elements that do not agree between measured %DV and reported %DV. 5

4. Spectral interferences on ICPAES. Compare the spectral profile run for the standard solution and the profile run on your vitamin tablet solution for the additional element that your group chose to analyze. Is there evidence from the vitamin tablet profile that suggests that there might be other elemental spectral interferences in this same region of the spectrum? If yes, how might this affect the final reported concentration for the additional element? (Hint: what is the wavelength for the background correction point you used to determine the net peak intensities for this added element?) 5. Lab Notebook pages. Turn in your duplicate pages from your lab notebook with all sample preparation information, file names, method names, and other information. These pages should be initialed by an instructor each day. PART II. AAS (section IVB) Work up the data according to the following instructions and turn in the results. Label each item with the numbers and titles given below. Show a sample calculation with actual values and proper units and significant figures. 1. Lab Notebook pages. Turn in your duplicate pages from your lab notebook with all sample preparation information, file names, method names, and other information. These pages should be initialed by an instructor each day. 2. Nonlinear calibration (do for Copper only). Use the data for all of the calibration standards (1, 2 or 3, 5, and 10 μg/ml) and make your own calibration graph of AU vs concentration in μg/ml for Cu only in Excel. Use a polynomial to fit the data with Trendline and report the polynomial equation (coefficients should have 3 sig figs). Does the line deviate from linearity at higher concentrations? If yes, what are two possible causes of the non- linearity? 3. Table 9. Linear Calibration in Excel versus SpectraAA software. Using only the concentration range data that yields a linear calibration for each element measured, make a calibration graph of AU vs concentration in μg/ml in Excel and determine the coefficients in the linear calibration equation. Report the calibration equation and give the slope in AU per μg/ml and report the intercept. Calculate a predicted absorbance value for each standard solution based on the linear calibration equation (i.e., your results from this step should be in the same format as those from the Spreadsheet Proficiency Test). Make a Table 9 and give the % difference for the elemental concentrations for the standards calculated using Excel above, and the values reported by the SpectraAA software. Note: SpectraAA is setyo to use the New Rational algorithm to find a calibration equation. This method is not the standard linear method we use in CH 461 but is accepted as industry standard for AAS and better represents the dynamic range of calibration for flame AAS.. 4. Table 10. Concentrations of test solutions from AAS. Report the concentrations in (μg/ml) based on either the calibration equation you found using Excel in Step 3 or the values as reported by the SpectraAA software for the test samples: (a) synthetic unknown, (b) tap water, ( c) oyster or clam, (d) Multi VitC1, (e) Multi VitC2, and (f) SRM. Indicate which values you are using in the calculation for Table 10. 6

5. Characteristic Concentration. The characteristic concentration (m A ) for atomic absorption is defined as the concentration of the element that results in a transmittance of 99% T or absorbance of 0.004365. If the intercept from the least squares linear fit is non-zero, the characteristic concentration is the concentration which yields an absorbance 0.004365 above the absorbance at the intercept. Hence, m A = 0.004365/(calibration curve slope in AU per concentration unit). Calculate the characteristic concentration of for each element in ng/ml. The characteristic concentration for Cu should be less than 100 ng/ml. If the characteristic concentration value is reported in the SpectraAA software, report it also. 6. Detection Limit. Report the repetitive measurements of absorbance from the blank (reference) solution, plus the mean and the standard deviation (use at least 4 place precision). Recall that the DL = 3s bk /m where m is the slope of the calibration curve. The units of s bk are typically signal units such as volts or absorbance units. Calculate and report the AAS detection limits for each element measured in ng/ml. For Cu this should be above zero but well below 100 ng/ml and it is normally higher for Pb. Part III. Graphite Furnace Atomic Absorption Spectrometry 1. Prepare Table 11. Concentrations for Pb and Pb with modifier using GFAA (see spreadsheet Pastorek sent and now posted on the course web page). Report the concentration of the test solutions in columns given by the SpectraAA software, and include the reported SD and RSD for the seafood S3 dilution, tap water sample (TW), the SRM, and the DL. Note concentrations are given in ng/ml Give the calibration equation for each method in a footnote to Table 11. Also include three columns in your table to show the results for the back calculation of these test solutions to give mg Pb/g sample for seafood, for 8 oz of tap water, and for 1 g of the SRM oyster. Part IV. Overall Comparison for Three Techniques. 1. Table 12. List results for all three techniques for Pb only: AAS, ICP, and GFAA (you already have these values in other tables). Give the concentration of the test solutions in ng/ml for S3, TW, SRM and include SD and RSD for each plus show the DL. Include in Table 12, the expected values for Pb in the SRM with given SD, and RSD according to the certificate posted on the course web page for comparison. If you needed to determine trace levels of Pb accurately and precisely - based on your results presented in Table 12- which technique would you use and why? 2. Table 13. Present the results from ICP and flame AAS for the SRM oyster you are reporting in this work for the elements Cu, Al, and Fe so a comparison can be made for the quality of the precision and accuracy for these three elements in these two techniques. You will want to include the SD and RSD and DL s. Based on your results presented in Table 13- if you needed to determine trace levels of Cu, Al, and Fe accurately and precisely which technique would you use for each of these elements and why? 7

3. Rank AAS, ICP, GFAA techniques with a 1, 2, or 3 (where 3 is the best) for the following reasons: a. DL s for Pb - for measure of sensitivity of technique b. Comparison with SRM - for measure of accuracy of technique c.. RSD - for measure of precision of technique 8