2302548 Sample Preparation for Chemical Analysis 1 Analytical Perspective Homogenization Sample Reduction Analytes Semivolatile Volatile Sample Metals ions DNA/RNA Solid Liquid Biological Sa m Gas pl in g Aqueous Semi-solid Extraction Information Concentration Clean-up Preservation Sample Preparation Methods • Accuracy • • • • • Precision Cost Qualitative Labor Quantitative Time Automation Chromatography Spectroscopy Analysis 2 Common instrument methods and the necessary sample preparation prior to analysis Analytes Sample preparation Instrument Organics Extraction, concentration, cleanup, derivatization GC, HPLC, GC/MS, LC/MS Volatile organics Transfer to vapor phase, concentration GC, GC/MS Metals Extraction, (derivatization) concentration, speciation AA, GFAA, ICP, ICP/MS, UV-VIS, IC Ions Extraction, concentration, derivatization UV-VIS, IC DNA/RNA Cell lysis, extraction, PCR CE, UV-VIS, Fluorescence Amino acids, fats, carbohydrates Extraction, cleanup GC, HPLC, CE Microstructures Etching, polishing, reactive ion techniques, ion bombardments, etc. SEM, microscopy, surface spectroscopy Mitra, S. editor, “Sample Preparation Techniques in Analytical Chemistry,” John Wiley & Sons, Inc. 2001. 3 Method of Quantitation z Calibration against chemical standards z If there is extraction step involved: measure recovery of spiked known amount of analyte to the matrix z Sample preparation is usually matrix dependent 4 Calibration curves Signal • Matrix of the standard should be as close to the samples as possible • Standards of known concentrations should cover the concentration range expected in the sample LOD (3 x S/N) Limit of linearity LOQ (10 x S/N) Analyte concentration 5 How to prepare calibration curve? z Pb in soil: Acid digestion and AAS 1. Standards are prepared by spiking clean soil with known amounts of Pb and taken through entire process of digestion and analysis (more accurate) 2. Standards are used to calibrate only the AA (simpler) 6 Errors in Quantitative Analysis: Accuracy and precision Mean − True value Accuracy = True value Measure of systematic error Measure of reproducibility affected by random error Σx i x= n Σ(x i − x ) 2 σ= n Σ(x i − x ) 2 s= n −1 Coefficient of variation (CV) or relative standard deviation (RSD) RSD = s x s %RSD = × 100 x 7 Horwitz Curve 70 60 Sample preparation accounts for majority of the variability Alflatoxins Relative Standard Deviation 50 40 Pesticides Drug residues in feeds 30 20 Random and systematic errors are higher during sample preparation than during analysis Pharmaceuticals 10 0 -10 Major components -20 -30 Minor components -40 Minimize the number of steps Trace analysis -50 -60 -70 1 1.E-02 1.E-04 1.E-06 1.E-08 1.E-10 Concentration V. Meyer, LC-GC North Am., 20, 106-112, 2 (2002) 1.E-12 8 Sources of Error in Sample Preparation and Analysis Sample Processing Operator Contamination Calibration Chromatography Instrumentation Columns Integration Sample Introduction Other 0 10 20 30 40 50 Percentage of Respondents Ronald E. Majors, Trends in Sample Preparation, LC-GC, Vol. 14, No. 9, 1996 9 Number of Sample Preparation Techniques Required per Sample Average Number Respondents (%) Respondents (%) (1996) (2001) 1 11.1 19.3 2 28.4 28.6 29.1 3 20.7 4 12.0 15.0 5 6.5 8.6 6 12.9 2.1 7 0.7 >7 5.0 10 Time spent in analytical process Sample preparation 60% Sample collection and data handling 33% Actual measurement 7% 11 Merit for instruments or analytical methods No. Parameter Definition 1. Accuracy Deviation from true value 2. Precision Reproducibility of replicate measurements 3. Sensitivity Ability to discriminate between small differences in concentration 4. Detection limit Lowest measurable concentration 5. Linear dynamic range Linear range of the calibration curve 6. Selectivity Ability to distinguish the analyte from interferences 7. Speed of analysis Time needs for sample preparation and analysis 8. Throughput Number of samples that can be run in a given time period 9. Ease of automation How well the system can be automated 10. Ruggedness Durability of measurement, ability to adverse conditions 11. Portability Ability to move instrument around 12. Greeness Ecoefficiency in terms of waste generation and energy consumption 13. Cost Equipment cost + cost of supplies + labor cost 12