| Instructors: | |
| Upali Siriwardane, CTH 311, Phone: 257-4941) | |
| Frank Ji, CTH 343/IfM 218, Phone: 257-4066/5125 Dale L. Snow, Office: CTH 331,Phone: 257-4403 | |
| Jim Palmer, BH 5 /IfM 121, Phone: 572885/5126 | |
| Bill Elmore, BH 222 /IfM 115 Phone: 257-2902/5143 | |
| Marilyn B. Cox, Office: CTH 337, Phone: 257-4631 | |
| REQUIRED TEXT: Principles of
Instrumental Analysis, 5th Edition, Douglas A. Skoog F. James Holler and Timothy A. Nieman. |
|
| . |
| Atomic Absorption & Fluorescence Spectroscopy (Upali) | |
|
6. An Introduction to Spectrometric Methods. 9. Atomic Absorption and Atomic Fluorescence Spectrometry. |
|
| Ultraviolet/Visible Spectroscopy(Snow) | |
| 13. An Introduction to Ultraviolet/Visible Molecular Absorption Spectrometry. | |
| 14. Applications of Ultraviolet/Visible Molecular Absorption Spectrometry. | |
| Infrared Spectrometry( Frank Ji) | |
| 16. An Introduction to Infrared
Spectrometry. 17. Applications of Infrared Spectrometry. |
|
| Nuclear Magnetic Resonance
Spectroscopy) (Upali) 19. Nuclear Magnetic Resonance Spectroscopy. |
|
| Mass Spectrometry (Palmer/Upali/Cox 20. Molecular Mass Spectrometry. |
|
| Gas Chromatography ( JimPalmer) | |
|
26. An Introduction to Chromatographic Separations. 27. Gas Chromatography. |
|
| High-Performance Liquid Chromatography (Bill Elmore) 28. High-Performance Liquid Chromatography. |
|
| Special Topics (Upali) | |
| 12. Atomic X-Ray Spectrometry. | |
| 31. Thermal Methods |
| art of recognizing different substances & determining their constituents, takes a prominent position among the applications of science, since the questions it enables us to answer arise wherever chemical processes are present. | |
| 1894 Wilhelm Ostwald |
You don’t need a course to tell you how to run an instrument
| They are all different and change | |
| Most of you won’t be analysts | |
| We will talk about experimental design | |
| Learn about the choices available and the basics of techniques |
| Why? Is sample representative | |
| What is host matrix? | |
| Impurities to be measured and approximate concentrations | |
| Range of quantities expected | |
| Precision & accuracy required |
| Send it off for analysis | |
| Do simple extractions | |
| Separation and identification by GC/MS | |
| Over 100 peaks but problem was in a valley between peaks (compare) | |
| Iodocresol at ppt | |
| Eliminate iodized salt that reacted with food coloring (creosol=methyl phenol) |
| • The digits in a measured quantity that are known exactly plus one uncertain digit. |
| Rule 1: To determine the number of significant figures in a measurement, read the number from left to right and count all digits, starting with the first non-zero digit. | |
| A. Precision – the reproducibility of a series of measurements. | |
| B. Accuracy – How close a measured value is to the known or accepted value. |
Performance Characteristics: Figures of Merit
| How to choose an analytical method? How good is measurement? | |
| How reproducible? - Precision | |
| How close to true value? - Accuracy/Bias | |
| How small a difference can be measured? - Sensitivity | |
| What range of amounts? - Dynamic Range | |
| How much interference? - Selectivity | |
| Ea = Es + Er | |
| Absolute error in a measurement arises from the sum of systematic (determinate) error and random (indeterminate) error. | |
| B. Random Error - Uncertainty in a measurement arising from an unknown and uncontrollable source . | |
| (Also commonly referred to as Noise.) |
IV. Statistical Treatment of Random Error (Er)
| A large number of replicate measurements result in a distribution of values which are symmetrically distributed about the mean value. |
| 68.3% of measurements will fall within ± s of the mean. |
| Random fluctuations | |
| Bell shaped curve | |
| Mean and standard deviation | |
| 1sigma 68.3%, 2sigma 95.5%, 3sigma 99.7% | |
| Absolute Vs Relative standard deviation | |
| Accuracy and its relationship to the measured mean |
| Population Mean (m) | |
| 2. Population Standard Deviation (s) | |
| 3. Population Variance (s2) |
| 4. Sample Mean (x) | |
| 5. Sample Standard Deviation (s) | |
| 6. Sample Variance - s2 |
| Population Mean (m) | |
| 2. Population Standard Deviation (s) | |
| 3. Population Variance (s2) |
| 4. Sample Mean (x) | |
| 5. Sample Standard Deviation (s) | |
| 6. Sample Variance - s2 |
| Detection limits | |
| Dynamic range | |
| Interferences | |
| Generality | |
| Simplicity |
| Data Domains: way of encoding analytical response in electrical or non-electrical signals. | |
| Interdomain conversions transform information from one domain to another. | |
| Detector (general): device that indicates change in environment | |
| Transducer (specific): device that converts non-electrical to electrical data | |
| Sensor (specific): device that converts chemical to electrical data | |
h(t) = a cos 2 pi freq. x time
| sum = cos(2pi((f1+f2)/2)t | |
| beat or difference = cos(2pi((f1-f2)/2)t | |
| 5104-sine-wa |
| Analyte - the substance being identified or quantified. | |
| Sample - the mixture containing the analyte. Also known as the matrix. | |
| Qualitative analysis - identification of the analyte. | |
| Quantitative analysis - measurement of the amount or concentration of the analyte in the sample. | |
| Signal - the output of the instrument (usually a voltage or a readout). | |
| Blank Signal - the measured signal for a sample containing no analyte (the sample should be similar to a sample containing the analyte) | |
| A standard (a.k.a. control) is a sample with known conc. of analyte which is otherwise similar to composition of unknown samples. | |
| A blank is one type of a standard without the analyte. | |
| A calibration curve - a plot of signal vs conc. for a set of standards. | |
| The linear part of the plot is the dynamic range.lin | |
| Linear regression (method of least squares) is used to find the best straight line through experimental data points. | |
| S = mC + Sbl | |
| where C = conc. of analyte; S = signal of instrument; m = sensitivity; Sbl = blank signal. The units of m depend on the instrument, but include reciprocal concentration. | |
| Avoid (cool, shield, etc.) | |
| Electronically filter | |
| Average | |
| Mathematical smoothing | |
| Fourier transform |
| signal - output measured as difference between sample and blank (averages) | |
| noise - std dev of the fluctuations of the instrument output with a blank | |
| S/N = 3 for limit of detection | |
| S/N = 10 for limit of quantitation |
| The limit of detection (LOD) is the conc. at which one is 95% confident the analyte is present in the | |
| sample. The LOD is affected by the precision of the measurements and by the magnitude of the blanks. | |
| From multiple measurements of blanks, determine the standard deviation of the blank signal sbl | |
| Then LOD = 3sbl /m where m is the sensitivity. |
| The limit of quantitation LOQ is the smallest conc. at which a reasonable precision can be obtained (as expressed by s). The LOQ is obtained by substituting 10 for 3 in the above equation; | |
| i.e., LOQ = 10sbl /m. | |
| Ex. In the earlier example of absorption spectroscopy, the standard deviation of the blank absorbance for | |
| 10 measurements was 0.0079. What is the LOD and LOQ? | |
| sbl = 0.0079; m = 0.0665 ppm-1 ; LOD = 3(0.0079)/(0.0665 ppm-1 ) = 0.36 ppm | |
| LOQ = 10(0.0079)/(0.0665 ppm-1 ) = 1.2 ppm | |