Instrumental methods of analysis

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Instrumental methods of analysis By Dr Hisham Ezzat Abdellatef Prof. of Analytical Chemistry Background: Analytical Chemistry: The Science of Chemical Measurements. Analyte: The compound or chemical species to be measured, separated or studied Types of analytical methods: 1.) Classical Methods (Earliest Techniques) a.) Separations: precipitation, extraction, distillation b.) Qualitative: boiling points, melting points, refractive index, color, odor, solubilities c.) Quantitative: titrations, gravimetric analysis 2.) Instrumental Methods (~post-1930 s) a.) Separations: chromatography, electrophoresis, etc. b.) Qualitative or Quantitative: spectroscopy, electrochemical methods, mass spectrometry, NMR, radiochemical methods, etc. Qualitative instrumental analysis is that measured property indicates presence of analyte in matrix Quantitative instrumental analysis is that magnitude of measured property is proportional to concentration of analyte in matrix

CHOOSING AN ANALYTICAL METHOD 1. What are the advantages or disadvantages of the technique versus other methods? 2. How reproducible and accurate is the technique? 3. How much or how little sample is required? 4. How much or how little analyte can be detected? 5. What types of samples can the method be used with? 6. Will other components of the sample cause interference? 7. Other factors: speed, convenience, cost, availability, skill required. Page 2 Page 2 Types of Instrumental Methods: Example methods Radiation emission Emission spectroscopy, fluorescence, phosphorescence, luminescence Radiation absorption Absorption spectroscopy, photometry, spectrophotometry, NMR Electrical potential Electrical charge Electrical current Electrical resistance Mass-to-charge ratio Potentiometry Coulometry Voltammetry - amperometry, polarography Conductometry Mass spectrometry Example: Spectrophotometry Instrument: spectrophotometer Stimulus: monochromatic light energy Analytical response: light absorption

Transducer: photocell Data: electrical current Data processor: current meter Readout: meter scale Page 3 Page 3 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 Performance Characteristics: Figures of Merit: How to choose an analytical method? How good is measurement? How reproducible? - Precision How close to true value? - Accuracy How small a difference can be measured? - Sensitivity What range of amounts? - Dynamic Range How much interference? Selectivity 1. Accuracy: The degree to which an experimental result approaches the true or accepted answer. Ways to Describe Accuracy: Error: An experimental measure of accuracy. The difference between the result obtained by a method and the true or accepted value. Absolute Error = (X m) Relative Error (%) = 100(X m)/m where: X = the experimental result m = the true result All Methods, except counting, contain errors don t know true value

2. Precision: The reproducibility of results. The degree to which an experimental result varies from one determination to the next. Accuracy indicates proximity of measurement results to the true value, precision to the repeatability or reproducibility of the measurement Page 4 Page 4 Ways to Describe Precision: Range: the high to low values measured in a repeat series of experiments. Standard Deviation: describes the distribution of the measured results about the mean or average value.

Absolute Standard Deviation (SD): S i N i 0 ( X i X ) N 1 SD Relative Standard Deviation (RSD): RSD(%) ( )100 X where: n = total number of measurements X i = measurement made for the trial X = mean result for the data sample 2 Page 5 Page 5 3. Response: The way in which the result or signal of a method varies with the amount of compound or property being measured. Ways to Describe Response: Calibration Curve: A plot of the result or signal vs. the known amount of a known compound or property (standard) being measured. A calibration curve plot showing limit of detection (LOD), limit of quantification (LOQ), dynamic range, and limit of linearity (LOL). Calibration expression is Absorbance = slope [Analyte (ppm)] + intercept

Parameters used to Describe a Calibration Curve: S = mc + S bl S measured signal c analyte concentration S bl instrument signal for blank m - slope Page 6 Page 6 Sensitivity: ability to discriminate between small differences in analyte concentration. Slope and reproducibility of the calibration curve. (Larger slope of calibration curve m, more sensitive measurement) Selectivity: degree to which the method is free from interference by other species the sample No analytical method is completely free from interference by concomitants. Best method is more sensitive to analyte than interfering species (interferent). Matrix with species A&B: Signal = m A c A +m B c B + Signal blank Selectivity coefficient: k B,A = m B /m A k's vary between 0 (no selectivity) and large number (very Selective).

Interested in detecting species A, but signal will be a combination of signal from the presence of species A and species B. Calibration methods Basis of quantitative analysis is magnitude of measured property is proportional to concentration of analyte Page 7 Page 7 Signal α[ x ] or Signal = m[x]+ Signal blank [ ] Dynamic Range: linear region of calibration curve where the lower limit is ten times the standard deviation of the blank. LOQ - limit of quantitation LOL - limit of linearity Detection Limit: The smallest [analyte] that can be determined with statistical confidence. Analyte must produce an analytical signal that is statistically greater than the random noise of blank. (i.e. analytical signal = 2 or 3 times std. dev. of blank measurement (approx. equal to the peak-peak noise level). Calculation of detection limit The minimum detectable analytical signal (Sm) is given by: Sm = Sbl + k(stdbl); for detection use k =3 To Experimentally Determine Perform 20 30 blank measurements over an extended period of time. Treat the resulting data statistically to obtain S bl (mean blank signal) and stdbl (std. dev. of blank signals). Use these to obtain S m value. Using slope (m) from calibration curve. Detection limit (Cm) is calculated by: (Rearranged from Sm = mc + Sbl)