CEM 333 Instrumental Analysis

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CEM 333 Instrumental Analysis Simon J. Garrett Room: CEM 234 Phone: 355 9715 ext 208 E-mail: garrett@cem.msu.edu Lectures: Tuesday, Thursday 9:00-9:50 am Room 136 Office Hours: Tuesdays 10:00-11:00 am CEM 333 page 1.1

Course Objectives Teach fundamentals of instrumental analysis Lecture: Discuss theory and background for (1) chemical/physical property measured (2) origin of chemical/physical property (3) instrument design and nature of response (4) signal processing and relationship between readout to property measured Laboratory: Provides hands-on experience in (1) relating lecture material to practical analysis (2) design and operation of a real instrument (3) measurements on range of instruments (4) example analyses to illustrate value of technique CEM 333 page 1.2

Introduction (Chapter 1) Classification of Analytical Methods 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 Species of interest All constituents including analyte. Matrix-analyte =concomitants Often need pretreatment - chemical extraction, distillation, separation, precipitation (A) Classical: Qualitative - identification by color, indicators, boiling points, odors Quantitative - mass or volume (e.g. gravimetric, volumetric) (B) Instrumental: Qualitative - chromatography, electrophoresis and identification by measuring physical property (e.g. spectroscopy, electrode potential) Quantitative - measuring property and determining relationship to concentration (e.g. spectrophotometry, mass spectrometry) Often, same instrumental method used for qualitative and quantitative analysis CEM 333 page 1.3

Types of Instrumental Methods: Property Radiation emission Example Method Emission spectroscopy - fluorescence, phosphorescence, luminescence Radiation absorption Absorption spectroscopy - spectrophotometry, photometry, nuclear magnetic resonance, electron spin resonance Radiation scattering Radiation refraction Radiation diffraction Radiation rotation Electrical potential Electrical charge Electrical current Electrical resistance Mass Mass-to-charge ratio Rate of reaction Thermal Radioactivity Turbidity, Raman Refractometry, interferometry X-ray, electron Polarimetry, circular dichroism Potentiometry Coulometry Voltammetry - amperometry, polarography Conductometry Gravimetry Mass spectrometry Stopped flow, flow injection analysis Thermal gravimetry, calorimetry Activation, isotope dilution (Often combined with chromatographic or electrophoretic methods) CEM 333 page 1.4

Energy Stimulus Example: Spectrophotometry Analyte (in matrix) Instrument: spectrophotometer Stimulus: monochromatic light energy Analytical response: light absorption Transducer: photocell Data: electrical current Data processor: current meter Readout: meter scale Analytical Response Data encoded information Data Domains: way of encoding analytical response in electrical or non-electrical signals. Interdomain conversions transform information from one domain to another. Photocell Current Meter Light Intensity Current Scale 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 CEM 333 page 1.5

Non-Electrical Domains Physical (light intensity, color) Chemical (ph) Scale Position (length) Number (objects) Electrical Domains Current Voltage Charge Frequency Pulse width Phase Count Serial Parallel Time - vary with time (frequency, phase, pulse width) Analog - continuously variable magnitude (current, voltage, charge) Digital - discrete values (count, serial, parallel, number*) CEM 333 page 1.6

Digital Binary Data Advantages (1) easy to store (2) not susceptible to noise 4th bit 3rd bit 2nd bit 1st bit Hi Lo Count Hi Lo 2 2 2 1 2 0 Serial Hi Lo Hi Lo Hi Lo 3 separate signals 2 0 2 1 2 2 Parallel 20=1, 21=2, 22=4... CEM 333 page 1.7

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 CEM 333 page 1.8

Precision - Indeterminate or random errors Absolute standard deviation: s = Variance: s 2 i= N i 0 ( x i x) 2 N 1 Relative standard deviation: RSD = s x Standard deviation of mean: s m = s N Accuracy - Determinate errors (operator, method, instrumental) Bias: bias = x x true Sensitivity S = dsignal c + Signal blank Calibration sensitivity: dc = mc + Signal blank (larger slope of calibration curve m, more sensitive measurement) Detection Limit Signal must be bigger than random noise of blank Minimum signal: Signal min = Av. Signal blank + ks blank From statistics k=3 or more (at 95% confidence level) CEM 333 page 1.9

Dynamic Range At detection limit we can say confidently analyte is present but cannot perform reliable quantitation Level of quantitation (LOQ): k=10 Limit of linearity (LOL): when signal is no longer proportional to concentration LOL Dynamic range: 10 2 to > 10 6 LOQ Selectivity: 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). CEM 333 page 1.10

Calibration methods Basis of quantitative analysis is magnitude of measured property is proportional to concentration of analyte Signal [x] or Signal = m[x]+ Signal blank [x]= Signal Signal blank m Calibration curves (working or analytical curves) Instrument Response (Signal) Signal blank LOQ DL Dynamic Range Slope m LOL [x] CEM 333 page 1.11

Example (if time): Analyte Concentration (ppm*) Absorbance 0.0 (blank) 0.05 0.9 0.15 2.0 0.24 3.1 0.33 4.1 0.42 Define Variance and Covariance: (x S xx = i x) 2 S xy = N 1 x = 2.02 y = 0.238 (x i x)(y i y) N 1 ( ) *ppm=1 µg per L S xx = 2.022 +1.12 2 + 0.02 2 +1.08 2 + 2.08 2 = 10.828 = 2.707 4 4 ( 2.02 0.188)+ ( 1.12 0.088)+ ( 0.02 0.002)+... S xy = 4 = 0.9562 = 0.23905 4 Slope: m = S xy Sx = 0.23905 2.707 = 0.0883 b = y mx Intercept: = 0.238 (0.0883 2.02) = 0.0596 Calibration expression is Absorbance=0.0883[Analyte (ppm)]+0.0596 CEM 333 page 1.12