Instrumental Methods PDF

INTRODUCTION TO INSTRUMENTAL METHODS  CLASSIFICATION OF ANALYTICAL METHODS Qualitative analysis – a measured property indicates the presence of an analyte. – Classical methods-Carried out by separating the components by precipitaion, extraction, etc and then the...

INTRODUCTION TO INSTRUMENTAL METHODS  CLASSIFICATION OF ANALYTICAL METHODS Qualitative analysis – a measured property indicates the presence of an analyte. – Classical methods-Carried out by separating the components by precipitaion, extraction, etc and then the separated components were treated with reagents to give products that could be recognized by: Color change, Solubility, Odor, Optical activity, BP, MP Quantitative analysis – the magnitude of a measured property indicates the concentration of a an analyte – Classical methods Gravimetric and volumetric  INSTRUMENTAL METHODS Began with electrical and absorption measurements (early 20th century). Properties of analytes shown below were used for quantitative analysis Light absorption or emission Fluorescence pH Electric potential and current Mass to charge ratio New separation techniques replaced the classical methods of separations. TYPES OF INSTRUMENTAL METHODS Radiation emission Emission spectroscopy-fluorescence, phosphorescence, luminescence Radiation absorption Absorption spectroscopy – spectrophotometry, photometry, NMR, ESR Radiation Scattering Turbidity, Raman Radiation refraction Refractometry, interferometry Radiation diffraction X-ray, electron Radiation rotation Polarimetry Electrical potential Potentiometry TYPES OF INSTRUMENTAL METHODS (CONTD.) Electrical charge Coulometry Electrical current Voltammetry Electrical resistance Conductometry Mass Gravimetry Mass to charge ratio Mass spectrometry Thermal Calorimetry Radioactivity Activation, isotope dilution  THE ANALYSIS CONCEPT PROBE RESPONSE Sample For Electrons, photons, atoms, Heat, ions, molecules, molecules, ions, heat Analysis atoms, photons, electrons  INSTRUMENT Any instrument converts information stored as chemical or physical characteristics into information that can be manipulated by humans To obtain the desired information from the analyte, stimulus is given in the form of EM, electrical or nuclear energy. Some examples of instrument components are shown on table 1.2  AN INSTRUMENT Controls the applied probe. Measures the system’s response. Instrument Encodes Data Transformation The Physical and The Analyst’s Chemical Domain Domain  DATA DOMAINS The measurements process is aided by devices that convert information from one form to another, that is they help to understand how the information measured is encoded. There are various forms of encoding information and are: – Non-electrical domains – Electrical domains  EXAMPLES OF DATA DOMAINS: Non-electrical domains Electrical domains Physical properties Current (light intensity, color). Voltage Chemical properties Charge (pH) Frequency Scale position Pulse width (length) Phase Number (objects) Count Serial parallel  DOMAIN CONVERSION An analyst seeks to measure the physical or chemical properties of a system. An instrument creates an electrical signal which represents this datum. Data proceeds through the instrument where different transducers convert the signal from one domain to another. The analysis of an instrument’s behavior proceeds by characterizing it as a sequence of data domain converters which can each be analyzed separately. DATA DOMAINS – WAY OF ENCODING AN ANALYTICAL RESPONSE Inter domain conversions transform information from one domain to another. photocell Current meter Light intensity à current à scale Some definitions: – Detector: device that indicates a change in the environment. – Transducer: device that converts non-electrical data to electrical data and the converse. – Sensor: device that converts chemical data to electrical data. Monitors specific chemical species continuously and reversibly. (glass electrode) INSTRUMENTAL MEASUREMENT EXAMPLE SPECTROPHOTOMETRY – Instrument: Spectrophotometer – Stimulus: monochromatic light energy – Analytical response: light absorption – Transducer: photocell – Data: electrical current – Data processor: current meter  HOW DO WE CHOOSE AN ANALYTICAL METHOD? Which instrument is the appropriate one for our measurement? We base it on the performance characteristics of our technique – figures of merit. How good is the measurement technique? – How reproducible? Precision – How close to the true value? Accuracy/bias – How small a difference can be measured? Sensitivity – What range of amounts can be measured? Dynamic range – How much interference? Selectivity  PERFORMANCE CHARACTERISTICS The following criteria can be used to decide if a given instrumental method is suitable for attacking an analytical problem. These are expressed in numerical terms called Figure of Merit and help to narrow the choice of instruments. Precision Accuracy Bias Sensitivity Detection Limit Quantitation Limit Linearity Limit Dynamic Range Selectivity  FIGURE OF MERIT A figure of merit is a number which has been derived experimentally for a given analytical instrument or technique that permits an evaluation or comparison of the technique to assess its applicability to a particular analysis problem. Performance characteristics is measured in terms of figures of merit.  PRECISION Mutual agreement of replicate measurements. The standard deviation and the variance are the most common measurements of a set of data’s precision. RSD and CV are also figure of merit. It is a result of random errors.  Bias Bias provides a measure of the systematic or determinate error of an analytical method and is defined as – Bias = µ –Xt µ is population mean and Xt is true concentration. – Determined by running a number of standard reference materials, 20-30 replicate analysis – Bias can be eliminated by the use of blank or by instrument calibration.  Accuracy Arises from the presence of determinate errors, or non-random errors. This shifts the measured mean value of a set of measurements away from the true value and is referred to as the error of the mean. Three types of such errors: Instrumental: something wrong with the instrument (batteries low, temperature effects the circuitry, calibration errors, etc. Personal: judgment errors, reading the meter from the wrong angle, lack of careful technique. Method: often a result of non-ideal chemical behaviour; slow reactions, contaminants, instability of reagents, loss of analyte by adsorption. Must use guaranteed standards (NIST).  Sensitivity Is a measure of an instrument or method’s ability to discriminate between small differences in anlyte concentration. How much does the signal change for a change in the measured variable? Two factors dictate a technique’s sensitivity: 1. Slope of calibration curve. The larger the slope, the more sensitive the measurement. 2. Precision or reproducibility of measurement. High Precision = High Sensitivity High Sensitivity Low Sensitivity Low Precision = Low Sensitivity  Calibration Sensitivity Slope of calibration curve (most curves are made linear) at concentration of interest.. S = m C + Sbl Blank signal (y-intercept) signal slope concentration m is the calibration sensitivity. The calibration sensitivity is independent of concentration. This is not the best figure of merit as it has no measure of the precision.  Analytical Sensitivity Incorporate precision g = m/s Analytical sensitivity factor Standard deviation of measurement Slope of calibration response Not affected by amplification. Increase in gain, increases m and s by similar amount. Independent of measurement units but does depend upon concentration since s can vary with concentration.  Detection Limit This is the smallest amount of analyte that can be reliably detected. Depends upon signal/noise ratio. Analysis signal must be larger than blank signal. How much larger? Sm = Sbl + k sbl Standard deviation on blank signal Minimum distinguishable analytical signal, determined by Usually taken to be 3 Mean blank signal Performing 20-30 blank Measurements. Detection limit cm = (Sm-Sbl)/m, Sbl = mean of blank measurement A student analyzed the iron content in a vitamin tablet by AAS method. The results for the standard solutions and unknown are given on the following table along with the calibration curve. [Fe2+], No. of ppm repeats Mean Absorbance Standard deviation 0 25 0.0151 0.0079 1 5 0.0865 0.0094 3 5 0.211 0.0084 5 5 0.351 0.0084 7 5 0.478 0.0085 9 5 0.624 0.011 Unknown 5 0.374 0.0085 Detn of Fe in vitamine tablet y = 0.0671x + 0.0148 0.8 2 R = 0.9996 Absorbance 0.6 0.4 0.2 0 0 2 4 6 8 10 [Fe2+], ppm a. What is the calibration sensitivity of the instrument? b. Find the analytical sensitivity at analyte concentration of 5 ppm and 9 ppm. c. Find the coefficient of variations at the two concentrations given in b. d. What is the detection limit for the method? e. What is the concentration of the unknown?  Dynamic Range This is the region between the Quantitation Limit (LOQ -Limit of Quantitation) and the Linearity Limit (LOL - Limit of Linearity). This is the range over which the technique is useful. To be viewed as a worthwhile, a technique should have a dynamic range of at least two orders of magnitude. Many techniques have a dynamic range of five to six orders of magnitude. (Fig 1.13)  Quantitation Limit The detection limit answers the question “Is this analyte present or not?” However, to actually answer the question “How much of the analyte is present?” requires a still larger signal. The widely accepted level at which the analyte can be quantified is TEN times the standard deviation. (Detection is THREE times.) Sq = Sbl + 10 sbl  Linearity Limit As the concentration or intensity increases, at some point, every detector stops responding linearly. This identifies the upper limit of concentration to which the technique can be successfully applied. Its origin can be electrical (the amplifier cannot produce a larger output voltage) or mechanical (the balance arm breaks under this load) in nature. Instrument response Linearity Limit Concentration  Signals and Noise Every analytical measurement has two components: – Signal (S)– carries information about the analyte. – Noise (N) – extraneous information that degrades the performance of our analysis. Typically the strength of N is constant and independent of S. Therefore N isn’t important until S becomes small.  Signal Every analytical procedure depends upon a signal which is derived from the output of the detector. Every analytical instrument has a non-zero output, even when no difference is present at the inputs to the detector. This non-zero output is called the background or baseline. This background is often slowly varying in time. This changing background is called drift. The analytical signal is the difference between the output amplitude and the expected baseline at the same moment in time.  Noise There are other variations in the output signal level; they can occur at all frequencies and constitute an unwanted random or almost random time-dependent changes in the output. These variations are collectively called noise. Noise is measured in the same units as the signal. This can be current, voltage, or power.  Signal-to-Noise The determination of the magnitude of the analytical signal level requires measuring the difference between the background and the sample signal. This measure is blurred by the presence of noise. One has to account for both the signal level and the noise level in arriving at this measure. Because of this, the important quantity is not the signal level alone nor is it the noise level alone; rather it is the ratio of the two that dictates the measurability of the signal level. This is the signal-to-noise ratio or simply S/N. S mean x = = N standard deviation s  Signal-to-noise ratio S mean x 1 = = = N standard deviation s RSD A. Small S/N B. Large S/N We always want to increase S while decreasing N to give a large S/N.  Sources of Instrumental Noise Chemical Noise – arises from uncontrollable variables that affect the chemistry of the system being analyzed. – Temperature and pressure fluctuations can shift chemical equilibria. – Humidity changes can affect the moisture content in the sample. – Changes in light intensity may affect photosensitive materials. – Gases in the lab may interact with the sample. Instrument Noise – Thermal noise or Johnson noise – caused by thermal agitation of electrons or other charge carriers in the circuits of the instrument. Sometimes called white noise. – Shot noise – encountered wherever electrons cross a junction. They randomly jump across (governed by quantum mechanics and is sometimes called quantum noise) causing statistical fluctuations in the current.  Sources of Instrumental Noise Instrument Noise – Flicker noise – Has a magnitude that is inversely proportional to the frequency. Sometimes called 1/f (one-over-f) noise. The cause is not really understood. – Environmental noise – comes from the surroundings. Conductors inside the instrument behave as antenna that can convert electromagnetic radiation to an electrical signal.  Hardware Devices for Noise Reduction Grounding and Shielding – surround a circuit with a conducting material that is attached to ground. EM radiation will then be absorbed by the shield and sent to ground. Very effective against environmental noise. Difference Amplifiers – a difference amplifier is a circuit used to subtract out the noise. Analog filtering – many instrument signals are of low frequency. – So use a low-pass filter to remove high-frequency interference. Modulation – Amplification of a low frequency or dc signal causes an amplification of the 1/f noise. 1. The low-frequency signal is modulated to higher frequency. 2. The 1/f noise is removed with a high pass filter. 3. The signal is then demodulated back to low frequency. 4. The low frequency, less noisy signal is then amplified.