1. chapter1
Introduction

2. Analytical Chemistry deals with methods for determining the chemical composition of samples.
Qualitative Analysis (identification) provides information about the identity of species or functional groups in the sample (an analyte can be identified).
Quantitative Analysis provides numerical information of analyte (quantitate the exact amount or concentration).

3. 1A CLASSIFICATION OF ANALYTICAL METHODS

4. 1A-1 Classical Methods: Wet chemical methods such as precipitation, extraction, distillation, boiling or melting points, gravimetric and titrimetric measurements.
1A-2 Instrumental Methods: Analytical measurements (conductivity, electrode potential, light absorption or emission, mass-to-charge ratio, fluorescence etc.) are made using instrumentation.

5. 1B Types of Instrumental Methods

6. Molecular spectroscopy
1. Spectroscopic methods:
Atomic spectroscopy
Molecular spectroscopy
2. Chromatographic methods (separations):
3. Electrochemistry:

8. 1C Instruments for
Analysis

9. An instrument for chemical analysis converts information
ahout the physical or chemical characteristics of
the analyte to information that can be manipulated
and interpreted by a human.

10. FIGURE 1-1 Block diagram showing the overall process of an instrumental measurement.

11. Data-domain map
FIGURE1-2 Data'domain map. The upper (shaded) half of the map consists of nonelectrical domains. The bottom half is made up of electrical domains. Note that the digital domain spans both electrical and nonelectrical domains.

13. 1C-1 data-domains data domains may be broadly classified into
nonelectrical domains and electrical domains.

14. 1C-2 nonelectrical domains.
The measurement process begins and ends in nonelectrical
domains. The physical and chemical information
that is of interest in a particular experiment
resides in these data domains. Among these characteristics
arc length, density, chemical composition,
intensity of light. pressure, and others listed in the firstcolumn of Table I-I.

15. 1 C-3 Electrical Domains
The modes of encoding information as electrical
quantities can be subdivided into analog domains,
time domains, and the digital domain, as illustrated in the
Bottom half of the circular map in Figure 1·2.

16. Diagram of a fluorometer
FIGURE1-3 Ablock diagram of a fluorometer showing (a)a general diagram of the instrument, (b) a diagrammatic representation of the flow of information through various data domains in the instrument. and (c) the rules governing the data·domain transformations during the measurement process.

17. Analog-Domain Signals
Information in the analog domain is encoded as the
magnitude of one of the electrical quantities - voltage,
Current, charge, or power.

18. Analog Signal of phototube
FIGURE 1-4 Analog signals. (a) Instrument response from the photometric detection system of a flow injection analysis experiment. A stream of reaction mixture containing plugs of red Fe( SCN)2+ flows past a monochromatic light source and a phototransducer, which produces a changing voltage as the sample concentration Changes. (b) The current response of a photomultipliertube when the light from a pulsed source falls on the photocathode of the device.

19. amplitudes of the signals.
Time domain signal
Information is stored in the time domain as the time
relationship of signal fluctuations, rather than in the
amplitudes of the signals.

20. Time domain signal
FIGURE 1-5 Time-domain signals. The horizontal dashed lines represent signal thresholds. When each signal is above the threshold, the signal is HI, and when it is below the threshold, the signal is LO.

21. Digital Information
Data are encoded in the digital domain in a two-level scheme. The information can be represented by the state of a lightbulb, a light-emitting diode, a toggle switch, or a logic-level signal, to cite but a few examples.The characteristic that these devices share is that
each of them must be in one of only two states. For example,
lights and switches may be only ON or OFF and logic-level signals may be only HI or LO.

22. Diagram for digital data
FIGURE 1-6 Diagram illustrating three types of digital data: (a) count serial data, (b) binarycoded senal ?ata, and (cl parallel binary data. In all three cases, the data represent the data represent the number n=5

23. 1D SELECTING AN ANALYTICAL METHOD

24. 1D-1 Defining the Problem
1. What accuracy is required?
2. How much sample is available?
3. What is the concentration range of the analyte?
4. What components of the sample might cause
Interference?
5. What are the physical and chemical properties of
the sample matrix?
6. How many samples are to be analyzed?

25. 1D-2 Performance Characteristics of Instruments
Table 1-3 lists quantitative instrument performance
criteria that can be used to decide whether a given instrumental
method is suitable for attacking an analytical
problem. These characteristics are expressed in numerical terms
that are called figures of merit. Figures of
merit permit us to narrow the choice of instruments for
a given analytical problem to a relatively few. Selection
among these few can then be based on the qualitative
performance criteria listed in Table 1-4

28. Figures of Merit Precision Bias Sensitivity Detection limit
Concentration range (Dynamic range)
Selectivity

29. Precision:
How close the same measurements are to one another. The degree of mutual agreement among data that have been obtained in the same way. Precision provides a measure of the random or indeterminate error of an analysis.
Figures of merit[or precision include absolute standard deviation, relative standard deviation, standard error of the mean,
coefficient of variation, and variance.

31. Bias:
Bias provides a measure of the systematic, or determinate error of an analytical method.
bias =  - xt, where,  is the population mean and
xt is the true value

32. Sensitivity:
Sensitivity of an instrument is a measure of its ability to discriminate between small differences in analyte concentration. The change in signal per unit change in analyte concentration. The slope of the calibration curve at the concentration of interest is known as calibration sensitivity.
S = mc + Sbl
S = measured signal; c= analyte concentration;
Sbl = blank signal; m = sensitivity (Slope of line)
Analytical sensitivity ()
 = m/ss
m = slope of the calibration curve
ss = standard deviation of the measurement

33. Detection Limit: The most generally accepted qualitative definition of
detection limit is that it is the minimum concentration
or mass of analyte that can be detected at a known confidence level.

34. Detection Limit (Limit of detection, LOD): The minimum concentration of analyte that can be detected with a specific method at a known confidence level.
LOD is determined by S/N, where, S/N = Signal-to-noise ratio = (magnitude of the signal)/(magnitude of the noise)
Noise: Unwanted baseline fluctuations in the absence of analyte signal (standard deviation of the background)
The detection limit is given by,
Cm = (Sm – Sbl)/m, where, Cm = minimum concentration i.e., LOD, Sm = minimum distinguishable analytical signal (i.e., S/N = 2 or S/N = 3), Sbl = mean blank signal
m = sensitivity (i.e., slope of calibration curve)
The amount of analyte necessary to yield a net signal equal to 2 or 3x the standard deviation of the background.

35. Dynamic Range:
The lowest concentration at which quantitative measurements can be made (limit of quantitation, or LOQ) to the concentration at which the calibration curve departs from linearity (limit of linearity, or LOL).
The lower limit of quantitative measurements is generally taken to be equal to ten times the standard deviation of repetitive measurements on a blank or 10 Sbl.
Dynamic range is the range over which detector still responds to changing concentration (at high concentrations – usually saturates – quits responding)
An analytical method should have a dynamic range of at least two orders of magnitude, usually 2-6 orders of magnitude.

36. FIGURE1-13 Useful range of an analytical method
FIGURE1-13 Useful range of an analytical method. LOQ = limit of quantitative measurement; LOL = limit of linear response.

37. Selectivity:
Selectivity: Selectivity of an analytical method refers to the degree to which the method is free from interference by other species contained in the sample matrix. No analytical method is totally free from interference from other species, and steps need to be taken to minimize the effects of these interferences. Selectivity coefficient gives the relative response of the method to interfering species as compared with analyte. Selectivity coefficient can range from zero (no interference) to values greater than unity. A coefficient is negative when the interference caused a reduction in the intensity of the output signal of the analyte.

38. 1 E Calibration of Instrumental Methods

39. Calibration of Instrumental Methods
All types of analytical methods require calibration for quantitation. Calibration is a process that relates the measured analytical signal to the concentration of analyte. We can’t just run a sample and know the relationship between signal and concentration without calibrating the response
The three most common calibration methods are:
Calibration curve
Standard addition method
Internal standard method

40. 1E-1
Calibration curve

41. Calibration Curves
Several standards (with different concentration) containing exactly known concentrations of the analyte are measured and the responses recorded.
A plot is constructed to give a graph of instrument signal versus analyte concentration.
Sample (containing unknown analyte concentration) is run, if response is within the LDR of the calibration curve then concentration can be quantitated.
Calibration curve relies on accuracy of standard concentrations.
It depends on how closely the matrix of the standards resemble that of the sample to analyzed.
If matrix interferences are low, calibration curve methods are OK.
If matrices for sample and standards are not same calibration curve methods are not good.
Need to consider the linear part of the curves.

43. 1E-2 Standard-Addition Methods

44. Standard Addition Methods
Better method to use when matrix effects can be substantial
Standards are added directly to aliquots of the sample, therefore matrix components are the same.
Procedure:
Obtain several aliquots of sample (all with the same volume).
Spike the sample aliquots ==> add different volume of standards with the same concentration to the aliquots of sample
Dilute each solution (sample + standard) to a fixed volume
Measure the analyte concentration

45. Standard Addition Methods
Instrumental measurements are made on each solutions to get instrument response (S). If the instrument response is proportional to concentration, we may write,
S = (kVsCs)/Vt + (kVxCx)/Vt
Where, Vx =Volume of sample = 25 mL (suppose)
Vs = Volume of standard = variable (5, 10, 15, 20 mL)
Vt = Total volume of the flask = 50 mL
Cs = Concentration of standard
Cx = concentration of analyte in aliquot
k = proportionality constant
A plot of S as a function of Vs is a straight line of the form,
S = mVs+b
Where, slope, m = (kCs)/Vt and intercept, b = (kVxCx)/Vt
Now, b/m = (kVxCx)/Vt x Vt/(kCs)
Cx = bCs /mVx

46. Standard Addition Method
Another approach to determine Cx
Extrapolate line on plot to x-intercept
Recall: At Vs = 0  instrument response (relating to concentration of x in sample)
At x-intercept, you know the volume of analyte added to (i.e., inherent in) the sample.
Another way: This value S = 0 (no instrument response)  no analyte present in sample
In any case, Since S = 0,
Therefore, S = (kVsCs)/Vt + (kVxCx)/Vt = 0
Solve for Cx,
Cx = - (Vs)oCs / Vx

47. Standard Addition Methods
In the interest of saving time or sample, it is possible to perform standard addition analysis by using only two increments of sample. A single addition of Vs mL of standard would be added to one of the two samples and we can write, S1 = (kVxCx)/Vt and S2 = (kVxCx)/Vt + (kVsCs)/Vt

48. Calibration plot for the standard addition method
S = kVsCs/Vt + kVxCx/ Vt , m = kCs/Vt , b=kVxCx/Vt , b/m = VxCx/Cs
Calibration plot for the standard addition method
FIGURE 1-10 Linear calibration plot for the method of standard additions. The concentration of the unknown solution may be calculated from the slope m and the intercept b, or it may be determined by extrapolation, as explained in the text.

49. 1E-3 Internal standard Method

50. Internal standard Method
An Internal Standard is a substance that is added in a constant amount to all samples, blanks and calibration standards in an analysis.
Calibration involves plotting the ratio of the analyte signal to the internal standard signal as a function of analyte concentration of the standards.
This ratio for the samples is then used to obtain their analyte concentrations from a calibration curve.
Internal standard can compensate for several types of both random and systematic errors.