Principles of Instrumental Analysis Chapter 1 Introduction

TABLE 1-1 Chemical and Physical Properties Used in Instrumental Methods P.2 Ch1 Introduction

FIGURE 1-1 Block diagram showing the overall process of an instrumental measurement. P.3 Ch1 Introduction

TABLE 1-2 Some Examples of Instrument Components Ch1 Introduction

FIGURE 1-2 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. P.4 Ch1 Introduction

data-domain transformations during the measurement process. FIGURE 1-3 A block 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. P.5 Ch1 Introduction

FIGURE 1-3(a) P.5 Ch1 Introduction

FIGURE 1-3(b) P.5 Ch1 Introduction

FIGURE 1-3(c) P.5 Ch1 Introduction

FIGURE 1-4 Analog signals. P.6 Ch1 Introduction

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. P.6 Ch1 Introduction

FIGURE 1-4 Analog signals. (b) The current response of a photomultiplier tube when the light from a pulsed source falls on the photocathode of the device. P.6 Ch1 Introduction

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. P.7 Ch1 Introduction

FIGURE 1-6 Diagram illustrating three types of digital data: (a) count serial data, (b) binary-coded serial data, and (c) parallel binary data. In all three cases, the data represent the number n = 5. P.8 Ch1 Introduction

FIGURE 1-7 Chemical sensor. The sensor consists of a molecular recognition element and a transducer. A wide variety of recognition elements are possible. Shown here are some fairly selective recognition elements particularly useful with biosensors. The recognition phase converts the information of interest into a detectable characteristic, such as another chemical, mass, light, or heat. The transducer converts the characteristic into an electrical signal that can be measured. P.10 Ch1 Introduction

curve for the determination of isooctane in a hydrocarbon FIGURE 1-8 Calibration curve for the determination of isooctane in a hydrocarbon mixture. The residual is the difference between an experimental data point yi and that calculated from the regression model, mxi + b, as shown in the insert. P.12 Ch1 Introduction

FIGURE 1-9 Effect of calibration curve uncertainty FIGURE 1-9 Effect of calibration curve uncertainty. The dashed lines show confidence limits for concentrations determined fro the regression line. Note that uncertainties increase at the extremities of the plot. Usually, we estimate the uncertainty in analyte concentration only from the standard deviation of the response. Calibration curve uncertainty can significantly increase the uncertainty in analyte concentration from sc to s’c. P.14 Ch1 Introduction

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. P.15 Ch1 Introduction

FIGURE 1-11 Spreadsheet for standard-addition Example 1-1. Ch1 Introduction

spectrometric determination of sodium. FIGURE 1-12 Spreadsheet to illustrate the internal-standard method for the flame spectrometric determination of sodium. P.18 Ch1 Introduction

TABLE 1-3 Numerical Criteria for Selecting Analytical Methods P.19 Ch1 Introduction

Other Characteristics to Be Considered in Method Choice TABLE 1-4 Other Characteristics to Be Considered in Method Choice P.19 Ch1 Introduction

TABLE 1-5 Figures of Merit for Precision of Analytical Methods Ch1 Introduction

FIGURE 1-13 Useful range of an analytical method. LOQ = limit of quantitative measurement; LOL=limit of linear response. P.21 Ch1 Introduction