CHAPTER 1
MAKING MEASUREMENTS

Learning Outcomes

• Describe aspects of good laboratory practice (GLP).
• Use correct terms to describe analytical measurements and data.
• Calculate analyte concentration from measurement results.
• Use statistical formulas to express the precision of analytical measurements.
• Use calibration methods to obtain accurate results.

1.1 INTRODUCTION

There are few areas in our modern life in which the quantity of substances is not important. Industries and government agencies spend substantial resources to determine and monitor the safe levels of chemicals in foods, pharmaceuticals, and the environment. Setting permissible levels of contaminants is based on quantitative results from toxicological studies and raising or lowering a level has significant costs and consequences. Similarly, companies compete for sales by providing high-quality goods at the lowest price. Optimizing industrial processes depends on making decisions based on analytical measurements. Poor measurements or incorrect data interpretation will lead to poor decisions.

You might not make many measurements yourself, but you probably rely on data and quantitative results to make decisions. You've probably read the ingredients or nutritional information on a product label to choose one product over another. I certainly want manufacturers to perform quality checks on the contents of the products that I buy. I'm also expecting an independent agency, say the FDA or USDA,1 to check that there is not too much of a mineral, or contaminants such as Pb or rat poison, that could make the food unhealthy. Think about the last time that you had a medical checkup. Did the doctor determine your health by just looking at you? At the least you had a quantitative measure of pulse rate and blood pressure. Modern medicine relies on a variety of technological tools and clinical analyses. At some time, you might need to make a significant decision such as beginning daily doses of a cholesterol-lowering drug. We all hope that doctors and clinical technicians analyzing our samples were paying attention when they took an analytical chemistry course!

When you make a measurement, or you need to make a decision based on someone else's measurement, do you trust the value? This chapter introduces the terminology and statistical tools to describe and assess quantitative results. Some of the details will be new to you, but they all fit into a framework for collecting and reporting quantitative measurements. Table 1.1 begins building our vocabulary of measurement science and data-handling concepts by defining general terms. Many of these terms are used rather loosely in the scientific and manufacturer literature. You might need to dig into the details to know exactly what is meant when a procedure refers to the sample, the signal, etc. It is also common that a given term will have a different definition for different instruments or techniques. Resolving power is a measure of selectivity in mass spectrometry. However, resolving power and the related term resolution have different meanings when discussing a spectrum, a microscope image, or the separation of components in a mixture.

TABLE 1.1 Measurement Terms

In quantitative analysis, we want a measurement or detector signal that we can relate to an analyte concentration. Doing so can be quite involved, and Chapter 2 discusses various sample preparation methods to isolate an analyte from interferences so that it can be measured. What mechanisms are available to detect an analyte? I can think of only three general strategies to detect and quantitate an analyte:

• measuring a physical property,
• using electromagnetic radiation, called spectroscopy, and
• measuring an electric charge or current.

Table 1.2 lists some examples in each of these categories. We will discuss most of these methods, so do not worry if they are unfamiliar. Chapter 3 discusses classical methods that rely on physical measurements and Part III of the text introduces instrumental methods based on electrochemistry, spectroscopy, and mass spectrometry.

TABLE 1.2 Measurement Strategies

Although I list only three general detection strategies, each of these general categories encompass a multitude of specific analytical techniques. For example, spectroscopic methods have been developed to use most of the electromagnetic spectrum, including X-ray, ultraviolet (UV), visible (Vis), infrared, and radio waves. The different regions of the electromagnetic spectrum interact with matter differently and provide different types of information. This text concentrates on quantitative methods for analytes in aqueous solution. There are numerous other spectroscopic techniques to make quantitative measurements of solids and to determine physical properties of materials.

These general categories vary in sensitivity and selectivity. Measurements based on a physical property are usually less sensitive than spectroscopic or charge-based instrumental methods. The methods based on physical methods are useful when analyte concentrations are relatively high and when preparing standards to calibrate instrumental methods. When coupled with a separation column, detectors based on physical methods are the most universal and capable of detecting all analytes in the sample. Spectroscopic and electroanalytical methods can be extremely sensitive and selective for specific analytes. Selecting from one of these three general strategies for a given analytical problem depends on the nature of the analyte, the expected concentration, and the sample matrix.

New analytical methods and instruments are developed continuously. The breadth of research and development in analytical chemistry is too extensive to convey through just a few examples. For an overview of current research topics in analytical sciences, browse the Technical or Preliminary Programs of upcoming analytical chemistry conferences.2

1.1.1 Concentration Units

Most of the quantitative methods that we will discuss are aimed toward determining the concentration of an analyte in a sample. Concentration is the quantity of one substance, the analyte, divided by the total quantity of all substances in the sample. Concentration is different from an amount, in moles, mass, or volume, and we often interconvert between the two. Table 1.3 lists the SI base units that are used to derive other units.3 In addition to these units, we drop or add the prefixes listed in Table 1.4 to indicate numerical factors. Common units that we work with in addition to the mole and kg are mmol (millimole), mg (milligram), and g (gram). The purpose of the prefixes is to simply express results in convenient values rather than...