{"id":5,"date":"2022-12-15T17:12:22","date_gmt":"2022-12-15T22:12:22","guid":{"rendered":"https:\/\/pressbooks.bccampus.ca\/instanchem1\/?p=5"},"modified":"2025-01-03T15:36:59","modified_gmt":"2025-01-03T20:36:59","slug":"introduction","status":"publish","type":"chapter","link":"https:\/\/pressbooks.bccampus.ca\/instanchem1\/chapter\/introduction\/","title":{"raw":"Introduction to Chemical Analysis","rendered":"Introduction to Chemical Analysis"},"content":{"raw":"

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There are many situations in which it is useful to know what elements or molecules are present in a sample, or if one or more specific elements or molecules of interest (i.e.<\/em> analytes<\/em>) are present. Such situations occur frequently in manufacturing, natural resource sectors, and other industries; in agriculture, food and water quality and safety; in environmental assessment; in forensics and security; in health care, medicine, and pharmaceuticals; and, of course, in many fields of scientific research and development. The obvious challenge is that elements and molecules cannot be directly seen, classified, and counted by eye\u2014special methods of analysis are needed.<\/p>\r\n\r\n

Classical Methods of Analysis<\/h2>\r\n

Classical methods<\/em> of chemical analysis are usually volume-based or mass-based, leveraging reactivity and other chemical properties of analytes to yield macroscopic observables (e.g.<\/em> colour changes, precipitates) that can be linked to analyte quantity. Titrations are perhaps the most famous type of classical volumetric analysis. Although classical methods work well in some situations\u2014potentially providing good accuracy and precision at low cost\u2014serious limitations are encountered as samples get more complex and smaller in quantity. Classical methods are also poorly suited to discovery and screening analyses, where there is not a predetermined analyte of interest and where there is limited foreknowledge about the composition of a sample.<\/p>\r\n

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\"Illustration<\/p>\r\n\r\n

Instrumental Methods of Analysis<\/h2>\r\n

Instrumental methods<\/em> of chemical analysis are technology-based, leveraging the interactions of atoms or molecules with light, other types of radiation, electric and magnetic fields, and other forms of energy. In general, an instrument applies a stimulus (e.g.<\/em> light\/radiation, electric potential, kinetic energy) to a sample and the response (e.g.<\/em> residual stimulus, emitted light\/radiation, electric current, velocity or trajectory) is transduced<\/em> into an electrical quantity (e.g.<\/em> current, voltage). The analog electrical signal is converted to a digital signal to interface with a computer or other data acquisition and recording system.<\/p>\r\n

It should be noted that transduction does not produce a current or voltage that is easily converted to the quantity of analyte. In most cases, a direct conversion using fundamental scientific theory is impossible or impractical. Instead, calibration<\/em> is required. Lab-made standard samples with known quantities of analyte(s) are prepared and measured using an instrument. The resulting plots of instrument signal versus known quantity of analyte enables determination of the unknown quantity in a sample of interest.<\/p>\r\n

Broad and strong knowledge of instrumental methods makes a scientist highly employable.<\/p>\r\n\r\n

Figures of Merit<\/h2>\r\n

Figures of merit<\/em> are used to discuss and compare methods of analysis. The limit of detection<\/em> is the smallest amount of analyte that can be reliably detected. The dynamic range<\/em> is the range over which the instrument signal scales predictably and significantly with analyte quantity. The sensitivity <\/em>is the change in signal per unit quantity of analyte.<\/p>\r\n

As instruments and analysis methods are never perfect, other important quantities are the signal-to-noise <\/em>(S\/N) ratio, the signal-to-background <\/em>(S\/B) ratio,\u00a0<\/em>and the selectivity<\/em>. \u201cSignal\u201d refers to the instrument response to analyte; \"background\" refers to what is measured by the instrument for a sample without analyte; and\u00a0\u201cnoise\u201d refers to random variation in the instrument response. Although a larger signal per unit quantity of analyte is often favourable, it can be negated by high levels of noise. Conversely, a smaller signal for analyte may be useful if the noise is very small or negligible. The goal is thus to maximize the S\/N ratio. When noise scales in proportion to the background, it is also useful to maximize the S\/B ratio.\u00a0\"Selectivity\"\u00a0<\/em>is the degree to which a method is sensitive to analyte versus non-analyte interferences in a sample.<\/p>\r\n

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Connections<\/h3>\r\n

Subsequent chapters discuss common instrumental methods of analysis and their underlying physicochemical basis.<\/p>\r\n\r\n