Analytical chemistry commonly is described as the area of chemistry responsible for qualitative and quantitative methods of analysis. This description is insufficient, however, as it fails to recognize that most chemists and biochemists routinely analyze samples. The craft in analytical chemistry is not in the act of carrying out an analysis; instead, the craft is in the act of designing the analysis. A simple example illustrates the importance of this difference. At the end of the 19th century, analytical chemists developed a host of chemical tests for identifying and quantifying inorganic species (Is there gold in this ore? How much?) and organic functional groups (Does this molecule include an aldehyde? How many?) A course in analytical chemistry in the late 1800's would give careful consideration to these methods. By the 1950s, such spot tests, as they are called, no longer were covered in the analytical curriculum, although they became an important part of the laboratory curriculum in inorganic chemistry and in organic chemistry. Meanwhile, analytical chemists in the 1950s and the 1960s were busy improving the instrumentation for infrared spectroscopy and UV-Vis spectroscopy, developing them as tools for functional group analysis, for structure determination, and for quantitative analysis using Beer's law, topics that are now covered in many introductory chemistry and organic chemistry courses. And so the cycle continues.
So, what is analytical chemistry? A better definition is that analytical chemistry is the science of chemical measurements. Analytical chemists work to improve established methods of analysis, to extend existing methods of analysis to new types of samples and to smaller amounts of sample, to develop new methods of analysis, and to discover more powerful tools for analyzing data. The curriculum in analytical chemistry at DePauw accomplishes this through four half-credit courses:
This course, Chem 351: Chemometics, provides an introduction to how chemists and biochemists can extract useful information from the data they collect in lab, including, among other topics, how to summarize data, how to visualize data, how to test data, how to build quantitative models to explain data, how to design experiments, and how to separate a useful signal from noise.
The links in the navigation bar provide access to course materials and other useful information, including the course syllabus, which serves as our contract, a detailed class schedule, and an archive of course materials.