Getting started in computational quantum chemistry

In the past few decades, computational resources have become more powerful every year and in addition methodology development has led to much more efficient techniques through parallelization of the calculations and the advent of density functional theory. These reasons make it possible for computational quantum chemists to work on relatively large chemical systems with a total number of atoms well over 100 nowadays. As a result of this, interest in applications of computational quantum chemistry has considerably widened and opened up research opportunities in novel areas. In particular, applications of “realistic” quantum chemical systems have become possible and as such it is starting to become common practise in fields of, e.g., bioinorganic chemistry and biochemistry, to do experimental studies side-by-side with computational modeling. This means that computational quantum chemistry does not operate in virtual worlds and settings anymore on small atomic systems, but can address major chemical problems. These combined experimental/computational studies generally give a broader perspective of a chemical problem and look into it from different angles and perspectives than stand-alone experimental studies. Thus, the computational studies give important additional information alongside experiment and assist in the interpretation of the experimental data. Furthermore, with computational quantum chemistry shortlived catalytic intermediates and their reactivity patterns can be investigated, which coupled to experimental work can explain product distributions and reaction rates. In addition, the computational work can make predictions that encourage future experimental studies. This symbiosis of experiment and theory has led to a large field of research, where theoreticians and experimentalists work together. As a result of that it is not uncommon anymore that PhD students and postdoctoral researchers do a combination of experiment and computation for a single multidisciplinary project. However, although many experimentally based groups are starting to use computational chemistry methods, almost at a routine basis, nowadays there are some serious caveats with the methods and techniques and often these computational studies cannot be done through “black-box”-procedures but require expert supervision. Although there is an increased popularity of computational quantum chemistry mainly through the use of computational quantum chemistry methods by experimentalists, this does not mean these methods and techniques are routinely done with little or no prior knowledge of the theories and backgrounds. To highlight the difficulties in doing computational quantum chemistry research on experimentally relevant chemical systems, McDouall has written a monograph on the chemical procedures and techniques behind the computational chemistry software packages and the many pitfalls the user should be aware of. The book, therefore, tries to address questions for beginners in doing computational chemistry research, including: