Experimental techniques computational chemistry

In the past 15 years, combined advances in computer technology and innovative algorithms development provided the possibility to perform complex computational operations in a reasonable time scale. Therefore these theoretical methods, when used together with modern experimental techniques (combinatorial chemistry and high-throughput screening), are now widely used. 

With the increasing capabilities of computers and development of new numerical methods, it is now possible to predict polymer properties computationally. In addition to saving time, computer-aided chemistry can sometimes provide new insights into some decomposition mechanisms which are difficult to obtain by experimental techniques. Computer modeling has been used in an increasing number of ways to simulate thermal degradation. A few representative examples are described below. 

The terminal groups of a polymer chain are different in some way from the repeat units that characterize the rest of the molecule. If some technique of analytical chemistry can be applied to determine the number of these end groups in a polymer sample, then the average molecular weight of the polymer is readily evaluated. In essence, the concept is no different than the equivalent procedure applied to low molecular weight compounds. The latter is often included as an experiment in general chemistry laboratory classes. The following steps outline the experimental and computational essence of this procedure ... 

When quantum calculations, at the ab initio and at the semiempirical level, gained foot in the realm of chemistry, a steadily increasing number of experimentalists began to use quantum calculations as a supplement in the exposition of their findings. In many case this was - and still is - nothing more that an ornament, like decorations on a cake. This use of quantum chemistry has been, in general, harmless, because results in contrast with experimental evidence have been rarely published, and this production may be considered now as a sort of advertising for the new-born computational chemistry. A more serious use of the facilities offered by the computational techniques is done by scientists provided of... 

Historically, some of those approaches have been developed with a considerable degree of independence, leading to a proliferation of thermochemical concepts and conventions that may be difficult to grasp. Moreover, the past decades have witnessed the development of new experimental methods, in solution and in the gas phase, that have allowed the thermochemical study of neutral and ionic molecular species not amenable to the classic calorimetric and noncalorimetric techniques. Thus, even the expert reader (e.g., someone who works on thermochemistry or chemical kinetics) is often challenged by the variety of new and sophisticated methods that have enriched the literature. For example, it is not uncommon for a calorimetrist to have no idea about the reliability of mass spectrometry data quoted from a paper many gas-phase kineticists ignore the impact that photoacoustic calorimetry results may have in their own field most experimentalists are notoriously unaware of the importance of computational chemistry computational chemists often compare their results with less reliable experimental values and the consistency of thermochemical data is a frequently ignored issue and responsible for many inaccuracies in literature values. 

Many areas of computational chemistry are gaining permanent place as dependable research techniques by providing reliable descriptions of structures and properties of chemical compounds. Due to improvements of hardware and accessibility of many commercial programs a theoretical study supplements experimental investigations and provides new accurate data when experiments are not available. Such... 

Infrared (IR) spectroscopy was the first modern spectroscopic method which became available to chemists for use in the identification of the structure of organic compounds. Not only is IR spectroscopy useful in determining which functional groups are present in a molecule, but also with more careful analysis of the spectrum, additional structural details can be obtained. For example, it is possible to determine whether an alkene is cis or trans. With the advent of nuclear magnetic resonance (NMR) spectroscopy, IR spectroscopy became used to a lesser extent in structural identification. This is because NMR spectra typically are more easily interpreted than are IR spectra. However, there was a renewed interest in IR spectroscopy in the late 1970s for the identification of highly unstable molecules. Concurrent with this renewed interest were advances in computational chemistry which allowed, for the first time, the actual computation of IR spectra of a molecular system with reasonable accuracy. This chapter describes how the confluence of a new experimental technique with that of improved computational methods led to a major advance in the structural identification of highly unstable molecules and reactive intermediates. 

At the start of the twenty-first century, efforts are underway to decrease society s dependence on fossil fuels. It is clear that alternate energy forms will bring with them their own sets of reactive radical intermediates and revisit the important intermediates seen from smaller model compounds, as we consider future challenges in combustion chemistry. We expect that advances in experimental techniques and computational approaches will correspondingly be developed in the years ahead. 

Computational chemistry is of course another technique to obtain theoretical information on perfect crystals at variable temperature. The background for this approach has been introduced in [113] and will not be further discussed here. It is important to stress that cryo-crystallography is not necessarily an experimental science, because predictions or explanations obtained from theoretical modeling are equally important in modem studies. 

In the following pages of this chapter, brief introductions or literature references to the various experimental techniques are given. Closely related theoretical and computational work is described in Chapter 22 by Borden in this book. " The interplay of theory and experiment, as well as the mumally supporting roles of preparative wet chemistry and instrumental techniques, are emphasized. 

The accuracy achieved through ab initio quantum mechanics and the capabilities of simulations to analyze structural elements and dynamical processes in every detail and separately from each other have not only made the simulations a valuable and sometimes indispensable basis for the interpretation of experimental studies of systems in solution, but also opened the access to hitherto unavailable data for solution processes, in particular those occurring on the picosecond and subpicosecond timescale. The possibility to visualize such ultrafast reaction dynamics appears another great advantage of simulations, as such visualizations let us keep in mind that chemistry is mostly determined by systems in continuous motion rather than by the static pictures we are used to from figures and textbooks. It can be stated, therefore, that modern simulation techniques have made computational chemistry not only a universal instrument of investigation, but in some aspects also a frontrunner in research. At least for solution chemistry this seems to be recognizable from the few examples presented here, as many of the data would not have been accessible with contemporary experimental methods. 

However, one should keep in mind that simplified models of the actual physical systems are routinely used and that molecular-level modeling techniques involve various levels of approximations. In principle, computational chemistry can only disprove, and never prove, a particular reaction mechanism. In practice, however, a computational investigation may still, in many cases, be a useful guide as to the likeliness of a given reaction pathway. Comparison to experimental information and to computational studies of alternative reaction mechanisms will help establish the kind of trust (or lack thereof) that should be put into a particular reaction mechanism obtained by computational chemistry. 

Since the availability of inexpensive high-speed computers and spectacular advances in computational chemistry methodology, mechanistic subtleties may now be investigated which are not amenable to experimental scrutiny. Of course, validation of a particular computational technique is essential and a comparison with a sound relevant experimental result is one method (see Chapter 7). 

There is thus no guarantee that computational modeling will resolve a research question such is the nature of research. But as with much of curiosity-driven science, a modeling calculation may be worth investigating and could be very revealing. We have tried to show the opportunities of computational chemistry, but we want the readers to embark on these experiments with their eyes wide open. Your first computer experiments may not work as you hoped, but just as in the case of laboratory experiments, persistence can pay off. If an experimental procedure or technique did not work for you the first time you tried it, you would not shun it forever. Likewise with computational chemistry experiments, if you do not get a satisfactory answer the first time you try it, do not assume the whole field is useless. 

---