Knowledge-Based Expert Systems in Chemistry
Philip Judson, Jonathan Hirst, Carmay Lim, Kenneth D Jordan, Walter Thiel
2 229 kr
AvJoseph J W McDouall,UK) McDouall, Joseph J W (University of Manchester,Joseph J. W. McDouall,Joseph J W Mcdouall
2 509 kr
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Walter Thiel studied chemistry at the University of Marburg (West Germany) from 1966 to 1971, where he subsequently obtained his doctorate with A. Schweig in 1973. After a post-doctoral stint at the University of Texas at Austin with M. J. S. Dewar (1973–1975), he obtained his habilitation from the University of Marburg in 1981. He was appointed Professor of Theoretical Chemistry at the University of Wuppertal (West Germany) in 1983 and Professor of Chemistry at the University of Zurich (Switzerland) in 1992. In 1987 he was a visiting professor at the University of California at Berkeley. Since 1999, he is a director at the Max Planck Institute for Coal Research in Mülheim an der Ruhr (Germany) and an honorary professor at the neighbouring University of Düsseldorf (Germany) since 2001.
In the past few decades, computational resources have become more powerful every year and in addition methodology development has led to much more effi- cient techniques through parallelization of the calculations and the advent of den- sity functional theory. These reasons make it possible for computational quantum chemists to work on relatively large chem- ical 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 opportu- nities in novel areas. In particular, applica- tions of "realistic" quantum chemical sys- tems 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 model- ing. This means that computational quan- tum 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 gen- erally 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 exper- iment and assist in the interpretation of the experimental data. Furthermore, with computational quantum chemistry short- lived catalytic intermediates and their reactivity patterns can be investigated, which coupled to experimental work can explain product distributions and reac- tion rates. In addition, the computationalwork can make predictions that encourage future experimental studies. This symbio- sis 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 any- more that PhD students and postdoctoral researchers do a combination of experi- ment and computation for a single mul- tidisciplinary project. However, although many experimentally based groups are starting to use computational chemistry methods, almost at a routine basis, nowa- days 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 meth- ods by experimentalists, this does not mean these methods and techniques are routinely done with little or no prior knowledge of the theories and back- grounds. To highlight the difficulties in doing computational quantum chem- istry 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: 1. What does computational quantum chemistry offer? 2. Where do you start? 3. How do you select a theoretical model? 4. What useful output do I generate and how do I relate this to my experiment? The book is subdivided into five chap- ters covering the basics of computational quantum chemistry, electronic structure methods, computation of molecular prop- erties, molecular orbitals, spin densities and relativistic effects. These are the key methods and techniques necessary for computational quantum chemistry in col- laboration with experiment and a descrip- tion of the essential components of the output that can be linked to experiment. Each chapter has a logic set-up that first gives a layman's explanation of the reasons and the background of the basic theories with clear figures. Of course, a quantum chemistry book cannot be complete with- out equations and there are quite a lot of those in this book. However, these are well explained andMcDouall puts them in a broad context and clearly defines their variables and uses. As such I do not feel that the equations scare off the reader here, but are illustrative of the background. There are plenty of examples in the text that explain the theories in better detail. The book is very well written and is aimed at starters in the field of compu- tational quantum chemistry, such as new Master and PhD students. This book, how- ever, is not like "normal" quantum chem- istry books, where the reader gets drowned in very difficult to understand equations that require a high level of Mathematics knowledge. Instead, the author has cho- sen a selective set of equations and explains in detail what the equation means in chemical terms, what you can do with it and how you can solve the equations. As such, it makes the book highly read- able even for starters in the field that not necessarily have a thorough previous background in computational quantum chemistry. It may even be worthwhile for experimentalists who collaborate with computational quantum chemist to read this book and get understanding of what computational quantum chemistry can offer. What I found particularly useful was the section on converting quantum chem- ical energies into free energies through thermodynamic state functions and thereby gives experimentally measurable variables. The book is illustrated with a large number of drawings and figures that highlight what is explained in the text. In summary, the book on "Computational Quantum Chemistry" by McDouall is highly recommended literature for anyone working in the field, collaborating with computational chemists or interested in moving into the field of computational quantum chemistry. The work is very accessi- ble to the lay-reader and should help and assist with getting started in the field. Received:12August2013;accepted:13August2013; published online:03September2013. Citation:deVisserSP(2013)Gettingstartedincom- putationalquantumchemistry.Front.Chem. 1:14. doi: 10.3389/fchem.2013.00014 This articlewassubmittedtoTheoreticaland ComputationalChemistry,asectionofthejournal FrontiersinChemistry. Copyright(c)2013deVisser.Thisisanopen-access articledistributedunderthetermsoftheCreative CommonsAttributionLicense(CCBY).Theuse,dis- tributionorreproductioninotherforumsisper- mitted, providedtheoriginalauthor(s)orlicensor arecreditedandthattheoriginalpublicationin this journaliscited,inaccordancewithaccepted academicpractice.Nouse,distributionorrepro- ductionispermittedwhichdoesnotcomplywith theseterms. -- Sam P de. Visser doi: 10.3389/fchem.2013.00014
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