CCL: Case Studies of QM Computational Chemistry in Reactivity



Hi Lars:
 There is no need for defense. We all agree that method development is
 important.
 Personally, I am a bit defensive of my own work which was published in 2009
 in a non-theoretical journal and consist of 80% experiment. I provided that
 example to show one where theory (whatever it is) worked well to the point
 of prediction. Again, this is what I am looking for in this thread.
 Unfortunately, theory can not exist on its own and the finances flow from
 experiment downward. You will find only blank looks with the arguments you
 have made outside of a room full of theorists and that is the reality. On
 the other hand, often we are in front of chemists, at least, and having
 verified chemical examples of the importance of theory in necessary. These
 should be chemically understandable and should be dealing with issues that
 are important to the audience. They should be transferable. That means
 using standard methods with the right statistics and history that can be
 computed in a reasonable time and executed, potentially, by non-experts.
 So, while I love MRCI, for example, even the best of us will have trouble
 getting it right on relevant molecules.
  Best,
 Peter
 On Wed, Sep 9, 2015 at 4:06 PM, Lars Goerigk lars.goerigk-,-unimelb.edu.au <
 owner-chemistry**ccl.net> wrote:
 >
 > Sent to CCL by: "Lars  Goerigk" [lars.goerigk : unimelb.edu.au]
 > Hi Peter,
 >
 > in defense of us people that believe in obtaining the right result for the
 > right reason: even if industry is interested in quick-and-dirty results,
 > would it not be highly embarassing to make recommendations based on a
 > method that relies on unforeseeable error compensation, only to then see
 > that the experimentalists cannot reproduce your predictions? Susi's comment
 > was therefore valid, albeit I would have worded it in a more diplomatic
 way.
 >
 > I find it very important to apply a level of theory that comes with a low
 > risk of unsystematic error compensation. For example, a
 > dispersion-corrected (double-)hybrid density functional with at least a
 > triple-zeta basis set is overall much more reliable than the popular
 > B3LYP/6-31G* level; the reasons for that are clear and they have been
 > discussed extensively in the literature and in this forum. If you cannot
 > afford a large basis set, but you want to quickly obtain results for bigger
 > systems with an acceptable accuracy, there are other promising methods out
 > there (e.g. HF-3c or PBEh-3c). Moreover, it is also important to use
 > reliable solvation models (e.g. COSMO-RS) and reliable enthalpy and entropy
 > corrections.
 >
 > As to your comment on "level nerds" being a barrier for
 successful
 > interaction between theory and experiment, quantum chemists do not
 > investigate and develop new methdods just because they do not know what
 > else to do with their time. I would rather say that this discussion
 > highlights a lack of communication between method developers and the users
 > of QM methods and as always the fault for that lies probably on both sides;
 > one consequence of that is that B3LYP/6-31G* is still so popular in the
 > year 2015.
 >
 > Giving a general answer to your question is difficult, as it is not quite
 > sure what property you want to calculate, which is exactly why the various
 > answers to your question differ so much. However, there are numerous
 > benchmark studies out there that provide some guidance on which methods to
 > use and which to avoid; I have given some hints on reliable methods above.
 >
 > Of course, there is never 100% certainty that your predictions are right
 > because in the end you try to describe a highly complex system with a
 > theoretical model, which by definition is only a simplification of the real
 > world. That complexity also means that there is not one sole, easy solution
 > to your question. Therefore, it is probably wise to run calculations at two
 > different levels of theory to distinguish between general trends and
 > methodological artifacts. By carefully choosing a statistically reliable
 > level of theory, you can at least minimise the possibilibity of making
 > wrong predictions, and that is something that also industry people will
 > accept if properly explained. I hope some of these hints were helpful.
 >
 > Finally, I hope you forgive me for saying that having efficient and ever
 > improving QM methods is something that would not be possible without all
 > those dedicated level nerds out there, which is why we should regard that
 > term as a compliment.
 >
 > Cheers,
 > Lars
 >
 > ---
 > Dr. Lars Goerigk
 > ARC DECRA Fellow
 > School of Chemistry
 > The University of Melbourne
 > VIC 3010
 > Australia
 >
 > Research profile:
 > http://www.chemistry.unimelb.edu.au/dr-lars-goerigk
 > List of my publications:
 > http://www.researcherid.com/rid/D-3717-2009
 > Follow me on Twitter: https://twitter.com/lgoer_compchem>;
 >
 >