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Computational chemistry

  • Prediction in organometallic catalysis – a challenge for computational chemistry

    Speaker: Dr Natalie Fey
    Institute: University of Bristol
    Country: UK
    Speaker Link:

    Dr Natalie Fey

    School of Chemistry, University of Bristol, Cantock’s Close, Bristol, BS8 1TS

    Computational studies of homogeneous catalysis play an increasingly important role in furthering (and changing) our understanding of catalytic cycles and can help to guide the discovery and evaluation of new catalysts [1, 2]. While a truly “rational design” process remains out of reach, detailed mechanistic information from both experiment and computation can be combined successfully with suitable parameters characterising catalysts [3] and substrates to predict outcomes and guide screening [4].

    The computational inputs to this process rely on large databases of parameters characterising ligand and complex properties in a range of different environments [5-9]. Such maps of catalyst space can be combined with experimental or calculated response data [7, 9], as well as large-scale data analysis. Rather than pursuing a purely computational solution ofin silico catalyst design and evaluation, an iterative process of mechanistic study, data analysis, prediction and experimentation can accommodate complicated mechanistic manifolds and lead to useful predictions for the discovery and design of suitable catalysts. 

    In this session, I will use examples drawn from our recent work, including the early stages of our development of a reactivity database, to illustrate this approach and discuss why organometallic catalysis is such a challenging yet rewarding area for prediction. 



    1. C. L. McMullin, N. Fey, J. N. Harvey, Dalton Trans., 43 (2014), 13545-13556
    2. N. Fey, M. Garland, J. P. Hopewell, C. L. McMullin, S. Mastroianni, A. G. Orpen, P. G. Pringle, Angew. Chem. Int. Ed., 51 (2012), 118-122.
    3. D. J. Durand, N. Fey, Chem. Rev., 119 (2019), 6561-6594.
    4. J. Jover, N. Fey, Chem. Asian J., 9 (2014), 1714-1723.
    5. A. Lai, J. Clifton, P. L. Diaconescu, N. Fey, Chem. Commun., 55 (2019), 7021-7024.
    6. O. J. S. Pickup, I. Khazal, E. J. Smith, A. C. Whitwood, J. M. Lynam, K. Bolaky, T. C. King, B. W. Rawe, N. Fey, Organometallics, 33 (2014), 1751-1791.
    7. J. Jover, N. Fey, J. N. Harvey, G. C. Lloyd-Jones, A. G. Orpen, G. J. J. Owen-Smith, P. Murray, D. R. J. Hose, R. Osborne, M. Purdie, Organometallics, 29 (2010), 6245-6258.
    8. J. Jover, N. Fey, J. N. Harvey, G. C. Lloyd-Jones, A. G. Orpen, G. J. J. Owen-Smith, P. Murray, D. R. J. Hose, R. Osborne, M. Purdie, Organometallics, 31 (2012), 5302-5306.
    9. A. I. Green, C. P. Tinworth, S. Warriner, A. Nelson, N. Fey, Chem. Eur. J. 2020, Accepted Article, DOI: 10.1002/chem.202003801.

  • Some thoughts on computational chemistry

    Speaker: Professor Frank Neese
    Institute: Max Planck Institut für Kohlenforschung
    Country: Germany
    Speaker Link:

    Frank Neese

    Department of Molecular Theory and Spectroscopy
    Max Planck Institut für Kohlenforschung
    Kaiser-Wilhelm Platz 1
    D-45470 Mülheim an der Ruhr

    Video Recording

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    The famous philosopher Karl Popper has taught us the elementary principles upon which modern science is built. The key concept is the one of falsification, that is, the realization that scientific theories can never be positively proven to be correct but can only be disproven by experience, e.g. experiment. This concept is of particular importance in the framework of contemporary computational chemistry where the link between theory and experiment is often broken or neglected. As a consequence, scientifically invalid conclusions are frequently being drawn from calculations that have no connection to reality whatsoever. In the lecture, the philosophical principles that should guide computational chemistry studies will be reviewed and it will be argued that the many different spectroscopic techniques provide a particular powerful meeting ground for theory and experiment. These principles will be illustrated by some examples from actual studies.