Virtual Winter School on Computational Chemistry

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Development of Automatic Reaction Path Search Methods Toward Systematic Chemical Reaction Design and Discovery

Speaker: Professor Satoshi Maeda
Institute: Hokkaido University
Country: Japan
Speaker Link:
Time: 09:00 CET 24-Feb-22

Professor Satoshi Maeda

Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University, Japan

Automation of the task of obtaining transition state structures and related reaction paths has been one of significant subjects in computational chemistry [1-3]. Recent advances made it possible to construct a complex reaction path network consisting of thousands or more of paths based on DFT calculations. In my talk, I will focus on the artificial force induced reaction (AFIR) method which has been developed by ourselves since 2010 [4,5]. AFIR finds a reaction path by inducing a structural transformation in a system by applying a virtual force to a fragment pair. Systematic applications of this procedure to various fragment pairs in a given system generates a network of paths for various structural transformations, i.e., reaction path network.

Its versatile applicability is the first topic [5]. AFIR has been applied to a variety of systems combining appropriate computational models such as semiempirical and QM/MM methods. In applications to large systems, several restrictions such as the one based on bonding patterns have been adopted to avoid combinatorial explosion of possible structural transformations. Ways to apply it to reactions involving multiple electronic states and their conical intersections have also been studied.

Combining it with chemical kinetics is the second topic [6]. It is desirable to control the search based on a kinetic simulation. To do that, a highly efficient and robust kinetics method is required. This is because the kinetics method needs to be applied repeatedly to a reaction path network to guide the further extension of the network. As such a method, the rate constant matrix contraction (RCMC) method has been developed by us [6]. By combining AFIR with RCMC, the on-the-fly kinetic simulation which explores a reaction path network while solving kinetic equations has been achieved.

Its use in chemical reaction discovery is the final topic [7]. Recently, a new reaction design concept, quantum chemistry-aided retrosynthetic analysis (QCaRA), which had been only hypothetical previously [1], has been demonstrated together with experimental collaborators [7]. In that study, difluoroglycine was set as the synthetic target and its isomerization and decomposition paths were explored systematically by AFIR. Then, a new synthetic route of producing a difluoroglycine derivative was proposed as the reverse process of one of the decomposition paths. The ab initio proposed synthetic route by QCaRA/AFIR was finally substantiated experimentally leading the discovery of a new synthetic method.


  1. S. Maeda, K. Ohno, K. Morokuma, Systematic exploration of the mechanism of chemical reactions: The global reaction route mapping (GRRM) strategy using the ADDF and AFIR methods. Phys. Chem. Chem. Phys. 15, 3683–3701 (2013).

  2. A. L. Dewyer, A. J. Argüelles, P. M. Zimmerman, Methods for exploring reaction space in molecular systems. WIREs Comput. Mol. Sci. 8, e1354 (2018).

  3. G. N. Simm, A. C. Vaucher, M. Reiher, Exploration of reaction pathways and chemical transformation networks. J. Phys. Chem. A 123, 385–399 (2019).

  4. S. Maeda, K. Morokuma, A systematic method for locating transition structures of A + B → X type reactions. J. Chem. Phys. 132, 241102 (2010).

  5. S. Maeda, Y. Harabuchi, Exploring paths of chemical transformations in molecular and periodic systems: An approach utilizing force. WIREs Comput. Mol. Sci. 11, e1538 (2021).

  6. Y. Sumiya, S. Maeda, Rate constant matrix contraction method for systematic analysis of reaction path networks. Chem. Lett. 49, 553–564 (2020).

  7. T. Mita, Y. Harabuchi, S. Maeda, Discovery of a synthesis method for a difluoroglycine derivative based on a path generated by quantum chemical calculations. Chem. Sci. 11, 7569–7577 (2020).


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