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N'Tsouaglo GK, Béland LK, Joly JF, et al. Probing Potential Energy Surface Exploration Strategies for Complex Systems. J Chem Theory Comput. 2015;11(4):1970-7doi: 10.1021/ct501032v.
N'Tsouaglo, G. K., Béland, L. K., Joly, J. F., Brommer, P., Mousseau, N., & Pochet, P. (2015). Probing Potential Energy Surface Exploration Strategies for Complex Systems. Journal of chemical theory and computation, 11(4), 1970-7. https://doi.org/10.1021/ct501032v
N'Tsouaglo, Gawonou Kokou, et al. "Probing Potential Energy Surface Exploration Strategies for Complex Systems." Journal of chemical theory and computation vol. 11,4 (2015): 1970-7. doi: https://doi.org/10.1021/ct501032v
N'Tsouaglo GK, Béland LK, Joly JF, Brommer P, Mousseau N, Pochet P. Probing Potential Energy Surface Exploration Strategies for Complex Systems. J Chem Theory Comput. 2015 Apr 14;11(4):1970-7. doi: 10.1021/ct501032v. PMID: 26574398.
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J Chem Theory Comput. 2015 Apr 14;11(4):1970-7. doi: 10.1021/ct501032v.

Probing Potential Energy Surface Exploration Strategies for Complex Systems.

Journal of chemical theory and computation

Gawonou Kokou N'Tsouaglo, Laurent Karim Béland, Jean-François Joly, Peter Brommer, Normand Mousseau, Pascal Pochet

Affiliations

  1. Département de physique and Regroupement québécois sur les matériaux de pointe, Université de Montréal , C.P. 6128, Succursale Centre-Ville, Montréal, H3C 3J7 Québec Canada.
  2. Centre for Predictive Modelling, School of Engineering, University of Warwick , Coventry CV4 7AL, United Kingdom.
  3. Laboratoire de Physique Théorique de la Matière Condensée, Université Pierre et Marie Curie , Boite 121, 4, Place Jussieu, 75252 Paris Cedex 05, France.
  4. Université de Grenoble Alpes , INAC-SP2M, L_Sim, F-38000 Grenoble, France.
  5. CEA, INAC-SP2M, Atomistic Simulation Laboratory, F-38000 Grenoble, France.

PMID: 26574398 DOI: 10.1021/ct501032v

Abstract

The efficiency of minimum-energy configuration searching algorithms is closely linked to the energy landscape structure of complex systems, yet these algorithms often include a number of steps of which the effect is not always clear. Decoupling these steps and their impacts can allow us to better understand both their role and the nature of complex energy landscape. Here, we consider a family of minimum-energy algorithms based, directly or indirectly, on the well-known Bell-Evans-Polanyi (BEP) principle. Comparing trajectories generated with BEP-based algorithms to kinetically correct off-lattice kinetic Monte Carlo schemes allow us to confirm that the BEP principle does not hold for complex systems since forward and reverse energy barriers are completely uncorrelated. As would be expected, following the lowest available energy barrier leads to rapid trapping. This is why BEP-based methods require also a direct handling of visited basins or barriers. Comparing the efficiency of these methods with a thermodynamical handling of low-energy barriers, we show that most of the efficiency of the BEP-like methods lie first and foremost in the basin management rather than in the BEP-like step.

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