AI Article Synopsis

  • The efficiency of minimum-energy configuration searching algorithms relies heavily on the structure of energy landscapes in complex systems, and understanding the steps in these algorithms can lead to improved insights.
  • Comparing BEP-based algorithms to kinetic Monte Carlo methods reveals that the BEP principle is ineffective for complex systems due to uncorrelated energy barriers.
  • Most of the effectiveness of BEP-based methods comes from managing visited energy basins rather than the principle itself, highlighting the importance of direct handling in these algorithms.

Article 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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http://dx.doi.org/10.1021/ct501032vDOI Listing

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