Literature DB >> 24832261

Accelerating rare events while overcoming the low-barrier problem using a temperature program.

Srikanth Divi1, Abhijit Chatterjee1.   

Abstract

We present a hierarchical coarse-grained simulation technique called the temperature programmed molecular dynamics (TPMD) method for accelerating molecular dynamics (MD) simulations of rare events. The method is targeted towards materials where a system visits many times a collection of energy basins in the potential energy surface, called a superbasin, via low-barrier moves before escaping to a new superbasin via a high-barrier move. The superbasin escape events are rare at the MD time scales. The low-barrier moves become accessible to MD by employing a temperature program, i.e., the MD temperature changes during the simulation. Once a superbasin is detected, transitions within the superbasin are ignored, in effect causing coarse-graining of basins. The temperature program enables the system to escape from the superbasin with reduced computational cost thereby overcoming the "low-barrier" problem. The main advantage of our approach is that the superbasin-to-superbasin transitions are accurately obtained at the original temperature with a reasonable computational cost. We study surface diffusion in Ag/Ag(001) system and demonstrate the ability of the TPMD method to span a wide-range of timescales.

Entities:  

Year:  2014        PMID: 24832261     DOI: 10.1063/1.4875476

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  2 in total

1.  A new class of enhanced kinetic sampling methods for building Markov state models.

Authors:  Arti Bhoutekar; Susmita Ghosh; Swati Bhattacharya; Abhijit Chatterjee
Journal:  J Chem Phys       Date:  2017-10-21       Impact factor: 3.488

2.  Generalized nano-thermodynamic model for capturing size-dependent surface segregation in multi-metal alloy nanoparticles.

Authors:  Srikanth Divi; Abhijit Chatterjee
Journal:  RSC Adv       Date:  2018-03-14       Impact factor: 3.361

  2 in total

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