Long-Timescale Simulations: Challenges, Pitfalls, Best Practices, for Development and Applications

Reference work entry


In this chapter, we examine the practice of developing, implementing, and applying long-timescale simulation methods. In contrast to standard molecular dynamics, the performance, and sometimes the accuracy, of long-timescale atomistic methods can vary greatly from one application to another. Therefore, for the practitioners, it is particularly important to understand the strengths and weaknesses of the methods, in order to assess their respective potential for specific problems, as well as maximize their efficiency. For the method developer, clearly assessing the challenges faced by current methods as well as the areas of opportunities for future development is paramount.

In the following, we present the opinion of five leaders in the field regarding best practices, challenges, and pitfalls in the use and development of such methods. Their answers both provide a roadmap to how best to approach the field and deliver insight into areas that need addressing in the future.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Chemistry and the Institute for Computational and Engineering SciencesUniversity of Texas at AustinAustinUSA
  2. 2.Department of Chemistry and BiochemistryUniversity of Texas at AustinAustinUSA
  3. 3.Faculty of Physical SciencesUniversity of IcelandReykjavíkIceland
  4. 4.CermicsEcole des Ponts ParisTechChamps-sur-MarneFrance
  5. 5.Department of PhysicsUniversity de MontréalMontréalCanada
  6. 6.Theoretical Division T-1Los Alamos National LaboratoryLos AlamosUSA

Section editors and affiliations

  • Danny Perez
    • 1
  • Blas Pedro Uberuaga
    • 2
  1. 1.Theoretical Division T-1Los Alamos National LaboratoryLos AlamosUSA
  2. 2.Materials Science and Technology DivisionLos Alamos National LaboratoryLos AlamosUSA

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