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Adaptive Resolution Molecular Dynamics Technique

  • M. PraprotnikEmail author
  • R. Cortes-Huerto
  • R. Potestio
  • L. Delle Site
Reference work entry
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Abstract

Soft matter systems display properties that span different time and length scales. In addition, scales’ interplay is often the key to understand fundamental mechanisms to the aim of controlling and/or designing materials with properties on demand. On the other hand, computational soft matter is limited by computational power for both, size and time of simulation and analysis of large sets of data. In this perspective, computational efficiency to treat large systems on long time scales becomes one of the main goals in constructing modern algorithms, together with the capability of designing theoretical schemes for data analysis capable of extracting the relevant information of interest above all the effects of scales’ interplay. One common and recurrent feature, in such studies, is the need to include relevant chemical details in a specific region where an event of interest is taking place, while the environment plays simply the role of a macroscopic thermodynamic bath that can be treatable at a coarse-grained level. Thus, an efficient computational strategy consists in employing multiple resolution methods, which simultaneously consider models with different resolution in different regions. This chapter provides a basic introduction to the adaptive resolution simulation (AdResS) method and its recent extensions. This methodology is designed with the idea of efficient computation and analysis of multiple scales as envisaged above. We will report its basic principles and technical aspects for the various directions along which the original idea was developed. As it will emerge in the next sections, the basic idea of adaptive resolution, already highly efficient in its first implementation, has now reached a high level of theoretical solidity, being framed in different but complementary ways in physically rigorous principles. Finally, selected applications, relevant in the field of materials science, chemical physics, and biochemistry, are illustrated in order to show the advanced possibilities of application of the method.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • M. Praprotnik
    • 1
    • 2
    Email author
  • R. Cortes-Huerto
    • 3
  • R. Potestio
    • 3
  • L. Delle Site
    • 4
  1. 1.Laboratory for Molecular ModelingNational Institute of ChemistryLjubljanaSlovenia
  2. 2.Department of PhysicsFaculty of Mathematics and Physics, University of LjubljanaLjubljanaSlovenia
  3. 3.Max Planck Institute for Polymer ResearchMainzGermany
  4. 4.Institute for MathematicsFreie Universitat BerlinBerlinGermany

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