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Development of Coarse-Grained Force Field by Combining Multilinear Interpolation Technique and Simplex Algorithm.

Mingwei WanJunjie SongWenli LiLianghui GaoWei-Hai Fang
Published in: Journal of computational chemistry (2019)
A fast, reasonable, and transferable coarse-grained (CG) molecular dynamics force field (FF) is essential to combine experimental and simulation data. However, the parameterization of CG FF usually requires massive computation, which hinders its rapid development. Here, we presented an efficient optimization protocol by combining multilinear interpolation technique with simplex algorithm. In this preliminary work, taking the experimental properties as the benchmark, we constructed a new set of CG FF for water and n-alkanes by adopting piecewise Morse function to describe the nonbonded interactions. This CG FF has a delicate balance between efficiency, accuracy, and transferability and well reproduced the correct structural and thermodynamics properties of pure water and alkane liquids. More importantly, optimized Morse potential was also successfully applied to describe the interactions between water and n-alkanes. It nicely predicted the phase separation, interface tension, hydration free energy, and formation of microemulsions of water/oil mixtures. © 2019 Wiley Periodicals, Inc.
Keyphrases
  • molecular dynamics
  • density functional theory
  • machine learning
  • deep learning
  • randomized controlled trial
  • single molecule
  • wastewater treatment
  • big data
  • risk assessment
  • virtual reality