AutoMapper: A python tool for accelerating the polymer bonding workflow in LAMMPS

Matt A Bone; Brendan J. Howlin; Ian Hamerton; Terence Macquart

doi:10.1016/j.commatsci.2022.111204

AutoMapper: A python tool for accelerating the polymer bonding workflow in LAMMPS

Matt A Bone^*, Brendan J. Howlin, Ian Hamerton, Terence Macquart

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

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Abstract

Polymeric materials modelling has the potential to rapidly accelerate the discovery of new materials due to the comparative ease of simulations compared to laboratory testing campaigns. High quality molecular dynamics simulation software, such as LAMMPS, are able to facilitate the transition from empirical to digitised chemistry. However, in order to fully benefit from the speed of simulations, tools need to be developed to automate the preprocessing stages required for modelling. AutoMapper is an open-source Python application that automates the generation of files required to use REACTER, a powerful polymer bonding package implemented within LAMMPS. To automate this process, the authors developed an iterative path search algorithm based on chemical graph theory to accurately map pre- and post-reaction polymerisation structures, and hence eliminating the bulk of the human effort previously required to run a simulation. AutoMapper requires minimal user input, is force field independent, and has shown marvellous performance on a wide range of polymerisation types.

Original language	English
Article number	111204
Number of pages	6
Journal	Computational Materials Science
Volume	205
Early online date	1 Feb 2022
DOIs	https://doi.org/10.1016/j.commatsci.2022.111204
Publication status	Published - 1 Apr 2022

Bibliographical note

Funding Information:
This research received no external funding. M. A. Bone is supported by the Engineering and Physical Science Research Council as part of the EPSRC Centre for Doctoral Training in Composites Science, Engineering, and Manufacturing. Grant number: EP/S021728/1 . M. A. Bone would like to thank Jacob Gissinger, Andrew Jewett and Benjamin Jenson for their useful discussion around the development of AutoMapper.

Publisher Copyright:
© 2022 The Authors

Keywords

Molecular Dynamics
LAMMPS
Polymer Simulation
Open Source Software

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10.1016/j.commatsci.2022.111204

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Accepted author manuscript, 427 KBLicence: CC BY-NC-ND

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title = "AutoMapper: A python tool for accelerating the polymer bonding workflow in LAMMPS",

abstract = "Polymeric materials modelling has the potential to rapidly accelerate the discovery of new materials due to the comparative ease of simulations compared to laboratory testing campaigns. High quality molecular dynamics simulation software, such as LAMMPS, are able to facilitate the transition from empirical to digitised chemistry. However, in order to fully benefit from the speed of simulations, tools need to be developed to automate the preprocessing stages required for modelling. AutoMapper is an open-source Python application that automates the generation of files required to use REACTER, a powerful polymer bonding package implemented within LAMMPS. To automate this process, the authors developed an iterative path search algorithm based on chemical graph theory to accurately map pre- and post-reaction polymerisation structures, and hence eliminating the bulk of the human effort previously required to run a simulation. AutoMapper requires minimal user input, is force field independent, and has shown marvellous performance on a wide range of polymerisation types.",

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N1 - Funding Information: This research received no external funding. M. A. Bone is supported by the Engineering and Physical Science Research Council as part of the EPSRC Centre for Doctoral Training in Composites Science, Engineering, and Manufacturing. Grant number: EP/S021728/1 . M. A. Bone would like to thank Jacob Gissinger, Andrew Jewett and Benjamin Jenson for their useful discussion around the development of AutoMapper. Publisher Copyright: © 2022 The Authors

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N2 - Polymeric materials modelling has the potential to rapidly accelerate the discovery of new materials due to the comparative ease of simulations compared to laboratory testing campaigns. High quality molecular dynamics simulation software, such as LAMMPS, are able to facilitate the transition from empirical to digitised chemistry. However, in order to fully benefit from the speed of simulations, tools need to be developed to automate the preprocessing stages required for modelling. AutoMapper is an open-source Python application that automates the generation of files required to use REACTER, a powerful polymer bonding package implemented within LAMMPS. To automate this process, the authors developed an iterative path search algorithm based on chemical graph theory to accurately map pre- and post-reaction polymerisation structures, and hence eliminating the bulk of the human effort previously required to run a simulation. AutoMapper requires minimal user input, is force field independent, and has shown marvellous performance on a wide range of polymerisation types.

AB - Polymeric materials modelling has the potential to rapidly accelerate the discovery of new materials due to the comparative ease of simulations compared to laboratory testing campaigns. High quality molecular dynamics simulation software, such as LAMMPS, are able to facilitate the transition from empirical to digitised chemistry. However, in order to fully benefit from the speed of simulations, tools need to be developed to automate the preprocessing stages required for modelling. AutoMapper is an open-source Python application that automates the generation of files required to use REACTER, a powerful polymer bonding package implemented within LAMMPS. To automate this process, the authors developed an iterative path search algorithm based on chemical graph theory to accurately map pre- and post-reaction polymerisation structures, and hence eliminating the bulk of the human effort previously required to run a simulation. AutoMapper requires minimal user input, is force field independent, and has shown marvellous performance on a wide range of polymerisation types.

KW - Molecular Dynamics

KW - LAMMPS

KW - Polymer Simulation

KW - Open Source Software

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DO - 10.1016/j.commatsci.2022.111204

M3 - Article (Academic Journal)

SN - 0927-0256

VL - 205

JO - Computational Materials Science

JF - Computational Materials Science

M1 - 111204

ER -

AutoMapper: A python tool for accelerating the polymer bonding workflow in LAMMPS

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