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nuSIMM: nanoHUB user Simulation Interface for Molecular Modeling
Simulated polymerization, equilibration, and characterization of molecular models
Version 1.0.4 - published on 10 Feb 2016
doi:10.4231/D3ZP3W18X cite this
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Abstract
This tool is designed to facilitate the “synthesis in the computer” of materials and characterize them requiring only building-block atomic information.
The tool consists of three independent modules. The first module, Polymerization, assists in generating virtual polymeric materials using the Polymatic algorithm. Polymatic is implemented using the computational algorithm published by Abbott and Colina (2013) and freely available Polymatic open-source code.
The second module, Equilibration, can be used to equilibrate a low density system to a realistic density for a given temperature and pressure in an entirely predictive manner using a compression/decompression simulation procedure described by Larsen, Lin, Hart and Colina (2011).
These two steps are often used in conjunction to design nanoporous polymeric materials for which the third module, Characterization, offers structural characterization capabilities implemented using Poreblazer v2.0 developed in the Sarkisov research group and published by Sarkisov and Harrison (2011).
For more information, see the documentation located within the tool by launching it with the button on the right-hand side of this page.
Version Information
Version 1.0.4 - February 10 2016
- General changes
- Polymatic v1.1 implementation
- Redesigned GUI
- Visualizations are now more colorful
- Packing
- Input to determine box size is now density instead of box length (eliminates need to scale parameter with varying system size)
- Uploading other systems
- There is no need to specify a forcefield template before uploading your own system
- Polymerization
- Each LAMMPS simulation during polymerization is submitted independently to a compute cluster. This decreases the chances your polymerization simulation will run out of wall time and also provides convenient feedback on the progress of your simulation.
- Each type of LAMMPS simulation (minimization, step md, cycle nvt/npt md) can either be sent to the cluster or not. For example you can perform minimization locally (in serial only) on the virtual machine, and run longer molecular dynamics simulations on a compute cluster on multiple processors.
- LAMMPS input for simulations during polymerization now have GUI settings instead of raw LAMMPS input, although editing raw input is still an option
- Equilibration
- Each of the 21 steps of the default equilibration simulation is submitted to the compute cluster independently. This also decreases the chances your simulation will run out of wall time and also provides convenient feedback on the progress of your simulation.
- Poreblazer Characterization
- Void volume and fractional free volume characterizations added. Void volume represents the volume within the simulation not occupied by the Van der Waals radii of the atoms in the system, which is in turn used to calculate the fractional free volume in the system.
- The pore size distribution simulation due to computational cost now must be sent to a compute cluster. More improvements coming soon!
Version 1.0.3 - July 11 2015
- Error catching was added when packing fails (i.e. - number of molecules doesn't fit in simulation box length selected by user)
Version 1.0.2 - July 9 2015
- Polymerizing PMMA now can make more than dimers.
Version 1.0.1 - July 6 2015
- Performing 21-step equilibration simulations with systems modeled with class2 forcefields (i.e. - PMMA) should now work.
Version 1.0 - June 18 2015
- Public release
nuSIMM features coming soon...
- new tutorials
- new pre-built molecular models
- toggle switch to disable polymerization (for now this is equivalent to setting the maximum bonds option to 0)
- control of 21-step equilibration simulation parameters (the actual LAMMPS input itself)
- new characterization techniques
- and more!
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Credits
We would like to thank the Strachan group, Ben Haley, and Chunyu Li at Purdue for helpful discussions.
Sponsored by
The development of this tool was supported in part by funding from the National Science Foundation (NSF) through grant ACI-1440685. Additionally, computational resources and support were provided by the Research Computing and Cyber infrastructure unit of Penn State Information Technology Services and the Materials Simulation Center of the Materials Research Institute.
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