Nanoparticle Shape Lab

Simulates the low-energy shapes of nanocontainers over a wide range of solution conditions

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Version 2.0.1 - published on 08 Jan 2021

doi:10.21981/X2HX-EV75 cite this

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Abstract

The shape of nanoparticles determines their ability to interact with biological systems in nanomedicine applications. This app simulates the shape deformation of deformable patchy nanoparticles for a broad variety of nanoparticle material properties and solution conditions. Molecular dynamics based simulated annealing is used to minimize the energy of the nanoparticle for a given set of material and solution parameters. Users can input control parameters such as the maximum surface charge, surface patch size, stretching modulus, and bending modulus, as well as control the solution ionic strength (salt concentration) changing the electrostatic drive to deform. Changing patch size parameter tunes the surface charge from a small value close to 0 to the maximum surface charge selected by the user. Suggested values of patch size are 0.25, 0.5, 0.75, 0.9 to observe a wide range of shape transitions. After running the simulation, in various output tabs, users can view the snapshots of the nanoparticle shape at various stages of the energy minimization process. Plots of the minimization of the electrostatic energy and increase in the area of the nanoparticle are also available (both these quantities are normalized by the associated values of the initial spherical conformation). Volume of the nanoparticle is conserved, representative of a finite amount of cargo.  The range of charge, elasticities, and salt concentrations enable users to observe deformation into varios equilibrium shapes including bowls, hemispheres, discs, and rods, and egg-like conformations.  The app is ran using hybrid MPI/OMP parallelized C++ codes and Python post-processing and app deployment. After the simulation, the following data files can be downloaded: final image of the shape of the container (PNG), movie of the entire deformation process (LAMMPS output format for viewing in Ovito or VMD), raw area data (in units of the radius of the sphere), and raw energy data including electrostatic energy variation with time (in kB T).

Sponsored by

NSF award 1720625 (Network for Computational Nanotechnology - Engineered nanoBIO Node)

References

N. E. Brunk, JCS Kadupitiya and V. Jadhao, Designing Surface Charge Patterns for Shape Control of Deformable Nanoparticles, Physical Review Letters, 125 (2020)


N. E. Brunk and V. Jadhao, Computational studies of shape control of charged deformable nanocontainers, Journal of Materials Chemistry B 7, 6370 (2019)


V. Jadhao, Z. Yao, C. K. Thomas, and M. Olvera de la Cruz, Coulomb energy of uniformly-charged spheroidal shell systems, Phys. Rev. E. 91, 032305 (2015)


V. Jadhao, C. K. Thomas, and M. Olvera de la Cruz, Electrostatics-driven shape transitions in softshells, Proceedings of the National Academy of Sciences (PNAS) USA 111, 12673 (2014)

Cite this work

Researchers should cite this work as follows:

  • JCS Kadupitiya, Nicholas E. Brunk, Vikram Jadhao (2021), "Nanoparticle Shape Lab," https://nanohub.org/resources/npshapelab. (DOI: 10.21981/X2HX-EV75).

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