Data for Configurations and Characteristics of Simulated Single-Chain Nanoparticles

Webb, Michael; Patel, Roshan; Colmenares, Sophia
Issue date: 2023
Rights:
Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC)
Cite as:
Webb, Michael, Patel, Roshan, & Colmenares, Sophia. (2023). Data for Configurations and Characteristics of Simulated Single-Chain Nanoparticles [Data set]. Princeton University. https://doi.org/10.34770/a2db-gy35
@electronic{webb_michael_2023,
  author      = {Webb, Michael and
                Patel, Roshan and
                Colmenares, Sophia},
  title       = {{Data for Configurations and Characterist
                ics of Simulated Single-Chain Nanopartic
                les}},
  publisher   = {{Princeton University}},
  year        = 2023,
  url         = {https://doi.org/10.34770/a2db-gy35}
}
Description:

This item provides access to all configurations of single-chain nanoparticles analyzed in the manuscript "Sequence Patterning, Morphology, and Dispersity in Single-Chain Nanoparticles: Insights from Simulation and Machine Learning" by Roshan A. Patel, Sophia Colmenares, and Michael A. Webb (DOI: 10.1021/acspolymersau.3c00007). The single-chain nanoparticles derive from 320 unique precursor chains that are distinguished by the fraction of linker beads that decorate a fixed-length polymer backbone and the distribution or blockiness of those linker beads. The data is provided in the form of serialized object using the `pickle' python module. The data was compiled using Python version 3.8.8 and Clang 10.0.0. The Python object loaded from the .pkl file is a nested list, with the first dimension having 7,680 entries for the 7,680 unique single-chain nanoparticles produced in the aforementioned paper. Each of those 7,680 entries is itself a list with 20 entries, representing the 20 different simulation snapshots of the given single-chain nanoparticle. Each of the 20 entries is another list with two entries, with the first being a numpy.ndarray containing the x,y,z coordinates of all the beads comprising the single-chain nanoparticle and the second being a numpy.ndarray with a numerical encoding to indicate whether the beads are backbone (indicated as '0') or linker beads (indicated as '1'). Altogether, this provides 153,600 configurations of single-chain nanoparticles.

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