This is the dataset and software supporting the study Theory of flow-induced covalent polymer mechanochemistry in dilute solutions by Etienne Rognin, Niamh Willis-Fox, Ronan Daly, Institute for Manufacturing, Department of Engineering, University of Cambridge, 17 Charles Babbage Road, Cambridge CB3 0FS, United Kingdom.

Contents

Main file ^^^^^^^^^

Use the Jupyter Notebook Supporting information.ipynb to run the data analysis and recreate the figures of the paper.

Alternatively, open Supporting information.pdf to view the notebook outputs in a PDF reader without having to install and run the scripts.

Raw data ^^^^^^^^

The folder bead-rod_dataset contains the results of bead-rod model simulations. For each simulation there is binary Python .npz file containing the data, and a text .json file containing metadata (such as date of the simulation, parameters...)

The data is imported using np.load function which creates a Python dictionary for each simulation file. This dictionary contains the following labels:

1. t the time axis.
2. gradU the time series of velocity gradients used as forcing terms in the bead-rod simulation.
3. g_max the time series of the maximum tensile force, for each molecule of the simulation ensemble.
4. i_max the time series of the positions of the maximum force in the chain (not used in this study)
5. g_12 the time series of the tensile force at the center of the chain, for each molecule.
6. A_average the time series of the average conformation tensor (second-order moment of the end-to-end vector). Used in section 4 for model validation.

Note that the bead-rod algorithm and dimension normalization are described in a previous study (see Rognin et al. https://www.repository.cam.ac.uk/bitstream/1810/279443/1/multiscale_revision_clean.pdf)

Other ^^^^^

The notebook JHTD_turbulence.ipynb has been used to extract data from the Johns Hopkins Turbulence Databases and is provided here for illustrative purposes only (it is not necessary to run this file).

License

CC-BY-4.0

To view the full license, visit: https://creativecommons.org/licenses/by/4.0/legalcode

Installation

In the target directory, clone this repository::

git clone https://github.com/etiennerognin/flowmechanochem_dataset.git

Usage

Run the notebook Supporting information.ipynb (you will need to have Jupyter installed, see https://jupyter.org/). The Python distribution will need to have packages listed in requirements.txt.