Code Repo for "Understanding polymer zip length through the lens of mechanistic modeling"

Overview

This repository contains computational models for understanding zip length of depolymerization through a mechanistic modeling lens. The work compares two computational approaches to analytical expressions:

1. Kinetic Monte Carlo (KMC)
2. Method of Moments (MoM)
3. Boyd (1959)

Publication

Title: Understanding polymer zip length through the lens of mechanistic modeling

DOI: https://doi.org/10.1021/acs.macromol.6c01473

Contents

kmc_src/ — Kinetic Monte Carlo Simulations

• spedup_cpp_files/ — KMC source code for simple mechanisms

  • main.cpp, reaction_functions.cpp/h, save_variables.cpp/h — Core simulation engine in C++17
  • Makefile — Compilation instructions (requires g++)
  • params.inp — Temperature-dependent kinetic parameters (A, Ea for I/D/T/SR reactions)
  • T_260/ — Simulations at multiple DPn values (100, 150, ..., 4000) for scaling analysis

• polyME_cpp_files_conv/ — KMC source code for modeling polyME depolymerization

  • run_conv_4_2_26/ — Simulation outputs at three conditions (T=250°C/300°C, ρ=5/25 g/L)
  • no_sr_run_conv_4_2_26/ — Control runs without side reactions

mom_src/ — Method of Moments Simulations

• T260/run400/ — MoM ODE solutions for comparison with KMC at DPn=400

paper_analysis/ — Figure Generation & Analysis

• plot_figures.ipynb — Jupyter notebook generating all publication figures (Main Figs 2–6 + SI Figs S3–S8)
• plot_helpers.py — Data loading and processing functions
  • read_data() — Loads KMC CSV outputs (time_based_data, zip_length, chain_weights, params)
  • process_data() — Calculates derived quantities (radical concentrations, Mn, zip length corrected values)
• presentation.mplstyle — Matplotlib style file for publication-quality figures
• fig_pdfs/ — Output directory for generated figures

parameter_exploration/ — Parameter Space Analysis

• radical_KMC_runs/ — Output directory for Scheme 2 radicals
• rs_methods_all_dpn_og_v*.csv — Comprehensive parameter search results for Scheme 1
• eci_summary_with_plots.csv — Comprehensive parameter search results for Scheme 2

Installation & Requirements

For Analysis Only (Jupyter Notebook)

Python: 3.8 or higher

Dependencies: pandas numpy matplotlib scipy scikit-learn jupyter

For KMC Simulations (C++ Compilation)

Compiler: g++ with C++17

Compile:

cd cpp_file_src
make

Usage

Reproducing Figures

All publication figures are generated from a single notebook:

Run cells sequentially to generate:

• Figure 2 — Model comparison (KMC vs MoM) at DPn=400
• Figure 3 — Scaling with initial chain length (DPn = 100, 400, 2000)
• Figure 4 — Parameter space exploration (KMC + ECI data)
• Figure 5 — ECI special cases across DPn values
• Figure 6 — Best-fit kinetics at three conditions (T, ρ variations)
• Figures S3–S8 — Supplementary analyses

Running KMC Simulations from Scratch

1. Modify parameters in kmc_src/polyME_cpp_files_conv/params.inp

2. Compile:

   cd kmc_src/polyME_cpp_files_conv
   make

3. Run (example):

   mkdir -p run_custom && cd run_custom
   cp ../params.inp ../program .
   ./program

   Generates: time_based_data.csv, zip_length.csv, chain_weights_*.csv

4. Analyze with plot_helpers.read_data() in your script

Data

Included in Repository

• KMC Outputs — CSV time-series for key conditions (T=250/300°C, ρ=5/25 g/L)

  • time_based_data.csv — Time evolution: Mn, conversion, radical counts
  • zip_length.csv — Detected backbiting events: zip length, occurrence time
  • chain_weights_*pct_conversion.csv — Molecular weight snapshots at conversion milestones

• Parameter Exploration — Summary CSV files with computed metrics across parameter space

Large Data / Excluded Files

Extended simulation data (all DPn, all dispersities) available upon request. Contact authors for:

• Full spedup_cpp_files/T_260/ outputs
• ECI parameter sweep raw data
• All Method of Moments results

License

MIT License

Authors & Contact

• Code Author(s): Shivani Kozarekar, Dachey Lin (PI: Linda Broadbelt)
• Affiliation: Northwestern University, Department of Chemical and Biological Engineering
• Contact: shivanikozarekar2026@u.northwestern.edu

Citation

If you use this code or data, please cite:

@article{10.1021/acs.macromol.6c01473,
    author = {Kozarekar, Shivani S. and Lin, Dachey and Deshmukh, Gaurav and Hu, Qixuan and Ogunfowora, Lawal and Wu, Pengfei and Savoie, Brett and Dou, Letian and Gao, Hanyu and Broadbelt, Linda J.},
    title = {Understanding Polymer Zip Length through the Lens of Mechanistic Modeling},
    journal = {Macromolecules},
    year = {2026},
    month = {09},
}