Data and analysis code for "A Probabilistic Survival Function for Polypropylene Recyclability"

This repository contains the complete dataset and analysis pipeline underlying the above manuscript (submitted to iScience, Cell Press). Contents: Dataset_for_Analysis.csv — a 388-row hand-curated literature database compiled from 29 published, peer-reviewed polypropylene (PP) reprocessing studies (1991–2026). Each row records one measurement occasion (study × formulation arm × reprocessing-cycle count), with columns for melt flow index (MFI, g/10 min), its reported standard deviation where available, weight-average molecular weight (Mw), crystallinity (Xc), tensile strength at yield, processing temperature, PP subtype, stabilizer status, and publication metadata (DOI, journal, year, first author). HMEL_InHouse_Validation.csv — an 8-row controlled in-house reprocessing series (unstabilized vs. antioxidant-stabilized arms of a single 10-MFI virgin PP resin, 0–3 extrusion passes, measured at 230°C/2.16 kg per ISO 1133-1 / ASTM D1238 Condition L), used to validate and calibrate the antioxidant-stabilizer effect reported in the paper. ANALYSIS_CODE.py — the single Python pipeline (NumPy, SciPy, pandas, Matplotlib) that performs all data cleaning, statistical testing, log-normal survival-function modelling, Monte Carlo lifecycle simulation, and figure generation reported in the paper. Running it against the two CSVs above reproduces every statistic, table, and figure in the manuscript exactly. Reproducing the analysis: pip install numpy pandas scipy matplotlib python ANALYSIS_CODE.pyPlace both CSVs in the same working directory as the script (or pass a path as a command-line argument). Figures (vector PDF + 600 dpi PNG) and a console log of every reported statistic are written to ./output/.