Chemical-Recycling Pathway Assessment for Mixed Plastic Waste
A chemical engineering study comparing ten mixed-plastic recycling pathways across feed tolerance, carbon retention, product quality, circularity, energy, climate, safety, scale and evidence uncertainty.
Project definition
Problem statement
Mixed plastic waste combines polymers, moisture, food residue, paper, metals, additives and halogens that affect reaction, separation, product quality, emissions and residues.
The engineering problem is to compare complete recycling pathways without treating reactor conversion, oil yield or a mass-balance claim as proof of polymer-to-polymer circularity.
Project objectives
- Compare pyrolysis, gasification, hydrothermal, dissolution, PET depolymerization, hydrogenolysis and cascade recovery pathways.
- Evaluate feedstock breadth, contamination tolerance, carbon yield, product quality and polymer circularity.
- Retain energy, climate, reagent safety, maturity, scale-up, economics and evidence positions.
- Test mixed municipal, polyolefin-rich, polyester-rich and halogen-contaminated contexts.
- Compare balanced, circularity, robustness and commercial decision priorities.
- Prioritize evidence through hard gates, uncertainty, sensitivity, FMEA and an assurance crosswalk.
Project structure
Project components
Pathway register
Declares ten pathway archetypes with transparent feed, product, circularity, energy, safety, scale and evidence positions.
Context model
Compares four waste-feed contexts without generalizing clean-feed evidence to contaminated municipal waste.
Decision model
Applies risk-specific gates and four transparent weighting scenarios to the same retained evidence.
Uncertainty model
Runs 20,000 fixed-seed samples per pathway and retains percentile and threshold results.
Assurance model
Ranks 180 workflow FMEA cells and links each pathway to fifteen evidence requirements.
Methodology
Project workflow
- 01Define the waste boundary
Waste origin, composition, sampling, sorting, washing, drying and rejects are declared.
- 02Compare complete pathways
Reaction, separation, upgrading, utilities, emissions, residues and final product remain inside the boundary.
- 03Apply decision priorities
Balanced, circularity, robustness and commercial scenarios expose conditional rankings.
- 04Propagate uncertainty
Fixed-seed sampling tests whether pathway positions persist when evidence values vary.
- 05Review validation gates
Feed, product, environment, safety, scale, carbon-yield and evidence gates cannot be cancelled by a weighted average.
Demonstration scenario
Under equal dimension weights, cascade sorting and polymer-specific recovery has the highest retained evidence position. Broad thermal routes remain stronger for mixed-feed acceptance, while PET depolymerization routes become stronger in polyester-rich contexts. The changing order is the main result: pathway choice depends on feed, product destination and engineering priorities.
Engineering
Tools and method
- Tools
- The project uses Python 3.12, NumPy, Pandas, Matplotlib for subject analysis, simulation, and results.
- Engineering model
- Python and NumPy implement the declared pathway, context, evidence and uncertainty calculations.
- Data analysis
- Pandas retains complete case matrices, summaries, scenarios, FMEA, assurance and sensitivity outputs.
- Figures
- Matplotlib generates twelve labelled comparison, uncertainty, risk and process-boundary figures.
- Reproducibility
- A fixed seed, explicit configuration, automated tests and Docker reproduce the study.
- Documentation
- The report covers waste composition, pathway chemistry, product quality, balances, lifecycle, safety, economics, methods, results and further work.
Testing
Evaluation
Evaluation measures
- Feedstock breadth and contamination tolerance
- Carbon yield, product quality and polymer-to-polymer circularity
- Energy efficiency, climate evidence and reagent safety
- Process maturity, scale-up readiness and economics
- Balanced, circularity, robustness and commercial scenario rankings
- Uncertainty intervals, sensitivity, workflow FMEA and assurance completeness
- Automated tests, accessibility audits, repository validation and container reproduction
Project boundaries
- Inputs are literature-informed screening positions, not measurements from one operating plant.
- Scores are not guaranteed yields, plant designs, safety assessments, lifecycle certificates or investment forecasts.
- Sorting efficiency, feed contamination, utility source, product acceptance, residue treatment and allocation can change the comparison.
- A site decision requires representative campaigns, complete balances, product trials, process safety review, local permits and qualified engineering assessment.
Included
- 01Complete reproducible Python source code
- 02Ten chemical-recycling pathway archetypes and twelve evidence dimensions
- 03800 deterministic pathway, risk, feed-context and evidence cases
- 04Four decision scenarios with 20,000 uncertainty samples per pathway
- 05180 workflow FMEA cells and 150 assurance crosswalk cells
- 06Complete CSV, JSON and twelve analytical figure outputs
- 07101-page project documentation in PDF and editable Word formats
- 0816-page setup and usage guide in PDF and editable Word formats
- 0960 annotated references and one sourced literature figure
- 10Automated tests, accessibility audits, repository validation and Docker verification
Project record
No information is collected on this page.
- Permanent project ID
- GP-CH-16L4GMP
- Catalogued
- 21 Aug 2026
- Completed
- 03 Sept 2026
- Verified
- 03 Sept 2026
- Demonstration
- Included in repository
Handover
After purchase
- 01Payment is confirmed
The project is marked unavailable and cannot be purchased again.
- 02Repository access is granted
The buyer's submitted GitHub account receives access to the private repository.
- 03The purchase record is delivered
The certification sheet is prepared from the reviewed buyer details and sent privately by email.