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Machine learning based kinetic modeling on the thermal decomposition of plastic waste via pyrolysis

Primary supervisor

Jackie Rong


  • Lian Zhang, Zongli Xie, Michael Batten, Leo Zhang

This project aims to develop a machine learning based kinetic model for an accurate prediction on the product yield and quality from the pyrolysis of plastic waste. The primary outcome of the Project is the development of a robust model that is effective in simulating the entire pyrolysis process at a relatively low computing cost, whereas its results will be sufficiently accurate to predict the composition and yields of the products. As a heterogeneous material with different types and compositions, waste plastic has a varying product distribution upon its thermal decomposition, which is further complicated by the process operating parameters such as heating rate, reactor type and the addition of catalyst within the reactor. This Project is significant in addressing this scientific knowledge gap, thereby delivering an accurate model that is beneficial in the large-scale reactor sizing and product quality control. Ultimately, the Project will cast an impact on the development of circular economy within Australia and even globally, promoting the recycling and reuse of waste plastic in a value-added manner.

This project is funded by CSIRO's Industry PhD (iPhD) scholarship program ( This program provides a great opportunity to "get real-world experience, develop transferable professional skills, and be well-positioned to work at the cutting edge of industry focussed research while accessing specialised expertise, equipment and training". The selected candidate will receive a four-year scholarship package of $46,000 per annum *2024 rate). For more details, please check the information for students from (

Required knowledge

Australian Domestic Student Only

Essential skills:

1) An H1 or H2A bachelor degree in the relevant discipline area or equivalent accreditation and standing, with a primary study area in Computer Science and/or Chemical Engineering or equivalent;

2) Excellent mathematical and programming skills, in particular in the areas of Artificial Intelligence (AI) and machine learning including deep learning and network-based optimisation; and coding programs including Python, R and Matlab;

3) Excellent written and verbal communication skills.

Desired skills:

4) Degree and/or knowledge on core chemical engineering disciplines such as reaction engineering, kinetic and process simulation;

5) Knowledge of chemistry and polymer science. 

Project funding

Project based scholarship

Learn more about minimum entry requirements.