AI for life cycle assessment
Methods for data curation, inventory modeling, impact analysis, and interpretation support — with an emphasis on where AI assistance is defensible and where it is not.
Research
Research areas
Advancing the science and practice of sustainable design with AI — across assessment methods, process systems, and the infrastructure that connects them.
Sustainable process design
Process design, optimisation, and scale-up for industrial and bio-based applications, evaluated across technical, economic, and environmental criteria.
Circular economy systems
Material flow modeling, waste and recovery systems, and circularity metrics for products and regions.
Green hydrogen & low-carbon technology
Techno-economic and environmental evaluation of emerging energy technologies, with a focus on hydrogen production pathways under varying market conditions.
Open sustainability infrastructure
Open tools, data standards, and connector infrastructure that make sustainability science reproducible and reusable.
Approach
How we work.
Applied research that has to survive contact with a real decision, not just a paper.
01
Method first
Every tool starts from a documented method. If the method is contested, we say so rather than smoothing it over.
02
Reproducible by default
Analyses are versioned, scripted, and re-runnable. A result that cannot be reproduced is not a result.
03
Published openly
Code, assumptions, and limitations are published together so others can check and extend the work.
Technical papers & notes
Method notes, implementation write-ups, and documentation are collected in the technical library as they are published.
Interested in collaborating on research?
We work with academic groups, industry teams, and open-source maintainers on applied sustainability problems.