AI-Powered Life Cycle Assessment for Emerging Clean Technologies
Explore how AI can revolutionize Life Cycle Assessment by automating data integration and modeling for emerging clean technologies. Work on real-world case studies to enhance sustainability feedback speed and reliability.
AI-generated overview
Project Description
Project Overview
The project focuses on developing an innovative AI-driven approach to automate and accelerate Life Cycle Assessment (LCA) for emerging clean technologies. Traditional LCA methods are time-consuming and rely heavily on expert judgement, which can delay sustainability feedback critical for rapidly evolving technologies such as advanced solar cells and batteries. By integrating multiple AI components into a coordinated workflow, this research aims to streamline data gathering, inventory refinement, and modeling processes specific to early-stage technological innovations.
What You Will Do
You will work under the supervision of Dr Andrea Paulillo and Dr Eike Cramer and collaborate with other groups in the department. Your tasks will include developing and refining AI tools to assist LCA practitioners, applying these tools to real-world case studies of next-generation solar cells and battery technologies, and evaluating AI’s effectiveness compared to traditional expert-driven methods. This hands-on work will engage with cutting-edge sustainability science and AI technologies.
Expected Outcomes
The project expects to deliver a novel, AI-powered LCA workflow that enhances the speed, consistency, reproducibility, and quality of environmental assessments. It will provide validated case studies demonstrating the approach’s value in real technology development contexts. The outcomes will help reshape sustainability assessments, facilitating quicker, more reliable environmental feedback for emerging clean technologies.
Why This Matters
As sustainability becomes increasingly urgent, accelerating accurate environmental assessments is crucial to guide technological innovation. The research addresses the current delays caused by manual and expert-dependent LCA processes. By automating and integrating AI into sustainability evaluations, the project advances how environmental impacts of new technologies are understood and mitigated, supporting a cleaner future.
Entry Requirements
How to Apply
Eligibility
Supervisor Profile
Dr. Andrea Paulillo is a researcher at University College London's Department of Chemical Engineering focusing on Life Cycle Assessment, planetary boundaries, energy systems, waste management, and carbon capture utilization and storage. Her approach integrates environmental modelling with sustainability science to understand and reduce the impacts of energy technologies. She has significant contributions in geothermal energy life cycle assessments and waste-to-energy processes, applying rigorous quantitative assessments to inform cleaner technologies.