AI-Driven Green Ammonia for Carbon-Neutral Hydrogen
This SCGC-FIRST project aims to enable cost-effective, carbon-neutral hydrogen production through improved ammonia synthesis and decomposition. Green ammonia is a promising hydrogen carrier, benefiting from established storage and distribution infrastructure, yet key aspects of its reaction mechanisms remain incompletely understood.
The project combines deep learning and reinforcement learning to autonomously uncover detailed chemical reaction pathways. By predicting potential energy surfaces and mapping reaction mechanisms with AI, the team seeks to generate accurate energy profiles and mechanistic insight beyond what is currently accessible through conventional approaches.
Prof Philip Torr
Professor of Engineering Science Five AI/Royal Academy of Engineering Research Chair in Computer Vision and Machine Learning
Dr Bruno Andreis
PDRA