Zhihao Xing

Research

Project title: AI-guided molecular simulations for optimising combustion mechanisms of sustainable aviation fuels (AIM-SAF)

Aviation is one of the most difficult sectors to decarbonise. Sustainable Aviation Fuels (SAF) are considered one of the most promising solutions for reducing aviation-related greenhouse gas emissions, but important scientific questions remain about how these fuels burn and how they generate pollutants such as nitrogen oxides (NOx) and soot. The AIM-SAF project develops a new data-driven approach to understand combustion at the molecular level. By combining quantum chemistry, machine learning, and large-scale molecular simulations, the project will identify previously unknown chemical reactions involved in pollutant formation. These discoveries will be used to build more accurate combustion models that can predict combustion performance and emissions under realistic engine conditions. Although the project focuses on sustainable aviation fuels, the developed framework can be extended to a wide range of alternative low-carbon fuels and energy carriers. AIM-SAF addresses major societal challenges including climate change mitigation, sustainable transport, and the transition to cleaner energy systems. The project supports the European Green Deal and the EU objective of achieving climate-neutral aviation by helping researchers and industry develop cleaner and more efficient aviation fuels while reducing environmental impacts and improving air quality.