• Tests convert CO₂ into jet fuel-range hydrocarbons 

• Machine Learning-driven optimization identified an unconventional catalyst capable of achieving a record yield and more than 1,000 hours of continuous stability 

• The upgraded fuel met key prescreening parameters aligned with international aviation standards 

 Researchers at King Abdullah University of Science and Technology (KAUST), in collaboration with researchers from Aramco, have achieved the highest reported efficiency in converting carbon dioxide into jet fuel-range hydrocarbons, advancing the development of sustainable aviation fuel (SAF).  

A study, published in ChemCatalysis, describes a catalyst that converts carbon dioxide into long-chain hydrocarbons in the range of aviation fuel. The system achieved the highest reported yield for converting CO2 into jet fuel-range hydrocarbons for producing these heavier fuel molecules. Around 75% of the liquid product falls within the range required for jet fuel. The catalyst also operated continuously for more than 1,000 hours under reaction conditions, a critical aspect for industrial implementation. 

Aviation is widely regarded as a hard-to-abate sector due to its reliance on high-energy liquid fuels. While SAF helps reduce emissions in long-haul flights, producing it efficiently from captured CO₂ remains technically challenging because many existing pathways either favor lighter hydrocarbons, which evaporate too easily and lack the energy density required for aircraft engines, or involve multiple processing stages. 

To address this, the team integrated a machine-learning method that systematically explores complex experimental conditions. The approach identified an unconventional copper-rich catalyst formulation that outperformed more commonly studied compositions. The formulation delivered higher selectivity toward jet fuel-range molecules, meaning a greater proportion of the carbon was converted into usable aviation fuel components rather than lower-value byproducts. 

However, to confirm the relevance of the formulation as an SAF candidate, the liquid product was upgraded through hydrogenation and distillation. The resulting upgraded fuel met key prescreening parameters aligned with ASTM D4054 standards, including flash point, volatility profile, and energy content. 

“This work demonstrates how data-driven methods can accelerate catalyst discovery” said Jorge Gascon, Professor of Chemical Engineering at KAUST. “By combining machine learning with high throughput experimentation, we were able to reach performance levels not previously reported for direct CO₂ conversion.” 

Further scale-up, techno-economic evaluation, and certification processes will be required before commercial deployment. The findings, however, establish a new performance benchmark for direct CO₂ conversion and contribute to ongoing efforts to develop lower-carbon fuel pathways for hard-to-abate sectors.  

In addition to the MoU from which Aramco invested in KAUST to establish a "Super Center", the finding reflects the ongoing commitment in advancing research and development and accelerating energy technologies and clean energy innovation.