Python for early-stage design of sustainable aviation fuels
Ali Martz, Kyle Niemeyer, Vi Rapp, Ana Comesana
Aviation accounts for 2% of global greenhouse gas emissions, and reliance on liquid petroleum-based fuels makes this sector challenging to decarbonize. We seek to accelerate the development of sustainable aviation fuels using an early-stage design tool with a data-driven approach. We developed our strategy using the Python-based optimization packages BoTorch and Ax, and also rely on Pandas. We will discuss how to down-select from many possible fuel components to a specified number of chemical species and identify which combinations are most promising for a novel sustainable aviation fuel. We will also present its integration in our open-source web tool supporting biofuel research.
