Properties vs. chemistry: Co-Optima research determines predictor of fuel performance, develops roadmap for biofuels design

Read the full story from Oak Ridge National Laboratory.

As Oak Ridge National Laboratory’s fuel properties technical lead for the U.S. Department of Energy’s Co-Optimization of Fuel and Engines, or Co-Optima, initiative, Jim Szybist has been on a quest for the past few years to identify the most significant indicators for predicting how a fuel will perform in engines designed for light-duty vehicles such as passenger cars and pickup trucks.

Most passenger vehicles on U.S. highways are powered by spark-ignition gasoline engines. It’s important for automakers to know how well a fuel will perform in these engines so that future vehicles can be designed with engines that achieve higher efficiency. Co-Optima, which was formed in 2016, has focused on research to maximize fuel economy and vehicle performance through higher efficiency and increased use of biofuels, resulting in new fuel performance insights.

Szybist and his research team at ORNL, working alongside Co-Optima collaborators from the National Renewable Energy Laboratory, Sandia National Laboratory and Argonne National Laboratory, determined it’s not so much the chemistry of a fuel that predicts performance, but rather its properties that hold the key to identifying a candidate with the potential for success. The research team published this finding in the journal Progress in Energy and Combustion Science, presenting for the first time comprehensive scientific details on Co-Optima’s initial phase of research.

Leave a Reply

Please log in using one of these methods to post your comment: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.