Advances in Predictive Chemistry Enable a Multi-Scale Rational Design Approach for Biofuels with Advantaged Properties

Katherine Lockwood, Sheikh Ahmed, Nabila Huq, Sadie Stutzman, Thomas Foust, Nicole Labbe

Research output: Contribution to journalArticlepeer-review

3 Scopus Citations


Recent advances in computational resources and algorithm development have spurred progress toward rational chemical design. However, progress towards automated rational chemical design in fuel development and gas phase chemical systems in general have fallen behind other fields such as pharmaceuticals and material discovery. In this manuscript, recent advancements in automated fuel ignition/gas phase reaction kinetics tool development are leveraged to create a systematic process to develop reaction mechanisms for biofuel ignition properties and apply these mechanisms to practical applications to understand the link between chemical structure and observable chemical phenomena. The proof-of-concept application of this work uses our modeling methodology to extract the chemical rational for disparate ignition behavior between two linear alcohols: n-butanol and n-pentanol. Our methodology can accurately predict the ignition behavior of both fuels across wide temperature ranges without any influence of experimental data or adjustment, and for the first time, can successfully pinpoint the differences in ignition behavior to the δ-pentanol carbon site. This work is demonstrated in the context of low carbon biofuels and accurate prediction of ignition delay times to show the versatility and utility of this method that can also be applied to many other sustainable gas phase reaction applications, including CO2 reduction and utilization approaches.

Original languageAmerican English
Pages (from-to)5371-5383
Number of pages13
JournalSustainable Energy and Fuels
Issue number23
StatePublished - 2022

Bibliographical note

Publisher Copyright:
© 2022 The Royal Society of Chemistry.

NREL Publication Number

  • NREL/JA-5100-83608


  • advantaged fuel properties
  • biofuels
  • predictive modeling
  • rational fuel design


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