2020 Virtual AIChE Annual Meeting
(148b) An Improved Method for Predicting Autoignition Temperatures Based on First Principles
Authors
Mark E. Redd - Presenter, Brigham Young University
Thomas A. Knotts, Brigham Young University
Neil Giles, Brigham Young University
Wade Vincent Wilding, Brigham Young University
Joseph M. Black, Brigham Young University
Glenn Seaton, Seltron LLC
Methods for predicting autoignition temperatures (AIT) have been historically inaccurate and are rarely based on the underlying physical phenomena leading to observed AIT. Previous attempts at predicting AIT have been developed based on Quantitative Structure-Property Relationships (QSPR) and additive group contribution methods. This work presents an improved method for predicting AIT based on the method originally developed by the late Dr. William H. Seaton. The method of Seaton is described in detail including its use of first principles to predict AIT. Improvements on the method of Seaton and underlying principles are presented and discussed.