(672b) Property Prediction and Outlier Identification Via Analogous Series | AIChE

(672b) Property Prediction and Outlier Identification Via Analogous Series


Peterson, B. K. - Presenter, ExxonMobil Research and Engineering

A novel correlation method is presented based on a general and useful regularity that exists between the properties of families of chemical species: the properties of the members of one family are shown to be simply, and often linearly, related to the properties of analogous materials in similar families. As examples, the phenomenon is shown to enable accurate predictive correlations from small amounts of data for properties such as critical temperatures, normal boiling points, adsorption in zeolites, infinite dilution activity coefficients, GC retention times, and closed-cup flash points. The method is suitable for single and multi-component systems and for equilibrium and transport properties and it produces useful correlations without any detailed structure/property model being assumed. The method is particularly useful for identifying outliers and/or anomalous data. A brief mathematical explanation is given and the relationship of the method to other methods is discussed.