Method for predicting chemical or physical properties of complex mixtures

• US 5,602,755 A
• Filed: 06/23/1995
• Issued: 02/11/1997
• Est. Priority Date: 06/23/1995
• Status: Expired due to Term

• Current Assignee: Exxon Research and Engineering Company (Exxon Mobil Corporation)
• Original Assignee: Exxon Research and Engineering Company (Exxon Mobil Corporation)
• Inventors: Pho, Ronald T.-K., Kelly, Jeffrey D., Lau, Tian C., Ashe, Terrence R.
• Primary Examiner(s): Trammell, James P.
• Application Number:
  US08/494,201
• Time in Patent Office: 599 Days
• Field of Search: 364/498, 364/497, 364/499, 364/571.01, 364/571.02, 364/571.04, 73/1 R, 73/23.35-23.42, 250/281, 250/288, 250/339.12, 250/339.13, 250/252.1
• US Class Current: 702/30
• CPC Class Codes: G01N 2030/025 Gas chromatography
• CPC Class Codes: G01N 2201/1293 resolving multicomponent spectra
• CPC Class Codes: G01N 30/7206 interfaced to gas chromatograph interfaces in general for introducing or extracting samples to be analysed with specially adapted mass spectrometer, see H01J49/04
• CPC Class Codes: G01N 30/8644 Data segmentation, e.g. time windows
• CPC Class Codes: G01N 30/8682 Group type analysis, e.g. of components having structural properties in common
• CPC Class Codes: G01N 30/8693 Models, e.g. prediction of retention times, method development and validation
• CPC Class Codes: G01N 33/2829 mixtures of fuels, e.g. determining the RON-number
• CPC Class Codes: G16C 20/30 Prediction of properties of chemical compounds, compositions or mixtures
• CPC Class Codes: H01J 49/0031 Step by step routines describing the use of the apparatus H01J49/0081 takes precedence
• CPC Class Codes: H01J 49/0422 for gaseous samples interfaces to gas chromatographs G01N30/7206
• CPC Class Codes: H01J 49/4215 Quadrupole mass filters H01J49/4225 takes precedence

Abstract

A Method for predicting the properties of a complex hydrocarbon mixture which comprises selecting one or more known chemical, perceptual, physical or performance properties of the complex mixture and creating a training set from reference samples which contain characteristic molecular species present in the mixture. The reference samples are subjected to GC/MS analysis wherein the often collinear data generated are treated by multivariate correlation methods. The training set produces coefficients which are multiplied by the matrix generated from a GC/MS analysis of an unknown mixture to produce a predicted value for the chemical, performance or physical property or groups of properties selected.

Claims

1. A method for predicting physical, perceptual, performance or chemical properties of a complex hydrocarbon mixture which comprises:

(a) selecting at least one property of the hydrocarbon mixture;

(b) selecting reference samples, said reference samples containing characteristic compound types present in the complex hydrocarbon mixture and which have known values of the property or properties selected in step (a);

(c) producing a training set by the steps of;

(1) injecting each reference sample into a gas chromatograph which is interfaced to a mass spectrometer thereby causing at least a partial separation of the hydrocarbon mixture into constituent chemical components;

(2) introducing the constituent chemical components of each reference sample into the mass spectrometer, under dynamic flow conditions;

(3) obtaining for each reference sample a series of time resolved mass chromatograms;

(4) calibrating the mass chromatograms to correct retention times;

(5) selecting a series of corrected retention time windows;

(6) selecting within each retention time window a series of molecular and/or fragment ions, said ions being representative of characteristic compounds or molecular classes expected within the retention time window;

(7) recording the total amount of each characteristic compound or compound group selected in step c(6);

(8) forming the data from steps c(6) and c(7) into a X-block matrix;

(9) forming the data selected in (a) for reference samples selected in (b) into a Y-block matrix;

(10) analyzing the data from steps c(8) and c(9) by multivariate correlation techniques including Partial Least Squares, Principal Component Regression, or Ridge Regression to produce a series of coefficients;

(d) subjecting an unknown hydrocarbon mixture to steps c(1) to c(3) in the same manner as the reference sample to produce a series of time resolved mass chromatograms;

(e) repeating steps c(4) to c(8) for each mass chromatogram from step (d);

(f) multiplying the matrix from step (e) by the coefficients from step c(10) to produce a predicted value of the property or properties.

2. The method of claim 1 wherein the gas chromatograph is a capillary gas chromatograph and the mass spectrometer is a quadrupole mass spectrometer.

3. The method of claim 1 wherein the gas chromatograph and mass spectrometer are operated under repeatable conditions.

4. The method of claim 1 wherein the selection of a series of molecular and/or fragment ions characteristic of compounds or compound classes is accomplished using Chemist'"'"'s Rules.

5. The method of claim 1 wherein the selection of a series of molecular and/or fragment ions characteristic of compounds or compound classes is accomplished using Hydrocarbon Type Analysis.

6. The method of claim 1 wherein data from the gas chromatograph and mass spectrometer are stored in a computer.

7. The method of claim 1 wherein data from steps (c) to (f) are treated in a computer.

8. The method of claim 1 wherein other chemical, performance, perceptual or physical properties of the hydrocarbon mixture are selected.

9. The method of claim 1 wherein the data are collinear.

10. The method of claim 1 wherein the multivariate correlation technique is Partial Least Squares.