JPH04231849A - Prediction of quality of product by analysis of basic factor of spectrum of reacting body - Google Patents

Abstract

PURPOSE: To make it possible to predict the properties of reaction product by spectrally analyzing reactive material, and analyzing quantitative factor induced from the spectrum. CONSTITUTION: To confirm the individual values of a series of parameters varying together with the values of selected feature, test mixture is spectrally analyzed, and a series of quantitative factors corresponding to the confirmed value is induced. To induce the predicted value of the selected feature of the product, the regression coefficient of the quantitative factor is conducted by using the regression coefficient of the representative of the mutual relationship between the predetermined value of the selected feature of the product due to the preliminarily selected in a series of standard mixtures and the quantitative factor induced from the spectral analysis for the mixture. Thus, the properties of the product can be predicted.

Description

[Detailed description of the invention]

The present invention relates to the field of chemical methods, in particular to the field of quality control by factor analysis. In many types of chemical processes, whether the reaction products meet specifications can be determined in advance by monitoring the raw materials. As those skilled in the art know, this type of pre-quality control can result in considerable savings in time, energy usage and raw material costs.

However, reliable and meaningful information is needed, whether it is the raw material or the product being sampled. The contributing factors are:
How representative the sample is, whether it undergoes or does not undergo physical or chemical changes between sampling and analysis, and how often the sample is taken. The information should also be useful, i.e. it should provide a correct indication of the nature of the object, and should even be obtained from small samples, and the analysis should allow for remedial action before many reactions occur. should be early enough to do so. Predictions based on raw material analysis have the additional requirement that the property of interest should be one that can actually be predicted without first forming the product.

It has been discovered that a virtually unlimited variety of properties of reaction products can be predicted by factor analysis based on spectral data obtained for the raw materials. Factor analysis of spectral information is a known technique, and to date has been limited to predicting the performance characteristics of the materials on which the spectral analysis is performed, rather than the performance characteristics of reaction products of the materials. The novel and surprising discovery described in this invention is that this technique can be advantageously applied to systems where there is a chemical reaction between the material whose properties are predicted and the material being analyzed.

A document corresponding to the present invention is US Pat. No. 4,370,20, issued on January 25, 1983.
No. 1 (Lowenhaupt, D.E.) and 198
U.S. Patent Nos. 4 and 7 issued on October 20, 2017
No. 01,838 (Swinkels, D.A., etc.)
and Patent Coo on November 22, 1984.
perationTreaty, Publicity
on No. The latter includes the corresponding international application published as WO 84/04594. Lowenhau
pt discloses the use of factor analysis to monitor and adjust coal blends. Swinkels et al. disclose a regulated loop for continuous blending of solid particles of various materials using factor analysis to regulate the blend. Example 2 of Swinkels et al. describes a factor analysis on coal to predict the microstrength index of cakes made from coal, but this is only a change in crystal structure rather than a true chemical reaction. do not have. Additional literature on FTIR factor analysis can be found in Lowenh
References listed on the cover page of aupt and Swi
can be found in international search reports relating to international applications such as NKELS.

SPECIFIC DESCRIPTION OF THE INVENTION The analysis of the present invention is performed on a test mixture that is either a small representative sample isolated from the reaction mixture or a portion of the reaction mixture itself. The term "reaction mixture" is used to refer to a mixture containing unreacted species that is converted into products after reaction. The present invention is also directed to applications in systems that contain other components in addition to the reactants and in which other components are added or removed (eg, solvents) following analysis. The test mixture of the invention can be a single phase, for example a liquid mixture, solution or emulsion or a mixture of solid particles of different species or compositions. It is also directed to test mixtures containing both liquid and solid phases, such as slurries, suspensions and pastes. The product may also consist of single or multiple phases.

The invention also applies to systems in which the test mixture and the products differ in their phase composition, and in which the test mixture contains a liquid phase and no product, especially systems in which the reactants are liquids and Of particular interest are systems in which the product is a solid.

Reactions that convert reactants to products in a test mixture involve multiple reactants to produce products that differ in chemical structure, rather than reactions that simply differ from the reactants in their crystalline phase. It can be any of a wide variety of chemical reactions. The reaction can be either a reaction that produces a single species of product or a reaction that produces a mixture of products. Reactions that produce a single product from multiple reactant species are of particular interest, and polymerizations are of even more interest. Polymerizations of particular interest are copolymerizations involving multiple chemically different monomers.

Analysis can be used to analyze the quality, properties, parameters and characteristic counts of a wide variety of products (this is generally because these counts are determined only by the requirements related to the starting materials from which the products are manufactured). limited) can be used to predict. The analysis is limited to systems in which the chemical reactions themselves can be performed in a reproducible and standardized manner, avoiding the introduction of additional variables or factors that would affect the counts of products of interest. Thus, a reaction can be one in which the products are not affected by variations in operating conditions, or one in which the variations in products that occur in the reaction can be eliminated by standardizing the operating conditions.

Analysis is performed to detect defects or variations in the test mixture that would result in a product that does not meet specifications in one or more of these counts. Such defects and variations can include deviations in the proportions of the reactants and in the quality or properties of the reactant or reactants themselves. For example, if the reactants contain polyfunctional groups and/or multiple types of functional groups, deviations and fluctuations from one batch to the next (leading to variations in the product) can be detected. If the reactants are oligomers or prepolymers with a molecular weight distribution rather than a single well-defined species, deviations in the molecular weight distribution, such as the average molecular weight and its spread, can be detected. Reactants with high impurity levels and unusually low or high activities can also be detected.

The standards used to develop factors and factor loadings in factor analysis are first subjected to the same spectral analysis as the test mixture and then subjected to chemical reactions in a reproducible manner to produce the products. and the product is then tested or measured to confirm the count in the specifications. For best results, the standard will be a mixture of the same chemical species as the species in the test mixture, or at least the same species as would be expected to constitute the test mixture or be acceptable for the test mixture. .

[0011] Standards may themselves be characterized in characteristics such as proportions or amounts of ingredients, type and content of functionality, or in any other characteristic that would confer variation in the product count or the count in question. There would be several such mixtures varying between. The standards will be sufficient in number and variation over a sufficient range to select factor loadings that are sufficiently reliable and accurate to provide accurate predictions of product characteristics. The greater the number of standards, the better correlation exists. However, the optimal number will vary depending on the complexity of the system. As the number of components in a system increases, the number of standards required to establish certain precise interrelationships will also increase. In most typical systems, the number of standards used is between 10 and 60, preferably between 20 and 40.
It would be within the range of individuals.

The count itself will vary widely and will depend on the product. Propellants and explosives are one example of this type of product. The target count for this type is
Physical properties such as melting or freezing point, density, tensile strength, elongation and modulus; thermal properties such as differential thermal analysis; performance properties such as burning rate, detonation rate and combustion temperature; safety properties such as impact sensitivity, friction Sensitivity; electrostatic sensitivity, detonation sensitivity; and stability properties, such as thermal stability and vacuum stability. This analysis can be used to predict one such count value or multiple counts simultaneously.

The analysis is spectral analysis, such as various forms of spectrometry, spectrometry and spectrophotometry. Typical examples are atomic absorption spectroscopy, flame emission spectroscopy, mass spectrometry,
These are infrared spectroscopy, radar Raman spectroscopy, ultraviolet spectroscopy, visible spectroscopy, nuclear magnetic resonance spectroscopy, and electron spin resonance spectroscopy. The appropriate choice is the reaction system,
That is, it will depend on the chemical and physical properties of the substance and the type and expected properties of the reaction. Preferred spectral methods are infrared spectroscopy, laser Raman spectroscopy, ultraviolet spectroscopy and nuclear magnetic resonance spectroscopy;
And infrared spectroscopy is particularly preferred. This encompasses various types of infrared spectroscopy, and the appropriate choice for any particular system will depend on the characteristics of the system itself. Examples are central infrared, near infrared and diffuse infrared.

[0014] Simultaneous use of the entire range of frequencies is preferred because of the advantages it offers in terms of sensitivity and speed. Therefore, techniques that involve Fourier transform procedures are preferred, typically Fourier transform infrared (FTIR). Conventional measurements can be used to obtain such spectra.

Factor analysis has been disclosed in the literature and used for the prediction of performance characteristics of materials such as coal, peat moss, mineral ores, and preformed propellant mixtures based on analysis of the materials themselves. This can be done according to known techniques. One of the many such disclosures in the literature is Swinkels, D.; A. No. 4,701,838 and its corresponding International Application No. WO 84/04594, both of which are incorporated herein by reference.

In accordance with further known techniques, the general method is to derive factor loadings for a test mixture from selected features of the spectral analysis of the test mixture, followed by the predicted factor loadings for the product features. This would involve regression analysis to calculate the value. The regression analysis is preferably a regression line analysis, most preferably a multiple regression line analysis. The analysis is easily performed by computer, and a wide variety of commercially available computer systems with sufficient capacity for analysis can be used. Minicomputers are particularly well suited for analysis. As an example, HP
1000 series (Hewlett Packard)
and VAX system (Digital Equipme
nt Corporation). The following examples are for illustrative purposes and are not intended to limit the invention.

[0017]

EXAMPLE 1 A solid rocket engine propellant based on aluminum powder, ammonium perchlorate (AP) and Fe2O3 and a polybutadiene/acrylonitrile copolymer binder was prepared as a calibration set of 18 small premix batches. , where the amounts of AP, Fe2O3 and binder prepolymer were varied between batches to mimic the typical range of manufacturing tolerances and variability. FT-IR
Spectra were taken for individual premix batches,
It was then cured into its final form as a solid propellant, and its mechanical and physical properties were then determined. Similarly for this set, take the spectrum for the premix and
After curing, the product properties were then determined for the individual batches.

sending the FT-IR spectra of all samples to a VAX computer, where the spectra corresponding to the calibration set are used to derive factor loadings for a number of factors equal to the number of samples in that calibration set; The validation set was then subjected to factor analysis based on these factor loadings. The result was a set of predicted values for the composition of the premix and a set of predicted values for the physical and chemical properties of the cured propellant. These predicted values are averaged and compared to the averaged actual values and listed in the table below, which shows that the predicted and measured values correlate very closely. shows. The entries in the table that are properties of the propellant after curing are density, Shore "A" hardness, tensile strength, elongation, and modulus.

[0019]

[Table 1]

Example 2 A series of samples of an improved solid rocket engine propellant were prepared using a method similar to that of Example 1. These 18 samples differed in their binder, AP and Fe2O3 proportions and were therefore used as a calibration set. Binder, AP and Fe2O3
20 additional samples with also different proportions were used as test samples to compare the measured and predicted values of the modulus and elongation of the product obtained after curing, where Predicted values are FT-IR taken before curing
Based on spectrum. Figure 1 is a representative graph of predicted versus measured values of modulus of elasticity (in PSI), and Figure 2 is a representative graph of predicted versus measured values of modulus of elongation (in PSI). It is a graph. Lines were drawn in individual figures to show approximations of interrelationships.

Example 3 A series of Peacekeeper propellant ANB-3600 samples were prepared using a method similar to that of Example 2. Forty-nine unknown samples of premix for this propellant were submitted to analysis and the cured propellant modulus (P
A comparison of predicted vs. measured values for (SI) is graphically illustrated in Figure 3, where lines have been drawn to indicate an approximation of the correlation. Each point on this graph represents the average of duplicate samples for each premix. Although the preferred embodiments of the invention have been shown and described in detail, the scope of the invention is not thereby limited.

[Brief explanation of the drawing]

FIG. 1 shows predicted versus measured elastic modulus for a sample of improved solid rocket propellant based on FT-IR factor analysis of spectra taken for the propellant premix of the present invention. This is a plot of values.

FIG. 2 is a plot of predicted versus measured elongation for the same sample.

FIG. 3 is a plot of predicted versus measured modulus for a sample of Peacekeeper propellant taken in a manner similar to that used for FIG. 1;

Claims (10)

[Claims] 1. A method for predicting the value of a selected characteristic of a product of a preselected reaction of a number of reactants in a test mixture, comprising: (a) the value of the selected characteristic; carrying out a spectral analysis on said test mixture in order to ascertain the individual values of a series of spectral parameters that vary with the (c) the use of regression coefficients to derive predicted values for the selected characteristics of the product; performing a regression analysis on the quantitative factor by (i) the regression coefficient being a predicted value of the selected characteristic of the product resulting from the preselected reaction in a series of standard mixtures; and (ii) the spectral analysis performed on each of said standard mixtures.
) is representative of the interrelationship between quantitative factors induced in the manner of: 2. The method of claim 1, wherein the spectral analysis of step (a) is an analysis selected from the group consisting of infrared spectroscopy, laser Raman spectroscopy, ultraviolet spectroscopy, and nuclear magnetic resonance spectroscopy. 3. The spectral analysis in step (a) comprises:
Claim 1 comprising the simultaneous use of many frequencies of the spectrum and the determination of the inverse Fourier transform of the emission resulting therefrom.
Method described. 4. The method of claim 1, wherein the regression analysis of step (c) is a multiple regression line analysis. 5. Further, (d) comparing the predicted value from step (c) with the preselected value as a means of detecting deviations in the test mixture from a predetermined standard. 2. The method of claim 1, comprising: 6. The method of claim 1, wherein said reactant is different in phase from said product. 7. The method of claim 1, wherein the reactants are liquids and the products are solids. 8. The method of claim 1, wherein the test mixture is a slurry and the product is a solid. 9. The method of claim 1, wherein the preselected reaction is a polymerization reaction. 10. A method for predicting the value of selected characteristics of a solid material that is the product of a preselected reaction of a number of reactants contained in a test mixture comprising a liquid phase, comprising: ) performing a Fourier transform infrared analysis on the test mixture to ascertain the individual values of a set of spectral parameters that vary with the values of the selected features;
(b) deriving a corresponding set of quantitative factors from the values so ascertained, said quantitative factors so derived being derived in such a manner that they are representative of said values;
(c) performing a plurality of regression line analyzes on said quantitative factors by use of regression coefficients to derive predicted values for said selected characteristics of said product, wherein said regression The coefficients are based on (i) the predetermined value of the selected characteristic of the product resulting from the preselected reaction in a series of standard mixtures and (ii) the spectral analysis performed on each of the known mixtures. and (d) in step (c) as a means of detecting deviations in said test mixture from a predetermined standard. Comparing the derived predicted value and a preselected value.