A method for constructing a model for quantitative analysis of energetic materials based on terahertz spectroscopy and an analysis method

Abstract

The application discloses a kind of based on terahertz spectrum's energetic material quantitative analysis model construction and analysis method, the disclosed model construction method includes first measurement a series of terahertz spectrum of containing different content energetic material sample, the terahertz spectrum of each sample and the content of the energetic material to be measured are input into modeling software, and model is established using partial least square method.The disclosed analysis method includes preparation sample to be measured, and the terahertz spectrum data of its terahertz spectrum data is measured, the terahertz spectrum data of sample to be measured is input into model, and finally the content numerical value thereof is obtained, so as to realize the rapid determination of energetic material component content.

Description

Technical Field

[0001] This application relates to the field of quantitative analysis technology, and in particular to a quantitative analysis model construction and analysis method for energetic materials based on terahertz spectroscopy. Technical Background

[0002] In practical research, production, and application, the content of the main energetic material components in mixed explosives plays a decisive role in quality control. Therefore, it is necessary to continuously develop new quantitative analysis techniques for energetic materials. Summary of the Invention

[0003] In view of the defects or deficiencies of the existing technology, the present invention provides a method for constructing a quantitative analysis model of energetic materials based on terahertz spectroscopy.

[0004] Therefore, the method for constructing a quantitative analysis model for energetic materials provided by this invention includes the following steps:

[0005] Step 1: Construct a dataset, which includes terahertz spectral data of multiple samples. At least three terahertz spectral data are obtained for each sample, and each spectral data is obtained under the same terahertz spectral measurement conditions. Each sample is composed of a background material and at least two energetic materials, wherein at least one of the energetic materials contains a known amount of the energetic material to be tested, and the content of the energetic material to be tested is different in each sample. The terahertz spectroscopy measurement conditions include sample preparation, spectral range, and humidity in the sample cell; the measurement sample is prepared using a mixed compression method, and the conditions for sample preparation include background material, total sample volume, and compression pressure and compression time of the mixed compression method; Step 2, Model Construction: Using the terahertz spectra of each sample and the content of the energetic material to be tested as inputs, the partial least squares method is used to construct the model.

[0006] Preferably, the cross-validation determination coefficient of the model is greater than 0.95, and the root mean square error of the cross-validation is less than 0.5%.

[0007] Optionally, each of the at least two energetic materials is a target energetic material, and the content of each energetic material is known. Further, the target energetic material is RDX or HMX.

[0008] Optionally, the background material is polyethylene, and the terahertz spectrum obtained by measuring pure polyethylene pellets is used as a blank background during measurement.

[0009] Optionally, the total mass of each sample is 300 mg, of which the mass of background material is 100-250 mg. As an example, the mass of energetic material can be, but is not limited to, 50, 62.5, 75, 87.5, 100, 112.5, 125, 137.5, 150, 162.5, 175, 187.5, 200 mg, or any range between any two of the above values.

[0010] Optionally, the spectral range is 0.1-3.0 THz, and the humidity in the sample cell is less than 3%.

[0011] This invention also relates to a quantitative analysis method for energetic materials. The method uses the same sample preparation method as in step 1 above to prepare the sample to be tested, measures the terahertz spectral data of the sample to be tested, and inputs the terahertz spectral data of the sample to be tested into the model constructed by the above method to obtain the content of the target energetic material in the sample to be tested.

[0012] This invention also provides a method for quantitative analysis of energetic materials. The method includes preparing a sample to be tested, measuring its terahertz spectral data, inputting the terahertz spectral data of the sample to be tested into a model, and obtaining its content value. Specifically, if the dataset contains the same type of energetic material as the sample to be tested, the model outputs the corresponding energetic material content; otherwise, it does not output any content.

[0013] This invention measures the terahertz spectra of a series of control samples containing different contents of energetic materials, inputs the terahertz spectra of the control samples into modeling software, and uses partial least squares method to establish a model. This model can be used to determine the content of the sample to be tested, and the error between the determined content and the actual content is small. Attached Figure Description

[0014] Figure 1 This is an example of terahertz spectral data measured in Example 1.

[0015] Figure 2 Example of terahertz spectral data measured for comparison.

[0016] Figure 3 The linear relationship between RDX absorption intensity and mass was established for comparison.

[0017] Figure 4 The linear relationship between HMX absorption intensity and mass was established for comparison. Detailed Implementation

[0018] To facilitate understanding of this application, a more complete description of the application will be provided below with reference to relevant embodiments. Preferred embodiments of the application are given below. However, the application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a thorough and complete understanding of the disclosure of this application.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0020] As used herein, the terms "and / or," "or / and," and "and / or" encompass any one of two or more of the related listed items, as well as any and all combinations of the related listed items. These arbitrary and all combinations include any two related listed items, any more related listed items, or a combination of all related listed items. It should be noted that when at least three items are connected using at least two conjunctions selected from "and / or," "or / and," and "and / or," it should be understood that, in this application, the technical solution undoubtedly includes solutions connected by "logical AND," and also undoubtedly includes solutions connected by "logical OR."

[0021] In this application, the technical features described in an open-ended manner include both closed technical solutions consisting of the listed features and open technical solutions that include the listed features.

[0022] In this application, numerical ranges are referred to as continuous unless otherwise specified, and include the minimum and maximum values ​​of the range, as well as every value between the minimum and maximum values. Furthermore, when the range refers to integers, it includes every integer between the minimum and maximum values ​​of the range. Additionally, when multiple ranges are provided to describe a feature or characteristic, the ranges may be merged. In other words, unless otherwise specified, all ranges disclosed herein should be understood to include any and all subranges to which they are incorporated.

[0023] This document only specifically discloses some numerical ranges. However, any lower limit can be combined with any upper limit to form an unspecified range; and any lower limit can be combined with other lower limits to form an unspecified range, just as any upper limit can be combined with any other upper limit to form an unspecified range. Furthermore, each individually disclosed point or single value can itself serve as a lower or upper limit and be combined with any other point or single value or with other lower or upper limits to form an unspecified range.

[0024] In this document, the term "suitable" as used in phrases such as "suitable combination," "suitable method," and "any suitable method" refers to the ability to implement the technical solution of this application, solve the technical problem of this application, and achieve the expected technical effect of this application.

[0025] In this application, terms such as "further," "even more," and "particularly" are used to describe purposes and indicate differences in content, but should not be construed as limiting the scope of protection of this application.

[0026] In this application, "optionally," "optionally," and "optional" mean that something is optional, that is, it means that it is selected from either "with" or "without." If there are multiple "optional" entries in a technical solution, unless otherwise specified, and there are no contradictions or mutual constraints, each "optional" entry shall be independent.

[0027] In the description of the application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0028] Unless otherwise specified, all embodiments and optional embodiments of this application can be combined to form new technical solutions. Unless otherwise specified, all technical features and optional technical features of this application can be combined to form new technical solutions.

[0029] Unless otherwise specified, all steps in this application may be performed sequentially or randomly, but sequentially is preferred.

[0030] The present invention provides a quantitative analysis model for energetic materials based on terahertz spectroscopy. The model involves first measuring the terahertz spectra of a series of control samples containing different amounts of energetic materials. The terahertz spectra of the control samples are then input into modeling software, and a model is established using partial least squares. The quantitative analysis method involves preparing the sample to be tested, measuring its terahertz spectral data, and inputting the terahertz spectral data of the sample to be tested into the model to obtain its content value, thereby achieving rapid determination of the content of energetic material components.

[0031] This invention is applicable to the quantitative analysis of energetic material components with terahertz spectra. The dataset used in model establishment includes terahertz spectral data of at least two energetic material samples, with each sample containing at least three spectral data points, and all spectral data were obtained under the same terahertz spectral measurement conditions.

[0032] The technical solution of the present invention will be described in detail below with reference to specific embodiments. It should be understood that these embodiments are only for illustrating the present invention and are not intended to limit the scope of the present invention. For experimental methods in the following embodiments where specific conditions are not specified, please refer to the guidelines given in this invention, or follow experimental manuals or conventional conditions in the art, or follow the conditions recommended by the manufacturer, or refer to experimental methods known in the art.

[0033] In the specific embodiments described below, the measurement parameters involving raw material components may have slight deviations within the weighing accuracy range unless otherwise specified. Temperature and time parameters are subject to acceptable deviations due to instrument testing accuracy or operational precision.

[0034] Example 1: In this embodiment, polyethylene was selected as the background material for sample testing. First, 300 mg of polyethylene powder was weighed and compressed to obtain pure polyethylene tablets. Then, RDX, HMX, and polyethylene powder were weighed in a mortar according to the mass in Table 1 to ensure that the total mass of polyethylene and energetic materials was 300 mg. After slight grinding, the mixed powder was compressed (10 MPa pressure for 30 s) to obtain tablets, and finally tablets with different contents of energetic materials were obtained.

[0035] Table 1 Sample preparation and weighing mass

[0036] For spectral measurements, pure polyethylene pellets were first placed in a sample cell, and nitrogen gas was introduced to reduce the humidity of the sample cell to below 3%. Terahertz spectra were then measured, with frequencies ranging from 0.1 to 3.0 THz. These spectra were subsequently used as background subtraction. Following this, samples of energetic materials with different contents were measured under the same conditions. After background subtraction, the terahertz spectra of each sample were obtained. Each sample was measured five times, yielding a total of 45 spectral data points. An example of the spectral data is shown below. Figure 1 As shown.

[0037] When establishing the model, the terahertz spectral data and RDX mass percentage of energetic material samples with different contents were input into MATLAB software. The partial least squares method was used to establish the model. The cross-validation determination coefficient of the model was 0.9815, and the root mean square error of the cross-validation was 0.16%, which met the model parameter requirements. At this point, the quantitative analysis model of energetic materials has been established.

[0038] Comparative example: This embodiment differs from Embodiment 1 in that it uses the linear relationship between the absorption intensity (dependent variable) and mass (independent variable) of the characteristic peaks in the terahertz spectrum (established by linearly fitting the absorption intensity to the mass in Origin software) for quantitative analysis. The characteristic peak of RDX is located at 0.75 THz, and the characteristic peak of HMX is located at 1.76 THz. The test samples for this comparative example are samples 3-9 from Embodiment 1. The tests were conducted in the same manner as in Embodiment 1, yielding a total of 7 spectral data points, as shown below. Figure 2 As shown, a linear relationship between RDX absorption intensity and mass is established using the characteristic peak absorption intensity and corresponding mass in this spectral data (see...). Figure 3 (as shown) and the linear relationship between HMX absorption intensity and mass (see) Figure 4 As shown in the figure, the correlation coefficients of the linear relationship between the absorption intensity and mass of RDX and HMX are 0.958 and 0.965, respectively, and the accuracy of the quantitative analysis based on this is low.

[0039] Example 2: Weigh 87.5 mg of RDX and 162.5 mg of HMX into a mortar, add 50 mg of polyethylene powder, and lightly grind. Compress the ground mixture to obtain a tablet. Place the tablet containing RDX and HMX in a sample cell, purge with nitrogen to reduce the humidity to below 3%, and then perform spectral measurements using the same method as in Example 1. After subtracting the blank background, obtain the terahertz spectrum of the tablet. Repeat the measurement three times and take the average value to obtain the terahertz spectral data. Input the above spectral data into the quantitative analysis model established in Example 1. After analysis and mass percentage conversion, the mass of RDX is 85.0 mg, with a relative error of [missing value]. 2.86%, HMX mass was 164.0 mg, and the relative error was 0.92%.

[0040] Example 3: 137.5 mg of RDX and 112.5 mg of HMX were weighed into a mortar, and 50 mg of polyethylene powder was added for light grinding. The ground mixture was then compressed into a tablet. The tablet containing RDX and HMX was placed in a sample cell, and nitrogen gas was introduced to reduce the humidity of the sample cell to below 3%. Spectroscopic measurements were then performed using the same method as in Example 1. After subtracting the blank background, the terahertz spectrum of the tablet was obtained. The measurements were repeated three times, and the average value was taken to obtain the terahertz spectral data. The above spectral data were input into the quantitative analysis model established in Example 1. After analysis and mass percentage conversion, the mass of RDX was 139.8 mg with a relative error of 1.67%, and the mass of HMX was 113.9 mg with a relative error of 1.24%.

[0041] Example 4: 187.5 mg of RDX and 62.5 mg of HMX were weighed into a mortar, and 50 mg of polyethylene powder was added for light grinding. The ground mixture was then compressed into a tablet. The tablet containing RDX and HMX was placed in a sample cell, and nitrogen gas was introduced to reduce the humidity of the sample cell to below 3%. Spectroscopic measurements were then performed using the same method as in Example 1. After subtracting the blank background, the terahertz spectrum of the tablet was obtained. The measurements were repeated three times, and the average value was taken to obtain the terahertz spectral data. The above spectral data was input into the quantitative analysis model established in Example 1. After analysis and conversion by mass percentage, the mass of RDX was found to be 184.7 mg, with a relative error of [missing value]. The content of HMX was 1.49%, the mass of HMX was 65.1 mg, and the relative error was 4.16%.

[0042] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for constructing a quantitative analysis model for energetic materials based on terahertz spectroscopy, characterized in that, The method includes the following steps: Step 1: Construct a dataset, which includes terahertz spectral data of multiple samples. At least three terahertz spectral data are obtained for each sample, and each spectral data is obtained under the same terahertz spectral measurement conditions. Each sample is composed of a background material and at least two energetic materials, wherein at least one of the energetic materials contains a known amount of the energetic material to be tested, and the content of the energetic material to be tested is different in each sample. The terahertz spectroscopy measurement conditions include sample preparation, spectral range, and humidity in the sample cell; the measurement sample is prepared using a mixed compression method, and the conditions for sample preparation include background material, total sample volume, and compression pressure and compression time of the mixed compression method. Step 2, Model Construction: Using the terahertz spectra of each sample and the content of the energetic material to be tested as inputs, the partial least squares method is used to construct the model.

2. The method for constructing a quantitative analysis model for energetic materials based on terahertz spectroscopy according to claim 1, characterized in that, The model's cross-validation determination coefficient is greater than 0.95, and the root mean square error of cross-validation is less than 0.5%.

3. The method for constructing a quantitative analysis model for energetic materials based on terahertz spectroscopy according to claim 1, characterized in that, In at least two energetic materials, each energetic material is the energetic material to be tested, and the content of each energetic material is known.

4. The method for constructing a quantitative analysis model for energetic materials based on terahertz spectroscopy according to claim 1, characterized in that, The energetic material to be tested is RDX or HMX.

5. The method for constructing a quantitative analysis model for energetic materials based on terahertz spectroscopy according to claim 1, characterized in that, The background material is polyethylene, and the terahertz spectrum obtained by measuring pure polyethylene pellets is used as the blank background during measurement.

6. The method for constructing a quantitative analysis model of energetic materials based on terahertz spectroscopy according to claim 1, wherein the total mass of each sample is 300 mg, and the mass of the background material is 100-250 mg.

7. The quantitative analysis model as described in claim 1, characterized in that, The spectral range is 0.1-3.0 THz, and the humidity in the sample cell is less than 3%.

8. A method for quantitative analysis of energetic materials, characterized in that, The sample to be tested is prepared using the same sample preparation method as in step 1 of claim 1. The terahertz spectral data of the sample to be tested is measured. The terahertz spectral data of the sample to be tested is input into the model constructed by the method described in any one of claims 1-7 to obtain the content of the target energetic material in the sample to be tested.

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