Method for rapidly determining optimal DSC sample amount to predict thermal safety parameter of autocatalytic substance

Abstract

The invention discloses a method for rapidly determining the optimal DSC sample amount to predict the thermal safety parameter of an autocatalytic substance. The method comprises the following steps: firstly, setting more than three groups of sample masses, carrying out a thermal decomposition test on the samples under a dynamic condition by using DSC to obtain initial decomposition temperatures T0, specific heat release amounts Q and peak temperatures Tp of the samples under different sample amounts, and analyzing the correlation between T0, Tp and Q and the sample amounts according to the change ranges and change trends of three thermodynamic parameters, if the thermodynamic parameters do not change obviously, selecting the maximum sample mass as a relatively conservative thermal safety parameter for predicting the optimal sample mass, and if the thermodynamic parameters change obviously, further comparing delta Y / delta X by taking the sample mass as an X variable and the thermodynamic parameters as a Y variable, and screening out the optimal sample mass in combination with different classification conditions. The method has the advantages of simple test conditions and short time consumption, can be widely applied to various autocatalytic substances, and can obtain more conservative and accurate evaluation results.

Description

Technical Field

[0001] The present invention belongs to the field of chemical thermal safety analysis, and relates to a method for quickly determining the optimal DSC sample amount to predict the thermal safety parameters of autocatalytic substances. Background Art

[0002] Autocatalytic substances have the characteristic of undergoing autocatalytic decomposition reactions under certain conditions, and the reactions are prone to be accidentally triggered by external influences. The consequences of the triggering are difficult to control, usually releasing a large amount of heat and gas, with great danger, resulting in thermal spontaneous combustion and explosion accidents during production and storage. Predicting the thermal runaway and explosion hazard parameters is one of the main tasks for the assessment of the thermal hazard of substances, which helps to optimize the conditions during the transportation and storage of chemicals. For example, an important parameter for a runaway reaction is the formation time of a thermal explosion under adiabatic conditions, or the time to maximum rate under adiabatic condition (TMRad). Therefore, the accurate acquisition of the kinetic test and thermal safety parameters of autocatalytic substances is of great significance for the actual application process.

[0003] Conventional process thermal safety assessment methods for obtaining thermal safety parameters have the advantages of simplicity and speed. However, in the actual process, when the reaction process is very complex, especially taking the thermal decomposition of some energetic materials with autocatalytic characteristics as an example, the models and kinetic parameters obtained with random sample masses are often insufficient to describe their complete decomposition process. Therefore, in the assessment process, there may be deviations or even errors in the kinetic calculation and assessment of thermal safety parameters based on a fixed sample amount.

[0004] In thermal analysis experiments, experimenters usually ignore the screening work of sample mass in order to save time, and select a certain fixed sample amount for testing and kinetic calculation results to study the thermal stability of the sample, providing a theoretical reference and basis for actual application so as to take preventive measures. However, when the sample mass has an impact on the thermodynamic parameters, the kinetic calculation and predicted thermal hazard parameters based on DSC data obtained under different sample amounts may also change. Therefore, finding a method for quickly determining the optimal DSC sample amount to predict the thermal safety parameters of autocatalytic substances is of great significance for the actual application process. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for quickly determining the optimal DSC sample amount to predict the thermal safety parameters of autocatalytic substances. This method combines the DSC of a thermal analysis instrument to obtain the initial decomposition temperature (T 0 ) and the heat release per unit mass (Q), and the peak temperature (T p)And judge the correlation between the three groups of thermodynamic parameters and the sample mass, screen out the optimal sample mass for kinetic testing, so as to predict more conservative and accurate thermal safety parameters, improve the limitations and accuracy of the existing evaluation methods, and provide reliable and complete information for the process of evaluating the thermal stability of self-catalytic substances.

[0006] The technical solution to achieve the object of the present invention is as follows:

[0007] A method for quickly determining the optimal DSC sample amount to predict the thermal safety parameters of self-catalytic substances, comprising the following steps:

[0008] S1: Prepare samples of the self-catalytic substance to be tested. According to the sample mass from low to high, the sample masses of each group are X 1 、X 2 、......、X i , i≥3;

[0009] S2: In a sealed crucible, use DSC to conduct thermal decomposition tests under dynamic conditions, and obtain the corresponding initial decomposition temperatures for each group of sample masses as T 01 、T 02 、......、T 0i , the corresponding specific heat release amounts for each group of sample masses are Q 1 、Q 2 、......、Q i , and the corresponding peak temperatures for each group of sample masses are T p1 、T p2 、......、T pi ;

[0010] S3: Calculate the change range ΔT 0 of T 0 , the change range ΔT p of T p , and the change range ΔQ of Q according to formulas (1), (2), and (3) respectively,

[0011] ΔT 0 = T 0max - T 0min (1), where T 0max is the highest initial decomposition temperature among all samples, and T 0min is the lowest initial decomposition temperature among all samples,

[0012] ΔT p = T pmax - T pmin (2), where T pmax is the highest peak temperature among all samples, and T pmin is the lowest peak temperature among all samples,

[0013] ΔQ = (Q max - Q min ) / Q 平均 (3), where Q max is the highest specific heat release among all samples, Q min is the lowest specific heat release among all samples, and Q 平均 is the average value of the specific heat releases of all samples;

[0014] S4: If the ranges of ΔT 0 and ΔT p are within 0 - 5 °C, the range of ΔQ is within 0 - 10%, and there is no obvious increasing or decreasing trend of change, it is determined that the sample quality has no effect on its thermodynamic parameters. At this time, the maximum sample quality is selected as the best sample quality for predicting thermal safety parameters;

[0015] If ΔT 0 or ΔT p is greater than 5 °C, or ΔQ exceeds 10%, and there is an obvious change rule for this thermodynamic parameter, it is determined that the sample quality has an effect on its thermodynamic parameters, and the next analysis is carried out according to S5;

[0016] If ΔT 0 and ΔT p are greater than 5 °C, ΔQ exceeds 10%, and there are obvious change rules for all three groups of thermodynamic parameters, it is determined that the sample quality has an effect on its thermodynamic parameters, and the next analysis is carried out according to S6;

[0017] S5: (1) If ΔQ exceeds 10%, the ranges of ΔT 0 and ΔT p are within 0 - 5 °C, and Q has an obvious change rule with the increase of sample quality, the following analysis is carried out:

[0018] When Q shows a change rule of first increasing and then decreasing, since the higher the specific heat release, the higher the degree of danger, at this time, the sample quality corresponding to the largest specific heat release is selected as the best sample quality for predicting thermal safety parameters;

[0019] When Q shows a monotonically increasing change rule, further compare the change trend Z Qi of ΔQ / ΔX to determine the best sample quality:

[0020] Take Compare Z Q1 , Z Q2 ,......, Z Q(i-1) in size. When there is a maximum value Z Qj , the best sample quality m best is obtained as follows:

[0021] Z Qmax = ZQj (j = 1, 2,......, i),

[0022] m best = X j+1 ;

[0023] (2) If ΔT 0 is greater than 5°C, ΔT p is in the range of 0 - 5°C, ΔQ is in the range of 0 - 10%, and as the sample mass increases, T 0 has an obvious change pattern. Further compare the change trend of ΔT 0 / ΔX to determine the optimal sample mass:

[0024] If T 0 shows a gradually increasing change pattern, take Compare the magnitudes. When there is a maximum value , the sample mass selected at this time is used as the optimal sample mass:

[0025]

[0026] m best = X j+1 ;

[0027] If T 0 shows a change pattern of first decreasing and then increasing, since the lower the initial decomposition temperature, the higher the risk level. At this time, the sample mass corresponding to the minimum initial decomposition temperature is selected as the optimal sample mass for predicting thermal safety parameters;

[0028] If T 0 shows a gradually decreasing change pattern, take Compare the magnitudes. When there is a minimum value , the sample mass selected at this time is used as the optimal sample mass:

[0029]

[0030] m best = X j+1 ;

[0031] (3) If ΔT p is greater than 5°C, ΔT 0 is in the range of 0 - 5°C, ΔQ is in the range of 0 - 10%. As the sample mass increases, T p has an obvious change pattern. Further compare the change trend of ΔT p / ΔX

[0032] If T p shows a gradually increasing change pattern, take Compare the magnitudes. When there is a maximum value , the sample mass selected at this time is used as the optimal sample mass:

[0033]

[0034] m best = X i+1 ;

[0035] If T p shows a change pattern of first decreasing and then increasing, since the lower the decomposition peak temperature, the higher the risk level, at this time, the sample mass corresponding to the minimum peak temperature is selected as the optimal sample mass for predicting thermal safety parameters;

[0036] If T p shows a gradually decreasing change pattern, take Compare the magnitudes. When there is a minimum value , the sample mass selected at this time is used as the optimal sample mass:

[0037]

[0038] m best = X j+1 ;

[0039] S6: If ΔT 0 , ΔT p are greater than 5°C and ΔQ exceeds 10%, and when there is an obvious change pattern in the three groups of thermodynamic parameters as the sample mass increases, analyze the optimal sample mass obtained for each thermodynamic parameter according to step S5. If the optimal sample masses obtained for the three groups of thermodynamic parameters are the same, then use it as the final optimal sample mass. If they are not the same, then further judge which thermodynamic parameter has the most obvious influence according to the values of ΔT 0 , ΔT p , ΔQ, specifically as follows:

[0040] (1) Divide the influence levels of each thermodynamic parameter. If ΔT 0 , ΔT p are in the range of 5 - 7.5°C and the ΔQ range is within 10% - 20%, it indicates that the influence degree of this thermodynamic parameter is low; if ΔT 0 , ΔT pIn the range of 7.5 - 10 °C but not equal to 7.5 °C, the ΔQ range is 20% - 30% but not equal to 20%, indicating that the influence degree of this thermodynamic parameter is medium; if ΔT 0 and ΔT p are in the range of 10 - 15 °C but not equal to 10 °C, and the ΔQ range is within 30% - 40% but not equal to 30%, it indicates that the influence degree of this thermodynamic parameter is high;

[0041] (2) If only one thermodynamic parameter has the greatest influence degree, at this time, the best sample mass obtained by analyzing it alone is used as the final best sample mass for predicting thermal safety parameters; if there are two or three thermodynamic parameters with the same influence degree level, at this time, the average value of the best sample masses obtained by analyzing the two or three thermodynamic parameters alone is used as the final best sample mass for predicting thermal safety parameters.

[0042] The self - catalytic substances described in the present invention are common substances with self - catalytic properties in the art, including but not limited to nitro - aromatic compounds such as 2,4 - dinitrotoluene, peroxides such as cumene hydroperoxide, azo substances such as azobisisobutyronitrile, dimethyl sulfoxide, azido - nitro compounds, etc. In the specific implementation manner of the present invention, 2,4 - dinitrotoluene is taken as a representative example.

[0043] Further, in S1, to ensure that the maximum value of the selected sample amount does not damage the instrument equipment and ensure the safe operation of the instrument, the mass of the self - catalytic substance sample is 0.5 - 2.0 mg.

[0044] In the thermal decomposition test of S2, a high - pressure sealed stainless - steel crucible is used to avoid the influence caused by the volatilization of products or itself, resulting in material or heat loss and thus affecting the experimental results.

[0045] Further, in S2, the temperature - rising rate adopted in the thermal decomposition test is 4 - 10 K / min.

[0046] Compared with the prior art, the present invention has the following advantages:

[0047] The method of the present invention has simple test conditions, short time - consuming, can avoid experimental errors caused by a single sample amount, and can be widely applied to substances with self - catalytic properties to obtain more conservative and accurate results for evaluating their thermal stability. During the test process, the environment of the closed system avoids the influence caused by the volatilization of products or the sample itself, resulting in material or heat loss, and improves the accuracy of the calculation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a dynamic DSC curve diagram of 2,4 - DNT under different sample masses.

[0049] Figure 2Comparison chart of the fitting curve and experimental curve of 2,4-DNT with a sample mass of 0.5 mg.

[0050] Figure 3 Comparison chart of the fitting curve and experimental curve of 2,4-DNT with a sample mass of 1.0 mg.

[0051] Figure 4 Comparison chart of the fitting curve and experimental curve of 2,4-DNT with a sample mass of 1.5 mg.

[0052] Figure 5 Comparison chart of the fitting curve and experimental curve of 2,4-DNT with a sample mass of 2.0 mg.

[0053] Figure 6 Temperature-TMRad curve graph of 2,4-DNT under different sample masses. Specific implementation mode

[0054] The present invention will be further described in detail below in conjunction with specific embodiments and the accompanying drawings.

[0055] In the following embodiments, the autocatalytic substance takes 2,4-dinitrotoluene (2,4-DNT) produced by the National Pharmaceutical Group with a purity of 99.5% as an example.

[0056] Embodiment 1

[0057] S1: Prepare the 2,4-DNT samples to be tested, and set four groups of sample masses of 0.5 mg, 1.0 mg, 1.5 mg, and 2.0 mg for testing, which are respectively represented as X 1 , X 2 , X 3 , X 4 .

[0058] S2: Under the high-purity nitrogen atmosphere, use a high-pressure sealed stainless steel crucible for sample loading, and use DSC to conduct thermal decomposition tests under dynamic conditions (10 K / min), as Figure 1 shown, to obtain three thermodynamic parameters of the starting decomposition temperature (T 0 ), specific heat release (Q), and peak temperature (T p ) of the substance thermal decomposition under different sample masses, and compare their regular differences. The corresponding parameters are shown in Table 1.

[0059] Table 1 Dynamic DSC results of 2,4-DNT under different sample masses

[0060]

[0061] Note: Q is the heat of decomposition; T 0 is the starting decomposition temperature; TP is the peak temperature.

[0062] S3: Combine Figure 1 It can be seen from Figure 1 and the data in Table 1 that at the masses of the four groups of samples, ΔT 0 is 0.9 °C, and ΔT p is 4.4 °C, with a change range within 5 °C. However, the corresponding thermodynamic parameters Q 1 , Q 2 , Q 3 , Q 4 increase monotonically with the increase of the sample mass, being 2306, 2645, 3120, and 3345 J / g respectively. It is known that ΔQ is 36.4%, and the change range exceeds 10%, indicating that one of the thermodynamic parameters in the above method is significantly affected, but the other two thermodynamic parameters do not change significantly. Therefore, the optimal sample mass is further analyzed and screened out.

[0063] S4: Compare the change trends of ΔQ / ΔX.

[0064] Take Compare the magnitudes of Z Q1 , Z Q2 , Z Q3 . When Z Qi has a maximum value, the sample mass selected at this time is used as the optimal sample mass:

[0065] Z Q1 = 678, Z Q2 = 950, Z Q3 = 450,

[0066] Z Qmax = Z Qi (i = 1, 2, 3)= Z Q2 ,

[0067] M best = X 3 = 1.5 mg.

[0068] S5: To verify the feasibility of this method, the corresponding temperature rise rate curves are obtained under the test conditions of different groups of sample masses for subsequent kinetic tests, and kinetic calculations and predictions of thermal safety parameters are carried out. The kinetic parameters are shown in Table 2-3, and the fitting results at different sample masses are as Figures 2 - 5 shown. The fitting correlation coefficients are 0.976, 0.980, 0.986, and 0.964 respectively. Among them, the fitting effect of the 1.5 mg sample amount is the best, further indicating the reliability of this model.

[0069] Table 2 Kinetic parameters of the first-stage reaction of 2,4-DNT at different sample amounts

[0070]

[0071] Table 3 Kinetic parameters of the second-stage reaction of 2,4-DNT with different sample amounts

[0072]

[0073] Prediction of the thermal hazard parameter TMR by combining the kinetic parameters obtained from the fitting analysis with the TSS software ad is shown as follows Figure 6 . It can be seen that the TD24 values of 2,4-DNT at sample masses of 0.5, 1.0, 1.5, and 2.0 mg are 187.9 °C, 179.1 °C, 178.0 °C, and 181.3 °C, respectively. By comparing the TMR ad at different masses, it is considered that the thermal safety parameters obtained from the experiment at the optimal sample mass of 1.5 mg are more conservative, accurate, and reliable.

Claims

1. Method for quickly determining the optimal DSC sample amount to predict thermal safety parameters of autocatalytic substances, characterized in that, it includes the following steps: S1: Prepare the autocatalytic substance samples to be measured. The masses of the samples in each group are X, X,....., Xx in ascending order of sample mass, where i ≥ 3. 1 、X 2 、.....、Xx,i≥3; S2: In a sealed crucible, perform a thermal decomposition test under dynamic conditions using DSC to obtain the initial decomposition temperatures corresponding to each group of sample masses as T 01 , T 02 ,......, T 0i , the specific heat release amounts corresponding to each group of sample masses are Q 1 , Q 2 ,......, Q i , and the peak temperatures corresponding to each group of sample masses are T p1 , T p2 ,......, T pi ; S3: Calculate ΔT 0 of the change range of T 0 , ΔT p of the change range of T p , and ΔQ of the change range of Q ΔT 0 = T 0max - T 0min (1), where T 0max is the highest initial decomposition temperature among all samples, and T 0min is the lowest initial decomposition temperature among all samples, ΔT p = T pmax - T pmin (2), where T pmax is the highest peak temperature among all samples, and T pmin is the lowest peak temperature among all samples. ΔQ = (Q max - Q min ) / Q 平均 (3), where Q max is the highest specific heat release among all samples, Q min is the lowest specific heat release among all samples, Q 平均 is the average value of the specific heat releases of all samples; S4: If ΔT 0 and ΔT p are in the range of 0 - 5 °C, ΔQ is in the range of 0 - 10%, and there is no obvious increasing or decreasing trend of change, it is determined that the sample quality has no effect on its thermodynamic parameters. At this time, the maximum sample quality is selected as the best sample quality for predicting thermal safety parameters; If ΔT 0 or ΔT p is greater than 5 °C, or when ΔQ exceeds 10%, and there is an obvious change rule for this thermodynamic parameter, it is determined that the sample quality has an impact on its thermodynamic parameter, and the next analysis is carried out according to S5; If ΔT 0 and ΔT p are greater than 5°C, ΔQ exceeds 10%, and there are obvious variation rules for all three groups of thermodynamic parameters, it is determined that the sample quality has an impact on its thermodynamic parameters, and the next analysis is carried out according to S6; S5: (1) If ΔQ exceeds 10%, ΔT 0 , ΔT p ranges from 0 to 5 °C, and as the sample mass increases, Q has an obvious change pattern. The following analysis is carried out: When Q shows a changing pattern of first increasing and then decreasing, since the greater the specific heat release, the higher the degree of danger, at this time, the sample mass corresponding to the maximum specific heat release is selected as the optimal sample mass for predicting thermal safety parameters; When Q shows a monotonically increasing variation pattern, further compare the variation trend Z of ΔQ / ΔX Qi to determine the optimal sample quality: Take Compare Z Q1 , Z Q2 ,......, Z Q(i-1) for their magnitudes. When there is a maximum value Z Qj , the optimal sample mass m best is obtained as follows: Z Qmax = Z Qj (j = 1, 2,......, i), m best = X i+1 ; (2) If ΔT 0 is greater than 5°C, ΔT p is in the range of 0 - 5°C, ΔQ is in the range of 0 - 10%, and as the sample mass increases, T 0 has an obvious change pattern. Further compare the change trend of ΔT 0 / ΔX to determine the optimal sample mass: If T 0 shows a gradually increasing change pattern, take to compare for their magnitudes. When there is a maximum value at this time, the sample mass selected is taken as the optimal sample mass: m best = X i+1 ; If T 0 shows a changing pattern of decreasing first and then increasing, since the lower the initial decomposition temperature, the higher the degree of danger, at this time, select the sample mass corresponding to the minimum initial decomposition temperature as the best sample mass for predicting thermal safety parameters; If T 0 shows a gradually decreasing change pattern, take to compare for size. When there is a minimum value , the sample mass selected at this time is used as the optimal sample mass: m best = X j+1 ; (3) If ΔT p is greater than 5°C, ΔT 0 is in the range of 0 - 5°C, ΔQ is in the range of 0 - 10%, and as the sample mass increases, T p has an obvious change pattern. Further compare the change trend of ΔT p / ΔX If T p shows a gradually increasing change pattern, take to compare for their magnitudes. When there is a maximum value , the sample mass selected at this time is taken as the optimal sample mass: m best = X j+1 ; If T p shows a changing pattern of decreasing first and then increasing, since the lower the decomposition peak temperature, the higher the degree of danger. At this time, the sample mass corresponding to the minimum peak temperature is selected as the best sample mass for predicting thermal safety parameters; If T p shows a gradually decreasing change pattern, take to compare for size. When there is a minimum value , the sample mass selected at this time is used as the optimal sample mass: m best = X j+1 ; S6: If ΔT 0 , ΔT p is greater than 5°C and ΔQ exceeds 10%, and when there are obvious variation rules for all three sets of thermodynamic parameters with the increase of sample mass, analyze the optimal sample mass obtained for each thermodynamic parameter according to step S5. If the optimal sample masses obtained for the three sets of thermodynamic parameters are the same, use it as the final optimal sample mass. If they are not the same, further judge which thermodynamic parameter has the most obvious influence according to the values of ΔT 0 , ΔT p , and ΔQ, specifically as follows: (1) Classify the influence levels of each thermodynamic parameter. If ΔT 0 and ΔT p are within the range of 5 - 7.5 °C and the ΔQ range is within 10% - 20%, it indicates that the influence degree of this thermodynamic parameter is low; if ΔT 0 and ΔT p are within the range of 7.5 - 10 °C but not equal to 7.5 °C and the ΔQ range is within 20% - 30% but not equal to 20%, it indicates that the influence degree of this thermodynamic parameter is medium; if ΔT 0 and ΔT p are within the range of 10 - 15 °C but not equal to 10 °C and the ΔQ range is within 30% - 40% but not equal to 30%, it indicates that the influence degree of this thermodynamic parameter is high; (2) If only one thermodynamic parameter has the greatest influence, at this time, the optimal sample mass obtained by analyzing it alone is used as the final optimal sample mass for predicting thermal safety parameters; if there are two or three thermodynamic parameters with the same influence level, at this time, the average value of the optimal sample masses obtained by analyzing the two or three thermodynamic parameters alone is used as the final optimal sample mass for predicting thermal safety parameters.

2. The method according to claim 1, characterized in that, the autocatalytic substance is a nitroaromatic compound, a peroxide, an azo substance, dimethyl sulfoxide or an azidonitro compound.

3. The method according to claim 2, characterized in that, the nitroaromatic compound is 2,4-dinitrotoluene, the peroxide is cumene hydroperoxide, and the azo substance is azobisisobutyronitrile.

4. The method according to claim 1, characterized in that, in S1, the mass of the autocatalytic substance sample is 0.5 - 2.0 mg.

5. The method according to claim 1, characterized in that, in S2, the temperature rise rate used in the thermal decomposition test is 4 - 10 K / min.

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