Modeling method of prediction model of particulate matter retention coefficient of smoke in cigarette filter and particulate matter retention rate prediction method

Abstract

The invention provides a modeling method of a prediction model of a smoke particulate matter retention coefficient in a cigarette filter and a particulate matter retention rate prediction method, and the modeling method comprises the following steps: taking solanesol as a smoke particulate matter marker, obtaining the particulate matter retention coefficient of a reference cigarette filter at different smoking flow rates, and obtaining the particulate matter retention coefficient of the reference cigarette filter at different smoking flow rates through least square fitting; obtaining a relational expression between the interception coefficient of the smoke particulate matters in the standard cigarette filter and the smoking flow rate; obtaining an interception coefficient prediction model of the filter tip of the to-be-predicted cigarette according to the interception coefficient of smoke particulate matters in the filter tip of the reference cigarette, the pressure drop per unit length of the filter tip and the pressure drop per unit length of the filter tip of the to-be-predicted cigarette; and predicting the particulate matter retention rate by using the retention coefficient prediction model of the filter tip of the to-be-predicted cigarette.

Description

Technical Field

[0001] The present invention relates to the technical field of cigarette filter performance analysis. Specifically, it relates to a method for establishing a prediction model of the retention coefficient of particulate matter in cigarette filters and a method for predicting the retention rate of particulate matter. Background Art

[0002] As the main means of reducing tar in current cigarettes, the filter can efficiently filter out various components in mainstream cigarette smoke. According to whether they can pass through a Cambridge filter, the components of mainstream cigarette smoke are divided into particulate matter and gaseous matter. Therefore, the retention of cigarette components by the cigarette also includes particulate matter retention and gaseous matter retention. Given that tar and nicotine mainly exist in particulate form, the retention of particulate matter in cigarette filters by the filter has become the focus of research. However, currently, the retention rate of particulate matter in cigarette filters is mainly obtained through experimental determination. When the design parameters of cigarette filters change, their retention rates also change accordingly. To obtain the retention rates of these new samples, new experiments must be carried out, and this repetitive work is both time-consuming and resource-wasting. Therefore, establishing a prediction model for the filter retention rate has important research significance.

[0003] Currently, there have been relevant studies on the retention models of cigarette filters for cigarette smoke components. For example, the article "An Approximate Model for the Retention of Cigarette Smoke Components by Cigarettes" proposed a general double-exponential form model, which can better fit the retention data of cigarette filters for cigarette smoke components. However, a fixed retention coefficient of particulate matter in the filter was adopted in the fitting process of this model. In fact, there are differences in the retention coefficients of particulate matter in different filter samples, which limits the wide promotion of this model. In addition, a patent application with the publication number CN117825238A and the invention name "Method, Device and Computer Readable Medium for Establishing a Prediction Model of the Retention Rate of Cigarette Filters for Aerosol Particles" established a prediction model for the retention rate of aerosol particles based on the retention law of exogenous dioctyl phthalate (DOP) in the filter. However, the generation method of aerosol, solvent content, and particle size generation stability have a greater impact on the retention results, resulting in its inability to reflect the true particulate matter retention situation in the filter.

[0004] To solve the above existing problems, people have been seeking an ideal technical solution. Summary of the Invention

[0005] The purpose of the present invention is to address the deficiencies of the prior art, and thus provide a method for establishing a prediction model of the retention coefficient of particulate matter in cigarette filters and a method for predicting the retention rate of particulate matter. Solanesol in cigarette smoke is selected as a particulate matter marker in cigarette smoke, and its retention law in cigarette filters is investigated to reflect the true particulate matter retention situation in the filter, and further establish a prediction model for the retention coefficient of particulate matter in the filter by the filter, so as to realize the prediction of the retention rate of particulate matter in cigarette filters.

[0006] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] In a first aspect, a method for modeling a prediction model of the retention coefficient of particulate matter in a cigarette filter is provided, including the following steps:

[0008] Taking solanesol as a marker of particulate matter in mainstream cigarette smoke, obtain the retention coefficient k of the filter of reference cigarette m for particulate matter at different suction flow rates v;

[0009] Perform least-squares fitting on the retention coefficient k and the suction flow rate v according to the equation k = α + βv + γv -2 / 3 to obtain the relationship between the retention coefficient of particulate matter in the filter of reference cigarette m and the suction flow rate v: k m = α m + β ml v + γ m v -2 / 3 ;

[0010] According to the retention coefficient of particulate matter in the filter of reference cigarette m, the pressure drop per unit length of the filter, and the pressure drop per unit length of the filter of the cigarette x to be predicted, obtain the retention coefficient prediction model of the filter of the cigarette x to be predicted:

[0011]

[0012] wherein, v is the suction flow rate, ΔP x is the pressure drop per unit length of the filter of the cigarette x to be predicted, and ΔP m is the pressure drop per unit length of the filter of reference cigarette m.

[0013] The content of solanesol in mainstream cigarette smoke is high, its boiling point is 686 °C, it is extremely difficult to volatilize, almost all of it exists in cigarette particulate matter, and it is not easy to undergo changes such as adsorption, and the detection is relatively easy. Therefore, the present invention takes solanesol as a particulate marker, examines its retention law in the cigarette filter to reflect the true particulate matter retention situation in the filter, and further establishes a mathematical model for the filter to retain particulate matter in mainstream cigarette smoke based on the particulate matter retention situation, so as to truly and reliably predict the particulate matter retention rate in the cigarette filter.

[0014] Further, correct the pressure drop per unit length ΔP m of the filter of reference cigarette m and the pressure drop per unit length ΔP x of the filter of the cigarette x to be predicted to the same flow rate, and obtain the corrected retention coefficient prediction model of the filter of the cigarette x to be predicted:

[0015]

[0016] wherein the C m and C xThey are the circumferences C of the reference cigarette m and the cigarette x to be predicted respectively. l and C x They are the circumferences of the reference cigarette and the cigarette to be predicted respectively.

[0017] Furthermore, obtaining the interception coefficient k of the filter tip of the reference cigarette m for particulate matter at different suction flow rates v includes:

[0018] Suction the filter tip of the reference cigarette m according to the set suction volume. After the suction is completed, cut the filter tip of the reference cigarette to the same length. Using solanesol as a marker for particulate matter in the mainstream smoke, quantitatively analyze solanesol in each section of the filter tip and Cambridge filter respectively. According to the quantitative data of solanesol in different sections of the filter tip and Cambridge filter, calculate the penetration rate of solanesol in each section of the filter tip. Make a natural logarithm fit for the penetration rate and the filter tip length to obtain the interception coefficient of particulate matter in the cigarette filter tip under the set suction volume. Convert the suction volume into the suction flow rate to obtain the interception coefficient of particulate matter in the cigarette filter tip under the set suction flow rate.

[0019] Change the set suction volume and re - execute the above steps to obtain the interception coefficient k of the filter tip of the reference cigarette for particulate matter at different suction flow rates.

[0020] Furthermore, use the HPLC - DAD method to quantitatively analyze solanesol in each section of the filter tip and Cambridge filter:

[0021] First, extract solanesol in each section of the filter tip or Cambridge filter. After filtering the extract, send it into the HPLC - DAD instrument for analysis to obtain the chromatographic peaks of solanesol in different sections of the filter tip and Cambridge filter, and use the external standard method to quantitatively analyze solanesol in different sections of the filter tip and Cambridge filter.

[0022] Furthermore, the chromatographic conditions of the HPLC - DAD instrument are as follows: chromatographic column: Waters XBridge C18, specification: 4.6×75mm×3.5μm; mobile phase: methanol, flow rate: 1mL / min, isocratic elution; column oven temperature: 30°C; injection volume: 10μL; detection wavelength: 210nm; running time: 9min;

[0023] The extraction solvent is methanol.

[0024] Furthermore, when suctioning the filter tip of the reference cigarette m according to the set suction volume, set the suction number of puffs to 5 - 10 puffs, the suction interval to 10 - 20s, and suction 1 - 6 filter tips of the reference cigarette.

[0025] In a second aspect, a method for predicting the interception rate of particulate matter in a cigarette filter tip is provided, including the following steps:

[0026] Using the modeling method of the prediction model for the particulate matter retention coefficient of flue gas described in the first aspect, a prediction model for the retention coefficient of the filter tip of the cigarette x to be predicted is obtained;

[0027] Obtain the suction flow rate of the filter tip of the cigarette x to be predicted, and obtain the retention coefficient k of the filter tip of the cigarette x to be predicted x ;

[0028] Calculate the particulate matter retention rate E of the filter tip of the cigarette x to be predicted through the following formula:

[0029]

[0030] where l is the length of the filter tip of the cigarette x to be predicted.

[0031] The third aspect provides a prediction device for the particulate matter retention rate in a cigarette filter tip, including:

[0032] A memory for storing a computer program;

[0033] A processor, when executing the computer program, implements the steps of the method for predicting the particulate matter retention rate in a cigarette filter tip as described in the second aspect.

[0034] The fourth aspect provides a computer-readable medium, on which a computer program is stored, and when the computer program is processed and executed, it implements the steps of the method for predicting the particulate matter retention rate in a cigarette filter tip as described in the second aspect.

[0035] The fifth aspect provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the steps of the method for predicting the particulate matter retention rate in a cigarette filter tip as described in the second aspect. Brief Description of the Drawings

[0036] Figure 1 is a schematic flow chart of the modeling method of the prediction model for the particulate matter retention coefficient in a cigarette filter tip.

[0037] Figure 2 is a schematic flow chart of the method for predicting the particulate matter retention rate in a cigarette filter tip.

[0038] Figure 3 is a fitting diagram of the solanesol retention coefficient and the suction flow rate in the filter tip of a reference cigarette under different suction volumes. Detailed Embodiments

[0039] The following further describes the technical solutions of the present invention in detail through specific embodiments.

[0040] Example 1

[0041] This embodiment provides a method for modeling a prediction model of the retention coefficient of gaseous particulate matter in a cigarette filter, as Figure 1 shown, including the following steps:

[0042] 1) Calculation of retention coefficient

[0043] Taking solanesol as the marker of gaseous particulate matter in cigarette smoke, obtain the retention coefficient k of the filter of the reference cigarette m for particulate matter at different suction flow rates v.

[0044] In this embodiment, a reference cigarette m is selected, with a circumference of C m , the pressure drop per unit length of the filter is ΔP m , taking solanesol as the marker of its gaseous particulate matter, measure the retention distribution data of solanesol in its filter, and use it as the actual particulate matter retention situation in the filter.

[0045] Specifically, use a single-channel smoking machine, set the suction volume, light the reference cigarette m, suck the filter of the reference cigarette m, after the suction is over, cut the filter of the reference cigarette m into equal lengths, weigh each section of the filter to calibrate uneven cutting; it should be noted that if multiple cigarettes are sucked, the filter sections corresponding to different cigarettes need to be combined and weighed.

[0046] Quantitatively analyze solanesol in each section of the filter and in the Cambridge filter respectively, according to the quantitative data of solanesol in different sections of the filter and in the Cambridge filter.

[0047] Specifically, when quantitatively analyzing solanesol in each section of the filter and in the Cambridge filter, use the HPLC-DAD method. The specific steps are as follows:

[0048] Put the obtained different sections of the filter into conical flasks respectively, add an appropriate amount of extraction solvent, perform ultrasonic extraction, and at the same time put the corresponding Cambridge filter into the conical flask, add the extraction solvent, and perform ultrasonic extraction; preferably, the extraction solvent is methanol;

[0049] After the extraction is over, take an appropriate amount of the extract and filter it through an organic phase filter membrane into a chromatographic vial, and analyze solanesol by HPLC-DAD instrument respectively to obtain the chromatographic peaks of solanesol in different filter sections and in the Cambridge filter; preferably, the chromatographic conditions of the HPLC-DAD instrument are: chromatographic column: Waters XBridge C18, specification: 4.6×75mm×3.5μm; mobile phase: methanol, flow rate: 1mL / min, isocratic elution; column oven temperature: 30°C; injection volume: 10μL; detection wavelength: 210nm; running time: 9min;

[0050] Quantitatively analyze solanesol in different filter sections and in the Cambridge filter by the external standard method.

[0051] Specifically, the interception process of the filter tip for particulate matter in cigarette smoke conforms to the first-order interception equation, and the interception rate of the filter tip and the filter tip length can be expressed by formula (1):

[0052] ln(1-E) = -kl(1)

[0053] where E is the interception rate, 1-E is the penetration rate, l is the length of the filter tip interception section, and k is the interception coefficient.

[0054] Calculate the solanesol penetration rate of each section of the filter tip, perform a natural logarithm fitting on the penetration rate and the filter tip length, obtain a fitting curve passing through the origin, and the absolute value of the curve slope is the interception coefficient of the particulate matter in the cigarette filter tip under the set puffing volume;

[0055] After obtaining the interception coefficient of the particulate matter in the cigarette filter tip under the set puffing volume, convert the puffing volume into the puffing flow rate v to obtain the interception coefficient of the particulate matter in the cigarette filter tip under the set puffing flow rate.

[0056] Change the set puffing volume, re-execute the above steps to obtain the interception coefficient k of the reference cigarette filter tip for particulate matter at different puffing flow rates.

[0057] It should be noted that when setting the puffing volume of the single-channel smoking machine, the number of puffs, puffing time, and puffing interval are also set at the same time; when changing the puffing volume, the number of puffs, puffing time, and puffing interval remain unchanged.

[0058] Perform a least-squares fitting on the interception coefficient k and the puffing flow rate v according to the equation k = α + βv + γv -2 / 3 to obtain the relationship between the interception coefficient of the particulate matter in the filter tip of the reference cigarette m and the puffing flow rate v: k m = α m + β ml v + γ m v -2 / 3 .

[0059] According to the interception coefficient of the particulate matter in the filter tip of the reference cigarette m, the pressure drop per unit length of the filter tip, and the pressure drop per unit length of the filter tip of the cigarette x to be predicted, obtain the interception coefficient prediction model of the filter tip of the cigarette x to be predicted:

[0060]

[0061] where v is the puffing flow rate, ΔP x is the pressure drop per unit length of the filter tip of the cigarette x to be predicted, and ΔP m is the pressure drop per unit length of the filter tip of the reference cigarette m.

[0062] Furthermore, assume that the circumference of the filter tip of the cigarette x to be predicted is C x , and the pressure drop per unit length of the filter tip is ΔP x, according to the fact that the retention coefficient is proportional to the pressure drop per unit length of the filter tip at the same flow rate, the retention coefficient k of the filter tip of the cigarette x to be predicted can be obtained. x It is formula (2); however, according to the regulations in GB / T18767-2002, the filter tip pressure drop is measured at a standard flow rate of 17.5 mL / s. Therefore, when the circumferences of the reference cigarette and the cigarette x to be predicted are different, the pressure drop per unit length of the filter tip of the reference cigarette (ΔP m ) and the pressure drop per unit length of the filter tip of the cigarette x to be predicted (ΔP x ) correspond to different flow rates, and it is necessary to correct them to the pressure drop values at the same flow rate.

[0063] It is known that at 17.5 mL / s, the suction flow rate of the reference cigarette is The suction flow rate of the cigarette x to be predicted is Therefore, at the unit flow rate, the pressure drop per unit length of the filter tip of the reference cigarette The pressure drop per unit length of the filter tip of the cigarette x to be predicted where the C m and C x are the circumferences of the reference cigarette m and the cigarette x to be predicted respectively.

[0064] Therefore, the particulate retention coefficient k of the filter tip of the cigarette x to be predicted x is corrected as follows:

[0065]

[0066] Example 2

[0067] This example provides a method for predicting the retention rate of particulate matter in a cigarette filter tip, as Figure 2 shown, including the following steps:

[0068] Adopt the modeling method of the particulate matter retention coefficient prediction model described in Example 1 to obtain the retention coefficient prediction model of the filter tip of the cigarette x to be predicted;

[0069] Obtain the suction flow rate of the filter tip of the cigarette x to be predicted to obtain the retention coefficient k of the filter tip of the cigarette x to be predicted x ;

[0070] Calculate the particulate matter retention rate E of the filter tip of the cigarette x to be predicted through the following formula:

[0071]

[0072] where l is the length of the filter tip of the cigarette x to be predicted.

[0073] Apply Example 1

[0074] Select a reference cigarette with a circumference of 24.2 mm, a filter length of 30 mm, a filter pressure drop of 2900 Pa, and a filter length of 120 mm.

[0075] Use a single-channel smoking machine to aspirate it, with the aspiration volume set to 10 mL, the number of puffs to 10, the puff duration to 2 s, the puff interval to 10 s, and a total of 4 cigarettes are aspirated. After the aspiration is completed, extinguish the cigarettes, remove the filter sections of the cigarettes, and use an automatic slicer to slice the filters of the 4 cigarettes sequentially, with each section being 5 mm long and a total of 6 sections. Combine and weigh the corresponding filter sections of the 4 cigarettes for calibration of uneven slicing. Tear the cigarette paper and tow of the same section of the filter, put them into a 25 mL conical flask, then accurately add 10 mL of methanol, and ultrasonicate for 30 min. At the same time, put the Cambridge filter pads that have trapped the smoke of 4 cigarettes into a 50 mL conical flask, add 20 mL of methanol, and ultrasonicate for 30 min. Take an appropriate amount of the extract and filter it through a 0.45 μm organic phase filter membrane into a 2 mL chromatographic vial, and analyze solanesol by HPLC-DAD instrument respectively to obtain the chromatographic peaks of solanesol in different filter sections and Cambridge filter pads. Further, use the external standard method to quantify solanesol in different filter sections and Cambridge filter pads.

[0076] Similarly, set the aspiration volume to 15 mL and keep other steps unchanged to obtain the quantitative data of solanesol in different filter sections and Cambridge filter pads at an aspiration flow rate of 15 mL.

[0077] By analogy, the quantitative data of solanesol in different filter sections and Cambridge filter pads at aspiration volumes of 20, 25, 30, 35, 40, 45, 50, 55, 60, 70 mL can be obtained.

[0078] According to the quantitative results of solanesol in different filter sections and Cambridge filter pads, calculate the solanesol penetration rate of each section of the filter. Make a linear fit of the natural logarithm of the penetration rate and the filter length to obtain a fitting curve passing through the origin. The absolute value of the slope of the curve is the retention coefficient of solanesol. Fit the retention data at different aspiration volumes to obtain the solanesol retention coefficient of the reference cigarette filter at different aspiration volumes. Perform the least-squares fit of the filter solanesol retention data of the reference cigarette at different aspiration flow rates to the equation k = α + βv + γv -2 / 3 to obtain as Figure 3 .

[0079] From Figure 3 the fitting curve, the coefficients can be obtained, and then the relationship model between the particulate matter retention coefficient of the reference filter and the aspiration velocity is obtained as follows:

[0080] k = 0.00485 + 2.61078×10 -5 v + 0.11038v -2 / 3 (5)

[0081] Application Example 2

[0082] The circumference of the cigarette 1 to be predicted is 19.8 mm, the filter tip pressure drop is 3340 Pa, the filter tip length is 120 mm, and its filter tip retention rate at a puff volume of 35 mL is predicted. According to the method in Example 1, the retention amounts of solanesol in the filter tips of different lengths of the cigarette to be predicted and in the Cambridge filter were measured during the experiment when the puff volume was 35 mL. The experimental results are shown in Table 1.

[0083] Then, by combining formulas (5), (3) and (4), the filter tip particulate matter retention rate of the cigarette x to be predicted is predicted. First, it is necessary to calculate that the puff flow rate of the cigarette 1 to be predicted at a puff volume of 35 mL is 56.09 cm / s, and the filter tip pressure drops per unit length of the cigarette 1 to be predicted and the reference cigarette are 27.83 Pa / mm and 36.10 Pa / mm respectively. Substituting the above data and formula (5) into formula (3), the predicted retention coefficient of solanesol in the filter tip of the cigarette 1 to be predicted is calculated to be 0.0106.

[0084] The particulate matter retention rates of the filter tips of the cigarette 1 to be predicted at different lengths are calculated by formula (4). The results are shown in Table 1, and the relative deviation between the predicted value and the measured value of the retention rate is less than 5%.

[0085] Table 1 Experimental values and predicted values of the particulate matter retention rate of the filter tip of the cigarette 1 to be predicted

[0086] Length / mm Measured retention amount / μg Measured retention rate / % Predicted retention rate / % Relative deviation / % 5 51.48 5.42 5.16 -4.80 10 96.51 10.16 10.06 -0.98 15 138.16 14.55 14.70 1.03 20 178.54 18.80 19.10 1.60 25 215.55 22.69 23.28 2.60 30 251.84 26.52 27.24 2.71 Total amount 949.78 / /

[0087] Therefore, this method can accurately predict the retention coefficient of solanesol in the filter tip of medium-sized cigarettes.

[0088] Application Example 3

[0089] The circumference of the cigarette 2 to be predicted is 17 mm, the filter tip pressure drop is 3790 Pa, the filter tip length is 120 mm, and its filter tip retention rate at a puff volume of 35 mL is predicted. According to the method in Example 1, the retention amounts of solanesol in the filter tips of different lengths of the cigarette to be predicted and in the Cambridge filter were measured during the experiment when the puff volume was 35 mL. The experimental results are shown in Table 2.

[0090] Then, by combining formula (5), formula (3) and (4), the filter tip particulate matter retention rate of the cigarette x to be predicted is predicted. First, it is necessary to calculate that the puff flow rate of the cigarette 2 to be predicted at a puff volume of 35 mL is 76.09 cm / s, and the filter tip pressure drops per unit length of the cigarette 2 to be predicted and the reference cigarette are 31.58 Pa / mm and 48.97 Pa / mm respectively. Substituting the above data and formula (5) into formula (3), the predicted retention coefficient of solanesol in the filter tip of the cigarette 2 to be predicted is calculated to be 0.0084. The particulate matter retention rates of the filter tips of the cigarette 2 to be predicted at different lengths are calculated by formula (4). The results are shown in Table 2, and the relative deviation between the predicted value and the measured value of the retention rate is less than 6%.

[0091] Table 2 Experimental values and predicted values of the particulate matter retention rate of the filter tip of cigarette 2 to be predicted

[0092] Length / mm Measured retention amount / μg Measured retention rate / % Predicted retention rate / % Relative deviation / % 5 43.04 4.21 4.11 -2.38 10 84.54 8.27 8.06 -2.54 15 127.98 12.51 11.84 -5.36 20 165.50 16.18 15.46 -4.45 25 201.10 19.66 18.94 -3.66 30 238.24 23.29 22.28 -4.34 Total amount 1022.76 / /

[0093] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that: it is still possible to modify the specific implementation manners of the present invention or perform equivalent replacements on some technical features; without departing from the spirit of the technical solutions of the present invention, they should all be covered within the scope of the technical solutions claimed by the present invention.

Claims

1. A modeling method for predicting the retention coefficient of particulate matter in cigarette filters, characterized in that: The following steps are involved: Solanesol was used as a marker of smoke particulate matter to obtain the filter tip of the benchmark cigarette m at different puff flow rates. v The retention coefficient k for particulate matter is as follows; For the retention coefficient k and the suction flow rate v, k=α+β v +γ v -2 / 3 The least squares fitting equation was used to obtain the retention coefficient and suction flow rate of smoke particles in the filter of the benchmark cigarette m. v The relationship between: k m =α m +β m v+γ m v -2 / 3 ; According to the interception coefficient of smoke particulate matter in the filter of the reference cigarette m, the pressure drop per unit length of the filter, and the pressure drop per unit length of the filter of the cigarette to be predicted x, the interception coefficient prediction model of the filter of the cigarette to be predicted x is obtained: in, v is the suction flow rate, ΔP x is the filter pressure drop per unit length of the cigarette x to be predicted, ΔP m is the filter pressure drop per unit length of the reference cigarette m.

2. The modeling method of a prediction model of the retention coefficient of smoke particles in a cigarette filter according to claim 1, characterized in that: The filter pressure drop per unit length of the reference cigarette m is ΔP m and the filter pressure drop per unit length of the cigarette x to be predicted ΔP x Corrected to the same flow rate, the modified filter interception coefficient prediction model of the cigarette x to be predicted is obtained: Wherein C m and C x are the circumferences of the reference cigarette m and the cigarette to be predicted x respectively.

3. The modeling method of a prediction model of the retention coefficient of smoke particulate matter in a cigarette filter according to claim 2, characterized in that: Obtain the filter tip of the benchmark cigarette m at different puff flow rates v The retention coefficient k for particulate matter includes: The filter of the reference cigarette m is smoked according to the set suction capacity, and after the smoking is completed, the filter of the reference cigarette is cut into equal lengths; the solanesol in each filter section and the Cambridge filter is quantitatively analyzed respectively, and the solanesol penetration rate of each filter section is calculated according to the quantitative data of solanesol in different filter sections and Cambridge filter discs, and the penetration rate and the filter length are fitted by natural logarithm to obtain the retention coefficient of the cigarette filter particulate matter at the set suction capacity, and the suction capacity is converted into the suction flow rate to obtain the retention coefficient of the cigarette filter particulate matter at the set suction flow rate; The set suction capacity is changed, and the above steps are repeated to obtain the retention coefficient k of the reference cigarette filter for particulate matter at different suction flow rates.

4. A modeling method for predicting the retention coefficient of particulate matter in a cigarette filter according to claim 3, characterized in that: HPLC‒DAD method was used to quantitatively analyze solanesol in each filter segment and Cambridge filter disc: First, the solanesol in each filter section or Cambridge filter disc is extracted, and the extract is filtered and sent to the HPLC-DAD instrument for analysis to obtain the chromatographic peaks of solanesol in different filter sections and Cambridge filter discs. The solanesol in different filter sections and Cambridge filter discs is quantified using the external standard method.

5. A modeling method for predicting the retention coefficient of particulate matter in a cigarette filter according to claim 4, characterized in that: The chromatographic conditions of the HPLC‒DAD instrument are as follows: chromatographic column: Waters XBridge C18, specifications 4.6×75mm×3.5μm; Mobile phase: methanol, flow rate: 1 mL / min, isocratic elution; column oven temperature: 30°C; injection volume: 10 μL; detection wavelength: 210 nm; running time: 9 min; The extraction solvent is methanol.

6. A modeling method for predicting the retention coefficient of particulate matter in a cigarette filter according to claim 5, characterized in that: When the filter tip of the reference cigarette m is smoked according to the set smoking capacity, the number of puffs is set to 5 to 10, the puff interval is 10 to 20 s, and 1 to 6 reference cigarette filters are smoked.

7. A method for predicting the retention rate of smoke particles in a cigarette filter, characterized in that: The following steps are involved: Using the modeling method of the smoke particulate matter interception coefficient prediction model according to any one of claims 1 to 6, a interception coefficient prediction model of the filter of the cigarette x to be predicted is obtained; Obtain the suction flow rate of the filter tip of the cigarette x to be predicted, and obtain the retention coefficient k of the filter tip of the cigarette x to be predicted x ; The particle retention rate E of the filter of the cigarette x to be predicted is calculated by the following formula: in, l is the length of the filter of the cigarette x to be predicted.

8. A device for predicting the interception rate of particulate matter in smoke in a cigarette filter, characterized in that: include: Memory for storing computer programs; The processor is used to implement the steps of the method for predicting the retention rate of smoke particulate matter in a cigarette filter as claimed in claim 7 when executing the computer program.

9. A computer readable medium, characterized in that: The computer readable medium stores a computer program, and when the computer program is processed and executed, the steps of the method for predicting the retention rate of smoke particulate matter in a cigarette filter according to claim 7 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method for predicting the retention rate of smoke particulate matter in a cigarette filter as claimed in claim 7 are implemented.

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