Material competitive adsorption performance evaluation method based on improved AHP-CRITIC comprehensive weight

Abstract

The invention discloses an improved AHP-CRITIC comprehensive weight-based material competitive adsorption performance evaluation method. The method comprises the following steps: performing hierarchical analysis on material competitive adsorption performance data by adopting a target-criterion-sub-criterion-index hierarchical framework to construct an evaluation index system; through an improved AHP-CRITIC combination method, calculating the comprehensive weight of each index in the overall evaluation model; collecting and calculating index data, and obtaining a comprehensive evaluation value through the evaluation model. The evaluation method can be used for scientifically and objectively evaluating the competitive adsorption performance of the material to the multi-element gas, the evaluation result accords with reality, the credibility is high, and the method has relatively high popularization and application values.

Description

Technical Field

[0001] The invention relates to the technical field of competitive adsorption performance of materials, and relates to but is not limited to a competitive adsorption performance evaluation method of materials based on improved AHP-CRITIC comprehensive weight. Background Art

[0002] With the continuous progress of materials science and industrial technology in my country, various new materials have been widely used in many fields, among which the competitive adsorption performance of materials has become one of the important indicators to measure the application value of materials. The competitive adsorption performance of materials refers to the adsorption capacity of materials for each gas component in a multi-component gas environment, which directly affects the application effect of materials in gas separation, storage, catalysis and other fields. Therefore, the scientific evaluation of the competitive adsorption performance of materials has important practical significance.

[0003] Existing experimental test methods are usually not comprehensive, and the test results are greatly affected by experimental conditions and environmental factors. Although theoretical calculation methods can provide certain predictions and references, since the adsorption process of materials involves many complex factors, it is difficult to fully and accurately reflect the actual adsorption performance of materials by relying on a single calculation method. In existing studies, the analytic hierarchy process (AHP), as a multi-criteria decision-making method, can effectively deal with multi-level and multi-factor evaluation problems in complex systems and is widely used in material performance evaluation. However, the traditional AHP method mainly relies on the subjective judgment of experts when calculating weights, which is easily affected by human factors, resulting in insufficient objectivity and accuracy of the evaluation results. In contrast, the CRITIC method can more objectively reflect the importance of each indicator by considering the contrast intensity and conflict of indicator data, but the use of the CRITIC method alone may ignore the influence of the hierarchical structure. In addition, existing methods often only focus on one aspect of the adsorption performance of the material, such as static adsorption performance or dynamic adsorption performance, and ignore the comprehensive evaluation of the two. Therefore, there is an urgent need for a method that integrates multiple factors and scientifically and objectively evaluates the competitive adsorption performance of materials.

[0004] In summary, the existing technology has the above-mentioned shortcomings when evaluating the competitive adsorption performance of materials. A method is needed that can comprehensively consider multiple factors and scientifically, objectively and comprehensively evaluate the competitive adsorption performance of materials to overcome the shortcomings of the existing technology. Summary of the invention

[0005] In view of the problems existing in the above-mentioned prior art, an embodiment of the present invention provides a material competitive adsorption performance evaluation method based on an improved AHP-CRITIC comprehensive weight, which can establish a comprehensive and hierarchical competitive adsorption performance evaluation system, and further conduct a scientific and objective evaluation of the competitive adsorption performance of materials based on multiple factors.

[0006] The technical solution of the embodiment of the present invention is achieved as follows:

[0007] An embodiment of the present invention provides a material competitive adsorption performance evaluation method based on improved AHP-CRITIC comprehensive weight, the method comprising:

[0008] According to the characteristics of the material's competitive adsorption of multiple gases, two factors, static competitive adsorption performance and dynamic competitive adsorption performance, are selected as performance influencing factors for the competitive adsorption of multiple gases and an evaluation index system is constructed; wherein, the evaluation index system includes a target layer A, a criterion layer B, a sub-criterion layer C and an indicator layer D; the improved AHP method and CRITIC method are used to determine the weight of each indicator from both subjective and objective perspectives and calculate the comprehensive weight of each indicator; the comprehensive weight of each indicator is used to obtain the evaluation score of each level, and the target layer is gradually introduced from the lowest level to the upper level, and finally the competitive adsorption performance evaluation result is given.

[0009] In some possible embodiments, the target layer is the competitive adsorption performance evaluation A1, and the criterion layer B includes two evaluation indicators, namely, static competitive adsorption performance B1 and dynamic competitive adsorption performance B2;

[0010] The sub-criteria layer C includes 10 evaluation indicators, namely, adsorption equilibrium C1, adsorption isotherm C2, adsorption selectivity C3, adsorption capacity C4 and adsorption energy C5, belonging to the static competitive adsorption performance B1; adsorption rate C6, adsorption kinetic model C7, adsorption efficiency C8, adsorption stability C9 and adsorption cycle regeneration capacity C10, belonging to the dynamic competitive adsorption performance B2;

[0011] The index layer D includes the adsorption amount D1, adsorbate mass D2, gas concentration D3, equilibrium time D4 and adsorbent mass D5 in the adsorption equilibrium C1; the Langmuir constant D6, Freundlich constant D7, Dubinin-Radushkevich constant D8, Temkin constant D9 and Redlich-Peterson constant D10 in the adsorption isotherm C2; the selectivity coefficient D11, separation factor D12, selective adsorption amount D13, competitive adsorption amount D14 and adsorption priority D15 in the adsorption selectivity C3; the maximum adsorption capacity D16, specific surface area D17, pore size distribution D18, pore size D19 and surface functional group D20 in the adsorption capacity C4; the adsorption heat D21, Gibbs free energy D22, adsorption entropy D23, adsorption energy distribution D24 and adsorption site energy D25 in the adsorption energy C5; the adsorption rate constant D26, intraparticle diffusion coefficient D27, apparent rate D28 in the adsorption rate C6 Constant D28, micropore diffusion coefficient D29 and rate-limiting step D30; Pseudo-first-order model parameters D31, Pseudo-second-order model parameters D32, Elovich model parameters D33, Weber-Morris model parameters D34 and Bangham model parameters D35 in the adsorption kinetic model C7; adsorption removal rate D36, adsorbent utilization D37, competitive adsorption rate D38, maximum removal rate D39 and equilibrium removal rate D40 in the adsorption efficiency C8; adsorption capacity after multiple cycles D41, dissolution loss during adsorption D42, adsorption efficiency after regeneration D43, adsorption energy after regeneration D44 and adsorption rate after regeneration D45 in the adsorption stability C9; competitive adsorption capacity recovery rate after regeneration D46, number of regeneration cycles D47, anti-interference stability D48, regeneration method D49 and regeneration conditions D50 in the adsorption cycle regeneration capacity C10, a total of 50 evaluation indicators.

[0012] In some possible embodiments, the improved AHP method and CRITIC method are used to determine the weight of each indicator from two subjective and objective perspectives respectively and calculate the comprehensive weight of each indicator, including: obtaining the subjective weight of each indicator of competitive adsorption performance based on the improved AHP method; wherein the improved AHP method constructs a comparison matrix through an improved scaling method, and then obtains the weight vector through different mathematical methods; obtaining the objective weight of each indicator of competitive adsorption performance based on the CRITIC method; performing a correlation analysis on the subjective weight and the customer weight, and judging whether the P value obtained by the significance test of the subjective weight and the objective weight is greater than a specific threshold; when it is judged that the P value is greater than the specific threshold, calculating the comprehensive weight of each indicator based on the subjective weight and the objective weight.

[0013] In some possible embodiments, the subjective weights of each index of competitive adsorption performance obtained based on the improved AHP method include: comparing each evaluation index of the same level in pairs by 1-9 scaling method and exponential scaling method, respectively constructing comparison matrices A and B and normalizing them by columns to obtain corresponding standard matrices; performing arithmetic averaging on each row of the normalized standard matrix to obtain the weight vector α of the comparison matrix A. i and the weight vector β of the comparison matrix B i ; Perform geometric mean on each row of the normalized standard matrix to obtain the weight vector of the comparison matrix A and the weight vector γ of the comparison matrix B i ; In each row, the maximum eigenvalue and the corresponding eigenvector of the standard matrix are obtained and normalized to obtain the weight vector λ of the comparison matrix A a-max and the weight vector λ of the comparison matrix B b-max ; Based on the maximum eigenvalue and the corresponding eigenvector, the weight rationality is checked for consistency; after passing the consistency check, the weight vector α of the comparison matrix A is compared i , weight vector Weight vector λ a-max Perform arithmetic averaging and compare the weight vector β of matrix B i , weight vector β i , weight vector λ b-max Perform weighted fusion to obtain the improved AHP comprehensive weight ν i .

[0014] In some possible embodiments, the objective weight of each index of competitive adsorption performance obtained based on the CRITIC method includes: standardizing the index data in the evaluation index system; calculating the standard deviation and correlation coefficient of each index; and determining the information content and objective weight of each index based on the calculated standard deviation and correlation coefficient.

[0015] In some possible embodiments, the comprehensive weights of the indicators are used to obtain evaluation scores for each level, and the target layer is gradually derived from the lowest layer to the upper layer, and finally the competitive adsorption performance evaluation result is given, including: multiplying the composite weight set of the indicator layer D relative to the sub-criteria layer C with the score matrix of each indicator of the indicator layer D to determine the comprehensive evaluation score of each indicator of the competitive adsorption performance sub-criteria layer C; multiplying the composite weight set of the sub-criteria layer C relative to the criterion layer B with the score matrix of each indicator of the sub-criteria layer C to determine the comprehensive evaluation score of each indicator of the competitive adsorption performance criterion layer B; multiplying the composite weight set of the criterion layer B relative to the target layer A with the score matrix of each indicator of the criterion layer B to determine the comprehensive evaluation score of the competitive adsorption performance indicators.

[0016] Compared with the prior art, the present invention combines the two factors of static competitive adsorption performance and dynamic competitive adsorption performance with the establishment of a four-level evaluation system, which has the following beneficial effects:

[0017] 1. A competitive adsorption performance evaluation system is established from two aspects: static competitive adsorption performance and dynamic competitive adsorption performance. It is divided into four levels: target layer A, criterion layer B, sub-criterion layer C and scheme layer D, with a total of 50 evaluation factors. The widely dispersed influencing factors are combined into a whole for analysis and evaluation, and the connection and hierarchy between the factors are reflected.

[0018] 2. The improved AHP-CRITIC combination method comprehensively calculates the weights of each indicator, reduces the impact of subjective judgment on the results, and improves the objectivity and rationality of weight calculation. The improved AHP method is used to construct a hierarchical structure and perform preliminary weight allocation, and then the preliminary weight is corrected in combination with the CRITIC method to finally obtain a comprehensive weight. Give full play to the advantages of both and improve the scientificity and credibility of the evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work, among which:

[0020] Figure 1 A schematic diagram of a process for evaluating the competitive adsorption performance of materials based on improved AHP-CRITIC comprehensive weights provided in an embodiment of the present invention;

[0021] Figure 2 A schematic diagram of static competitive adsorption performance in a competitive adsorption performance evaluation system established in an embodiment of the present invention;

[0022] Figure 3 A schematic diagram of dynamic competitive adsorption performance in a competitive adsorption performance evaluation system established in an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. The following embodiments are used to illustrate the present invention, but are not used to limit the scope of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0024] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0025] It should be pointed out that the terms "first\second\third" involved in the embodiments of the present invention are only used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of the present invention described here can be implemented in an order other than that illustrated or described here.

[0026] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art in the field to which the embodiments of the present invention belong. It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with those in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless specifically defined as here.

[0027] The existing methods for evaluating the competitive adsorption performance of materials have the following disadvantages: (1) The experimental test methods are not comprehensive enough: The experimental test methods can usually only cover part of the adsorption performance of the materials and it is difficult to provide a comprehensive evaluation. In addition, the test results are easily affected by experimental conditions and environmental factors, resulting in poor stability and repeatability of the results, making it difficult to fully and accurately reflect the actual adsorption performance of the materials.

[0028] (2) Limitations of theoretical calculation methods: Although theoretical calculation methods can predict the adsorption performance of materials to a certain extent, since the adsorption process involves many complex factors, a single calculation method is difficult to fully consider all influencing factors. This method often relies on idealized models and assumptions, resulting in deviations between the calculation results and the actual situation, and cannot fully and accurately reflect the actual adsorption performance of the material.

[0029] (3) Subjectivity of the traditional AHP method: AHP (analytic hierarchy process) is a commonly used multi-criteria decision-making method, but it mainly relies on the subjective judgment of experts when calculating weights, which is easily affected by personal experience and bias. This subjectivity may lead to unreasonable weight distribution and affect the objectivity and accuracy of the evaluation results.

[0030] (4) Limitations of using the CRITIC method alone: ​​The CRITIC (Criteria Importance Through Intercriteria Correlation) method can more objectively determine the importance of each indicator by considering the comparative strength and conflict of indicator data, but it ignores the hierarchical structure between indicators. Using the CRITIC method alone may not fully reflect the comprehensive impact of multiple levels and factors in a complex system, resulting in an incomplete evaluation result.

[0031] (5) Lack of comprehensive evaluation methods: Existing evaluation methods are usually single, whether experimental testing, theoretical calculation or multi-criteria decision-making method, each has its own limitations, and it is difficult to comprehensively evaluate various factors. This leads to the evaluation results of the competitive adsorption performance of materials may be one-sided and cannot fully reflect the actual performance and application potential of the materials.

[0032] (6) Insufficient evaluation of dynamic and static adsorption performance: Existing methods often only focus on one aspect of the adsorption performance of the material, such as static adsorption performance or dynamic adsorption performance, and ignore the comprehensive evaluation of the two. As a result, the evaluation results cannot fully reflect the performance of the material in practical applications.

[0033] The embodiment of the present invention provides a material competitive adsorption performance evaluation method based on improved AHP-CRITIC comprehensive weight, which is applied to electronic devices. The electronic devices include but are not limited to mobile phones, laptops, tablet computers and handheld Internet devices, multimedia devices, streaming media devices, mobile Internet devices, wearable devices or other types of electronic devices. The functions implemented by the method can be implemented by calling program codes by a processor in the electronic device. Of course, the program codes can be stored in a computer storage medium. It can be seen that the electronic device at least includes a processor and a storage medium. The processor can be used to process the material competitive adsorption performance evaluation process based on the improved AHP-CRITIC comprehensive weight, and the memory can be used to store the data required and the data generated in the material competitive adsorption performance evaluation process based on the improved AHP-CRITIC comprehensive weight.

[0034] Figure 1 A schematic diagram of a material competitive adsorption performance evaluation method based on improved AHP-CRITIC comprehensive weight provided in an embodiment of the present invention is shown in FIG. Figure 1 As shown, the method comprises at least the following steps:

[0035] Step S1, according to the characteristics of the material for competitive adsorption of multiple gases, two factors, static competitive adsorption performance and dynamic competitive adsorption performance, are selected as performance influencing factors for competitive adsorption of multiple gases and an evaluation index system is constructed.

[0036] Here, the evaluation index system includes target layer A, criterion layer B, sub-criterion layer C and index layer D; target layer A is the evaluation of competitive adsorption performance, criterion layer B includes static competitive adsorption performance B1 and dynamic competitive adsorption performance B2, sub-criterion layer C includes adsorption equilibrium, adsorption isotherm, adsorption selectivity, adsorption capacity, adsorption energy, etc.; solution layer D is the specific evaluation index, such as adsorption amount, Langmuir constant, selectivity coefficient, etc. The widely dispersed influencing factors are combined into a whole for analysis and evaluation, while reflecting the connection and hierarchy between the factors.

[0037] C is the sub-criteria layer, which is both the influencing layer of the criterion layer B and the dominant layer of the solution layer D. Among them: the static competitive adsorption performance B1 is responsible for describing the adsorption equilibrium state, adsorption selectivity and adsorption capacity. The dynamic competitive adsorption performance B2 is responsible for describing the adsorption rate, kinetic behavior and adsorption efficiency.

[0038] Step S2, using the improved AHP method and CRITIC method to determine the weight of each indicator from the subjective and objective perspectives respectively and calculate the comprehensive weight of each indicator.

[0039] Here, the improved AHP method is used to determine the subjective weight of each indicator, and the CRITIC method is used to determine the objective weight of each indicator. The subjective and objective weights are combined to calculate the comprehensive weight through a formula. In this way, the weight of each indicator is calculated comprehensively, which reduces the impact of human subjective judgment on the results and improves the objectivity and rationality of weight calculation.

[0040] In the implementation, the improved AHP method is first used to construct the hierarchical structure and perform preliminary weight allocation, and then the preliminary weight is modified by combining the CRITIC method to finally obtain the comprehensive weight, giving full play to the advantages of both methods and improving the scientificity and credibility of the evaluation results.

[0041] Step S3, using the comprehensive weights of the indicators to obtain evaluation scores for each level, and gradually deriving the target level A from the lowest level to the upper levels, and finally giving the competitive adsorption performance evaluation result.

[0042] Here, the comprehensive evaluation score is calculated layer by layer, and a comprehensive evaluation is finally given from the solution layer to the target layer. Specifically, the weight of the indicator layer relative to the sub-criteria layer is multiplied by the score matrix to obtain the comprehensive evaluation score of each indicator in the sub-criteria layer. The weight of the sub-criteria layer relative to the criterion layer is multiplied by the score matrix to obtain the comprehensive evaluation score of each indicator in the criterion layer. The weight of the criterion layer relative to the target layer is multiplied by the score matrix to obtain the final comprehensive evaluation score of the competitive adsorption performance index (API).

[0043] In the embodiment of the present invention, a hierarchical analysis of the competitive adsorption performance data of materials is performed using the "goal-criteria-sub-criteria-indicator" hierarchical framework to construct a multi-level evaluation index system. The comprehensive weights of each indicator in the overall evaluation model are calculated through the improved AHP-CRITIC combination method; the index data is collected and calculated, and the comprehensive evaluation value is obtained through the evaluation model. In this way, by combining weights from different angles, a comprehensive material competitive adsorption performance evaluation method is provided, which can more accurately evaluate the multi-gas competitive adsorption performance of the material.

[0044] In some possible embodiments, the target layer is the competitive adsorption performance evaluation A1, and the criterion layer B includes two evaluation indicators, namely, static competitive adsorption performance B1 and dynamic competitive adsorption performance B2;

[0045] The sub-criteria layer C includes 10 evaluation indicators, namely, adsorption equilibrium C1, adsorption isotherm C2, adsorption selectivity C3, adsorption capacity C4 and adsorption energy C5, belonging to the static competitive adsorption performance B1; adsorption rate C6, adsorption kinetic model C7, adsorption efficiency C8, adsorption stability C9 and adsorption cycle regeneration capacity C10, belonging to the dynamic competitive adsorption performance B2;

[0046] The index layer D includes the adsorption amount D1, adsorbate mass D2, gas concentration D3, equilibrium time D4 and adsorbent mass D5 in the adsorption equilibrium C1; the Langmuir constant D6, Freundlich constant D7, Dubinin-Radushkevich constant D8, Temkin constant D9 and Redlich-Peterson constant D10 in the adsorption isotherm C2; the selectivity coefficient D11, separation factor D12, selective adsorption amount D13, competitive adsorption amount D14 and adsorption priority D15 in the adsorption selectivity C3; the maximum adsorption capacity D16, specific surface area D17, pore size distribution D18, pore size D19 and surface functional group D20 in the adsorption capacity C4; the adsorption heat D21, Gibbs free energy D22, adsorption entropy D23, adsorption energy distribution D24 and adsorption site energy D25 in the adsorption energy C5; the adsorption rate constant D26, intraparticle diffusion coefficient D27, apparent rate D28 in the adsorption rate C6 Constant D28, micropore diffusion coefficient D29 and rate-limiting step D30; Pseudo-first-order model parameters D31, Pseudo-second-order model parameters D32, Elovich model parameters D33, Weber-Morris model parameters D34 and Bangham model parameters D35 in the adsorption kinetic model C7; adsorption removal rate D36, adsorbent utilization D37, competitive adsorption rate D38, maximum removal rate D39 and equilibrium removal rate D40 in the adsorption efficiency C8; adsorption capacity after multiple cycles D41, dissolution loss during adsorption D42, adsorption efficiency after regeneration D43, adsorption energy after regeneration D44 and adsorption rate after regeneration D45 in the adsorption stability C9; competitive adsorption capacity recovery rate after regeneration D46, number of regeneration cycles D47, anti-interference stability D48, regeneration method D49 and regeneration conditions D50 in the adsorption cycle regeneration capacity C10, a total of 50 evaluation indicators.

[0047] Here, the static competitive adsorption performance B1 plays the role of describing the adsorption equilibrium state, adsorption selectivity and adsorption capacity. Figure 2 As shown, the static competitive adsorption performance B1 is mainly composed of the following factors:

[0048] The adsorption equilibrium amount C1 includes the adsorption amount D1, the mass of the adsorbate D2, the gas concentration D3, the equilibrium time D4 and the mass of the adsorbent D5 at the solution layer D. A good adsorption equilibrium amount can effectively describe the adsorption capacity of the adsorbent for the target substance in the equilibrium state.

[0049] Adsorption isotherm C2, which in turn includes Langmuir constant D6, Freundlich constant D7, Dubinin-Radushkevich constant D8, Temkin constant D9 and Redlich-Peterson constant D10 at solution level D. The adsorption isotherm model is used to describe the adsorption behavior and characteristics of the adsorbent at different concentrations.

[0050] Adsorption selectivity C3 mainly includes selectivity coefficient D11, separation factor D12, selective adsorption capacity D13, competitive adsorption capacity D14 and adsorption priority D15 at solution level D. Good adsorption selectivity can significantly improve the separation efficiency of target substances and other substances.

[0051] The adsorption capacity C4 includes the maximum adsorption capacity D16, specific surface area D17, pore size distribution D18, pore size D19 and surface functional group D20 at solution layer D. The adsorption capacity reflects the total adsorption capacity of the adsorbent and is an important indicator for evaluating the performance of the adsorbent.

[0052] Adsorption energy C5, which includes adsorption heat D21, Gibbs free energy D22, adsorption entropy D23, adsorption energy distribution D24 and adsorption site energy D25 at solution level D. Adsorption energy reflects the thermodynamic characteristics of the adsorption process and is of great significance for understanding the adsorption mechanism.

[0053] Dynamic competitive adsorption performance B2 is responsible for describing the adsorption rate, kinetic behavior and adsorption efficiency. Figure 2 As shown, the dynamic competitive adsorption performance B2 is mainly composed of the following factors:

[0054] The adsorption rate C6 includes the adsorption rate constant D26, the intraparticle diffusion coefficient D27, the apparent rate constant D28, the micropore diffusion coefficient D29 and the rate limiting step D30 at the solution layer D. The adsorption rate reflects the speed of the adsorption process and is an important indicator of dynamic adsorption performance.

[0055] The adsorption kinetic model C7 includes the Pseudo-first-order model parameter D31, the Pseudo-second-order model parameter D32, the Elovich model parameter D33, the Weber-Morris model parameter D34 and the Bangham model parameter D35 at the scheme level D. The kinetic model is used to describe the time dependence and law of the adsorption process.

[0056] Adsorption efficiency C8, which includes adsorption removal rate D36, adsorbent utilization rate D37, competitive adsorption rate D38, maximum removal rate D39 and equilibrium removal rate D40 at solution level D. Adsorption efficiency reflects the removal effect of the adsorbent on the target substance and is an important indicator for evaluating adsorption performance.

[0057] Adsorption stability C9, which includes the adsorption capacity D41 after multiple cycles at solution level D, dissolution loss D42 during adsorption, adsorption efficiency D43 after regeneration, adsorption energy D44 after regeneration, and adsorption rate D45 after regeneration. Adsorption stability reflects the performance retention of the adsorbent during repeated use.

[0058] Adsorption cycle regeneration capacity C10, which includes the competitive adsorption capacity recovery rate D46 after regeneration, the number of regeneration cycles D47, the anti-interference stability D48, the regeneration method D49 and the regeneration conditions D50 at the solution layer D. The adsorption cycle regeneration capacity reflects the performance recovery of the adsorbent after multiple regenerations.

[0059] In some possible embodiments, the above step S2 "using the improved AHP method and CRITIC method to determine the weight of each indicator from the subjective and objective perspectives and calculate the comprehensive weight of each indicator" is further implemented by the following steps:

[0060] S21, the subjective weights of each index of competitive adsorption performance were obtained based on the improved AHP method.

[0061] Here, the comparison matrix is ​​constructed by an improved scaling method, and then the weight vector is obtained by different mathematical methods (such as arithmetic mean, geometric mean, eigenvalue method).

[0062] Improved scaling method is a commonly used method in multi-criteria decision analysis, which evaluates the relative importance of different schemes or evaluation indicators by constructing a comparison matrix.

[0063] S22, based on the CRITIC method, the objective weights of each index of competitive adsorption performance were obtained.

[0064] Here, the indicator data are first standardized, then the standard deviation and correlation coefficient are calculated, and finally the information content and objective weight are calculated based on these.

[0065] S23, performing a correlation analysis on the subjective weight and the customer weight, and determining whether a P value obtained by performing a significance test on the subjective weight and the objective weight is greater than 0.05.

[0066] Here, in statistical analysis, correlation analysis is used to evaluate whether there is a certain relationship between two sets of data, as well as the strength and direction of this relationship. For the correlation analysis of subjective weights and objective weights, the following steps can usually be used:

[0067] Data preparation: First, make sure you have two sets of weight data, subjective weights and objective weights.

[0068] Data standardization: If the dimensions or numerical ranges of two sets of data are very different, they may need to be standardized first to ensure the fairness of the analysis.

[0069] Calculate the correlation coefficient: Use statistical software or calculation tools to calculate the correlation coefficient between two sets of weighted data. The most commonly used correlation coefficient is the Pearson correlation coefficient, which measures the linear correlation between two variables.

[0070] Conduct hypothesis testing: After obtaining the correlation coefficient, conduct a hypothesis test to determine whether the correlation between the two sets of data is significant. Hypothesis testing usually involves the following steps: Establish the null hypothesis (H_0): The two sets of data are not related, that is, the correlation coefficient is equal to 0. Establish the alternative hypothesis (H_1): The two sets of data are related. Calculate the test statistic, such as the t statistic. Determine a specific threshold to represent the significance level (such as 0.05), and find the corresponding critical value or use the P value method.

[0071] Conclusion: If the calculated P value is greater than the significance level (for example, 0.05), the null hypothesis cannot be rejected, and it is considered that the correlation between the two sets of data is not significant. If the P value is less than the significance level, the null hypothesis is rejected, and it is considered that there is a significant correlation between the two sets of data.

[0072] For example, under a specific threshold of 0.05, if the P value of the subjective weight and the objective weight is greater than 0.05, it is considered that there is no significant correlation between them. This means that the two weights may come from different factors, or at least the relationship between them is not linear or not statistically significant. If the P value is less than 0.05, it is considered that there is a significant correlation between the subjective weight and the objective weight.

[0073] S24, when it is determined that the P value is greater than 0.05, calculating the comprehensive weight of each indicator based on the subjective weight and the objective weight.

[0074] Here, the comprehensive weight of each indicator is calculated by the following formula (1):

[0075]

[0076] Where: P AHP-CRITIC The comprehensive weight of indicators obtained by improving the AHP-CRITIC method; W i-AHP is the i-th weight index obtained by improving the AHP method; W i-CRITICThe i-th weight index obtained by improving the CRITIC method.

[0077] In some possible embodiments, the above step S21 "obtaining the subjective weights of various competitive adsorption performance indicators based on the improved AHP method" is further implemented by the following process:

[0078] S211, compare the evaluation indicators of the same level in pairs through the 1-9 scaling method and the e-index scaling method, construct comparison matrices A and B respectively, and normalize them by column to obtain the corresponding standard matrix.

[0079] Here, the 1-9 scale is a standard method for comparing two evaluation indicators. In the 1-9 scale, the number 1 means that the two comparison items are equally important, while 9 means that one comparison item is much more important than the other. The numbers 2 to 8 represent different degrees of relative importance. 0 / 4 ~e 8 / 4 It is introduced in the improved scaling method to express the intensity of comparison in more detail. Here, e usually represents the base of the natural logarithm, which is approximately equal to 2.71828. The specific scaling results are shown in Table 1:

[0080] Table 1 Scaling results of the improved scaling method

[0081]

[0082]

[0083] From equally important to absolutely important, each adjacent level can be quantified by 2, 4, 6, 8 or 1.284, 2.117, 3.490, 5.755, and a comprehensive evaluation matrix of evaluation indicators is established. It is defined by the 1-9 and e0 / 4-e8 / 4 scaling methods. After pairwise comparison, the comparison judgment matrix is ​​obtained: A = (a ij ) n×n , B=(b ij ) n×n .

[0084] in In the formula, a ii =1, b ii =1; thus the relative importance of factors at each level can be obtained.

[0085] S212, perform arithmetic mean on each row of the normalized standard matrix to obtain the weight vector α of the comparison matrix A i and the weight vector β of the comparison matrix B i .

[0086] Here, the specific calculation formula is:

[0087]

[0088] S213, perform geometric mean on each row of the normalized standard matrix to obtain the weight vector of the comparison matrix A and the weight vector γ of the comparison matrix B i .

[0089] Here, the specific calculation formula is:

[0090]

[0091]

[0092] S214, in each row, the maximum eigenvalue and the corresponding eigenvector of the standard matrix are obtained, and normalized to obtain the weight vector λ of the comparison matrix A a-max and the weight vector λ of the comparison matrix B b-max .

[0093] Here, the specific calculation formula for the maximum eigenvalue is:

[0094]

[0095] In the formula, ω ai The weight vector obtained after the judgment matrix A is normalized; ω bi The weight vector obtained after the judgment matrix B is normalized.

[0096] S215: Perform consistency check on the rationality of the weights based on the maximum eigenvalue and the corresponding eigenvector.

[0097] Here, the consistency index CI calculation formula is:

[0098]

[0099] Next, calculate the random consistency ratio CR:

[0100]

[0101] In the formula, λ max is the maximum characteristic root of the matrix; n is the order of the judgment matrix; RI is the average random consistency index of the judgment matrix.

[0102] S216, after passing the consistency check, compare the weight vector α of the matrix A i , weight vector Weight vector λ a-max Perform arithmetic averaging and compare the weight vector β of matrix B i , weight vector β i , weight vector λ b-maxPerform weighted fusion to obtain the improved AHP comprehensive weight ν i .

[0103] Here, the specific calculation formula is:

[0104]

[0105] In the above embodiment, the improved AHP method introduces the e-index scaling method to increase the precision of the evaluation. The CRITIC method takes into account the conflict of indicators and determines the weights through standard deviation and correlation coefficient, which increases the objectivity of the evaluation. Finally, the comprehensive weight combines subjective and objective weights, ensures the relevance of the weights through significance tests, and improves the accuracy and reliability of the evaluation.

[0106] In some possible embodiments, the above step S22 of "obtaining objective weights of various indicators of competitive adsorption performance based on the CRITIC method" is further implemented by the following process:

[0107] S221, performing standardization processing on the indicator data in the evaluation indicator system;

[0108] Here, it is divided into positive indicators and reverse indicators. The standardized value b ij , the calculation formulas of the positive index and the reverse index are as follows:

[0109]

[0110] Where b ij is the value after data normalization; x ij is the value before data normalization; maxx j is the maximum value of the j-th index; minx j is the minimum value of the j-th indicator.

[0111] S222, calculate the standard deviation and correlation coefficient of each indicator.

[0112] Here, the calculation formulas for the standard deviation and correlation coefficient of the evaluation index are as follows:

[0113]

[0114] In the formula, σ j is the standard deviation of the j-th indicator; r ij is the correlation coefficient between the i-th indicator and the j-th indicator; is the average value of the j-th indicator.

[0115] S223, based on the calculated standard deviation and correlation coefficient, determine the information content and objective weight of each indicator.

[0116] Here, the information content and objective weight of the indicator are determined by the following formulas (15) and (16) respectively:

[0117]

[0118]

[0119] In the formula, c j is the information content of the jth indicator; W j is the objective weight of the j-th indicator.

[0120] In some possible embodiments, the above step S3 "using the comprehensive weights of the indicators to obtain evaluation scores at each level, and gradually pushing the target level from the lowest level to the upper level, and finally giving the competitive adsorption performance evaluation result" can be further implemented through the following process:

[0121] S31, multiplying the composite weight set of the indicator layer D relative to the sub-criteria layer C by the score matrix of each indicator of the indicator layer D to determine the comprehensive evaluation score of each indicator of the competitive adsorption performance sub-criteria layer C.

[0122] Here, the calculation formula for the comprehensive evaluation of the sub-criteria layer C index is as follows:

[0123]

[0124] In the formula, S i D is the comprehensive evaluation value of the sub-criteria layer indicators; i is the corresponding comprehensive weight value of the indicator layer indicator; It is the evaluation matrix corresponding to the indicators at the indicator layer.

[0125] S32, multiplying the composite weight set of the sub-criteria layer C relative to the criterion layer B by the score matrix of each indicator of the sub-criteria layer C to determine the comprehensive evaluation score of each indicator of the competitive adsorption performance criterion layer B.

[0126] Here, the calculation formula for the comprehensive evaluation of the criterion layer B indicators is as follows:

[0127]

[0128] In the formula, Z i is the comprehensive evaluation value of the criterion layer indicators; C i is the corresponding comprehensive weight value of the indicator layer indicator; It is the evaluation matrix corresponding to the indicators at the sub-criteria level.

[0129] S33, multiplying the composite weight set of the criterion layer B relative to the target layer A by the score matrix of each indicator of the criterion layer B to determine the comprehensive evaluation score of the competitive adsorption performance indicator.

[0130] Here, the calculation formula of the target layer A, i.e., the comprehensive evaluation index of competitive adsorption performance, is as follows:

[0131]

[0132] Among them, API is the comprehensive evaluation value of the target layer; B i is the corresponding comprehensive weight value of the indicator layer indicator; is the evaluation matrix corresponding to the criterion layer indicators.

[0133] The embodiment of the present invention constructs a multi-level evaluation system to evaluate the performance of materials for competitive adsorption of multiple gases. The subjective weights are determined by expert scoring and the 1-9 scale method. The objective weights are determined by combining the conflict, standard deviation and correlation coefficient of the indicators. The subjective and objective weights are combined, and the comprehensive weights of the indicators are calculated using a formula through correlation analysis and weighted fusion. The evaluation from the lowest level to the target level ensures the hierarchy and systematic nature of the evaluation. This method provides a comprehensive evaluation system by combining weights from different angles, which can more accurately evaluate the competitive adsorption performance of multiple gases of materials.

[0134] The present invention provides a material competitive adsorption performance evaluation method based on improved AHP-CRITIC comprehensive weight, which can scientifically and objectively evaluate the performance of materials for multi-gas competitive adsorption. The evaluation result is in line with reality, has high credibility, and has great promotion and application value.

[0135] It should be noted that, in the embodiment of the present invention, if the above-mentioned material competitive adsorption performance evaluation method based on the improved AHP-CRITIC comprehensive weight is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention, or the part that contributes to the relevant technology, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling an electronic device to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM), a magnetic disk or an optical disk. In this way, the embodiment of the present invention is not limited to any specific combination of hardware and software.

[0136] Correspondingly, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps in any of the above-mentioned methods for evaluating the competitive adsorption performance of materials based on the improved AHP-CRITIC comprehensive weight are implemented. Correspondingly, in an embodiment of the present invention, a computer program product is also provided, and when the computer program product is executed by a processor of an electronic device, it is used to implement the steps in any of the above-mentioned methods for evaluating the competitive adsorption performance of materials based on the improved AHP-CRITIC comprehensive weight.

[0137] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present invention. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present invention, the size of the serial number of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention. The serial numbers of the above-mentioned embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments.

[0138] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0139] In the several embodiments provided by the present invention, it should be understood that the disclosed methods can be implemented in other ways. The methods disclosed in the several method embodiments provided by the present invention can be arbitrarily combined without conflict to obtain new method embodiments. The features disclosed in the several methods provided by the present invention can be arbitrarily combined without conflict to obtain new method embodiments.

[0140] The above is only an embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A material competitive adsorption performance evaluation method based on improved AHP-CRITIC comprehensive weight, characterized in that: include: According to the characteristics of the material for competitive adsorption of multiple gases, two factors, static competitive adsorption performance and dynamic competitive adsorption performance, are selected as performance influencing factors for competitive adsorption of multiple gases and an evaluation index system is constructed; wherein the evaluation index system includes a target layer A, a criterion layer B, a sub-criterion layer C and an index layer D; The improved AHP method and CRITIC method are used to determine the weight of each indicator from the subjective and objective perspectives respectively and calculate the comprehensive weight of each indicator; The comprehensive weights of the indicators are used to obtain evaluation scores at each level, and the target layers are gradually introduced from the lowest level to the upper levels, and finally the competitive adsorption performance evaluation results are given.

2. The method according to claim 1, characterized in that The target layer is the competitive adsorption performance evaluation A1, and the criterion layer B includes two evaluation indicators, namely, static competitive adsorption performance B1 and dynamic competitive adsorption performance B2; The sub-criteria layer C includes the adsorption equilibrium C1, adsorption isotherm C2, adsorption selectivity C3, adsorption capacity C4 and adsorption energy C5 belonging to the static competitive adsorption performance B1; There are 10 evaluation indicators belonging to the dynamic competitive adsorption performance B2, including adsorption rate C6, adsorption kinetic model C7, adsorption efficiency C8, adsorption stability C9 and adsorption cycle regeneration capacity C10; The index layer D includes the adsorption amount D1, adsorbate mass D2, gas concentration D3, equilibrium time D4 and adsorbent mass D5 in the adsorption equilibrium C1; the Langmuir constant D6, Freundlich constant D7, Dubinin-Radushkevich constant D8, Temkin constant D9 and Redlich-Peterson constant D10 in the adsorption isotherm C2; the selectivity coefficient D11, separation factor D12, selective adsorption amount D13, competitive adsorption amount D14 and adsorption priority D15 in the adsorption selectivity C3; the maximum adsorption capacity D16, specific surface area D17, pore size distribution D18, pore size D19 and surface functional group D20 in the adsorption capacity C4; the adsorption heat D21, Gibbs free energy D22, adsorption entropy D23, adsorption energy distribution D24 and adsorption site energy in the adsorption energy C5. D25; adsorption rate constant D26, intraparticle diffusion coefficient D27, apparent rate constant D28, micropore diffusion coefficient D29 and rate limiting step D30 in adsorption rate C6; Pseudo-first-order model parameter D31, Pseudo-second-order model parameter D32, Elovich model parameter D33, Weber-Morris model parameter D34 and Bangham model parameter D35 in adsorption kinetic model C7; adsorption removal rate D36, adsorbent utilization rate D37, competitive adsorption rate D38, maximum removal rate D39 and equilibrium removal rate D40 in adsorption efficiency C8; adsorption capacity after multiple cycles D41, dissolution loss during adsorption D42, adsorption efficiency after regeneration D43, adsorption energy after regeneration D44 and adsorption rate after regeneration D45 in adsorption stability C9; The adsorption cycle regeneration capacity C10 includes 50 evaluation indicators, namely, the competitive adsorption capacity recovery rate after regeneration D46, the number of regeneration cycles D47, the anti-interference stability D48, the regeneration method D49 and the regeneration conditions D50.

3. The method according to claim 1, characterized in that The improved AHP method and CRITIC method are used to determine the weight of each indicator from the subjective and objective perspectives and calculate the comprehensive weight of each indicator, including: The subjective weights of various indicators of competitive adsorption performance are obtained based on the improved AHP method; wherein the improved AHP method constructs a comparison matrix through an improved scaling method, and then obtains a weight vector through different mathematical methods; Based on the CRITIC method, the objective weights of each index of competitive adsorption performance were obtained; Performing a correlation analysis on the subjective weight and the customer weight, and determining whether a P value obtained by performing a significance test on the subjective weight and the objective weight is greater than a specific threshold; When it is determined that the P value is greater than a specific threshold, the comprehensive weight of each indicator is calculated based on the subjective weight and the objective weight.

4. The method according to claim 3, characterized in that The subjective weights of various competitive adsorption performance indicators obtained based on the improved AHP method include: The evaluation indicators at the same level are compared pairwise by 1-9 scaling method and index scaling method, and the comparison matrices A and B are constructed respectively and normalized by columns to obtain the corresponding standard matrices. Perform arithmetic mean on each row of the normalized standard matrix to obtain the weight vector α of the comparison matrix A i and the weight vector β of the comparison matrix B i ; Perform geometric mean on each row of the normalized standard matrix to obtain the weight vector of the comparison matrix A. and the weight vector γ of the comparison matrix B i ; In each row, the maximum eigenvalue and the corresponding eigenvector of the standard matrix are obtained and normalized to obtain the weight vector λ of the comparison matrix A. a-max and the weight vector λ of the comparison matrix B b-max ; Based on the maximum eigenvalue and the corresponding eigenvector, a consistency check is performed on the rationality of the weights; After passing the consistency check, the weight vector α of the comparison matrix A is i , weight vector Weight vector λ a-max Perform arithmetic averaging and compare the weight vector β of matrix B i , weight vector β i , weight vector λ b-max Perform weighted fusion to obtain the improved AHP comprehensive weight ν i .

5. The method according to claim 3, characterized in that: The objective weights of various indicators of competitive adsorption performance obtained based on the CRITIC method include: Standardizing the indicator data in the evaluation indicator system; Calculate the standard deviation and correlation coefficient of each indicator; Based on the calculated standard deviation and correlation coefficient, the information content and objective weight of each indicator are determined.

6. The method according to any one of claims 1 to 5, characterized in that: The comprehensive weights of the indicators are used to obtain evaluation scores at each level, and the target level is gradually introduced from the lowest level to the upper level, and finally the competitive adsorption performance evaluation results are given, including: The composite weight set of the index layer D relative to the sub-criteria layer C is multiplied by the score matrix of each index of the index layer D to determine the comprehensive evaluation score of each index of the competitive adsorption performance sub-criteria layer C; The composite weight set of sub-criteria layer C relative to criterion layer B is multiplied by the score matrix of each indicator of sub-criteria layer C to determine the comprehensive evaluation score of each indicator of competitive adsorption performance criterion layer B; The composite weight set of criterion layer B relative to target layer A is multiplied by the score matrix of each indicator of criterion layer B to determine the comprehensive evaluation score of the competitive adsorption performance index.

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