Hardwood pyrolysis gas product analysis method and system

Abstract

The invention discloses a hardwood pyrolysis gas product analysis method and system. The method comprises the following steps: S1, carrying out a thermogravimetric-infrared spectroscopy instrument experiment on a typical hardwood material, collecting and processing data, and determining peak temperatures of three components (hemicellulose, cellulose and lignin) according to a K-K method; s2, determining a specific pyrolysis temperature range of each component by using a double-Gaussian function; s3, dividing temperature regions of the pyrolysis gas product of each component, including an overlapping region and a non-overlapping region, and performing curve area integration on each region; and S4, calculating the corresponding gas yield in each component, performing data separation, and comparing and observing the corresponding relation of hemicellulose, cellulose and lignin gas products. According to the method, the limitation of the prior art on general analysis of biomass pyrolysis is broken through, accurate tracking and quantification of release behaviors of the three main component gases are realized, and key data support is provided for optimizing a pyrolysis process.

Description

Technical Field

[0001] This invention relates to the field of woody biomass energy conversion, and in particular to a method and system for determining the correspondence between gaseous products of multiple components during pyrolysis. Background Technology

[0002] Woody biomass is a recognized important energy source. The effective utilization of renewable resources can reduce the environmental impact of fossil fuel extraction. Biomass can be converted through several thermochemical processes, including pyrolysis, gasification, and combustion. Since pyrolysis is the initial stage of thermochemical conversion, understanding the pyrolysis characteristics of biomass is crucial.

[0003] Thermogravimetric Fourier Transform Infrared (TG-FTIR) technology is also widely used in pyrolysis research because it allows for in-situ analysis of the thermal decomposition process. In biomass pyrolysis, hemicellulose decomposes first, followed by cellulose, while lignin gradually decomposes throughout the process. Existing studies have used TGA data to perform kinetic and thermodynamic analyses on wood, identifying three main pyrolysis stages. This technique allows researchers to simultaneously acquire information on sample mass changes and the release of volatile gases. However, biomass pyrolysis is a complex process involving the parallel reactions of multiple components, with significantly overlapping mass loss peaks on its thermogravimetric curves, and the released mixed gases are difficult to directly attribute to specific components. Currently, most research remains at the macroscopic analysis level of the overall pyrolysis behavior of biomass and its gaseous products. Summary of the Invention

[0004] The technical problem to be solved by this invention is how to quantify the proportion of gaseous products of each component during the pyrolysis of hardwood.

[0005] The present invention solves the above-mentioned technical problems through the following technical means: A method for analyzing gaseous products from hardwood pyrolysis includes the following steps: S1. Perform thermogravimetric-infrared spectroscopy experiments on typical hardwood materials, collect and process the data, and determine the peak temperatures of hemicellulose, cellulose and lignin according to the KK method. S2. Use the double Gaussian function to determine the specific pyrolysis temperature range of each component; S3. Divide the temperature regions of the pyrolysis gas products of each component, including overlapping and non-overlapping regions, and perform curve area integration on each region. S4. Calculate the corresponding gas yield in each component, separate the data, compare and observe the corresponding relationship between hemicellulose, cellulose and lignin gas products.

[0006] Furthermore, in step S1, thermogravimetric-infrared spectroscopy (TGA) experiments were performed on typical hardwood materials. The experimental data were converted into TG, DTG, and conversion rate data, and individual absorbance-dependent curves for each gas were obtained, i.e., gas generation curves as a function of temperature. The peak temperatures of the three components (hemicellulose, cellulose, and lignin) were determined using the KK method.

[0007] Where |DDTG| represents the second derivative of the TG curve, T is the temperature, mt represents the mass at t, and m0 is the mass at the initial temperature.

[0008] Furthermore, in step S2, a double Gaussian function is used to determine the specific pyrolysis temperature range of each component. The overlapping pyrolysis peaks are analyzed using a deconvolution method, decomposing them into three independent components corresponding to pseudohemicellulose, pseudocellulose, and pseudolignin, respectively. This method uses a double Gaussian function that can describe peak shape asymmetry for fitting. By setting the maximum value of the peak as the center position (xc) of each peak, the asymmetric geometric characteristics of each peak can be effectively characterized. The specific expression of the double Gaussian function used to describe the biomass pyrolysis process is as follows:

[0009] Where y0 represents the baseline offset, H represents the peak height of the maximum reaction rate, x represents the independent variable, xc represents the position of the maximum reaction rate on the horizontal axis, w1 represents the width of the left half of the peak, and w2 represents the width of the right half of the peak. The quality of deconvolution is evaluated using the residual sum of squares (RSS), which is defined as:

[0010] Where yiexp represents the experimental data at a given temperature or time, and yith represents the corresponding value. The reliability of deconvolution is evaluated based on the goodness of fit and the relative magnitude of RSS.

[0011] Furthermore, in step S3, the temperature regions of the pyrolysis gas products of each component are divided, including overlapping and non-overlapping regions. The area integral of each region is then performed, and the area of ​​the left and right regions within the same temperature range is calculated using the peak value as the baseline to determine the ratio of the two regions. When the area of ​​one side is known, the area of ​​the other side can be calculated based on the corresponding ratio. The non-overlapping region represents the amount of gas generated by a single component, while the amount of gas generated in the overlapping region is composed of multiple components.

[0012] The present invention also provides a system for analyzing gaseous products from hardwood pyrolysis, comprising the following steps: Peak temperature calculation module: Thermogravimetric-infrared spectroscopy experiments were conducted on typical hardwood materials, data were collected and processed, and the peak temperatures of hemicellulose, cellulose and lignin were determined according to the KK method; The pyrolysis temperature range calculation module uses a double Gaussian function to determine the specific pyrolysis temperature range of each component. Temperature region calculation module: Divides the temperature regions of the pyrolysis gas products of each component, including overlapping and non-overlapping regions, and performs curve area integration on each region; Correspondence calculation module: Calculates the corresponding gas yield in each component, performs data separation, and compares and observes the correspondence between hemicellulose, cellulose and lignin gas products.

[0013] Furthermore, the peak temperature calculation module performs thermogravimetric-infrared spectroscopy experiments on typical hardwood materials, converting the experimental data into TG, DTG, and conversion rate data, and obtaining individual absorbance-dependent curves for each gas, i.e., gas generation curves as a function of temperature. The peak temperatures of the three components (hemicellulose, cellulose, and lignin) are determined using the KK method.

[0014] Where |DDTG| represents the second derivative of the TG curve, T is the temperature, mt represents the mass at t, and m0 is the mass at the initial temperature.

[0015] Furthermore, the pyrolysis temperature range calculation module utilizes a double Gaussian function to determine the specific pyrolysis temperature range of each component. A deconvolution method is employed to analyze overlapping pyrolysis peaks, decomposing them into three independent components corresponding to pseudohemicellulose, pseudocellulose, and pseudolignin, respectively. This method uses a double Gaussian function capable of describing peak asymmetry for fitting. By setting the maximum peak value as the center position (xc) of each peak, the asymmetric geometric characteristics of each peak can be effectively characterized. The specific expression of the double Gaussian function used to describe the biomass pyrolysis process is as follows:

[0016] Where y0 represents the baseline offset, H represents the peak height of the maximum reaction rate, x represents the independent variable, xc represents the position of the maximum reaction rate on the horizontal axis, w1 represents the width of the left half of the peak, and w2 represents the width of the right half of the peak. The quality of deconvolution is evaluated using the residual sum of squares (RSS), which is defined as:

[0017] Where yiexp represents the experimental data at a given temperature or time, and yith represents the corresponding value. The reliability of deconvolution is evaluated based on the goodness of fit and the relative magnitude of RSS.

[0018] Furthermore, the temperature region calculation module divides the temperature regions of the pyrolysis gas products of each component, including overlapping and non-overlapping regions, and performs curve area integration on each region. Using the peak value as the baseline, the areas of the left and right regions within the same temperature range are calculated to determine the ratio of the two regions. When the area of ​​one side is known, the area of ​​the other side can be deduced based on the corresponding ratio. The non-overlapping region represents the amount of gas generated by a single component, while the amount of gas generated in the overlapping region is composed of multiple components.

[0019] The advantages of this invention are: This invention overcomes the limitations of existing research, which provides a general analysis of the overall pyrolysis behavior of biomass and lacks the ability to trace gas sources at the component level. It offers a systematic and quantitative analytical method. This method can clearly distinguish and quantify the gas release amounts of the three main components during complex pyrolysis processes, providing crucial data support and theoretical basis for precisely controlling pyrolysis products and optimizing biomass energy conversion processes. Attached Figure Description

[0020] Figure 1 This is a flowchart of the analysis and calculation method for hardwood pyrolysis gas products based on double Gaussian functions described in this invention; Figure 2 The peak temperatures of the three components were determined by the TG, DTG, and DDTG curves obtained in the embodiments of this invention, taking white oak, a typical hardwood material, as an example, under nitrogen atmosphere with a heating rate of 20 K / min. Figure 3 The composition and proportion of multi-component pyrolysis gas obtained by thermogravimetric-infrared spectroscopy during pyrolysis in a nitrogen environment at a heating rate of 20 K / min, as described in the embodiments of the present invention. Figure 4 This is the method for calculating the lignocellulose ratio based on a double Gaussian function obtained in the embodiments of the present invention; Figure 5 The deconvolution results obtained using the double Gaussian function in the embodiments of the present invention include a comparison graph of experimental and simulated values, as well as independent curves of hemicellulose, cellulose and lignin separated. Figure 6 This refers to the proportions of the three components of white oak in CH4 emissions, calculated based on a double Gaussian function, obtained in an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] An embodiment of the present invention provides a method for analyzing gaseous products from the pyrolysis of hardwood, the method flow of which is as follows: Figure 1 As shown, by Figure 1 As can be seen, the method for calculating the pyrolysis kinetic parameters of carbonized combustibles based on a single-peak pyrolysis curve of the present invention includes the following steps: S1. Perform thermogravimetric-infrared spectroscopy experiments on typical hardwood materials, collect and process the data, and determine the peak temperatures of the three components (hemicellulose, cellulose and lignin) according to the KK method.

[0023] In this embodiment, step S1 specifically involves: performing thermogravimetric-infrared spectroscopy (TGA) experiments on typical hardwood materials, converting the experimental data into TG, DTG, conversion rate, and other data, and obtaining individual absorbance-dependent curves for each gas, i.e., gas generation curves as a function of temperature. The pyrolysis process can be divided into three stages, corresponding to the decomposition of cellulose, lignin, and hemicellulose over time. The lowest point of DDTG and the three peak positions of the DTG curve correspond to the peak temperatures of the three components. The KK method is used to determine the peak temperatures of the three components (hemicellulose, cellulose, and lignin). Where |DDTG| represents the second derivative of the TG curve, T is the temperature, mt represents the mass at t, and m0 is the mass at the initial temperature. Using the KK method, the peak temperatures of hemicellulose, cellulose, and lignin during the high-temperature decomposition of white oak are 585 K, 660 K, and 700 K, respectively. Figure 2 As shown. Simultaneously processing the infrared data yields absorbance curves (positively correlated with gas generation) of the multi-component pyrolysis gas components, resulting in... Figure 3 .

[0024] S2. Use the double Gaussian function to determine the specific pyrolysis temperature range of each component.

[0025] In this embodiment, step S2 specifically involves quantifying the contributions of hemicellulose, cellulose, and lignin to individual gaseous products by combining the deconvolution results with the gas yield. Since the curves obtained from the double Gaussian fitting are asymmetrical, the areas of the left and right regions within the same temperature range are evaluated separately, using the peak value as the dividing point. Figure 4 illustrates the calculation method for the lignocellulose ratio. With x = 319 as the baseline, the integral from 319 to 364 is 16.89, while the integral from 273 to 319 is 16.68. Therefore, the right region is 1.12 times larger than the left region, indicating that the contribution of the right half is 1.12 times that of the left half. This proportional relationship can be used to estimate the contributions of hemicellulose, cellulose, and lignin in gaseous products. When the area of ​​one side is known, the area of ​​the other side can be calculated based on the corresponding proportion.

[0026] The specific pyrolysis temperature range of each component is determined using a double Gaussian function. The overlapping pyrolysis peaks are analyzed using a deconvolution method, decomposing them into three independent components corresponding to hemicellulose, cellulose, and lignin, respectively. This method uses a double Gaussian function to fit the peak shape asymmetry. By setting the maximum value of each peak as its center position (xc), the asymmetric geometric characteristics of each peak can be effectively characterized. The specific expression of the double Gaussian function used to describe the biomass pyrolysis process is as follows: , where y0 represents the baseline offset, H represents the peak height of the maximum reaction rate, x represents the independent variable, xc represents the position of the maximum reaction rate on the horizontal axis, w1 represents the width of the left half of the peak, and w2 represents the width of the right half of the peak.

[0027] The quality of deconvolution is evaluated using the residual sum of squares (RSS), which is defined as: Where yiexp represents the experimental data at a given temperature or time, and yith represents the corresponding value. The reliability of deconvolution is evaluated based on the goodness of fit and the relative magnitude of RSS. Figure 5 As shown, the deconvolution curves of the three components exhibit high R² values, which are in good agreement with the experimental data.

[0028] S3. Divide the temperature regions of the pyrolysis gas products of each component, including overlapping and non-overlapping regions, and perform curve area integration on each region. In this embodiment, step S3 specifically involves: through the preceding analysis, the gaseous products of the entire pyrolysis process can be determined, including the gaseous products generated at the peak temperature. However, during the pyrolysis process, the proportions of the three components (hemicellulose, cellulose, and lignin) in a particular gaseous product remain unclear. Figure 6The diagram shows large overlapping regions resulting from the decomposition of hemicellulose, cellulose, and lignin. Therefore, by combining the deconvolution results with the amount of gas produced, the proportions of hemicellulose, cellulose, and lignin in specific gaseous products can be determined. Based on the preceding analysis, the gaseous products throughout the pyrolysis process, including those produced at the peak temperature, can be identified.

[0029] Since the curves obtained by double Gaussian fitting do not exhibit a normal distribution, the peak value is used as the baseline to calculate the areas of the left and right regions within the same temperature range, respectively, to determine the ratio between the two regions. Once the area of ​​one region is known, the area of ​​the other can be calculated based on the corresponding ratio. The non-overlapping regions represent the amount of gas generated by a single component, while the overlapping regions represent the amount of gas generated by multiple components.

[0030] S4. Calculate the corresponding gas yield in each component, separate the data, compare and observe the corresponding relationship between hemicellulose, cellulose and lignin gas products.

[0031] In this embodiment, step S3 specifically includes: Figure 6 The CH4 emissions during the pyrolysis of white oak at a heating rate of 20 K / min are shown. The purple region between 700 K and 900 K represents pure lignin. This study indicates that lignin decomposes throughout the pyrolysis process, a result consistent with our previous findings. The gas production rate within each temperature range was determined by the area under the integral curve. A double Gaussian function effectively separated overlapping peaks. Given that the curve obtained from the double Gaussian fitting is not normally distributed, the areas of the left and right regions within the same temperature range were calculated separately, using the peak as a baseline, to determine the ratio of the two regions. The overlapping ranges of hemicellulose and lignin between 600 K and 700 K are designated Part-H and Part-L, respectively. The remaining portion of the overlapping region, attributable to cellulose decomposition, is labeled Part-C. Figure 5 The results show that lignin decomposes between 400 and 900 K, with a peak temperature of 700 K. The integral value in the 700-900 K range is 1.73 times that in the 400-600 K range and 1.46 times that in the 600-700 K range. Based on the observed integral multiples across different temperature ranges, the area corresponding to lignin pyrolysis can also be determined. This method can also be used to determine the area of ​​hemicellulose and cellulose regions. During methane formation, lignin produces the highest amount of methane, followed by cellulose, while hemicellulose produces the lowest amount.

[0032] Repeating the above steps yields the proportions of these three components in different types of generated gases. From this, we can conclude that during the pyrolysis of white oak, hemicellulose produces the least amount of CH4, cellulose produces the most CH3OH and the least H2O, while lignin produces the most H2O and CH4.

[0033] The pyrolysis process can be divided into three stages, corresponding to the decomposition of cellulose, lignin, and hemicellulose over time. Due to the different molecular structures of the three components, their decomposition temperatures also differ. For example, hemicellulose is composed of short-chain heteropolysaccharides and easily hydrolyzed low-polymerization-degree heteropolysaccharides. These components readily separate from the bulk at low temperatures and decompose into volatile substances. Figure 5 These are independent pyrolysis curves of the three components, which provide the specific pyrolysis temperature of each component (i.e., each component reacts only within this temperature range), and are presented in [the format shown]. Figure 4 Taking the CH4 curve as an example, it is divided according to the pyrolysis temperature to obtain... Figure 6 . Figure 6 The unlined portion to the left of the hemicellulose region indicates that only hemicellulose is decomposed at this stage, so the CH4 produced in this stage is entirely from hemicellulose. The lined portion, however, represents the simultaneous pyrolysis of hemicellulose, cellulose, and lignin, resulting in a mixed CH4 composition, not solely from a single component. Therefore, the CH4 produced by hemicellulose between 600 and 700 K (Part-H) can be obtained by calculating the area between 470 and 570 K and applying the corresponding proportional relationships. This method is simple, computationally efficient, and has significant potential for wider application.

[0034] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for analyzing gaseous products from the pyrolysis of hardwood, characterized in that, Includes the following steps: S1. Perform thermogravimetric-infrared spectroscopy experiments on typical hardwood materials, collect and process the data, and determine the peak temperatures of hemicellulose, cellulose and lignin according to the KK method. S2. Use the double Gaussian function to determine the specific pyrolysis temperature range of each component; S3. Divide the temperature regions of the pyrolysis gas products of each component, including overlapping and non-overlapping regions, and perform curve area integration on each region. S4. Calculate the corresponding gas yield in each component, separate the data, compare and observe the corresponding relationship between hemicellulose, cellulose and lignin gas products.

2. The method for analyzing gaseous products from hardwood pyrolysis according to claim 1, characterized in that, In step S1, thermogravimetric-infrared spectroscopy (TGA) experiments were performed on typical hardwood materials. The experimental data were converted into TG, DTG, and conversion rate data, and individual absorbance-dependent curves for each gas were obtained, i.e., gas generation curves as a function of temperature. The peak temperatures of the three components (hemicellulose, cellulose, and lignin) were determined using the KK method. Where |DDTG| represents the second derivative of the TG curve, T is the temperature, mt represents the mass at t, and m0 is the mass at the initial temperature.

3. The method for analyzing gaseous products from hardwood pyrolysis according to claim 1, characterized in that, In step S2, a double Gaussian function is used to determine the specific pyrolysis temperature range of each component. The overlapping pyrolysis peaks are analyzed using a deconvolution method, decomposing them into three independent components corresponding to pseudohemicellulose, pseudocellulose, and pseudolignin, respectively. This method uses a double Gaussian function that can describe peak shape asymmetry for fitting. By setting the maximum value of the peak as the center position (xc) of each peak, the asymmetric geometric characteristics of each peak can be effectively characterized. The specific expression of the double Gaussian function used to describe the biomass pyrolysis process is as follows: Where y0 represents the baseline offset, H represents the peak height of the maximum reaction rate, x represents the independent variable, xc represents the position of the maximum reaction rate on the horizontal axis, w1 represents the width of the left half of the peak, and w2 represents the width of the right half of the peak. The quality of deconvolution is evaluated using the residual sum of squares (RSS), which is defined as: Where yiexp represents the experimental data at a given temperature or time, and yith represents the corresponding value. The reliability of deconvolution is evaluated based on the goodness of fit and the relative magnitude of RSS.

4. The method for analyzing gaseous products of hardwood pyrolysis according to any one of claims 1 to 3, characterized in that, In step S3, the temperature regions of the pyrolysis gas products of each component are divided, including overlapping and non-overlapping regions. The area integral of each region is performed, and the area of ​​the left and right regions within the same temperature range is calculated with the peak value as the baseline to determine the ratio of the two regions. When the area of ​​one side is known, the area of ​​the other side can be calculated according to the corresponding ratio. The non-overlapping region is the amount of gas generated by a single component, while the amount of gas generated in the overlapping region is composed of multiple components.

5. A hardwood pyrolysis gas product analysis system, characterized in that, Includes the following steps: Peak temperature calculation module: Thermogravimetric-infrared spectroscopy experiments were conducted on typical hardwood materials, data were collected and processed, and the peak temperatures of hemicellulose, cellulose and lignin were determined according to the KK method; The pyrolysis temperature range calculation module uses a double Gaussian function to determine the specific pyrolysis temperature range of each component. Temperature region calculation module: Divides the temperature regions of the pyrolysis gas products of each component, including overlapping and non-overlapping regions, and performs curve area integration on each region; Correspondence calculation module: Calculates the corresponding gas yield in each component, performs data separation, and compares and observes the correspondence between hemicellulose, cellulose and lignin gas products.

6. The hardwood pyrolysis gas product analysis system according to claim 5, characterized in that, The peak temperature calculation module performs thermogravimetric-infrared spectroscopy (TGA) experiments on typical hardwood materials, converting the experimental data into TG, DTG, and conversion rate data, and obtaining individual absorbance-dependent curves for each gas, i.e., gas generation curves as a function of temperature. The peak temperatures of the three components (hemicellulose, cellulose, and lignin) are determined using the KK method. Where |DDTG| represents the second derivative of the TG curve, T is the temperature, mt represents the mass at t, and m0 is the mass at the initial temperature.

7. The hardwood pyrolysis gas product analysis system according to claim 5, characterized in that, The pyrolysis temperature range calculation module utilizes a double Gaussian function to determine the specific pyrolysis temperature range of each component. A deconvolution method is employed to analyze overlapping pyrolysis peaks, decomposing them into three independent components corresponding to pseudohemicellulose, pseudocellulose, and pseudolignin, respectively. This method uses a double Gaussian function capable of describing peak shape asymmetry for fitting. By setting the maximum peak value as the center position (xc) of each peak, the asymmetric geometric characteristics of each peak can be effectively characterized. The specific expression of the double Gaussian function used to describe the biomass pyrolysis process is as follows: Where y0 represents the baseline offset, H represents the peak height of the maximum reaction rate, x represents the independent variable, xc represents the position of the maximum reaction rate on the horizontal axis, w1 represents the width of the left half of the peak, and w2 represents the width of the right half of the peak. The quality of deconvolution is evaluated using the residual sum of squares (RSS), which is defined as: Where yiexp represents the experimental data at a given temperature or time, and yith represents the corresponding value. The reliability of deconvolution is evaluated based on the goodness of fit and the relative magnitude of RSS.

8. The hardwood pyrolysis gas product analysis system according to any one of claims 5 to 7, characterized in that, In the temperature region calculation module, the temperature regions of the pyrolysis gas products of each component are divided, including overlapping and non-overlapping regions. The area integral of each region is then performed, and the area of ​​the left and right regions within the same temperature range is calculated with the peak value as the baseline to determine the ratio of the two regions. When the area of ​​one side is known, the area of ​​the other side can be calculated according to the corresponding ratio. The non-overlapping region represents the amount of gas generated by a single component, while the amount of gas generated in the overlapping region is composed of multiple components.

9. A processing device, characterized in that, It includes at least one processor and at least one memory communicatively connected to the processor, wherein: the memory stores program instructions executable by the processor, and the processor can execute the method as described in any one of claims 1 to 4 by invoking the program instructions.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause the computer to perform the method as described in any one of claims 1 to 4.

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