A method for characterizing wood cell wall stiffness based on low-field nuclear magnetic resonance

Abstract

The present invention discloses a method for characterizing wood cell wall stiffness based on low-field nuclear magnetic resonance. When the wood sample is dried, the wood sample is taken out at regular intervals for weighing and low-field nuclear magnetic resonance scanning. The complete relaxation signal intensity of the wood sample is collected by using an MSE-CPMG pulse sequence, thereby obtaining the moisture content and free induction decay curve of the wood sample. The transverse relaxation time T of the wood sample is calculated by a data inversion algorithm combining Gaussian fitting and exponential fitting. 21 , transverse relaxation time integral peak area A1. The characterization method of the present invention is non-destructive, continuous and has high measurement accuracy.

Description

Technical Field

[0001] The invention relates to the field of wood cell wall stiffness characterization, and in particular to a wood cell wall stiffness characterization method based on low-field nuclear magnetic resonance. Background Art

[0002] Water-soluble resins are low molecular weight resins containing a large number of hydrophilic groups. They have the characteristics of low viscosity, good fluidity, small molecular weight range, and excellent water mixing ratio. They are suitable for impregnation and enhancement modification of wood and bamboo. The water-soluble low molecular weight resin is impregnated into the cell cavity and cell wall of biomass fiber materials such as wood and bamboo using the vacuum-pressure method. In the subsequent drying stage, the liquid resin that has entered the micro-nano pores of the cell cavity wall continues to change phase, gradually solidifies to form a solid macromolecular structure that fills the cell cavity, and may undergo chemical cross-linking reactions with cell wall components, thereby enhancing the mechanical properties of the cell wall. Therefore, by characterizing the drying process and the real-time response of the stiffness of the cell wall of the modified material after drying, the enhancement and modification mechanism of the resin-impregnated material can be better interpreted.

[0003] The characterization methods of the stiffness of resin-impregnated modified materials include macroscopic mechanical properties characterization and microscopic mechanical properties characterization. Among them, the universal mechanical testing machine is often used to measure the macroscopic mechanical properties of resin-impregnated modified materials. By applying a constant deformation or load to the test sample, the corresponding load or deformation is measured, and then the elastic modulus (MOE) and flexural strength (MOR) of the sample are calculated by the formula. However, the testing process of this method causes irreversible damage to the sample, and it is impossible to characterize the stiffness change of the sample during the entire drying process through one sample. If multiple samples are tested continuously, there may be test errors caused by the natural variability of wood. The characterization method of the microscopic mechanical properties of modified materials mainly uses nanoindentation technology, which applies a continuous load to the cell wall of the sample and tests the indentation depth at the nanoscale, and then obtains the stiffness value of the cell wall of the sample by fitting. This method can accurately measure the stiffness of the cell wall and has been used to characterize the mechanical properties of the cell wall of wood, bamboo, and modified materials, but its sample preparation and testing requirements are high, and it is also a destructive test that can only measure the mechanical properties of the cell wall at a certain moisture content state.

[0004] Therefore, it is of great significance to provide a continuous and non-destructive testing method for the cell wall stiffness of modified materials, which can provide data support for the research on water-soluble low molecular weight resin impregnation modification and subsequent drying and curing of biomass materials such as wood and bamboo. Summary of the invention

[0005] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a non-destructive, continuous and high-precision method for characterizing wood cell wall stiffness based on low-field nuclear magnetic resonance.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0007] A method for characterizing wood cell wall stiffness based on low-field nuclear magnetic resonance comprises the following steps:

[0008] S1, drying the wood sample, taking it out at regular intervals to weigh and perform low-field nuclear magnetic resonance scanning on the wood sample, wherein the MSE-CPMG pulse sequence is used to collect the complete relaxation signal intensity of the wood sample during the low-field nuclear magnetic resonance scanning;

[0009] S2. Calculate the moisture content of the wood sample according to the weighed mass, and establish the free induction decay curve of the wood sample according to the intensity of the complete relaxation signal;

[0010] S3. According to the moisture content and free induction decay curve of the wood sample, the transverse relaxation time T of the wood sample is calculated by combining Gaussian fitting and exponential fitting. 21 , transverse relaxation time integrated peak area A1.

[0011] As a further improvement to the above technical solution:

[0012] The step S3 specifically comprises the following steps:

[0013] S301, determining whether the moisture content of the wood sample is greater than a preset threshold value, when the moisture content of the wood sample is lower than the preset threshold value, executing step S302, otherwise, executing step S303;

[0014] S302, according to the free induction decay curve of the wood sample, the data inversion algorithm uses the fitting function shown in formula (1) to calculate the transverse relaxation time T of the wood sample 21 , transverse relaxation time integrated peak area A1;

[0015]

[0016] S303, according to the free induction decay curve of the wood, the data inversion algorithm uses the fitting function shown in formula (2) to calculate the transverse relaxation time T of the wood 21 , transverse relaxation time integrated peak area A1;

[0017]

[0018] In the formula (1) and formula (2), T 21 , T 22 , T 23 is the transverse relaxation time of components with different degrees of freedom, A1, A2, A3 are the integrated peak areas of the transverse relaxation time spectra of components with different degrees of freedom, t is the decay time, n1=2, n2=n3=1, and C is a constant.

[0019] In the present invention, the preset threshold is 30%.

[0020] The parameters of the MSE-CPMG pulse sequence are: the number of echoes is 2000-12000; the number of scans is 8-64; and the echo time is 0.1-0.25 ms.

[0021] The wood sample is a wood sample that has been subjected to resin modification treatment or has not been subjected to resin modification treatment.

[0022] The wood sample is a wood sample that has been subjected to end-sealing treatment.

[0023] The resin modification treatment specifically includes the following steps: immersing a wood sample with a moisture content of 0% in a resin solution with a mass concentration of 10% to 50% to obtain a resin-impregnated and modified wood sample with a moisture content exceeding 30%.

[0024] The impregnation is vacuum pressure impregnation, which specifically includes the following steps: placing a wood sample with a moisture content of 0% in a resin solution with a mass concentration of 10% to 50% and maintaining it at a pressure of 0.06 to 0.08 MPa for 30 to 50 minutes, then maintaining it at a pressure of 0.5 to 0.8 MPa for 5 to 10 hours, releasing the pressure and taking out the wood sample to obtain a resin-impregnated modified wood sample with a moisture content exceeding 30%.

[0025] As a general inventive concept, the present invention also provides a wood cell wall stiffness characterization device based on low-field nuclear magnetic resonance, comprising:

[0026] The first weighing and scanning module is used to dry the wood sample, take it out at regular intervals to weigh it and perform low-field nuclear magnetic resonance scanning on it, wherein the MSE-CPMG pulse sequence is used to collect the complete relaxation signal intensity of the wood sample during the low-field nuclear magnetic resonance scanning;

[0027] The second data processing module is used to calculate the moisture content of the wood sample according to the weighed mass, and to establish a free induction decay curve of the wood sample according to the intensity of the complete relaxation signal;

[0028] The third data processing module is used to calculate the transverse relaxation time T of the wood sample according to the moisture content and free induction decay curve of the wood sample through a data inversion algorithm combining Gaussian fitting and exponential fitting. 21 , transverse relaxation time integrated peak area A1.

[0029] As a general inventive concept, the present invention also provides a wood cell wall stiffness characterization device based on low-field nuclear magnetic resonance, comprising an interconnected microprocessor and a memory, wherein the microprocessor is programmed or configured to execute the steps of the aforementioned wood cell wall stiffness characterization method based on low-field nuclear magnetic resonance.

[0030] As a general inventive concept, the present invention also provides a computer-readable storage medium storing a computer program programmed or configured to execute the aforementioned method for characterizing wood cell wall stiffness based on low-field nuclear magnetic resonance.

[0031] The principle of the present invention is:

[0032] The applicant discovered in long-term experiments that wood and bamboo, as a natural biomass material, has natural variability, and there are significant differences in the stiffness of the cell walls of samples taken from different parts. At present, the methods for characterizing the stiffness of the cell walls of modified and unmodified wood and bamboo materials at the macro or micro level are almost all destructive methods. The test process causes structural damage to the test sample itself, and it is impossible to characterize the stiffness of a sample at different moisture content stages. The moisture content is a crucial influencing factor of the stiffness of the wood cell wall. Therefore, the applicant measured the hydrogen proton content (H proton) in the water molecules through a specific sequence (MSE-CPMG pulse sequence) to obtain the transverse relaxation time T of the sample. 21 (used to characterize the stiffness of wood cell walls) and the transverse relaxation time integral peak area A1 (used to characterize the content of wood cell wall stiffness components). There is no sample destruction in the testing process, and the real-time response of the cell wall stiffness can be obtained through the changes in relaxation signals of the same sample at different moisture content stages, so the test results are more accurate.

[0033] Compared with the prior art, the advantages of the present invention are:

[0034] 1. The method for characterizing wood cell wall stiffness based on low-field nuclear magnetic resonance of the present invention adopts MSE-CPMG pulse sequence to collect the complete relaxation signal intensity of wood sample during low-field nuclear magnetic resonance scanning. Compared with commonly used pulse sequences such as CPMG (Carr-Purcell-Meiboom-Gill) and SE-SPI (Spin Echo Single Point Imaging), the significant advantage of the MSE-CPMG pulse sequence used in the present invention is that the sequence breaks through the limitation of the dead time of low-field nuclear magnetic resonance equipment, that is, it can not only capture the signals of wood cell wall, ordinary bound water and all free water with a decay time longer than the dead time of the instrument, but also capture the nuclear magnetic signals of cell wall and the most tightly bound water of wood with a decay time shorter than the dead time of the instrument (for example, 0.042ms for a certain device), while other sequences can only capture the signals of part of wood cell wall material, part of ordinary bound water and all free water. Therefore, the MSE-CPMG pulse sequence is more accurate in capturing the relaxation information of wood cell wall and solid materials such as resin with a certain degree of curing, and has a higher signal-to-noise ratio.

[0035] 2. The wood cell wall stiffness characterization method based on low-field nuclear magnetic resonance in the present invention uses a data inversion algorithm combining Gaussian fitting and exponential fitting to calculate the transverse relaxation time T of the wood sample. 21 , transverse relaxation time integrated peak area A1. Compared with traditional data inversion algorithms such as CONTIN and SIRT (simultaneous iterative reconstruction technique), the data inversion algorithm combined with Gaussian fitting and exponential fitting adopted in the present invention selects different fitting functions according to the components and content changes of solid and liquid in the sample, so as to more accurately invert the relaxation information change from solid to liquid (extremely short transverse relaxation time to long transverse relaxation time). BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a flow chart of the present invention.

[0037] Figure 2 Schematic diagram of the changes in MOE and MOR of the unmodified material sample during the drying process in Example 1 of the present invention.

[0038] Figure 3 is the A1 and T of the unmodified material sample in the drying process of Example 1 of the present invention. 21 Schematic diagram of changes.

[0039] Figure 4 It is a schematic diagram of the changes in MOE and MOR of the modified material sample during the drying process in Example 2 of the present invention.

[0040] Figure 5 is the A1 and T of the modified material sample in the drying process in Example 2 of the present invention. 21 Schematic diagram of changes.

[0041] Figure 6 is the T of the sample drying process before and after modification in Example 3 of the present invention 21 Schematic diagram of changes.

[0042] Figure 7 Schematic diagram of the change of A1 during the drying process of the sample before and after modification in Example 3 of the present invention. DETAILED DESCRIPTION

[0043] The present invention will be described in further detail below. Unless otherwise specified, the instruments or materials used in the present invention are commercially available.

[0044] like Figure 1 As shown, a method for characterizing wood cell wall stiffness based on low-field nuclear magnetic resonance of the present invention comprises the following steps:

[0045] S1, drying the wood sample, taking it out at regular intervals to weigh and perform low-field nuclear magnetic resonance scanning on the wood sample, wherein the MSE-CPMG pulse sequence is used to collect the complete relaxation signal intensity of the wood sample during the low-field nuclear magnetic resonance scanning;

[0046] S2. Calculate the moisture content of the wood sample according to the weighed mass, and establish the free induction decay curve of the wood sample according to the intensity of the complete relaxation signal;

[0047] S3. According to the moisture content and free induction decay curve of the wood sample, the transverse relaxation time T of the wood sample is calculated by combining Gaussian fitting and exponential fitting. 21 , transverse relaxation time integrated peak area A1.

[0048] The step S3 specifically comprises the following steps:

[0049] S301, determining whether the moisture content of the wood sample is greater than a preset threshold (the preset threshold of the present invention is the fiber saturation point, and the moisture content is 30%). When the moisture content of the wood sample is lower than the preset threshold, executing step S302, otherwise, executing step S303;

[0050] S302, according to the free induction decay curve of the wood sample, the data inversion algorithm uses the fitting function shown in formula (1) to calculate the transverse relaxation time T of the wood sample 21 , transverse relaxation time integrated peak area A1;

[0051]

[0052] S303, according to the free induction decay curve of the wood, the data inversion algorithm uses the fitting function shown in formula (2) to calculate the transverse relaxation time T of the wood 21 , transverse relaxation time integrated peak area A1;

[0053]

[0054] In the formula (1) and formula (2), T 21 , T 22 , T 23 is the transverse relaxation time of components with different degrees of freedom, A1, A2, A3 are the integrated peak areas of transverse relaxation time spectra of components with different degrees of freedom, t is the decay time, n1=2, n2=n3=1, C is a constant. Components with different degrees of freedom include but are not limited to wood cell walls, free water in cell cavities of different tissues, bound water in cell walls, and solidified resins (or gradually solidified resins (from liquid to solid)).

[0055] The data inversion algorithm adopts a method that combines Gaussian fitting (n1=2) and exponential fitting (n2=n3=1). Gaussian fitting is used to interpret the fast decay interval of the FID decay (free induction decay) curve and the signals belonging to short relaxation substances (such as cell wall signals and tightly bound water signals). Exponential fitting is used to interpret the slow decay interval of the FID decay curve and the signals belonging to long relaxation substances (such as free water signals). By combining the two fitting formulas, the FID decay curve can be interpreted more accurately and more precise data can be obtained.

[0056] Example 1: Cell wall characterization method of unmodified material sample, macroscopic mechanical properties and microscopic mechanical properties of unmodified material sample Comparison of academic performance

[0057] In the present embodiment, a method for characterizing wood cell wall stiffness based on low-field nuclear magnetic resonance is used. The wood resin is not modified. The wood is taken out at regular intervals during drying to perform low-field nuclear magnetic resonance scanning test and macroscopic mechanical property test. The low-field nuclear magnetic resonance scanning test results are calculated and fitted. Specifically, the following steps are included:

[0058] (1) Sample preparation: Twenty samples of 20 mm (R) × 20 mm (T) × 300 mm (L) and one sample of 7 mm (R) × 7 mm (T) × 20 mm (L) were sawn from fresh sawn timber of Populus tomentosa. The initial moisture content was about 100%.

[0059] (2) Drying treatment: Use epoxy resin to seal the end faces of the two-size samples, and record the mass of each sample after sealing. Place the above samples in an oven at 80°C, take them out at regular intervals and record their mass, and then perform macroscopic mechanical property tests and low-field nuclear magnetic resonance scanning.

[0060] (3) Macro-mechanical properties test: During the drying process, a sample of 20 mm (R) × 20 mm (T) × 300 mm (L) was taken out regularly, its mass was weighed and the real-time moisture content was calculated, and then the MOR and MOE changes of the unmodified material were tested according to the national standards "GB / T 1936.1-2009 Test method for wood bending strength" and "GB / T 1936.2-2009 Test method for wood bending elastic modulus". In this embodiment, the macro-mechanical properties test is mainly to verify the feasibility of the characterization method of the present invention. In the actual characterization method, this step is not a necessary step.

[0061] (4) Low-field NMR test: During the drying process, take out the unmodified material sample of 7mm (R) × 7mm (T) × 20mm (L) regularly, weigh the mass and calculate the real-time moisture content, and then perform low-field NMR scanning. After scanning, put the sample back into the oven to continue drying, and repeat this process. The sequence used is the MSE-CPMG pulse sequence, and the pulse sequence parameters are: number of echoes 2000; number of scans 8; echo time 0.1ms.

[0062] In this embodiment, the moisture content is calculated using the following formula:

[0063]

[0064] Where: MC is the moisture content of the sample, M1 is the mass of the sample when it is dried, and M0 is the absolute dry mass of the sample.

[0065] (5) Data processing: The free induction decay (FID) curve of the sample is obtained using the MSE-CPMG pulse sequence, and its transverse relaxation time T is obtained through the fitting algorithm. 21 , transverse relaxation time integral peak area A1. The fitting algorithm used is a data inversion algorithm that combines Gaussian fitting and exponential fitting. The fitting functions are shown in equations (1) and (2), where equation (1) is a two-component fitting, which is suitable for a state with a low water content; equation (2) is a three-component fitting, which is suitable for a state with a high water content, depending on the water content of the sample.

[0066]

[0067]

[0068] Where, T 21 , T 22 , T 23 is the transverse relaxation time of components with different degrees of freedom, A1, A2, A3 are the integrated peak areas of transverse relaxation time spectra of components with different degrees of freedom, t is the decay time, n1=2, n2=n3=1, and C is a constant. In this embodiment, the degree of freedom component refers to the cell wall, free water in the cell cavity of different tissues, bound water in the cell wall, such as the rigid polymer component of the wood cell wall, free water in the cell cavity of wood fiber and wood ray, and water in the lumen of wood vessel cells. A1, A2, A3 correspond to the peak areas of the above relaxation times appearing on the T2 spectrum, respectively, and the unit is the intensity of the signal, such as the content of rigid polymers in the cell wall, bound water in the cell wall, free water in the cell cavity of wood fiber and wood ray, and water in the lumen of wood vessel cells.

[0069] Through the macroscopic mechanical properties test, the MOR and MOE changes of the samples at different drying stages were obtained. The transverse relaxation time T of the samples at different drying stages was obtained by formulas (1) and (2): 21 , and the transverse relaxation time integrated peak area A1, respectively. Figure 2 , 3 shown.

[0070] from Figure 2It can be seen that when the moisture content is above the fiber saturation point, the macroscopic mechanical properties MOE and MOR of the unmodified material hardly change with the decrease of moisture content. When the moisture content is below the fiber saturation point, the MOE and MOR of the unmodified material gradually increase with the decrease of moisture content.

[0071] Figure 3 is the change in cell wall stiffness response of the unmodified material during the drying process, including the transverse relaxation time T 21 From the transverse relaxation time integrated peak area A1, it can be found that the macroscopic mechanical properties and microscopic mechanical properties of the unmodified material have the same trend, indicating that it is feasible to characterize the microscopic mechanical properties of the material cell wall by the characterization method of this embodiment.

[0072] Example 2: Cell wall characterization method of modified materials, comparison of macroscopic and microscopic mechanical properties of modified materials

[0073] A method for characterizing wood cell wall stiffness based on low-field nuclear magnetic resonance in this embodiment comprises the following steps: firstly modifying the wood with resin, taking it out at regular intervals during the drying process to perform low-field nuclear magnetic resonance scanning test and macroscopic mechanical property test, and performing calculation fitting on the low-field nuclear magnetic resonance scanning test results:

[0074] (1) Modifier preparation: The solid content of the water-soluble melamine formaldehyde resin (MUF) solution was measured, and its concentration was adjusted to 30% by mass using distilled water according to the modification requirements.

[0075] (2) Sample preparation: 20 samples of 20 mm (R) × 20 mm (T) × 300 mm (L) and 1 sample of 7 mm (R) × 7 mm (T) × 20 mm (L) were sawn from fully air-dried white poplar lumber, and the moisture content was dried to an absolute dry state of 0%. Vacuum-pressure impregnation treatment was performed using a 30% concentration resin solution. The vacuum-pressure impregnation process was as follows: first, the pressure was maintained at 0.08 MPa for 30 minutes, then at 0.8 MPa for 5 hours, and finally, the pressure was slowly released to remove the sample. The initial moisture content was about 90%.

[0076] (3) Drying treatment: seal the end faces of the samples with epoxy resin and record the mass of each sample after sealing. Place the above samples in an oven at 80°C, take them out at regular intervals and record their mass, and then conduct macroscopic mechanical property tests and low-field nuclear magnetic resonance scanning.

[0077] (4) Macro-mechanical properties test: During the drying process, a sample of 20 mm (R) × 20 mm (T) × 300 mm (L) was taken out regularly, its mass was weighed and the real-time moisture content was calculated, and then the MOR and MOE changes of the modified material sample were tested according to the national standards "GB / T 1936.1-2009 Test method for wood bending strength" and "GB / T 1936.2-2009 Test method for wood bending elastic modulus". In this embodiment, the macro-mechanical properties test is mainly to verify the feasibility of the characterization method of the present invention. In the actual characterization method, this step is not a necessary step.

[0078] In this embodiment, the moisture content is calculated using the following formula:

[0079]

[0080] Where: MC is the moisture content of the sample, M1 is the mass of the sample when it is dried, and M0 is the absolute dry mass of the sample.

[0081] (5) Low-field NMR test: During the drying process, the modified material sample of 7mm (R) × 7mm (T) × 20mm (L) was taken out regularly, the mass was weighed and the real-time moisture content was calculated, and then a low-field NMR scan was performed. After the scan, the sample was put back into the oven to continue drying, and this process was repeated. The sequence used was the MSE-CPMG pulse sequence, and the pulse sequence parameters were: number of echoes 2000; number of scans 8; echo time 0.1ms.

[0082] (6) Data processing: The free induction decay (FID) curve of the sample is obtained using the MSE-CPMG pulse sequence, and its transverse relaxation time T is obtained through the fitting algorithm. 21 , transverse relaxation time integral peak area A1. The fitting algorithm used is a data inversion algorithm that combines Gaussian fitting and exponential fitting. The fitting functions are shown in formulas (1) and (2), where formula (1) is a two-component fitting, which is suitable for a state with a low water content; formula (2) is a three-component fitting, which is suitable for a state with a high water content. The specific fitting algorithm depends on the water content of the sample.

[0083]

[0084]

[0085] Where, T 21 , T 22 , T 23is the transverse relaxation time of components with different degrees of freedom, A1, A2, A3 are the integrated peak areas of transverse relaxation time spectra of components with different degrees of freedom, t is the decay time, n1=2, n2=n3=1, and C is a constant. In this embodiment, the degree of freedom components refer to free water in cell walls, cell cavities of different tissues, bound water in cell walls, solidified resins (or gradually solidified resins (from liquid to solid)), such as rigid polymer components of wood cell walls, free water in wood fiber cell cavities and wood ray cell cavities, and water in wood vessel cell cavities.

[0086] Through macroscopic mechanical properties testing, the MOR and MOE changes of modified material samples at different drying stages were obtained. The transverse relaxation time T of samples at different drying stages was obtained by formulas (1) and (2): 21 , and the transverse relaxation time integrated peak area A1, respectively. Figure 4 , 5 shown.

[0087] Figure 4 The changes in the macroscopic mechanical properties of MOE and MOR of the modified material samples during the drying process. As can be seen from the figure, due to the gradual solidification of the resin in the drying process of the modified material and filling in the pore structure of each level of the wood, the changes in its macroscopic mechanical properties show a linear increase trend in the entire moisture content stage above and below the moisture content fiber saturation point.

[0088] Figure 5 The stiffness response of the cell wall of the modified material during the drying process, including the transverse relaxation time T 21 and the transverse relaxation time integral peak area A1, it can be found that the two have the same trend. However, compared with the macroscopic mechanical properties test, the microscopic mechanical properties test sample is always the same sample, so A1 and T 21 The fitting effect is better and the data is more accurate.

[0089] Example 3: Cell wall characterization method of modified materials, comparison of cell wall stiffness before and after wood modification

[0090] A method for characterizing wood cell wall stiffness based on low-field nuclear magnetic resonance in this embodiment includes performing a low-field nuclear magnetic resonance test on the wood before wood modification, performing a low-field nuclear magnetic resonance scanning test on the wood after wood modification, and performing calculation fitting on the low-field nuclear magnetic resonance scanning test results respectively, specifically comprising the following steps:

[0091] (1) Modifier preparation: The solid content of the water-soluble melamine formaldehyde resin (MUF) solution was measured, and its concentration was adjusted to 50% by mass using distilled water according to the requirements of wood impregnation modification.

[0092] (2) Sample preparation: Samples of 7 mm (R) × 7 mm (T) × 20 mm (L) were sawn from fresh wood, with an initial moisture content of approximately 90%.

[0093] (3) Drying treatment: seal the end faces with epoxy resin and record the mass of each sample after sealing. Place the above samples in a 60°C oven, take them out and weigh them at regular intervals and record the mass, and then perform low-field nuclear magnetic resonance scanning.

[0094] (4) Low-field NMR test: The sequence used for low-field NMR scanning is the MSE-CPMG pulse sequence, and the pulse sequence parameters are: number of echoes 12000; number of scans 64; echo time 0.25ms. After the test, the moisture content is dried to 0% absolute dry state for low molecular weight resin impregnation modification treatment.

[0095] (5) Modification treatment: The unmodified material was treated with a 50% mass concentration resin solution under vacuum-pressure impregnation. The vacuum-pressure impregnation process was to first maintain a pressure of 0.06 MPa for 50 min, then maintain a pressure of 0.5 MPa for 5 h, and finally slowly release the pressure to take out the sample. The initial moisture content was about 90%.

[0096] (6) Low-field NMR test of modified materials: During the drying process, the modified material samples with the size of 7 mm (R) × 7 mm (T) × 20 mm (L) were taken out regularly, the mass was weighed and the real-time moisture content was calculated, and then low-field NMR scanning was performed. The sequence used was MSE-CPMG, and the sequence parameters were: number of echoes 12000; number of scans 64; echo time 0.25 ms.

[0097] In this embodiment, the moisture content is calculated using the following formula:

[0098]

[0099] Where: MC is the moisture content of the sample, M1 is the mass of the sample when it is dried, and M0 is the absolute dry mass of the sample.

[0100] (7) Data processing: The free induction decay (FID) curve of the sample is obtained using the MSE-CPMG pulse sequence, and its transverse relaxation time T is obtained by fitting algorithm. 21 , transverse relaxation time integral peak area A1. The fitting algorithm used is a data inversion algorithm combining Gaussian fitting and exponential fitting. The fitting functions are shown in formulas (1) and (2), where formula (1) is a two-component fitting, which is suitable for a state with a low water content; formula (1) is a three-component fitting, which is suitable for a state with a high water content. The specific fitting algorithm depends on the water content of the sample.

[0101]

[0102]

[0103] Where, T 21 , T22 , T 23 is the transverse relaxation time of components with different degrees of freedom, A1, A2, A3 are the integrated peak areas of transverse relaxation time spectra of components with different degrees of freedom, t is the decay time, n1=2, n2=n3=1, and C is a constant. In this embodiment, the degree of freedom components refer to free water in cell walls, cell cavities of different tissues, bound water in cell walls, solidified resins (or gradually solidified resins (from liquid to solid)), such as rigid polymer components of wood cell walls, free water in wood fiber cell cavities and wood ray cell cavities, and water in wood vessel cell cavities.

[0104] This example characterizes the changes in cell wall stiffness of the same sample before and after resin impregnation modification, more accurately interprets the effect of resin impregnation modification, and provides a scientific reference for the optimization of wood resin impregnation parameters and process control. That is, first, the unmodified wood is taken out regularly during the drying process for low-field nuclear magnetic resonance scanning, then the low molecular weight resin is impregnated and modified, and then the modified material is taken out regularly during the drying process for low-field nuclear magnetic resonance scanning, and the T of the same sample before and after modification under the same moisture content is compared. 21 Variations with A1.

[0105] Figure 6 , 7 are the transverse relaxation time T before and after wood modification during the drying process. 21 , the change of the transverse relaxation time integral peak area A1. The higher the cell wall stiffness, the smaller the freedom of hydrogen proton movement, and the transverse relaxation time T 21 The shorter. Figure 6 , 7 It can be seen that the stiffness and stiffness component content of the wood before and after modification are significantly improved, and the modification treatment effectively enhances the mechanical strength of the wood cell wall. This shows that the characterization method of the present invention eliminates the shortcomings of the traditional method and can make an in-situ and accurate comparison of the cell wall strength of the sample before and after modification.

[0106] In addition, the present invention also provides a wood cell wall stiffness characterization device based on low-field nuclear magnetic resonance, comprising:

[0107] The first weighing and scanning module is used to dry the wood sample, take it out at regular intervals to weigh it and perform low-field nuclear magnetic resonance scanning on it, wherein the MSE-CPMG pulse sequence is used to collect the complete relaxation signal intensity of the wood sample during the low-field nuclear magnetic resonance scanning;

[0108] The second data processing module is used to calculate the moisture content of the wood sample according to the weighed mass, and to establish a free induction decay curve of the wood sample according to the intensity of the complete relaxation signal;

[0109] The third data processing module is used to calculate the transverse relaxation time T of the wood sample according to the moisture content and free induction decay curve of the wood sample through a data inversion algorithm combining Gaussian fitting and exponential fitting. 21 , transverse relaxation time integrated peak area A1.

[0110] In addition, the present invention also provides a wood cell wall stiffness characterization device based on low-field nuclear magnetic resonance, comprising an interconnected microprocessor and a memory, wherein the microprocessor is programmed or configured to execute the steps of the aforementioned wood cell wall stiffness characterization method based on low-field nuclear magnetic resonance.

[0111] In addition, the present invention also provides a computer-readable storage medium, in which a computer program programmed or configured to execute the aforementioned method for characterizing wood cell wall stiffness based on low-field nuclear magnetic resonance is stored.

[0112] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the functions in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0113] Although the present invention has been disclosed as above with preferred embodiments, it is not intended to limit the present invention. Any technician familiar with the art can make many possible changes and modifications to the technical solution of the present invention by using the technical content disclosed above without departing from the scope of the technical solution of the present invention, or modify it into an equivalent embodiment of equivalent changes. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention should fall within the scope of protection of the technical solution of the present invention.

Claims

1. A method for characterizing wood cell wall stiffness based on low-field nuclear magnetic resonance, characterized in that: The following steps are involved: S1, drying the wood sample, taking it out at regular intervals to weigh and perform low-field nuclear magnetic resonance scanning on the wood sample, wherein the MSE-CPMG pulse sequence is used to collect the complete relaxation signal intensity of the wood sample during the low-field nuclear magnetic resonance scanning; S2. Calculate the moisture content of the wood sample according to the weighed mass, and establish the free induction decay curve of the wood sample according to the intensity of the complete relaxation signal; S3. According to the moisture content and free induction decay curve of the wood sample, the transverse relaxation time T of the wood sample is calculated by combining Gaussian fitting and exponential fitting. 21 , transverse relaxation time integrated peak area A1; The step S3 specifically comprises the following steps: S301, determining whether the moisture content of the wood sample is greater than a preset threshold value, when the moisture content of the wood sample is lower than the preset threshold value, executing step S302, otherwise, executing step S303; S302, according to the free induction decay curve of the wood sample, the data inversion algorithm uses the fitting function shown in formula (1) to calculate the transverse relaxation time T of the wood sample 21 , transverse relaxation time integrated peak area A1; （1） S303, according to the free induction decay curve of wood, the data inversion algorithm uses the fitting function shown in formula (2) to calculate the transverse relaxation time T of wood 21 , transverse relaxation time integrated peak area A1; （2） In the above formula (1) and formula (2), T 21 , T 22 , T 23 is the transverse relaxation time of components with different degrees of freedom, A1, A2, A3 are the peak areas of the transverse relaxation time spectrum of components with different degrees of freedom, t is the decay time, n1=2, n2=n3=1, C is a constant; The parameters of the MSE-CPMG pulse sequence are: the number of echoes is 2000 to 12000; the number of scans is 8 to 64; and the echo time is 0.1 to 0.25 ms.

2. The method for characterizing wood cell wall stiffness according to claim 1, characterized in that: The wood sample is a wood sample that has been subjected to resin modification treatment or has not been subjected to resin modification treatment.

3. The method for characterizing wood cell wall stiffness according to claim 2, characterized in that: The wood sample is a wood sample that has been subjected to end-sealing treatment.

4. The method for characterizing wood cell wall stiffness according to claim 2, characterized in that: The resin modification treatment specifically includes the following steps: immersing a wood sample with a moisture content of 0% in a resin solution with a mass concentration of 10% to 50% to obtain a wood sample impregnated and modified with resin.

5. The method for characterizing wood cell wall stiffness according to claim 4, characterized in that: The impregnation is vacuum pressure impregnation, which specifically includes the following steps: placing a wood sample with a moisture content of 0% in a resin solution with a mass concentration of 10% to 50% and maintaining it at a pressure of 0.06 to 0.08 MPa for 30 to 50 minutes, then maintaining it at a pressure of 0.5 to 0.8 MPa for 5 to 10 hours, releasing the pressure and taking out the wood sample to obtain a wood sample treated by resin impregnation modification.

6. A device for implementing the method for characterizing wood cell wall stiffness based on low-field nuclear magnetic resonance according to any one of claims 1 to 5, characterized in that: include: The first weighing and scanning module is used to dry the wood sample, take it out at regular intervals to weigh it and perform low-field nuclear magnetic resonance scanning on it, wherein the MSE-CPMG pulse sequence is used to collect the complete relaxation signal intensity of the wood sample during the low-field nuclear magnetic resonance scanning; The second data processing module is used to calculate the moisture content of the wood sample according to the weighed mass, and to establish a free induction decay curve of the wood sample according to the intensity of the complete relaxation signal; The third data processing module is used to calculate the transverse relaxation time T of the wood sample according to the moisture content and free induction decay curve of the wood sample through a data inversion algorithm combining Gaussian fitting and exponential fitting. 21 , transverse relaxation time integrated peak area A1.

7. A wood cell wall stiffness characterization device based on low-field nuclear magnetic resonance, comprising an interconnected microprocessor and a memory, characterized in that: The microprocessor is programmed or configured to execute the steps of the method for characterizing wood cell wall stiffness based on low-field nuclear magnetic resonance as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program programmed or configured to execute the wood cell wall stiffness characterization method based on low-field nuclear magnetic resonance as described in any one of claims 1 to 5.

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