A substrate detection and preparation method of a semi-coke-based activated carbon filter element

Abstract

The application provides a substrate detection and preparation method of semi-coke-based activated carbon filter element. The deashing detection method synchronously detects the explicit ash content and the implicit ash content of the graded powder sample, and respectively obtains the explicit ash content and the implicit ash content. The ash detection process optimization model is constructed according to the explicit ash content, the implicit ash content and the deashing process parameters, and the deashing effect judgment and the deashing process adjustment parameters are output. The double-dimensional quantitative detection of the ash content precisely improves the total ash content detection of the semi-coke powder. The detection of the explicit ash content and the implicit ash content is further distinguished, the problems that the deashing process has poor removal effect on the implicit ash content and the acid pickling parameters are frequently adjusted due to the non-standard deashing caused by the conventional detection method are avoided, and in particular, the metal ions can be more accurately removed, so that the prepared activated carbon filter element has better product quality in the fields of water purification and catalysis.

Description

Technical Field

[0001] This invention relates to a method for detecting and preparing a substrate for a semi-coke-based activated carbon filter element, belonging to the field of resource conversion technology for activated carbon filter elements based on semi-coke raw materials. Background Technology

[0002] Semi-coke, as a solid product of low-rank coal pyrolysis, has become an ideal material to replace traditional coal-based raw materials for the preparation of high-performance activated carbon due to its advantages of high fixed carbon content, low volatile matter, and low cost.

[0003] In existing semi-coke resource conversion and utilization processes, the ash contained in the semi-coke raw material mainly includes SiO2, Al2O3, CaO, etc., which need to be removed by acid washing and deashing during the semi-coke resource conversion process. When using existing processes to prepare activated carbon after acid washing and deashing of semi-coke raw material, the key parameters such as specific surface area and porosity of different batches of semi-coke raw material fluctuate significantly due to ash residue. Testing of the ash composition of semi-coke raw material has revealed that traditional acid washing and deashing is effective in removing conventional inorganic oxides. Accurate control of ash residue can be achieved by detecting the inorganic oxide composition of different batches of raw material and controlling the acid washing and deashing process accordingly. However, in addition to inorganic oxides, semi-coke also contains ash in lattice-intercalated or organically bonded forms. These ash forms are more tightly bound to the carbon matrix, and conventional acid washing processes are ineffective in removing them. The current mainstream GB / T 212-2008 calcination method measures the total ash content, but it does not include the small amount of ash in the form of lattice embedded or organic matter bound in semi-coke raw materials. These ash components will be converted into fixed impurities during the subsequent activation process, resulting in a decrease in the specific surface area of ​​activated carbon and a reduction in the amount of pores formed. In particular, some metal ion residues existing in the form of lattice embedded or organic matter bound seriously restrict the high-value conversion and utilization of activated carbon in the fields of water purification and catalysis.

[0004] Therefore, existing ash content detection methods that only target inorganic oxides are insufficient for detecting the ash content of semi-coke powder, which is used as a raw material for activated carbon filter element preparation. Inaccurate ash content detection leads to substandard semi-coke deashing, which in turn requires frequent adjustments to acid washing parameters, increasing the maintenance cost and reducing the service life of the reactor equipment. Furthermore, the inability of semi-coke deashing to effectively remove metal ions results in activated carbon filter elements failing to meet standards in water purification, catalysis, and other fields. Thus, existing technologies have shortcomings and urgently need further improvement and refinement. Summary of the Invention

[0005] To address the shortcomings of the existing technologies, the present invention aims to provide a method for detecting and preparing substrates for semi-coke-based activated carbon filter cartridges. This method is particularly suitable for ash control and process optimization in the production of high-performance carbon materials such as semi-coke activated carbon and adsorption materials, and is especially applicable to industrial manufacturing in environmental protection, water purification, and chemical industries.

[0006] According to an embodiment of the present invention, a first embodiment is provided: a method for detecting the substrate of a semi-coke-based activated carbon filter element, applied to a semi-coke-based activated carbon filter element preparation system, the method comprising: Collect samples of deashed semi-coke powder and perform pretreatment; The pretreated semi-coke powder samples were classified by particle size and the classified powder samples within the target particle size range were screened. The explicit ash content and implicit ash content were simultaneously detected in the graded powder samples to obtain the explicit ash content and implicit ash content, respectively. An optimization model for ash content detection is constructed based on the explicit ash content, implicit ash content, and deashing process parameters, and the model outputs the deashing effect judgment and deashing process adjustment parameters.

[0007] Furthermore, the steps for detecting the apparent ash content of the pretreated semi-coke powder sample include: detecting the apparent ash content by X-ray fluorescence spectroscopy, where apparent ash includes ash present in the form of inorganic oxides; The steps for detecting the latent ash content of pretreated semi-coke powder samples include: detecting the latent ash content by inductively coupled plasma mass spectrometry, where latent ash includes ash precursors that are converted into oxides after subsequent high-temperature oxidation and exist in ionic or soluble salt form.

[0008] Furthermore, the ash precursors of the explicit ash include SiO2, Al2O3, and CaO; the ash precursors of the implicit ash include iron ions, calcium ions, and sodium ions.

[0009] Furthermore, the step of detecting the dominant ash content by X-ray fluorescence spectroscopy includes: Graded powder samples are compressed into circular thin sheets using a tablet press for testing. The X-ray fluorescence spectrometer parameters were adjusted as follows: tube voltage 40-50kV, tube current 40-60mA, excitation source rhodium target, spectral scanning range 0.1-100keV, elemental analysis range covering Na-U, and detection time 3-5min / sample. A calibration curve was established using a series of standard samples containing SiO2, Al2O3, and CaO. The matrix effect was corrected by the basic parameter method. The mass percentages of SiO2, Al2O3, and CaO in the circular thin-film test sample were determined. The sum of the mass percentages of SiO2, Al2O3, and CaO was the explicit ash content.

[0010] Furthermore, the step of detecting latent ash content by inductively coupled plasma mass spectrometry includes: Take a graded powder sample and place it in a polytetrafluoroethylene digestion tube. Add a nitric acid-hydrofluoric acid mixture and then digest it. The parameters of the inductively coupled plasma mass spectrometer were adjusted as follows: radio frequency power 1400W-1600W, sampling depth 5-10mm, carrier gas flow rate 0.8-1.2L / min, and the detected isotopes included: Fe. 56 Ca 44 Na 23 The matrix interference was corrected using the internal standard method. Based on the detected metal ion concentration, the mass percentage of the corresponding oxide is converted according to the stoichiometric ratio of the oxide.

[0011] Furthermore, the steps for constructing an optimization model for ash content detection processes include: The controllable parameters of the deashing process are used as input variables: pickling concentration, pickling temperature, pickling time, and solid-liquid ratio; The total ash content is used as the output variable: the total ash content is the sum of the explicit ash content and the implicit ash content; Collect at least 100 sets of sample data. Each set of sample data corresponds to a combination of input variables and the explicit ash content and implicit ash content detected simultaneously. Normalize the input variables and convert the total ash content using Z-score and remove outliers. Key features of input variables were selected and a feature matrix was constructed. A random forest regression algorithm was used to build a mapping model between input variables and total gray content. The number of decision trees and the number of layers were set, and the hyperparameters were optimized through cross-validation to make the model's prediction error for total gray content less than ±0.3%. An optimization function is constructed with the goal of minimizing the total ash content: f(x) = w1 × A(x) + w2 × B(x), where A(x) is the predicted value of explicit ash content, B(x) is the predicted value of implicit ash content, and the weighting coefficients w1 = 0.3 and w2 = 0.7.

[0012] Furthermore, the steps for outputting the deashing effect judgment and deashing process adjustment parameters include: Based on the detection results of explicit and implicit ash content of graded powder samples, the judgment result is output by comparing them with the preset threshold: Grade 1 (Excellent), total ash content ≤0.5%; Grade II qualified, total ash content is 0.5%-0.8%, including 0.8%; Level 3 is unqualified, with a total ash content > 0.8%; When the judgment result is Level II qualified or Level III unqualified, the ash content detection process optimization model solves the optimal process parameter adjustment scheme based on the optimization function in reverse: Adjustment direction: Determine the adjustment trend based on the deviation between the current input variables and the optimal parameters predicted by the model; Adjustment range: The adjustment value of the quantified input variable; Adjustment basis: Synchronously output the total ash content predicted by the adjusted model; For each batch of testing, the actual detected total ash content is compared with the model prediction. If the deviation exceeds ±0.3%, the batch of data is included in the training set, and the model parameters are updated through incremental learning.

[0013] Furthermore, when the visible ash content exceeds the standard, the process adjustment parameters include: Add 0.5-1.0 mol / L hydrofluoric acid to the basic pickling solution, wherein: If SiO2 exceeds the standard, the amount of hydrofluoric acid added should be 0.8-1.0 mol / L, and the volume ratio with hydrochloric acid should be controlled at 1:3-1:4. If Al2O3 or CaO exceeds the standard, the amount of hydrofluoric acid added should be 0.5-0.7 mol / L, while maintaining the hydrochloric acid concentration at 2.0-2.5 mol / L. During the pickling process, ultrasonic treatment at 20-30 kHz is introduced, with a power density of 1.0-1.5 W / cm³. 2 Each ultrasonic treatment lasts 15-20 minutes, with a 30-minute interval, breaking down visible ash aggregates through cavitation.

[0014] Furthermore, when the latent ash content exceeds the standard, the process adjustment parameters include: The acid pickling concentration in the deashing process is increased by 0.3-0.5 mol / L within the basic process parameter range, where: If the oxides corresponding to iron ions or calcium ions exceed the standard, hydrochloric acid concentration should be increased first. If the sodium ion-corresponding oxide exceeds the standard, adjust the hydrofluoric acid concentration accordingly. Add 0.3%-0.5% sodium citrate as a chelating agent to the pickling solution. It preferentially chelates calcium and iron ions, destroys the complex structure of hidden ash and organic matter, and controls the chelation reaction time to 1 / 3 of the total pickling time.

[0015] According to an embodiment of the present invention, utilizing the substrate detection method for semi-coke-based activated carbon filter cartridges in the first embodiment of the present invention, a second embodiment is provided as follows: A method for preparing a substrate for a semi-coke-based activated carbon filter element includes the following steps: Obtain semi-coke raw material and crush it to obtain semi-coke powder; Input preset basic process parameters to deash semi-coke powder. The basic process parameters include acid washing concentration, acid washing temperature, acid washing time and solid-liquid ratio. After deashing treatment, the semi-coke powder is tested for deashing and the process parameters are adjusted accordingly to obtain low-ash semi-coke powder. High specific surface area activated carbon powder is obtained by activating low ash semi-coke powder. The activated carbon water filter element is obtained through bonding, extrusion molding, and sintering curing. Compared with the prior art, the beneficial effects of the independent claims of the technical solution provided in this application are as follows: This method incorporates inductively coupled plasma mass spectrometry (ICP-MS) for detecting latent ash content. By employing dual-dimensional quantitative analysis of ash, it significantly improves the accuracy of total ash content detection in semi-coke powder. Further differentiation between visible and latent ash detection avoids problems associated with conventional methods, such as poor removal of latent ash components during deashing processes and frequent adjustments to acid washing parameters due to substandard deashing. In particular, it allows for more accurate removal of metal ions, resulting in activated carbon filter cartridges with superior product quality in water purification and catalysis applications. This detection method provides crucial technical support for replacing expensive coconut shell charcoal and wood charcoal in the preparation of high-performance activated carbon, promoting the industrial upgrading of coal chemical solid waste resources. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. 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 effort.

[0017] in: Figure 1 This is a flowchart of a substrate testing method for a semi-coke-based activated carbon filter cartridge in one embodiment; Figure 2 This is a flowchart of a method for preparing a substrate for a semi-coke-based activated carbon filter element in one embodiment. Detailed Implementation

[0018] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] Example 1

[0020] This embodiment targets a semi-coke-based activated carbon water filter production line for coal chemical enterprises. Semi-coke raw material is used as a base material for preparing high-performance activated carbon due to its high fixed carbon content and low cost. However, the total ash content of semi-coke raw material will significantly reduce the specific surface area of ​​activated carbon and cause secondary pollution of the water filter. Its technical defects are: First, the traditional ignition method is inaccurate. Measuring only the total ash content will cause some latent ash to be converted back into fixed impurities in the subsequent activation process, affecting product performance. Second, the adjustment of process parameters depends on manual experience and requires multiple debugging and iterations to meet the standards, resulting in increased maintenance costs.

[0021] To address the aforementioned technical problems, this embodiment provides a method for detecting the substrate of a semi-coke-based activated carbon filter element, such as... Figure 1 As shown, it includes: S1: Collect and pre-treat semi-coke powder samples after deashing. S2: Perform particle size classification on the pretreated semi-coke powder sample and screen out the classified powder samples within the target particle size range; S3: Simultaneously detect the visible ash content and the latent ash content of the graded powder samples to obtain the visible ash content and the latent ash content respectively; S4: Construct an ash content detection process optimization model based on visible ash content, latent ash content, and deashing process parameters, and output the deashing effect judgment and deashing process adjustment parameters.

[0022] Specifically, step S1, which involves collecting and pre-treating semi-coke powder, includes: randomly collecting 5 samples (500g each) from the outlet of the deashing reactor, mixing them, and taking 200g as the test sample. The test sample is then placed in a vacuum drying oven to dry for 1.5 hours to remove moisture, ground in a ball mill for 30 minutes, and passed through a 100-mesh sieve to make the initial particle size <150μm. Specifically, the steps in step S2 to obtain graded powder samples include: using standard test sieves, the first standard sieve is 100 mesh with an aperture of 150 μm, and the second standard sieve is 200 mesh with an aperture of 75 μm. The pretreated powder is passed through the 100 mesh sieve to remove coarse particles and through the 200 mesh sieve to remove fine powder, and graded powder samples of 75-150 μm are collected.

[0023] Specifically, the steps for total ash content detection of graded powder samples include: Detection of visible ash content: 5g of graded powder was pressed into circular thin slices with a diameter of 40mm using a hydraulic tablet press; the X-ray fluorescence spectrometer was set to a tube voltage of 45kV, a tube current of 50mA, and a rhodium target excitation source, with a scanning range of 0.1-100keV and a detection time of 4min / sample. Calibration curves were established using a series of standard samples containing SiO2, Al2O3, and CaO. Matrix effects were corrected using the basic parameter method, and the mass percentages of SiO2, Al2O3, and CaO in the circular thin slice samples were determined.

[0024] In this embodiment, the apparent ash content is SiO2=0.62%, Al2O3=0.38%, CaO=0.20%, and apparent ash content=1.20%.

[0025] Latent ash content detection: 2.5g of fractionated powder was placed in a polytetrafluoroethylene digestion tube, and 12mL of a nitric acid-hydrofluoric acid mixture (volume ratio 3:1) was added. Microwave digestion was performed at 120℃ for 10 minutes, followed by 180℃ for 20 minutes. After cooling, the acid was removed to a final volume of 2mL, and then diluted to 50mL with 2% nitric acid. The inductively coupled plasma mass spectrometer (ICP-MS) was used with a radio frequency power of 1500W, a sampling depth of 8mm, and a carrier gas flow rate of 1.0L / min to detect the Fe isotope. 56 Ca 44 Na 23 , internal standard Ge 72 In 115 Correct matrix interference.

[0026] Concentration conversion steps: Fe 3+ Concentration = 85 mg / kg, Fe2O3 content = 85 × 1.4297 / 10000 = 0.1215%, where the conversion factor 1.4297 = Fe2O3 molecular weight / 2Fe atomic weight; Ca 2+ Concentration = 52 mg / kg, CaO content = 52 × 1.3992 / 10000 = 0.0728%, where the conversion factor 1.3992 = CaO molecular weight / Ca atomic weight; Na + Concentration = 35 mg / kg, Na2O content = 35 × 1.3479 / 10000 = 0.0472%, where the conversion factor 1.3479 = Na2O molecular weight / 2Na atomic weight; Total latent ash content = 0.1215% + 0.0728% + 0.0472% = 0.2415%.

[0027] Total ash content = visible ash content + latent ash content = 1.4415%. 1.4415% is higher than the target threshold of 0.8%, so process adjustment is required.

[0028] Specifically, the steps for constructing the ash content detection process optimization model are as follows: Input variables: pickling concentration 1.5-2.5 mol / L, pickling temperature 60-80℃, pickling time 0.5-2.5 h, solid-liquid ratio 6:1-9:1; Output variable: total ash content. The optimization function is f(x) = w1 × A(x) + w2 × B(x), where A(x) is the predicted value of explicit ash content, B(x) is the predicted value of implicit ash content, and the weighting coefficients are w1 = 0.3 and w2 = 0.7. In this embodiment, the weighting coefficient of implicit ash content is higher to prioritize the control of activation risk.

[0029] 120 sets of historical data were collected to cover different batches of semi-coke. Each set included a combination of input variables and corresponding explicit and implicit ash content detection values. The input variables were normalized to the [0,1] interval. The total ash content was Z-score transformed, and 3 outliers were removed, with an error > ±0.5%. The random forest regression algorithm was used with 100 decision trees and a maximum depth of 8 layers. After optimization with 5-fold cross-validation, the prediction error was < ±0.25%.

[0030] Specifically, the steps for judging the deashing effect and adjusting the process are as follows: The current total ash content is 1.4415%, compared to the preset threshold: Grade 1 (Excellent), total ash content ≤0.5%; Grade II qualified, total ash content is 0.5%-0.8%, including 0.8%; Level 3 is unqualified, with a total ash content > 0.8%; The model is based on the inverse solution of the optimization function to find the optimal parameter output adjustment scheme: The saturated ash content exceeded the standard. Hydrofluoric acid was added to the original 2.0 mol / L hydrochloric acid to bring the concentration to 0.8 mol / L, with a volume ratio of hydrochloric acid to hydrofluoric acid of 3:1. Ultrasonic treatment at 25 kHz with a power density of 1.2 W / cm³ was then used. 2 Each session lasts 20 minutes, with a 30-minute interval between sessions. Simultaneously, auxiliary control of latent ash content was implemented: sodium citrate was added as a chelating agent at a mass fraction of 0.4%, chelating Ca... 2+ To disrupt the mineral encapsulation structure.

[0031] After adjustment, the total ash content is 0.48%, which meets the first-class standard.

[0032] The above steps enable precise quantification of substrate testing and intelligent process adjustment for semi-coke-based activated carbon filter cartridges, solving the problems of inaccurate testing and lagging adjustment in traditional methods, and providing a repeatable and efficient technical solution for the industrial production of semi-coke-based activated carbon water purification filter cartridges.

[0033] Example 2

[0034] The solution in Example 1 still has technical pain points in industrial continuous production: the offline sampling and detection cycle is too long, which leads to the lag in process adjustment, and the existing ash removal process has low recognition accuracy for some hidden ash structures.

[0035] Based on Example 1, this example provides a method for detecting the substrate of a semi-coke-based activated carbon filter element, including the following steps: Online sample acquisition and processing procedure. A laser-induced sampler is installed at the outlet of the deashing reactor, sampling once every 5 minutes. Representative samples are collected from the flowing powder using laser cutting technology, avoiding the bias of manual sampling. The collected samples automatically enter a microwave drying and grinding equipment. The pre-treated powder is divided into two paths: one path enters the force classification system, and the other path enters the microstructure analysis unit.

[0036] Particle size classification and ash distribution analysis procedures. Particle size classification is performed using an air classifier to further improve classification efficiency. 10 mg of the classified powder is taken and dispersed on conductive adhesive. The particle surface and cross-section are analyzed using field emission scanning electron microscopy (FET), combined with EDS scanning to identify high-ash regions and calculate their proportion.

[0037] Synergistic detection of explicit and implicit ash. Based on Example 1, a valence state separation column was added to analyze Fe. 2+ / Fe 3+ Cr 3+ / Cr 6+ Plasma chromatography was used to determine the concentration of different valence states. Ion chromatography was also used to detect Ca in pickling wastewater. 2+ -SO4 2- The concentration of the composite salt, combined with SEM-EDS results, was used to determine the encapsulation effect of the composite salt on latent ash. For example, the detection rate of CaSO4 encapsulation was 15%.

[0038] Deep learning dynamic optimization model construction. Input variables are expanded to include three types of real-time data: microscopic features: proportion of high-ash areas, ash coverage of particle surfaces; ionic speciation data: Fe... 3+ / Fe 2+Ratios and complex salt concentrations; online sensor data: pH value and stirring torque within the reactor. A CNN-LSTM hybrid model was constructed (convolutional neural network extracts microscopic image features, long short-term memory network processes time-series process data), with the training set including data from Example 1 plus 200 newly added micro-macro linkage data sets. The model outputs graded process parameters in real time. For samples with a high ash content >10%, the pickling temperature is automatically increased, and 0.5% sodium citrate is added to chelate Ca. 2+ This disrupts the complex salt coating. For Fe... 3+ For samples with a ash content greater than 60%, the acid washing time was extended to 2.2 hours, while the stirring rate was simultaneously reduced to 200 r / min to minimize particle breakage and prevent re-adsorption of latent ash after exposure. This approach overcomes the limitations of traditional offline detection, achieving microscopic targeted control and providing an industrially viable technical path for the intelligent upgrading of semi-coke deashing processes.

[0039] Example 3 In the existing preparation process of semi-coke-based activated carbon water filter cartridges, fixed deashing process parameters, including acid washing parameters, are typically used. This is a crude production method that basically does not consider the differences in ash content of the semi-coke raw material, resulting in unstable ash residue in the low-ash semi-coke powder. This instability in ash residue directly affects the fluctuation of the specific surface area of ​​the activated carbon after activation. The reason for this relationship is that ash content physically hinders and chemically interferes with the activation process. Physical hindrance refers to the residual visible ash after deashing, including fluctuations in the content of surface mineral particles, which cause some ash particles to adhere to the surface of the semi-coke carbon skeleton, hindering the contact between the activator and the carbon matrix, resulting in a reduction in the amount of voids generated and a decrease in specific surface area. It also includes the presence of latent ash residue. Latent ash, such as metal ions embedded in the carbon skeleton lattice, occupies activation sites in the carbon material. When the content of latent ash is unstable, the number of activation sites varies greatly, directly leading to fluctuations in the number of voids after activation and causing changes in specific surface area. Chemical interference refers to the non-selective chemical reaction between metal oxides in ash and activators, which interferes with the orderly etching of the carbon skeleton. Fluctuations in ash content directly lead to changes in reaction intensity, resulting in catalytic over-etching or inhibited activation reaction, and causing fluctuations in specific surface area.

[0040] Furthermore, existing methods for preparing activated carbon water filter cartridges suffer from problems such as using a single activator, insufficient control over pore structure, and uneven final filter cartridge structure. Therefore, existing methods for preparing activated carbon water filter cartridges require further improvement and refinement.

[0041] In this embodiment, hollow columnar activated carbon water filter cartridges are prepared using semi-coke raw materials. The semi-coke raw materials have 82% fixed carbon and 3.2% initial ash content.

[0042] A method for preparing a substrate for a semi-coke-based activated carbon filter element, such as... Figure 2 As shown, the steps include: P01: Obtain semi-coke raw material and crush it to obtain semi-coke powder; This step involves the crushing and pretreatment of semi-coke raw materials. Select semi-coke blocks with a particle size of 5-10 mm, coarsely crush them using a jaw crusher, and then further crush them into semi-coke powder with a particle size of 0.1-0.5 mm using an impact pulverizer. Place the semi-coke powder in a hot air dryer and dry for 1 hour to ensure the moisture content is less than 2%.

[0043] P02: Input preset basic process parameters to deash the semi-coke powder. The basic process parameters include acid washing concentration, acid washing temperature, acid washing time and solid-liquid ratio. This step, the first step in the dynamic deashing treatment of semi-coke powder, involves a 500L pickling reactor equipped with an online pH meter. The basic process parameters are set as follows: pickling solution is hydrochloric acid, diluted pickling concentration is 2.0 mol / L, solid-liquid ratio is 7:1, initial temperature is 70℃, heating rate is 5℃ / min, and holding time is 2.0 h.

[0044] P03: After deashing treatment, the semi-coke powder is tested for deashing and the process parameters are adjusted accordingly to obtain low-ash semi-coke powder. Step two of the dynamic deashing treatment of the semi-coke powder involves sampling every 30 minutes and performing deashing tests using the scheme described in Example 1. When the latent ash content is detected to be >0.5%, the acid washing temperature is increased to 75°C and the holding time is extended by 0.5 hours. The deashed semi-coke powder is then filtered and dehydrated to obtain low-ash semi-coke powder.

[0045] P04: High specific surface area activated carbon powder is obtained by activating low ash semi-coke powder; This step involves a composite activator-controlled activation process. A continuous vertical activation furnace is used, with three temperature control zones: a preheating zone at 400°C, an activation zone at 850°C, and a cooling zone at 200°C. The activator is prepared as follows: a mixed gas of water vapor and carbon dioxide at a volume ratio of 3:2, with a total flow rate of 15 m³ / h. Low-ash semi-coke powder is fed into the activation furnace at a rate of 50 kg / h. The residence time in the activation zone is 3 hours to ensure sufficient development of mesopores and micropores. After activation, the product is cooled to room temperature under nitrogen protection, and unactivated particles are sieved to obtain high specific surface area activated carbon powder.

[0046] P05: The activated carbon water filter cartridge is obtained by bonding, extrusion molding and sintering curing.

[0047] This step is the filter element molding step. The activated carbon slurry is prepared as follows: 85 parts of high specific surface area activated carbon powder, 10 parts of phenolic resin binder, 5 parts of sodium carboxymethyl cellulose, and 20 parts of deionized water. The mixture is stirred for 30 minutes at a speed of 600 rpm to form a uniform paste. The filter element matrix is ​​then formed using a single-screw extruder at an extrusion rate of 30 cm / min. After sintering in a sintering furnace, the matrix is ​​cooled, ultrasonically cleaned with deionized water, and then dried with hot air to obtain the finished activated carbon water purification filter element.

[0048] Through dynamic adjustment of deashing parameters, the residual ash content of low-ash semi-coke powder is further reduced and the ash content fluctuation is smaller. The composite activator increases the proportion of mesopores and micropores, and the specific surface area can reach up to 1800 m². 2 / g, achieving high performance and low cost of semi-coke-based activated carbon water purification filter cartridges, solving the industry pain points of large performance fluctuations and low adsorption efficiency in traditional processes.

[0049] Example 4 The scheme in Example 3 stabilized the residual ash content by controlling the deashing parameters. However, it did not specifically consider the differences in ash composition and the selective effect of activation temperature on different ash components, resulting in shortcomings in Example 3. For example, when the proportions of silica, ferric oxide, and other components in semi-coke ash fluctuate with different batches of raw materials, ferric oxide acts as a catalyst for the activation reaction, while silica is an inert component. The porosity generation efficiency fluctuates between 10% and 25% when the component proportions are different. Furthermore, the single activation temperature in Example 3 can cause calcium oxide in the ash to be in a molten state at higher temperatures, which can block the pores and reduce the specific surface area. At the same time, when the silica content is high, the same temperature is insufficient to promote the reaction between silica and carbon, causing residual silica particles to occupy pore sites. The fluctuation of specific surface area still needs to be optimized.

[0050] To solve the above-mentioned technical problems, this embodiment provides a method for preparing the substrate of the semi-coke-based activated carbon filter element, including the following steps: The deashed low-ash semi-coke powder was semi-quantitatively analyzed by X-ray fluorescence spectroscopy, and quantitatively analyzed simultaneously by inductively coupled plasma mass spectrometry to determine the main ash components and their proportions. For example, ash with an Fe2O3 content ≥20% is defined as Category A. A typical Category A semi-coke powder has the following ash content: Fe2O3 ≥20%, CaO ≤8%, SiO2 = 30%-40%. Ash with high calcium oxide content is defined as Category B. A typical Category B semi-coke powder has the following ash content: CaO ≥12%, Fe2O3 ≤10%, SiO2 = 35%-45%. Ash with high silica content is defined as Category C. A typical Category C semi-coke powder has the following ash content: SiO2 ≥45%, Fe2O3 ≤15%, CaO ≤8%. The significance of this definition step is that the ash content of the category serves as the basis for subsequent activation temperature control.

[0051] Specifically, the traditional three-stage vertical activation furnace will be transformed into a five-stage vertical activation furnace, including a preheating stage, a low-temperature stage, a medium-temperature stage, a high-temperature stage, and a cooling stage, with each stage having its temperature independently controlled. Differential temperature profiles will be set according to the ash content category, for example: Category A: 400 (1h), 600 (0.5h), 800 (1h), 850 (0.5h), total activation time 3.0h; Category B: 400 (1h), 700 (1h), 800 (0.5h), 820 (0.5h), total activation time 3.0h; Category C: 400 (1h), 700 (0.5h), 900 (1h), 850 (0.5h), total activation time 3.0h; Category A: Utilizing the catalytic effect of Fe2O3 at 600-800℃, shortening the high-temperature section to avoid over-etching; Category B: Extending the low-temperature section to 1 hour, allowing CaO to preferentially react with the activator CO2 to generate CaCO3, avoiding high-temperature melting; Category C: Increasing the medium-temperature section to 900℃, promoting the reaction between SiO2 and carbon, and reducing inert SiO2 residue.

[0052] Similarly, the activator ratio is dynamically adjusted according to the ash composition: Activator mixing ratio optimization: Adjusting the volume ratio of water vapor to CO2 according to the ash type: Category A: H2O:CO2 = 7:3, enhances the catalytic activation efficiency of Fe2O3 for water vapor; Category B: H2O:CO2 = 3:7, increasing the CO2 ratio promotes the conversion of CaO to CaCO3; Category C: H2O:CO2 = 5:5, balancing SiO2 reaction and pore etching; In addition, flow control is required, with a total activator flow rate of 15m³. 3 / h, the mixing ratio is adjusted in real time by mass flow meter and synchronized with gradient temperature curve.

[0053] This solution solves the performance fluctuation problem caused by compositional differences under the same total ash content by accurately classifying ash and combining it with dynamic adaptation of gradient temperature and activator control, and brings about a significant improvement in the specific surface area stability of activated carbon.

[0054] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification. The above embodiments only illustrate several implementation methods of this application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of this application's patent. It should be noted that for those skilled in the art, several modifications and improvements can be made without departing from the concept of this application, and these all fall within the protection scope of this application.

[0055] It should be noted that when an element is referred to as being "fixed to" or "set on" another component, it can be directly or indirectly set on the other component; when a component is referred to as being "connected to" another component, it can be directly or indirectly connected to the other component. It should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or component referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application.

[0056] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" or "several" means two or more, unless otherwise explicitly specified.

[0057] It should be noted that the structures, proportions, sizes, etc., shown in the accompanying drawings are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed in the specification, and are not intended to limit the conditions under which this application can be implemented. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportions, or adjustments to the size should still fall within the scope of the technical content disclosed in this application, provided that they do not affect the effects and purposes that this application can produce.

Claims

1. A method for detecting the substrate of a semi-coke-based activated carbon filter element, applied to a semi-coke-based activated carbon filter element preparation system, characterized in that, The method includes: Collect samples of deashed semi-coke powder and perform pretreatment; The pretreated semi-coke powder samples were classified by particle size and the classified powder samples within the target particle size range were screened. The explicit ash content and implicit ash content were simultaneously detected in the graded powder samples to obtain the explicit ash content and implicit ash content, respectively. An optimization model for ash content detection process is constructed based on the explicit ash content, implicit ash content, and deashing process parameters, and the outputs the deashing effect judgment and deashing process adjustment parameters. The steps for detecting the apparent ash content of pretreated semi-coke powder samples include: detecting the apparent ash content by X-ray fluorescence spectroscopy, where apparent ash includes ash present in the form of inorganic oxides; The steps for detecting the latent ash content of pretreated semi-coke powder samples include: detecting the latent ash content by inductively coupled plasma mass spectrometry, where latent ash includes ash precursors that are converted into oxides after subsequent high-temperature oxidation and exist in ionic or soluble salt form. The ash precursors of the explicit ash include SiO2, Al2O3 and CaO; the ash precursors of the implicit ash include iron ions, calcium ions and sodium ions. The steps for constructing an optimization model for ash content detection processes include: The controllable parameters of the deashing process are used as input variables: pickling concentration, pickling temperature, pickling time, and solid-liquid ratio. The total ash content is used as the output variable: the total ash content is the sum of the explicit ash content and the implicit ash content; Collect at least 100 sets of sample data. Each set of sample data corresponds to a combination of input variables and the explicit and implicit ash contents detected simultaneously. Normalize the input variables and convert the total ash content using Z-score and remove outliers. Key features of input variables were selected and a feature matrix was constructed. A random forest regression algorithm was used to build a mapping model between input variables and total gray content. The number of decision trees and the number of layers were set, and the hyperparameters were optimized through cross-validation to make the model's prediction error for total gray content less than ±0.3%. An optimization function is constructed with the goal of minimizing the total ash content: f(x) = w1 × A(x) + w2 × B(x), where A(x) is the predicted value of the explicit ash content, B(x) is the predicted value of the implicit ash content, and the weighting coefficients w1 = 0.3 and w2 = 0.

7. When the visible ash content exceeds the standard, the process adjustment parameters include: Add 0.5-1.0 mol / L hydrofluoric acid to the basic pickling solution, wherein: If SiO2 exceeds the standard, the amount of hydrofluoric acid added should be 0.8-1.0 mol / L, and the volume ratio with hydrochloric acid should be controlled at 1:3-1:

4. If Al2O3 or CaO exceeds the standard, the amount of hydrofluoric acid added should be 0.5-0.7 mol / L, while maintaining the hydrochloric acid concentration at 2.0-2.5 mol / L. During the pickling process, ultrasonic treatment at 20-30 kHz is introduced, with a power density of 1.0-1.5 W / cm³. 2 Each ultrasonic treatment lasts 15-20 minutes, with a 30-minute interval, breaking down visible ash aggregates through cavitation. When the latent ash content exceeds the standard, the process adjustment parameters include: The acid pickling concentration in the deashing process is increased by 0.3-0.5 mol / L within the basic process parameter range, where: If the oxides corresponding to iron or calcium ions exceed the standard, increase the concentration of hydrochloric acid. If the sodium ion-corresponding oxide exceeds the standard, adjust the hydrofluoric acid concentration accordingly. Add 0.3%-0.5% sodium citrate as a chelating agent to the pickling solution to chelate calcium and iron ions and destroy the complex structure of hidden ash and organic matter. The chelation reaction time should be controlled to 1 / 3 of the total pickling time.

2. The method for detecting the substrate of the semi-coke-based activated carbon filter element according to claim 1, characterized in that, The step of detecting the dominant ash content by X-ray fluorescence spectroscopy includes: Graded powder samples are compressed into circular thin sheets using a tablet press for testing. The X-ray fluorescence spectrometer parameters were adjusted as follows: tube voltage 40-50kV, tube current 40-60mA, excitation source rhodium target, spectral scanning range 0.1-100keV, elemental analysis range covering Na-U, and detection time 3-5min / sample; A calibration curve was established using a series of standard samples containing SiO2, Al2O3, and CaO. The matrix effect was corrected by the basic parameter method. The mass percentages of SiO2, Al2O3, and CaO in the circular thin-film test sample were determined. The sum of the mass percentages of SiO2, Al2O3, and CaO was the explicit ash content.

3. The method for detecting the substrate of the semi-coke-based activated carbon filter element according to claim 1, characterized in that, The steps for detecting latent ash content by inductively coupled plasma mass spectrometry include: Take a graded powder sample and place it in a polytetrafluoroethylene digestion tube. Add a nitric acid-hydrofluoric acid mixture and then digest it. The parameters of the inductively coupled plasma mass spectrometer were adjusted as follows: radio frequency power 1400W-1600W, sampling depth 5-10mm, carrier gas flow rate 0.8-1.2L / min, and the detected isotopes included: Fe. 56 Ca 44 and Na 23 The matrix interference was corrected using the internal standard method. Based on the detected metal ion concentration, the mass percentage of the corresponding oxide is converted according to the stoichiometric ratio of the oxide.

4. The method for detecting the substrate of the semi-coke-based activated carbon filter element according to claim 1, characterized in that, The steps for determining the deashing effect and adjusting the deashing process parameters include: Based on the detection results of explicit and implicit ash content of graded powder samples, the judgment result is output by comparing with the preset threshold: Grade 1 (Excellent), total ash content ≤0.5%; Grade II qualified, total ash content is 0.5%-0.8%, including 0.8%; Level 3 is unqualified, with a total ash content > 0.8%; When the judgment result is Level II qualified or Level III unqualified, the ash content detection process optimization model solves the optimal process parameter adjustment scheme based on the optimization function in reverse: Adjustment direction: Determine the adjustment trend based on the deviation between the current input variables and the optimal parameters predicted by the model; Adjustment range: The adjustment value of the quantified input variable; Adjustment basis: Synchronously output the total ash content predicted by the adjusted model; For each batch of testing, the actual detected total ash content is compared with the model prediction. If the deviation exceeds ±0.3%, the batch of data is included in the training set, and the model parameters are updated through incremental learning.

5. A method for preparing a substrate for a semi-coke-based activated carbon filter element, characterized in that, The substrate used in the substrate testing method for preparing the semi-coke-based activated carbon filter element according to any one of claims 1 to 4, wherein the preparation method includes the steps of: Obtain semi-coke raw material and crush it to obtain semi-coke powder; Input preset basic process parameters to deash semi-coke powder. The basic process parameters include acid washing concentration, acid washing temperature, acid washing time and solid-liquid ratio. After deashing treatment, the semi-coke powder is tested for deashing and the process parameters are adjusted accordingly to obtain low-ash semi-coke powder. High specific surface area activated carbon powder is obtained by activating low ash semi-coke powder. The activated carbon water filter cartridge is obtained by bonding, extrusion molding and sintering curing.

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