Method and system for preparing high-purity silicon carbide through self-adaptive collaborative conversion of fluctuating silicon-aluminum ratio of fly ash

Abstract

The application provides a method and system for preparing high-purity SiC through self-adaptive collaborative conversion of fluctuating fly ash silicon-aluminum ratio, comprising: adopting a differential acid etching technology for silicon-aluminum separation; performing differential acid treatment on high-silicon and low-silicon fly ash to efficiently separate silicon-aluminum components in the fly ash in an acid activation-ultrasonic mechanical chemical coupling mode; adopting a deep deterministic policy gradient algorithm to construct a temperature decision model for precise temperature control; establishing a temperature decision model, and optimizing a temperature rising path and a holding time based on the deep deterministic policy gradient algorithm; in-situ resource utilization of excessive Al2O3 in a low-silicon phase to prepare high-performance SiC; and converting the excessive Al2O3 in the low-silicon phase into a functional carrier that can be used for preparing a composite material through an in-situ chemical reaction. The acid activation-mechanical chemical coupling method is used to dissociate silicon-aluminum in fly ash, a dynamic optimization carbon thermal reduction path mode is fused with a reinforcement learning algorithm, and the two modes are coupled to improve the quality and efficiency of SiC material prepared from fly ash.

Description

Technical Field

[0001] This invention relates to the field of SiC preparation technology from fly ash, specifically to a method and system for preparing high-purity SiC by adaptive synergistic conversion of fly ash with fluctuating silicon-to-aluminum ratio. Background Technology

[0002] In the field of fly ash resource utilization, especially in the preparation of high-purity SiC materials, existing technologies such as CN119954450A and CN102583468A have achieved certain results in concrete preparation and alumina extraction, but have failed to effectively solve the impact of fly ash silicon-aluminum ratio fluctuations on SiC preparation.

[0003] CN119954450A solves the interfacial incompatibility problem between GO and SA through silanization modification and magnetic field induction, but does not involve the preparation of SiC, and its technical solution is not entirely related to the field of this application. CN102583468A extracts alumina from fly ash based on an ammonium sulfate activation process, which solves the problems of high equipment corrosion and long process chain, but its technical route does not involve the synthesis of SiC and fails to propose an adaptive control strategy for the fluctuation of the silicon-aluminum ratio in fly ash.

[0004] The technological innovation of this application lies in constructing a three-level control system of "acid activation-mechanical-chemical coupling → reinforcement learning dynamic temperature control → in-situ Al2O3 conversion" to address the impact of fluctuating SiO2 / Al2O3 ratios in fly ash on SiC preparation. Through differentiated acid leaching, ultrasonic mechanical activation, reinforcement learning dynamic temperature control, and in-situ Al2O3 resource utilization, highly efficient activation and conversion of SiO2 and Al2O3 in fly ash are achieved, improving the purity and performance of SiC. Simultaneously, it solves the problems of low temperature control precision, amorphous SiC formation, and the presence of Al2O3 as an impurity in existing technologies. This technical solution not only enhances the added value of SiC products but also achieves "zero waste discharge," demonstrating significant economic and environmental benefits. Summary of the Invention

[0005] The present invention aims to at least solve one of the technical problems existing in the prior art, and provides a method and system for preparing high-purity SiC by adaptive synergistic conversion of fly ash silicon-aluminum ratio fluctuation.

[0006] In a first aspect, embodiments of the present invention provide a method for preparing high-purity SiC by adaptive synergistic conversion of fly ash silicon-aluminum ratio fluctuations, the method comprising the following steps: Step 1: Differentiated acid etching technology for silicon-aluminum separation: Differentiated acid treatment is applied to high-silicon and low-silicon fly ash to efficiently separate the silicon-aluminum components in fly ash using an acid activation-ultrasonic mechanochemical coupling method. Step 2: Construct a temperature decision model using a deep deterministic strategy gradient algorithm for precise temperature control: Establish a temperature decision model and optimize the heating path and holding time based on the deep deterministic strategy gradient algorithm; Step 3: In-situ resource utilization of excess Al2O3 in the low-silicon phase to prepare high-performance SiC: The excess Al2O3 in the low-silicon phase is converted into a functional carrier that can be used to prepare composite materials through in-situ chemical reaction.

[0007] Furthermore, in step 1, the differentiated acid etching refers to: high-silica fly ash is treated with a two-step acid process, in which dilute sulfuric acid and oxalic acid are used sequentially to dissolve SiO and Al2O3 in the fly ash; low-silica fly ash is treated with citric acid, which uses citric acid to complex Al in the fly ash to form a soluble complex, thereby blocking the reaction between the acid and the fly ash and achieving etching.

[0008] Furthermore, in step 1, a uniformly mixed micron-sized composite slurry is obtained after ultrasonic mechanochemical treatment.

[0009] Furthermore, in step 1, the two-step acid treatment refers to the following steps: first, dissolving SiO in fly ash with dilute sulfuric acid; second, selectively activating Al2O3 in fly ash with oxalic acid.

[0010] Furthermore, in step 2, the temperature decision model constructed by the deep deterministic policy gradient algorithm refers to: constructing a temperature decision model based on the deep deterministic policy gradient algorithm, starting from the initial temperature point T and ending at the final temperature point T, dividing the temperature into N equal temperature intervals, setting the width ΔT for each temperature interval, and obtaining a series of temperature sequences T={T, T, ..., T}; selecting a sample point T in each temperature interval as the representative temperature point of that interval, obtaining a temperature sequence T={T, T, ..., T}, sorting the sample points according to the difference between the temperature of each sample point and the ideal temperature, and calculating the update rate v; after optimizing the temperature interval, continuing to optimize adjacent temperature intervals until all temperature intervals meet the accuracy requirements.

[0011] Furthermore, in step 2, the construction of the temperature decision model includes input parameters and output parameters; wherein, the input parameters include: real-time silicon-to-aluminum ratio, carbon-to-silicon ratio, and material thermal conductivity; the output parameters include: dynamically adjusting the reduction temperature range and heating rate.

[0012] Furthermore, in step 3, the in-situ chemical reaction refers to promoting the growth of β-SiC crystals in an alkaline melt environment while inducing the formation of magnesium aluminum spinel.

[0013] Furthermore, in step 3, the functional carrier used to prepare the composite material refers to a magnesium aluminum spinel phase with high strength and high fire resistance.

[0014] Furthermore, in step 3, after in-situ chemical reaction, a multiphase product with prismatic a-SiC (hexagonal silicon nitride) as the main component is obtained.

[0015] Secondly, embodiments of the present invention provide a system for the adaptive synergistic conversion of fly ash silicon-aluminum ratio fluctuations to prepare high-purity SiC, the system comprising: The system comprises an information acquisition module, a computation and decision-making module, and an execution operation module; the information acquisition module and the computation and decision-making module transmit signals bidirectionally; the computation and decision-making module includes a data history storage unit, a neural network weight coefficient correction unit, and a gradient descent operator; the execution operation module includes a temperature control device, a spray gun, and a high-speed stirrer. The information acquisition module probes detect the furnace temperature, carbon-silicon ratio, and simulated atmosphere in real time. The data history storage unit records the detection values ​​at different times; The neural network weight coefficient correction unit updates the network weight coefficients to optimize the heating path; The gradient descent operator continuously updates the temperature control command for the next time step; The temperature control device maintains the furnace temperature within a specific range; The spray gun and high-speed mixer receive instructions from the calculation and decision module and spray the reducing agent onto the surface of the fly ash.

[0016] Compared with existing technologies, the present invention provides a method and system for preparing high-purity SiC by adaptive synergistic conversion of fly ash silica-alumina ratio fluctuation. It is the first to propose an acid activation-mechanical-chemical coupling method to dissociate fly ash silica-alumina, and integrates a reinforcement learning algorithm to dynamically optimize the carbothermic reduction path. The two external forces coupled together greatly improve the quality and efficiency of SiC material preparation from fly ash. Attached Figure Description

[0017] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 A flow chart of a system for preparing high-purity SiC from fly ash according to an embodiment of the present invention; Figure 2 This is a structural diagram of the internal structure of a three-layer heating furnace according to an embodiment of the present invention. Detailed Implementation

[0019] To enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0020] Unless otherwise specifically stated, the technical or scientific terms used in the embodiments of this invention should be understood in their ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains. The terms "comprising" or "including," as used in the embodiments of this invention, do not limit the shapes, numbers, steps, actions, operations, components, elements, and / or groups thereof mentioned, nor do they exclude the appearance or addition of one or more other different shapes, numbers, steps, actions, operations, components, elements, and / or groups thereof, or the inclusion of these.

[0021] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention. It should also be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale, and techniques, methods, and apparatus known to those skilled in the art may not be discussed in detail; however, where appropriate, the illustrated techniques, methods, and apparatus should be considered part of the specification. In all the examples shown and discussed herein, any other specific example may have different values. It should be noted that similar symbols and letters in the following figures denote similar items; therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0022] In the description of the embodiments of the present invention, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In the embodiments of the present invention, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in the embodiments of the present invention, as well as the features of different embodiments or examples.

[0023] Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments of the present invention. It should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0024] This invention discloses a method for preparing high-purity SiC by adaptive synergistic conversion of fly ash with fluctuating silicon-to-aluminum ratio, comprising the following steps: Step 1: Differentiated acid leaching - ultrasonic mechanical and chemical pretreatment of special fly ash.

[0025] like Figure 1 As shown, in Figure 1 The components used in the system process are as follows: 1. Acid etching container; 2. Ultrasonic mechanochemical processor; 3. Slurry storage tank; 4. Temperature sensor; 5. Carbon-silicon ratio sensor; 6. Data history storage unit; 7. Neural network weight coefficient correction; 8. Gradient descent operator; 9. Spray gun; 11. High-speed stirrer; 12. Three-layer heating furnace; 13. Mixing homogenizer; 14. Preheating furnace; 15. Corundum crucible; 16. When preparing SiC from fly ash, because the effective component α-SiO in fly ash has an inhibitory effect on high-temperature pyrolysis, and Al2O3 encapsulated in the glass does not form a low-melting-point liquid phase around α-SiO, resulting in a mass transfer barrier, it is necessary to thoroughly activate α-SiO and dispose of it in situ.

[0026] The fly ash is either high-silica fly ash or low-silica fly ash.

[0027] When the SiO content in fly ash is high (>2.5%), a two-step acid treatment is adopted: First, dilute sulfuric acid (10wt%) is used to dissolve amorphous SiO, and the insoluble part is activated with oxalic acid (5wt%).

[0028] The second step involves adding ammonium citrate solution to inhibit the formation of Al(SiO) precipitate, while simultaneously complexing alkali metal ions and raising the pH to 7-8, thereby achieving complete activation of amorphous SiO and α-SiO.

[0029] When the SiO content in fly ash is low (<1.5%), a single acidic solution, ammonium citrate solution, is used to suppress the molten Al2O3 and avoid a decrease in reducing power.

[0030] The two-step acid treatment is carried out sequentially through pipelines into a container where ultrasonic waves are added for ultrasonic mechanochemical treatment.

[0031] The ultrasonic mechanochemical treatment conditions are: power 300~550W, time 0.5~24h.

[0032] Preferably, the power is 350~450W and the time is 12h.

[0033] Step 2: Reinforce learning dynamic temperature control restoration.

[0034] By optimizing process parameters through gradient carbothermal reduction temperature and deep learning algorithms, the excess carbon and aluminum elements from in-situ reactions can be maximized.

[0035] The reinforcement learning dynamic temperature control restoration monitors the temperature gradient distribution through a temperature sensor installed inside the heating furnace, and adjusts the heating rate by opening or closing the inner insulation cover of the heating furnace to achieve precise temperature control.

[0036] Specifically, this means: constructing a temperature decision model through the Deep Deterministic Policy Gradient (DDPG) algorithm to accurately predict the temperature state and its changing trend at different times, and formulating a scientific and reasonable heating plan; for situations with extreme temperatures, prioritizing the introduction of argon gas to rapidly cool down to the specified temperature range; and adopting a three-layer protection mode for temperature monitoring and reduction processes: the outer protective atmosphere of the heating furnace is inert argon gas, the middle heat insulation layer is an alumina hollow layer castable, and the inner side is a high-temperature resistant stainless steel plate.

[0037] Preferably, the reducing atmosphere is an argon-hydrogen mixture with a volume ratio of 1:1; during the reduction process, a magnetic stirrer with a stirring speed of 80 r / min is used to stir the material at a uniform speed.

[0038] The reduction temperature range for the above process is 1250~1450°C, and the heating rate is 4~8°C / min.

[0039] like Figure 2 As shown, the three-layer heating furnace includes an argon protective layer a1, an alumina insulation layer a2, a stainless steel reaction chamber a3, a heating element a4, temperature sensors a5, 6, and 7, a piezoelectric vibrator array a8, a spray gun inlet a9, a high-speed stirrer a10, a pressure relief valve a11, temperature probes a12, 13, and 14, and a material outlet a15. The temperature monitoring and reduction process shown exhibits a stepped increase in temperature, with several isothermal sections.

[0040] Step 3: In-situ resource utilization of Al2O3: Excess Al2O3 in the low-silicon phase is converted into a functional carrier.

[0041] Based on the above two steps, an appropriate amount of magnesium salt (MgClMgSO·7H2O) is added to induce the formation of magnesium aluminum spinel (MgAl), which serves as the growth matrix for SiC whiskers.

[0042] Specifically, this refers to thoroughly mixing the powdered base material and magnesium salt in a solid mixing homogenizer, transferring it to an alumina crucible, and preheating it in a furnace to 400~600°C.

[0043] Furthermore, the amount of magnesium salt added is 3% to 6% of the base.

[0044] Preferably, the mol ratio of MgO:Al2O3:MgO is 1:2:1.

[0045] It is understood that the above embodiments are merely exemplary implementations used to illustrate the principles of the present invention, and the present invention is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A method for preparing high-purity SiC by adaptive synergistic conversion of fly ash silica-alumina ratio fluctuation, characterized in that, The method includes the following steps: Step 1: Differentiated acid etching technology for silicon-aluminum separation: Differentiated acid treatment is applied to high-silicon and low-silicon fly ash to efficiently separate the silicon-aluminum components in fly ash using an acid activation-ultrasonic mechanochemical coupling method. Step 2: Construct a temperature decision model using a deep deterministic strategy gradient algorithm for precise temperature control: Establish a temperature decision model and optimize the heating path and holding time based on the deep deterministic strategy gradient algorithm; Step 3: In-situ resource utilization of excess Al2O3 in the low-silicon phase to prepare high-performance SiC: The excess Al2O3 in the low-silicon phase is converted into a functional carrier that can be used to prepare composite materials through in-situ chemical reaction.

2. The method for preparing high-purity SiC by adaptive synergistic conversion of fly ash silica-alumina ratio fluctuation according to claim 1, characterized in that, In step 1, the differentiated acid etching refers to the following: high-silica fly ash is treated with a two-step acid process, in which dilute sulfuric acid and oxalic acid are used sequentially to dissolve SiO and Al2O3 in the fly ash; low-silica fly ash is treated with citric acid, which uses citric acid to complex Al in the fly ash to form a soluble complex, thereby blocking the reaction between the acid and the fly ash and achieving etching.

3. The method for preparing high-purity SiC by adaptive synergistic conversion of fly ash silica-alumina ratio fluctuation according to claim 1, characterized in that, In step 1, a uniformly mixed micron-sized composite slurry is obtained after ultrasonic mechanochemical treatment.

4. The method for preparing high-purity SiC by adaptive synergistic conversion of fly ash silica-alumina ratio fluctuation according to any one of claims 1 to 3, characterized in that, In step 1, the two-step acid treatment refers to the following steps: first, dissolving SiO in fly ash with dilute sulfuric acid; second, selectively activating Al2O3 in fly ash with oxalic acid.

5. The method for preparing high-purity SiC by adaptive synergistic conversion of fly ash silica-alumina ratio fluctuation according to any one of claims 1 to 3, characterized in that, In step 2, the temperature decision model constructed by the deep deterministic policy gradient algorithm refers to: constructing a temperature decision model based on the deep deterministic policy gradient algorithm, starting from the initial temperature point T and ending at the final temperature point T, dividing the temperature into N equal temperature intervals, setting the width ΔT for each temperature interval, and obtaining a series of temperature sequences T={T, T, ..., T}; selecting a sample point T in each temperature interval as the representative temperature point of that interval, obtaining a temperature sequence T={T, T, ..., T}, sorting the sample points according to the difference between the temperature of each sample point and the ideal temperature, and calculating the update rate v; after optimizing the temperature interval, continuing to optimize adjacent temperature intervals until all temperature intervals meet the accuracy requirements.

6. The method for preparing high-purity SiC by adaptive synergistic conversion of fly ash silica-alumina ratio fluctuation according to any one of claims 1 to 3, characterized in that, In step 2, the temperature decision model includes input parameters and output parameters; wherein, the input parameters include: real-time silicon-to-aluminum ratio, carbon-to-silicon ratio, and material thermal conductivity; and the output parameters include: dynamically adjusting the reduction temperature range and heating rate.

7. The method for preparing high-purity SiC by adaptive synergistic conversion of fly ash silica-alumina ratio fluctuation according to any one of claims 1 to 3, characterized in that, In step 3, the in-situ chemical reaction refers to promoting the growth of β-SiC crystals in an alkaline melt environment while inducing the formation of magnesium aluminum spinel.

8. The method for preparing high-purity SiC by adaptive synergistic conversion of fly ash silica-alumina ratio fluctuation according to any one of claims 1 to 3, characterized in that, In step 3, the functional carrier used to prepare the composite material refers to a magnesium aluminum spinel phase with high strength and high fire resistance.

9. The method for preparing high-purity SiC by adaptive synergistic conversion of fly ash silica-alumina ratio fluctuation according to any one of claims 1 to 3, characterized in that, In step 3, after in-situ chemical reaction, a multiphase product with prismatic a-SiC (hexagonal silicon nitride) as the main component is obtained.

10. A system for the adaptive synergistic conversion of fly ash silica-alumina ratio fluctuations to prepare high-purity SiC, characterized in that, The system includes: The system comprises an information acquisition module, a computation and decision-making module, and an execution operation module; the information acquisition module and the computation and decision-making module transmit signals bidirectionally; the computation and decision-making module includes a data history storage unit, a neural network weight coefficient correction unit, and a gradient descent operator; the execution operation module includes a temperature control device, a spray gun, and a high-speed stirrer. The information acquisition module probes detect the furnace temperature, carbon-silicon ratio, and simulated atmosphere in real time. The data history storage unit records the detection values ​​at different times; The neural network weight coefficient correction unit updates the network weight coefficients to optimize the heating path; The gradient descent operator continuously updates the temperature control command for the next time step; The temperature control device maintains the furnace temperature within a specific range; The spray gun and high-speed mixer receive instructions from the calculation and decision module and spray the reducing agent onto the surface of the fly ash.

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