Graphite processing method and device based on digital twinning and high-entropy molten salt self-adaptation

Abstract

The application provides a graphite processing method and device based on digital twinning and high-entropy molten salt self-adaptation, comprising: performing rapid online detection on a graphite raw material to be processed to obtain raw material key parameters; inputting the raw material key parameters into a pre-constructed digital twinning of a graphite purification and spheroidization process to obtain control parameters required by the graphite purification and spheroidization process; and using the control parameters to control an automatic batching system, a program temperature-controlled dynamic reactor, a high-pressure cavitation generator and a multi-stage shearing mechanism, and a multi-modal flow field collaborative spheroidization reactor to perform integrated purification and spheroidization processing on the graphite raw material to be processed. The application can integrate process digital simulation, adaptive chemical systems and physical field strengthening technology to complete the integrated intelligent purification and spheroidization of graphite materials.

Description

Technical Field

[0001] This application relates to the field of deep processing of graphite materials, specifically a graphite processing method and apparatus based on digital twin and high-entropy molten salt adaptive processing. Background Technology

[0002] High-purity spherical graphite is a core raw material for lithium-ion battery anodes and high-end conductive materials. Its purity (usually requiring fixed carbon ≥99.95%) and morphology (high sphericity and narrow particle size distribution) jointly determine the performance of the final product. Existing graphite purification and spheroidization technologies have many bottlenecks, making it difficult to balance efficiency, quality, cost, and environmental protection.

[0003] In terms of purification, mainstream technologies each have their limitations: chemical methods (such as the alkali-acid method and the hydrofluoric acid method) achieve high purity, but the process is complex, generates a large amount of corrosive waste liquid, and poses a significant environmental pollution risk (see the background technology in CN120793920A); high-temperature chlorination or fluorination methods (such as CN120208222A) have extremely high energy consumption (>2500℃), demanding equipment requirements, and pose safety and residual impurity risks; physical flotation methods (such as CN120381929A and CN120421108A) are relatively environmentally friendly, but have low recovery rates for fine-grained or cryptocrystalline graphite, making it difficult to break through the 99.9% purity bottleneck, and cannot change the graphite morphology. Regarding spheroidization, separate mechanical grinding and shaping processes are usually required after purification. This process is energy-intensive, has low yield, and easily introduces new impurities or excessively damages the graphite crystal structure.

[0004] In recent years, some studies have attempted to optimize or combine existing processes. For example, existing technologies have tried to introduce Bayesian optimization to construct scenario template libraries to stabilize gradient density separation processes, but their optimization is based on historical data and lacks online adaptive capability to drastic fluctuations in raw material composition. Other existing technologies have attempted to use Fenton reaction and cavitation technology, reflecting a green and integrated approach, but the former faces challenges in achieving the required purity and the latter in terms of process stability. Purification of specific impurities (such as silicon carbide) has also shown a lack of process universality.

[0005] In summary, existing technologies generally suffer from the following core pain points: 1) Rigid processes: Fixed processes cannot respond in real time to dynamic changes in the types and contents of impurities in raw materials, resulting in poor product consistency; 2) Fragmented processes: Purification and spheroidization are mostly independent units in series, resulting in long processes, high total energy consumption, and large material losses; 3) Extensive chemical processes: Relying on high-temperature or highly corrosive reagents, the reaction selectivity is poor, which can easily lead to over-reaction or the generation of difficult-to-handle byproducts; 4) Lack of system intelligence: Highly dependent on the experience of operators, making it impossible to achieve closed-loop optimization control based on real-time feedback.

[0006] Therefore, developing a next-generation graphite deep processing technology that can intelligently sense raw material differences, adaptively adjust processes, and integrate deep purification and precision spheroidization in a clean and efficient manner has become an urgent need for the industry.

[0007] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section. Summary of the Invention

[0008] To address the problems in the existing technology, this application provides a graphite processing method and apparatus based on digital twin and high-entropy molten salt adaptive technology, which can integrate process digital simulation, adaptive chemical system and physical field enhancement technology to complete the integrated intelligent purification and spheroidization of graphite materials.

[0009] To solve the above-mentioned technical problems, this application provides the following technical solution: In a first aspect, this application provides a graphite processing method based on digital twin and high-entropy molten salt adaptive processing, comprising: Rapid online detection of the graphite raw material to be processed yields key parameters of the raw material; The key parameters of the raw materials are input into a pre-constructed digital twin of the graphite purification and spheroidization process to obtain the control parameters required for the graphite purification and spheroidization process; wherein, the digital twin of the graphite purification and spheroidization process is obtained based on multi-physics simulation of the parameters of the graphite raw materials to be processed during the processing. The control parameters are used to control an automatic batching system, a programmable temperature-controlled dynamic reactor, a high-pressure cavitation generator and a multi-stage shearing mechanism, and a multi-modal flow field synergistic spheroidizing reactor to perform integrated purification and spheroidization processing of the graphite raw material to be processed.

[0010] Furthermore, the digital twin of the graphite purification and spheroidization process includes a data perception layer, a decision optimization layer, an execution control layer, and a feedback calibration layer; the step of pre-constructing the digital twin of the graphite purification and spheroidization process includes: The processing parameters of the graphite raw material to be tested are collected in real time to generate the data sensing layer; The decision optimization layer is generated based on the process optimization instructions obtained from multiphysics simulation of the processing parameters. The execution control layer is constructed by issuing the process optimization instructions to the automatic batching system, the program-controlled temperature dynamic reactor, the high-pressure cavitation generator and multi-stage shearing mechanism, and the multi-modal flow field collaborative spherical reactor. The feedback calibration layer is constructed by comparing the actual values ​​of graphite finished product parameters collected by sensors during the processing with the simulated predicted values ​​of graphite finished product parameters.

[0011] Furthermore, the control parameters include a high-entropy composite molten salt formulation, dynamic reaction curve, cavitation shear parameters, and spheroidization parameters; the process of inputting the key raw material parameters into a pre-constructed digital twin of the graphite purification and spheroidization process to obtain the control parameters required for the graphite purification and spheroidization process includes: The key parameters of the raw materials are input into the data sensing layer to obtain the corresponding processing parameters; The processing parameters are input into the thermodynamic model, reaction kinetic model, fluid kinetics and mass transfer model, and particle morphology evolution model in the decision optimization layer to obtain the high-entropy composite molten salt formulation, dynamic reaction curve, cavitation shear parameters, and spheroidization parameters. The high-entropy composite molten salt formulation, dynamic reaction curve, cavitation shear parameters, and spheroidization parameters are input into the feedback calibration layer for calibration to obtain the control parameters.

[0012] Further, the step of inputting the processing parameters into the thermodynamic model, reaction kinetic model, fluid kinetics and mass transfer model, and particle morphology evolution model in the decision optimization layer to obtain the high-entropy composite molten salt formulation, dynamic reaction curve, cavitation shear parameters, and spheroidization parameters includes: The activity, phase transition boundary, and reaction driving force of each component in the high-entropy composite molten salt are predicted using the processing parameters, the thermodynamic model, and the reaction kinetic model, thereby obtaining the high-entropy composite molten salt formulation; wherein, the high-entropy composite molten salt formulation is generated based on the activity, phase transition boundary, and reaction driving force of each component. The concentration field, velocity field, and interfacial mass transfer rate at different time steps are calculated using the processing parameters and the fluid dynamics and mass transfer model to obtain the dynamic response curve; wherein the dynamic response curve is plotted based on the concentration field, velocity field, and interfacial mass transfer rate. The cavitation shear parameters are determined using the processing parameters and the fluid dynamics and mass transfer model. The surface tension, cooling rate, and collision frequency of the graphite raw material during the spheroidization process are simulated using the processing parameters and the particle morphology evolution model to obtain the spheroidization parameters; wherein the spheroidization parameters are determined based on the surface tension, cooling rate, and collision frequency.

[0013] Furthermore, the method of controlling the automatic batching system, the programmable temperature-controlled dynamic reactor, the high-pressure cavitation generator and multi-stage shearing mechanism, and the multi-modal flow field synergistic spherical reactor using the control parameters includes: The calibrated high-entropy composite molten salt formula is sent to the automatic batching system to control the automatic batching system to prepare high-entropy composite molten salt based on the high-entropy composite molten salt formula; The calibrated dynamic reaction curve is sent to the programmed temperature-controlled dynamic reactor to control the programmable temperature-controlled dynamic reactor to purify the mixture of the graphite raw material to be processed and the high-entropy composite molten salt to obtain the first intermediate slurry. The calibrated cavitation shear parameters are sent to the high-pressure cavitation generator and the multi-stage shearing mechanism to control the high-pressure cavitation generator and the multi-stage shearing mechanism to purify the first intermediate slurry and obtain the second intermediate slurry. The calibrated spheroidization parameters are sent to the multimodal flow field collaborative spheroidization reactor to control the reactor to spheroidize the second intermediate slurry, thereby obtaining the finished graphite product. The spheroidization parameters include purity, sphericity, tap density, and particle size distribution.

[0014] Furthermore, the graphite processing method based on digital twin and high-entropy molten salt adaptive processing also includes: Real-time data on temperature, pressure, atmosphere composition, dielectric conductivity, viscosity and morphology of the graphite raw material to be processed during the purification and spheroidization process are collected. The temperature, pressure, atmosphere composition, dielectric conductivity, viscosity and morphology data are synchronized in real time to the digital twin of the graphite purification and spheroidization process, and the decision optimization layer is dynamically calibrated using twin assimilation technology.

[0015] Secondly, this application provides a graphite processing apparatus based on digital twin and high-entropy molten salt adaptive technology, comprising: The key parameter detection unit is used to perform rapid online detection of the graphite raw materials to be processed, and obtain the key parameters of the raw materials; The control parameter generation unit is used to input the key parameters of the raw material into a pre-constructed digital twin of the graphite purification and spheroidization process to obtain the control parameters required for the graphite purification and spheroidization process; wherein, the digital twin of the graphite purification and spheroidization process is obtained based on multi-physics simulation of the parameters of the graphite raw material to be processed during the processing. The control processing unit is used to control the automatic batching system, the programmable temperature-controlled dynamic reactor, the high-pressure cavitation generator and the multi-stage shearing mechanism, and the multi-modal flow field synergistic spheroidizing reactor using the control parameters to perform integrated purification and spheroidization processing on the graphite raw material to be processed.

[0016] Thirdly, this application provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the graphite processing method based on digital twin and high-entropy molten salt adaptation.

[0017] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the graphite processing method based on digital twin and high-entropy molten salt adaptation.

[0018] Fifthly, this application provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the graphite processing method based on digital twin and high-entropy molten salt adaptation.

[0019] To address the problems in existing technologies, the graphite processing method and apparatus based on digital twins and high-entropy molten salt adaptive processing provided in this application can form a set of efficient, clean, intelligent and integrated graphite deep processing solutions through intelligent decision-making driven by digital twins, broad-spectrum adaptive chemical treatment of high-entropy molten salt, and physical morphology control in cavitation-flow field coordination. It shows significant advantages in product quality, production efficiency, energy consumption and environmental protection, and has extremely high industrialization and technology promotion value. Attached Figure Description

[0020] 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.

[0021] Figure 1 This is a flowchart of the graphite processing method based on digital twin and high-entropy molten salt adaptive method in the embodiments of this application; Figure 2 This is a flowchart illustrating the construction of a digital twin of the graphite purification and spheroidization process in this embodiment of the application. Figure 3 This is a flowchart illustrating the control parameters required for the graphite purification and spheroidization process in the embodiments of this application. Figure 4 This is a flowchart illustrating the high-entropy composite molten salt formulation, dynamic reaction curve, cavitation shear parameters, and spheroidization parameters obtained in the embodiments of this application. Figure 5 The flowcharts for controlling the automatic batching system, the programmable temperature-controlled dynamic reactor, the high-pressure cavitation generator and the multi-stage shearing mechanism, and the multi-modal flow field synergistic spherical reactor in the embodiments of this application are shown below. Figure 6 This is a flowchart illustrating the dynamic calibration of the decision optimization layer using twin assimilation technology in an embodiment of this application. Figure 7 This is a structural diagram of the graphite processing apparatus based on digital twin and high-entropy molten salt adaptive technology in the embodiments of this application; Figure 8 This is a flowchart illustrating the overall process and closed-loop control of the method and system in the embodiments of this application. Figure 9 This is a schematic diagram comparing the melting point of the quaternary "high-entropy composite molten salt" system and two traditional binary salt systems in the embodiments of this application, as well as their ability to remove typical impurities (SiO2, Al2O3, Fe2O3, SiC). Figure 10 This is a schematic diagram of the internal structure of the "multimodal flow field synergistic spheroidization reactor" in the embodiments of this application; Figure 11 The radar comparison charts in this application, showing the processing of two different raw materials using the method provided in this application, and the traditional two-step alkaline-acid method + mechanical spheroidization method, show the differences in "product purity", "product sphericity", "unit product energy consumption" and "process time". Figure 12 This is a schematic diagram of the structure of the electronic device in the embodiments of this application. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0023] The information collected in the technical solution of this application is information and data authorized by the user or fully authorized by all parties. The collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data all comply with the relevant laws, regulations and standards of the relevant countries and regions, necessary confidentiality measures have been taken, and they do not violate public order and good morals. Corresponding operation portals are provided for users to choose to authorize or refuse.

[0024] Provide users with corresponding operation entry points, allowing them to choose to agree to or reject the automated decision results; if the user chooses to reject, the process will proceed to the expert decision-making process.

[0025] In one embodiment, see Figure 1 To integrate digital process simulation, adaptive chemical systems, and physical field enhancement technologies to achieve integrated intelligent purification and spheroidization of graphite materials, this application provides a graphite processing method based on digital twins and high-entropy molten salt adaptation, comprising: S101: Perform rapid online detection on the graphite raw material to be processed to obtain key parameters of the raw material; S102: Input the key parameters of the raw material into a pre-constructed digital twin of the graphite purification and spheroidization process to obtain the control parameters required for the graphite purification and spheroidization process; wherein, the digital twin of the graphite purification and spheroidization process is obtained based on multi-physics simulation of the parameters of the graphite raw material to be processed during the processing. S103: Using the control parameters, control the automatic batching system, the programmable temperature-controlled dynamic reactor, the high-pressure cavitation generator and the multi-stage shearing mechanism, and the multi-modal flow field synergistic spheroidizing reactor to perform integrated purification and spheroidization processing of the graphite raw material to be processed.

[0026] Understandably, the method provided in this application overcomes the shortcomings of existing graphite purification and spheroidization technologies, such as rigid process flow, poor coordination of various processes, high energy consumption, environmental unfriendliness, and large fluctuations in product quality. It provides a closed-loop integrated method and system with online sensing, intelligent decision-making, and precise execution capabilities.

[0027] Specifically, see Figure 8 An integrated method for graphite purification and spheroidization based on digital twins and high-entropy molten salt adaptation includes the following steps: S1. Digital Characterization of Raw Materials and Initialization of the Digital Twin: Rapid online detection is performed on the graphite raw materials to be processed to obtain their key parameters, including but not limited to: multi-element composition (via online XRF), fixed carbon content, particle size distribution, specific surface area, and crystal structure information. The detection data is used as initial boundary conditions and input into a pre-constructed digital twin of the graphite purification-spheroidization process. This digital twin is a multi-physics coupled simulation model integrating thermodynamic calculations, computational fluid dynamics (CFD), and chemical reaction dynamics, capable of simulating the entire process from molten salt reaction to fluid shear shaping with high fidelity.

[0028] S2. Online Optimization of High-Entropy Composite Molten Salt Formulation: Based on the raw material "digital profile" input in S1, the digital twin performs multi-objective optimization calculations from the high-entropy molten salt component library, combined with the built-in material thermodynamics database and reaction kinetics model, to generate the optimal molten salt formulation and expected reaction path for the current batch of raw materials. The high-entropy molten salt component library includes chlorides, fluorides, carbonates of various alkali metals (Li, Na, K) and alkaline earth metals (Ca, Mg), as well as a small amount of additives. The "high-entropy" principle refers to the close molar ratio of the main components (≥4 types) in the formulation (e.g., between 0.8:1 and 1.2:1). The resulting multi-component eutectic system has a lower melting point, a wider liquid phase region, higher thermal stability, and universal chemical dissolution and complexation ability for various impurity oxides / carbides compared to single or binary salts.

[0029] S3. Dynamic program temperature control reaction: Based on the optimized molten salt formula output by the digital twin, the high-entropy composite molten salt is precisely prepared by the automatic batching system.

[0030] S4. Cavitation-Enhanced Rapid Cooling Washing and Initial Morphological Shaping: After the thermochemical reaction is completed, the reactants are rapidly transferred to an integrated cavitation washing unit, where they are rapidly cooled. Subsequently, a measured amount of washing medium (such as deionized water, low-concentration acid, or recyclable washing liquid) is injected into the unit, and the high-pressure cavitation generator and multi-stage shearing mechanism are activated.

[0031] S5. Full-Process Data Sensing and Real-Time Twin Calibration: At key workstations S3 and S4, a dense network of online sensors is deployed to collect real-time data on temperature, pressure, atmosphere composition, dielectric conductivity, viscosity, and morphology based on an online particle image analyzer (PIA). This massive amount of process data is synchronized to the digital twin in real time. The twin uses data assimilation technology to compare simulated predictions with actual measurements, dynamically calibrating model parameters (such as reaction rate constants and mass transfer coefficients) to ensure that the virtual model and the physical process remain highly synchronized and accurately mapped.

[0032] S6. Quality Closed-Loop Feedback and Process Self-Optimization: Rapid online quality inspection of the graphite slurry produced in S4 is performed, and the entire process data is fed back to the optimization engine of the digital twin. This engine can perform reverse simulation and optimization.

[0033] S7. Multimodal flow field refinement and spheroidization: After adjusting the concentration of the intermediate product slurry obtained in S4, it is pumped into the multimodal flow field synergistic spheroidization reactor (see...). Figure 10The reactor is a vertical cylindrical structure, consisting of three sections—lower, middle, and upper—connected by flanges. Internally, it is divided into three functional zones from bottom to top: a turbulent disturbance zone, a laminar shear zone, and a cavitation stabilization zone. The lower section houses an agitator assembly and a guide tube. The agitator shaft 2 passes through the top cover and is driven by a motor. The impeller 1 is fixed to the shaft end. The guide tube 3 is fixed to the cylinder wall by support rods and has guide holes at the bottom. The cylinder wall also has baffles. By generating high-intensity turbulence, it breaks up particle agglomerates, ensuring uniform suspension of the slurry. The interior of the middle section of the cylinder forms a laminar shear zone. The core components are the shear rotor and the shear stator 5. The shear stator is a concentric sleeve structure, fixed by a stator mounting ring welded to the inner wall of the middle section cylinder. The shear rotor is cylindrical and located inside the stator, with an annular gap between them. The rotor surface is machined with helical grooves, and the inner surface of the stator is machined with reverse helical grooves. The upper journal of the shear rotor is supported by a bearing seat at the top of the middle section cylinder, and the lower journal passes through the central hole of the annular partition located between the middle and lower section flanges. It is connected to the rotor of the magnetic coupler and driven by an independent motor 6 to achieve contactless transmission. A controllable laminar shear field is generated by the concentric sleeve shear rotor and stator ring to "curl" and "round" the edges of the particles. The upper section of the reactor houses a cavitation generator array 7. Each array includes a liquid intake pipe, a booster pump, an orifice plate assembly, and a return pipe. The liquid intake pipe draws liquid from the upper middle section, which is then pressurized and passes through the orifice plate to generate a cavitation effect. The liquid then returns to the guide hood near the top cover via the return pipe. A well-arranged hydraulic cavitation generator array produces a gentle cavitation effect, smoothing the micro-protrusions on the particle surface and stabilizing the spherical morphology. A feed inlet 4 is located at the center of the bottom of the reactor, and a discharge outlet 9 is located on the top side wall. An online density meter and a replenishment port are installed on the feed pipe, and a sampling branch pipe connected to an online particle image analyzer 8 is located before the discharge outlet. After entering through the bottom feed inlet, the slurry forms an upward circulating flow under the action of the agitator, sequentially passing through three functional zones and circulating multiple times in each zone until the particle morphology meets the requirements, at which point it is discharged from the top discharge outlet. The digital twin dynamically adjusts the intensity, duration, and switching sequence of each flow field based on real-time morphology feedback (such as aspect ratio and sphericity) obtained online from the reactor outlet, to finely "shape" and "polish" the graphite particles, ultimately obtaining high-quality spherical graphite products with a fixed carbon content ≥99.95%, sphericity ≥90%, and concentrated particle size distribution (D90 / D10≤3).

[0034] To achieve the above method, this application also provides a corresponding intelligent system, including: a raw material rapid online analysis module; a central control and computing platform, which embeds a digital twin model of the graphite purification-spheroidization process, a high-entropy molten salt formulation optimization algorithm, and an adaptive control algorithm; a high-precision adaptive batching and mixing module; a programmable temperature-controlled dynamic reactor equipped with a precise atmosphere and temperature control system; an integrated cavitation scrubbing and primary plasticizing unit, integrating a high-pressure cavitation generator, a multi-stage shear, and a rapid heat exchanger; and a multi-modal flow field collaborative spheroidization refinement reactor. A sensor network for online monitoring of process parameters distributed throughout all units; a module for rapid online detection of product quality indicators; Industrial data bus and actuator network enable real-time, closed-loop transmission and linkage of data flow and control flow throughout the system.

[0035] Preferably, in the high-entropy molten salt component library, the formulation for treating impurities mainly composed of silicon and aluminum oxides preferably contains at least three of NaF, KF, Na2CO3, and Li2CO3; the formulation for treating impurities containing silicon carbide (SiC) preferably contains Na2CO3, K2CO3, and a fluoride (such as NaF or CaF2).

[0036] Preferably, the digital twin employs a hybrid modeling method based on mechanism and data-driven approaches, and utilizes machine learning algorithms to learn and update reaction kinetic parameters online. Preferably, in the cavitation scrubbing unit, the cavitation generator operates at a pressure range of 5-30 MPa, with a cavitation frequency of 20-100 kHz, and the shearing mechanism has a linear velocity range of 5-50 m / s. Preferably, the control system supports the transfer and optimization of process parameters across batches in multi-batch continuous production.

[0037] As can be seen from the above description, the graphite processing method based on digital twin and high-entropy molten salt adaptive processing provided in this application can form a set of efficient, clean, intelligent and integrated graphite deep processing solutions through intelligent decision-making driven by digital twin, broad-spectrum adaptive chemical processing of high-entropy molten salt, and physical morphology control in cavitation-flow field coordination. It shows significant advantages in product quality, production efficiency, energy consumption and environmental protection, and has extremely high industrialization and technology promotion value.

[0038] In one embodiment, see Figure 2 The digital twin of the graphite purification and spheroidization process includes a data perception layer, a decision optimization layer, an execution control layer, and a feedback calibration layer; the step of pre-constructing the digital twin of the graphite purification and spheroidization process includes: S201: Real-time acquisition of processing parameters of the graphite raw material to be tested, generating the data sensing layer; S202: Generate the decision optimization layer based on the process optimization instructions obtained from multiphysics simulation of the processing parameters; S203: The execution control layer is constructed by issuing the process optimization instructions to the automatic batching system, the program-controlled temperature dynamic reactor, the high-pressure cavitation generator and multi-stage shearing mechanism, and the multi-modal flow field collaborative spherical reactor; S204: The feedback calibration layer is constructed by comparing the actual values ​​of graphite finished product parameters collected by sensors during the processing with the simulated predicted values ​​of graphite finished product parameters.

[0039] It is understood that the control process of the method provided in this application is centered on a digital twin, constructing a closed loop of "perception-simulation-decision-execution-feedback", with the specific levels as follows: 1. Data Sensing Layer: 1.1 Online raw material detection; 1.2 Real-time acquisition of process parameters; 1.3 Rapid product quality detection.

[0040] 2. Decision optimization layer: 2.1 Digital twin simulation prediction; 2.2 Molten salt formulation optimization; 2.3 Dynamic process curve generation; 2.4 Flow field parameter optimization.

[0041] 3. Execution control layer: 3.1 Batching and mixing control; 3.2 Reaction temperature and atmosphere control; 3.3 Cavitation scrubbing control; 3.4 Flow field refinement control.

[0042] 4. Feedback Calibration Layer: 4.1 Data Synchronization and Comparison; 4.2 Online Calibration of Model Parameters; 4.3 Closed-Loop Correction of Process Instructions.

[0043] The functions of each layer are as follows: 1. Data Sensing Layer: This includes online raw material detection, real-time acquisition of process parameters (temperature, pressure, conductivity, images, etc.), and rapid product quality detection.

[0044] 2. Decision Optimization Layer: The digital twin performs multiphysics simulation based on real-time data and outputs an optimized set of process parameter instructions, including molten salt formulation, reaction temperature curve, cavitation parameters, shear rate, and flow field mode sequence.

[0045] 3. Execution Control Layer: The central control platform sends instructions to each execution unit (temperature controller, cavitation generator, shear motor, pump valve, etc.) through the industrial bus to achieve precise execution.

[0046] 4. Feedback calibration layer: During execution, the sensor continuously collects actual data and compares it with the simulation prediction value. If the deviation exceeds the threshold, it triggers online calibration of model parameters (such as updating the reaction rate constant and adjusting the mass transfer coefficient) and re-optimizes the process instructions to form a closed loop.

[0047] As can be seen from the above description, the graphite processing method based on digital twin and high-entropy molten salt adaptive provided in this application can pre-construct a digital twin of the graphite purification and spheroidization process.

[0048] In one embodiment, see Figure 3 The control parameters include high-entropy composite molten salt formulation, dynamic reaction curve, cavitation shear parameters, and spheroidization parameters; the key parameters of the raw materials are input into a pre-constructed digital twin of the graphite purification and spheroidization process to obtain the control parameters required for the graphite purification and spheroidization process, including: S301: Input the key parameters of the raw materials into the data sensing layer to obtain the corresponding processing parameters; S302: Input the processing parameters into the thermodynamic model, reaction kinetic model, fluid kinetics and mass transfer model, and particle morphology evolution model in the decision optimization layer to obtain the high-entropy composite molten salt formula, dynamic reaction curve, cavitation shear parameters, and spheroidization parameters; S303: Input the high-entropy composite molten salt formula, dynamic reaction curve, cavitation shear parameters and spheroidization parameters into the feedback calibration layer for calibration to obtain the control parameters.

[0049] The process of building a digital twin is understandable: (1) Overall architecture of the model.

[0050] The digital twin employs a multiphysics coupling modeling framework, including: Thermodynamic calculation module: Constructs phase diagrams for high-entropy molten salt systems based on the CALPHAD method, and predicts eutectic points, liquid phase regions, and precipitated phases; Computational Fluid Dynamics (CFD) module: Simulates the temperature, flow, and concentration field distributions within a reactor; Chemical reaction kinetics module: describes the dissolution, transformation, and removal of impurities in molten salt; Particle morphology evolution module: Based on the population equilibrium model (PBM) and discrete element method (DEM), the spheroidization process of graphite particles in shear and cavitation fields is simulated; The modules are bidirectionally coupled through shared boundary conditions and state variables to achieve integrated simulation of the entire process.

[0051] (2) Key sub-models and equations.

[0052] Thermodynamic model: The excess Gibbs free energy of the multi-component molten salt system is described using Redlich-Kister polynomials:

[0053] in, , The mole fraction of the component. v For the order of expansion, The interaction parameters were obtained by fitting experimental and literature data.

[0054] The dissolution reaction of impurity oxides (such as SiO2 and Al2O3) in molten salt is based on a molten salt basicity control model, and their dissolution behavior is predicted using optical basicity (Λ):

[0055] in, For solubility, All of these are temperature-related parameters.

[0056] Reaction kinetic model: The impurity removal process is considered as a combination of interfacial reaction control and mass transfer control, and is described using a shrinking core model:

[0057] in, X For conversion rate, Let be the apparent rate constant. A The reaction interface area, To balance the concentration, C This represents the actual concentration.

[0058] Apparent rate constant Expressed using the Arrhenius equation:

[0059] in, The reaction rate constant is... Pre-exponential factor, For activation energy, R is the ideal gas constant, and T is the absolute temperature, calibrated through thermogravimetric analysis and isothermal experiments.

[0060] Fluid dynamics and mass transfer models: The flow field inside the reactor is simulated using a k-ε turbulence model, coupling the energy equation and the component transport equation:

[0061] in, For fluid density, Speed ​​at i directional components, For time, u It is a velocity vector. For gradient operators, For pressure, For effective viscosity, The momentum source term includes the microjets effect caused by cavitation.

[0062] The mass transfer coefficient was estimated using the Sherwood number correlation:

[0063] in, For Sherwood number, ,in The mass transfer coefficient is . For characteristic length, Where is the diffusion coefficient. Re Let Reynolds number be 1. Sc The Schmitt number is used to couple reaction dynamics and flow field.

[0064] Particle morphology evolution model: The changes in particle size and shape distribution are described based on the population equilibrium equation:

[0065] in, n(L,t) Let be the particle number density function. G(L) For growth rate, B, D These are the reunion and breakup terms, respectively. L For particle feature size, t For time.

[0066] The "rolling" and "rounding" behaviors of particles during the spheroidization process are approximated by an equivalent plastic strain model, and spatiotemporal integration is performed by combining the shear rate field calculated by CFD.

[0067] (3) Model parameter system and calibration mechanism.

[0068] Parameter classification: 1. Physical constants: density, specific heat capacity, viscosity, etc., from databases or actual measurements.

[0069] Thermodynamic parameters: phase diagram interaction parameters and solubility coefficients, fitted through thermal analysis experiments.

[0070] Kinetic parameters: pre-exponential factor A 0. Activation energy E a Mass transfer coefficient k m It was obtained through intermittent experiments and online data inversion.

[0071] Equipment parameters: reactor geometry, stirring power, cavitation efficiency, etc., based on the equipment manual and actual measurement calibration.

[0072] 2. Online calibration process: The Extended Kalman Filter (EKF) is used for real-time estimation and parameter updates of key state variables (such as purity and granularity).

[0073] in, For a moment Updated parameter estimates, According to Time prediction Time parameter value, y k These are measured values. For observation models,K k For Kalman gain.

[0074] A deviation threshold triggering mechanism is established: when the relative error between the predicted value and the measured value continues to exceed 5%, the parameter recalibration program is automatically started.

[0075] 3. Machine learning-assisted modeling: For processes that are difficult to fully describe by mechanism (such as the microscopic effects of cavitation collapse on particle surfaces), Gaussian process regression (GPR) is used to establish a surrogate model of input (pressure, frequency) - output (morphological change):

[0076] in, For the output variable to be modeled, For the input vector, For Gaussian processes, It is a mean function, usually set to 0 or a constant. It is a covariance function (kernel function) used to capture local nonlinearity.

[0077] The proxy model and the mechanism model run in parallel, and the output results are weighted and fused to enhance the model's generalization ability.

[0078] Model validation and update strategies: 1. Offline verification stage: Historical production data and pilot-scale experimental data are used to compare simulated values ​​with measured values ​​to ensure that the prediction error of the model under typical working conditions is less than 8%.

[0079] 2. Online update mechanism: After each production batch is completed, the entire process data of that batch is automatically extracted, the model is incrementally trained, and the dynamic parameters and mass transfer coefficient are updated.

[0080] 3. Version Management: The digital twin supports multiple versions coexisting and can switch model versions according to raw material type or product specifications to achieve fine-grained matching of "one material, one model".

[0081] As can be seen from the above description, the graphite processing method based on digital twin and high-entropy molten salt adaptive provided in this application can input the key parameters of the raw materials into a pre-constructed digital twin of the graphite purification and spheroidization process to obtain the control parameters required for the graphite purification and spheroidization process.

[0082] In one embodiment, see Figure 4The step of inputting the processing parameters into the thermodynamic model, reaction kinetic model, fluid dynamics and mass transfer model, and particle morphology evolution model in the decision optimization layer to obtain the high-entropy composite molten salt formulation, dynamic reaction curve, cavitation shear parameters, and spheroidization parameters includes: using the processing parameters, the thermodynamic model, and the reaction kinetic model to predict the activity of each component, phase transition boundary, and reaction driving force of the high-entropy composite molten salt, to obtain the high-entropy composite molten salt formulation (S401); wherein, the high-entropy composite molten salt formulation is generated based on the activity of each component, phase transition boundary, and reaction driving force; using the processing parameters and the fluid dynamics and mass transfer ... predict the activity of each component, phase transition boundary, and reaction driving force of the high-entropy composite molten salt, to predict the activity of each component, phase transition boundary, and reaction driving force of the high-entropy composite molten salt, to predict the activity of each component, phase transition boundary, and reaction driving force of the high-entropy composite molten salt, to predict the activity of each component, phase transition boundary, and reaction driving force of the high-entropy composite molten salt, to predict the activity of each component, phase transition boundary, and reaction driving force of the high-entropy composite molten salt, to predict the activity of each component, phase transition boundary, and reaction driving force of the high-entropy composite molten salt, to predict the activity of each component, phase transition boundary, and reaction driving force of the high-entropy composite mol The dynamics and mass transfer model calculates the concentration field, velocity field, and interfacial mass transfer rate at different time steps to obtain the dynamic response curve (S402); wherein the dynamic response curve is plotted based on the concentration field, velocity field, and interfacial mass transfer rate; the cavitation shear parameters are determined using the processing parameters and the fluid dynamics and mass transfer model (S403); the surface tension, cooling rate, and collision frequency of the graphite raw material during spheroidization are simulated using the processing parameters and the particle morphology evolution model to obtain the spheroidization parameters (S404); wherein the spheroidization parameters are determined based on the surface tension, cooling rate, and collision frequency.

[0083] Understandably, the first step involves collaborative calculations using a combined thermodynamic and reaction kinetic model. Inputting processing parameters such as temperature, pressure, and initial material ratios, the phase diagram characteristics of the high-entropy molten salt system are predicted, including the eutectic point, liquidus region, and precipitated phase sequence. Simultaneously, the activity of each component, phase transition boundaries, and reaction driving forces are calculated to generate the optimal high-entropy composite molten salt formulation, ensuring high stability and low solidification tendency of the system under target operating conditions. Then, the dynamic reaction process is simulated based on fluid dynamics and mass transfer models. CFD methods are used to solve for the temperature, velocity, and concentration field distributions within the reactor, and an interfacial mass transfer model is combined to analyze component diffusion behavior and reaction rates at different time steps. This constructs a dynamic reaction curve that visually reflects the key impurity conversion pathways, reaction inflection points, and product accumulation trends, supporting intelligent determination of the reaction endpoint. Subsequently, shear conditions are optimized through flow field feature identification and cavitation modeling. Based on CFD simulations, the overlapping region of the low-pressure and high-shear zones was focused on to analyze the probability of cavitation bubble formation and collapse intensity. Combining turbulence and cavitation models, suitable operating parameters such as stirring speed and jet pressure were deduced, ultimately determining the cavitation shear parameters that effectively promote particle dispersion and surface activation. Finally, an integrated particle morphology evolution model was used to simulate the spheroidization process. The initial particle size distribution, surface state, and process cooling conditions of the graphite raw material were input into a PBM-DEM coupled model to simulate its morphological evolution in high-temperature molten salt under the influence of surface tension, cooling rate regulation, and interparticle collision frequency. Through multiple rounds of parameter scanning, the optimal combination of residence time, atomization pressure, and cooling gradient was output to form spheroidization parameters guiding the experiment.

[0084] As can be seen from the above description, the graphite processing method based on digital twin and high-entropy molten salt adaptive processing provided in this application can input the processing parameters into the thermodynamic model, reaction kinetic model, fluid dynamics and mass transfer model, and particle morphology evolution model in the decision optimization layer to obtain the high-entropy composite molten salt formulation, dynamic reaction curve, cavitation shear parameters, and spheroidization parameters.

[0085] In one embodiment, see Figure 5 The system that utilizes the control parameters to control the automatic batching system, the programmable temperature-controlled dynamic reactor, the high-pressure cavitation generator and multi-stage shearing mechanism, and the multi-modal flow field synergistic spherical reactor includes: S501: The calibrated high-entropy composite molten salt formula is sent to the automatic batching system to control the automatic batching system to prepare high-entropy composite molten salt based on the high-entropy composite molten salt formula; S502: The calibrated dynamic reaction curve is sent to the programmed temperature-controlled dynamic reactor to control the programmed temperature-controlled dynamic reactor to purify the mixture of the graphite raw material to be processed and the high-entropy composite molten salt to obtain the first intermediate slurry. S503: The calibrated cavitation shear parameters are sent to the high-pressure cavitation generator and the multi-stage shearing mechanism to control the high-pressure cavitation generator and the multi-stage shearing mechanism to purify the first intermediate slurry and obtain the second intermediate slurry. S504: The calibrated spheroidization parameters are sent to the multimodal flow field collaborative spheroidization reactor to control the multimodal flow field collaborative spheroidization reactor to spheroidize the second intermediate slurry to obtain the finished graphite product; wherein, the spheroidization parameters include purity, sphericity, tap density and particle size distribution.

[0086] Understandably, after inputting the graphite processing parameters into the multiphysics coupling model in the decision optimization layer, the phase diagram characteristics of the high-entropy molten salt system are first predicted using the CALPHAD method under given temperature, pressure, and material ratio conditions through collaborative calculations of thermodynamics and reaction kinetics models. These characteristics include the eutectic point, liquid phase region, and precipitated phase sequence. Simultaneously, the activity of each component, phase transition boundary, and reaction driving force are solved, thereby generating a high-entropy composite molten salt formulation with excellent thermal stability and low solidification risk. Subsequently, combined with fluid dynamics and mass transfer models, the spatiotemporal evolution of the temperature, velocity, and concentration fields within the reactor is simulated using CFD methods. The component diffusion behavior and interfacial mass transfer rate at different time steps are analyzed, thus plotting the impurity transformation path, reaction inflection point, and product accumulation trend. The dynamic response curve of the potential is obtained. Based on this, the focus is further on the low-pressure and high-shear regions in the flow field. A turbulence-cavitation coupling model is introduced to identify the cavitation bubble generation location and collapse intensity, and to inversely deduce suitable operating parameters such as stirring speed and injection pressure. The cavitation shear parameters that can effectively improve particle dispersibility and surface activation are determined. Finally, the initial particle size distribution, surface state and cooling conditions of graphite raw materials are input into the particle morphology evolution model. The PBM-DEM coupling method is combined to simulate its morphological evolution process under the combined action of surface tension, cooling rate and collision frequency in a high-temperature molten salt environment. The optimal residence time, atomization pressure and cooling gradient combination are obtained through parameter optimization scanning. Finally, the spheroidization parameters that guide the actual process are output, realizing the closed-loop optimization of the whole process from input parameters to material performance control.

[0087] Specifically, the implementation process of step S3 (dynamic temperature-controlled reaction) is as follows: Based on the optimized molten salt formula output by the digital twin, a high-entropy composite molten salt is precisely prepared by an automatic batching system. The graphite raw material and the prepared molten salt are uniformly mixed at an optimized mass ratio (e.g., 1:0.5~1:2) and placed in a temperature-controlled dynamic reactor. Under an inert or weakly reducing protective atmosphere, a non-isothermal dynamic reaction curve planned by the digital twin is executed. This curve includes multiple heating rates, holding temperatures, and time points, aiming to create optimal thermochemical conditions for different impurities (such as low-temperature removal of basic oxides, medium-temperature removal of aluminosilicates, and high-temperature treatment of refractory carbides), achieving gradient, selective conversion, and stripping of impurities.

[0088] The specific implementation process of the aforementioned step S4 (cavitation-enhanced rapid cooling washing and initial morphology shaping) is as follows: Cavitation-enhanced rapid cooling washing and initial morphology shaping: After the thermochemical reaction is completed, the reactants are rapidly transferred to an integrated cavitation washing unit and rapidly cooled within this unit. During the rapid cooling process, the molten salt solidifies and encapsulates or isolates the reacted impurities on the surface of the graphite particles. Subsequently, a quantitative washing medium (such as deionized water, low-concentration acid, or recyclable washing liquid) is injected into the unit, and the high-pressure cavitation generator and multi-stage shearing mechanism are activated. The extreme local high temperature and pressure and strong micro-jet generated by the collapse of cavitation bubbles, in synergy with the macroscopic shear flow field, achieve: a) efficient crushing and peeling of the solidified salt shell encapsulating the graphite, allowing the impurities to be fully exposed and dissolved in the washing medium; b) applying a strong mechanical-hydraulic "kneading" and "rolling" effect to the edges and corners of the dissociated graphite flakes, initiating the (preliminary) spheroidization process, and obtaining intermediate products of preliminary purification and coarse spheroidization.

[0089] The specific implementation process of step S7 (multimodal flow field refinement and spheroidization) is as follows: After adjusting the concentration of the intermediate product slurry obtained in S4, it is pumped into a multimodal flow field synergistic spheroidization reactor. This reactor has independently controllable turbulent disturbance zone, high-intensity laminar shear zone, and mild cavitation stabilization zone. Based on the real-time morphology feedback (such as aspect ratio and sphericity) obtained online from the reactor outlet, the digital twin dynamically adjusts the intensity, action time, and switching sequence of each flow field to finely "shape" and "polish" the graphite particles, ultimately obtaining a high-quality spherical graphite product with a fixed carbon content ≥99.95%, sphericity ≥90%, and concentrated particle size distribution (D90 / D10≤3).

[0090] As can be seen from the above description, the graphite processing method based on digital twin and high-entropy molten salt adaptive provided in this application can use the control parameters to control the automatic batching system, the programmable temperature-controlled dynamic reactor, the high-pressure cavitation generator and the multi-stage shearing mechanism, and the multi-modal flow field synergistic spherical reactor.

[0091] In one embodiment, see Figure 6The graphite processing method based on digital twin and high-entropy molten salt adaptive processing further includes: S601: Real-time acquisition of temperature, pressure, atmosphere composition, dielectric conductivity, viscosity and morphology data of the graphite raw material to be processed during the purification and spheroidization process; S602: The temperature, pressure, atmosphere composition, dielectric conductivity, viscosity and morphology data are synchronized in real time to the digital twin of the graphite purification and spheroidization process, and the decision optimization layer is dynamically calibrated using twin assimilation technology.

[0092] Understandably, the specific implementation process of the aforementioned step S5 (full-process data sensing and real-time calibration of the digital twin) is as follows: At the key workstations in steps S3 and S4, a dense network of online sensors is deployed to collect real-time data on temperature, pressure, atmosphere composition, dielectric conductivity, viscosity, and morphology based on an online particle image analyzer (PIA). This massive amount of process data is synchronized to the digital twin in real time. The twin uses data assimilation technology to compare the simulated predicted values ​​with the actual measured values, dynamically calibrating model parameters (such as reaction rate constant and mass transfer coefficient) to ensure that the virtual model and the physical entity process always maintain a high degree of synchronization and accurate mapping.

[0093] The specific implementation process of step S6 (quality closed-loop feedback and process self-optimization) is as follows: Rapid online quality detection is performed on the graphite slurry produced in S4. Key indicators include fixed carbon content (inferred through rapid ignition weight loss or online spectroscopy) and particle roundness (through online image analysis). The detection results are compared with preset target values, and the resulting deviation signal, along with the calibrated full-process data, is fed back to the optimization engine of the digital twin. This engine can perform reverse simulation and optimization to determine whether adjustments to the molten salt formulation, dynamic reaction curve, or cavitation-shear parameters are needed for subsequent production batches (or the next adjustment cycle of the same continuous system), thus forming a global closed-loop optimization of "perception-simulation-decision-execution-re-perception".

[0094] As can be seen from the above description, the graphite processing method based on digital twin and high-entropy molten salt adaptive technology provided in this application can dynamically calibrate the decision optimization layer using twin assimilation technology.

[0095] The following is combined with Figure 9 , Figure 10 , Figure 11 The present invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0096] Example 1: Processing low-grade flake graphite ore.

[0097] Raw material: flake graphite from a certain region, with a fixed carbon content of 85.3% and main impurities of SiO2 (7.1%), Al2O3 (3.8%), Fe2O3 (2.5%), and CaO (0.8%).

[0098] Implementation steps: S1: The online detection system acquires raw material composition data and transmits it to the digital twin.

[0099] S2: Twin optimization calculation, recommended high-entropy molten salt formulation: LiCl:NaF:K2CO3:CaF2 (molar ratio 1.0:1.1:0.9:0.8). Predicted eutectic point approximately 515℃.

[0100] S3: Mix raw materials and molten salt in a ratio of 1:1.2 (mass ratio) and perform a dynamic reaction under argon protection: raise the temperature to 550℃ at 15℃ / min and hold for 40min; then raise the temperature to 800℃ at 8℃ / min and hold for 50min.

[0101] S4: The material is transferred to the cavitation scrubbing unit and rapidly cooled to 250°C with nitrogen. Deionized water at 60°C is injected, and cavitation (pressure 15MPa, frequency 35kHz) and high-speed shearing (linear velocity 25m / s) are started for 12 minutes.

[0102] S5 / S6: Online monitoring of changes in the conductivity of the washing liquid and the purity of the intermediate slurry (reached 98.8%), data feedback, twin calibration model, confirmation that the parameters are reasonable and no adjustment is required for this batch.

[0103] S7: The slurry enters the spheroidizing refinement reactor. Online images show that the particles are mostly irregular agglomerates. The twin-controlled reactor sequentially executes: high-intensity turbulence mode (120s, breaking up agglomerates) → strong laminar shear mode (300s, main shaping stage) → low-frequency mild cavitation mode (90s, surface smoothing and stabilization). The slurry concentration is maintained at 25wt% throughout the process.

[0104] Results: The final product was obtained after dehydration and drying. Third-party testing showed a fixed carbon content of 99.97%, a sphericity (calculated based on projection images) of 93.5%, a D50 of 16.8 μm, and a D90 / D10 ratio of 2.7. The unit energy consumption for the entire process (from raw materials to dried product) was calculated to be 52% of that of the traditional "alkali fusion-acid leaching-high temperature drying-mechanical spheroidization" route.

[0105] Example 2: Processing waste graphite hot zone material from photovoltaic monocrystalline furnaces.

[0106] Raw materials: Crushed waste graphite parts with a fixed carbon content of 91.5% and the main characteristic impurity being SiC (content 5.2%), as well as small amounts of SiO2, metallic Fe, etc.

[0107] Implementation steps: S1: The raw material was identified as having a high SiC content.

[0108] S2: The twin is formulated to address the chemical inertness of SiC, using the following formula: Na2CO3:K2CO3:NaF:LiF (molar ratio 1.0:0.9:0.8:0.7). This formula can effectively decompose SiC under oxidizing conditions.

[0109] S3: The reaction was carried out in an Ar mixed atmosphere containing 5% O2, with the following procedure: hold at 650℃ for 60 min, then increase to 780℃ and hold for 40 min. The weak oxygen atmosphere was intended to slightly oxidize the SiC surface, promoting its reaction with carbonates.

[0110] S4: Enhanced cavitation washing parameters: pressure 18MPa, frequency 28kHz, processing time 15 minutes, to ensure that the generated silicates and residual salts are completely removed.

[0111] S5 / S6: Online detection showed that the characteristic peaks of SiC (via online Raman spectroscopy) had largely disappeared, and the purity reached 99.5%. The model was used to optimize subsequent batches after calibration.

[0112] S7: Since the raw material itself is dense graphite, the particles have certain angularity after crushing and purification. Spherization focuses on "shaping". The finishing reactor adopts the mode of "medium-intensity shear as the main process, intermittent turbulence as the auxiliary process", with a total processing time of 8 minutes.

[0113] Results: The final product had a fixed carbon content of 99.92%, a sphericity of 88%, and a SiC impurity removal rate of >99.5%. Waste materials were successfully transformed into high-value-added spherical graphite products, achieving high-value recycling of resources.

[0114] Comparative example: The same raw materials as in Example 1 were used, and the conventional two-step method of "alkali-acid purification (refer to a similar process in CN120793920A) + subsequent mechanical grinding and spheroidization" was adopted for processing.

[0115] Process: The raw material is alkali-fused with NaOH at 600℃ for 2 hours, washed with water, and then leached with a mixed acid of hydrochloric acid / hydrofluoric acid at 80℃ for 4 hours. After multiple washings and drying, purified graphite (purity 99.6%) is obtained. This purified graphite is then processed in a high-speed mechanical impact spheroidizing machine for 2 hours.

[0116] Results: The final product had a fixed carbon content of 99.6%, a sphericity of 85%, and a D50 of 19.5 μm, but the distribution was relatively wide (D90 / D10 = 4.1). The total process time was approximately 2.5 times that of Example 1, and the estimated comprehensive energy consumption per unit product (including acid and alkali production, wastewater treatment, and mechanical spheroidization energy consumption) was 1.9 times that of Example 1. Furthermore, a large amount of fluoride- and alkali-containing wastewater was generated during the production process.

[0117] The above embodiments and comparative examples fully demonstrate that the present invention, through intelligent decision-making driven by digital twins, broad-spectrum adaptive chemical treatment of high-entropy molten salt, and physical morphology control in cavitation-flow field synergy, forms a set of efficient, clean, intelligent, and integrated graphite deep processing solutions. It exhibits significant advantages in product quality, production efficiency, energy consumption, and environmental protection, and has extremely high industrialization and promotion value.

[0118] Compared with the prior art, the solution provided by the present invention has the following outstanding advantages: 1. A fundamental breakthrough in intelligent technology: For the first time, the core concept of "digital twin" has been introduced into the field of graphite deep processing, realizing a paradigm shift from "experience-driven, open-loop production" to "data-driven, closed-loop optimization." The system possesses self-sensing, self-decision-making, and self-optimization capabilities, and can proactively adapt to raw material fluctuations, fundamentally ensuring high product consistency and stability. Its technological advancement far surpasses existing optimization methods based on static historical templates.

[0119] 2. Innovative Design of the Chemical System: The design concept of "high-entropy alloys" from materials science is creatively applied to molten salt media. The developed "high-entropy composite molten salt" system features a lower eutectic temperature (down to 400-600℃), a wider operating window, and a synergistic removal capability of multiple impurities due to the "cocktail effect." Compared to existing binary halides or specific salt pairs, the molten salt system of this invention is more universal, has a milder reaction, and is easier to design and adjust, significantly reducing reaction energy consumption and equipment corrosion.

[0120] 3. Deep Integration and Enhancement of the Process: An innovative design seamlessly integrates the "thermochemical reaction" and the "cavitation physical field" in both time and space. Cavitation technology is not only used to assist washing but also given the crucial function of "initial morphology shaping," forming a "rough shaping-fine shaping" spherical gradient process with the subsequent flow field spherical finishing unit. This integrated design highly integrates the traditionally sequential multi-step processes, significantly shortening the process and expected to reduce overall energy consumption by 30%-50%, while avoiding intermediate material transfer losses.

[0121] 4. Avoid using high-risk reagents: The entire process is closed and continuous, using water or weak acid for washing, avoiding the use of high-risk reagents such as hydrofluoric acid and concentrated hydrochloric acid; the molten salt system can be designed to be water-soluble, and most of the salt in the washing solution can be recovered through evaporation and crystallization, achieving recycling.

[0122] 5. Excellent overall product performance: This method can simultaneously and efficiently pursue extreme purity and perfect morphology. The resulting spherical graphite products meet or exceed the requirements of high-end applications in key indicators such as purity (≥99.95%), sphericity (≥90%), tap density and particle size distribution.

[0123] 6. Achieved true closed-loop intelligent control: The system constructs a complete "perception-simulation-decision-execution-feedback" control hierarchy, and the digital twin can be calibrated and continuously optimized in real time, which greatly improves process adaptability and product consistency.

[0124] Based on the same inventive concept, this application also provides a graphite processing apparatus based on digital twin and high-entropy molten salt adaptation, which can be used to implement the method described in the above embodiments, as described in the following embodiments. Since the principle of solving the problem based on digital twin and high-entropy molten salt adaptation graphite processing apparatus is similar to that of the graphite processing method based on digital twin and high-entropy molten salt adaptation, the implementation of the graphite processing apparatus based on digital twin and high-entropy molten salt adaptation can refer to the implementation of the software performance benchmark determination method, and repeated details will not be elaborated further. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the system described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0125] In one embodiment, see Figure 7 To integrate digital process simulation, adaptive chemical systems, and physical field enhancement technologies to achieve integrated intelligent purification and spheroidization of graphite materials, this application provides a graphite processing apparatus based on digital twins and high-entropy molten salt adaptation, comprising: The key parameter detection unit 701 is used to perform rapid online detection on the graphite raw material to be processed and obtain the key parameters of the raw material. The control parameter generation unit 702 is used to input the key parameters of the raw material into a pre-constructed digital twin of the graphite purification and spheroidization process to obtain the control parameters required for the graphite purification and spheroidization process; wherein, the digital twin of the graphite purification and spheroidization process is obtained based on multi-physics simulation of the parameters of the graphite raw material to be processed during the processing. The control processing unit 703 is used to control the automatic batching system, the programmable temperature-controlled dynamic reactor, the high-pressure cavitation generator and the multi-stage shearing mechanism, and the multi-modal flow field synergistic spheroidizing reactor using the control parameters to perform integrated purification and spheroidization processing on the graphite raw material to be processed.

[0126] From a hardware perspective, in order to integrate digital process simulation, adaptive chemical systems, and physical field enhancement technologies to achieve integrated intelligent purification and spheroidization of graphite materials, this application provides an embodiment of an electronic device for implementing all or part of the aforementioned graphite processing method based on digital twins and high-entropy molten salt adaptation. The electronic device specifically includes the following components: The system comprises a processor, a memory, a communications interface, and a bus; wherein the processor, memory, and communications interface communicate with each other via the bus; the communications interface is used to realize information transmission between the graphite processing device based on digital twin and high-entropy molten salt adaptation and core business systems, user terminals, and related databases and other related devices; the logic controller can be a desktop computer, tablet computer, or mobile terminal, etc., and this embodiment is not limited to these. In this embodiment, the logic controller can be implemented with reference to the embodiments of the graphite processing method based on digital twin and high-entropy molten salt adaptation and the embodiments of the graphite processing device based on digital twin and high-entropy molten salt adaptation in the embodiments, the contents of which are incorporated herein, and repeated details will not be described again.

[0127] It is understood that the user terminal may include smartphones, tablet computers, network set-top boxes, portable computers, desktop computers, personal digital assistants (PDAs), in-vehicle devices, smart wearable devices, etc. Among these, the smart wearable devices may include smart glasses, smartwatches, smart bracelets, etc.

[0128] In practical applications, parts of the graphite processing method based on digital twins and high-entropy molten salt adaptation can be executed on the electronic device side as described above, or all operations can be completed in the client device. The specific choice depends on the processing power of the client device and the limitations of the user's usage scenario. This application does not impose any limitations on this. If all operations are completed in the client device, the client device may further include a processor.

[0129] The aforementioned client device may have a communication module (i.e., a communication unit) that can communicate with a remote server to achieve data transmission. The server may include a server on the task scheduling center side; in other implementation scenarios, it may also include a server on an intermediate platform, such as a server on a third-party server platform that has a communication link with the task scheduling center server. The server may include a single computer device, a server cluster consisting of multiple servers, or a distributed server structure.

[0130] Figure 12 This is a schematic block diagram illustrating the system configuration of the electronic device 9600 according to an embodiment of this application. Figure 12 As shown, the electronic device 9600 may include a central processing unit 9100 and a memory 9140; the memory 9140 is coupled to the central processing unit 9100. It is worth noting that... Figure 12 This is an example; other types of structures can also be used to supplement or replace this structure to achieve telecommunications functions or other functions.

[0131] In one embodiment, the graphite processing method based on digital twins and high-entropy molten salt adaptation can be integrated into the central processing unit 9100. The central processing unit 9100 can be configured to perform the following control: S101: Perform rapid online detection on the graphite raw material to be processed to obtain key parameters of the raw material; S102: Input the key parameters of the raw material into a pre-constructed digital twin of the graphite purification and spheroidization process to obtain the control parameters required for the graphite purification and spheroidization process; wherein, the digital twin of the graphite purification and spheroidization process is obtained based on multi-physics simulation of the parameters of the graphite raw material to be processed during the processing. S103: Using the control parameters, control the automatic batching system, the programmable temperature-controlled dynamic reactor, the high-pressure cavitation generator and the multi-stage shearing mechanism, and the multi-modal flow field synergistic spheroidizing reactor to perform integrated purification and spheroidization processing of the graphite raw material to be processed.

[0132] As can be seen from the above description, the graphite processing method based on digital twin and high-entropy molten salt adaptive processing provided in this application can form a set of efficient, clean, intelligent and integrated graphite deep processing solutions through intelligent decision-making driven by digital twin, broad-spectrum adaptive chemical processing of high-entropy molten salt, and physical morphology control in cavitation-flow field coordination. It shows significant advantages in product quality, production efficiency, energy consumption and environmental protection, and has extremely high industrialization and technology promotion value.

[0133] In another embodiment, the graphite processing apparatus based on digital twin and high-entropy molten salt adaptation can be configured separately from the central processing unit 9100. For example, the data composite transmission device based on digital twin and high-entropy molten salt adaptation graphite processing apparatus can be configured as a chip connected to the central processing unit 9100, and the function of the graphite processing method based on digital twin and high-entropy molten salt adaptation can be realized through the control of the central processing unit.

[0134] like Figure 12 As shown, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is worth noting that the electronic device 9600 does not necessarily need to include these components. Figure 12 All components shown; in addition, the electronic device 9600 may also include Figure 12 For components not shown, please refer to existing technology.

[0135] like Figure 12 As shown, the central processing unit 9100, sometimes also referred to as a controller or operating control, may include a microprocessor or other processor device and / or logic device, which receives inputs and controls the operation of various components of the electronic device 9600.

[0136] The memory 9140 may be, for example, one or more of a cache, flash memory, hard drive, removable media, volatile memory, non-volatile memory, or other suitable devices. It may store the aforementioned failure-related information, and also store a program for executing that information. The central processing unit 9100 may execute the program stored in the memory 9140 to perform information storage or processing, etc.

[0137] Input unit 9120 provides input to central processing unit 9100. Input unit 9120 may be, for example, a keypad or touch input device. Power supply 9170 provides power to electronic device 9600. Display 9160 displays images and text. Display may be, for example, an LCD display, but is not limited thereto.

[0138] The memory 9140 can be a solid-state memory, such as a read-only memory (ROM), random access memory (RAM), a SIM card, etc. It can also be a memory that retains information even when power is off, can be selectively erased, and contains more data; examples of this type of memory are sometimes referred to as EPROMs. The memory 9140 can also be some other type of device. The memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application / function storage unit 9142 for storing application programs and function programs or processes for executing the operation of the electronic device 9600 via the central processing unit 9100.

[0139] The memory 9140 may also include a data storage unit 9143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 9144 of the memory 9140 may include various drivers for the electronic device's communication functions and / or for performing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0140] The communication module 9110 is a transmitter / receiver that sends and receives signals via the antenna 9111. The communication module (transmitter / receiver) 9110 is coupled to the central processing unit 9100 to provide input signals and receive output signals, which is the same as in a conventional mobile communication terminal.

[0141] Based on different communication technologies, multiple communication modules 9110 can be configured in the same electronic device, such as cellular network modules, Bluetooth modules, and / or wireless LAN modules. The communication module (transmitter / receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and receive audio input from the microphone 9132, thereby realizing typical telecommunications functions. The audio processor 9130 may include any suitable buffer, decoder, amplifier, etc. Additionally, the audio processor 9130 is also coupled to a central processing unit 9100, enabling on-device recording via the microphone 9132 and on-device playback of stored sound via the speaker 9131.

[0142] Embodiments of this application also provide a computer-readable storage medium capable of implementing all steps of the graphite processing method based on digital twins and high-entropy molten salt adaptation, where the execution subject is a server or client, as described in the above embodiments. The computer-readable storage medium stores a computer program that, when executed by a processor, implements all steps of the graphite processing method based on digital twins and high-entropy molten salt adaptation, where the execution subject is a server or client, as described in the above embodiments. For example, when the processor executes the computer program, it implements the following steps: S101: Perform rapid online detection on the graphite raw material to be processed to obtain key parameters of the raw material; S102: Input the key parameters of the raw material into a pre-constructed digital twin of the graphite purification and spheroidization process to obtain the control parameters required for the graphite purification and spheroidization process; wherein, the digital twin of the graphite purification and spheroidization process is obtained based on multi-physics simulation of the parameters of the graphite raw material to be processed during the processing. S103: Using the control parameters, control the automatic batching system, the programmable temperature-controlled dynamic reactor, the high-pressure cavitation generator and the multi-stage shearing mechanism, and the multi-modal flow field synergistic spheroidizing reactor to perform integrated purification and spheroidization processing of the graphite raw material to be processed.

[0143] As can be seen from the above description, the graphite processing method based on digital twin and high-entropy molten salt adaptive processing provided in this application can form a set of efficient, clean, intelligent and integrated graphite deep processing solutions through intelligent decision-making driven by digital twin, broad-spectrum adaptive chemical processing of high-entropy molten salt, and physical morphology control in cavitation-flow field coordination. It shows significant advantages in product quality, production efficiency, energy consumption and environmental protection, and has extremely high industrialization and technology promotion value.

[0144] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0145] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0146] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0147] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0148] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A graphite processing method based on digital twin and high-entropy molten salt adaptive processing, characterized in that, include: Rapid online detection of the graphite raw material to be processed yields key parameters of the raw material; The key parameters of the raw materials are input into a pre-constructed digital twin of the graphite purification and spheroidization process to obtain the control parameters required for the graphite purification and spheroidization process; wherein, the digital twin of the graphite purification and spheroidization process is obtained based on multi-physics simulation of the parameters of the graphite raw materials to be processed during the processing. The control parameters are used to control an automatic batching system, a programmable temperature-controlled dynamic reactor, a high-pressure cavitation generator and a multi-stage shearing mechanism, and a multi-modal flow field synergistic spheroidizing reactor to perform integrated purification and spheroidization processing of the graphite raw material to be processed.

2. The graphite processing method based on digital twin and high-entropy molten salt adaptive processing according to claim 1, characterized in that, The digital twin of the graphite purification and spheroidization process includes a data perception layer, a decision optimization layer, an execution control layer, and a feedback calibration layer; the steps for pre-constructing the digital twin of the graphite purification and spheroidization process include: The processing parameters of the graphite raw material to be tested are collected in real time to generate the data sensing layer; The decision optimization layer is generated based on the process optimization instructions obtained from multiphysics simulation of the processing parameters. The execution control layer is constructed by issuing the process optimization instructions to the automatic batching system, the program-controlled temperature dynamic reactor, the high-pressure cavitation generator and multi-stage shearing mechanism, and the multi-modal flow field collaborative spherical reactor. The feedback calibration layer is constructed by comparing the actual values ​​of graphite finished product parameters collected by sensors during the processing with the simulated predicted values ​​of graphite finished product parameters.

3. The graphite processing method based on digital twin and high-entropy molten salt adaptive processing according to claim 2, characterized in that, The control parameters include high-entropy composite molten salt formulation, dynamic reaction curve, cavitation shear parameters, and spheroidization parameters; the key parameters of the raw materials are input into a pre-constructed digital twin of the graphite purification and spheroidization process to obtain the control parameters required for the graphite purification and spheroidization process, including: The key parameters of the raw materials are input into the data sensing layer to obtain the corresponding processing parameters; The processing parameters are input into the thermodynamic model, reaction kinetic model, fluid kinetics and mass transfer model, and particle morphology evolution model in the decision optimization layer to obtain the high-entropy composite molten salt formulation, dynamic reaction curve, cavitation shear parameters, and spheroidization parameters. The high-entropy composite molten salt formulation, dynamic reaction curve, cavitation shear parameters, and spheroidization parameters are input into the feedback calibration layer for calibration to obtain the control parameters.

4. The graphite processing method based on digital twin and high-entropy molten salt adaptive processing according to claim 3, characterized in that, The process parameters are input into the thermodynamic model, reaction kinetic model, fluid kinetics and mass transfer model, and particle morphology evolution model in the decision optimization layer to obtain the high-entropy composite molten salt formulation, dynamic reaction curve, cavitation shear parameters, and spheroidization parameters, including: The activity, phase transition boundary, and reaction driving force of each component in the high-entropy composite molten salt are predicted using the processing parameters, the thermodynamic model, and the reaction kinetic model, thereby obtaining the high-entropy composite molten salt formulation; wherein, the high-entropy composite molten salt formulation is generated based on the activity, phase transition boundary, and reaction driving force of each component. The concentration field, velocity field, and interfacial mass transfer rate at different time steps are calculated using the processing parameters and the fluid dynamics and mass transfer model to obtain the dynamic response curve; wherein the dynamic response curve is plotted based on the concentration field, velocity field, and interfacial mass transfer rate. The cavitation shear parameters are determined using the processing parameters and the fluid dynamics and mass transfer model. The surface tension, cooling rate, and collision frequency of the graphite raw material during the spheroidization process are simulated using the processing parameters and the particle morphology evolution model to obtain the spheroidization parameters; wherein the spheroidization parameters are determined based on the surface tension, cooling rate, and collision frequency.

5. The graphite processing method based on digital twin and high-entropy molten salt adaptive processing according to claim 3, characterized in that, The system that utilizes the control parameters to control the automatic batching system, the program-controlled temperature dynamic reactor, the high-pressure cavitation generator and multi-stage shearing mechanism, and the multi-modal flow field synergistic spherical reactor includes: The calibrated high-entropy composite molten salt formula is sent to the automatic batching system to control the automatic batching system to prepare high-entropy composite molten salt based on the high-entropy composite molten salt formula; The calibrated dynamic reaction curve is sent to the programmed temperature-controlled dynamic reactor to control the programmable temperature-controlled dynamic reactor to purify the mixture of the graphite raw material to be processed and the high-entropy composite molten salt to obtain the first intermediate slurry. The calibrated cavitation shear parameters are sent to the high-pressure cavitation generator and the multi-stage shearing mechanism to control the high-pressure cavitation generator and the multi-stage shearing mechanism to purify the first intermediate slurry and obtain the second intermediate slurry. The calibrated spheroidization parameters are sent to the multimodal flow field collaborative spheroidization reactor to control the reactor to spheroidize the second intermediate slurry, thereby obtaining the finished graphite product. The spheroidization parameters include purity, sphericity, tap density, and particle size distribution.

6. The graphite processing method based on digital twin and high-entropy molten salt adaptive processing according to claim 2, characterized in that, Also includes: Real-time data on temperature, pressure, atmosphere composition, dielectric conductivity, viscosity and morphology of the graphite raw material to be processed during the purification and spheroidization process are collected. The temperature, pressure, atmosphere composition, dielectric conductivity, viscosity and morphology data are synchronized in real time to the digital twin of the graphite purification and spheroidization process, and the decision optimization layer is dynamically calibrated using twin assimilation technology.

7. A graphite processing apparatus based on digital twin and high-entropy molten salt adaptive technology, characterized in that, include: The key parameter detection unit is used to perform rapid online detection of the graphite raw materials to be processed, and obtain the key parameters of the raw materials; The control parameter generation unit is used to input the key parameters of the raw material into a pre-constructed digital twin of the graphite purification and spheroidization process to obtain the control parameters required for the graphite purification and spheroidization process; wherein, the digital twin of the graphite purification and spheroidization process is obtained based on multi-physics simulation of the parameters of the graphite raw material to be processed during the processing. The control processing unit is used to control the automatic batching system, the programmable temperature-controlled dynamic reactor, the high-pressure cavitation generator and the multi-stage shearing mechanism, and the multi-modal flow field synergistic spheroidizing reactor using the control parameters to perform integrated purification and spheroidization processing on the graphite raw material to be processed.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the graphite processing method based on digital twin and high-entropy molten salt adaptive method as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the graphite processing method based on digital twin and high-entropy molten salt adaptive as described in any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the graphite processing method based on digital twin and high-entropy molten salt adaptation as described in any one of claims 1 to 6.

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