Copper slag crystallization process analysis method and device, electronic equipment and storage medium

Abstract

The invention discloses a copper slag crystallization process analysis method and device, electronic equipment and a storage medium. The method comprises the following steps: determining first data; performing crystallization simulation on each element in the copper slag through a first model according to the first data to obtain copper slag crystallization information; and all elements in the copper slag are crystallized and separated out according to the copper slag crystallization information. According to the method, the crystallization process of the copper slag is simulated, the problem that microscopic detail changes in the crystallization process of the copper slag cannot be captured can be solved, all elements in the copper slag are crystallized according to the copper slag crystallization information obtained through simulation, and the copper slag resource recovery rate can be increased.

Description

Technical Field

[0001] The present invention relates to the technical field of copper smelting processes, and in particular to a method, device, electronic equipment and storage medium for analyzing a copper slag crystallization process. Background Art

[0002] During the copper smelting process, large amounts of copper slag are produced, which often contains complex chemical compositions and phase structures. The effective utilization and treatment of copper slag are of great significance for resource recovery and environmental protection. However, the accurate calculation of physical properties such as the crystallization behavior and thermal conductivity of copper slag has always been a challenge in the copper smelting process. Traditional experimental methods have problems such as long cycles, high costs, and difficulty in capturing microscopic details, which limit the in-depth understanding and optimized control of copper slag properties. Summary of the Invention

[0003] The present invention provides a copper slag crystallization process analysis method, device, electronic equipment and storage medium to solve the problem of poor copper slag resource recovery rate caused by inaccurate copper slag crystallization process analysis.

[0004] According to one aspect of the present invention, a method for analyzing a copper slag crystallization process is provided, comprising:

[0005] Determining first data; the first data is used to characterize the arrangement of each element in the copper slag and the initial crystallization conditions of each element;

[0006] performing a crystallization simulation of each element in the copper slag using a first model based on the first data to obtain copper slag crystallization information; the first model is used to simulate a process in which each element melts and forms grains at a corresponding temperature by changing the temperature during the copper slag crystallization process; the copper slag crystallization information is used to describe the shape and size of grains formed by each element in the copper slag, and the state of grain boundaries formed between different grains;

[0007] Each element in the copper slag is crystallized and precipitated according to the copper slag crystallization information.

[0008] According to another aspect of the present invention, there is provided a copper slag crystallization process analysis device, comprising:

[0009] A first data determination module is used to determine first data; the first data is used to characterize the arrangement of each element in the copper slag and the initial crystallization conditions of each element;

[0010] a copper slag crystallization information determination module, configured to perform a crystallization simulation of each element in the copper slag using a first model based on the first data to obtain copper slag crystallization information; the first model is configured to simulate a process in which each element melts and forms grains at a corresponding temperature by changing the temperature during the copper slag crystallization process; the copper slag crystallization information is configured to describe the shape and size of grains formed by each element in the copper slag, and the state of grain boundaries formed between different grains;

[0011] The crystallization precipitation module is used to crystallize and precipitate various elements in the copper slag according to the copper slag crystallization information.

[0012] According to another aspect of the present invention, an electronic device is provided, comprising:

[0013] at least one processor; and

[0014] a memory communicatively connected to the at least one processor; wherein,

[0015] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the copper slag crystallization process analysis method described in any embodiment of the present invention.

[0016] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the copper slag crystallization process analysis method described in any embodiment of the present invention when executed.

[0017] The technical solution of an embodiment of the present invention comprises determining first data; performing a crystallization simulation of each element in copper slag using a first model based on the first data to obtain copper slag crystallization information, which can reveal microscopic details of the copper slag crystallization process, providing a reference for subsequent crystallization and precipitation of the copper slag; and crystallizing each element in the copper slag based on the copper slag crystallization information. By simulating the copper slag crystallization process, this method can address the problem of being unable to capture microscopic details of copper slag crystallization during the crystallization process. Crystallizing each element in the copper slag based on the simulated copper slag crystallization information can improve the copper slag resource recovery rate.

[0018] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 A flow chart of a copper slag crystallization process analysis method provided by an embodiment of the present invention;

[0021] Figure 2 A schematic structural diagram of a copper slag crystallization process analysis device provided by an embodiment of the present invention;

[0022] Figure 3 A schematic diagram of the structure of an electronic device for implementing the copper slag crystallization process analysis method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0024] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] Figure 1 This is a flow chart of a copper slag crystallization process analysis method provided by an embodiment of the present invention. This embodiment is applicable to the case of microscopic analysis of the copper slag crystallization process. The method can be performed by a copper slag crystallization process analysis device. The copper slag crystallization process analysis device can be implemented in the form of hardware and / or software. The copper slag crystallization process analysis device can be configured in any electronic device with network communication function. Figure 1 As shown, the method includes:

[0026] S110, determining first data; the first data is used to characterize the arrangement of elements in the copper slag and the initial crystallization conditions of the elements.

[0027] Among them, copper slag is a large amount of slag containing metal elements produced during the copper smelting process.

[0028] The elements may be metal elements with recycling value, for example, copper, iron, silicon, oxygen and other elements and their compounds.

[0029] The arrangement of the elements can be a three-dimensional periodic regular arrangement of atoms, ions and molecules in the crystal grains and oxides formed in the copper slag.

[0030] The initial crystallization conditions for each element may be the temperature and pressure corresponding to when each element melts into liquid and condenses into crystal grains.

[0031] Specifically, the copper slag is subjected to structural analysis to analyze the elements contained in the copper slag and the structure of the elements, thereby obtaining the elements contained in the copper slag and the arrangement of the elements in the copper slag.

[0032] Structural analysis involves cleaning the copper slag to remove surface impurities and contaminants. The cleaned copper slag is then placed in a transmission electron microscope (TEM). Low-magnification imaging is used to locate the region of interest where the elements are to be observed, and this region is then circled using a selection aperture. The TEM's accelerating voltage and electron beam intensity are adjusted so that the electron beam shines perpendicularly on the selected region, and the resulting diffraction image is recorded. Analysis of this diffraction image reveals the microstructure of the elements within the slag.

[0033] Furthermore, the initial crystallization conditions of each element in the copper slag are determined based on the element characteristics of each element in the copper slag, wherein the element characteristics are the melting point or crystallization point of the element under standard atmospheric pressure.

[0034] S120. Performing a crystallization simulation on each element in the copper slag using a first model according to the first data to obtain copper slag crystallization information; the first model is used to simulate a process in which each element melts and generates grains at a corresponding temperature by changing the temperature during the copper slag crystallization process; the copper slag crystallization information is used to describe the shape and size of grains formed by each element in the copper slag, and the state of grain boundaries formed between different grains.

[0035] Among them, the grains are crystals condensed after the elements in the copper slag melt.

[0036] Among them, the state of the grain boundary is the morphology when the interface area between different grains is formed after the elements in the copper slag crystallize to form grains.

[0037] Crystallization simulation is the process of precipitation of various elements in copper slag under different temperatures and pressures. Precipitation is the process of metal elements melting and crystallizing during the heat treatment of copper slag, and then leaving the copper slag.

[0038] Furthermore, crystallization simulations show that when the temperature changes, the interactions between atoms weaken, causing the atomic arrangement of the elements in the copper slag to change. This means that at high temperatures, the elements in the copper slag will transform from one crystal structure to another. For example, assuming the elements in the copper slag are metallic iron, when heated to a certain temperature, the metallic iron will transform from a body-centered cubic α-Fe to a face-centered cubic γ-Fe.

[0039] Further, by lowering the temperature and applying pressure, the elements in the copper slag may be forced to adopt a tighter arrangement to adapt to the pressure change, which will cause the structure of the elements in the copper slag to change, and the properties of the metal bonds will also change accordingly, thus condensing into grains.

[0040] Specifically, the first data is input into the first model. The first model determines the interaction force between the atoms of each element in the copper slag according to the arrangement of each element in the copper slag. The first model then simulates the crystallization process according to the initial crystallization conditions and the interaction force, and records the grain change data during the simulation process as the copper slag crystallization information.

[0041] Among them, the interaction force between atoms is used to characterize the attraction or repulsion between atoms.

[0042] Furthermore, the first model comprises a neural network algorithm and an evolutionary algorithm. The neural network algorithm is used to calculate the interaction forces between atoms of each element in the copper slag based on the arrangement of each element in the copper slag. The evolutionary algorithm iteratively simulates the crystallization process between atoms of each element in the copper slag based on the acquired interaction forces and the first data. Specifically, under initial crystallization conditions, the velocity and position of atoms of each element in the copper slag at the next moment are calculated based on the velocity and position of atoms of each element in the copper slag. This model is continuously iterated, and the crystallization changes of each element in the copper slag are recorded during the iterative process.

[0043] Exemplarily, the first model may adopt a Neuroevolution Potential (NEP) model.

[0044] S130, crystallizing and precipitating each element in the copper slag according to the copper slag crystallization information.

[0045] Specifically, corresponding crystallization change information is matched from the copper slag crystallization information according to the elements contained in the copper slag, crystallization conditions are determined according to the crystallization change information, and the copper slag is crystallized and precipitated according to the crystallization conditions.

[0046] Furthermore, the copper slag is crystallized and precipitated by crystallization conditions: by changing the temperature and pressure in the precipitation device where the copper slag is located, different elements are melted and crystallized.

[0047] The crystallization change information is the corresponding change information and corresponding crystallization conditions when the element changes from solid to liquid and then from liquid to solid.

[0048] Among them, the crystallization conditions are temperature and pressure change information.

[0049] Optionally, at least one method for determining the first model includes steps A1-A4:

[0050] Step A1, determining second data; the second data is used to characterize the interaction force between elements in the copper slag sample at different temperatures; the copper slag sample is selected from the copper slag.

[0051] The second data may also include data that can characterize microscopic changes of elements in the copper slag, such as position changes of atoms in each element, speed changes of atoms in each element, and molecular structure changes of atoms in each element.

[0052] Specifically, molecular dynamics simulation is performed on the third data, and the generated data is collected and sorted during the simulation process to obtain the second data.

[0053] The third data is used to characterize the arrangement of each element in the copper slag sample and the initial crystallization conditions of each element.

[0054] Molecular dynamics simulation uses a numerical integration algorithm to calculate the position and velocity of atoms at the next moment based on the position, velocity, and force of each element in the copper slag at the current moment, using the third data and potential function. Within each time step, the interaction force is determined based on the change in atomic velocity and position.

[0055] Among them, the potential function is used to describe the function of the intermolecular potential energy changing with the intermolecular distance.

[0056] Furthermore, the process of determining the position and velocity of the atoms at the next moment is: under the conditions of the third data and the potential function, the motion equation of the atoms of each element in the copper slag is determined according to the position, velocity and force conditions of the atoms of each element in the copper slag at the current moment, the motion equation is converted into a group of first-order ordinary differential equations, and the first-order ordinary differential equations are approximately solved by a numerical integration algorithm to obtain the position and velocity of the atoms of each element in the copper slag at the next moment.

[0057] The numerical integration algorithm is a method for calculating the approximate value of a definite integral, and can be exemplified by the Euler method or the Runge-Kutta method.

[0058] Furthermore, temperature and pressure can be adjusted during molecular dynamics simulations using the NPT ensemble. The NPT ensemble maintains or modulates temperature by exchanging heat with a heat source, and maintains or modulates pressure by varying the pressure applied by an external pressurizing device.

[0059] Furthermore, the third data is determined by selecting individual copper slags from the copper slag as copper slag samples, performing structural analysis on the copper slag samples, and obtaining the elements contained in the copper slag samples and their distribution within the copper slag samples. The initial crystallization conditions for the copper slag samples are determined based on the melting points of the elements and the corresponding melting and crystallization pressures.

[0060] For further structural analysis, the copper slag sample is cleaned to remove surface impurities and contaminants. The cleaned copper slag sample is placed in a transmission electron microscope (TEM). Low-magnification imaging is used to locate the region of interest where the elements are to be observed, and this region is then circled using a selection aperture. The TEM's accelerating voltage and electron beam intensity are adjusted so that the electron beam shines perpendicularly on the selected region, and the resulting diffraction image is recorded. Analysis of the diffraction image reveals the microstructure of the elements within the slag sample.

[0061] Step A2: input the third data into the second model to perform crystallization simulation to obtain fourth data; the third data is used to characterize the arrangement of each element in the copper slag sample and the initial crystallization conditions of each element.

[0062] Specifically, the third data is input into the second model. The second model obtains the interaction force between the atoms of each element in the copper slag through the corresponding relationship according to the arrangement of each element in the copper slag. Under the initial crystallization conditions, the second model performs crystallization simulation according to the obtained interaction force, the current speed and position of the atoms to obtain the fourth data.

[0063] The corresponding relationship is a pre-established correlation between the arrangement of elements in the copper slag and the interaction forces between atoms of each element in the copper slag. For example, the corresponding interaction force of element A is X, and the corresponding interaction force of element B is Y.

[0064] Furthermore, the corresponding relationship between the arrangement of elements in the copper slag and the interaction force between atoms of each element in the copper slag is due to the mutual influence between the two.

[0065] For example, assuming a metal element, its arrangement is guaranteed by metallic bonds. The non-directional and non-saturated nature of metallic bonds causes metal atoms to tend to form dense packings, achieving the lowest energy and most stable crystal state. This dense packing of metal atoms strengthens the interaction forces, allowing for the mutual conversion between the interaction forces between the atoms of each element within the copper slag and the arrangement of the elements within it. The metallic bond is the strong interaction between the metal element's cations and free electrons.

[0066] Step A3: Modify the second model according to the second data and the fourth data to obtain the first model.

[0067] Specifically, an error parameter is determined based on the second data and the fourth data, and parameters of the second model and the number of crystallization simulations are determined based on the error parameter to obtain a correction parameter. The parameters or structure of the second model are modified based on the correction parameter to obtain the first model.

[0068] Furthermore, the error parameter can be calculated using the root mean square error.

[0069] Optionally, determining the second data includes steps B1-B4:

[0070] Step B1: Determine third data.

[0071] Specifically, individual copper slag pieces are selected from the copper slag as copper slag samples, and the copper slag samples are structurally analyzed to obtain the elements contained in the copper slag samples and the distribution of each element within the copper slag samples. Initial crystallization conditions for the copper slag crystallization are determined based on the melting points of each element and the pressures corresponding to melting and crystallization. The obtained initial crystallization conditions and the distribution of each element within the copper slag sample are used as third data.

[0072] Step B2: constructing a molecular model based on the third data; the molecular model is used to characterize the initial distribution of each element in the copper slag.

[0073] Specifically, the structure of the copper slag is constructed according to the arrangement of each element in the copper slag sample to obtain a molecular model.

[0074] Furthermore, modeling software is used to place the corresponding atoms in the copper slag sample according to the atomic coordinates in the arrangement pattern, obtaining a structural model of each element in the copper slag. If the copper slag also contains amorphous components, a structural model of the amorphous portion is constructed using some approximate methods or combined with experimental data (such as XRD full spectrum fitting).

[0075] Furthermore, the modeling software performs energy optimization on the obtained atomic structure model, so that the constructed atomic structure model reaches a more stable state.

[0076] The modeling software may be Materials Studio, Vesta, etc.

[0077] Step B3: Determine the electron density distribution among the elements based on the third data.

[0078] Specifically, the Kohn-Sham Hamiltonian is constructed based on density functional theory and basis set according to the arrangement of elements in the copper slag sample, the types and quantities of elements in the copper slag sample, and the Kohn-Sham Hamiltonian is iteratively solved by the self-consistent field (SCF) method. That is, an initial electron density distribution is first initialized, and then substituted into the Hamiltonian to obtain the electron wave function and energy eigenvalue, and then the new electron density distribution is calculated based on the obtained wave function.

[0079] Among them, density functional theory is used to express the ground state energy in copper slag as a functional of electron density, that is, a complex function of the probability distribution of electrons in copper slag.

[0080] The basis set may be a plane wave basis set, a pseudopotential basis set, or the like.

[0081] Among them, the Kohn-Sham Hamiltonian is used to describe the motion of single electrons in copper slag.

[0082] The core idea of the SCF method is to iteratively solve the wave function of each electron in each element of the copper slag sample and the total energy of the system, so that the average field generated by the electron distribution is self-consistent with the field used to calculate the electron wave function. The wave function is used to characterize the state of each electron in each element of the copper slag sample.

[0083] Step B4: determining second data through molecular modeling according to the electron density distribution and the initial crystallization conditions.

[0084] Specifically, the forces acting on each atom in the copper slag are determined based on the electron density distribution. Within the initial crystallization conditions and time step, the atomic motion is continuously simulated based on the positions of the atoms in the molecular model and the forces acting on them, resulting in atomic motion trajectories. These atomic motion trajectories are then analyzed to generate the second data.

[0085] Furthermore, during the simulation process, the preset conditions can be continuously adjusted.

[0086] Optionally, performing crystallization simulation on each element in the copper slag using a first model according to the first data to obtain copper slag crystallization information includes steps C1-C5:

[0087] Step C1: determining the interaction force between atoms of each element in the copper slag according to the first data.

[0088] Among them, the interaction forces between atoms of each element in copper slag include: the interaction forces between atoms of the elements and the interaction forces between atoms of different elements at the intersection.

[0089] Specifically, under the initial crystallization conditions, the first model matches the interaction forces corresponding to the elements through a corresponding relationship according to the arrangement of the elements in the copper slag, and obtains the interaction forces between the atoms of the elements in the copper slag.

[0090] Among them, the corresponding relationship is the correlation between the pre-constructed arrangement of each element in the copper slag and the interaction force between the atoms of each element in the copper slag.

[0091] Step C2: construct the interaction potential energy surface between the elements based on the interaction force.

[0092] Specifically, if the interaction force is the interaction force between atoms of different elements, an interaction potential energy surface is generated within the same atomic range; if the interaction force is the interaction force between atoms at the intersection of different elements, an interaction potential energy surface is generated within the intersection range.

[0093] Among them, the interaction force between atoms of elements is the interaction force between atoms within a single element, that is, the interaction force between atoms of grains; the interaction force between atoms at the intersection of different elements is the interaction force between atoms in the area where different elements are fused with each other, that is, the interaction force between atoms of grain boundaries.

[0094] Step C3: The motion trajectory of atoms in each element according to the interaction potential energy surface.

[0095] Specifically, the negative gradient of the interaction potential energy surface is determined based on the interaction potential energy surface. Based on the obtained negative gradient of the interaction potential energy surface, the initial positions of the atoms within each element, and the initial velocities of the atoms within each element, the Newtonian cloud dynamics equation is constructed and converted into a first-order ordinary differential equation. This equation is solved using numerical integration to obtain the positions and velocities of the atoms within each element at different times. These positions are then plotted to determine the motion trajectories of the atoms within each element.

[0096] The negative gradient of the interaction potential energy surface can be expressed as follows:

[0097]

[0098] Where F is the interaction force and V is the potential energy.

[0099] Step C4: determining grain change information based on the motion trajectory; the grain change information is used to characterize the dynamic behavior or physical property changes of atoms in each element in the copper slag.

[0100] Specifically, the atomic trajectories can be used to determine the movement of atoms during the crystallization process. This movement can reflect the state change of the element to which the atoms correspond, i.e., the change from liquid to solid or from solid to liquid. It can also reflect changes in the shape and size of the crystal grains formed by the atoms, as well as changes in the crystallization of the boundaries between different elements. The obtained information on the state change of each element, the shape and size change of the crystal grains, and the crystallization change of the boundaries between different elements is referred to as grain change information.

[0101] Step C5: analyzing the crystallization phenomenon based on the grain change information to obtain copper slag crystallization information.

[0102] Specifically, phase change information is determined based on state change information; grain growth information is determined based on grain shape and size change information; grain boundary information is determined based on crystallization changes at the boundaries between different elements, and the acquired information is matched to obtain copper slag crystallization information.

[0103] Optionally, performing crystallization phenomenon analysis based on the grain change information to obtain copper slag crystallization information includes steps D1-D4:

[0104] Step D1: Determine the change in the state of each element based on the grain change information, and obtain phase change information based on the change in the state of each element; the phase change information is used to characterize the change of each element in the copper slag from liquid to solid.

[0105] Specifically, the changes of each element from melting in a solid state to a liquid state and then solidifying in a liquid state to a solid state are determined based on the grain change information, and phase change information is generated based on the change state.

[0106] In the above steps, the determination of phase change information can provide a basis for the change of thermal conductivity.

[0107] Step D2: determining the grain change state of each element in the copper slag during crystallization based on the grain change information, and generating grain growth information based on the grain change state.

[0108] The growth information of the grains includes changes in size and shape of the grains during their growth process.

[0109] Specifically, the change information of the grain size and shape during the crystallization process of each element is determined based on the grain change information, and the obtained change information is used to generate grain growth information according to stages.

[0110] Among them, the stages are segmented according to the grain growth process, such as the initial stage of grain crystallization, the middle stage of grain crystallization, and the stage of completed grain crystallization.

[0111] Among them, the initial stage of grain crystallization corresponds to the stage when the grains just begin to crystallize; the middle stage of grain crystallization corresponds to the stage when the grains have formed to a preset size; and the completed stage of grain crystallization corresponds to the stage when the grains are no longer growing.

[0112] For example, assuming that the crystallization element is A, the grain growth information is: element A-early crystallization stage-grain size-grain shape; element A-middle crystallization stage-grain size-grain shape; element A-complete crystallization stage-grain size-grain shape; change in grain size of element A from early crystallization stage to middle crystallization stage; change in grain shape of element A from early crystallization stage to middle crystallization stage and the reasons for the shape change, etc.

[0113] Step D3: Determine the state of the interface region between each grain based on the grain change information to obtain grain boundary information.

[0114] Among them, the grain boundary is the interface area between different grains after the elements in the copper slag crystallize to form grains.

[0115] Specifically, characteristic information of the interface region formed between the crystallization edges of different elements and the crystallization edges of other elements during the crystallization process is determined based on the grain change information, and the obtained characteristic information is used as grain boundary information.

[0116] The characteristic information may be the color, size, shape, etc. of the formed area.

[0117] Furthermore, the grain boundary information includes: the composition of the grain boundary, the arrangement of atoms in the grain boundary, the size of the grain boundary, etc.

[0118] The determination of the above-mentioned grain boundary information can more clearly describe the crystallization changes of various elements in the copper slag, and also provide a basis for the determination of thermal conductivity.

[0119] Step D4: Arrange the phase change information, grain formation information and grain boundary information to obtain copper slag crystallization information.

[0120] Specifically, the phase change information, grain growth information and grain boundary information are matched according to the growth process to obtain the copper slag crystallization information.

[0121] Among them, the growth process is the process of various elements in the copper slag from melting to re-condensing into grain boundaries.

[0122] Optionally, after simulating the crystallization of each element in the copper slag using the first model according to the first data to obtain the copper slag crystallization information, the method includes steps E1-E2:

[0123] Step E1: determining the temperature information corresponding to the crystallization of each element according to the copper slag crystallization information.

[0124] Specifically, the temperature change data of each element in the crystallization process is obtained from the temperature correspondence according to the crystallization speed of the copper slag and the size of the crystal grains, and the temperature change data is sorted to obtain the temperature information.

[0125] Among them, the temperature correspondence is used to characterize the temperature corresponding to different crystallization speeds and grain sizes when each element in the copper slag crystallizes.

[0126] Step E2: determining thermal conductivity based on temperature information; thermal conductivity can affect the crystallization of various elements in the copper slag.

[0127] Furthermore, when the thermal conductivity is high, the copper slag can quickly transfer heat to the surrounding environment, accelerating the cooling rate, thereby forming smaller grains of each element in the copper slag. When the thermal conductivity is high, the cooling rate is slow, resulting in larger grains of each element in the copper slag.

[0128] Specifically, a temperature gradient is constructed based on the acquired temperature information; a heat flux density is determined based on the copper slag crystallization information; and a thermal conductivity is determined based on the temperature gradient and the heat flux density.

[0129] Furthermore, the thermal conductivity can be obtained by the following formula:

[0130] J=-λ▽T;

[0131] Where J is the heat flux, λ is the thermal conductivity, and ▽T is the temperature gradient.

[0132] Furthermore, the velocity of each atom in the copper slag at each time step, the interaction potential energy surface, and the interaction force between each element are obtained from the copper slag crystallization information. The interaction force between atoms within each element is determined based on the interaction force between each element. The potential energy of each atom is determined based on the interaction potential energy surface. The heat flux density is determined based on the interaction force and velocity between each atom.

[0133] Furthermore, the heat flux can be expressed by the following formula:

[0134]

[0135] Where V is the volume of the copper slag, N is the total number of atoms in the copper slag, and v i is the velocity of the ith atom, m i is the mass of the i-th atom, U i is the potential energy of the ith atom, f ij is the interaction force between atoms i and j, r ij =r i -r j is the relative position vector between atoms i and j.

[0136] Optionally, after determining the thermal conductivity according to the temperature information, steps F1-F2 are included:

[0137] Step F1: determining the corresponding crystal structure from the copper slag crystallization information according to the temperature information; the crystal structure is used to characterize the atomic arrangement of the copper slag under the temperature information.

[0138] Specifically, the size, shape and structure of the corresponding element crystals are matched from the copper slag crystallization information according to the temperature information, and a correlation relationship between the temperature and the crystal structure is established.

[0139] For example, the association relationship may be expressed as temperature XX°C-element A-element structure.

[0140] Furthermore, environmental factors such as stress can also be considered when constructing association relationships.

[0141] Step F2: Establishing a correlation between the crystal structure and the thermal conductivity.

[0142] Specifically, the corresponding thermal conductivity is matched according to the temperature information, and a correlation relationship between the temperature information, the thermal conductivity, and the crystal structure is established.

[0143] The above steps and the establishment of the correlation relationship can more directly obtain the relationship between thermal conductivity and temperature as well as the relationship between the elements in the copper slag.

[0144] The above steps involve establishing a correlation because the proportions of various elements in copper slag vary, and the thermal conductivity of the slag changes after the crystallization of each element. Therefore, once this correlation is established, the precipitation conditions can be modified directly based on this correlation, thereby improving both the recovery rate and the efficiency of copper slag processing.

[0145] The technical solution of this embodiment comprises determining first data; performing a crystallization simulation of each element in the copper slag using a first model based on the first data to obtain copper slag crystallization information, which can reveal microscopic details of the copper slag crystallization process, providing a reference for subsequent crystallization and precipitation of the copper slag; and crystallizing each element in the copper slag based on the copper slag crystallization information. By simulating the copper slag crystallization process, this method can address the problem of being unable to capture microscopic details of copper slag crystallization during the crystallization process. Crystallizing each element in the copper slag based on the simulated copper slag crystallization information can improve the copper slag resource recovery rate.

[0146] Figure 2 This is a schematic diagram of the structure of a copper slag crystallization process analysis device provided by an embodiment of the present invention. This embodiment is applicable to the case of microscopic analysis of the crystallization process of copper slag. The copper slag crystallization process analysis device can be implemented in the form of hardware and / or software. The copper slag crystallization process analysis device can be configured in any electronic device with network communication function. Figure 2 As shown, the device includes: a first data determination module 210, a copper slag crystallization information determination module 220 and a crystallization precipitation module 230, wherein:

[0147] The first data determination module 210 is used to determine the first data; the first data is used to characterize the arrangement of each element in the copper slag and the initial crystallization conditions of each element;

[0148] Copper slag crystallization information determination module 220: configured to perform crystallization simulation of each element in the copper slag using a first model based on the first data to obtain copper slag crystallization information; the first model is configured to simulate the process of melting each element at a corresponding temperature and forming grains by changing the temperature during the copper slag crystallization process; the copper slag crystallization information is configured to describe the shape and size of the grains formed by each element in the copper slag, and the state of the grain boundaries formed between different grains;

[0149] The crystallization and precipitation module 230 is used to crystallize and precipitate various elements in the copper slag according to the copper slag crystallization information.

[0150] Optionally, the copper slag crystallization information determination module 220 includes:

[0151] A second data determination unit is used to determine second data; the second data is used to characterize the interaction force between elements in the copper slag sample at different temperatures; the copper slag sample is selected from the copper slag;

[0152] a fourth data determination unit, configured to input the third data into the second model for crystallization simulation to obtain fourth data; the third data being used to characterize the arrangement of elements in the copper slag sample and the initial crystallization conditions of the elements;

[0153] The first model determining unit is configured to modify the second model according to the second data and the fourth data to obtain the first model.

[0154] Optionally, the second data determination unit includes:

[0155] A third data determining subunit: configured to determine third data;

[0156] Molecular model determination subunit: used to construct a molecular model based on the third data; the molecular model is used to characterize the initial distribution of each element in the copper slag;

[0157] an electron density distribution determining subunit: configured to determine the electron density distribution among the elements according to the third data;

[0158] The second data determination subunit is configured to determine the second data through a molecular model according to the electron density distribution and the initial crystallization conditions.

[0159] Optionally, the copper slag crystallization information determination module 220 includes:

[0160] An interaction force determination unit is used to determine the interaction force between atoms of each element in the copper slag according to the first data;

[0161] Interaction potential energy surface unit: used to construct the interaction potential energy surface between elements based on the interaction force;

[0162] Motion trajectory determination unit: used to determine the motion trajectory of atoms in each element based on the interaction potential energy surface;

[0163] Grain change information determination unit: used to determine grain change information based on the motion trajectory; grain change information is used to characterize the dynamic behavior or physical property changes of atoms in each element in the copper slag;

[0164] Copper slag crystallization information determination unit: used to analyze the crystallization phenomenon according to the grain change information to obtain copper slag crystallization information.

[0165] Optionally, the copper slag crystallization information determination unit includes:

[0166] Phase change information determination subunit: used to determine the change in the state of each element based on the grain change information, and obtain phase change information based on the change in the state of each element; the phase change information is used to characterize the change from liquid to solid of each element in the copper slag;

[0167] Grain growth information subunit: used to determine the grain change state of each element in the copper slag during crystallization based on the grain change information, and generate grain growth information based on the grain change state;

[0168] Grain boundary information subunit: used to determine the state of the interface area between each grain based on the grain change information and obtain grain boundary information;

[0169] Copper slag crystallization information subunit: used to obtain copper slag crystallization information based on phase change information, grain formation information and grain boundary information.

[0170] Optional, copper slag crystallization process analysis device, including:

[0171] Temperature information determination module: used to determine the temperature information corresponding to the crystallization of each element according to the copper slag crystallization information;

[0172] Thermal conductivity determination module: used to determine thermal conductivity based on temperature information; thermal conductivity can affect the crystallization of various elements in copper slag.

[0173] Optional, copper slag crystallization process analysis device, including:

[0174] Crystal structure determination module: used to determine the corresponding crystal structure from the copper slag crystallization information according to the temperature information; the crystal structure is used to characterize the atomic arrangement of the copper slag under the temperature information;

[0175] Correlation building module: used to build a correlation based on crystal structure and thermal conductivity.

[0176] The copper slag crystallization process analysis device provided in the embodiment of the present invention can execute the copper slag crystallization process analysis method provided in any embodiment of the present invention mentioned above, and has the corresponding functions and beneficial effects of executing the copper slag crystallization process analysis method. For detailed process, please refer to the relevant operations of the copper slag crystallization process analysis method in the above embodiment.

[0177] Figure 3 A schematic diagram of the structure of an electronic device for implementing the copper slag crystallization process analysis method of an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0178] like Figure 3As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0179] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0180] The processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the copper slag crystallization process analysis method.

[0181] In some embodiments, the copper slag crystallization process analysis method can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the copper slag crystallization process analysis method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to execute the copper slag crystallization process analysis method in any other appropriate manner (e.g., via firmware).

[0182] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system comprising at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0183] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0184] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0185] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0186] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0187] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0188] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0189] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for analyzing the crystallization process of copper slag, characterized in that: include: determining first data; The first data is used to characterize the arrangement of elements in the copper slag and the initial crystallization conditions of each element; performing a crystallization simulation of each element in the copper slag using a first model based on the first data to obtain copper slag crystallization information; the first model is used to simulate a process in which each element melts and forms grains at a corresponding temperature by changing the temperature during the copper slag crystallization process; the copper slag crystallization information is used to describe the shape and size of grains formed by each element in the copper slag, and the state of grain boundaries formed between different grains; Each element in the copper slag is crystallized and precipitated according to the copper slag crystallization information.

2. The method according to claim 1, characterized in that At least one determination method of the first model includes: Determine second data; the second data is used to characterize the interaction force between elements in the copper slag sample at different temperatures; the copper slag sample is arbitrarily selected from the copper slag; Inputting the third data into the second model for crystallization simulation to obtain fourth data; the third data is used to characterize the arrangement of each element in the copper slag sample and the initial crystallization conditions of each element; The second model is modified according to the second data and the fourth data to obtain a first model.

3. The method according to claim 2, characterized in that The determining of the second data includes: determining third data; Constructing a molecular model based on the third data; the molecular model is used to characterize the initial distribution of each element in the copper slag; determining the electron density distribution among the elements according to the third data; Second data is determined by the molecular model according to the electron density distribution and the initial crystallization conditions.

4. The method according to claim 1, wherein The step of performing crystallization simulation on each element in the copper slag using a first model according to the first data to obtain copper slag crystallization information includes: determining the interaction force between atoms of each element in the copper slag based on the first data; constructing an interaction potential energy surface between the elements according to the interaction force; According to the motion trajectory of atoms in each element of the interaction potential energy surface; Determining grain change information based on the motion trajectory; the grain change information is used to characterize the dynamic behavior or physical property changes of atoms in each element in the copper slag; The crystallization phenomenon is analyzed based on the grain change information to obtain the copper slag crystallization information.

5. The method according to claim 4, characterized in that The crystallization phenomenon analysis is performed based on the grain change information to obtain the copper slag crystallization information, including: Determine the change in the state of each element based on the grain change information, and obtain phase change information based on the change in the state of each element; the phase change information is used to characterize the change of each element in the copper slag from liquid to solid; determining the grain change state of each element in the copper slag during crystallization according to the grain change information, and generating grain growth information according to the grain change state; Determine the state of the interface region between each grain based on the grain change information to obtain grain boundary information; The phase change information, grain formation information and grain boundary information are sorted out to obtain copper slag crystallization information.

6. The method according to claim 1, characterized in that After simulating the crystallization of each element in the copper slag using a first model according to the first data to obtain the copper slag crystallization information, the method includes: Determining the temperature information corresponding to the crystallization of each element according to the copper slag crystallization information; The thermal conductivity is determined based on the temperature information; the thermal conductivity can affect the crystallization of each element in the copper slag.

7. The method according to claim 6, characterized in that After determining the thermal conductivity according to the temperature information, the method includes: Determining a corresponding crystal structure from the copper slag crystallization information according to the temperature information; the crystal structure is used to characterize the atomic arrangement of the copper slag under the temperature information; A correlation is established based on the crystal structure and thermal conductivity.

8. A copper slag crystallization process analysis device, characterized in that: include: A first data determining module, configured to determine first data; The first data is used to characterize the arrangement of elements in the copper slag and the initial crystallization conditions of each element; a copper slag crystallization information determination module, configured to perform a crystallization simulation of each element in the copper slag using a first model based on the first data to obtain copper slag crystallization information; the first model is configured to simulate a process in which each element melts and forms grains at a corresponding temperature by changing the temperature during the copper slag crystallization process; the copper slag crystallization information is configured to describe the shape and size of grains formed by each element in the copper slag, and the state of grain boundaries formed between different grains; The crystallization precipitation module is used to crystallize and precipitate various elements in the copper slag according to the copper slag crystallization information.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the copper slag crystallization process analysis method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the copper slag crystallization process analysis method according to any one of claims 1 to 7 when executed.

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