Research on diffusion wear mechanism of WC tool cutting Al2024 based on MD

Al2024 belongs to a typical Al-Cu-Mg series alloy. It has the advantages of high-strength, low-specific gravity, stress resistance, corrosion resistance, good heat resistance, and high fatigue resistance. It is widely used in aerospace, automobiles, ships, chemicals, and other fields. Aluminum alloys play a pivotal role in industry and manufacturing. Cemented carbide tools are often used in the processing of aluminum alloys, and diffusion wear is prone to occur during the processing. It is of great significance to study the diffusion phenomenon of WC tools in the process of cutting aluminum alloys for improving tool life and workpiece surface machining accuracy. In this paper, based on the molecular dynamics (MD) simulation method, the WC tool and the Al2024 model were established, the Morse potential parameters between the tool and the workpiece atoms were calculated, and the diffusion wear mechanism of the WC tool in the process of cutting Al2024 was studied. Through the displacement nephogram in the tool-worker X direction, it is found that the workpiece atoms have a tendency to diffuse to the tool. Using the mean square displacement (MSD) method, the diffusion velocities of Al, Cu, and Mg atoms in the workpiece were obtained. The results show that the activation energy of atomic vacancies at the grain boundary is smaller than that at the lattice, and the Al, Cu, and Mg atoms at the grain boundary of the workpiece are more likely to diffuse, and the diffusion rate of Mg atoms is the fastest. The total energy of single atoms in the cutting process was analyzed, and it was found that the energy required for Al, Cu, and Mg elements at the grain boundary of the workpiece to diffuse into the WC tool and the energy required for the Mg and Al elements at the workpiece lattice to diffuse into the WC tool were satisfied.


Introduction
2024 aluminum alloy is a typical aviation Al-Cu-Mg alloy invented by Alcoa in 1939, and it is also the first Al-Cu-Mg alloy found to have a yield strength close to 345 Mpa, because 2024 aluminum alloy has high strength and good fatigue resistance. Therefore, Al2024 is widely used to manufacture various high-load parts and components (but not including stamping forgings), such as skeleton parts, skins, bulkheads, ribs, spars, and rivets on aircraft below 150 °C working parts [1,2].
In the process of machining aluminum alloy, the problem of tool wear is always a big problem. It is affected by a variety of factors, and the cutting mechanism is complicated. At present, most of the research on the cutting mechanism of aluminum alloy cutting process, through the combination of finite element simulation and experiment, it is necessary to study tool wear from a microscopic perspective, which is of great significance for tool protection and workpiece surface quality improvement.
Molecular dynamics can track the motion trajectories of atoms from the atomic and molecular scale, amplify details that cannot be observed in macroscopic simulations and experiments, and establish nanoscale models to calculate various physical quantities. Therefore, it is widely used in chemistry, materials science and physics, and application [3].
In the 1950s, the world's first computer was born. Fermi established a simple system of 16 particles based on molecular dynamics and applied some basic potential function theory [4]. In 1957, Wainwright et al. [5] studied the equation of state of liquid and gas by establishing a molecular dynamics model of rigid spheres, which means that MD (molecular dynamics method) began to be applied to physical research. In 1967, Verlet [6] used the Verlet algorithm to apply classical Newtonian mechanics to molecular dynamics. In the 1990s, molecular dynamics really began to be applied to the field of precision machining. The Lawrence Livermore National Laboratory in the USA established a model of diamond nano-cutting copper to analyze the process of material removal from a microscopic perspective. In 1995, K. Maekawa et al. [7] used molecular dynamics to simulate the orthogonal nanofabrication of copper by diamond-like tools and simulated tool wear by reducing the condensation energy of carbon atoms. The cutting mechanism includes the interdiffusion of workpiece and tool atoms and the adhesion of wear particles to the tool. The effects of friction and tool wear on the cutting process in nanoscale machining were found to be similar to those observed in macroscale machining. In 2000, Te-Hua Fang et al. [8] established a three-dimensional molecular dynamics model of diamond cutting single-crystal copper to study the influence of tool shape and machining resistance on the cutting mechanism at the atomic scale. The potential function between the tool and the workpiece is simulated, and the cutting resistance increases with the depth of cut, and work hardening and stick-slip phenomena are also observed. In 2004, Shimizu J. [9] established a molecular dynamics model of ultrahigh acceleration and vibrationassisted cutting of aluminum and sets up a Morse potential function for the interaction between the workpiece and the tool. The results show that ultrahigh acceleration and vibration-assisted cutting can effectively reduce plastic flow and improve machined surface quality. In the same year, Tang Yulan [10] and others established molecular dynamics models of single-crystal silicon and single-crystal aluminum, respectively. Morse potential function was used between C and Al atoms, and Tersoff potential function was used between C and Si atoms. The cutting force, energy, and the machined surface were analyzed at the same time, and it was found that silicon was more prone to amorphous phase transformation and chip volume change than aluminum. In 2016, Zhang [11] analyzed the influence of different cutting parameters (including vibration parameters) on the cutting force and cutting temperature during nano-cutting of titanium alloys based on the technology of molecular dynamics and vibration-assisted cutting.
With the increasing development of nano-cutting, more and more experts and scholars have begun to study the friction and wear of cutting tools and the changes of microstructure through molecular dynamics methods, because tool wear has a great influence on the surface machining quality and machining accuracy of workpieces. big. In 2003, K. Cheng used the molecular dynamics simulation method to study the tool wear of diamond tools when cutting single-crystal silicon plates. At the same time, he carried out processing experiments on AMF to verify the MD simulation results. The results show that the basic wear mechanism of diamond is as follows: thermochemical wear [12]. In 2007, M. B. Cai studied the groove wear mechanism of diamond tools in the process of single-crystal silicon nano-cutting through molecular dynamics simulation during the cutting process and found that the bond length between single-crystal silicon atoms became shorter, resulting in higher hardness. The atomic group increases the wear of diamond tools [13]. In 2009, R. Narulkar established the nano-cutting simulation and experiment of diamond cutting iron and concluded that the wear of diamond is mainly caused by graphitization, and then, it will react with iron to form iron carbide [14]. In 2012, S. Goel [15] studied the wear mechanism of diamond tools in the process of single-point diamond turning silicon carbide based on molecular dynamics method and obtained good results by using radial distribution function and found that diamond tools appeared graphite in the cutting process. This phenomenon occurs based on the mutual grinding between two superhard materials. In the nano-cutting process, the workpiece and the tool, the chip and the tool will produce friction and extrusion, and the workpiece atoms will diffuse into the tool, causing the tool to produce diffusion wear. Numerous studies. In 2007, Han [16] conducted research on single-crystal aluminum nano-cutting. The simulation results show that with the increase of cutting depth, the contact area between the tool and the workpiece increases, and the diffusion wear of the tool increases. The effect of tool diffusion wear is small, and the accumulated chips that spread to the tool replace the tool cutting, which deteriorates the ultraprecision machined surface, increases the temperature of the cutting area, and aggravates the degree of tool diffusion wear. In 2018, Guojun Dong et al. [17] studied the wear mechanism of diamond tool precision cutting largediameter aluminum alloy mirror. It leads to the chemical wear of the diamond tool. The main part of the wear is the side of the tool, which is obtained by orthogonal experiments; the influence of the feed speed of the tool on the tool wear is greater than that of the cutting speed; through the single-factor experiment, it is concluded that the tool gap increases, and the tool wear is reduced. In 2020, Hao Zhaopeng et al. [18] established a molecular dynamics model for cutting Ni-Fe-Cr-Co-Cu nickel-based alloys with silicon carbide toughened alumina ceramic tools and analyzed the bonding wear and tear of the tool from the atomic point of view. In diffusion wear, the tool wear process was analyzed from the temperature, atomic displacement, coordination number, and crystal order. The wear theory of nano-cutting tools is perfected.
At present, in the nano-cutting process, some achievements have been made in the diffusion wear of tools, but most of the researches are aimed at diamond tools and single-crystal workpieces, and they are also limited by the potential function. In this paper, based on the MD (molecular dynamics) method, a WC tool cutting aluminum alloy 2024 model is established, and the tool and the workpiece are both polycrystalline models, the Morse potential function between the atoms of the tool and the workpiece is calculated, and the material removal process is observed. The influence of cutting force and cutting temperature on tool wear was studied, and the diffusion activation energy of workpiece atoms at different positions (grain boundary and lattice) was calculated by MD program, and the difficulty of workpiece atoms diffusing into the tool was obtained. At the same time, the total energy of single atoms in the cutting process is also calculated, and the actual situation of workpiece atoms entering the tool is judged by the total energy of single atoms.

WC tool model establishment
The tool material is WC, and the structure is hexagonal closest packing, with lattice constants a = 2.9 and b = 2.83. A WC polycrystalline tool was established by Atomsk with the grains randomly distributed in the crystal. The rake angle of the tool is 20°, the relief angle is 6°, and the total number of atoms is 4657. The shape, structure, and atomic species are shown in Fig. 1. The polycrystalline structure was analyzed using Ovito, as shown in Fig. 2.

Al2024 model establishment
The workpiece material is aluminum alloy, and a simplified model of Al-Cu-Mg ternary alloy is established. It can be seen from Table 1 that the three elements Al, Cu, and Mg occupy the mass fraction of Al2024, respectively. By formula [19] (1), the mass fraction of the three elements in Al2024 is recorrected.
After correction, the mass fraction of Al is 94.22%, the mass fraction of Cu is 4.24%, and the mass fraction of Mg is 1.54%.
Using formula [20] (2), the ratio of the atomic numbers of the three elements is 54:1:1.
The polycrystalline structure of Al element is established by Atomsk, and then atoms are randomly replaced, and the energy of the model is minimized to obtain an aluminum alloy workpiece that is closer to the real situation. The size of the workpiece is 10 × 10 × 6 nm, and the total number of atoms is 36,341. The structure is as follows shown in Fig. 3.

Determination of tool and workpiece potential functions
In this paper, the WC tool is a nonmetallic covalent bond, so the ABOP (analytical bond-order potential)/tersoff potential function [21] is used, which can more accurately describe the force of the atoms in the WC tool. The workpiece mainly uses the EAM potential function. Zhou et al. [22] developed a method to generate precise binary potentials by combining single-element potentials to form multicomponent alloy potentials. This tool is very useful for modeling metal alloys. The Al-Cu-Mg potential function fitted by this method is more suitable for aluminum alloys. At the same time, the Morse potential function is used between the workpiece and the tool atoms. Please refer to related materials [20,23,24]. The Morse potential parameters of the same element are obtained as shown in Table 2. The Morse potential parameters of different atoms are derived according to formula [25]: where D --binding energy (EV).
Apply an equivalent way to express the following: The two-atom potential parameters can be fitted by interpolation to obtain the following equation: The parameter r 0AB can be derived from the parameter AB : Finally, the Morse potential function between WC and aluminum alloy workpiece is obtained, some of which are referred to [26], as shown in Table 3.   Table 3 Morse potential parameters of different atoms

MD modeling and simulation
The WC tool and the workpiece are separately layered, namely Newtonian layer, constant temperature layer, and fixed layer. As shown in Fig. 4, the boundary layer plays a fixed role in the cutting process, which can reduce the boundary effect and maintain lattice symmetry; the boundary layer is set as a rigid body, which will not be destroyed during the cutting process; and in the constant temperature layer, the temperature is calibrated at regular intervals to simulate the heat transfer and dissipation in the real cutting environment and prevent the workpiece from overheating during processing. High; the Newtonian layer is the main cutting area, which is used to simulate the atomic motion trajectories during the cutting process. During the cutting process, set the X and Y as fixed boundaries, and set the Z direction as the periodic boundary. The specific cutting conditions are shown in Table 4.

Tool temperature analysis
As can be seen from Fig. 5, when the tool and the workpiece first contact, a large friction force is generated, and the strain energy released in the deformed lattice is converted into cutting heat, which makes the temperature of the cutting area rise, and a lot of heat is transmitted to the tool. The average temperature suddenly increased. With the progress of cutting, the average temperature of the tool has a process of slow decline. At this time, the tool cutting the workpiece is in a relatively stable state. The workpiece material softens at high temperature, and the cutting force decreases, which makes the temperature of the cutting area drop. Moreover, the tool-worker and tool-chip contact areas were stabilized, and the final average temperature of the tool was stabilized at about 400 K, which was about 100 °C for actual cutting, which was in line with the actual situation. It can also be seen from the figure that the temperature fluctuation of the tool before the tool surface is relatively large, and the fluctuation of the tool surface and the part of the tool tip is relatively small. The main reason is that the contact area of the tool surface and the chip is constantly changing, the heat conduction fluctuation is large, and the blade and the tool surface contact of the workpiece material are more uniform, so the heat change is little. When the temperature of the front tool surface peaks, the diffusion coefficient of atoms is larger, and the equilibrium vacancy concentration of the tool is higher; the workpiece and chip material atoms are easier to enter the surface and subsurface of the tool, so the

Analysis of cutting force and workpiece dislocation
Cutting force is also one of the important factors affecting tool wear. It can be seen from Fig. 6 that when the tool is in contact with the workpiece, the main cutting force F C of the tool increases significantly, because during the cutting process, the WC tool needs to destroy the aluminum alloy. The chemical bond between atoms overcomes the binding energy between atoms, so that the atoms of the workpiece move, breaking the original lattice of the atoms of the workpiece, and more and more atoms are in contact, and the cutting force is also increasing. At the same time, during the cutting process, a large number of dislocations are generated between the workpiece atoms, as shown in Fig. 7 the workpiece and the shear slip area of the chip. With the increase of the cutting distance, the atomic displacement of the workpiece also increases, the dislocation density also increases, and the internal energy is more complex; the lattice of the workpiece atoms will be deformed, destroyed, and reorganized, and the main cutting force of the tool will fluctuate in a small range. At the same time, it can be seen from the figure that the feed force and radial force are much smaller than the main cutting force.

Atomic displacement analysis
In the process of cutting aluminum alloy by WC, the displacement of Al, Cu, and Mg atoms is calibrated by molecular dynamics method, which can better understand the material removal process and tool wear. As shown in Fig. 8, different colors represent the magnitude of the displacement. When the tool is in contact with the workpiece, the workpiece material is squeezed and will move toward the tool, the local atomic spacing will change, the workpiece atoms will undergo plastic deformation, and part of the lattice will become disordered, which is easy to diffuse into the tool.
As the cutting progresses, more and more workpiece atoms move to the tool, forming a shear slip surface, and continue to move to this surface, eventually forming chips. When the workpiece atomic group accumulates to a certain extent, it will be removed from the workpiece surface.

Analysis of tool diffusion wear
The aluminum alloy 2024 established in this paper is polycrystalline, which is close to the usual existence mode of metals. Polycrystalline has multiple crystal directions, and grain boundaries are formed in the transition regions of different crystal directions. The arrangement form of atoms in the crystal boundaries is rather irregular. In the process of atomic diffusion, the diffusion activation energy of a single

Formation energy of atomic vacancies in the workpiece lattice
The formation of vacancies can directly reflect the ease with which vacancy defects are created. The vacancy formation energies of the workpiece atoms Al, Cu, and Mg at the lattice and grain boundaries were calculated. The specific calculation formula is as follows [27] (Fig. 9): where E(N,0) is the total energy of a vacancy-free crystal with N atoms, E(N-K,N) is the total energy of a crystal containing K vacancies and the remaining number of (c) 7nm Fig. 9 Polycrystalline workpiece atoms is N-K, and K is the number of vacancies where N is the number of atoms in the system before point defects are introduced.
Change the calculated boundary to PPP, perform an energy minimization on the model in LAMMPS, set the ensemble to NVT, calculate the total energy E(N,0) of the workpiece crystal, and randomly introduce a vacancy at the crystal lattice of the workpiece, as shown in the figure. As shown in 9, after the energy minimization relaxation is performed, the total energy of the workpiece after the introduction of vacancy defects is obtained as E (N-K,N). Using formula (9), the vacancies at the lattice of Al, Cu, and Mg elements are obtained. The formation energies are shown in Fig. 10 and are close to the vacancy formation energies of 0.76, 0.74, and 1.11 eV measured for aluminum, magnesium, and copper in literature [28]. The results show that the vacancy formation energy of Mg atoms at the lattice is higher than low.

Formation energy of atomic vacancies in grain boundaries of workpieces
In the same way, introduce a vacancy at the grain boundary of the workpiece, calculate the total energy change of the workpiece model before and after the introduction of the vacancy, and use the formula to obtain the atomic vacancy formation energy of the workpiece at the grain boundary.
The calculation results are shown in Fig. 11. By calculating the vacancy formation energies of Al, Cu, and Mg elements at the lattice and grain boundaries, it can be determined that the vacancy formation energies of these three elements at the grain boundaries are smaller than those at the lattice. The main reason is that yes the arrangement of the workpiece atoms in the lattice is more orderly, the potential energy between atoms is smaller, and the structure is more stable. If the atoms in the lattice are to be freed from the bondage of other atoms around, it obviously needs more energy for the crystal lattice. The atoms at the boundary have many defects, their structure is unstable, their average potential energy is high, and they are more prone to displacement, forming vacancies, and diffusing to low energy. At the same time, it can be seen that in the workpiece atoms, the vacancy formation energy of Mg atoms is lower, and it is easier to generate vacancies and diffuse. When the workpiece atoms form vacancies, the vacancies need to satisfy the vacancy migration energy before migration can occur.

Atomic vacancy migration energy of workpiece
Due to the complex structure of multielement workpieces, there are many vacancies and other defects, and migration is easy to occur during the cutting process. In this paper, the mean square displacement (MSD) method is used to obtain the Al and other defects at the cutting temperature of 300 K. The diffusion area of the three elements Cu and Mg can effectively determine which element is more likely to migrate. The resulting MSD curve is shown in Fig. 12.
According to Fig. 12, it can be concluded that at the temperature of 300 K, the diffusion area of Mg is larger than that of Al and Cu in the same time period, and the diffusion rate of Mg is faster. The main reason is that the melting point of Mg is relatively low, which is the easiest to achieve. At the melting point temperature, the atomic state is more active at this time, so the diffusion of Mg atoms is faster, and the melting point of Cu is about 1400 °C, so the diffusion of atoms is slower at this temperature. The following formula is used to obtain the diffusion migration energy.
First, the simulated diffusion coefficient D sim is obtained as follows: Therefore, the slope in the above figure is the absolute value of the effective diffusion coefficient D eff , and the Arrhenius relationship is as follows: Available, Among them, R is the gas constant, which is found to be 8.314 J/(mol × K). From this, it can be concluded that lnD eff and T are roughly a linear relationship. As shown in Fig. 13, the vacancy migration of Al was fitted by origin. The energy E m is 0.2544 eV, and the fitting effect is good.
In the same way, the migration energies of copper and magnesium atoms can be obtained as follows.
• Calculation results: The vacancy migration energy E m of Cu atoms is 0.2548 ev, and the vacancy migration energy E m of Mg atoms is 0.2339 ev. From Figs. 13, 14, and 15, it can be seen that the three elements of Al, Cu, and Mg are in the cut- ting process. The vacancy migration energies are not much different, and the vacancy migration energy of Mg atoms is the smallest, and migration occurs most easily.

Atomic diffusion activation energy of workpiece
The diffusion activation energy of the atom is calculated by formula (14), and the vacancy formation energy and the vacancy migration energy are summed.  Fig. 16, Q1 is the diffusion activation energy of each element at the grain boundary, and Q 2 is the diffusion activation energy of each element in the lattice. It can be seen that the diffusion activation energy at the grain boundary is smaller than the diffusion activation energy at the lattice, indicating that the three elements are more likely to diffuse at the grain boundary, because the structure at the grain boundary is relatively unstable, and diffusion can occur under the impetus of extremely small energy; while the lattice atoms are arranged in an orderly manner, the structure is stable, and it is not easy to generate vacancies, where migration occurs and often requires higher energies.
The diffusion activation energy of the three elements is not much different, Q 1Mg < Q 1Al < Q 1Cu ; the Mg atom at the grain boundary of the workpiece needs the lowest diffusion energy and is most likely to diffuse.

WC tool diffusion conditions
Since the tool is a polycrystalline tool built with Atomsk, large deformation of the tool occurs at the grain boundaries. By calculating the energy required to generate vacancies in different positions of WC, it can be judged whether the workpiece atoms migrate to the lattice or grain boundary of the tool, and the gap formation energy of different workpiece atoms in the tool can be calculated at the same time to determine whether the workpiece atoms can form a gap structure with the tool atoms.

Vacancy formation energy at WC lattice and grain boundaries
For the polycrystalline model WC tool, the single vacancy formation energy of W and C atoms is mainly studied, and vacancies are randomly formed in the tool. According to the calculation formula, the vacancy formation energy of the tool at the lattice and grain boundaries is obtained, as shown in Table 5, and compared with the related literature [20]. By calculating the vacancy formation energy at the lattice and grain boundaries of the WC tool, it can be seen that the vacancy formation energy at the grain boundary is smaller than that at the lattice, and vacancies are more likely to be formed at the grain boundary. It is found that the vacancy formation energy of W atoms is smaller than that of C atoms, and W is easier to form vacancies than C atoms. Generally speaking, atoms in the workpiece generate vacancies and migrate and diffuse into the grain boundaries of the tool more easily.

Activation energy of interstitial atoms in WC lattice
This paper mainly studies the diffusion wear of the tool and further judges whether the migrated workpiece atoms will enter the tool and form a gap structure with the tool atoms. The gap formation energy E i of the three elements Al, Cu, and Mg in WC can be calculated by the following formula calculated:   Fig. 16 The diffusion activation energy of three elements in grain boundary and lattice Among them, E 2 is the energy after gap formation, N is the number of atomic systems, E i is the energy before gap formation, and the obtained gap formation energy E i is as follows.
From Table 6, it can be seen that the interstitial formation energy of Mg atoms is the lowest, and Mg atoms are easier to form interstitial structures than Al and Cu. One important reason is that the structures of Al and Cu atoms are face-centered cubic (FCC), and Mg the crystal structure of atoms is hexagonal close-packed (HCP). Studies have shown [29] that in the face-centered cubic structure, the atoms are arranged closely, and it is difficult for the atoms to form a gap structure during the movement process. At the same time, the activation energy required by the exchange mechanism is relatively large. Diffusion, which leads to exchange of atomic positions, hardly occurs; therefore, Mg is the element most likely to generate interstitial structures.

Single-atom energy analysis during WC cutting of aluminum alloys
The workpiece atoms generate vacancies and migrate, the tool atoms generate vacancies, and the workpiece atoms and the tool generate gap structures, all of which need to provide energy for atomic diffusion in the process of cutting aluminum alloys by the WC tool. In Fig. 16a, the tool and the workpiece are just in contact. At this time, the total energy of the single atom of the workpiece and the tool is at most 0.61 eV, and the atoms with this energy are relatively few, most of which are distributed at the grain boundary, and compared with the vacancy formation energy obtained above, it can be concluded that a small amount of Mg atoms at the lattice and grain boundaries form vacancies, and only a small amount of Al atoms at the grain boundary has a single-atom energy that meets the vacancy formation energy, which may form vacancies, but it is possible that the modeling itself creates vacancy defects in the crystal. When the tool stroke reaches 3 nm, the maximum single-atom total energy is 1.25 eV, and the atoms with this energy are distributed in the grain boundary and the tool-chip contact interface of the workpiece, and the number is relatively large. At this time, the maximum single-atom total energy reaches the vacancy formation energy between the lattice and grain boundary of Al and Mg, and the vacancy formation energy of Cu atom at the grain boundary is achieved, and the diffusion activation energy of Al and Mg at the lattice and grain boundary has also been reached, but the Cu atom has not been reached. At this time, some atoms of Al and Mg diffuse to the surface and inside of the tool, and the tool produces a slight diffusion wear. When the tool stroke is 5 nm, the atomic energy of the tool-worker reaches 1.49 eV, which can promote Al, Cu, and Mg to generate vacancies in the grain boundaries and lattices. The tool further diffused, and the Cu atoms at the grain boundaries also diffused to the tool. When the tool stroke is 7 nm, the maximum single-atom energy of the tool-worker atom is 1.67 eV, and the energy value can only be reached. The diffusion of Al and Mg atoms in the lattice and grain boundaries to the tool does not reach the diffusion of Cu atoms in the lattice activation energy, so only the Cu atoms at the grain boundaries diffuse. Tool diffusion wear increases with tool travel. According to the formation energy of the gap between the three elements of Al, Cu, and Mg and the tool atom, it is easy for the Mg atom to form a gap structure with the tool atom, but the maximum energy of the single atom generated in the process of WC cutting aluminum alloy comes from See, not enough for the Mg atoms to bond with the cutter atoms to form the interstitial structure (Fig. 17).

Specific analysis of the diffusion process
According to (a) in Fig. 18, we can see that in the process of WC cutting aluminum alloy, the workpiece atoms first generate vacancies under the action of single atomic energy and then migrate and diffuse to the surface of the tool. At the same time, the tool-chip interface exists. In potential energy difference, the potential energy of the tool is lower than the potential energy of the chip, which makes the workpiece atoms move to the tool. During the initial cutting process, most of the workpiece atoms diffuse to the surface of the tool, which causes the tool to produce diffusion wear. At the same time, the diffused atoms increase. The friction coefficient of the chip interface, the cutting force, and the cutting temperature increases, which accelerates the diffusion of workpiece atoms, and the degree of tool wear becomes more and more serious. In figure b, as the cutting progresses, it can be seen that the number of workpiece atoms diffused to the surface and inside of the tool increases, and the diffusion wear of the tool increases. During the cutting process, the tool is also squeezed by the workpiece and the chip atoms, which causes the internal lattice to change. The tool has a hexagonal crystal structure, so the coordination number of the tool is 12. During the extrusion process of the workpiece, the coordination number occurs. With the continuous change, it is obvious that the coordination number of the tool is greater than 12, and the coordination number is 0. This is very likely that the workpiece atoms enter the tool, and the tool atoms  (c) 5nm (d) 7nm are in a critical state of lattice fracture. There is a case of falling off. From figure c, it can be seen that the workpiece atoms diffuse into the inside of the tool, and the W and C atoms that are about to fall off can also be seen. From figures a and b, it can also be seen that the tool in the atomic bonds is broken, and the tool atoms are sloughed off to the workpiece surface.

Conclusions
In this paper, based on the molecular dynamics method, a WC cutting aluminum alloy model is established, and the changes of physical quantities during the material removal process are studied, and the diffusion wear of the tool during the cutting process is mainly explored. During the cutting process, the tool temperature increases first and then decreases sharply and finally fluctuates within a certain range. The relationship between the three-way cutting force is as follows: F c > F p > F f . The workpiece dislocation line is densely in the toolworker contact zone and shear slip zone, which makes the cutting force increase. By analyzing the displacement nephogram, it is found that the workpiece atoms have a tendency to diffuse to the tool. The diffusion wear in the process of WC tool cutting aluminum alloy was specifically explored, and it was found that atoms at the grain boundary of the workpiece were more likely to diffuse than those at the crystal lattice, and the order of atomic diffusion rate was Mg > Al > Cu: the energy of single atom in the cutting process was enough for Mg, Al, and Cu atoms at the grain boundary of the workpiece and Mg and Al atoms at the crystal lattice to diffuse to the tool. With the increase of cutting distance, the diffusion wear of WC tool becomes more and more serious.