Nanofluid-assisted single crystal silicon cutting method based on molecular dynamics simulation and computer system

Abstract

The application relates to the computer technical field, in particular to a nanofluid-assisted monocrystalline silicon cutting method based on molecular dynamics simulation and a computer system. By establishing a model of monocrystalline silicon, abrasive particles and nanofluid, cutting parameters in a nanofluid-assisted monocrystalline silicon cutting process are obtained through molecular dynamics simulation, the reduction effect of nanofluid-assisted lubrication on processing temperature and stress is intuitively quantified, and the feasibility and advantages of the nanofluid-assisted cutting monocrystalline silicon method are added. The application aims to solve the problem of how to simulate nanofluid-assisted monocrystalline silicon cutting through molecular dynamics simulation.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a nanofluid-assisted single-crystal silicon cutting method and computer system based on molecular dynamics simulation. Background Technology

[0002] Monocrystalline silicon, a commonly used semiconductor material, is widely applied in photovoltaics, electronic devices, and other fields. The processing quality of monocrystalline silicon has a crucial impact on the performance and reliability of subsequent components. Wire sawing is currently the main method for processing monocrystalline silicon. Diamond abrasive grains are fixed on the surface of a metal wire, and the monocrystalline silicon is repeatedly rubbed against it, eventually sawing the monocrystalline silicon into thin slices. However, in this process, friction and wear between the abrasive grains and the monocrystalline silicon directly affect the cutting efficiency and the surface quality of the monocrystalline silicon. To improve the cutting effect and reduce friction, lubricants are usually used to reduce friction and wear, cool the cutting area, and remove some of the chips.

[0003] In related technical solutions, molecular dynamics simulation is a computer simulation method for studying the motion of matter at the atomic and molecular scale. It can reveal the physicochemical phenomena of materials during processing at the microscopic level, providing theoretical guidance for optimizing processing techniques, improving processing efficiency, and enhancing material properties. Specifically applied to the wire sawing process of single-crystal silicon, molecular dynamics simulation can provide in-depth analysis of the interatomic interactions and mechanisms during wire sawing under nanodiamond lubrication.

[0004] In the process of conceiving and realizing this application, the inventors discovered that nano-diamond (ND) fluid lubricant (hereinafter referred to as nanofluid) has unique physicochemical properties, such as high hardness, good wear resistance and chemical stability. However, current methods lack a nanofluid-assisted single-crystal silicon cutting method based on molecular dynamics simulation.

[0005] In view of this, this application proposes a nanofluid-assisted single-crystal silicon cutting method based on molecular dynamics simulation, aiming to optimize the single-crystal silicon wire saw cutting process and provide technical support for the application of nanodiamond fluid lubrication in single-crystal silicon cutting. Summary of the Invention

[0006] The main objective of this application is to provide a nanofluid-assisted single-crystal silicon cutting method based on molecular dynamics simulation, aiming to solve the problem of how to simulate nanofluid-assisted single-crystal silicon cutting through molecular dynamics simulation.

[0007] To achieve the above objectives, this application provides a nanofluid-assisted single-crystal silicon cutting method based on molecular dynamics simulation, the method comprising: S10, initialize the workpiece region and the abrasive region, wherein the workpiece region includes a boundary layer, a thermostatic layer, a Newton layer and a fluid layer, the boundary layer is used to keep the atoms fixed, the thermostatic layer is used to keep the atomic temperature constant, the Newton layer is used to constrain the atoms to follow Newton's second law, and the fluid layer is used to generate nanodiamond particles that meet the preset number and preset size. S20: Obtain the atomic grouping identifier of the single crystal silicon workpiece to be cut; fill the boundary layer, the isothermal layer and the Newton layer with atoms bearing the first atomic grouping identifier; fill the abrasive region with atoms bearing the second atomic grouping identifier; fill the fluid layer with atoms bearing the third and fourth atomic grouping identifiers; and generate nanodiamond particles in the fluid layer using atoms bearing the fifth atomic grouping identifier. S30, a force field is constructed by calling preset force field parameters, and constraints are set in the fluid layer to fix the bond length and bond angle of the nanodiamond particles. The force field parameters include the Tersoff potential function and the Lanner-Jones potential function. The Tersoff potential function is used to simulate the strong interaction between silicon-silicon covalent bonds and silicon-carbon covalent bonds, and the Lanner-Jones potential function is used to simulate the weak interaction and electrostatic interaction. S40 calls the energy minimization function to minimize the simulation energy; S50, obtain a preset initial temperature, and adjust the velocity of all atoms in the abrasive region to the velocity corresponding to the preset initial temperature; S60, call the micro-regular constraint function to configure the atoms in the Newton layer, the isothermal layer, and the fluid layer, and call the regular constraint function to configure the atoms in the boundary layer; S70, start the monocrystalline silicon cutting simulation process, obtain the cutting parameters generated in the monocrystalline silicon cutting simulation process, and cut the monocrystalline silicon workpiece to be cut based on the cutting parameters.

[0008] Optionally, the first atomic group identifier is characterized as silicon atoms, the second atomic group identifier is characterized as carbon atoms, the third atomic group identifier is characterized as oxygen atoms, the fourth atomic group identifier is characterized as hydrogen atoms, and the fifth atomic group identifier is characterized as nanodiamond atoms.

[0009] Optionally, before step S10, the method further includes: Configure basic parameters, including: system unit system, spatial dimension, boundary conditions, time step, atom type, and neighbor list parameter configuration.

[0010] Optionally, in S10, the workpiece region has a size of 270×120×180Å, and the fluid layer has a size of 270×120×5Å.

[0011] Optionally, in S30, the interaction potential between the bond length and the bond angle is a harmonic potential, which is suitable for simulating the stretching effect between chemical bonds and the bending effect of chemical bond angles. The force constant is set to 1000, the equilibrium bond length is set to 1 Å, and the equilibrium bond angle is set to 109.47 degrees. The constraints set for the fluid layer include: a constraint precision of 1e-4, a maximum number of iterations of 10, a maximum number of attempts of 10000, and a command to clear atomic overlaps.

[0012] Optionally, in S40, the energy minimization function is set using the conjugate gradient method.

[0013] Optionally, the S60 includes: The micro-regular constraint function is invoked to keep the number of atoms, volume, and energy of atoms in the Newtonian layer, the isothermal layer, and the fluid layer constant. The regular constraint function is invoked to keep the number of atoms, volume, and energy temperature of atoms in the boundary layer constant.

[0014] Optionally, the cutting parameters include temperature, paradigmatic equivalent stress, cutting force, dislocations, and potential and kinetic energy distribution.

[0015] Optionally, in step S70, the step of cutting the single-crystal silicon workpiece based on the cutting parameters includes: Based on the temperature, paradigm equivalent stress, cutting force, dislocation, potential energy and kinetic energy distribution in the cutting parameters, the target process parameters in the actual cutting process are determined. The target process parameters include cutting speed, nanofluid volume fraction and nanofluid particle size. The cutting equipment is controlled to operate in a state that meets the target process parameters in order to perform a cutting operation on the monocrystalline silicon workpiece to be cut.

[0016] In addition, to achieve the above objectives, this application also provides a computer system comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the nanofluid-assisted single-crystal silicon cutting method based on molecular dynamics simulation as described in any of the preceding claims.

[0017] This application has at least the following beneficial effects: 1. Deeper understanding of microscopic mechanisms: This invention uses molecular dynamics to conduct simulations from a microscopic perspective. Compared with macroscopic studies, this invention considers the unique atomic effects at the microscopic level and explores the interaction between nanofluids and single-crystal silicon at the microscopic level, which is closer to the actual processing conditions and the experimental results are more accurate.

[0018] 2. Intuitive and reliable cutting performance analysis: This invention establishes a model of single-crystal silicon, abrasive particles, and nanofluids. Through molecular dynamics simulation, stress and temperature cloud maps are obtained during the cutting process. The effect of nanofluid-assisted lubrication on reducing processing temperature and stress is intuitively quantified, proving the feasibility and advantages of adding nanofluids to assist in cutting single-crystal silicon.

[0019] 3. Reduced experimental costs: The experimental conditions for single-crystal silicon wire saw cutting are harsh, and the construction of an experimental platform requires high costs. The simulation method of this invention is applicable to Windows and Linux systems, with a flexible computing environment. It eliminates the need to conduct a large number of actual cutting experiments, significantly reducing experimental costs and saving experimental time. Attached Figure Description

[0020] Figure 1 This is a schematic flowchart of the nanofluid-assisted single-crystal silicon cutting method based on molecular dynamics simulation involved in the embodiments of this application; Figure 2 This is a molecular dynamics simulation model diagram of the simulated nanofluid-assisted cutting of single-crystal silicon involved in the embodiments of this application; Figure 3 This is a molecular dynamics simulation model diagram of fluidless-assisted cutting of single-crystal silicon, as described in the embodiments of this application. Figure 4 This is a cross-sectional view of the motion trajectory of simulated nanofluid-assisted cutting of single-crystal silicon according to an embodiment of this application; Figure 5 This is a temperature distribution cloud map of nanofluid-assisted cutting of single-crystal silicon according to an embodiment of this application; Figure 6 This is a temperature distribution cloud map of single-crystal silicon cut without nanofluid-assisted cutting, as described in the embodiments of this application. Figure 7 This is a stress distribution cloud map of nanofluid-assisted cutting of single-crystal silicon according to an embodiment of this application; Figure 8 This is a stress distribution cloud map of single-crystal silicon cut without nanofluid-assisted cutting, as described in the embodiments of this application. Figure 9 This is a schematic diagram of the hardware operating environment of the computer system involved in the embodiments of this application.

[0021] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0022] To better understand the above technical solutions, exemplary embodiments of this disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of this disclosure to those skilled in the art.

[0023] First Embodiment Reference Figure 1 This embodiment provides a nanofluid-assisted single-crystal silicon cutting method based on molecular dynamics simulation. In this embodiment, the molecular dynamics simulation environment parameters for nanodiamond-assisted cutting are set using LAMMPS software.

[0024] As an optional pre-configuration scheme, basic parameters are configured, including: system unit system, spatial dimension, boundary conditions, time step, atom type, and neighbor list parameter configuration. Specifically, the system unit is pre-defined as metal, the spatial dimension as three-dimensional, the boundary conditions as ppp periodic boundary conditions, and the time step as 0.005 ps. Due to the bond angles of water molecules, the atom type is set to full, and the neighbor list update rule is to start updating after 5 steps, and then update the neighbor list once every 1 step thereafter. The method includes the following steps: S10, initialize the workpiece region and the abrasive region, wherein the workpiece region includes a boundary layer, a thermostatic layer, a Newton layer and a fluid layer, the boundary layer is used to keep the atoms fixed, the thermostatic layer is used to keep the atomic temperature constant, the Newton layer is used to constrain the atoms to follow Newton's second law, and the fluid layer is used to generate nanodiamond particles that meet the preset number and preset size. In this embodiment, the established workpiece region and abrasive region are first initialized. The boundary layer, isothermal layer, Newton layer, and fluid layer of the single-crystal silicon workpiece are established separately. After each region is established individually, they are combined into the workpiece region using the unio instruction. The boundary layer keeps the atoms fixed, the isothermal layer keeps the atomic temperature constant, and the Newton layer atoms obey Newton's second law.

[0025] In some alternative implementations, the workpiece region size is 270×120×5Å, and the radius of the established abrasive region is 20Å.

[0026] In some alternative implementations, the fluid layer size is 270×120×5Å, a specified number of nanodiamond particles are generated using the label loop command, and the number and radius of the nanodiamond particles to be generated are set using the variable command. For example, the number can be set to 30 and the radius to be 6Å.

[0027] S20: Obtain the atomic grouping identifier of the single crystal silicon workpiece to be cut; fill the boundary layer, the isothermal layer and the Newton layer with atoms bearing the first atomic grouping identifier; fill the abrasive region with atoms bearing the second atomic grouping identifier; fill the fluid layer with atoms bearing the third and fourth atomic grouping identifiers; and generate nanodiamond particles in the fluid layer using atoms bearing the fifth atomic grouping identifier. In this embodiment, we pre-configure the corresponding lattice constant and atomic mass for each type of atom in the single-crystal silicon workpiece to be cut, and assign a unique atomic grouping identifier based on the type of atom. After initializing the region, we can complete the classification of the single-crystal silicon workpiece to be cut by obtaining the atomic grouping identifiers of these single-crystal silicon workpieces to be cut, and assign atoms with different identifiers to different positions in the workpiece region to complete the creation of the simulation box.

[0028] Further and optionally, the atomic characterization of the first atomic group identifier is silicon atom, the atomic characterization of the second atomic group identifier is carbon atom, the atomic characterization of the third atomic group identifier is oxygen atom, the atomic characterization of the fourth atomic group identifier is hydrogen atom, and the atomic characterization of the fifth atomic group identifier is nanodiamond atom.

[0029] In addition, during the creation of the simulation box, a water molecule template (using the SPC / E water molecule model in this embodiment) is read, and the template is read using the molecule command to fill the fluid layer with 3000 water molecules.

[0030] S30, a force field is constructed by calling preset force field parameters, and constraints are set in the fluid layer to fix the bond length and bond angle of the nanodiamond particles. The force field parameters include the Tersoff potential function and the Lanner-Jones potential function. The Tersoff potential function is used to simulate the strong interaction between silicon-silicon covalent bonds and silicon-carbon covalent bonds, and the Lanner-Jones potential function is used to simulate the weak interaction and electrostatic interaction. In this embodiment, after the simulation box is created, the set position parameters are called to complete the position initialization.

[0031] Optionally, the interaction potential between the bond length and the bond angle is a harmonic potential, which is suitable for simulating the stretching effect between chemical bonds and the bending effect of chemical bond angles. The force constant is set to 1000, the equilibrium bond length is set to 1 Å, and the equilibrium bond angle is set to 109.47 degrees. The constraints set for the fluid layer include: a constraint precision of 1e-4, a maximum number of iterations of 10, a maximum number of attempts of 10000, and a command to clear atomic overlaps.

[0032] S40 calls the energy minimization function to minimize the simulation energy; In this step, energy minimization is performed on all atoms in the system to eliminate unreasonable structures in the model.

[0033] In some alternative implementations, the min_style directive is used to set the energy minimization method, which is the conjugate gradient method (cg), and the minimize directive is used to perform energy minimization.

[0034] S50, obtain a preset initial temperature, and adjust the velocity of all atoms in the abrasive region to the velocity corresponding to the preset initial temperature; In this step, after minimizing the energy, temperature initialization is performed. The temperature of the system is calculated based on the atomic velocities, so temperature initialization is equivalent to initializing the atomic velocities.

[0035] In some alternative implementations, the initial temperature is preset to 300K, and the velocity instruction is used to assign an initial velocity to all atoms.

[0036] S60, call the micro-regular constraint function to configure the atoms in the Newton layer, the isothermal layer, and the fluid layer, and call the regular constraint function to configure the atoms in the boundary layer; This step involves relaxation. The atoms in the Newtonian layer, isothermal layer, and fluid layer are set to micro-canonical constraints (NVE), i.e., constant particle number N, volume V, and energy E, with no temperature control. Other atoms are set to canonical constraints (NVT), i.e., constant particle number N, volume V, and temperature T. This allows for full relaxation of the simulation system, minimizing system energy and achieving a stable structure. The boundary layer is fixed, with atomic velocities and forces set to 0 to reduce boundary effects.

[0037] In some alternative implementations, "Berendsen" temperature control is set for the atoms in the isothermal layer, with a target temperature of 100K and a temperature coupling coefficient of 0.1.

[0038] S70, start the monocrystalline silicon cutting simulation process, obtain the cutting parameters generated in the monocrystalline silicon cutting simulation process, and cut the monocrystalline silicon workpiece to be cut based on the cutting parameters.

[0039] In this embodiment, after completing the above steps, a single-crystal silicon cutting simulation process is started to obtain the cutting parameters generated in the single-crystal silicon cutting simulation process, so as to cut the single-crystal silicon workpiece to be cut based on the cutting parameters.

[0040] In some alternative implementations, the cutting parameters include temperature, paradigmatic equivalent stress, cutting force, dislocations, and potential and kinetic energy distribution.

[0041] In some alternative implementations, the spherical abrasive particles are set to move horizontally along the negative x-axis, the output results are processed and recorded, and the OVITO software is used for visualization.

[0042] In some alternative implementations, the target process parameters in the actual cutting process are determined based on the temperature, paradigm equivalent stress, cutting force, dislocation, potential energy and kinetic energy distribution in the cutting parameters. The target process parameters include cutting speed, nanofluid volume fraction and nanofluid particle size. The cutting equipment is controlled to operate in a state that meets the target process parameters in order to perform a cutting operation on the monocrystalline silicon workpiece to be cut.

[0043] For example, refer to Figure 2-8 The following diagrams are shown respectively: molecular dynamics simulation model diagram of simulating nanofluid-assisted cutting of single-crystal silicon, molecular dynamics simulation model diagram of simulating non-fluid-assisted cutting of single-crystal silicon, motion trajectory profile diagram of simulating nanofluid-assisted cutting of single-crystal silicon, temperature distribution cloud map of nanofluid-assisted cutting of single-crystal silicon, temperature distribution cloud map of non-nanofluid-assisted cutting of single-crystal silicon, stress distribution cloud map of nanofluid-assisted cutting of single-crystal silicon, and stress distribution cloud map of non-nanofluid-assisted cutting of single-crystal silicon.

[0044] Specifically, Figure 2 This is a molecular dynamics simulation model of nanofluid-assisted cutting of single-crystal silicon. The workpiece part is divided into a boundary layer (red), a isothermal layer (blue), and a Newtonian layer (yellow). The fluid layer region contains ND particles (green) and water molecules (light blue). In the figure, the water molecules exhibit a non-uniform aggregated distribution after passing through the energy minimum and forming a discrete cluster structure. The abrasive particles are spherical (purple).

[0045] Figure 3 This is a simulation model of molecular dynamics of dry cutting of single-crystal silicon without nanofluid assistance. The workpiece region and the abrasive region in the figure are shown. Figure 2 Consistent with the simulated dry cutting state, forming a contrast with nanofluid-assisted cutting.

[0046] Figure 4 This is a cross-sectional view of the motion trajectory of nanofluid-assisted cutting of single-crystal silicon. In the figure, the abrasive particles move horizontally along the negative x-axis, simulating the process of abrasive particles cutting single-crystal silicon.

[0047] Figure 5 and Figure 6 The atomic temperature distribution cloud maps of the two models show that the high-temperature region is mainly concentrated at the crescent-shaped surface where the abrasive grains contact the workpiece. The atomic temperature during nanofluid-assisted cutting is lower than that during dry cutting, and the range of the high-temperature region is smaller than that during dry cutting. This proves that nanofluid-assisted cutting of single-crystal silicon has heat conduction and cooling effects.

[0048] Figure 7 and Figure 8 The atomic stress distribution cloud maps of the two models show that the stress is mainly concentrated at the contact point between the abrasive grains and the workpiece. Furthermore, the stress range and intensity under nanofluid-assisted cutting are smaller, indicating that nanofluid-assisted cutting of single-crystal silicon has a buffering and lubricating effect.

[0049] In the technical solution provided in this embodiment, a model of single-crystal silicon, abrasive particles, and nanofluid is established. The cutting parameters in the nanofluid-assisted single-crystal silicon cutting process are obtained through molecular dynamics simulation. The effect of nanofluid-assisted lubrication on reducing processing temperature and stress is intuitively quantified, thereby demonstrating the feasibility and advantages of the nanofluid-assisted single-crystal silicon cutting method.

[0050] Second Embodiment Based on the first embodiment, in this embodiment, monocrystalline silicon can be replaced with other hard and brittle materials, such as silicon carbide, monocrystalline copper, etc. The values ​​of temperature, linear velocity, and other conditions in the processing depend on the experience of the processor. The potential function of the replaced material is replaced with a potential function suitable for this material. Alternatively, the nanodiamond particles in the fluid can be replaced with other nanoparticles, such as Al2O3, SiO2, etc., while the other steps remain unchanged.

[0051] As one implementation scheme, Figure 9 This is a schematic diagram of the hardware operating environment of the computer system involved in the embodiments of this application.

[0052] like Figure 9 As shown, the computer system may include: a processor 1001, such as a CPU; a memory 1005; a user interface 1003; a network interface 1004; and a communication bus 1002. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen and an input unit such as a keyboard. Optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be high-speed RAM or non-volatile memory, such as a disk drive. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0053] Those skilled in the art will understand that Figure 9 The computer system architecture shown does not constitute a limitation on the computer system and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0054] like Figure 9 As shown, the memory 1005, as a storage medium, may include an operating system, a network communication module, a user interface module, and computer programs. The operating system is a program that manages and controls the hardware and software resources of the computer system, as well as the operation of the computer programs and other software or programs.

[0055] exist Figure 9 In the computer system shown, the user interface 1003 is mainly used to connect to the terminal and communicate with the terminal; the network interface 1004 is mainly used to communicate with the backend server; and the processor 1001 can be used to call the computer program stored in the memory 1005.

[0056] In this embodiment, the computer system includes: a memory 1005, a processor 1001, and a computer program stored in the memory and executable on the processor, wherein: When processor 1001 calls a computer program stored in memory 1005, it performs the following operations: S10, initialize the workpiece region and the abrasive region, wherein the workpiece region includes a boundary layer, a thermostatic layer, a Newton layer and a fluid layer, the boundary layer is used to keep the atoms fixed, the thermostatic layer is used to keep the atomic temperature constant, the Newton layer is used to constrain the atoms to follow Newton's second law, and the fluid layer is used to generate nanodiamond particles that meet the preset number and preset size. S20: Obtain the atomic grouping identifier of the single crystal silicon workpiece to be cut; fill the boundary layer, the isothermal layer and the Newton layer with atoms bearing the first atomic grouping identifier; fill the abrasive region with atoms bearing the second atomic grouping identifier; fill the fluid layer with atoms bearing the third and fourth atomic grouping identifiers; and generate nanodiamond particles in the fluid layer using atoms bearing the fifth atomic grouping identifier. S30, a force field is constructed by calling preset force field parameters, and constraints are set in the fluid layer to fix the bond length and bond angle of the nanodiamond particles. The force field parameters include the Tersoff potential function and the Lanner-Jones potential function. The Tersoff potential function is used to simulate the strong interaction between silicon-silicon covalent bonds and silicon-carbon covalent bonds, and the Lanner-Jones potential function is used to simulate the weak interaction and electrostatic interaction. S40 calls the energy minimization function to minimize the simulation energy; S50, obtain a preset initial temperature, and adjust the velocity of all atoms in the abrasive region to the velocity corresponding to the preset initial temperature; S60, call the micro-regular constraint function to configure the atoms in the Newton layer, the isothermal layer, and the fluid layer, and call the regular constraint function to configure the atoms in the boundary layer; S70, start the monocrystalline silicon cutting simulation process, obtain the cutting parameters generated in the monocrystalline silicon cutting simulation process, and cut the monocrystalline silicon workpiece to be cut based on the cutting parameters.

[0057] It should be noted that, since the storage medium provided in the embodiments of this application is the storage medium used to implement the methods of the embodiments of this application, those skilled in the art can understand the specific structure and variations of the storage medium based on the methods described in the embodiments of this application, and therefore will not be repeated here. All storage media used in the methods of the embodiments of this application fall within the scope of protection of this application.

[0058] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0059] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0060] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0061] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0062] It should be noted that any reference signs placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. This application can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0063] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0064] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A nanofluid-assisted single-crystal silicon cutting method based on molecular dynamics simulation, characterized in that, The method includes the following steps: S10, initialize the workpiece region and the abrasive region, wherein the workpiece region includes a boundary layer, a thermostatic layer, a Newton layer and a fluid layer, the boundary layer is used to keep the atoms fixed, the thermostatic layer is used to keep the atomic temperature constant, the Newton layer is used to constrain the atoms to follow Newton's second law, and the fluid layer is used to generate nanodiamond particles that meet the preset number and preset size. S20: Obtain the atomic grouping identifier of the single crystal silicon workpiece to be cut; fill the boundary layer, the isothermal layer and the Newton layer with atoms bearing the first atomic grouping identifier; fill the abrasive region with atoms bearing the second atomic grouping identifier; fill the fluid layer with atoms bearing the third and fourth atomic grouping identifiers; and generate nanodiamond particles in the fluid layer using atoms bearing the fifth atomic grouping identifier. S30, a force field is constructed by calling preset force field parameters, and constraints are set in the fluid layer to fix the bond length and bond angle of the nanodiamond particles. The force field parameters include the Tersoff potential function and the Lanner-Jones potential function. The Tersoff potential function is used to simulate the strong interaction between silicon-silicon covalent bonds and silicon-carbon covalent bonds, and the Lanner-Jones potential function is used to simulate the weak interaction and electrostatic interaction. S40 calls the energy minimization function to minimize the simulation energy; S50, obtain a preset initial temperature, and adjust the velocity of all atoms in the abrasive region to the velocity corresponding to the preset initial temperature; S60, call the micro-regular constraint function to configure the atoms in the Newton layer, the isothermal layer, and the fluid layer, and call the regular constraint function to configure the atoms in the boundary layer; S70, start the monocrystalline silicon cutting simulation process, obtain the cutting parameters generated in the monocrystalline silicon cutting simulation process, and cut the monocrystalline silicon workpiece to be cut based on the cutting parameters.

2. The method as described in claim 1, characterized in that, The first atomic group identifier is characterized as silicon atoms, the second atomic group identifier is characterized as carbon atoms, the third atomic group identifier is characterized as oxygen atoms, the fourth atomic group identifier is characterized as hydrogen atoms, and the fifth atomic group identifier is characterized as nanodiamond atoms.

3. The method as described in claim 1, characterized in that, Before step S10, the method further includes: Configure basic parameters, including: system unit system, spatial dimension, boundary conditions, time step, atom type, and neighbor list parameter configuration.

4. The method as described in claim 1, characterized in that, In S10, the workpiece area has a size of 270×120×180Å, and the fluid layer has a size of 270×120×5Å.

5. The method as described in claim 1, characterized in that, In S30, the interaction potential between the bond length and the bond angle is a harmonic potential, which is suitable for simulating the stretching effect between chemical bonds and the bending effect of chemical bond angles. The force constant is set to 1000, the equilibrium bond length is set to 1 Å, and the equilibrium bond angle is set to 109.47 degrees. The constraints set for the fluid layer include: a constraint precision of 1e-4, a maximum number of iterations of 10, a maximum number of attempts of 10000, and a command to clear atomic overlaps.

6. The method as described in claim 1, characterized in that, In S40, the conjugate gradient method is used to set the energy minimization function.

7. The method as described in claim 1, characterized in that, The S60 includes: The micro-regular constraint function is invoked to keep the number of atoms, volume, and energy of atoms in the Newtonian layer, the isothermal layer, and the fluid layer constant. The regular constraint function is invoked to keep the number of atoms, volume, and temperature of atoms in the boundary layer constant.

8. The method as described in claim 1, characterized in that, The cutting parameters include temperature, paradigmatic equivalent stress, cutting force, dislocations, and potential and kinetic energy distribution.

9. The method as described in claim 8, characterized in that, In step S70, the step of cutting the single-crystal silicon workpiece based on the cutting parameters includes: Based on the temperature, paradigm equivalent stress, cutting force, dislocation, potential energy and kinetic energy distribution in the cutting parameters, the target process parameters in the actual cutting process are determined. The target process parameters include cutting speed, nanofluid volume fraction and nanofluid particle size. The cutting equipment is controlled to operate in a state that meets the target process parameters in order to perform a cutting operation on the monocrystalline silicon workpiece to be cut.

10. A computer system, characterized in that, The computer system includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the nanofluid-assisted single-crystal silicon cutting method based on molecular dynamics simulation as described in any one of claims 1 to 9.

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