Method for evaluating the effect of porosity of interconnect dielectric materials on performance of integrated circuits

Abstract

This invention discloses a method for evaluating the performance impact of porosity in integrated circuit interconnect dielectric materials, comprising the following steps: S1: Testing the porosity, pore size, and pore distribution of the dielectric material in subsequent processes; S2: Establishing a molecular model of the dielectric material at the microscale and calculating the electrical, structural, mechanical, and thermal parameters related to porosity; S3: Performing finite element simulation calculations with coupled electro-thermal-solid multiphysics fields at the macroscale to simulate the electric field, temperature field, stress and deformation field, and the formation and evolution of macroscopic pores during the interconnect process in subsequent processes; S4: Analyzing the impact of porosity on electrical, structural, thermal, and mechanical properties and the manufacturing process based on the multi-scale simulation results. This invention establishes a quantitative relationship between dielectric material, porosity, process, and performance through multi-scale multiphysics field coupled simulation to evaluate the performance impact of porosity in integrated circuit interconnect dielectric materials and guide the design of dielectric materials and structures.

Description

Technical Field

[0001] This method belongs to the field of semiconductor integrated circuit manufacturing technology, and in particular relates to a multi-scale simulation method for the impact of porosity of dielectric materials in back-end process interconnect structures on performance. Background Technology

[0002] As device density and feature linewidth in very large-scale integrated circuits (VLSI) continue to increase, low-k dielectric materials (low-κ) are replacing silicon dioxide (SiO2) as dielectric materials to address the significant parasitic capacitance between copper conductors caused by smaller conductor spacing. Among available low-k dielectric materials, with process improvements, the dielectric constant κ of black diamond (SiCOH) has decreased from 3.0 to 2.2, meeting the requirements of 90nm to 7nm process technologies, and is a potential candidate material for future ultra-low-κ applications.

[0003] SiCOH, a low-dielectric-constant material, is a porous amorphous material. SiCOH represents the material's elemental composition. By introducing carbon molecular bonds with lower polarizability (mainly CH3 groups) or introducing more pores, the overall polarizability and density of the material are reduced to meet the requirement of a low dielectric constant. SiCOH is commonly prepared using spin coating and chemical vapor deposition. For spin coating, the precursor mainly consists of an organic or inorganic polymer matrix mixed with a solvent, plus a porogen precursor. Heating and curing, or using electron beam technology to remove the organic matter and porogen, allows the polymer chains to crosslink while forming a porous membrane that meets mechanical strength requirements. For chemical vapor deposition films, the matrix material and organic polymer (porogen) are deposited simultaneously, followed by curing to decompose the porogen. The previously occupied sites are transformed into micropores / nanopores, and the remaining matrix is ​​reorganized and strengthened to form the final nanoporous membrane. Different matrix and porogen compositions, deposition and curing conditions can form various novel network structures in the final film.

[0004] The introduction of porosity into dielectric materials reduces the mechanical properties of SiCOH materials and their adhesion to adjacent materials such as etch stop layers and copper diffusion barrier layers in the interconnect structure, thus decreasing the mechanical stability of the material during processes such as chemical mechanical polishing and dicing. It also increases the surface area of ​​the structure, making it easier for moisture to be adsorbed and for copper ions to diffuse into the dielectric material, leading to electrical instability and accelerated dielectric breakdown. Furthermore, it reduces the thermal conductivity of the structure, resulting in increased circuit resistance and a shorter electromigration lifetime, which is detrimental to heat dissipation within the chip and reduces its thermal stability. Therefore, porosity is a crucial parameter in the design, manufacturing, and use of low dielectric constant materials. Adjusting the porosity is essential to finding the optimal combination that satisfies the requirements for dielectric constant and related thermal, mechanical, and structural fracture performance.

[0005] Quantitative analysis of the relationship between porosity and performance through process and experimentation is limited by funding and time costs. Furthermore, reliable experimental techniques and methods are lacking in research on porosity distribution and evolution, as well as stress-strain evolution, during multi-step processes such as plasma etching, laser ablation, chemical mechanical polishing, and dicing in the fabrication of interconnect structures. Conducting multi-scale, multi-physics simulation studies of dielectric materials during interconnect structure manufacturing can effectively and quantitatively analyze the relationship between porosity and performance, and the process, enabling precise control of material-process-porosity evolution-performance, and improving the reliability of interconnect dielectric materials and interconnect structures in very large-scale integrated circuits. Summary of the Invention

[0006] The purpose of this invention is to address the difficulty in quantitatively analyzing the impact of porosity on the performance of interconnect dielectric materials through experiments. It proposes a multi-scale, multi-physics simulation method that can reveal the formation and evolution of porosity in the multi-step process of interconnect structure manufacturing, as well as the quantitative relationship between the structure, dielectric, thermal, and mechanical properties of interconnect dielectric materials and porosity. This method also establishes a precise design model for the preparation of dielectric materials, encompassing material, process, porosity evolution, and performance.

[0007] This invention is implemented as follows:

[0008] This invention provides a method for evaluating the impact of porosity on the performance of integrated circuit interconnect dielectric materials. This method is used to perform multi-scale simulations of the microscopic porosity distribution and evolution, macroscopic voids and crack formation and evolution, stress and deformation of the dielectric material during the fabrication of interconnect structures in subsequent processes. The method includes the following steps:

[0009] S1: Test the porosity, pore size and pore distribution of the medium material used in subsequent processes;

[0010] S2: At the microscale, based on quantum mechanics and molecular dynamics, an atomic model of the medium material is established to obtain the distribution and evolution of pores, stress-strain response, dynamic crack propagation process, and temperature gradient field, and to calculate electrical, structural, mechanical, and thermal parameters.

[0011] S3: At the macroscopic scale, perform electro-thermal-solid multiphysics coupled finite element simulation calculations, establish finite element models of interconnect materials and structures, simulate the electric field, temperature field, stress field and structural deformation of the interconnect structure in the subsequent process, and solve for the macroscopic dielectric properties of the material, the temperature decay state of the dielectric material between the conductors, the adhesion properties of the interconnect structure interface and the structural stability of the manufacturing process.

[0012] S4: Based on the simulation results of multi-scale multi-physics field simulation, establish a quantitative correlation model between porosity and electrical, thermal and mechanical properties, analyze the formation and evolution of micro and macro pores, and use the results to control the establishment of multi-scale simulation model and material design; establish a database of downstream process medium material properties and process parameters.

[0013] Furthermore, the material testing methods for the porosity and pore distribution of the downstream process medium material in step S1 include small-angle X-ray scattering microscopy, positron annihilation lifetime spectroscopy, positron annihilation spectroscopy, small-angle X-ray diffraction, elliptic mercury intrusion porosimetry, microscopy, industrial CT technology, microwave detection technology, and ultrasonic detection technology; the pore size and distribution of the obtained micro and macro pores are used to establish a multi-scale simulation model.

[0014] Furthermore, in step S1, small-angle X-ray scattering microscopy, positron annihilation lifetime spectroscopy, positron annihilation spectroscopy, small-angle X-ray diffraction, and elliptic mercury intrusion porosimetry are techniques applicable to thin films, used to characterize the nanoscale porosity, pore distribution, and pore size of materials; while microscopy, industrial computed tomography, microwave detection, and ultrasonic detection are mainly used to test macroscopic pores in interconnect materials and structures.

[0015] Further, step S2 includes the following sub-steps:

[0016] S2a uses the first-principles method to establish a molecular model of SiCOH, uses density functional theory to calculate the electronic structure inside the material, and calculates various material properties, mechanical properties and electrical properties to obtain the dielectric constant parameter;

[0017] S2b utilizes molecular dynamics methods, employing ReaxFF potential functions or machine learning potential functions to simulate interatomic interactions. It uses the melt-cooling method to establish a molecular dynamics model of SiCOH, and calculates the structural, thermal, mechanical, fracture mechanics, and interconnected composite material mechanical properties to comprehensively evaluate the model's performance.

[0018] S2c adjusts the porosity, pore size, and pore distribution of the microscopic model, rebalances the model structure, and compares it with the pore test results of S1. Porosity and pore distribution are important microscale modeling variables of dielectric materials, and the quantitative relationship between electrical, structural, thermal, mechanical, and fracture mechanical properties and pores is calculated.

[0019] Furthermore, in step S2b, the temperature field, stress-strain curves, dynamic crack propagation process of the bulk and composite materials, stress and pore evolution of the material are obtained, and parameters describing the properties such as porosity and pore distribution, radial distribution function, structure factor, bond length, bond angle, dihedral angle, coordination number, elastic modulus, Poisson's ratio, hardness, fracture toughness, coefficient of thermal expansion, thermal conductivity, specific heat, and glass transition temperature are calculated.

[0020] Furthermore, S2a and S2b are used to obtain electrical and structural properties to verify the rationality of the microscale model network topology. The dielectric properties need to meet the requirements of the interconnect structure and process technology for the dielectric material.

[0021] Furthermore, in step S2c, the porosity, pore size, and pore distribution of the microscopic model are adjusted by adjusting the simulation frame volume, adjusting the temperature, and deleting specific pore atoms.

[0022] Furthermore, step S3 includes the following sub-steps:

[0023] S3a uses 3D geometric modeling software to create 3D geometric models of dielectric materials and downstream interconnect structures, uses finite element software to generate finite element meshes, and simulates the electric field, temperature field, stress field and structural deformation of the downstream interconnect structure. When building the 3D model, macroscopic pore size and distribution are considered.

[0024] S3b applies an electric field to the finite element model of the dielectric material to obtain the total current response of the composite material under AC voltage, and obtains the macroscopic dielectric properties, AC conductivity and relative permittivity.

[0025] S4c defines the dielectric material as a nonlinear heat transfer material. The thermal conductivity, density, specific heat, coefficient of thermal expansion, Young's modulus, and Poisson's ratio of the dielectric material obtained from S2 are input into the finite element model to solve for heat dissipation during chip operation, multiple thermal cycles in the back-end process, and temperature distribution, deformation, and stress of the structure in the subsequent advanced packaging process.

[0026] S3d considers the self-heating of each copper wire in the subsequent process, obtains the typical temperature distribution of the model and wires, the attenuation state of the dielectric material between the wires, and calculates the temperature of the nanowires and the thermal coupling between the wires.

[0027] S3e inputs the Young's modulus, Poisson's ratio, and energy release rate parameters of the medium material obtained from S2 into the finite element model, defines the damage initiation and evolution criteria, solves the crack propagation process of the composite interface material, and obtains the stress field and fracture toughness at the crack tip.

[0028] S3f uses a finite element model of the interconnect structure in the back-end process to simulate the removal of copper material and the stress and deformation of the entire interconnect structure under force load during chemical mechanical polishing.

[0029] S3g uses a finite element model of the interconnect structure in the back-end process to simulate the effect of the tool / laser on the interconnect material and structure during the dicing process, and calculates the temperature, stress, deformation and material failure of the interconnect structure.

[0030] Furthermore, in step S3, when performing macroscopic calculations, the parameters input to the finite element model can use the microscopic material properties calculated in S2, which are related to microscopic pores; at the same time, when establishing the three-dimensional model, the macroscopic pore size and distribution are considered.

[0031] Furthermore, in step S4, based on the multi-scale multi-physics simulation results of S2-S3, a quantitative correlation model between the porosity of the medium and its electrical, thermal, and mechanical properties is established to analyze the formation and evolution of micro-pores and macro-pores, as well as the changes in porosity during the process.

[0032] Furthermore, the multi-scale, multi-physics simulation results based on S2-S3 are used to establish a database of downstream process dielectric material performance and process parameters. By adjusting the pore parameters, feedback control is provided to establish a multi-field, multi-scale model for integrated circuits and to guide the design of porous interconnect materials.

[0033] Compared with the prior art, the present invention has the following advantages:

[0034] This invention establishes a multi-scale, multi-physics simulation model of the dielectric material for copper interconnects in very large-scale integrated circuits (VLSI). It quantifies the relationship between porosity and performance of the dielectric material, analyzes the distribution and evolution of porosity during chemical mechanical polishing (CMP) and tool / laser dicing processes, and simultaneously observes the formation and evolution of microscopic and macroscopic porosity, as well as stress and deformation. This method effectively characterizes the porosity-related properties and process parameters of dielectric materials, achieving precise control over material-process-porosity evolution-performance. It optimizes the design and manufacturing process parameters of dielectric materials and structures, reduces experimental costs, and improves the reliability of interconnect dielectric materials and interconnect structures for VLSI. Attached Figure Description

[0035] Figure 1 A flowchart illustrating the evaluation method for the impact of porosity in copper interconnect dielectric materials for very large-scale integrated circuits on performance, provided as an embodiment of the present invention;

[0036] Figure 2 This is a system framework diagram of a method for evaluating the performance impact of porosity in copper interconnect dielectric materials for very large-scale integrated circuits, provided in an embodiment of the present invention. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] like Figure 1 He Ru Figure 2 As shown, this invention provides a method for evaluating the impact of porosity on the performance of integrated circuit interconnect dielectric materials. This method is used for multi-scale, multi-physics simulation of porosity formation and evolution, stress and deformation, and performance changes with porosity in dielectric materials during downstream manufacturing processes. The method includes the following steps:

[0039] S1: Test the porosity, pore size and pore distribution of the medium material used in subsequent processes;

[0040] S2: At the microscale, based on quantum mechanics and molecular dynamics, an atomic model of the medium material is established to obtain the distribution and evolution of pores, stress-strain response, dynamic crack propagation process, and temperature gradient field, and to calculate electrical, structural, mechanical, and thermal parameters.

[0041] S3: At the macroscopic scale, perform electro-thermal-solid multiphysics coupled finite element simulation calculations, establish finite element models of interconnect materials and structures, simulate the electric field, temperature field, stress field and structural deformation of the interconnect structure in the subsequent process, and solve for the macroscopic dielectric properties of the material, the temperature decay state of the dielectric material between the conductors, the adhesion properties of the interconnect structure interface and the structural stability of the manufacturing process.

[0042] S4: Based on the simulation results of multi-scale multi-physics field simulation, establish a quantitative correlation model between porosity and electrical, thermal and mechanical properties, analyze the formation and evolution of micro and macro pores, and use the results to control the establishment of multi-scale simulation model and material design; establish a database of downstream process medium material properties and process parameters.

[0043] In the above embodiments, in step S1, the porosity and pore distribution of the downstream process dielectric material are tested using methods such as small-angle X-ray scattering microscopy, positron annihilation lifetime spectroscopy (PALS), positron annihilation spectroscopy (PAS), small-angle X-ray diffraction (SAXS), elliptic mercury intrusion porosimetry (EP), microscopy, industrial computed tomography, microwave detection, and ultrasonic detection. This lays the foundation for establishing a multi-scale simulation calculation model of the dielectric material SiCOH. Among these methods, small-angle X-ray scattering microscopy, positron annihilation lifetime spectroscopy (PALS), positron annihilation spectroscopy (PAS), small-angle X-ray diffraction (SAXS), and elliptic mercury intrusion porosimetry (EP) are techniques suitable for thin films and can characterize the nanoscale porosity, pore distribution, and pore size of the material. However, microscopy, industrial computed tomography, microwave detection, and ultrasonic detection are not sensitive enough to the nanoscale pores of porous thin films and are mainly used to test macroscopic pores that may appear in interconnect materials and structures.

[0044] Furthermore, in step S1, the material testing methods for the porosity and pore distribution of the downstream process medium material include density methods, adsorption methods, mercury intrusion porosimetry, industrial CT technology, microwave detection technology, and ultrasonic detection technology. The first three are destructive testing methods, while the others are non-destructive testing methods. Density methods can only measure porosity, while other methods can measure pore distribution and pore size. The most commonly used is industrial computed tomography (CT) technology, which clearly displays the internal structure, composition, material, and defects of the object being tested in the form of two-dimensional tomographic images or three-dimensional stereoscopic images. By improving spatial resolution and density resolution, it enhances the ability to identify the smallest structural details and the smallest density differences.

[0045] Further, step S2 includes the following sub-steps:

[0046] S2a uses first-principles methods to establish a molecular model of SiCOH, employs density functional theory to calculate the material's internal electronic structure, and calculates various material properties based on this, such as structural parameters like bond lengths and bond angles, and mechanical properties like elastic modulus. Simultaneously, the relationship between the dielectric functions and frequencies of electrons and ions is calculated separately. Then, zero-frequency approximations are made to the electronic and ionic dielectric constants, and the results are summed to obtain the material's static dielectric constant.

[0047] S2b utilizes molecular dynamics methods, employing ReaxFF potential functions or machine learning potential functions to simulate interatomic interactions, and establishes a molecular dynamics model of SiCOH using the melt-cooling method. The model's performance is comprehensively evaluated by calculating structural, thermal, mechanical, fracture mechanics, and interconnected composite material mechanical properties. This yields the material's temperature gradient field, stress-strain curves, dynamic crack propagation process in both bulk and composite materials, stress and pore evolution, and calculates parameters describing properties such as porosity and pore distribution, radial distribution function, structure factor, bond length, bond angle, dihedral angle, coordination number, elastic modulus, hardness, Poisson's ratio, fracture toughness, coefficient of thermal expansion, thermal conductivity, specific heat, and glass transition temperature.

[0048] S2c adjusts the porosity, pore size, and pore distribution of the microscopic model, rebalances the model structure, and compares it with the pore test results of S1. Porosity and pore distribution are important microscale modeling variables of dielectric materials, and the quantitative relationship between electrical, structural, thermal, mechanical, and fracture mechanical properties and pores is calculated.

[0049] In a further preferred embodiment, S2a and S2b are used to obtain dielectric and structural properties to verify the rationality of the model network topology. The dielectric properties need to meet the requirements of the interconnect structure and manufacturing process for the dielectric material. The radial distribution function and structural factor can be used to evaluate the short- and medium-range order of the network topology; bond length and bond angle are used to analyze local structural changes in the network; and coordination number and dihedral angle are used to evaluate the cross-linking of the structure.

[0050] In a further preferred embodiment, the micropores of the S2 model are visualized using an quasi-molecular density isosurface identification method. The method for identifying pores involves superimposing the electron densities of each atom in its free state to form a quasi-molecular density, which represents the state where atoms appear at their corresponding positions within a molecule, but whose electron densities have not yet changed due to bonding. Regions within a certain isosurface of the quasi-molecular density are considered intramolecular regions, while regions outside this isosurface can be considered molecular pores.

[0051] In a further preferred embodiment, the pore distribution and porosity of the first-principles and molecular dynamics models are compared with the pore test results of the S1 experiment. The porosity, pore size, and pore distribution of the microscopic model can be adjusted by methods such as adjusting the simulation frame volume, adjusting the temperature, and deleting specific pore atoms. After adjusting the pore size and pore distribution, the model structure needs to be rebalanced.

[0052] In a further preferred embodiment, porosity and pore distribution are used as important microscale modeling variables for dielectric materials to calculate the quantitative relationship between electrical, structural, thermal, mechanical, and fracture mechanical properties and porosity. Meanwhile, existing microscale models can also consider the influence of parameters such as elemental composition, simulation conditions (strain rate, ensemble, size), temperature, dopant atoms, and impurities on performance.

[0053] In a further preferred embodiment, in step S3, a thermo-electric-solid multiphysics coupled finite element simulation calculation is performed on a macroscopic scale. A three-dimensional geometric model of the dielectric material and the interconnect structure of the subsequent processing is created using three-dimensional geometric modeling software. A finite element mesh is generated using finite element software, and the electric field, temperature field, stress field, and structural deformation of the interconnect structure of the subsequent processing are simulated. The macroscopic dielectric properties and thermal conductivity of the material are obtained, as well as the formation and evolution of macroscopic pores and cracks, and stress and deformation during manufacturing and use.

[0054] In a further preferred embodiment, the electrical properties of the material are calculated using a finite element model of the dielectric material. An electric field is applied to the finite element model to obtain the total current response of the composite material under AC voltage. The total current obtained from the simulation is decomposed using the time-domain least squares method to obtain the macroscopic dielectric properties, AC conductivity, and relative permittivity of the composite material.

[0055] In a further preferred embodiment, the temperature distribution, deformation, and thermal stress of the structure are calculated using a finite element model of the interconnect structure in the subsequent process. The dielectric material is defined as a nonlinear heat transfer material. The thermal conductivity, density, specific heat, and coefficient of thermal expansion of the dielectric material obtained by S2 are input as parameters into the finite element model established by S3. The temperature of the specified structure is set, and the temperature distribution under steady-state conditions is solved and obtained, as well as the temperature distribution, deformation, and stress of the structure under thermal load.

[0056] In a further preferred embodiment, the thermal load includes heat dissipation during chip operation, multiple thermal cycles in subsequent processes, and advanced packaging processes (such as filling and curing).

[0057] In a further preferred embodiment, the self-heating of each copper wire in the subsequent process is considered. Thermal boundary conditions, analysis models, and typical temperature distributions of the wires are applied, along with the attenuation state of the dielectric material between the wires. The temperature of the nanowires and the thermal coupling between the wires are calculated. During the simulation, factors such as the current, resistance, and position of the wires, as well as the thickness, geometry, position, and thermal conductivity of the dielectric layer, are considered.

[0058] In a further preferred embodiment, the fracture mechanical properties of the composite material of the structure are calculated using a finite element model of the interconnected structure of the subsequent process. The Young's modulus, Poisson's ratio, energy release rate, and other parameters of the medium material obtained by S2 are input into the structural finite element model. Damage initiation and evolution criteria are defined, and the crack propagation process of the composite interface material is solved to obtain the stress field and fracture toughness at the crack tip.

[0059] In a further preferred embodiment, a finite element model of the interconnect structure in the subsequent process is used to simulate the removal of copper material and the stress and deformation of the entire interconnect structure under force load during the chemical mechanical polishing process.

[0060] In a further preferred embodiment, a finite element model of the interconnect structure in the subsequent process is used to simulate the effect of the tool / laser on the interconnect material and structure during the dicing process, and to calculate the temperature, stress, deformation and material failure of the interconnect structure.

[0061] In a further preferred embodiment, when performing macroscopic calculations, the parameters input to the finite element model can be the microscopic material properties calculated by S2, which are related to microscopic pores; at the same time, when establishing the three-dimensional model, the macroscopic pore size and distribution are considered.

[0062] In a further preferred embodiment, in step S4, based on the multi-scale multiphysics simulation results of S2-S3, a quantitative correlation model between the porosity of the medium and its electrical, thermal, and mechanical properties is established to analyze the formation and evolution of micro and macro pores, as well as the changes in pores during processes such as plasma etching, laser action, and chemical mechanical polishing.

[0063] In a further preferred embodiment, in step S4, the multi-scale multi-physics simulation results from S2-S3 are used to establish a database of downstream process medium material properties and a database of process parameters.

[0064] In a further preferred embodiment, such as Figure 2 As shown, the execution order of steps S2-S3 in this invention can be changed, and multiple steps can be performed simultaneously, thereby combining first-principles calculations, molecular dynamics, and macroscopic finite element simulation to achieve multi-scale, multi-physics coupled modeling and simulation analysis. Based on the material properties of the dielectric material obtained from first-principles and molecular dynamics simulations, the macroscopic finite element simulation conditions are modified, while considering the influence of microscopic porosity and pore distribution. Combining mesoscopic and macroscopic scale models of actual processes and usage provides a design basis for the microscopic model, and simultaneously reveals the effect of the process on macroscopic porosity. On this basis, a multi-scale data interaction algorithm is developed to achieve multi-scale, multi-physics coupled modeling and simulation of downstream process dielectric materials and structures.

[0065] It should be understood that the above description of the preferred embodiments is quite detailed, but it should not be considered as a limitation on the scope of protection of this invention. Those skilled in the art, under the guidance of this invention, can make substitutions or modifications without departing from the scope of protection of the claims of this invention, and all such substitutions or modifications fall within the scope of protection of this invention. The scope of protection of this invention should be determined by the appended claims.

Claims

1. A method for evaluating the impact of porosity on the performance of integrated circuit interconnect dielectric materials, used for multi-scale simulation of the micro-pore distribution and evolution, macro-pore and crack formation and evolution, stress and deformation of dielectric materials during the fabrication of interconnect structures in downstream processes, characterized in that, The method includes the following steps: S1: Test the porosity, pore size and pore distribution of the medium material used in subsequent processes; S2: At the microscale, based on quantum mechanics and molecular dynamics, an atomic model of the medium material is established to obtain the distribution and evolution of pores, stress-strain response, dynamic crack propagation process, and temperature field, and to calculate electrical, structural, mechanical, and thermal parameters. S3: At the macroscopic scale, perform electro-thermal-solid multiphysics coupled finite element simulation calculations, establish finite element models of interconnect materials and structures, simulate the electric field, temperature field, stress field and structural deformation of the interconnect structure in the subsequent process, and solve for the macroscopic dielectric properties of the material, the temperature decay state of the dielectric material between the conductors, the adhesion properties of the interconnect structure interface and the structural stability of the manufacturing process. S4: Based on the simulation results of multi-scale multi-physics field simulation, establish a quantitative correlation model between porosity and electrical, thermal and mechanical properties, analyze the formation and evolution of micro and macro pores, and use the results to control the establishment of multi-scale simulation model and material design; establish a database of downstream process medium material properties and process parameters.

2. The method for evaluating the impact of porosity on the performance of integrated circuit interconnect dielectric materials according to claim 1, characterized in that, The material testing methods for the porosity and pore distribution of the downstream process medium material in step S1 include small-angle X-ray scattering microscopy, positron annihilation lifetime spectroscopy, positron annihilation spectroscopy, small-angle X-ray diffraction, elliptic mercury intrusion porosimetry, microscopy, industrial CT technology, microwave detection technology, and ultrasonic detection technology; the pore size and distribution of the obtained micro and macro pores are used to establish a multi-scale simulation model.

3. The method for evaluating the impact of porosity on the performance of integrated circuit interconnect dielectric materials according to claim 2, characterized in that, In step S1, small-angle X-ray scattering microscopy, positron annihilation lifetime spectroscopy, positron annihilation spectroscopy, small-angle X-ray diffraction, and elliptic mercury intrusion porosimetry are techniques applicable to thin films, which characterize the nanoscale porosity, pore distribution, and pore size of materials; while microscopy, industrial computed tomography, microwave detection, and ultrasonic detection are mainly used to test macroscopic pores in interconnect materials and structures.

4. The method for evaluating the impact of porosity on the performance of integrated circuit interconnect dielectric materials according to claim 1, characterized in that, Step S2 includes the following sub-steps: S2a uses first-principles methods to establish a molecular model of SiCOH, uses density functional theory to calculate the internal electronic structure of the material, and calculates various material properties, mechanical properties and electrical properties; S2b utilizes molecular dynamics methods, employing ReaxFF potential functions or machine learning potential functions to simulate interatomic interactions. It uses the melt-cooling method to establish a molecular dynamics model of SiCOH, and calculates the structural, thermal, mechanical, fracture mechanics, and interconnected composite material mechanical properties to comprehensively evaluate the model's performance. S2c adjusts the porosity, pore size, and pore distribution of the microscopic model, rebalances the model structure, and compares it with the pore test results of S1. Porosity, pore size, and pore distribution are important microscale modeling variables of dielectric materials, and the quantitative relationship between electrical, structural, thermal, mechanical, and fracture mechanical properties and pore size is calculated.

5. The method for evaluating the impact of porosity on the performance of integrated circuit interconnect dielectric materials according to claim 4, characterized in that, In step S2b, the temperature field, stress-strain curves, dynamic crack propagation process of bulk and composite materials, stress and pore evolution of the material are obtained. The parameters describing the properties, such as porosity and pore distribution, radial distribution function, structure factor, bond length, bond angle, dihedral angle, coordination number, elastic modulus, Poisson's ratio, hardness, fracture toughness, coefficient of thermal expansion, thermal conductivity, specific heat, and glass transition temperature, are calculated.

6. The method for evaluating the performance impact of porosity in integrated circuit interconnect dielectric materials according to claim 4, characterized in that, In step S2c, the porosity, pore size, and pore distribution of the microscopic model are adjusted by adjusting the simulation frame volume, adjusting the temperature, and deleting specific pore atoms.

7. The method for evaluating the performance impact of porosity in integrated circuit interconnect dielectric materials according to claim 1, characterized in that, Step S3 includes the following sub-steps: S3a uses 3D geometric modeling software to create 3D geometric models of dielectric materials and downstream interconnect structures, uses finite element software to generate finite element meshes, and simulates the electric field, temperature field, stress field and structural deformation of the downstream interconnect structure. When building the 3D model, macroscopic pore size and distribution are considered. S3b applies an electric field to the finite element model of the dielectric material to obtain the total current response of the composite material under AC voltage, and obtains the macroscopic dielectric properties, AC conductivity and relative permittivity. S3c defines the dielectric material as a nonlinear heat transfer material. The thermal conductivity, density, specific heat, coefficient of thermal expansion, elastic modulus, and Poisson's ratio parameters of the dielectric material obtained from S2 are input into the finite element model to solve for heat dissipation during chip operation, multiple thermal cycles in the back-end process, and temperature distribution, deformation, and stress of the structure in the subsequent advanced packaging process. S3d considers the self-heating of each copper wire in the subsequent process, obtains the typical temperature distribution of the model and wires, the attenuation state of the dielectric material between the wires, and calculates the temperature of the nanowires and the thermal coupling between the wires. S3e inputs the Young's modulus, Poisson's ratio, and energy release rate parameters of the medium material obtained from S2 into the finite element model, defines the damage initiation and evolution criteria, solves the crack propagation process of the composite interface material, and obtains the stress field and fracture toughness at the crack tip. S3f uses a finite element model of the interconnect structure in the back-end process to simulate the removal of copper material and the stress and deformation of the entire interconnect structure when subjected to force load during chemical mechanical polishing. S3g uses a finite element model of the interconnect structure in the back-end process to simulate the effect of the tool / laser on the interconnect material and structure during the dicing process, and calculates the temperature, stress, deformation and material failure of the interconnect structure.

8. The method for evaluating the performance impact of porosity in integrated circuit interconnect dielectric materials according to claim 1, characterized in that, In step S3, when performing macroscopic calculations, the parameters input to the finite element model can use the microscopic material properties calculated in S2, which are related to microscopic porosity; at the same time, when establishing the three-dimensional model, macroscopic porosity, pore size and distribution are considered, and the distribution and evolution of pores are observed during the simulation process.

9. The method for evaluating the performance impact of porosity in integrated circuit interconnect dielectric materials according to claim 1, characterized in that, In step S4, based on the multi-scale multi-physics simulation results of S2-S3, a quantitative correlation model between the porosity of the medium and its electrical, structural, thermal, and mechanical properties is established to analyze the formation and evolution of micro and macro pores, as well as the changes in pores during the process.

10. The method for evaluating the performance impact of porosity in integrated circuit interconnect dielectric materials according to claim 8, characterized in that, Based on the multi-scale multiphysics simulation results of S2-S3, a database of downstream process dielectric material performance and process parameters is established. By adjusting the pore parameters, feedback control is provided to establish a multi-field multi-scale model of integrated circuits and to guide the design of porous interconnect materials.

Images