Method, apparatus, and computer device for evaluating soft error rate of electronic device

Abstract

The present application relates to a method, device, computer device, storage medium and computer program product for evaluating the soft error rate of an electronic device. The method includes: obtaining the flux-energy spectrum of particles released by the packaging material of the electronic device; performing reverse analysis on the electronic device to determine the dielectric property information between the active region of the electronic device and the packaging material; determining the particle flux-linear energy transfer value spectrum of the electronic device in the active region according to the flux-energy spectrum and the dielectric property information; obtaining the single event effect cross-section value-linear energy transfer value spectrum of the electronic device obtained by irradiating the electronic device; performing an operation on the particle flux-linear energy transfer value spectrum and the single event effect cross-section value-linear energy transfer value spectrum to determine the soft error rate of the electronic device. Using this method can improve the evaluation accuracy of the soft error rate of the electronic device.

Description

Technical Field

[0001] The present application relates to the technical field of electronic device reliability, and particularly to a method, device, computer device, storage medium, and computer program product for evaluating the soft error rate of an electronic device. Background Art

[0002] With the development of electronic device reliability technology, 235U (uranium) and other substances used as nuclear reaction raw materials, as well as their daughter isotopes such as 232Th (thorium), are relatively common radioactive elements. Due to the large amount of 235U naturally present on the earth, these elements are likely to appear in various materials of semiconductor devices, such as molding compounds, solder balls, fillers, etc. These elements usually undergo α (alpha) decay, which may cause adverse effects such as data loss and function interruption in semiconductor devices.

[0003] To solve the above problems, in the prior art, an artificial α-particle radiation source is generally used to conduct irradiation tests to obtain the soft error cross-section, and then the soft error rate is calculated by combining the α-particle emission rate of the device itself. However, when conducting artificial radiation source irradiation tests, the spatial geometric effect between the artificial radiation source and the device under test and the shielding effect of the air layer may cause a certain proportion of reduction in the effective flux of α-particles reaching the surface of the device under test, resulting in a large error in the test. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a method, device, computer device, computer-readable storage medium, and computer program product for evaluating the soft error rate of an electronic device that can improve the accuracy of soft error rate evaluation.

[0005] In a first aspect, the present application provides a method for evaluating the soft error rate of an electronic device, the method comprising:

[0006] Obtaining the flux-energy spectrum of particles released by the packaging material of the electronic device;

[0007] Performing reverse analysis on the electronic device to determine the dielectric property information between the active region of the electronic device and the packaging material;

[0008] Determining the particle flux-linear energy transfer value spectrum in the active region of the electronic device according to the flux-energy spectrum and the dielectric property information;

[0009] Obtaining the single-event effect cross-section value-linear energy transfer value spectrum of the electronic device obtained by irradiating the electronic device;

[0010] Performing operations on the particle flux-linear energy transfer value spectrum and the single-event effect cross-section value-linear energy transfer value spectrum to determine the soft error rate of the electronic device.

[0011] In one embodiment, obtaining the flux - energy spectrum of particles released by the packaging material of the electronic device includes:

[0012] Preparing a sample of the packaging material to obtain a sampled specimen;

[0013] Using an alpha - particle surface emission measurement device to conduct test measurements on the sampled specimen to obtain the flux - energy spectrum of the particles released by the packaging material;

[0014] In one embodiment, obtaining the flux - energy spectrum of particles released by the packaging material of the electronic device includes: establishing a simulation model of the packaging material;

[0015] Simulating the packaging material simulation model to cause the packaging material simulation model to emit particles and extracting the outgoing parameters of the particles emitted by the packaging material simulation model;

[0016] Determining the flux - energy spectrum of the particles released by the packaging material according to the outgoing parameters of the particles.

[0017] In one embodiment, the medium property information includes: a dielectric layer, the dielectric thickness information of each dielectric layer, and the dielectric composition information;

[0018] Determining the particle flux - effective linear energy transfer value spectrum of the electronic device in the active region according to the flux - energy spectrum and the medium property information includes:

[0019] Establishing a simulation model of the active region according to the medium property information, where the simulation model of the active region includes an active region layer and each dielectric layer;

[0020] Simulating the simulation model of the active region according to the flux - energy spectrum, injecting the particles corresponding to the flux - energy spectrum into the dielectric layer of the active region simulation model, and obtaining particle characteristic information on the surface of the active region layer of the active region simulation model, where the particle characteristic information includes the associated active region surface energy, outgoing angle, and particle flux;

[0021] Determining the particle flux - effective linear energy transfer value spectrum of the active region based on the particle characteristic information.

[0022] In one embodiment, determining the particle flux - effective linear energy transfer value spectrum of the active region based on the particle characteristic information includes:

[0023] Determining the effective linear energy transfer value of the active region based on the active region surface energy and the outgoing angle;

[0024] Determine the particle flux-effective linear energy transfer value spectrum of the active region based on the particle flux and the effective linear energy transfer value of the active region.

[0025] In one embodiment, the determining the effective linear energy transfer value of the active region based on the surface energy of the active region and the emission angle includes:

[0026] Determine the linear energy transfer value based on the type of particle and the surface energy of the active region;

[0027] Divide the linear energy transfer value by the cosine value of the emission angle to determine the effective linear energy transfer value of the active region.

[0028] In one embodiment, the calculating the soft error rate of the electronic device based on the particle flux-effective linear energy transfer value spectrum and the single event effect cross-section value-effective linear energy transfer value spectrum includes:

[0029] Integrate the particle flux-effective linear energy transfer value spectrum and the single event effect cross-section value-effective linear energy transfer value spectrum to obtain the soft error rate of the electronic device.

[0030] In a second aspect, the present application further provides an electronic device soft error rate evaluation device, the device includes:

[0031] A flux-energy spectrum determination module, configured to obtain the flux-energy spectrum of the particles released by the packaging material of the electronic device;

[0032] A dielectric property information determination module, configured to perform reverse analysis on the electronic device to determine the dielectric property information between the active region of the electronic device and the packaging material;

[0033] An active region information determination module, configured to determine the particle flux-effective linear energy transfer value spectrum of the electronic device in the active region according to the flux-energy spectrum and the dielectric property information;

[0034] An electronic device information acquisition module, configured to obtain the single event effect cross-section value-effective linear energy transfer value spectrum of the electronic device obtained by irradiating the electronic device;

[0035] A soft error rate determination module, configured to perform operations on the particle flux-effective linear energy transfer value spectrum and the single event effect cross-section value-effective linear energy transfer value spectrum to determine the soft error rate of the electronic device.

[0036] In a third aspect, the present application further provides a computer device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the steps of the method for evaluating the soft error rate of the electronic device are implemented.

[0037] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method for evaluating the soft error rate of the electronic device are implemented.

[0038] In a fifth aspect, the present application further provides a computer program product, including a computer program, and when the computer program is executed by a processor, the steps of the method for evaluating the soft error rate of the electronic device are implemented.

[0039] For the above method, device, computer device, storage medium, and computer program product for evaluating the soft error rate of an electronic device, by obtaining the flux-energy spectrum of particles released by the packaging material of the electronic device and performing reverse analysis on the electronic device to determine the dielectric property information between the active region of the electronic device and the packaging material, the active region particle flux-linear energy transfer value spectrum of the electronic device in the active region can be determined according to the flux-energy spectrum and the dielectric property information. Then, in combination with the irradiation experiment, the single-event effect cross-section value-linear energy transfer value spectrum of the electronic device obtained from the irradiation test of the electronic device is obtained. Finally, based on the active region particle flux-linear energy transfer value spectrum and the single-event effect cross-section value-linear energy transfer value spectrum in the active region, the soft error rate of the electronic device is determined, thereby improving the evaluation accuracy of the soft error rate of the electronic device through the above method. Description of the Drawings

[0040] Figure 1 It is a schematic flowchart of the method for evaluating the soft error rate of an electronic device in an embodiment;

[0041] Figure 2 It is a schematic diagram of the flux-energy spectrum of particles in an embodiment;

[0042] Figure 3 It is a schematic flowchart of the method for evaluating the soft error rate of an electronic device in another embodiment;

[0043] Figure 4 It is a schematic diagram of the structure of the intermediate dielectric layer and the active region layer in an embodiment;

[0044] Figure 5 It is a block diagram of the structure of the device for evaluating the soft error rate of an electronic device in an embodiment;

[0045] Figure 6 It is an internal structure diagram of a computer device in an embodiment. Detailed Embodiments

[0046] In order to make the objectives, technical solutions and advantages of the present application more clear and understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this invention belongs. The terms used in the description of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0048] 235U, 238U as nuclear reaction raw materials and their daughter isotopes (such as 232Th) are relatively common radioactive elements. Since a large amount of 235U (0.72%), 238U (99.2%) and 232Th (100%) exist naturally on the earth, these elements are very likely to appear in various materials of semiconductor devices, such as molding compounds, solder balls, fillers, etc. At the same time, there is always a very small amount of 210Po in the solder joints of semiconductor devices. These heavy radioactive isotopes usually undergo α decay, continuously releasing α particles with an energy of approximately 4 MeV - 9 MeV. The energetic α particles incident on the active region of the semiconductor device will generate a high density of electron-hole pairs along their tracks. After the electron-hole pairs are separated under the action of the device electric field and collected by the nodes, an interference current signal will be generated in the circuit, which will cause serious consequences such as data loss and function interruption of the semiconductor device. It can be seen that the impact of α particles on the circuit system may be fatal. For example, when α particles cause a soft error in the instruction cache of the CPU, the CPU cannot execute the expected function. Therefore, in the following embodiments, α particles are taken as an example for illustration.

[0049] In one embodiment, as Figure 1 shown, a method for evaluating the soft error rate of an electronic device is provided, including the following steps:

[0050] Step S102, obtaining the flux-energy spectrum of the particles released by the packaging material of the electronic device.

[0051] Among them, an electronic device refers to a device that can achieve various specific functions. For example, the electronic device can be a semiconductor device, and the semiconductor device can be applied to devices such as communication and radar. Among various materials of the semiconductor device, such as molding compounds, solder balls, fillers, etc., radioactive elements may appear. The radioactive elements can be 235U (0.72%), 238U (99.2%), 232Th (100%), etc. There will also be extremely small amounts of 210Po in the solder joints of the semiconductor device. These radioactive elements will undergo α decay and continuously release α particles with an energy of approximately 4 MeV (mega-electron volts) - 9 MeV (mega-electron volts). The α particles with energy enter the soft error sensitive area of the semiconductor device and generate a high-density electron-hole pair along their tracks. After the electron-hole pair is separated under the action of the electric field of the semiconductor device, it is collected by the node, generating an interference current signal in the circuit, thereby causing adverse effects such as data loss and function interruption in the semiconductor device.

[0052] Among them, the packaging material of the electronic device is the main area for generating α particles. The packaging material of the electronic device is related to the packaging structure of the electronic device. Different packaging structures of the electronic device result in different packaging materials. Taking the semiconductor device as an example, for a plastic-packaged face-up device, the packaging material is the plastic encapsulant; for a plastic-packaged flip-chip device, the packaging material is the solder ball. When the α particles with energy enter the soft error sensitive area of the semiconductor device, it will cause adverse effects such as data loss and function interruption in the semiconductor device. Among them, a soft error refers to an effect such as single event upset, single event transient pulse, multiple bit upset, etc. that does not cause hard damage to the semiconductor device, and the soft error sensitive area refers to the sensitive area where the above effects are likely to occur.

[0053] Among them, the radioactive isotopes in the packaging material usually continue to emit alpha particles continuously after undergoing α decay. The particle flux refers to the number of alpha particles per unit area and per unit time, and the particle flux-energy spectrum refers to the fitting relationship between the flux of alpha particles and the energy. After determining the packaging material of the electronic device, the particle flux-energy spectrum released by the packaging material of the electronic device can be obtained.

[0054] Step S104, perform reverse analysis on the electronic device to determine the dielectric property information between the active region of the electronic device and the packaging material.

[0055] In one embodiment, taking a semiconductor device as an example for illustration, there is a dielectric layer between the active region of the semiconductor device and the packaging material. The dielectric layer may include only one type of dielectric or more than one type of dielectric. The dielectric property information may refer to information such as the thickness of the dielectric layer. By performing reverse analysis on the soft error sensitive region, the dielectric property information between the active region of the electronic device and the packaging material can be obtained. Among them, when performing reverse analysis, a bottom-up analysis method can be adopted to perform hierarchical analysis and processing on the electronic device.

[0056] Step S106: Determine the particle flux-linear energy transfer value spectrum of the electronic device in the active region according to the flux-energy spectrum and the dielectric property information.

[0057] In one embodiment, the particle flux in the active region refers to the number of alpha particles per unit area and per unit time on the surface of the active region. The linear energy transfer value refers to the energy deposited by alpha particles per unit thickness on the active region. According to the flux-energy spectrum and the dielectric property information, the particle flux-linear energy transfer value spectrum of the electronic device in the active region can be determined.

[0058] Step S108: Obtain the single event effect cross-section value-linear energy transfer value spectrum of the electronic device obtained from the irradiation test of the electronic device.

[0059] In one embodiment, for the irradiation experiment of the electronic device, specifically, heavy ions with different linear energy transfer values can be used to irradiate the electronic device to obtain the single event effect cross-section values of the electronic device under the irradiation of heavy ions with different linear energy transfer values. The single event effect cross-section value-linear energy transfer value spectrum may refer to the fitting relationship between the single event effect cross-section value and the linear energy transfer value.

[0060] In one embodiment, the single event effect cross-section values under the irradiation of heavy ions with at least five groups of linear energy transfer values can be obtained, and software tools such as Matlab or Origin can be used to plot the data of the single event effect cross-section values and the linear energy transfer values, and then the Weibull function is used to fit the data points to obtain the optimal fitting curve.

[0061] Step S110: Perform operations on the particle flux-linear energy transfer value spectrum and the single event effect cross-section value-linear energy transfer value spectrum to determine the soft error rate of the electronic device.

[0062] In one embodiment, the soft error rate of an electronic device refers to the calculated probability of a soft error occurring in the electronic device. After obtaining the particle flux - linear energy transfer value spectrum and the single - event effect cross - section value - linear energy transfer value spectrum, operations are performed on the particle flux - linear energy transfer value spectrum and the single - event effect cross - section value - linear energy transfer value spectrum to determine the soft error rate of the electronic device.

[0063] In the above - mentioned method for evaluating the soft error rate of an electronic device, by obtaining the flux - energy spectrum of particles released by the packaging material of the electronic device and performing reverse analysis on the electronic device to determine the dielectric property information between the active region of the electronic device and the packaging material, the active - region particle flux - linear energy transfer value spectrum of the electronic device in the active region can be determined according to the flux - energy spectrum and the dielectric property information. Then, combined with the irradiation experiment, the single - event effect cross - section value - linear energy transfer value spectrum of the electronic device obtained from the irradiation test of the electronic device is obtained. Finally, according to the active - region particle flux - linear energy transfer value spectrum and the single - event effect cross - section value - linear energy transfer value spectrum in the active region, the soft error rate of the electronic device is determined, so that the evaluation accuracy of the soft error rate of the electronic device can be improved through the above - mentioned method.

[0064] In one embodiment, the obtaining of the flux - energy spectrum of particles released by the packaging material of the soft - error sensitive region includes:

[0065] Sample the packaging material to obtain a sampled specimen;

[0066] Use an alpha - particle surface emission measurement device to perform test measurements on the sampled specimen to obtain the flux - energy spectrum of particles released by the packaging material.

[0067] The flux - energy spectrum of particles can be obtained by experimental measurement. Specifically, the packaging material can be specially sampled to obtain a sampled specimen, and then the sampled specimen is tested and measured by an alpha - particle surface emission measurement device to obtain the flux - energy spectrum of particles released by the packaging material. In one embodiment, the flux - energy spectrum of particles released by the packaging material obtained through experiments is as Figure 2 shown. By specially sampling the packaging material and performing test measurements on this basis, the flux - energy spectrum of particles released by the packaging material can be accurately obtained.

[0068] In one embodiment, the obtaining of the flux - energy spectrum of particles released by the packaging material of the soft - error sensitive region includes:

[0069] Establish a simulation model of the packaging material;

[0070] Simulate the encapsulation material simulation model to make the encapsulation material simulation model emit particles, and extract the emission parameters of the particles emitted by the encapsulation material simulation model;

[0071] Determine the flux-energy spectrum of the particles released by the encapsulation material according to the emission parameters of the particles.

[0072] In one embodiment, an encapsulation material simulation model of the encapsulation material can be established based on any simulation method such as Monte Carlo simulation. The emission parameters of the particles can refer to parameters such as the energy, flux, and emission direction of the particles after the encapsulation material simulation model emits particles. Among them, the energy of the particles is determined by trace amounts of radionuclides contained in the encapsulation material in the encapsulation material simulation model, such as U (uranium), Th (thorium), Po (polonium), etc.

[0073] In one embodiment, after establishing the encapsulation material simulation model of the encapsulation material, simulate the encapsulation material simulation model to make the encapsulation material simulation model emit alpha particles. Specifically, the encapsulation material simulation model can be made to emit alpha particles uniformly and isotropically, and extract parameters such as the energy, flux, and emission direction of the alpha particles emitted by the encapsulation material simulation model, so that the flux-energy spectrum of the particles released by the encapsulation material can be accurately obtained through the above method.

[0074] In one embodiment, the medium property information includes: medium layers, the medium thickness information of each medium layer, and the medium composition information. Among them, the medium layers can include a metal wiring layer, a passivation layer, and an oxide layer, etc. Each medium layer corresponds to a medium thickness and a medium composition. For the metal wiring layer, its medium composition can mainly be Cu (copper) or Al (aluminum). For the oxide layer, its medium composition can mainly be SiO2 (silicon dioxide). For the passivation layer, its medium composition can mainly be Si3N4 (silicon nitride). Refer to Figure 4 shown, which is a schematic diagram of the medium layer and the active region layer structure.

[0075] At this time, determining the particle flux-linear energy transfer value spectrum in the active region of the electronic device according to the flux-energy spectrum and the medium property information includes:

[0076] Step S302, establish a simulation model of the active region according to the medium property information. The simulation model of the active region includes an active region layer and each of the medium layers.

[0077] Step S304: Simulate the simulation model of the active region according to the flux-energy spectrum, and let the particles corresponding to the flux-energy spectrum enter the dielectric layer of the simulation model of the active region, and obtain particle characteristic information on the surface of the active region layer of the simulation model of the active region. The particle characteristic information includes the associated surface energy, emission angle, and particle flux.

[0078] Among them, the active region surface energy can refer to the energy of alpha particles on the surface of the active region, the emission angle can refer to the angle at which alpha particles are emitted on the surface of the active region, and the particle flux refers to the number of alpha particles per unit area and per unit time on the surface of the active region.

[0079] Step S306: Determine the flux-linear energy transfer value spectrum of the active region based on the particle characteristic information.

[0080] This embodiment is a process of determining the particle flux-linear energy transfer value spectrum in the active region of an electronic device. A simulation model of the active region is established through dielectric property information. Specifically, the dielectric layer includes a metal wiring layer, a passivation layer, and an oxide layer. A simulation model of the active region is established according to the dielectric thickness and dielectric composition of each dielectric layer. Then, the simulation model of the active region is simulated according to the flux-energy spectrum, that is, the particles corresponding to the flux-energy spectrum are incident on the dielectric layer of the simulation model of the active region, and particle characteristic information is obtained on the surface of the active region layer of the simulation model of the active region. The particle characteristic information includes the associated active region surface energy, emission angle, and particle flux, and the particle flux-linear energy transfer value spectrum of the active region is determined according to the particle characteristic information. Thus, the particle flux-linear energy transfer value spectrum of the active region can be accurately determined through the above method.

[0081] In one embodiment, the determining the flux-linear energy transfer value spectrum of the active region based on the particle characteristic information includes:

[0082] Determine the linear energy transfer value of the active region based on the active region surface energy and emission angle;

[0083] Determine the flux-linear energy transfer value spectrum of the active region based on the particle flux and the linear energy transfer value of the active region.

[0084] In one embodiment, the linear energy transfer value of the active region can be determined first according to the active region surface energy and emission angle, and then the flux-linear energy transfer value spectrum of the active region can be determined according to the active region flux and the linear energy transfer value of the active region. Thus, the flux-linear energy transfer value spectrum of the active region can be determined through the above method.

[0085] In one embodiment, determining the effective linear energy transfer value of the active region based on the surface energy of the active region and the emission angle includes:

[0086] Determining the linear energy transfer value based on the type of particle and the surface energy of the active region;

[0087] Dividing the linear energy transfer value by the cosine value of the emission angle to determine the effective linear energy transfer value of the active region.

[0088] In one embodiment, as shown in Equation 1:

[0089]

[0090] where LET eff refers to the effective linear energy transfer value of the active region, LET0 refers to the linear energy transfer value, cos(θ) refers to the cosine value of the emission angle. After determining the type of particle, such as an alpha particle, the alpha particle and the active region flux of the alpha particle can be input into a software tool (such as SRIM) or an empirical formula to obtain the linear energy transfer value. Finally, the linear energy transfer value is divided by the cosine value of the emission angle to obtain the effective linear energy transfer value of the active region. Thus, the effective linear energy transfer value of the active region can be determined through the above method.

[0091] In one embodiment, performing operations on the active region particle flux-effective linear energy transfer value spectrum and the single event effect cross-section value-effective linear energy transfer value spectrum to determine the soft error rate of the electronic device includes:

[0092] Integrating the active region particle flux-effective linear energy transfer value spectrum and the single event effect cross-section value-effective linear energy transfer value spectrum to obtain the soft error rate of the electronic device.

[0093] In one embodiment, the active region particle flux-effective linear energy transfer value spectrum and the single event effect cross-section value-effective linear energy transfer value spectrum can be integrated to obtain the soft error rate of the electronic device. Specifically, the active region particle flux corresponding to the same effective linear energy transfer value and the single event effect cross-section value can be multiplied to obtain the soft error rate of the electronic device. Thus, the calculation accuracy of the soft error rate can be improved through the above method.

[0094] Further, to enable those skilled in the art to understand the present application more clearly, the present application will be described below with a specific example.

[0095] Specifically, taking the particle as an alpha particle and the electronic device as a semiconductor device as an example for illustration. First, obtain the flux-energy spectrum of the particles released by the encapsulation material of the electronic device. Among them, the encapsulation material of the electronic device is the main region where alpha particles are generated. The encapsulation material of the electronic device is related to the encapsulation structure of the electronic device. Different encapsulation structures of the electronic device have different encapsulation materials. Taking the semiconductor device as an example for illustration, for the plastic-encapsulated face-up device, the encapsulation material is the plastic encapsulant. For the plastic-encapsulated flip-chip device, the encapsulation material is the solder ball. When an alpha particle with energy is incident on the soft error sensitive area of the semiconductor device, it will cause adverse effects such as data loss and function interruption in the semiconductor device. Among them, a soft error refers to an effect such as single event upset, single event transient pulse, and multiple bit upset that does not cause hard damage to the semiconductor device. The soft error sensitive area refers to the sensitive area where the above effects are likely to occur.

[0096] Among them, the radioactive isotope in the encapsulation material usually can continuously emit alpha particles after undergoing alpha decay. The flux of the particles refers to the number of alpha particles per unit area and per unit time. The flux-energy spectrum of the particles refers to the fitting relationship between the flux and energy of the alpha particles. After determining the encapsulation material of the electronic device, the flux-energy spectrum of the particles released by the encapsulation material of the electronic device can be obtained.

[0097] Among them, there is a dielectric layer between the active region of the semiconductor device and the encapsulation material. The dielectric layer can include only one dielectric or more than one dielectric. The dielectric property information can refer to information such as the thickness of the dielectric layer. By performing reverse analysis on the soft error sensitive area, the dielectric property information between the active region of the semiconductor device and the encapsulation material can be obtained. Among them, the dielectric property information can include the dielectric layer, the dielectric thickness information of each dielectric layer, and the dielectric composition information. Among them, the dielectric layer can include a metal wiring layer, a passivation layer, and an oxide layer, etc. Each dielectric layer corresponds to a dielectric thickness and a dielectric composition. For the metal wiring layer, its dielectric composition can mainly be Cu (copper) or Al (aluminum). For the oxide layer, its dielectric composition can mainly be SiO2 (silicon dioxide). For the passivation layer, its dielectric composition can mainly be Si3N4 (silicon nitride).

[0098] After obtaining the flux-energy spectrum of particles released from the encapsulation material of an electronic device and the information on the dielectric properties between the active region and the encapsulation material, a simulation model of the active region can be established based on the dielectric layer, the dielectric thickness information of each dielectric layer, and the dielectric composition information. The simulation model of the active region includes the active region layer and each dielectric layer. The simulation of the active region simulation model is performed according to the flux-energy spectrum, that is, the particles corresponding to the flux-energy spectrum are incident on the dielectric layer of the active region simulation model, and particle characteristic information is obtained on the surface of the active region layer of the active region simulation model. The particle characteristic information includes the associated active region surface energy, the emission angle, and the particle flux, and the flux-effective linear energy transfer value spectrum of the active region is determined based on the particle characteristic information.

[0099] Among them, when determining the particle flux-effective linear energy transfer value spectrum of the active region according to the particle characteristic information, the effective linear energy transfer value of the active region can be determined first according to the active region energy and the emission angle, and then the flux-effective linear energy transfer value spectrum of the active region can be determined according to the active region flux and the effective linear energy transfer value of the active region. When determining the effective linear energy transfer value, the alpha particles and the active region flux of the alpha particles can be input into a software tool (such as SRIM) or an empirical formula to obtain the initial effective linear energy, and finally the initial effective linear energy is divided by the cosine value of the emission angle to obtain the effective linear energy transfer value of the active region.

[0100] Finally, an integral operation can be performed on the particle flux-effective linear energy transfer value spectrum and the single-event effect cross-section value-effective linear energy transfer value spectrum to obtain the soft error rate of the electronic device. Specifically, the active region particle flux corresponding to the same effective linear energy transfer value and the single-event effect cross-section value can be multiplied to obtain the soft error rate of the electronic device. Thus, the calculation accuracy of the soft error rate can be improved through the above method.

[0101] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are sequentially shown according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0102] Based on the same inventive concept, an embodiment of the present application further provides an electronic device soft error rate evaluation device for implementing the electronic device soft error rate evaluation method involved above. The solution provided by this device for solving the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the electronic device soft error rate evaluation device provided below can refer to the limitations on the electronic device soft error rate evaluation method in the above text, and will not be elaborated here.

[0103] In one embodiment, as Figure 5 shown, an electronic device soft error rate evaluation device is provided, including: a soft error sensitive area determination module, a flux-energy spectrum determination module, a dielectric property information determination module, an active area information determination module, an electronic device information acquisition module, and a soft error rate determination module, where:

[0104] The flux-energy spectrum determination module 502 is configured to obtain the flux-energy spectrum of the particles released by the packaging material of the electronic device.

[0105] The dielectric property information determination module 504 is configured to perform reverse analysis on the electronic device to determine the dielectric property information between the active area of the electronic device and the packaging material.

[0106] The active area information determination module 506 is configured to determine the active area particle flux-linear energy transfer value spectrum of the electronic device in the active area according to the flux-energy spectrum and the dielectric property information.

[0107] The electronic device information acquisition module 508 is configured to obtain the single particle effect cross section value-linear energy transfer value spectrum of the electronic device obtained by irradiating the electronic device.

[0108] The soft error rate determination module 510 is configured to perform operations on the active area particle flux-linear energy transfer value spectrum and the single particle effect cross section value-linear energy transfer value spectrum to determine the soft error rate of the electronic device.

[0109] In one of the embodiments, the flux-energy spectrum determination module is configured to prepare a sample of the packaging material to obtain a sample; use an alpha particle surface emission measurement device to perform experimental measurement on the sample to obtain the flux-energy spectrum of the particles released by the packaging material.

[0110] In one embodiment, the flux-energy spectrum determination module is configured to establish a simulation model of the encapsulation material; simulate the simulation model of the encapsulation material to cause the simulation model of the encapsulation material to emit particles, and extract the outgoing parameters of the particles emitted by the simulation model of the encapsulation material; and determine the flux-energy spectrum of the particles released by the encapsulation material according to the outgoing parameters of the particles.

[0111] In one embodiment, the active region information determination module is configured to establish a simulation model of the active region according to the medium property information, where the simulation model of the active region includes an active region layer and each of the medium layers; simulate the simulation model of the active region according to the flux-energy spectrum, incident the particles corresponding to the flux-energy spectrum on the medium layers of the simulation model of the active region, and obtain particle characteristic information on the surface of the active region layer of the simulation model of the active region, where the particle characteristic information includes the associated active region surface energy, outgoing angle, and active region flux; and determine the active region flux-effective linear energy transfer value spectrum of the active region based on the particle characteristic information, where the medium property information includes: medium layers, medium thickness information of each medium layer, and medium composition information.

[0112] In one embodiment, the active region information determination module is configured to determine the effective linear energy transfer value of the active region based on the active region surface energy and the outgoing angle; and determine the particle flux-effective linear energy transfer value spectrum of the active region based on the particle flux and the effective linear energy transfer value of the active region.

[0113] In one embodiment, the active region information determination module is configured to determine the linear energy transfer value based on the type of particle and the active region surface energy; and divide the linear energy transfer value by the cosine value of the outgoing angle to determine the effective linear energy transfer value of the active region.

[0114] In one embodiment, the soft error rate determination module is configured to integrate the particle flux-effective linear energy transfer value spectrum and the single-event effect cross-section value-effective linear energy transfer value spectrum to obtain the soft error rate of the electronic device.

[0115] Each module in the above electronic device soft error rate evaluation device can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor of the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above respective modules.

[0116] In one embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 5As shown in the figure. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a method for evaluating the soft error rate of electronic devices. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0117] Those skilled in the art can understand that Figure 5 the structure shown in the figure is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0118] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, it implements the steps of the above-mentioned method for evaluating the soft error rate of electronic devices.

[0119] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by the processor, it implements the steps of the above-mentioned method for evaluating the soft error rate of electronic devices.

[0120] In one embodiment, a computer program product is provided, including a computer program. When the computer program is executed by the processor, it implements the steps of the above-mentioned method for evaluating the soft error rate of electronic devices.

[0121] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0122] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0123] The above-described embodiments only represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for evaluating the soft error rate of an electronic device, characterized in that, The method includes: Obtaining the flux - energy spectrum of particles released by the packaging material of the electronic device; Performing reverse analysis on the electronic device to determine the dielectric property information between the active region of the electronic device and the packaging material; Determining the particle flux - effective linear energy transfer value spectrum of the electronic device in the active region according to the flux - energy spectrum and the dielectric property information; wherein, the effective linear energy transfer value is the ratio between the linear energy transfer value and the cosine value of the emission angle of alpha particles on the surface of the active region; Obtaining the single - event effect cross - section value - effective linear energy transfer value spectrum of the electronic device obtained from the irradiation test of the electronic device; Performing operations on the particle flux - effective linear energy transfer value spectrum and the single - event effect cross - section value - effective linear energy transfer value spectrum to determine the soft error rate of the electronic device; The performing operations on the particle flux - effective linear energy transfer value spectrum and the single - event effect cross - section value - effective linear energy transfer value spectrum to determine the soft error rate of the electronic device includes: Integrating the particle flux - effective linear energy transfer value spectrum and the single - event effect cross - section value - effective linear energy transfer value spectrum to obtain the soft error rate of the electronic device.

2. The method according to claim 1, characterized in that The obtaining the flux - energy spectrum of particles released by the packaging material of the electronic device includes: Preparing a sample of the packaging material to obtain a sample for preparation; Using an alpha - particle surface emission measurement device to perform test measurements on the sample for preparation to obtain the flux - energy spectrum of particles released by the packaging material; Or, Establishing a simulation model of the packaging material; Simulating the packaging material simulation model to make the packaging material simulation model emit particles, and extracting the emission parameters of the particles emitted by the packaging material simulation model; Determining the flux - energy spectrum of particles released by the packaging material according to the emission parameters of the particles.

3. The method according to claim 1, wherein The dielectric property information includes: dielectric layers, the dielectric thickness information of each dielectric layer, and dielectric composition information; The determining the particle flux - effective linear energy transfer value spectrum of the electronic device in the active region according to the flux - energy spectrum and the dielectric property information includes: Establishing a simulation model of the active region according to the dielectric property information, and the simulation model of the active region includes an active region layer and each dielectric layer; Simulating the simulation model of the active region according to the flux - energy spectrum, making the particles corresponding to the flux - energy spectrum incident on the dielectric layer of the simulation model of the active region, and obtaining particle characteristic information on the surface of the active region layer of the simulation model of the active region, where the particle characteristic information includes the associated active region surface energy, emission angle, and particle flux; Determining the particle flux - effective linear energy transfer value spectrum of the active region based on the particle characteristic information.

4. The method according to claim 3, wherein The determining the particle flux - effective linear energy transfer value spectrum of the active region based on the particle characteristic information includes: Determining the effective linear energy transfer value of the active region based on the active region surface energy and emission angle; Determine the particle flux-linear energy transfer value spectrum of the active region based on the particle flux and the effective linear energy transfer value of the active region.

5. The method according to claim 4, characterized in that The determination of the effective linear energy transfer value of the active region based on the surface energy and the emission angle of the active region includes: Determine the linear energy transfer value based on the type of particle and the surface energy of the active region; Divide the linear energy transfer value by the cosine value of the emission angle to determine the effective linear energy transfer value of the active region.

6. An electronic device soft error rate evaluation device, characterized in that, The device includes: A flux-energy spectrum determination module, configured to obtain the flux-energy spectrum of the particles released by the packaging material of the electronic device; A dielectric property information determination module, configured to perform reverse analysis on the electronic device to determine the dielectric property information between the active region of the electronic device and the packaging material; An active region information determination module, configured to determine the particle flux-effective linear energy transfer value spectrum of the electronic device in the active region according to the flux-energy spectrum and the dielectric property information; wherein, the effective linear energy transfer value is the ratio between the linear energy transfer value and the cosine value of the emission angle of the alpha particle on the surface of the active region; An electronic device information acquisition module, configured to acquire the single-event effect cross-section value-effective linear energy transfer value spectrum of the electronic device obtained by irradiating the electronic device; A soft error rate determination module, configured to perform an operation on the particle flux-effective linear energy transfer value spectrum and the single-event effect cross-section value-effective linear energy transfer value spectrum to determine the soft error rate of the electronic device; The soft error rate determination module is configured to integrate the particle flux-effective linear energy transfer value spectrum and the single-event effect cross-section value-effective linear energy transfer value spectrum to obtain the soft error rate of the electronic device.

7. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 5 are implemented.

9. A computer program product comprising a computer program, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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