Microstructure change tracking method based on chip aging analysis

Abstract

The application relates to the technical field of data analysis, and is a microstructure change tracking method based on chip aging analysis, and specifically comprises the following steps: obtaining chip factory structure data is imported into a chip change prediction model, an initial aggregation stability index is obtained, chip aging condition evaluation is carried out, if the evaluation result is a to-be-refurbished level, a chip repair and refurbishment process is entered; if the evaluation result is a to-be-recycled level, a physical field coupling migration model is constructed, the initial instantaneous migration speed of noble metal atoms on the output chip is analyzed, adjacent noble metal atoms are interfered, the instantaneous migration speed is corrected and compensated, the aggregation density of noble metal atoms at each recycling evaluation point position on the chip is tracked, and a high-potential point of the chip is screened out. The application solves the problem of low identification efficiency of high-potential recycling points on an aging chip in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data analysis, and is a microstructure change tracking method based on chip aging analysis. BACKGROUND

[0002] With the rapid development of the semiconductor industry, the problem of the rapid increase of electronic waste and the shortage of precious metal resources is becoming increasingly serious, and chip recycling has become a key link of green manufacturing. During the long-term service of the chip, the internal microstructure of the chip will undergo irreversible aging due to the influence of dynamic stress such as temperature fluctuation and current load. In particular, precious metals (such as gold, platinum, and palladium) will gather or dissipate in a specific area due to the electromigration and thermomigration effect, forming a high-value recovery target point. The existing recycling process relies on physical crushing and chemical leaching, which not only has high energy consumption and causes serious pollution, but also leads to low recovery rate due to the inability to locate the precious metal gathering area.

[0003] The existing chip aging analysis technology focuses on life prediction and failure protection, and although it can indirectly evaluate the aging degree through electrical parameter degradation (such as resistance drift), it still has the following problems: first, the chip operating parameters cannot map the migration trajectory of the precious metal atoms, and there is no quantitative correlation between the structural changes and the historical working conditions; second, the existing migration model usually only considers a single physical field, which leads to deviation in the prediction of the migration speed of the precious metal atoms, which also distorts the simulation of the aggregation density; in addition, the existing technology rarely deeply mines the chip historical working log, making it difficult to accurately track the spatial distribution of the precious metals during the chip recycling stage. The above defects lead to low identification efficiency of high-potential recovery points on the aging chip. SUMMARY

[0004] This section aims to summarize some aspects of the embodiments of the present application and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the abstract and title of the specification to avoid obscuring the purpose of this section, abstract and title, and such simplifications or omissions cannot be used to limit the scope of the present application.

[0005] The technical problem to be solved by the present application is that the existing technology has low identification efficiency of high-potential recovery points on the aging chip. The present application provides a microstructure change tracking method based on chip aging analysis.

[0006] In order to achieve the above-mentioned purpose, the microstructure change tracking method based on chip aging analysis of the present application comprises the following steps:

[0007] S1: Obtain the chip factory structure data and the aging log data in the use process;

[0008] S2: Obtain the chip factory structure data, import the chip change prediction model, and perform initial aggregation area positioning to obtain an initial aggregation stability index;

[0009] S3: Perform chip aging condition evaluation according to the initial aggregation stability index;

[0010] If the evaluation result is a level to be refurbished, the chip repair and refurbishment process is entered;

[0011] If the evaluation result is a level to be recycled, step S4 is performed;

[0012] S4: Construct a physical field coupling migration model, and analyze the initial instantaneous migration speed of noble metal atoms on the chip through the physical field coupling migration model;

[0013] S5: Perform interference analysis on the migration behavior between adjacent noble metal atoms, correct and compensate the instantaneous migration speed output by S4 according to the interference analysis result, and then track the aggregation density of noble metal atoms at each recycling evaluation point position on the chip;

[0014] S6: Extract the aggregation density situation output by S5 and sort it to obtain an aggregation density sequence, and filter the aggregation density sequence to output the filtering result as the high potential points of the chip.

[0015] Preferably, step S1 comprises:

[0016] S11: Obtain three-dimensional structure map data of the chip at the time of factory shipment, wherein the three-dimensional structure map data comprises: noble metal initial distribution coordinate set data and lattice stress data;

[0017] S12: Obtain aging log data during use of the chip, wherein the aging log data comprises: chip cumulative use total duration, temperature fluctuation history, and current load curve;

[0018] S13: Construct an encrypted database to store the obtained three-dimensional structure map data and aging log data.

[0019] Preferably, step S2 comprises:

[0020] S21: Establish a chip change prediction model, and simultaneously extract chip factory structure data;

[0021] S22: Import the chip factory structure data into the chip change prediction model to perform initial aggregation area positioning and obtain an initial aggregation stability index .

[0022] Preferably, step S3 comprises:

[0023] S31: According to the initial aggregation stability index calculated in step S22 and the maximum stress value in the lattice stress data , chip aging condition assessment is performed, including:

[0024] When and , it is determined that the aggregation area is in a repairable state, and output is a refurbished level;

[0025] When or , it is determined that the aggregation area is in an unrecoverable state, and output is a recycling level;

[0026] wherein, is the yield strength of the material;

[0027] S32: chip processing decision according to the state assessment result of step S31, including:

[0028] If the assessment result is the refurbished level, proceed to chip repair and refurbishment processing;

[0029] If the assessment result is the recycling level, execute step S4.

[0030] Preferably, S4 includes:

[0031] S41: according to the aging log data of chip history in step S12, analyze to obtain the original impact intensity data set, including: thermal field impact intensity and electric field impact intensity ;

[0032] S42: according to the thermal field impact intensity and electric field impact intensity , the field coupling effect between the thermal physical field and the electric physical field is quantified to obtain the field coupling efficiency;

[0033] S43: combine the field coupling efficiency output by step S42 to synchronously evaluate the influence of the thermal physical field and the electric physical field on the noble metal migration behavior, and obtain the influence dominant intensity coefficient;

[0034] S44: according to the original impact intensity data set in step S41 and the influence dominant intensity coefficient output by step S43, construct the noble metal atom migration equation;

[0035] The noble metal atom migration equation is specifically:

[0036] ;

[0037] wherein, is the migration speed of the noble metal atom; is the influence dominant intensity coefficient of the thermal physical field; is the influence dominant intensity coefficient of the electric physical field; a thermal migration driving component and an electromigration driving component, respectively;

[0038] S45: According to the noble metal atom migration equation constructed in step S44, the initial instantaneous migration speed and the instantaneous position of the noble metal atom are calculated by a preset unit migration time.

[0039] Preferably, step S5 comprises:

[0040] S51: Interference analysis is performed on the migration behavior between adjacent noble metal atoms, and the initial instantaneous migration speed of the noble metal atom is modified and compensated according to the result of the interference analysis, and the modified instantaneous migration speed of the noble metal atom is output;

[0041] S52: According to Euler integral, the modified instantaneous migration speed of the noble metal atom is converted into displacement corresponding to the current unit migration time;

[0042] Meanwhile, the above strategy is executed in a loop to continue to calculate the displacement corresponding to the next unit migration time until the total migration time reaches the total cumulative use time of the chip, and the loop is stopped, and finally the displacement of the noble metal atom corresponding to all unit migration times is output to form an initial trajectory set;

[0043] S53: The initial trajectory set of the noble metal atom is output by step S52, and the aggregation density of the noble metal atom at each recovery evaluation point position on the chip is tracked;

[0044] The tracking strategy of the aggregation density of the noble metal atom is specifically:

[0045] ;

[0046] Wherein, is the aggregation density of the noble metal at the recovery evaluation point with a position of on the chip; N is the total number of noble metal atoms; i is the index of the noble metal atom; represents the mass of the i-th noble metal atom; represents the recovery evaluation point position on the chip; represents the real-time position of the i-th noble metal atom; is a Gaussian kernel function.

[0047] Preferably, step S51 comprises:

[0048] S511: Select any one noble metal atom on the chip as a target atom, construct a neighboring atom scope corresponding to the target atom with the target atom as the center, and simultaneously extract the position vector, stress value and real-time temperature value of all neighboring atoms in the neighboring atom scope;

[0049] S512: analyze the interference intensity of each neighboring atom in the neighboring atom scope to the target atom;

[0050] S513: extract the interference intensity of each neighboring atom in the neighboring atom scope to the target atom, and analyze the interference resultant force vector of all neighboring atoms in the neighboring atom scope to the target atom ;

[0051] S514: correct and compensate the initial instantaneous migration speed of the noble metal atom in step S44 by the interference resultant force vector output in step S513, to obtain the corrected instantaneous migration speed of the target atom;

[0052] S515: traverse all noble metal atoms on the chip, and repeatedly execute steps S511-S514 to complete the correction and compensation of the instantaneous migration speed of all noble metal atoms on the chip.

[0053] Preferably, step S6 comprises:

[0054] S61: extract the aggregation density of the noble metal atom at each recycling evaluation point position on the chip output in S5;

[0055] S62: sort the aggregation density corresponding to each recycling evaluation point position on the chip from large to small to obtain an aggregation density sequence;

[0056] S63: screen the top 30% of recycling evaluation point positions in the aggregation density sequence, and output the screened recycling evaluation point positions as high-potential points of the chip.

[0057] A storage medium, wherein instructions are stored in the storage medium, when a computer reads the instructions, the computer executes the microstructure change tracking method based on chip aging analysis.

[0058] An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the microstructure change tracking method based on chip aging analysis when executing the computer program.

[0059] Compared with the prior art, the technical effects of the present application are as follows:

[0060] 1. In terms of noble metal migration trajectory prediction accuracy, the present application quantifies the synergistic driving mechanism of temperature gradient and current density by fusing a double-field coupling migration model of thermal and electrical physical fields, thereby reducing migration speed prediction deviation; at the same time, the present application also performs real-time dynamic compensation on the short-range stress interference of neighboring atoms, thereby improving the accuracy of noble metal atom aggregation density.

[0061] 2. Regarding the efficiency of target location in the recycling of aged chips, this invention estimates the aggregation density of precious metal atoms and accurately maps the gradient distribution of precious metals on the chip, thereby significantly improving the accuracy of identifying high-value recycling points.

[0062] 3. This invention combines chip factory structure data with chip aging log data to evaluate the initial aggregation stability index, thereby realizing the analysis and tracking of chip aging status throughout its entire life cycle, reducing energy consumption in precious metal refining, and improving the utilization rate of chip resources. Attached Figure Description

[0063] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0064] Figure 1 This is a flowchart illustrating the microstructure change tracking method based on chip aging analysis of the present invention. Detailed Implementation

[0065] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0066] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0067] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0068] Example 1:

[0069] like Figure 1 As shown in the figure, the microstructure change tracking method based on chip aging analysis in this embodiment of the invention is as follows: Figure 1 As shown, the specific steps include the following:

[0070] S1: Obtain chip factory structure data and aging log data during use;

[0071] Step S1 includes:

[0072] S11: Obtain three-dimensional structure map data of the chip at the time of factory shipment, wherein the three-dimensional structure map data comprises: noble metal initial distribution coordinate set data and lattice stress data;

[0073] Illustratively, in this embodiment, the noble metal initial distribution coordinate set data comprises initial position data of noble metal elements (such as gold, platinum or palladium) within the chip;

[0074] Illustratively, the lattice stress data is used to quantify the stress state in each direction inside the chip crystal;

[0075] S12: Obtain aging log data during the use of the chip, wherein the aging log data comprises: chip cumulative use total duration, temperature fluctuation history and current load curve.

[0076] It should be noted that the temperature fluctuation history is used to quantify the influence of temperature fluctuation on chip aging; it should also be noted that the current load curve is used to analyze the influence of electromigration or current overload on chip aging;

[0077] S13: Construct an encrypted database to store the obtained three-dimensional structure map data and aging log data.

[0078] S2: Import chip factory structure data into a chip change prediction model to perform initial aggregation area positioning, and obtain an initial aggregation stability index;

[0079] Step S2 comprises:

[0080] S21: Establish a chip change prediction model, and simultaneously extract chip factory structure data;

[0081] S22: Import the chip factory structure data into the chip change prediction model to perform initial aggregation area positioning, and obtain an initial aggregation stability index.

[0082] Illustratively, in this embodiment, a strategy for performing initial aggregation area positioning is provided, which comprises: extracting a stress value corresponding to each noble metal atomic coordinate point and the aggregation area center coordinate from the noble metal initial distribution coordinate set and the lattice stress tensor matrix in the chip factory structure data , while obtaining the material yield strength ;

[0083] It should be noted that, in this embodiment, the characteristic diffusion distance is ;

[0084] Illustratively, in this embodiment, a strategy for calculating the initial aggregation stability index is provided, which specifically comprises:

[0085] ;

[0086] wherein, is the initial aggregation stability index; n is the total number of noble metal atoms in the aggregation region; is the coordinate point of the kth noble metal atom; is the center coordinate of the aggregation region; is the characteristic diffusion distance; is the stress value; is the material yield strength;

[0087] It should be noted that, for the exponential term , when the noble metal atom is farther away from the aggregation center, i.e. , the exponential term is smaller, i.e. the contribution of the edge noble metal atom to the initial aggregation stability index is weakened; for the stress stability term , considering that high stress will promote the migration of noble metal atoms, the stress stability term is used to quantify the inhibition of the mechanical environment on the stability, when the local stress is larger, the stress stability term is smaller, i.e. the contribution to the initial aggregation stability index is also reduced;

[0088] It should be further noted that, first, the exponential term and the stress stability term are multiplied to represent the comprehensive ability of the noble metal atom at the current position to resist migration, and then all the atoms in the aggregation region are averaged to reflect the overall stability level of the aggregation region on the chip.

[0089] S3: evaluating the chip aging condition according to the initial aggregation stability index;

[0090] If the evaluation result is the to-be-renovated level, the chip repair and renovation process is entered;

[0091] If the evaluation result is the to-be-recycled level, step S4 is executed;

[0092] Step S3 includes:

[0093] S31: evaluating the chip aging condition according to the initial aggregation stability index and the maximum stress value in the lattice stress data calculated in step S22, including:

[0094] When and , it is determined that the aggregation region is in a repairable state, and the to-be-renovated level is output;

[0095] When or , it is determined that the aggregation region is in an unrepairable state, and the to-be-recycled level is output;

[0096] S32: making a chip processing decision according to the state evaluation result of step S31, including:

[0097] If the evaluation result is a level to be overhauled, the chip is sent to a chip repair and overhaul process;

[0098] If the evaluation result is a level to be recycled, step S4 is performed.

[0099] S4: constructing a physical field coupling migration model, and analyzing the initial instantaneous migration speed of noble metal atoms on the output chip through the physical field coupling migration model;

[0100] S4 includes:

[0101] S41: according to the aging log data of the chip history of step S12, analyzing to obtain an original impact intensity data set, including: thermal field impact intensity and electric field impact intensity ;

[0102] Exemplarily, in the embodiment, the acquisition strategy of the thermal field impact intensity is specifically: according to the aging log data of the chip history, determining the total number M of chip temperature fluctuations in the chip use process, synchronously extracting the temperature change amount of each chip temperature fluctuation, using the temperature change amount of each chip temperature fluctuation divided by the baseline temperature of the chip working to obtain the chip thermal fluctuation ratio, and taking the average of the chip thermal fluctuation ratios generated by M times of chip temperature fluctuations to obtain the thermal field impact intensity;

[0103] Exemplarily, in the embodiment, the acquisition strategy of the electric field impact intensity is specifically: according to the aging log data of the chip history, determining the total number G of chip current fluctuations in the chip use process, synchronously extracting the current change amount of each chip current fluctuation, using the current change amount of each chip current fluctuation divided by the baseline current of the chip working to obtain the chip electric fluctuation ratio, and taking the average of the chip electric fluctuation ratios generated by G times of chip current fluctuations to obtain the electric field impact intensity;

[0104] S42: quantifying the field coupling effect between the thermal physical field and the electric physical field according to the thermal field impact intensity and the electric field impact intensity , to obtain the field coupling efficiency;

[0105] It should be noted that in the chip working process, the temperature field (i.e. thermal physical field) and the electric field (i.e. electric physical field) will influence each other, because high temperature will aggravate the electromigration of noble metal atoms, and the joule heat generated by the current will also affect the temperature distribution, so the two have a synergistic effect on the migration of noble metal atoms;

[0106] Based on the above description, in this embodiment, a quantification strategy of the field coupling effect between the thermal physical field and the electric physical field is provided, specifically:

[0107] ;

[0108] wherein, is the field coupling efficiency between the thermal physical field and the electric physical field; is the maximum field coupling efficiency between the thermal physical field and the electric physical field, which represents the maximum coupling strength under the condition that the two fields are sufficiently strong and balanced, in this embodiment, is calibrated through a plurality of sets of double-field joint aging experiments; is the field synergy function;

[0109] It should be noted that, considering that the field coupling effect is subject to the weaker one of the two fields, in this embodiment, a limiting factor is set, which aims to ensure that when a single field dominates, the field coupling effect tends to zero, avoiding false coupling signals generated by a single field strong driving;

[0110] In this embodiment, an implementation example of the field synergy function is provided, specifically: ;

[0111] wherein, are the coupling activation thresholds of the thermal physical field and the electric physical field, respectively, that is, the physical field needs to reach a certain strength to contribute to the coupling;

[0112] It should be noted that, is the thermal field activation function, which is used to quantify the contribution of the thermal field to the coupling, when is very small, this term is close to 0; when increases, this term gradually saturates to 1; is the electric field activation function, which is used to quantify the contribution of the electric field to the coupling.

[0113] S43: The field coupling efficiency output in step S42 is combined to synchronously evaluate the influence dominant situation of the thermal physical field and the electric physical field on the noble metal migration behavior, to obtain an influence dominant intensity coefficient;

[0114] In this embodiment, an evaluation strategy of the influence dominant situation of the thermal physical field and the electric physical field on the noble metal migration behavior is also provided, specifically:

[0115] ;

[0116] wherein, y is the index of the physical field, is the impact intensity of the physical field with index y; a dominant intensity coefficient of a physical field indexed by y;

[0117] S44: constructing a noble metal atom migration equation according to the original impact intensity data set in step S41 and the impact dominant intensity coefficient output in step S43;

[0118] The noble metal atom migration equation is specifically:

[0119] ;

[0120] Wherein, is the migration speed of the noble metal atom; is the impact dominant intensity coefficient of the thermal physical field; is the impact dominant intensity coefficient of the electric physical field; are a thermal migration driving component and an electric migration driving component, respectively;

[0121] Exemplarily, in the embodiment, an implementation example of a thermal migration driving component is provided, which is specifically: ;

[0122] Wherein, is a thermal migration coefficient, used for quantifying a thermal driving force; is a thermal migration activation energy, used for representing a thermal activation process; is a Boltzmann constant; is a real-time temperature value; is a temperature gradient;

[0123] In the embodiment, the thermal migration coefficient is a material constant, and is obtained by fitting the migration speed at multiple temperatures under the condition that the thermal migration activation energy and the temperature are known;

[0124] It should be noted that, for the thermal migration driving component, it is aimed at quantifying the migration of the noble metal atom due to the non-uniform temperature, and is used for predicting the redistribution of the noble metal atom caused by local overheating on the chip; the thermal migration driving component represents the migration of the noble metal atom driven by the temperature gradient, i.e. thermal migration, wherein the exponential term represents the thermal activation process, the higher the temperature, the easier the migration, and the greater the temperature gradient, the faster the migration speed;

[0125] Exemplarily, in the embodiment, based on a standard electric migration model, i.e. Black equation, an implementation example of an electric migration driving component is provided, which is specifically:

[0126] ;

[0127] Wherein, is an electric migration coefficient; is an electric migration activation energy, used for representing an electric migration activation process; is the current density, used to quantify the electromigration driving force; is the Boltzmann constant; is the real-time temperature value; is the effective electrical load; it is noted that for the electromigration driving component, which aims to predict the atomic migration in the direction of the current, it represents the current-driven atomic migration.

[0128] Exemplarily, in the embodiment, based on the Black equation, the electromigration coefficient is specifically: ; wherein, is the standard diffusion coefficient; represents the elementary charge; represents the resistivity;

[0129] S45: According to the noble metal atomic migration equation constructed in step S44, the initial instantaneous migration speed and the instantaneous position of the noble metal atom are calculated through a preset unit migration time.

[0130] S5: Interference analysis is performed on the migration behavior between adjacent noble metal atoms, the instantaneous migration speed output in S4 is modified and compensated according to the interference analysis result, and then the aggregation density of the noble metal atoms at each recycling evaluation point position on the chip is tracked;

[0131] Step S5 includes:

[0132] S51: Interference analysis is performed on the migration behavior between adjacent noble metal atoms, the initial instantaneous migration speed of the noble metal atom is modified and compensated according to the interference analysis result, and the modified instantaneous migration speed of the noble metal atom is output;

[0133] S52: The modified instantaneous migration speed of the noble metal atom is converted into the displacement corresponding to the current unit migration time according to Euler integral;

[0134] Exemplarily, in the embodiment, a conversion strategy for converting the modified instantaneous migration speed into the displacement corresponding to the current unit migration time is provided, which is specifically:

[0135] ;

[0136] wherein, is the atomic position of the next unit migration time; is the real-time position of the atom at the kth unit migration time; is the modified instantaneous migration speed of the noble metal atom, which is calculated by the noble metal atomic migration equation, is the unit migration time;

[0137] Meanwhile, the above strategy is executed in a loop to continue calculating the displacement corresponding to the next unit migration time until the total migration time reaches the total accumulated use time of the chip, at which point the loop is stopped, and finally the displacement of the noble metal atoms corresponding to all unit migration times is output to form the initial trajectory set;

[0138] S53: Output the initial trajectory set of the noble metal atoms by step S52 to track the aggregation density of the noble metal atoms at each recovery evaluation point position on the chip;

[0139] The tracking strategy of the aggregation density of the noble metal atoms is specifically:

[0140] ;

[0141] wherein, is the aggregation density of the noble metal at the recovery evaluation point with the position on the chip; N is the total number of noble metal atoms; i is the index of the noble metal atom; represents the mass of the i-th noble metal atom; represents the recovery evaluation point position on the chip; represents the real-time position of the i-th noble metal atom; is a Gaussian kernel function;

[0142] It should be noted that for , it represents the displacement vector of the recovery evaluation point position on the chip relative to the real-time position of the i-th noble metal atom, which is used to determine the distance between each recovery evaluation point on the chip and the noble metal atom;

[0143] It should be further noted that first, the mass of the noble metal atom is multiplied by the Gaussian kernel function, which essentially distributes the mass of the noble metal atom on the chip according to the Gaussian kernel function. This processing aims to convert the mass of the discrete noble metal atom on the chip into a continuous density field; then, the above product is summed to superimpose the contribution of all noble metal atoms on the chip to the recovery evaluation point position on the chip;

[0144] Exemplarily, in the present embodiment, the Gaussian kernel function is:

[0145] ;

[0146] wherein, is the standard deviation of the Gaussian kernel; represents the Euclidean distance between the recovery evaluation point position on the chip and the atomic position ;

[0147] It should be noted that, for the normalization coefficient term , based on the mass conservation law of the atomic density field, it aims to ensure that the integral of the Gaussian function is 1; for the exponential term , it aims to construct a continuous distribution of atomic mass in space, and the closer the noble metal atoms are to the chip recycling evaluation point position, the greater the aggregation density of the chip recycling evaluation point position.

[0148] Step S51 includes:

[0149] S511: Select any one noble metal atom on the chip as a target atom, and construct the adjacent atom scope corresponding to the target atom with the target atom as the center, and simultaneously extract the position vector, stress value and real-time temperature value of all adjacent atoms in the adjacent atom scope;

[0150] Exemplarily, in the embodiment, a construction strategy of the adjacent atom scope is provided, specifically: in the current unit migration time, the adjacent atom scope corresponding to the target atom is constructed with the target atom as the center, the noble metal atoms in the adjacent atom scope are queried by using the spatial indexing technology, and the queried noble metal atoms are marked as adjacent atoms;

[0151] Exemplarily, the radius of the adjacent atom scope is three times the characteristic diffusion distance of the noble metal atom, that is, 45nm; it should be noted that, in the embodiment, the radius of the adjacent atom scope is set to three times the characteristic diffusion distance of the noble metal atom, which aims to ensure that the interaction of the medium and short-range migration behavior can be completely captured.

[0152] S512: Analyze the interference intensity of each adjacent atom in the adjacent atom scope on the target atom;

[0153] Exemplarily, in the embodiment, a strategy for analyzing the interference intensity of the jth adjacent atom on the target atom is provided, specifically:

[0154] ;

[0155] Wherein, i represents the target atom; j represents the jth adjacent atom; is the interference intensity of the jth adjacent atom on the target atom; represents the stress of the jth adjacent atom, represents the yield strength of the material; is the real-time position of the target atom; is the position vector of the jth adjacent atom; is the characteristic diffusion distance; is the coupling effect strength of the thermophysical field and the electrophysical field;

[0156] S513: Extract the interference intensity of each neighboring atom in the neighboring atom scope to the target atom, and analyze the interference resultant force vector of all neighboring atoms in the neighboring atom scope to the target atom ;

[0157] Exemplarily, in the embodiment, the construction strategy of the interference resultant force vector of all neighboring atoms to the target atom is specifically:

[0158] ;

[0159] wherein, is the reference force vector between noble metal atoms;

[0160] S514: The interference resultant force vector output by step S513 is used to correct and compensate the initial instantaneous migration speed of the noble metal atom in step S44, to obtain the corrected instantaneous migration speed of the target atom;

[0161] Exemplarily, in the embodiment, the strategy for correcting and compensating the initial instantaneous migration speed of the noble metal atom is: the initial instantaneous migration speed of the noble metal atom obtained in step S44 is added to the product of the interference resultant force vector obtained in step S452 and the migration rate coefficient, to obtain the corrected instantaneous migration speed;

[0162] Exemplarily, in the embodiment, a strategy for obtaining the migration rate coefficient is provided, which is specifically: ;

[0163] wherein, is the migration rate coefficient; is the basic migration rate; is the activation energy; it should be noted that the basic migration rate and the activation energy are obtained according to a material database;

[0164] S515: All noble metal atoms on the chip are traversed, and steps S511-S514 are repeatedly executed to complete the correction and compensation of the instantaneous migration speed of all noble metal atoms on the chip.

[0165] S6: Extract and sort the aggregation density situation output by S5 to obtain an aggregation density sequence, and perform screening processing on the aggregation density sequence, and output the screening result as the high potential point of the chip.

[0166] Step S6 includes:

[0167] S61: Extract the aggregation density of the noble metal atom at each recycling evaluation point position on the chip output by S5;

[0168] S62: Sort the aggregation density of each recycling evaluation point position on the chip from large to small to obtain an aggregation density sequence.

[0169] S63: Screen the top 30% recycling evaluation point positions in the aggregation density sequence, and output the screened recycling evaluation point positions as high potential points of the chip.

[0170] Embodiment Two:

[0171] The embodiment provides an electronic device, comprising a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0172] The processor executes the microstructure change tracking method based on chip aging analysis by calling the computer program stored in the memory.

[0173] The electronic device can have great differences due to different configurations or performances, and can include one or more processors (Central Processing Units, CPUs) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement the microstructure change tracking method based on chip aging analysis provided by the above method embodiments. The electronic device can also include other components for realizing device functions, for example, the electronic device can also have a wired or wireless network interface and an input and output interface, and the like, so as to perform input and output of data. The embodiment will not be described here.

[0174] Embodiment Three:

[0175] The embodiment provides a computer readable storage medium, which stores an erasable computer program;

[0176] When the computer program runs on the computer device, the computer device executes the microstructure change tracking method based on chip aging analysis.

[0177] For example, the computer readable storage medium can be a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a read-only compact disc (Compact Disc Read-Only Memory, CD-ROM), a magnetic tape, a floppy disk and an optical data storage device, etc.

[0178] It should be understood that the magnitude of the sequence number of each process described above does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0179] It should be understood that determining B according to A does not mean that B is determined only according to A, but B can also be determined according to A and / or other information.

[0180] The above embodiments can be realized wholly or partially by software, hardware, firmware or any other combination. When realized by software, the above embodiments can be realized wholly or partially in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the flow or function according to the embodiments of the present application is wholly or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through a wired network or / and wireless network. The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server, data center and the like containing one or more available medium collections. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD) or a semiconductor medium. The semiconductor medium can be a solid-state disk.

[0181] Those skilled in the art can realize that the units and algorithm steps of the examples described in combination with the disclosed embodiments of the present application can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0182] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described system, device and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be described here.

[0183] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the device embodiments described above are merely illustrative, and the division of units is merely one kind, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed units can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0184] The basic principles and main features of the present application and the advantages of the present application are shown and described above. Those skilled in the art should understand that the present application is not limited to the above embodiments, and the above embodiments and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A microstructure change tracking method based on chip aging analysis, characterized by, The method comprises the following specific steps: S1: Obtain chip factory structure data and aging log data in use process; S2: Obtain chip factory structure data and import chip change prediction model for initial cluster positioning to obtain initial cluster stability index; S3: Perform chip aging condition evaluation according to the initial cluster stability index: If the evaluation result is a level to be refurbished, enter the chip repair and refurbishment process; If the evaluation result is a level to be recycled, execute step S4; S4: Build a physical field coupling migration model, and analyze the initial instantaneous migration speed of noble metal atoms on the chip through the physical field coupling migration model; S4 comprises: S41: According to the chip history aging log data, the original impact intensity data set is analyzed, including: thermal field impact intensity and electric field impact intensity ; S42: according to the thermal field impact strength and the electric field impact strength , quantifying the field coupling effect between the thermal physical field and the electric physical field, obtaining the field coupling efficiency; S43: Synchronize the evaluation of the influence of the thermal physical field and the electrical physical field on the migration behavior of the noble metal by combining the field coupling efficiency output in step S42, and obtain an influence dominant intensity coefficient; S44: According to the original impact intensity data set in step S41 and the influence dominant intensity coefficient output in step S43, build a noble metal atom migration equation; The noble metal atom migration equation is specifically: ； wherein is the migration speed of noble metal atoms; is the dominant intensity coefficient of the influence of the thermophysical field; is the dominant intensity coefficient of the influence of the electro-physical field; are the thermal and electric migration driving components, respectively; S45: According to the noble metal atom migration equation obtained in step S44, calculate the initial instantaneous migration speed and instantaneous position of the noble metal atom through a preset unit migration time; S5: Perform interference analysis on the migration behavior between adjacent noble metal atoms, modify and compensate the instantaneous migration speed output in S4 according to the interference analysis result, and then track the aggregation density of the noble metal atoms at each recycling evaluation point position on the chip; S6: Extract and sort the aggregation density situation output in S5 to obtain an aggregation density sequence, and filter the aggregation density sequence to output the filtering result as the high potential points of the chip.

2. The microstructure change tracking method based on chip aging analysis according to claim 1, characterized by, Step S1 comprises: S11: Obtain three-dimensional structure map data of the chip at the time of factory shipment, wherein the three-dimensional structure map data comprises noble metal initial distribution coordinate set data and lattice stress data; S12: Obtain aging log data in the use process of the chip, wherein the aging log data comprises chip cumulative use total time length, temperature fluctuation history and current load curve; S13: Build an encrypted database to store the obtained three-dimensional structure map data and aging log data.

3. The microstructure change tracking method based on chip aging analysis according to claim 2, characterized by, Step S2 comprises: S21: Establish a chip change prediction model, and simultaneously extract chip factory structure data; S22: import the chip factory structure data into the chip change prediction model, perform initial cluster positioning, and obtain an initial cluster stability index .

4. The microstructure change tracking method based on chip aging analysis according to claim 3, characterized by, Step S3 comprises: S31: the maximum stress value in the lattice stress data calculated according to step S22 chip aging condition evaluation, including: When and the aggregation area is determined to be in a repairable state, and output as a refurbished level; When or the aggregation area is determined to be in an irreparable state, and output as a recycling level. wherein, Ys is the yield strength of the material; S32: Make chip processing decisions according to the state evaluation result of step S31, including: If the evaluation result is a level to be refurbished, enter the chip repair and refurbishment process; If the evaluation result is a level to be recycled, execute step S4.

5. The microstructure change tracking method based on chip aging analysis according to claim 4, characterized by, Step S5 comprises: S51: Perform interference analysis on the migration behavior between adjacent noble metal atoms, modify and compensate the initial instantaneous migration speed of the noble metal atom according to the interference analysis result, and output the modified instantaneous migration speed of the noble metal atom; S52: Convert the modified instantaneous migration speed of the noble metal atom into displacement corresponding to the current unit migration time according to Euler integral; Meanwhile, the above strategy is executed in a loop to continue calculating the displacement corresponding to the next unit migration time until the total migration time reaches the total accumulated use time of the chip, the loop is stopped, and finally the displacements of the noble metal atoms corresponding to all unit migration times are output to form the initial trajectory set; S53: Output the initial trajectory set of the noble metal atoms by step S52 to track the aggregation density of the noble metal atoms at each recovery evaluation point position on the chip; The tracking strategy of the aggregation density of the noble metal atoms is specifically: ； wherein, is the aggregated density of noble metals at the recovery evaluation point with the on-chip position ; N is the total number of noble metal atoms; i is the index of noble metal atoms; represents the mass of the i-th noble metal atom; represents the on-chip recovery evaluation point position; represents the real-time position of the i-th noble metal atom; is a Gaussian kernel function.

6. The microstructure change tracking method based on chip aging analysis according to claim 5, wherein, Step S51 includes: S511: Select any one noble metal atom on the chip as a target atom, construct a neighboring atom scope corresponding to the target atom with the target atom as the center, and simultaneously extract the position vector, stress value and real-time temperature value of all neighboring atoms in the neighboring atom scope; S512: Analyze the interference intensity of each neighboring atom in the neighboring atom scope on the target atom; S513: Extract the interference intensity of each neighboring atom in the neighboring atom scope to the target atom, and analyze the interference resultant force vector of all neighboring atoms in the neighboring atom scope to the target atom ; S514: The interference resultant force vector output by step S513 is used to correct and compensate the initial instantaneous migration speed of the noble metal atom in step S44 to obtain the corrected instantaneous migration speed of the target atom; S515: Traverse all noble metal atoms on the chip, and repeat steps S511-S514 to complete the correction and compensation of the instantaneous migration speed of all noble metal atoms on the chip.

7. The microstructure change tracking method based on chip aging analysis according to claim 6, wherein, Step S6 includes: S61: Extract the aggregation density of the noble metal atoms at each recovery evaluation point position on the chip output by S5; S62: Sort the aggregation density corresponding to each recovery evaluation point position on the chip from large to small to obtain an aggregation density sequence; S63: Screen the top 30% of the recovery evaluation point positions in the aggregation density sequence, and output the screened recovery evaluation point positions as the high-potential points of the chip.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the microstructure change tracking method based on chip aging analysis according to any one of claims 1-7.

9. An electronic device, comprising: Comprise: A memory for storing instructions; A processor for executing the instructions to enable the device to perform operations to implement the microstructure change tracking method based on chip aging analysis according to any one of claims 1-7.

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