Device transport property analysis system integrating digital twinning and multi-scale coupling methods

Abstract

The invention discloses a device transport property analysis system fusing a digital twinning method and a multi-scale coupling method, and relates to the field of device transport property analysis. Comprising a data acquisition and preprocessing module, a digital twin model construction module, a multi-scale coupling analysis module, a transport property analysis and prediction module, a result display and interaction module and a system management module. According to the device transport property analysis system fusing the digital twinning method and the multi-scale coupling method, the limitation of traditional single-scale analysis is broken through by the multi-scale coupling analysis module, and microscopic, mesoscopic and macroscopic scale models are organically combined; according to the multi-scale coupling method, information interaction and collaborative analysis among different scales are realized through a unique scale coupling mechanism, and the multi-scale coupling method can comprehensively reveal the physical process and mutual influence of the device under different scales, so that the analysis result is more in line with the actual situation, and a more scientific way is provided for deeply understanding the transportation property of the device.

Description

Technical Field

[0001] The present invention relates to the field of analysis of device transport properties, and in particular to a device transport property analysis system that integrates digital twins and multi-scale coupling methods. Background Art

[0002] In fields such as semiconductor devices, accurately analyzing device transport properties is crucial for device design, performance optimization, and new product development. Existing semiconductor transport software is mostly based on single-scale models. For example, the macroscopic classical electrodynamics model can only describe the device's electrical characteristics from a holistic perspective, making it difficult to delve into the quantum behavior of electrons at the microscopic scale or the influence of nanostructures on carrier transport at the mesoscopic scale. This single-scale analysis approach results in an incomplete understanding of the physical processes within the device, making it impossible to accurately predict device performance under complex operating conditions.

[0003] Furthermore, existing analysis software has shortcomings in data utilization and model building. Data sources are relatively limited, typically relying solely on experimental test data or theoretical calculation data, making it difficult to integrate and utilize multi-source data from device design and manufacturing processes. Model construction lacks realistic simulations of actual devices and cannot reflect the dynamic behavior of devices under different operating conditions in real time, resulting in significant deviations between analysis results and actual conditions. Furthermore, the various analysis steps in existing technologies are relatively independent, lacking effective data interaction and collaborative analysis mechanisms, making it difficult to achieve systematic research and comprehensive optimization of device transport properties.

[0004] Therefore, it is necessary to propose a device transport property analysis system that integrates digital twins and multi-scale coupling methods to solve the above problems. Summary of the Invention

[0005] The main purpose of the present invention is to provide a device transport property analysis system that integrates digital twins and multi-scale coupling methods, which can effectively solve the problems in the background technology.

[0006] To achieve the above object, the technical solution adopted by the present invention is: A device transport property analysis system that integrates digital twins and multi-scale coupling methods includes a data acquisition and preprocessing module, a digital twin model construction module, a multi-scale coupling analysis module, a transport property analysis and prediction module, a result display and interaction module, and a system management module. The data acquisition and preprocessing module is used to collect multi-source data on device design and process, clean it, fill missing values, and standardize it. The digital twin model construction module constructs a hierarchical digital twin model based on the collected data, which is calibrated with the experimental data to accurately reproduce the working state of the device for analyzing the virtual object; The multi-scale coupling analysis module is used to divide the microscopic, mesoscopic and macroscopic scale modeling, realize scale coupling through interpolation mapping, and comprehensively analyze the transport properties of the device; The transport property analysis and prediction module analyzes the electrical and thermal transport properties of the device based on the model and analysis results, predicts performance and provides optimization suggestions; The result display and interaction module is used to present the results in a variety of visual ways, provide interactive functions, and support parameter adjustment and result export; The system management module covers user, data management and system monitoring and maintenance, and is used to ensure the safe operation of the system.

[0007] Preferably, the data acquisition and preprocessing module includes a data acquisition module and a data preprocessing module, wherein the data acquisition module is used to collect data related to the analysis of the transport properties of the device; The data preprocessing module is used to preprocess the collected data, including data cleaning, missing value processing, and standardization.

[0008] Preferably, the digital twin model construction module includes a model architecture design module and a model parameter calibration module, wherein the model architecture design module constructs a digital twin model of the device based on the data provided by the data acquisition and preprocessing module. The model adopts a layered architecture and is divided into a geometric model layer, a material property layer and a physical field model layer. The geometric model layer constructs the three-dimensional geometric structure of the device according to the design drawings of the device, including the shape and size information of the device; the material property layer maps the material characteristic data to the geometric model and assigns corresponding material properties to each component; the physical field model layer establishes equations describing the physical phenomena inside the device based on the laws of physics; The model parameter calibration module is used to calibrate the parameters of the constructed digital twin model, compare the model simulation results with the experimental test data, and adjust the parameters in the model to make the two match, so as to truly reproduce the working status of the device.

[0009] Preferably, the multi-scale coupling analysis module includes a scale division and modeling module and a scale coupling mechanism module, wherein the scale division and modeling module is used to divide the physical process of the device according to different scales in the semiconductor device, and establish corresponding models respectively, specifically including microscopic, mesoscopic and macroscopic scales. At the microscopic scale, the quantum mechanics model is used to describe the behavior of electrons at the atomic and molecular scales; at the mesoscopic scale, molecular dynamics simulation and other methods are used to study the transport characteristics of carriers in nanostructures; at the macroscopic scale, based on classical electrodynamics and thermodynamics theory, equations describing the overall electrical and thermal performance of the device are established.

[0010] Preferably, the scale coupling mechanism module is used to realize information interaction and collaborative analysis between multiple scales, and adopts a method based on interpolation and mapping to transfer the calculation results at the micro and meso scales to the macro scale model, providing boundary conditions and parameters for the macro model; at the same time, the calculation results at the macro scale are also fed back to the micro and meso scale models, affecting the physical processes at the micro and meso scales.

[0011] Preferably, the transport property analysis and prediction module includes a transport property analysis module and a performance prediction and optimization suggestion module, wherein the transport property analysis module conducts an in-depth analysis of the transport properties of the device based on the digital twin model and multi-scale coupling analysis results, and analyzes the change patterns of the device's current, voltage characteristics, conductivity, and resistance parameters with working conditions from the perspective of electrical performance; from the perspective of thermal performance, studies the temperature distribution and heat flux density inside the device, evaluates the device's heat dissipation performance, and uses visualization tools to intuitively display the analysis results in charts and cloud maps.

[0012] Preferably, the performance prediction and optimization suggestion module simulates the transport performance of the device under different design schemes based on changing the parameters in the digital twin model, predicts the performance of the device under future working conditions, and provides users with suggestions for optimizing device design and performance based on the prediction results combined with multi-scale coupling analysis.

[0013] Preferably, the result display and interaction module includes a visualization display module and a user interaction module, wherein the visualization display module displays the results of the transport property analysis and prediction module to the user in a rich and diverse visualization form, and also uses animation demonstration to dynamically display the physical process changes of the device at different working stages; The user interaction module is used to freely select analysis objects and parameters of interest through a graphical interface and adjust the method and angle of visual display.

[0014] Preferably, the system management module includes a user management module, a data management module and a system monitoring and maintenance module, wherein the user management module is used to manage system users, including user registration, login, and authority allocation, and to set different operation permissions according to the user's role; The system monitoring and maintenance module is used to uniformly manage the data in the system, including data storage, backup, recovery and deletion. It uses a database management system to classify and store the collected data, model data and analysis result data to ensure the security and integrity of the data, and back up the data regularly to prevent data loss.

[0015] Preferably, the system monitoring and maintenance module is used to monitor the operating status of the system in real time, including server resource usage and module operation status. When the system fails or is abnormal, an alarm is issued in time and relevant log information is recorded.

[0016] Compared with the existing technology, the present invention provides a device transport property analysis system that integrates digital twins and multi-scale coupling methods, which has the following beneficial effects: This device transport property analysis system, which integrates digital twins and multi-scale coupling methods, can collect data from multiple channels such as device design, manufacturing process, material properties, and experimental testing through acquisition and preprocessing modules. Through preprocessing, it can convert multi-source heterogeneous data into high-quality usable data. This multi-dimensional data integration method enables the system to comprehensively obtain information related to the device transport properties, providing a rich and accurate data foundation for subsequent analysis. Compared with traditional analysis software with a single data source, it greatly improves the integrity and availability of the data. This device transport property analysis system integrates digital twins and multi-scale coupling methods. The digital twin model construction module is based on multi-source data and uses a hierarchical architecture to accurately construct a three-dimensional digital twin model of the device. It can not only accurately restore the geometric structure of the device, but also accurately map the material properties and physical field models to the model. Through calibration with experimental data, the digital twin model can truly reproduce the actual working state of the device, providing highly reliable virtual objects for transport property analysis, and changing the problem of disconnection between traditional models and actual devices. This device transport property analysis system integrates digital twins and multi-scale coupling methods. The multi-scale coupling analysis module breaks the limitations of traditional single-scale analysis, organically combines microscopic, mesoscopic and macroscopic scale models, and realizes information interaction and collaborative analysis between different scales through a unique scale coupling mechanism. This multi-scale coupling method can comprehensively reveal the physical processes of devices at different scales and their mutual influence, making the analysis results more in line with actual conditions and providing a more scientific approach to in-depth understanding of device transport properties. This device transport property analysis system integrates digital twins and multi-scale coupling methods. The transport property analysis and prediction module can not only conduct in-depth analysis of the device's electrical and thermal transport properties, but also has performance prediction and optimization suggestion functions to help users plan device design and optimization directions in advance. The result display and interaction module provides rich and diverse visual displays and convenient user interaction methods, allowing users to intuitively understand the analysis results and conveniently adjust parameters and export results, significantly improving the user experience and work efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0018] In order to make the technical means, creative features, objectives and effects achieved by the present invention easier to understand, the present invention is further described below in conjunction with specific implementation methods. Example

[0019] like Figure 1 As shown, a device transport property analysis system that integrates digital twins and multi-scale coupling methods includes a data acquisition and preprocessing module, a digital twin model construction module, a multi-scale coupling analysis module, a transport property analysis and prediction module, a result display and interaction module, and a system management module. The data acquisition and preprocessing module is used to collect multi-source data of device design and process, clean it, fill missing values and standardize it. The data acquisition and preprocessing module includes a data acquisition module and a data preprocessing module, wherein the data acquisition module is used to collect data related to device transport property analysis; The data preprocessing module is used to preprocess the collected data, including data cleaning, missing value processing, and standardization.

[0020] The digital twin model construction module constructs a hierarchical digital twin model based on the collected data. After calibration with the experimental data, it accurately reproduces the working status of the device for analyzing the virtual object. The digital twin model construction module includes a model architecture design module and a model parameter calibration module. The model architecture design module constructs the digital twin model of the device based on the data provided by the data acquisition and preprocessing module. The model adopts a hierarchical architecture and is divided into a geometric model layer, a material property layer, and a physical field model layer. The geometric model layer constructs the three-dimensional geometric structure of the device according to the design drawings of the device, including the shape and size information of the device; the material property layer maps the material characteristic data to the geometric model and assigns corresponding material properties to each component; the physical field model layer establishes equations describing the physical phenomena inside the device based on the laws of physics; The model parameter calibration module is used to calibrate the parameters of the constructed digital twin model, compare the model simulation results with the experimental test data, and adjust the parameters in the model to make the two match, so as to truly reproduce the working status of the device.

[0021] The multi-scale coupling analysis module is used to divide the modeling into micro, meso, and macro scales, achieve scale coupling through interpolation mapping, and comprehensively analyze the transport properties of the device. The multi-scale coupling analysis module includes a scale division and modeling module and a scale coupling mechanism module. The scale division and modeling module is used to divide the physical processes of the device according to different scales in the semiconductor device and establish corresponding models for each scale, including micro, meso, and macro scales. At the microscale, quantum mechanical models are used to describe the behavior of electrons at the atomic and molecular scales; at the mesoscale, methods such as molecular dynamics simulation are used to study the transport characteristics of carriers in nanostructures; at the macroscale, equations describing the overall electrical and thermal performance of the device are established based on classical electrodynamics and thermodynamics theory. The scale coupling mechanism module is used to achieve information interaction and collaborative analysis between multiple scales. It uses interpolation and mapping-based methods to transfer the calculation results at the micro and mesoscales to the macroscale model, providing boundary conditions and parameters for the macroscale model; at the same time, the calculation results at the macroscale are also fed back to the micro and mesoscale models, affecting the physical processes at the micro and mesoscales.

[0022] The transport property analysis and prediction module analyzes the electrical and thermal transport properties of the device based on the model and analysis results, predicts performance and provides optimization suggestions. The transport property analysis and prediction module includes a transport property analysis module and a performance prediction and optimization suggestion module. The transport property analysis module conducts an in-depth analysis of the device's transport properties based on the digital twin model and multi-scale coupling analysis results. From the perspective of electrical performance, it analyzes the changes in the device's current, voltage characteristics, conductivity, and resistance parameters with working conditions; from the perspective of thermal performance, it studies the temperature distribution and heat flux density inside the device, and evaluates the device's heat dissipation performance. Through visualization tools, the analysis results are intuitively displayed in charts and cloud maps. The performance prediction and optimization suggestion module simulates the transport performance of the device under different design schemes based on changing the parameters in the digital twin model, and predicts the performance of the device under future working conditions. Based on the prediction results and combined with multi-scale coupling analysis, it provides users with suggestions for optimizing device design and performance.

[0023] The result display and interaction module is used to present the results in a variety of visual forms, provide interactive functions, and support parameter adjustment and result export. The result display and interaction module includes a visualization module and a user interaction module. The visualization module presents the results of the transport property analysis and prediction module to the user in a variety of visual forms. It also uses animation demonstrations to dynamically display the physical process changes of the device at different working stages. The user interaction module is used to freely select the analysis objects and parameters of interest through the graphical interface and adjust the method and angle of visualization display.

[0024] The system management module covers user and data management as well as system monitoring and maintenance, and is used to ensure the safe operation of the system. The system management module includes the user management module, the data management module and the system monitoring and maintenance module. The user management module is used to manage system users, including user registration, login, and permission allocation. Different operation permissions are set according to the user's role. The system monitoring and maintenance module is used to uniformly manage the data in the system, including data storage, backup, recovery and deletion. It uses a database management system to classify and store the collected data, model data and analysis result data to ensure the security and integrity of the data, and back up the data regularly to prevent data loss. The system monitoring and maintenance module is used to monitor the operating status of the system in real time, including the usage of server resources and the operation of modules. When the system fails or is abnormal, it will issue an alarm in time and record relevant log information. Example

[0025] A device transport property analysis system that integrates digital twins and multi-scale coupling methods includes the following steps: S1: Data acquisition and preprocessing: select the data source related to the device and automatically obtain data from the selected data source, including device design drawings, process parameters, material characteristics data and experimental test data, etc., and then clean the data, handle missing values and standardize the data; S2: Digital twin model construction, creating a geometric model: Import device design drawings, use 3D modeling tools to accurately adjust the device's shape, size and other geometric parameters according to the drawing information, and build the device's 3D geometric structure; assign material properties: After the geometric model is built, in the material property layer interface, select the corresponding material from the collected material property data, and map the material properties to the corresponding components of the geometric model; establish a physical field model: In the physical field model layer, based on the device's working principle and physical laws, select appropriate physical equations, set the model's boundary conditions and initial conditions, and complete the establishment of the physical field model; Import experimental data: import pre-processed experimental test data into the system; parameter adjustment: compare the model simulation results with the experimental data, and adjust the parameters in the model to make the simulation results as consistent as possible with the experimental data; S3: Multi-scale coupling analysis, select micro, meso and macro scale types, establish models of each scale: including micro scale, meso scale and macro scale, transfer the calculation results of micro and meso scale models to macro scale model according to preset rules, and feed back the results of macro scale model to micro and meso scale models; S4: Transport property analysis and prediction: Select the constructed digital twin model and multi-scale coupling analysis results, set the analysis parameters as needed, analyze the device's transport properties based on the model and parameter settings, and generate analysis results. The results are displayed in the interface in visual forms such as charts and cloud maps. By modifying the parameters in the digital twin model, the device's transport performance under different design schemes is simulated. After setting the new parameters, the device's performance under the new parameters is calculated and displayed. Based on the prediction results and multi-scale coupling analysis, the system automatically generates recommendations for optimizing device design and performance. S5: In the Results Display and Interaction module, you can directly view the visualization results generated by the Transport Property Analysis and Prediction module, such as animated demonstrations of electron transport processes and multi-dimensional data comparison charts. This system expands and innovates upon the existing "Semiconductor Transport Software," integrating digital twins with multi-scale coupling technology to provide a more comprehensive, accurate, and efficient solution for analyzing the transport properties of semiconductor devices. By building upon multiple functional modules, the system enables in-depth analysis of device transport properties at scales from microscopic to macroscopic, providing strong support for device design, optimization, and performance improvement.

[0026] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A device transport property analysis system that integrates digital twins and multi-scale coupling methods, including a data acquisition and preprocessing module, a digital twin model construction module, a multi-scale coupling analysis module, a transport property analysis and prediction module, a result display and interaction module, and a system management module. Its characteristics are: The data acquisition and preprocessing module is used to collect multi-source data of device design and process, clean it, fill in missing values and perform standardization processing; The digital twin model construction module constructs a hierarchical digital twin model based on the collected data, which is calibrated with the experimental data to accurately reproduce the working state of the device for analyzing the virtual object; The multi-scale coupling analysis module is used to divide the microscopic, mesoscopic and macroscopic scale modeling, realize scale coupling through interpolation mapping, and comprehensively analyze the transport properties of the device; The transport property analysis and prediction module analyzes the electrical and thermal transport properties of the device based on the model and analysis results, predicts performance and provides optimization suggestions; The result display and interaction module is used to present the results in a variety of visual ways, provide interactive functions, and support parameter adjustment and result export; The system management module covers user, data management and system monitoring and maintenance, and is used to ensure the safe operation of the system.

2. The device transport property analysis system integrating digital twin and multi-scale coupling method according to claim 1 is characterized by: The data acquisition and preprocessing module includes a data acquisition module and a data preprocessing module, wherein the data acquisition module is used to collect data related to the analysis of the device transport properties; The data preprocessing module is used to preprocess the collected data, including data cleaning, missing value processing, and standardization.

3. The device transport property analysis system integrating digital twin and multi-scale coupling method according to claim 1 is characterized by: The digital twin model construction module includes a model architecture design module and a model parameter calibration module. The model architecture design module constructs a digital twin model of the device based on the data provided by the data acquisition and preprocessing module. The model adopts a layered architecture and is divided into a geometric model layer, a material property layer, and a physical field model layer. The geometric model layer constructs the three-dimensional geometric structure of the device according to the design drawings of the device, including the shape and size information of the device. The material property layer maps material property data to the geometric model and assigns corresponding material properties to each component; The physical field model layer establishes equations that describe the physical phenomena inside the device based on the laws of physics; The model parameter calibration module is used to calibrate the parameters of the constructed digital twin model, compare the model simulation results with the experimental test data, and adjust the parameters in the model to make the two match, so as to truly reproduce the working status of the device.

4. The device transport property analysis system integrating digital twin and multi-scale coupling method according to claim 1 is characterized by: The multi-scale coupling analysis module includes a scale division and modeling module and a scale coupling mechanism module. The scale division and modeling module is used to divide the physical process of the device according to different scales in the semiconductor device and establish corresponding models respectively, including microscopic, mesoscopic and macroscopic scales. At the microscopic scale, the quantum mechanics model is used to describe the behavior of electrons at the atomic and molecular scales; at the mesoscopic scale, molecular dynamics simulation and other methods are used to study the transport characteristics of carriers in nanostructures. At the macroscopic scale, equations describing the overall electrical and thermal performance of the device are established based on classical electrodynamics and thermodynamics theories.

5. The device transport property analysis system integrating digital twin and multi-scale coupling method according to claim 4 is characterized by: The scale coupling mechanism module is used to realize information interaction and collaborative analysis between multiple scales. It adopts interpolation and mapping-based methods to transfer the calculation results at the micro and meso scales to the macro scale model, providing boundary conditions and parameters for the macro scale model. At the same time, the calculation results at the macro scale are also fed back to the micro and meso scale models, affecting the physical processes at the micro and meso scales.

6. The device transport property analysis system integrating digital twin and multi-scale coupling method according to claim 1 is characterized by: The transport property analysis and prediction module includes a transport property analysis module and a performance prediction and optimization suggestion module. The transport property analysis module conducts an in-depth analysis of the device's transport properties based on the digital twin model and multi-scale coupling analysis results. From the perspective of electrical performance, it analyzes how the device's current, voltage characteristics, conductivity, and resistance parameters change with working conditions; from the perspective of thermal performance, it studies the temperature distribution and heat flux density inside the device, evaluates the device's heat dissipation performance, and uses visualization tools to intuitively display the analysis results in charts and cloud maps.

7. The device transport property analysis system integrating digital twin and multi-scale coupling method according to claim 6 is characterized by: The performance prediction and optimization suggestion module simulates the transport performance of the device under different design schemes based on changing the parameters in the digital twin model, predicts the performance of the device under future working conditions, and provides users with suggestions for optimizing device design and performance based on the prediction results combined with multi-scale coupling analysis.

8. The device transport property analysis system integrating digital twin and multi-scale coupling method according to claim 1 is characterized by: The result display and interaction module includes a visualization display module and a user interaction module. The visualization display module displays the results of the transport property analysis and prediction module to the user in a variety of visualization forms, and also uses animation demonstration to dynamically display the physical process changes of the device at different working stages. The user interaction module is used to freely select analysis objects and parameters of interest through a graphical interface and adjust the method and angle of visual display.

9. The device transport property analysis system integrating digital twin and multi-scale coupling method according to claim 1 is characterized by: The system management module includes a user management module, a data management module and a system monitoring and maintenance module. The user management module is used to manage system users, including user registration, login, and authority allocation, and to set different operation permissions according to the user's role; The system monitoring and maintenance module is used to uniformly manage the data in the system, including data storage, backup, recovery and deletion. It uses a database management system to classify and store the collected data, model data and analysis result data to ensure the security and integrity of the data, and back up the data regularly to prevent data loss.

10. The device transport property analysis system integrating digital twin and multi-scale coupling method according to claim 9, characterized in that: The system monitoring and maintenance module is used to monitor the operating status of the system in real time, including the usage of server resources and module operation status. When the system fails or is abnormal, it will promptly issue an alarm and record relevant log information.

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