An optoelectronic device packaging method, apparatus, computer device and storage medium

Abstract

The application discloses a photoelectric device packaging method and device, computer equipment and storage medium, which is suitable for short-wave infrared detector or sensor packaging scene. The application improves the light transmission efficiency and stability in the multi-layer optical structure by simulating and optimizing the light path in the packaging process. On the one hand, ray tracing and dynamic optimization of geometric structure parameters are used to improve the light propagation path and reduce energy loss caused by refraction angle deviation. On the other hand, by identifying the key points of energy loss and combining interface matching deviation analysis, the material layer thickness and refractive index combination are iteratively optimized to reduce interface reflection and absorption loss and improve transmission efficiency. The application significantly enhances the effective signal acquisition capability of the short-wave infrared device, which can improve its performance in high-precision application scenarios such as industrial detection, medical imaging and environmental monitoring, thereby promoting the engineering and practical development of short-wave infrared devices.

Description

Technical Field

[0001] This application belongs to the field of packaging technology, specifically relating to a method, apparatus, computer equipment, and storage medium for packaging optoelectronic devices for short-wave infrared detectors / sensors. Background Technology

[0002] Shortwave infrared technology, as an important field of optical application, demonstrates irreplaceable value in industrial inspection, medical imaging, and environmental monitoring. Its core lies in its ability to capture light signals in specific wavelengths, thereby revealing details imperceptible to the naked eye. However, technological advancements in this field place extremely high demands on the precise transmission and efficient utilization of optical signals, becoming crucial for driving breakthroughs in related applications.

[0003] Currently, although various methods exist for short-wave infrared encapsulation technology, a common problem is the difficulty in maintaining the stability and efficiency of optical signals in complex environments. Many existing solutions often overlook the complex interactions between light at different interfaces during design, leading to significant energy loss during transmission, especially when dealing with multi-layered structures or interfaces between different materials. This limitation not only affects device performance but also restricts the application of the technology in a wider range of scenarios.

[0004] Against this backdrop, the core technical challenges of short-wave infrared packaging have gradually become apparent. The primary problem lies in insufficient optimization of the light path. When light enters the packaging window, due to geometric limitations, it often cannot be refracted or transmitted at an ideal angle, resulting in energy loss. This problem further exacerbates the difficulty of matching the light with the packaging interface, as differences in the optical properties of different materials cause additional deviations or losses as the light passes through. For example, in some industrial inspection equipment, short-wave infrared light needs to undergo multiple refractions within a small space. If the path design is unreasonable, it can lead to a significant decrease in signal strength and even affect the clarity of the final image.

[0005] Therefore, how to effectively optimize the light path in the packaging design and ensure that the light can maintain efficient transmission and precise refraction when passing through different interfaces has become a key issue in the application of shortwave infrared technology. Summary of the Invention

[0006] The purpose of this application is to provide a method, apparatus, computer device, and storage medium for packaging optoelectronic devices, in order to solve the technical problem of how to effectively optimize the light path in the packaging design and ensure that light can maintain efficient transmission and accurate refraction when passing through different interfaces.

[0007] To address the aforementioned technical problems, this application provides a method for packaging optoelectronic devices, employing the following technical solution: Light data is collected during the packaging process of short-wave infrared devices, and the propagation trajectory of the light signal in the multi-layer optical structure is calculated based on the light data to obtain the initial light path distribution; Based on the initial ray path distribution, analyze the refraction and transmission characteristics of light at different material interfaces; The packaging geometry parameters are adjusted based on refractive and transmission properties to determine the optimized light path model. The key points of energy loss are extracted from the optimized light path model, and the differences in optical properties at the key points of energy loss are obtained to obtain the interface matching deviation index. To address the interface matching deviation index, the combination of material layer thickness and refractive index is iteratively adjusted to obtain the interface configuration scheme with the least loss. The packaging structure design is then updated based on the interface configuration scheme.

[0008] To address the aforementioned technical problems, this application also provides an optoelectronic device packaging apparatus, which employs the following technical solution: The initial distribution module is used to collect light data during the packaging process of short-wave infrared devices, and calculate the propagation trajectory of the light signal in the multi-layer optical structure based on the light data to obtain the initial light path distribution; The optical properties module is used to analyze the refraction and transmission properties of light at different material interfaces based on the initial light path distribution. The optical path optimization module is used to adjust the package geometry parameters based on refractive and transmission characteristics to determine the optimized ray path model. The deviation identification module is used to extract key energy loss points from the optimized light path model, obtain the differences in optical properties at the key energy loss points, and obtain the interface matching deviation index. The configuration iteration module is used to iteratively adjust the combination of material layer thickness and refractive index based on the interface matching deviation index, so as to obtain the interface configuration scheme with the least loss, and update the packaging structure design through the interface configuration scheme.

[0009] To address the aforementioned technical problems, this application also provides a computer device that employs the following technical solution: A computer device includes a memory and a processor, the memory storing computer-readable instructions, the processor executing the computer-readable instructions to implement the steps of the optoelectronic device packaging method as described in any of the preceding claims.

[0010] To address the aforementioned technical problems, this application also provides a computer-readable storage medium, employing the technical solution described below: A computer-readable storage medium storing computer-readable instructions, which, when executed by a processor, implement the steps of the optoelectronic device packaging method as described above.

[0011] Compared with the prior art, the embodiments of this application have the following main advantages: This application discloses a method, apparatus, computer device, and storage medium for packaging optoelectronic devices, particularly applicable to the packaging of short-wave infrared detectors / sensors. This application significantly improves the transmission efficiency and stability of optical signals in multi-layer optical structures through systematic optimization of the light path and precise control of interface matching in the packaging of short-wave infrared devices. First, by using ray simulation and dynamic adjustment of geometric parameters, the problem of light refraction angle deviation caused by unreasonable path design in traditional packaging is effectively solved, making the initial light path distribution more reasonable and reducing energy loss caused by angle deviation. Second, for interface matching deviations at key energy loss points, iterative optimization of the combination of material layer thickness and refractive index significantly reduces the reflection and absorption losses of light between different material interfaces, significantly improving the light transmission efficiency at the interface, enabling the device to capture stronger effective light signals. This application synergistically combines packaging geometry optimization and interface optical matching optimization to form a multi-level optimization mechanism from macroscopic optical path layout optimization to microscopic interface transmission optimization. This not only improves the overall propagation state of light in the packaging structure but also further eliminates energy loss caused by local interfaces, thereby achieving an overall improvement in light energy utilization. Attached Figure Description

[0012] To more clearly illustrate the solutions in this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 An exemplary system architecture diagram is shown, in which this application can be applied; Figure 2 A flowchart of one embodiment of the optoelectronic device packaging method according to this application is shown; Figure 3 It shows Figure 2 A flowchart of one embodiment of step S201; Figure 4 It shows Figure 3 A flowchart of an embodiment of step S305; Figure 5 A schematic diagram of the structure of an embodiment of the optoelectronic device packaging apparatus according to this application is shown; Figure 6 A schematic diagram of the structure of one embodiment of a computer device according to this application is shown. Detailed Implementation

[0014] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application, are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0015] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0016] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0017] like Figure 1 As shown, system architecture 100 may include terminal device 101, network 102, and server 103. Terminal device 101 may be a laptop 1011, tablet 1012, or mobile phone 1013. Network 102 is used as a medium to provide a communication link between terminal device 101 and server 103. Network 102 may include various connection types, such as wired, wireless communication links, or fiber optic cables.

[0018] Users can use terminal device 101 to interact with server 103 via network 102 to receive or send messages, etc. Various communication client applications can be installed on terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social media platform software, etc.

[0019] Terminal device 101 can be various electronic devices with a display screen and support web browsing. In addition to laptops 1011, tablets 1012, or mobile phones 1013, terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 player (Moving Picture Experts Group Audio Layer IV), a laptop computer, and a desktop computer, etc.

[0020] Server 103 can be a server that provides various services, such as a backend server that provides support for the pages displayed on terminal device 101.

[0021] It should be noted that the optoelectronic device packaging method provided in this application embodiment is generally executed by a server / terminal device, and correspondingly, the optoelectronic device packaging device is generally disposed in the server / terminal device.

[0022] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative; the system can have any number of terminal devices, networks, and servers depending on implementation needs.

[0023] Continue to refer to Figure 2 A flowchart illustrating an embodiment of a method for packaging an optoelectronic device according to this application is shown. The optoelectronic device packaging method includes the following steps: S201: Collect light data during the packaging process of short-wave infrared devices, and calculate the propagation trajectory of the light signal in the multi-layer optical structure based on the light data to obtain the initial light path distribution; Specifically, in the light data acquisition stage, a data acquisition model is first constructed based on the packaging process environment of short-wave infrared devices. Optical sensing units or virtual simulation sampling points are deployed inside the packaging cavity to acquire multi-dimensional emission parameters of the incident light source. The acquired data includes light intensity distribution, emission angle distribution, time synchronization parameters, and spatial coordinates. Structural parameters of different material interfaces are also recorded synchronously, forming a complete initial input dataset. This dataset is used to characterize the initial propagation conditions of light within the packaging structure.

[0024] In the path calculation stage, a multi-layer optical structure model is constructed based on the ray data. This model includes at least two layers of materials with different refractive indices and corresponding interface geometries. Ray tracing algorithms are used to discretize the ray beam, dividing the continuous beam into multiple ray units, and propagation calculations are performed segment by segment according to a set step size. In each propagation step, the change in the ray propagation direction is calculated based on Snell's law and the interface geometric relationship, while the propagation path nodes of the ray in each layer are recorded.

[0025] In the initial ray path distribution generation stage, the propagation trajectories of all ray units are spatially reconstructed and mapped to a unified three-dimensional coordinate system. By integrating the density distribution of path nodes, propagation direction vectors, and interlayer crossing relationships, a ray path distribution matrix is ​​constructed. This matrix is ​​used to characterize the overall propagation trajectory features of the light signal in the multi-layer structure.

[0026] Multilayer optical structure refers to a composite interface structure in the packaging structure of short-wave infrared devices, which consists of at least two layers of materials with different optical refractive indices, such as a light-transmitting layer of the packaging shell, a protective adhesive layer, a chip passivation layer, and an optical window layer. There are clear interfaces between different material layers, and light needs to pass through multiple material interfaces in sequence to complete the propagation process.

[0027] S202, Based on the initial ray path distribution, analyze the refraction and transmission characteristics of light at different material interfaces; Specifically, in the interface recognition stage, the interaction points between light rays and each material interface are extracted based on the initial light path distribution. The type of each interaction behavior, including refraction, reflection, and transmission events, is determined according to the interface normal vector and the incident direction of the light rays. By matching the interface geometric parameters with the material refractive index parameters, an interface response mapping relationship is established to describe the changes in light propagation behavior at different interfaces.

[0028] In the refractive property calculation stage, for each interface interaction point, the change in refraction angle is calculated based on the difference between the incident angle and the material's refractive index. Light rays of different wavelengths or energies are grouped to obtain the refractive behavior distribution under multiple conditions. Simultaneously, the refraction direction vector is normalized to form a standardized set of refractive property parameters.

[0029] In the transmission characteristic analysis stage, an interface transmission model is established by calculating the transmission ratio and energy distribution relationship of light at the interface. This model comprehensively considers interface roughness parameters, material absorption coefficients, and multiple internal reflection paths to decompose and express the energy change of light after transmission, thereby forming a complete transmission characteristic data structure to characterize the light energy transfer state under different interface conditions.

[0030] S203, adjust the packaging geometry parameters according to the refractive and transmission characteristics to determine the optimized light path model; Specifically, in the geometric parameter extraction stage, based on the results of refractive and transmission characteristics, key structural parameters that affect the change of light path are identified, including material layer thickness, interface tilt angle, spatial layout of encapsulation cavity, and position of optical window, and these are transformed into a set of calculable parameter variables.

[0031] During the parameter adjustment phase, parameter perturbation modeling is performed on the set of geometric parameter variables. By introducing fine-tuning step size and constraint boundaries, different structural parameters are combined and varied to generate candidate structural schemes. Simultaneously, combined with the ray propagation model, the ray path under each candidate structure is recalculated to obtain the corresponding changes in the propagation trajectory.

[0032] In the model optimization stage, all candidate ray path results are uniformly evaluated and calculated, including path continuity analysis, interface crossing stability analysis, and energy distribution consistency analysis. By screening candidate models that meet preset constraints, an optimized ray path model set is constructed, and the path model with the most stable structure is selected as the output result.

[0033] The ray path model is a digital model used to characterize the complete propagation trajectory and energy change of the optimized ray unit in the encapsulated multilayer optical structure. It can intuitively reflect the propagation characteristics of optical signals under different structural parameters.

[0034] Furthermore, the steps of adjusting the packaging geometry parameters based on refractive and transmission characteristics to determine the optimized ray path model specifically include: Based on refractive and transmission properties, the light deflection parameters, transmission efficiency parameters, and energy distribution parameters of each material interface in the multilayer optical structure are extracted to establish a set of interface optical features. Based on the interface optical feature set, target areas with abnormal energy accumulation or reduced transmission efficiency during light propagation are identified, and the encapsulation geometric parameters corresponding to the target areas are determined. For the packaging geometry parameters, a set of geometry adjustment variables is constructed, and the material layer spacing, interface tilt angle, packaging cavity size and optical window position are parameterized. By inputting the set of geometric adjustment variables into the ray path simulation model, the propagation trajectory of light in the multi-layer optical structure, the interface transmission, and the energy distribution are recalculated to obtain multiple candidate ray path models. The transmission efficiency and energy uniformity of multiple candidate ray path models are evaluated, and the candidate ray path model with the best comprehensive evaluation result is selected as the optimized ray path model.

[0035] In this embodiment, firstly, based on the obtained refractive and transmission characteristics, refined parameters are extracted from the interfaces of each material in the multilayer optical structure. The deflection behavior of light at different interfaces is transformed into quantifiable deflection parameters, such as refraction angle shift and direction vector change rate. Simultaneously, transmission efficiency parameters and energy distribution parameters are calculated by combining the energy changes at the interfaces, thereby constructing a unified set of interface optical features. Subsequently, spatial positioning analysis is performed on this feature set. By analyzing the density statistics of the light path distribution and energy attenuation gradient, target areas with abnormal energy accumulation or significant decrease in transmission efficiency during propagation are identified. These areas are then mapped to specific encapsulation structure locations to determine the corresponding material layer thickness, interface position, and spatial geometric relationships, among other encapsulation geometric parameters. Based on this, the aforementioned geometric parameters are variableized to construct a set of geometric adjustment variables, which parameterize key structural parameters such as material layer spacing, interface tilt angle, encapsulation cavity size, and optical window position. Subsequently, the set of geometric adjustment variables was input into the ray path simulation model to recalculate the propagation behavior of light in the multi-layer optical structure. Through multiple rounds of simulation, the ray path variations under different parameter combinations were obtained, including changes in propagation trajectory, interface transmission, and energy distribution, thus forming multiple candidate ray path models. Finally, all candidate models were comprehensively evaluated and analyzed, with quantitative assessments performed from two dimensions: transmission efficiency and energy uniformity. The model with the best overall performance was selected as the final optimized ray path model using a weighted scoring method.

[0036] In this embodiment, the optimization process is a macroscopic structural optimization process oriented towards the light propagation path. Its optimization object is mainly the geometric parameters of the encapsulation structure. By adjusting the spatial geometric relationship of the encapsulation structure, light can pass through the multi-layer optical structure with a more reasonable propagation path, thereby reducing the energy loss caused by unreasonable propagation path and improving the overall light transmission efficiency.

[0037] Through the above steps, the systematic optimization of the encapsulation structure parameters and the high-precision reconstruction of the ray path model can be achieved.

[0038] S204. Extract key energy loss points from the optimized ray path model, obtain the differences in optical properties at the key energy loss points, and obtain the interface matching deviation index. Specifically, in the energy distribution analysis stage, based on the optimized ray path model, the energy value of the ray at each propagation node is calculated point by point to form a continuous energy attenuation curve. The region of abrupt energy change is identified through differential operation to preliminarily locate potential energy loss locations.

[0039] In the key point extraction stage, spatial clustering analysis is performed on the aforementioned energy abrupt change regions. Points that are spatially adjacent and have consistent energy change trends are merged to form a set of key energy loss points. Simultaneously, based on interface positional relationships, the interface affiliation of these key points is determined to clarify their corresponding material layer structure.

[0040] In the interface matching deviation calculation stage, local optical parameters at key points are extracted, including refractive index difference, reflectivity change and energy loss ratio, etc., and each parameter is weighted and calculated by constructing a multi-parameter deviation model to form an interface matching deviation index, which is used to quantify the interface optical matching status.

[0041] Key energy loss points refer to spatial interaction sites where energy abruptly decreases when light passes through the interfaces of multiple materials. These sites often have optical parameter mismatches and are the core influencing locations that reduce the overall light transmission efficiency of the packaging structure.

[0042] S205, for the interface matching deviation index, iteratively adjusts the combination of material layer thickness and refractive index to obtain the interface configuration scheme with the least loss, and updates the packaging structure design through the interface configuration scheme.

[0043] Specifically, in the parameter sensitivity analysis stage, the influence of material layer thickness and refractive index parameters is decomposed based on the interface matching deviation index to determine the contribution weight of each parameter to energy loss, and a parameter optimization priority sequence is constructed accordingly.

[0044] During the iterative optimization phase, the material parameters are updated iteratively multiple times based on the priority sequence. In each iteration, a new set of parameter combinations is generated, and the corresponding energy loss and interface deviation values ​​are recalculated through the ray path simulation model, thus forming an iterative convergence process.

[0045] During the structural update phase, all iteration results are globally filtered to select parameter combinations that meet the conditions of minimum energy loss and optimal interface matching. These combinations are then mapped back to the encapsulation structure design space to update the design schemes for material layer thickness configuration and refractive index combination configuration, thereby forming the final encapsulation structure design output.

[0046] In this embodiment, the optimization process iteratively adjusts the material layer thickness and refractive index combination to obtain the interface configuration scheme with minimal loss, and then updates the packaging structure design using this interface configuration scheme. Its core objective is to improve the refractive index matching relationship between different material interfaces, reduce interface reflection loss, scattering loss, and local energy accumulation phenomena, thereby further improving overall optical performance.

[0047] This application employs a layered optimization strategy of "prioritizing geometric structure optimization and fine-tuning interface parameters." In practical optical packaging systems, the influence of geometric structure parameters on the light path is usually a first-order factor. For example, changes in material interlayer spacing, window position, or interface angle often directly alter the light propagation direction, propagation distance, and number of reflections, significantly impacting overall transmission efficiency. Adjustments to material thickness and refractive index are more often considered second-order factors, primarily improving interface transmission effects along a predetermined propagation path. Therefore, this application first optimizes the macroscopic propagation path using step S203, achieving a superior overall optical path layout. Subsequently, step S205 performs fine-tuning compensation on local interfaces, further reducing residual losses.

[0048] Furthermore, after obtaining the interface configuration scheme with the minimum loss in S205, this application also includes re-performing the ray path simulation on the interface configuration scheme and verifying the transmission efficiency and energy uniformity of the packaging structure. When the preset optimization conditions are met, the final packaging structure design is output.

[0049] Specifically, during the parameter write-back stage, the material layer thickness configuration and refractive index combination configuration in the interface configuration scheme are mapped to the updated encapsulation structure model to construct a comprehensive encapsulation model that includes optimized geometric structure parameters and optimized interface parameters.

[0050] During the co-simulation phase, the integrated packaging model is input into the ray path simulation model to recalculate the ray propagation trajectory, interface transmission, reflection, and energy distribution in the multi-layer optical structure. The corresponding transmission efficiency index, energy uniformity index, and interface loss index are obtained to evaluate the impact of interface parameter optimization on the overall optical path transmission performance.

[0051] During the performance verification phase, the recalculated indicators are compared and analyzed with preset optimization conditions. These preset optimization conditions include transmission efficiency not lower than a target threshold, energy uniformity meeting preset uniformity requirements, and interface loss lower than a preset loss threshold. When the transmission efficiency, energy uniformity, and interface loss indicators all meet their respective preset conditions, the current integrated packaging model is determined to have met the optimization requirements, and the corresponding final packaging structure design is output.

[0052] If at least one indicator fails to meet the preset optimization conditions, the structural or interface parameter with the greatest impact is determined based on the verification results, and the process is returned to the corresponding optimization stage for adjustment. Specifically, if the impact originates from abnormal light path distribution, the process is returned to the encapsulation geometry optimization process to readjust the geometry parameters. If the impact originates from interface matching deviation, the process is returned to the interface configuration optimization process to readjust the material layer thickness configuration and refractive index combination configuration until the preset optimization conditions are met.

[0053] Through the above methods, after completing the optimization of the packaging geometry and interface matching, this application further establishes a closed-loop verification mechanism based on ray path simulation. This mechanism can not only verify whether the optimized ray path transmission effect is maintained after the interface parameters are adjusted, but also avoid the negative impact of local interface optimization on the overall optical path performance. This achieves the synergistic optimization of packaging structure parameters and interface parameters, thereby improving the optical transmission efficiency, energy uniformity and long-term operational stability of the final packaging structure.

[0054] For example, the target device is a short-wave infrared InGaAs detector package structure with an operating wavelength of 0.9-1.7 μm. The initial package structure consists of three optical layers: an upper optical window (sapphire, refractive index n≈1.76), a middle encapsulation layer (epoxy resin, n≈1.52), and a lower photosensitive chip protective layer (SiNx, n≈2.05). The incident light source is a quasi-parallel beam with a center wavelength of 1.55 μm, an incident angle range of 0°-25°, and an initial normalized light intensity of 1.0. By arranging a virtual light sampling grid (50×50×30) inside the package cavity, the light emission position, angle distribution, and energy distribution are collected, resulting in a total of 12,000 valid light data samples. Based on these data, a three-dimensional optical model was constructed, and a ray tracing algorithm was used to calculate the propagation of each ray through each interface. For example, at the first interface (sapphire / air), the refraction angle range was calculated to be 0°-14.8° according to Snell's law. At the second interface (sapphire / resin layer), the angle was further extended to 0°-21.3°, and finally the initial ray path distribution matrix (12000×N nodes) was formed.

[0055] Interface interaction analysis was performed on the aforementioned path distribution. Statistical analysis revealed that at the sapphire / epoxy interface, approximately 18.6% of the light was reflected, with a transmittance of about 81.4%. However, at the epoxy / SiNx interface, due to the significant difference in refractive index (1.52 vs 2.05), the reflectance increased to approximately 27.3%. Further calculations of refractive properties showed that when the incident angle was greater than 18°, the interface refraction angle deviation increased to ±3.2°, leading to a localized shift in light concentration. Simultaneously, transmittance analysis showed that in the high incident angle region (20°-25°), energy transmission loss increased by approximately 12%-15%. Based on these results, the interface refraction angle distribution function and the transmission energy distribution matrix were constructed.

[0056] The encapsulation geometry was optimized. The initial encapsulation cavity height was 1.2 mm, the window thickness was 0.8 mm, and the adhesive layer thickness was 0.15 mm. By introducing a parameter perturbation mechanism, the window thickness was adjusted to 0.6-1.0 mm, the adhesive layer thickness to 0.1-0.25 mm, and the cavity tilt angle to 0°-5°. After simulations of 200 candidate structures, it was found that when the window thickness was adjusted to 0.72 mm, the adhesive layer thickness to 0.18 mm, and the cavity tilt angle to 2.3°, the light path concentration increased by approximately 22%, and the refraction angle dispersion decreased to 0.63 times the original value. Simultaneously, ray tracing was re-performed under this structure, resulting in an optimized path model where the effective light ray ratio increased to 92.7%.

[0057] Energy loss analysis was performed on the optimized path model. Statistical analysis revealed three main energy attenuation regions near the epoxy / SiNx interface, located at coordinates (0.32, 1.15, 0.9), (0.41, 1.10, 0.92), and (0.38, 1.18, 0.88) mm, with corresponding energy decreases of 0.21, 0.18, and 0.23 (normalized values), respectively. Cluster analysis grouped these points into the same key energy loss region, with an average energy loss rate of 0.206. Simultaneously, local optical parameters of this region were extracted, revealing an interface refractive index mismatch of 0.14 and a reflected energy proportion increasing to 29%. The interface matching deviation index calculated using a weighted model was 0.37 (normalized value), significantly higher than the system average of 0.21.

[0058] Iterative optimization was performed to address the interface matching deviation index. First, sensitivity analysis of material parameters revealed that the refractive index of the adhesive layer contributed 0.48 to energy loss, thickness contributed 0.32, and the window material contributed 0.20. Therefore, the adhesive layer material formulation was adjusted first, changing the refractive index from 1.52 to 1.46, while the thickness was slightly adjusted from 0.18 mm to 0.16 mm. After 10 rounds of iterative optimization, the interface matching deviation index decreased to 0.19, and energy loss decreased by approximately 31%. The optimal interface configuration was finally determined to be: window thickness 0.70 mm, adhesive layer thickness 0.16 mm, adhesive layer refractive index 1.46, and cavity tilt angle 2.0°. After updating the encapsulation structure design based on this scheme, the overall effective transmittance increased to 94.8%, and the uniformity of light energy distribution was significantly improved.

[0059] Further, please refer to Figure 3 The process of collecting light data during the packaging of short-wave infrared devices and calculating the propagation trajectory of the light signal in a multi-layer optical structure based on the light data to obtain the initial light path distribution includes the following steps: S301: Collect the light source emission parameters, beam incident angle parameters, and structural parameters of each material layer in the packaging structure of the short-wave infrared device to construct an optical model of the packaging structure. S302, determine the initial emission position and initial propagation direction of the light rays based on the emission parameters of the light source, and generate a set of light rays for propagation calculation; S303, based on the optical model of the encapsulation structure, performs ray tracing calculations on the light beam set to obtain the propagation path information of the light in each material layer; S304, Identify the interaction positions between the light and different material interfaces based on the propagation path information, and calculate the propagation direction change parameters and energy change parameters of the light at each interaction position; S305 summarizes and analyzes the propagation trajectory, propagation direction change parameters, and energy change parameters of light rays to generate the initial light path distribution of the light signal in the multi-layer optical structure.

[0060] First, a complete optical modeling foundation is established for the packaging environment of short-wave infrared devices. An initial data system is formed by collecting key input parameters from the packaging structure. These parameters include: light source emission parameters (emission power distribution, center wavelength, spectral width, and spatial emission angle distribution) to characterize the energy and directional characteristics of the light source; beam incident angle parameters to describe the angular distribution range and statistical characteristics of light entering the multi-layer packaging structure; and structural parameters for each material layer (refractive index, thickness, surface roughness, and interface geometry). Based on these parameters, an optical model of the packaging structure is constructed to fully describe the propagation environment and boundary conditions of light in different media. Furthermore, by spatially discretizing the light source emission position, the light source region is divided into multiple sampling units, and an initial ray set is generated by combining the emission angle distribution, ensuring that each ray has a clear starting point coordinate and propagation direction vector.

[0061] In the calculation of light propagation, a numerical method based on ray tracing is used to simulate the propagation of light rays step by step. Specifically, the propagation process of light in space is discretized into multiple consecutive steps, and the change in propagation direction is calculated at each step based on the refractive index and interface geometry of the current material layer. When the light reaches the material interface, the refraction angle is calculated according to Snell's law, and the energy distribution ratio of reflection and transmission is determined by combining it with Fresnel's formula, thereby updating the energy weight and propagation path of the light. For complex interface cases in multi-layer structures, multiple reflection and internal propagation mechanisms are also introduced to fully model the multi-path propagation behavior of light within the encapsulation cavity. During this process, the system records the propagation path nodes of each light ray in each material layer, including spatial coordinates, points of change in propagation direction, and energy attenuation nodes, thus forming high-resolution path information data.

[0062] In the post-processing stage of path information, the propagation trajectories of all light rays are uniformly normalized, mapping discrete path points to a three-dimensional spatial coordinate system and constructing a path topology network to express the traversal relationships of light rays between different material layers. Simultaneously, the propagation direction variation parameters of each light ray at each interface are vectorized to characterize the refraction angle shift and the degree of directional perturbation; the energy variation parameters are calculated using continuous integration to reflect the cumulative energy loss characteristics of the light ray during propagation. Subsequently, statistical fusion analysis is performed on all light ray data to generate a comprehensive data structure containing path density distribution, energy distribution gradient, and directional variation characteristics, thus obtaining an initial light ray path distribution that can comprehensively characterize the propagation state of light signals in a multi-layered optical structure.

[0063] Through the above steps, it is possible to achieve refined modeling of the light propagation process and accurate acquisition of the path distribution in the packaging of short-wave infrared devices.

[0064] Furthermore, based on the optical model of the encapsulation structure, the steps of performing ray tracing calculations on the ray set to obtain the propagation path information of the light in each material layer specifically include: A three-dimensional medium space mesh is constructed based on the optical model of the encapsulated structure, and the refractive index distribution, interface geometry and interlayer boundary conditions of each material layer are discretized. For each ray in the ray set, initialize the parameters, determine its initial spatial position, propagation direction vector and energy weight, and establish the ray propagation state variables; The ray tracing algorithm is used to calculate the propagation of light step by step. Within each calculation step, the interaction between the light and the material interface is determined, and the propagation direction and energy distribution of the light are updated according to the interface conditions. Record the propagation node information of light in each material layer, including spatial coordinates, interface interaction positions, propagation path length, and energy change state, to form complete propagation path data.

[0065] In this embodiment, the optical model of the encapsulation structure is first processed into a three-dimensional mesh, transforming the continuous multi-layered material structure into a computable discrete spatial representation, thereby clarifying the physical boundaries and optical property distribution of each material layer. Subsequently, each ray in the ray tracing set is initialized with a clear starting position, propagation direction, and initial energy, ensuring the uniformity and repeatability of the ray tracing calculation. During ray propagation, an iterative ray tracing method is employed. At each propagation step, it is determined whether the ray interacts with the material interface, and the refraction and reflection behavior of the ray is calculated based on the interface normal vector and the difference in refractive index. Simultaneously, energy is allocated and updated accordingly to simulate the real light propagation process. Throughout the calculation, the propagation trajectory of the ray in different material layers is continuously recorded, including its spatial path nodes, interface interaction points, and energy changes, ultimately forming a complete ray propagation path information data structure.

[0066] Further, please refer to Figure 4 The steps involved in summarizing and analyzing the propagation trajectory, propagation direction change parameters, and energy change parameters of light rays to generate the initial light path distribution of the light signal in the multilayer optical structure include: S401, spatial coordinate mapping of the propagation trajectory, uniformly calibrating the propagation position, propagation direction and propagation distance of light in the multi-layer optical structure, forming a light path dataset; S402, based on the propagation direction change parameters, calculate the degree of light deflection at different material interfaces and construct the corresponding direction change feature sequence; S403, based on the energy change parameters, calculate the energy attenuation value, interface transmission energy value, and interface reflection energy value of light during propagation, and form an energy distribution characteristic sequence; S404, perform correlation analysis on the direction change characteristic sequence and the energy distribution characteristic sequence to determine the propagation stability index and energy retention index of light in multi-layer optical structures; S405, based on the ray path dataset, propagation stability index, and energy retention index, statistically fuses the propagation results of each ray to generate an initial ray path distribution that characterizes the overall propagation state of the light signal.

[0067] In this embodiment, the light propagation trajectory data obtained from the preceding steps are first subjected to unified data structuring processing. The discrete path points of different light rays in the multi-layer optical structure are standardized and mapped to spatial coordinates, unifying them into the same three-dimensional reference coordinate system. Simultaneously, the material layer information and interface numbers are labeled, thus forming a structurally consistent light path dataset. Based on this, for the propagation direction change parameters of each light ray, the angle between the direction vectors of adjacent path nodes is calculated to obtain the degree of deflection of the light ray at different interfaces. Furthermore, a direction change feature sequence is constructed according to the propagation order to describe the directional evolution law of the light ray throughout the entire propagation process.

[0068] Simultaneously, the energy change parameters are calculated segmentally, extracting the energy attenuation, interface transmission energy, and reflected energy at each propagation stage. These are then used to form an energy distribution feature sequence according to the propagation path, characterizing the distribution and loss of light energy in the multilayer structure. Subsequently, the direction change feature sequence and the energy distribution feature sequence are correlated and matched. By establishing a feature correspondence model, stability and energy retention indices are calculated during light propagation. The stability index reflects the degree of light path deviation fluctuation, while the energy retention index reflects the fidelity of light energy during propagation. Finally, based on the light path dataset and the two indices, multidimensional statistical fusion is performed. A weighted aggregation and distribution modeling approach is used to construct an overall optical signal propagation state model, outputting the initial light path distribution. This achieves a comprehensive characterization and structured expression of light propagation behavior in multilayer optical structures.

[0069] Through the above steps, we can achieve collaborative modeling and unified expression of light propagation trajectory and energy characteristics, thereby improving the completeness and consistency of the description of light path distribution.

[0070] Furthermore, the steps for determining the propagation stability index and energy retention index of light in a multilayer optical structure by performing correlation analysis on the characteristic sequences of direction change and energy distribution include: The directional change feature sequence is processed by time series processing, and the refraction angle change and directional offset at each interface are reconstructed according to the light propagation sequence to form a standardized directional evolution sequence. The energy distribution characteristic sequence is divided into stages, and the energy attenuation value, transmission energy value and reflection energy value of light at each material layer and interface are segmented and normalized to form an energy evolution sequence. Establish a mapping relationship between the direction change sequence and the energy evolution sequence, align the two types of sequence data based on the same propagation node, and extract coupling feature parameters; A multidimensional evaluation model is constructed based on coupled characteristic parameters to calculate the light propagation stability index and energy retention index.

[0071] In this embodiment, the direction change feature sequence is first normalized by reconstructing the refraction angle changes and direction offsets of light at different material interfaces according to the propagation sequence. This allows the sequence to reflect the directional evolution trend of light throughout the propagation path, thus eliminating inconsistencies between discrete nodes. Next, the energy distribution feature sequence is segmented, uniformly normalizing the energy changes of light at different material layers and interfaces. This ensures that the energy attenuation and transfer processes are reflected on the same scale, forming a comparable energy evolution sequence. Based on this, a mapping relationship between the direction change sequence and the energy sequence is established through propagation node alignment. This ensures that each spatial propagation node corresponds to both direction and energy change information, and the coupling feature parameters between the two are extracted to characterize the relationship between direction change and energy loss. Finally, a multi-dimensional evaluation model is constructed based on these coupling feature parameters. This model comprehensively calculates the propagation stability and energy retention capabilities from two dimensions, yielding propagation stability and energy retention indices to characterize the light propagation properties.

[0072] Furthermore, based on the ray path dataset, propagation stability index, and energy preservation index, the propagation results of each ray are statistically fused to generate an initial ray path distribution characterizing the overall propagation state of the optical signal. This process specifically includes: Based on the propagation area and propagation level of light in the multi-layer optical structure, the light samples in the light path dataset are classified and grouped to form multiple path feature subsets. For each path feature subset, the offset of light propagation direction, the distribution of propagation distance, and the frequency of interface interaction are statistically analyzed to obtain the corresponding path aggregation feature parameters. The propagation stability index and path aggregation feature parameters are fused together to obtain the path credibility weight corresponding to each path feature subset. The energy preservation index is weighted based on the path credibility weight to obtain the comprehensive propagation contribution value corresponding to each path feature subset. The optical energy spatial distribution matrix is ​​constructed by statistically superimposing the comprehensive propagation contribution values ​​of each path feature subset, and an initial ray path distribution characterizing the overall propagation state of the optical signal is generated based on the optical energy spatial distribution matrix.

[0073] In this embodiment, firstly, based on the ray path dataset, a large number of discrete ray samples obtained from ray tracing calculations are classified and aggregated according to their propagation regions and propagation levels in the multi-layer optical structure. For example, they are divided into window layer propagation subsets, encapsulation adhesive layer propagation subsets, and chip protective layer propagation subsets, thus forming a structured set of path feature subsets. Based on this, statistical analysis is performed on each type of path feature subset to extract the propagation direction offset distribution characteristics, propagation distance distribution characteristics, and ray-interface interaction frequency characteristics. These statistical results are summarized to form path aggregation feature parameters, which characterize the overall behavior of this type of path in spatial propagation. Subsequently, a propagation stability index is introduced into the fusion calculation process. By establishing a mapping relationship between the stability index and the path aggregation feature parameters, the reliability of different path feature subsets is quantitatively evaluated, generating path credibility weights to reflect the stability and consistency level of the path subset in the overall propagation structure. Building upon this foundation, the energy contributions of each path feature subset are weighted by incorporating energy preservation metrics, thus coupling energy information with path reliability to obtain the comprehensive propagation contribution value for each path feature subset. Finally, by statistically superimposing the comprehensive propagation contribution values ​​of all path feature subsets in the spatial dimension, a spatial distribution matrix of light energy is constructed. This matrix reflects the distribution density and propagation intensity of light energy in different spatial regions. Based on this matrix, an initial ray path distribution is generated to characterize the overall propagation behavior, achieving unified modeling and fusion expression of complex light propagation processes in multi-layer optical structures.

[0074] Through the above steps, hierarchical fusion and unified modeling of multipath optical propagation data can be achieved, improving the structural degree and consistency of the overall propagation state representation of optical signals.

[0075] Furthermore, the steps of extracting key energy loss points from the optimized ray path model, obtaining the differences in optical properties at these key energy loss points, and deriving the interface matching deviation index specifically include: The energy distribution of light rays in the optimized light path model is analyzed to identify propagation locations where the energy attenuation rate exceeds a preset attenuation threshold, and these propagation locations are determined as candidate energy loss points. Based on the spatial location and interface distribution relationships of the candidate energy loss points, adjacent candidate energy loss points are clustered to determine key energy loss points. The local optical parameters of the material interface at each key energy loss point are obtained, and the optical property difference value is calculated based on the local optical parameters. The local optical parameters include at least the interface refractive index, transmission efficiency, reflection efficiency, and light energy flux. An interface matching evaluation model is constructed based on the differences in optical properties at key energy loss points. The degree of matching deviation of each material interface is calculated and quantified into an interface matching deviation index.

[0076] In this embodiment, the energy distribution of light in the multi-layer optical structure is first analyzed point-by-point based on the optimized ray path model. The energy change of each ray during propagation is serialized according to spatial nodes to form a continuous energy attenuation curve. Based on this, anomaly detection is performed on the energy change curve by setting a preset energy attenuation threshold. When the local energy attenuation rate at a certain propagation position exceeds the threshold, that position is marked as a candidate energy loss point, and its corresponding spatial coordinates and material layer information are recorded. Subsequently, considering the potential spatial discreteness of a single energy loss point, the candidate energy loss points are clustered based on their spatial proximity and interface affiliation. Points with similar spatial locations and consistent energy change trends are merged using density clustering or region merging to determine a representative set of key energy loss points. After obtaining the key points, the local optical parameters of the interfaces at each key point are further extracted, including interface refractive index, transmission efficiency, reflection efficiency, and local light energy flux. These parameters are then standardized and converted to a unified dimension to eliminate scale differences between different parameters. Based on this, an optical property difference calculation model is constructed to compare and analyze the local optical parameters at each key point, calculate the degree of deviation between them and the ideal optical matching state, and thus obtain the optical property difference value. Finally, an interface matching evaluation model is established based on the optical property difference values ​​of all key points. Through weighted summarization and spatial correlation analysis, the degree of matching deviation of each material interface is calculated, and the degree of deviation is numerically quantified to form an interface matching deviation index, which is used to characterize the overall deviation of the interface optical matching state.

[0077] Through the above steps, the precise identification of the energy loss location at the optical interface and the quantitative characterization of interface matching deviation can be achieved.

[0078] Furthermore, based on the interface matching deviation index, the combination of material layer thickness and refractive index is iteratively adjusted to obtain the interface configuration scheme with minimum loss. The steps of updating the packaging structure design through the interface configuration scheme specifically include: Based on the interface matching deviation index, the deviation contribution of each material interface is decomposed to determine the sensitivity weights of the thickness parameter and refractive index parameter of each material layer. A joint optimization parameter space for material layer thickness and refractive index is constructed based on sensitivity weights, and constraints are set for the joint optimization parameter space, including structural stability constraints, process feasibility constraints, and optical performance boundary constraints. In the joint optimization parameter space, an initial material layer thickness and refractive index combination scheme is generated, and the corresponding optical energy loss value and interface matching deviation value are calculated. A multi-objective evaluation function is constructed based on the light energy loss value and the interface matching deviation value to evaluate the fitness of each combination scheme. An iterative optimization algorithm is used to update each combination scheme generation by generation, and low-loss combination schemes that meet the convergence conditions are selected and retained to obtain a set of candidate optimal interface configuration schemes. A comprehensive comparative analysis of the candidate optimal interface configuration schemes was conducted, and the scheme with the lowest optical energy loss and the lowest interface matching deviation was selected as the interface configuration scheme with the lowest loss. The packaging structure design parameters were then updated based on the interface configuration scheme.

[0079] In this embodiment, a reverse decomposition analysis is first performed on the interfaces of each material based on the interface matching deviation index. The overall deviation value is broken down into different material layers and interface locations to determine the contribution of each material layer's thickness and refractive index parameters to the interface matching deviation. Based on this, a parameter sensitivity analysis model is constructed. By calculating the rate of change of deviation caused by changes in thickness and refractive index, the sensitivity weight distribution of each parameter is obtained, thereby clarifying the priority adjustment order of different structural parameters during the optimization process.

[0080] Subsequently, a joint optimization parameter space for material layer thickness and refractive index is constructed based on sensitivity weights. Multiple constraints are introduced within this parameter space, including structural stability constraints to ensure the physical integrity of the packaging structure; process feasibility constraints to limit the machinability range of parameter combinations in actual manufacturing processes; and optical performance boundary constraints to limit the acceptable range of light energy loss and transmission efficiency, thereby ensuring that the optimization process is conducted within the feasible region. After the parameter space is constructed, initial material layer thickness and refractive index combinations are generated through random sampling or regularization. Optical simulation calculations are then performed for each parameter combination to obtain the corresponding light energy loss value and interface matching deviation value, thus forming the initial evaluation dataset.

[0081] Furthermore, a multi-objective evaluation function is constructed based on optical energy loss and interface matching deviation. Different combinations are evaluated for fitness using weighted or Pareto optimization methods to simultaneously consider the comprehensive performance of energy loss and interface matching. During iterative optimization, iterative optimization strategies such as genetic algorithms, particle swarm optimization, or gradient descent are employed to update and screen parameter combinations generation by generation. New generations of candidate schemes are continuously generated through crossover, mutation, or perturbation mechanisms. Degraded schemes are eliminated based on convergence conditions, retaining combinations with low loss and low deviation, thus gradually forming a stable set of candidate optimal interface configuration schemes. Finally, a global comparative analysis is performed on each scheme in this set. Starting from the two core indicators of optical energy loss and interface matching deviation, the scheme with the best overall performance is selected as the interface configuration scheme with the lowest final loss. Its corresponding material layer thickness, refractive index, and structural geometric parameters are mapped back to the packaging design model, thereby completing the update and reconstruction of the packaging structure design.

[0082] Through the above steps, multi-objective iterative optimization of material parameters and refined reconstruction of packaging structure can be achieved.

[0083] Furthermore, the device packaging method also includes: Analog optical signals are transmitted within the updated encapsulation structure; Determine whether the transmission efficiency of the simulated optical signal is less than a preset transmission threshold; If the transmission efficiency is less than the transmission threshold, the path curvature characteristics in the ray path model are adjusted until the transmission efficiency is greater than or equal to the transmission threshold, thus obtaining the final ray path adjustment result.

[0084] In this embodiment, after updating the packaging structure, a simulated optical signal is first introduced to perform a verification transmission analysis on the overall optical system. A simulated light source model consistent with actual operating conditions is constructed, and its incident power, wavelength distribution, and spatial divergence angle are parameterized to represent the actual operating state of short-wave infrared devices. Subsequently, the simulated optical signal is input into the updated packaging structure model, and its propagation process in the multilayer material structure is tracked and calculated based on established optical propagation rules. Its transmission, reflection, and absorption behavior at each interface is obtained, and the overall transmission efficiency is further calculated. During this process, the energy attenuation of light along different propagation paths is integrated to obtain the system-level light energy output ratio, which serves as a transmission efficiency evaluation index. When the transmission efficiency is determined to be lower than a preset threshold, a path optimization mechanism is triggered to adjust the path curvature characteristics in the light path model. These path curvature characteristics include the range of refraction angle distribution, the degree of propagation direction shift, and the path curvature change characteristics at the interfaces. By iteratively correcting the above parameters, the propagation trajectory of light in the multilayer structure can be changed, leading to a more optimal energy transmission path. After each round of adjustment, the simulated transmission calculation is performed again and the transmission efficiency result is updated until the transmission efficiency reaches or exceeds the preset threshold. Finally, a stable and converged light path adjustment result is obtained, thereby realizing closed-loop optimization and verification of the optical performance of the packaging structure.

[0085] Through the above steps, closed-loop verification of the packaging structure and adaptive optimization of the light path can be achieved, thereby improving the stability of optical transmission.

[0086] In this embodiment, the optoelectronic device packaging method operates on an electronic device (e.g., Figure 1 The server shown can receive instructions or acquire data via wired or wireless connection. It should be noted that the aforementioned wireless connection methods may include, but are not limited to, 3G / 4G connections, WiFi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (ultra-wideband) connections, and other currently known or future wireless connection methods.

[0087] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing related hardware through computer-readable instructions. These computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0088] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0089] Further reference Figure 5 As a response to the above Figure 2 The present application provides an embodiment of an optoelectronic device packaging apparatus to implement the method shown. This apparatus embodiment is similar to... Figure 2 Corresponding to the method embodiments shown, this device can be specifically applied to various electronic devices.

[0090] like Figure 5 As shown, the optoelectronic device packaging device 500 described in this embodiment includes: The initial distribution module 501 is used to collect light data during the packaging process of short-wave infrared devices and calculate the propagation trajectory of light signals in the multi-layer optical structure based on the light data to obtain the initial light path distribution. The optical properties module 502 is used to analyze the refraction and transmission properties of light at different material interfaces based on the initial light path distribution. The optical path optimization module 503 is used to adjust the package geometry parameters according to the refractive and transmission characteristics to determine the optimized ray path model. The deviation identification module 504 is used to extract key energy loss points from the optimized light path model, obtain the optical characteristic differences at the key energy loss points, and obtain the interface matching deviation index. The configuration iteration module 505 is used to iteratively adjust the combination of material layer thickness and refractive index based on the interface matching deviation index, so as to obtain the interface configuration scheme with the least loss, and update the packaging structure design through the interface configuration scheme.

[0091] The implementation principle of the optoelectronic device packaging device 500 is consistent with that of the above method embodiment, and the specific working process of each module will not be described in detail here. This device integrates light propagation analysis, deviation identification, and parameter iterative optimization into a unified process through multi-module collaborative division of labor. It can efficiently complete the fine optimization of the optoelectronic device packaging structure, effectively reduce light energy loss, and improve the optical transmission performance after packaging.

[0092] To address the aforementioned technical problems, embodiments of this application also provide a computer device. Please refer to [link / reference needed]. Figure 6 , Figure 6 This is a basic structural block diagram of the computer device in this embodiment.

[0093] The computer device 6 includes a memory 61, a processor 62, and a network interface 63 that are interconnected via a system bus. It should be noted that only the computer device 6 with memory 61, processor 62, and network interface 63 is shown in the figure; however, it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented alternatively. Those skilled in the art will understand that the computer device described here is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0094] The computer device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device can interact with the user via a keyboard, mouse, remote control, touchpad, or voice control.

[0095] The memory 61 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 61 may be an internal storage unit of the computer device 6, such as the hard disk or memory of the computer device 6. In other embodiments, the memory 61 may also be an external storage device of the computer device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 6. Of course, the memory 61 may also include both the internal storage unit and its external storage device of the computer device 6. In this embodiment, the memory 61 is typically used to store the operating system and various application software installed on the computer device 6, such as computer-readable instructions for optoelectronic device packaging methods. In addition, the memory 61 can also be used to temporarily store various types of data that have been output or will be output.

[0096] In some embodiments, the processor 62 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 62 is typically used to control the overall operation of the computer device 6. In this embodiment, the processor 62 is used to execute computer-readable instructions stored in the memory 61 or to process data, for example, to execute computer-readable instructions for the optoelectronic device packaging method.

[0097] The network interface 63 may include a wireless network interface or a wired network interface, which is typically used to establish communication connections between the computer device 6 and other electronic devices.

[0098] This application also provides another embodiment, namely, providing a computer-readable storage medium storing computer-readable instructions that can be executed by at least one processor to cause the at least one processor to perform the steps of the optoelectronic device packaging method described above.

[0099] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0100] Obviously, the embodiments described above are only some embodiments of this application, not all embodiments. The accompanying drawings show preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms; rather, the purpose of providing these embodiments is to provide a more thorough and comprehensive understanding of the disclosure of this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this application's specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the scope of patent protection of this application.

Claims

1. A method for packaging optoelectronic devices, characterized in that, include: Light data is collected during the packaging process of short-wave infrared devices, and the propagation trajectory of the light signal in the multi-layer optical structure is calculated based on the light data to obtain the initial light path distribution; Based on the initial ray path distribution, analyze the refraction and transmission characteristics of light at different material interfaces; Based on the refractive and transmission properties, the packaging geometry parameters are adjusted to determine the optimized light path model; Extract key energy loss points from the optimized ray path model, obtain the differences in optical properties at the key energy loss points, and obtain the interface matching deviation index. For the interface matching deviation index, the combination of material layer thickness and refractive index is iteratively adjusted to obtain the interface configuration scheme with the minimum loss. The packaging structure design is updated through the interface configuration scheme. In this case, the light path simulation is re-executed for the interface configuration scheme, and the transmission efficiency and energy uniformity of the packaging structure are verified. When the preset optimization conditions are met, the final packaging structure design is output. The step of adjusting the encapsulation geometry parameters based on the refractive and transmission characteristics to determine the optimized ray path model specifically includes: Based on the refractive and transmission properties, the light deflection parameters, transmission efficiency parameters, and energy distribution parameters of each material interface in the multilayer optical structure are extracted to establish a set of interface optical features. Based on the set of interface optical features, target areas with abnormal energy accumulation or reduced transmission efficiency during light propagation are identified, and the encapsulation geometry parameters corresponding to the target areas are determined. For the aforementioned packaging geometry parameters, a set of geometric adjustment variables is constructed, and the material layer spacing, interface tilt angle, packaging cavity size, and optical window position are parameterized. The set of geometric adjustment variables is input into the ray path simulation model to recalculate the ray propagation trajectory, interface transmission, and energy distribution in the multi-layer optical structure, thereby obtaining multiple candidate ray path models. The transmission efficiency and energy uniformity of the multiple candidate ray path models are evaluated, and the candidate ray path model with the best comprehensive evaluation result is selected as the optimized ray path model.

2. The optoelectronic device packaging method as described in claim 1, characterized in that, The steps of acquiring light data during the packaging process of short-wave infrared devices and calculating the propagation trajectory of the light signal in the multi-layer optical structure based on the light data to obtain the initial light path distribution specifically include: The light source emission parameters, beam incident angle parameters, and structural parameters of each material layer in the packaging structure of the short-wave infrared device are collected to construct an optical model of the packaging structure. The initial emission position and initial propagation direction of the light are determined based on the emission parameters of the light source, and a set of light rays for propagation calculation is generated. Based on the optical model of the encapsulation structure, ray tracing calculations are performed on the light ray set to obtain the propagation path information of the light ray in each material layer; Based on the propagation path information, the interaction positions between the light and different material interfaces are identified, and the propagation direction change parameters and energy change parameters of the light at each interaction position are calculated. The propagation trajectory of light, the parameters of the propagation direction change, and the parameters of energy change are summarized and analyzed to generate the initial light path distribution of the light signal in the multilayer optical structure.

3. The optoelectronic device packaging method as described in claim 2, characterized in that, The step of summarizing and analyzing the propagation trajectory of light, the propagation direction change parameters, and the energy change parameters to generate the initial light path distribution of the light signal in the multilayer optical structure specifically includes: The propagation trajectory is spatially mapped to uniformly calibrate the propagation position, propagation direction, and propagation distance of the light in the multi-layer optical structure, forming a light path dataset. Based on the propagation direction change parameters, the degree of light deflection at different material interfaces is calculated, and the corresponding direction change feature sequence is constructed. Based on the energy change parameters, calculate the energy attenuation value, interface transmission energy value, and interface reflection energy value of light during propagation to form an energy distribution characteristic sequence. Correlation analysis is performed on the direction change characteristic sequence and the energy distribution characteristic sequence to determine the propagation stability index and energy retention index of light in the multilayer optical structure; Based on the light path dataset, the propagation stability index, and the energy preservation index, the propagation results of each light ray are statistically fused to generate an initial light path distribution that characterizes the overall propagation state of the light signal.

4. The optoelectronic device packaging method as described in claim 3, characterized in that, The step of statistically fusing the propagation results of each ray based on the ray path dataset, the propagation stability index, and the energy preservation index to generate an initial ray path distribution characterizing the overall propagation state of the optical signal specifically includes: According to the propagation area and propagation level of light in the multi-layer optical structure, the light samples in the light path dataset are classified and grouped to form multiple path feature subsets. For each of the aforementioned path feature subsets, the offset of light propagation direction, the distribution of propagation distance, and the frequency of interface interaction are statistically analyzed to obtain the corresponding path aggregation feature parameters. The propagation stability index and the path aggregation feature parameters are fused together to obtain the path credibility weight corresponding to each path feature subset. The energy preservation index is weighted based on the path credibility weight to obtain the comprehensive propagation contribution value corresponding to each path feature subset. The optical energy spatial distribution matrix is ​​constructed by statistically superimposing the comprehensive propagation contribution values ​​of each path feature subset, and an initial ray path distribution characterizing the overall propagation state of the optical signal is generated based on the optical energy spatial distribution matrix.

5. The optoelectronic device packaging method as described in claim 1, characterized in that, The steps of extracting key energy loss points from the optimized ray path model, obtaining the optical characteristic differences at the key energy loss points, and obtaining the interface matching deviation index specifically include: The energy distribution of light rays in the optimized light path model is analyzed to identify propagation locations where the energy attenuation rate exceeds a preset attenuation threshold, and these propagation locations are determined as candidate energy loss points. Based on the spatial location relationship and interface distribution relationship of the candidate energy loss points, clustering is performed on adjacent candidate energy loss points to determine key energy loss points; The local optical parameters of the material interface at each of the key energy loss points are obtained, and the optical property difference value is calculated based on the local optical parameters. The local optical parameters include at least the interface refractive index, transmission efficiency, reflection efficiency, and light energy flux. An interface matching evaluation model is constructed based on the differences in optical properties at each key energy loss point. The degree of matching deviation of each material interface is calculated, and the degree of matching deviation is quantified into an interface matching deviation index.

6. The optoelectronic device packaging method as described in claim 1, characterized in that, The step of iteratively adjusting the combination of material layer thickness and refractive index to obtain the interface configuration scheme with minimum loss based on the interface matching deviation index, and updating the packaging structure design through the interface configuration scheme, specifically includes: Based on the interface matching deviation index, the deviation contribution of each material interface is decomposed to determine the sensitivity weights of the thickness parameter and refractive index parameter of each material layer. Based on the sensitivity weights, a joint optimization parameter space for material layer thickness and refractive index is constructed, and constraints are set for the joint optimization parameter space, including structural stability constraints, process feasibility constraints, and optical performance boundary constraints. Within the joint optimization parameter space, an initial material layer thickness and refractive index combination scheme is generated, and the corresponding optical energy loss value and interface matching deviation value are calculated. A multi-objective evaluation function is constructed based on the light energy loss value and the interface matching deviation value to evaluate the fitness of each combination scheme. An iterative optimization algorithm is used to update each of the aforementioned combination schemes generation by generation, and low-loss combination schemes that meet the convergence conditions are selected and retained to obtain a set of candidate optimal interface configuration schemes. A comprehensive comparative analysis is performed on the set of candidate optimal interface configuration schemes. The scheme with the lowest light energy loss and the lowest interface matching deviation is selected as the interface configuration scheme with the lowest loss. The packaging structure design parameters are then updated based on the interface configuration scheme.

7. A photoelectric device packaging device, characterized in that, The optoelectronic device packaging apparatus implements the steps of the optoelectronic device packaging method as described in any one of claims 1 to 6, and the optoelectronic device packaging apparatus includes: The initial distribution module is used to collect light data during the packaging process of short-wave infrared devices, and calculate the propagation trajectory of the light signal in the multi-layer optical structure based on the light data to obtain the initial light path distribution; The optical properties module is used to analyze the refraction and transmission properties of light at different material interfaces based on the initial light path distribution. The optical path optimization module is used to adjust the package geometry parameters according to the refractive and transmission characteristics to determine the optimized light path model. The deviation identification module is used to extract key energy loss points from the optimized light path model, obtain the optical characteristic differences at the key energy loss points, and obtain the interface matching deviation index. The configuration iteration module is used to iteratively adjust the combination of material layer thickness and refractive index based on the interface matching deviation index to obtain the interface configuration scheme with the least loss, and update the packaging structure design through the interface configuration scheme.

8. A computer device, characterized in that, The device includes a memory and a processor, wherein the memory stores computer-readable instructions, and the processor executes the computer-readable instructions to implement the steps of the optoelectronic device packaging method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the optoelectronic device packaging method as described in any one of claims 1 to 6.

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