A method and system for fast optical simulation of cross-scale optoelectronic devices

Abstract

The application belongs to the technical field of photoelectric devices, and particularly discloses a fast optical simulation method and system for cross-scale photoelectric devices, which comprises the following steps: S1, dividing a functional layer and a non-functional layer according to the size of each film layer region of a photoelectric device; S2, judging the complex feature type of the functional layer, processing the complex feature by using a corresponding physical optical simulation method, and obtaining the optical characteristics at the interface; S3, judging whether the photoelectric device is an active device or a passive device according to the function of the photoelectric device, and then determining the light source characteristics; S4, calculating the optical characteristic parameters of the entire photoelectric device by using a geometric optical simulation method on the non-functional layer according to the light source characteristics and the optical characteristics at the interface, and completing the fast optical simulation of the photoelectric device. The fast optical simulation method is established for the complex features that may exist in the actual three-dimensional cross-scale photoelectric device, and the change rule and trend of the optical performance of the device can be reflected.

Description

Technical Field

[0001] This invention belongs to the field of optoelectronic device technology, and more specifically, relates to a rapid optical simulation method and system for cross-scale optoelectronic devices. Background Technology

[0002] Semiconductor optoelectronic devices are a new type of device that utilizes the photoelectric effect of semiconductors to achieve the mutual conversion of light energy and electrical energy. They include three main categories: light-emitting diodes (LEDs) and laser diodes (LDs), photoelectric detectors, and photovoltaic (PV) solar cells. Among them, LEDs and laser diodes release energy through the recombination of electrons and holes, converting electrical energy into light energy, and are considered active devices; while photoelectric detectors and solar cells utilize the photovoltaic effect to achieve the mutual conversion of light energy and electrical energy, and are considered passive devices. According to NRE statistics on the highest conversion efficiency trends of solar cells in the laboratory for different technical routes, the efficiency of silicon-based solar cells has now exceeded 40% (Iea. World Energy Outlook 2020), and the internal quantum efficiency of organic light-emitting diodes has also reached 100% (Physical Review B, 2015, 92(24), 245306). Most optoelectronic devices have successfully moved out of the laboratory and are widely used in daily life, military fields, industrial production, and other aspects.

[0003] Since the discovery of optoelectronic devices such as Organic Light Emitting Diodes (OLEDs) and Organic Photovoltaics (OPVs), researchers have continuously improved the performance and lifespan of these devices by adjusting their structures and material properties. Material innovation often leads to a qualitative leap in device quality, but the development of new materials is time-consuming and costly. For commercially available optoelectronic devices, researchers generally optimize device performance by adjusting the device structure to fully utilize the potential of the materials. Some companies and researchers use empirical and trial-and-error methods for device structure optimization design. To avoid randomness and errors in the experimental process, multiple experiments are required for a specific device structure. Furthermore, the diversity of device materials and film structures further complicates this approach, making it costly and time-consuming. Other researchers employ optical simulation methods to avoid the cumbersome experimental steps and high costs associated with empirical and trial-and-error methods.

[0004] Optical simulation is categorized into analytical / semi-analytical models and numerical simulation models based on structure discretization, based on the type of simulation algorithm. Analytical / semi-analytical models include methods such as the 4×4 transfer matrix method (Opt. Express, 2020, 28, 2381-2397) and anisotropic OLED device optical models (Optics Express, 2019, 27, A1014–A1029). While highly efficient, analytical / semi-analytical models can only analyze one-dimensional device structures, ignoring the three-dimensional features in the actual device space and simplifying it to an infinite one-dimensional structure in the horizontal direction. This method struggles to analyze the impact of the three-dimensional structure on device performance. Numerical simulation models based on structure discretization include the Finite Difference Time Domain (FDTD) method and the Finite Element Method (FEM). This method can establish a three-dimensional structure based on the actual device conditions, but its computational accuracy is highly dependent on the fineness of the geometric discretization of the device structure, and it is only applicable to device structures with similar feature sizes and simulation wavelengths. When processing multi-scale device structures, it requires significant computer resources, placing high demands on hardware performance and consuming a long time. Furthermore, in 2018, Wu Zhongzhi et al. proposed a hybrid-level algorithm for multi-scale organic light-emitting diodes (OLEDs) (Advance Science, 2018, 5, 1800467). This method combines the characteristics of physical optics and geometric optics, but it cannot handle the complex features in multi-scale devices, such as surface roughness films, optically anisotropic films, micro / nano structure array films, partially coherent / incoherent films, and metal layers containing random nanoparticles. Therefore, there is an urgent need to propose a systematic optical simulation method to achieve rapid optical simulation of multi-scale semiconductor optoelectronic devices with complex structures. Summary of the Invention

[0005] In view of the above-mentioned defects or improvement needs of the existing technology, the present invention provides a fast optical simulation method and system for cross-scale optoelectronic devices. Its purpose is to realize fast optical simulation of three-dimensional cross-scale optoelectronic devices with complex features, and lay the foundation for high-throughput simulation optimization.

[0006] To achieve the above objectives, according to one aspect of the present invention, a fast optical simulation method for cross-scale optoelectronic devices is proposed, comprising the following steps:

[0007] S1. Divide the functional layer and non-functional layer according to the size of each film layer region of the optoelectronic device;

[0008] S2. For the functional layer, determine its complex feature type, use the corresponding physical optics simulation method to process the complex features, and obtain the optical properties at the interface.

[0009] S3. Determine whether the optoelectronic device is an active or passive device based on its function, and then determine the characteristics of the light source.

[0010] S4. Based on the characteristics of the light source and the optical characteristics at the interface, and using the geometric optics simulation method on the non-functional layer, calculate the optical characteristic parameters of the entire optoelectronic device to complete the rapid optical simulation of the optoelectronic device.

[0011] As a further preferred embodiment, in step S1, the method for dividing the functional layer and the non-functional layer is as follows: when the thickness of the film layer in the vertical direction is at the nanometer level, it is determined to be a functional layer; when the thickness of the film layer in the vertical direction is at the micrometer level, it is determined to be a non-functional layer.

[0012] As a further preferred option, in step S3, for active devices, their light source characteristics are calculated based on CPS theory; for passive devices, the external light source characteristics are determined based on actual working conditions.

[0013] As a further preferred option, in step S4, the Poynting vector is calculated using the three-dimensional polarization ray tracing theory to obtain the far-field radiation spectrum of the entire optoelectronic device, and thus obtain the optical characteristic parameters of the entire device.

[0014] As a further preferred embodiment, the light source characteristics specifically refer to the spectrum, and the optical characteristics at the interface specifically refer to the reflectivity and transmittance at the interface; the optical characteristic parameters include the short-circuit current density and open-circuit voltage of passive devices, and the current efficiency and color coordinates of active devices.

[0015] As a further preferred option, in step S2, a corresponding physical optics simulation method is used to process complex features. Specifically, for interfaces containing anisotropic films, the reflectivity and transmittance of the interface are calculated using the 4×4 matrix method; for films containing micro-nano structure arrays in coherent layers, the transmission of electromagnetic fields in the films is calculated using the rigorous coupled-wave analysis method; for films containing partially coherent films, an optical model is constructed using the equal-phase method, and after inserting an additional layer of random thickness into the partially coherent layers, all films are treated as coherent films, and then the calculated refractive index and reflectivity are averaged.

[0016] According to another aspect of the present invention, a rapid optical simulation system for multi-scale optoelectronic devices is provided, comprising a computer-readable storage medium and a processor, wherein:

[0017] The computer-readable storage medium is used to store executable instructions; the processor is used to read the executable instructions stored in the computer-readable storage medium and execute the above-described fast optical simulation method for cross-scale optoelectronic devices.

[0018] In summary, compared with the prior art, the above-described technical solutions conceived by this invention mainly possess the following technical advantages:

[0019] 1. This invention establishes a systematic and rapid optical simulation method for the complex features that may exist in actual three-dimensional multi-scale optoelectronic devices. Specifically, it combines physical optics and geometric optics theories, and rationally divides the simulation area of ​​multi-scale semiconductor optoelectronic devices according to their applicable scope and device structure. At the same time, it adopts corresponding processing methods for the complex structures that may be contained in the device, realizing the optical simulation of three-dimensional multi-scale optoelectronic devices containing complex features. It can reflect the changing laws and trends of the device's optical performance. This simulation method has a wide range of applications and is simple and fast.

[0020] 2. The computational accuracy of this invention does not depend on the spatial discretization of the device structure, consumes less computer resources, and is highly efficient. It lays the foundation for high-throughput optimization of cross-scale optoelectronic devices and has broad application prospects in structural optimization design.

[0021] 3. This invention provides a method for distinguishing and processing functional and non-functional layers. The vertical thickness of functional layers is mostly between tens and hundreds of nanometers, and the horizontal dimension of the device is mostly between tens and hundreds of micrometers. Its horizontal dimension is much larger than its vertical dimension. Therefore, functional layers can still be equivalent to a one-dimensional structure and can be calculated using analytical / semi-analytical methods. For non-functional layers, their vertical thickness is generally between several micrometers and tens of micrometers. Their horizontal and vertical dimensions are on the same order of magnitude, and the influence of geometric characteristics such as sidewalls cannot be ignored. Therefore, geometric optics theory is used for simulation. Attached Figure Description

[0022] Figure 1 This is a flowchart of a rapid optical simulation method for cross-scale optoelectronic devices according to an embodiment of the present invention;

[0023] Figure 2 The equivalent three-dimensional structure of the multi-scale pixel OLED device to be simulated and analyzed in this embodiment of the invention;

[0024] Figure 3 The optical constants of the anisotropic film layer (PEDOT) in the embodiments of the present invention;

[0025] Figure 4 In the middle (a) and (b), the TE polarization state spectrum and TM polarization state spectrum of the line light source in the embodiment of the present invention are respectively.

[0026] Figure 5 In the middle (a)-(d), the reflectances of the anisotropic film interface Rss, Rsp, Rpp, and Rps in the embodiments of the present invention are respectively.

[0027] Figure 6In the examples of this invention, (a)-(d) represent the transmittance of the anisotropic film interface Tss, Tsp, Tpp, and Tps, respectively.

[0028] Figure 7 In the figures (a)-(i), the far-field radiation spectra calculated at 0°, 10°, 20°, 30°, 40°, 50°, 60°, 70°, and 80° respectively, are the far-field radiation spectra calculated by the FDTD algorithm and the far-field radiation spectra calculated by the FDTD algorithm in the embodiments of the present invention.

[0029] Figure 8 This is a comparison between the normalized current efficiency calculated in the embodiments of the present invention and the normalized current efficiency calculated by the FDTD algorithm.

[0030] Figure 9 This is a comparison between the color coordinates calculated by the embodiment of the present invention and the color coordinates calculated by the FDTD algorithm. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0032] This invention provides a fast optical simulation method for cross-scale optoelectronic devices, such as... Figure 1 As shown, it includes the following steps:

[0033] S1: Determine the basic information of the optoelectronic device and divide the simulation area.

[0034] S11 determines the device's equivalent three-dimensional structure, material optical constants, and film thickness, among other basic information.

[0035] Specifically, draw a simplified three-dimensional equivalent structure of the device, determine key dimensional parameters such as width, height, and sidewall angles; determine the positions of the main interfaces in the device and label them in a certain order; and determine the optical constants (including refractive index and extinction coefficient) and thickness of the film by testing with an ellipsometer or by consulting relevant literature.

[0036] S12, determine the functional and non-functional layers based on the device size, and divide the simulation area by combining the applicable range of physical optics and geometric optics.

[0037] Specifically, since the vertical thickness of the functional layer in semiconductor optoelectronic devices is mostly between tens and hundreds of nanometers, and the horizontal dimension of the device is mostly between tens and hundreds of micrometers, the horizontal dimension of the functional layer is much larger than the vertical dimension. Therefore, the functional layer can still be equivalent to a one-dimensional structure and can be calculated using analytical / semi-analytical methods (i.e., physical optics theory).

[0038] For non-functional layers, such as encapsulation layers or pixel boundaries, their vertical thickness is generally between a few micrometers and tens of micrometers. Their horizontal and vertical dimensions are on the same order of magnitude, and the influence of geometric characteristics such as sidewalls cannot be ignored. Therefore, simulation is performed using three-dimensional polarization ray tracing theory based on geometric optics.

[0039] S2. For the applicable area of ​​physical optics theory, determine the type of complex feature, and select the appropriate method such as rigorous coupled-wave analysis, 4×4 matrix method, equivalent medium theory or two-way scattering function to process the complex feature and calculate the optical properties at the interface.

[0040] Specifically, for interfaces containing anisotropic films, the reflectivity and transmittance of the interface are calculated using the 4×4 matrix method (Opt. Express 2020, 28, 2318-2397). For films containing micro / nano structure arrays within coherent layers, the electromagnetic field transmission within the film can be calculated using rigorous coupled-wave analysis (Nanomaterials, 2021, 11, 3187). For partially coherent films, an optical model can be constructed using the equal-phase method. After inserting an additional layer of random thickness into the partially coherent layer, all films are treated as equivalent to coherent films, and then the calculated refractive index and reflectivity are averaged (IEEE Photonics J, 2016, 8, 1-12).

[0041] Specifically, for films containing periodic nanostructures in incoherent layers, calculations can be performed using rigorous coupled-wave analysis combined with a two-way scattering function. By combining rigorous coupled-wave analysis, the transfer matrix, and electromagnetic field boundary conditions, the electromagnetic field expressions for the upper and lower surfaces of the film containing the grating structure can be obtained. Then, the reflectivity and transmittance can be calculated based on the relationship between the electromagnetic field and reflectivity and transmittance. The two-way scattering function can be described as:

[0042]

[0043] In the formula, P1 is the incident light energy distribution, P2 is the emitted light energy, and R... s R is the reflectivity of the grating medium when incident on the upper half of the medium. g T is the reflectivity when incident on the grating from the upper part. gThe transmittance is the light emitted from the upper part of the grating.

[0044] Specifically, the presence of random nanoparticles in a thin metal layer can modulate plasmon resonances on the metal surface, thereby improving device efficiency. The optical properties of the thin film can be studied by examining its optical properties or dielectric function; specifically, the refractive index and extinction coefficient of the nanoparticle-containing film can be measured using ellipsometric analysis. This film can then be treated as a uniform layer and incorporated into calculations using models such as a 4×4 matrix.

[0045] S3, determine the light source characteristics of the optoelectronic device.

[0046] S31. Based on the function of the semiconductor optoelectronic device, determine whether the device to be simulated and analyzed is an active device or a passive device, and determine its basic operating conditions.

[0047] Specifically, light-emitting diodes (LEDs) and laser diodes convert electrical energy into light energy, and are therefore active devices. It is necessary to determine the internal light source and operating wavelength range of these devices. λ , angle of departure θ Photodetectors and solar cells convert light energy into electrical energy; they are passive devices, and it is necessary to determine the spectrum and operating wavelength range of the external light source. λ Angle of incidence θ .

[0048] S32, for active optical devices, calculate the characteristics of the light source based on CPS theory, etc.; for passive optical devices, determine the characteristics of the external light source based on the actual working conditions.

[0049] Specifically, the far-field radiation spectrum of the internal light source is determined using the dipole radiation model, the microcavity coherence model, and the electromagnetic field transmission model. S ( λ , θ (Opt. Express, 2019, 27, A1014–A1029.); The spectrum of an external light source is detected by consulting known literature or using a spectrometer. S ( λ , θ ).

[0050] S4, combining the characteristics of the light source and the interface characteristics with complex features, uses the three-dimensional polarization ray tracing theory based on geometric optics to calculate the far-field radiation spectrum and optical characteristic parameters of the entire device.

[0051] Specifically, three-dimensional polarized ray tracing involves two parts: coordinate system transformation and planar reflection / transmission.

[0052] Coordinate system transformation can be described as:

[0053]

[0054] Here, matrix C is the transition matrix (basis transformation matrix) from the basis {s0,p0,k0} to the basis {s1,p1,k1}. The coordinate system basis in the incident plane O is {s0,p0,k0}, and the electric field intensity is... In the incident plane 1, the coordinate system basis is {s1,p1,k1}, and the electric field intensity is... .

[0055] For s(p) polarized light in coordinate system {s0,p0,k0}, it can be converted into s and p light in coordinate system {s1,p1,k1}:

[0056]

[0057] in, The Poynting vector represents the polarization state of TE(TM) in coordinate system {s0,p0,k0}. E TE(TM) (1) represents the electric field intensity vector in the incident plane 1. E TE(TM) The first component in E TE(TM) (2) represents the electric field intensity vector in the incident plane 1. E TE(TM) The second component in. The Poynting vector represents the light whose polarization state is transformed from TE(TM) in coordinate system {s0,p0,k0} to TE polarization state in coordinate system {s1,p1,k1}. The Poynting vector represents the light whose polarization state is transformed from TE(TM) in coordinate system {s0,p0,k0} to TM polarization state in coordinate system {s1,p1,k1}.

[0058] Plane reflection can be described as:

[0059]

[0060] In the formula, The Poynting vector represents the polarization state of TE(TM) when incident on the interface. and These represent the Poynting vectors of the TE and TM polarized light reflected from the interface, respectively. R TE(TM)-TE This represents the reflectivity when the incident TE(TM) polarization state is reflected to produce the TE polarization state. R TE(TM)-TM It represents the reflectivity when the incident TE(TM) polarization state is reflected to produce the TM polarization state.

[0061] Plane transmission can be described as:

[0062]

[0063] In the formula, T TE(TM)-TE This represents the transmittance when the incident TE(TM) polarization state is transmitted to produce the TE polarization state. T TE(TM)-TM This represents the transmittance when the incident TE(TM) polarization state is transmitted to generate the TM polarization state. Since light emitted from the light source undergoes multiple reflections and transmissions at different interfaces, and the simulation also requires tracing the paths of multiple light beams, the coordinate system transformation and plane reflection / transmission need to be iterated multiple times to obtain the far-field radiation spectrum of the entire device.

[0064] Specifically, the main performance parameters of the device are calculated based on its far-field radiation spectrum, including but not limited to the short-circuit current density of passive devices. J sc Open circuit voltage of passive devices V OC Current efficiency of active devices CE Color coordinates of active devices CIE .

[0065] The following are specific examples:

[0066] Taking a multi-scale pixel OLED device as an example, its complex features include anisotropic film layers. The film material information in the device includes: PDL (2.54μm) / Glass (2.02μm) / ITO (160nm) / PEDOT (40nm) / BCP (70nm) / Alq3 (50nm) / BCP (80nm) / MgAg (100nm) / Ag (20nm), where the PEDOT film layer is anisotropic. It is worth noting that, to verify the accuracy of the proposed method, a comparison with FDTD simulation results is used. Since the two methods use different fundamental theories in their calculations, only the changing trends of the device performance parameters can be verified; that is, if the trends are consistent, the simulation results can be considered reliable. The simulation of the proposed method is based on Matlab code, while the FDTD method simulation is based on ExpertOLED software. The ExpertOLED software simulation uses medium mesh precision and a current density of 10mA / cm². 2 The carrier balance rate is 1, the exciton recombination probability is 1, the simulation wavelength is 380~780nm, the step size is 5nm, the excitons are horizontally oriented, the exciton distribution function is Delta distribution, and they are located at the center of the emitting layer.

[0067] The above-mentioned rapid optical simulation method for multi-scale semiconductor optoelectronic devices with complex structures mainly includes the following steps:

[0068] S1, the equivalent three-dimensional structure of the multi-scale pixel OLED device to be simulated and analyzed is as follows: Figure 2 As shown, the film thickness of the device is as described above, and the horizontal dimensions and sidewall angles are given in the figure. Interface locations are indicated by ① to ④, and the dipole positions are also shown in the figure. The optical constants and thicknesses of each film material were determined using an ellipsometer. Figure 3 The values ​​in denoted as PEDOT are the optical constants of the anisotropic film.

[0069] S2, considering the applicability of geometrical optics and physical optics, as well as the structural characteristics of the device, the nanostructure film in this structure is analyzed using physical optics theory. Figure 2 The solid-lined rectangle indicates that the trapezoidal encapsulation layer is analyzed using geometric optics theory. Figure 2 The trapezoidal frame indicated by dashed lines is shown in the middle.

[0070] S3, a multi-scale pixel OLED device, is an optoelectronic device that converts electrical energy into light energy under the action of external voltage, with the light-emitting dipole located in the Alq3 film layer.

[0071] S4. When performing geometric optics analysis, the light source needs to be redefined based on the emission characteristics at the nanoscale. The light source for ray tracing is a surface source located at the interface between the ITO and PEDOT films. The far-field radiation spectrum of the surface source is determined using a dipole radiation model, a microcavity coherence model, and an electromagnetic field transport model, such as... Figure 4 As shown.

[0072] S5, the complex features of this device include an anisotropic film layer, namely the PEDOT film layer. The properties of interface 4 are determined by the film system composed of Glass (2.02 μm) / ITO (160 nm) / PEDOT (40 nm) / BCP (70 nm) / Alq3 (50 nm) / BCP (80 nm) / MgAg (100 nm) / Ag (20 nm). The reflectivity and transmittance of this interface calculated using the 4×4 matrix method are as follows: Figure 5 and Figure 6 As shown.

[0073] S6, combining the characteristics of the light source and the interface characteristics with complex features, uses three-dimensional polarization ray tracing theory to calculate the optical performance of the entire device.

[0074] S6.1, based on the outgoing ray, the outgoing interface, and the interface to be incident, determine the incident planes 0 and 1, and calculate their basis transformation matrix C, thereby calculating the electric fields of the TE and TM rays after coordinate transformation. Since the Poynting vector is proportional to the square of the electric field intensity, the Poynting vectors for different polarization states after coordinate transformation can be determined:

[0075]

[0076] in, The Poynting vector represents the polarization state of TE(TM) in coordinate system {s0,p0,k0}. E TE(TM) (1) represents the electric field intensity vector in the incident plane 1. E TE(TM) The first component in E TE(TM) (2) represents the electric field intensity vector in the incident plane 1. E TE(TM) The second component in. The Poynting vector represents the light whose polarization state is transformed from TE(TM) in coordinate system {s0,p0,k0} to TE polarization state in coordinate system {s1,p1,k1}. The Poynting vector represents the light whose polarization state is transformed from TE(TM) in coordinate system {s0,p0,k0} to TM polarization state in coordinate system {s1,p1,k1}.

[0077] S6.2, consider the reflection and transmission characteristics of the interface. The Poynting vector for the reflected light is:

[0078]

[0079] In the formula, The Poynting vector represents the polarization state of TE(TM) when incident on the interface. and These represent the Poynting vectors of the TE and TM polarized light reflected from the interface, respectively. R TE(TM)-TE This represents the reflectivity when the incident TE(TM) polarization state is reflected to produce the TE polarization state. R TE(TM)-TM It represents the reflectivity when the incident TE(TM) polarization state is reflected to produce the TM polarization state.

[0080] Plane transmission can be described as:

[0081]

[0082] In the formula, T TE(TM)-TE This represents the transmittance when the incident TE(TM) polarization state is transmitted to produce the TE polarization state. T TE(TM)-TM It represents the transmittance when the incident TE(TM) polarization state is transmitted to generate the TM polarization state.

[0083] S6.3, the ray tracing method involves the propagation of multiple light rays, and each light ray undergoes multiple reflections and transmissions within the structure, requiring multiple iterations of steps 6.1 and 6.2. The overall optical characteristics of the device are determined by combining the emission results after multiple iterations. Figure 7 The comparison between the emission spectra of the entire device calculated using the proposed method and those calculated using the FDTD algorithm is presented. The FDTD algorithm simulation was performed using the commercial software ExpertOLED. The spectra obtained using the proposed method can generally describe the approximate shape of the spectra calculated by the FDTD algorithm and can reflect changes in device efficiency. The fluctuations in the spectra obtained by the FDTD algorithm reflect the coherent modulation of the glass layer.

[0084] S6.4, calculate the key optical performance parameters of the device, current efficiency, and color coordinates based on the calculated Poynting vector. Figure 8 The paper presents a comparison between the normalized current efficiency calculated using the proposed method and the normalized current efficiency calculated using the FDTD algorithm. Figure 9 The comparison between the color coordinates calculated by the proposed method and those calculated by the FDTD algorithm is shown.

[0085] S6.5 compares the computation time consumed by the proposed method and the FDTD method to achieve the same simulation results. The FDTD algorithm simulation is based on the ExpertOLED commercial software.

[0086] The ExpertOLED software requires 2 hours and 46 minutes to simulate excitons at a single location. Figure 7 The simulation results, with 11 excitons at different positions, show that ExpertOLED simulation takes approximately 30 hours. Simulations using the method proposed in this invention with 5,000,000 random rays achieve... Figure 7 The simulation effect only takes about 0.84 hours, which greatly improves the simulation efficiency.

[0087] In summary, this application proposes a rapid optical simulation method for multi-scale semiconductor optoelectronic devices with complex structures. This method comprehensively considers the geometric characteristics of the device and the applicability of physical optics and geometrical optics theories, and systematically handles the complex features that may exist in actual structures. Compared with spatially discrete numerical simulation methods, the method proposed in this invention is more efficient and more flexible in its application. Furthermore, it lays the foundation for high-throughput simulation optimization of multi-scale semiconductor optoelectronic devices with complex structures.

[0088] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A rapid optical simulation method for cross-scale optoelectronic devices, characterized in that, Includes the following steps: S1. The aforementioned cross-scale optoelectronic device is a cross-scale pixel OLED device. Based on the size of each film layer region of the optoelectronic device, functional layers and non-functional layers are divided: when the thickness of the film layer in the vertical direction is at the nanometer level, it is determined to be a functional layer; when the thickness of the film layer in the vertical direction is at the micrometer level, it is determined to be a non-functional layer. S2. For the functional layer, determine its complex feature type. The complex features are processed using appropriate physical optics simulation methods to obtain the optical properties at the interface. S3. Calculate the light source characteristics of OLED devices based on near-field coupled wave theory; S4. Based on the characteristics of the light source and the optical characteristics at the interface, and using the geometric optics simulation method on the non-functional layer, calculate the optical characteristic parameters of the entire optoelectronic device to complete the rapid optical simulation of the optoelectronic device. Specifically, the Poynting vector is calculated using the three-dimensional polarization ray tracing theory, thereby obtaining the far-field radiation spectrum of the entire optoelectronic device, and then obtaining the optical characteristic parameters of the entire device. Three-dimensional polarized ray tracing involves two parts: coordinate system transformation and plane reflection and transmission. Coordinate system transformation is described as follows: Where matrix C is the transition matrix from basis {s0,p0,k0} to basis {s1,p1,k1}, the coordinate system basis in the incident plane O is {s0,p0,k0}, and the electric field intensity is... In the incident plane 1, the coordinate system basis is {s1,p1,k1}, and the electric field intensity is... ; The s-polarized or p-polarized light in coordinate system {s0,p0,k0} is converted into s-light and p-light in coordinate system {s1,p1,k1} by the following formula: in, The Poynting vector represents the TE polarization state or TM polarization state in the coordinate system {s0,p0,k0}. E TE(TM) (1) represents the electric field intensity vector in the incident plane 1. E TE(TM) The first component in E TE(TM) (2) represents the electric field intensity vector in the incident plane 1. E TE(TM) The second component; It represents the Poynting vector of light that is transformed from the TE polarization state or TM polarization state in coordinate system {s0,p0,k0} to the TE polarization state in coordinate system {s1,p1,k1}. It represents the Poynting vector of light that is transformed from the TE polarization state or TM polarization state in coordinate system {s0,p0,k0} to the TM polarization state in coordinate system {s1,p1,k1}. Plane reflection is described as follows: In the formula, The Poynting vector represents the TE polarization state or TM polarization state when incident on the interface. and These represent the Poynting vectors of the TE and TM polarized light reflected from the interface, respectively. R TE(TM)-TE This represents the reflectivity when a TE polarization state is generated by reflection from an incident TE polarization state or a TM polarization state. R TE(TM)-TM This represents the reflectivity when a TM polarization state is generated by reflection from an incident TE polarization state or a TM polarization state. Planar transmission is described as follows: In the formula, T TE(TM)-TE This represents the transmittance when the TE polarization state is generated by transmission from the incident TE polarization state or TM polarization state. T TE(TM)-TM This represents the transmittance when the TM polarization state is generated by the transmission of the incident TE polarization state or TM polarization state; the far-field radiation spectrum of the entire device is obtained by iterating through the above coordinate system transformation and plane reflection and transmission multiple times.

2. The rapid optical simulation method for cross-scale optoelectronic devices as described in claim 1, characterized in that, The light source characteristics specifically refer to the spectrum, and the optical characteristics at the interface specifically refer to the reflectivity and transmittance at the interface; the optical characteristic parameters include the current efficiency and color coordinates of the active device.

3. The rapid optical simulation method for cross-scale optoelectronic devices as described in claim 1 or 2, characterized in that, In step S2, a corresponding physical optics simulation method is used to handle complex features. Specifically, for interfaces containing anisotropic films, the reflectivity and transmittance of the interface are calculated using the 4×4 matrix method. For films containing micro-nano structure arrays in coherent layers, the transmission of electromagnetic fields in the films is calculated using the rigorous coupled-wave analysis method. For films containing partially coherent layers, an optical model is constructed using the equal-phase method. After inserting an additional layer with a random thickness into the partially coherent layers, all films are treated as coherent films, and then the calculated refractive index and reflectivity are averaged.

4. A rapid optical simulation system for cross-scale optoelectronic devices, characterized in that, Includes computer-readable storage media and processor, wherein: The computer-readable storage medium is used to store executable instructions; the processor is used to read the executable instructions stored in the computer-readable storage medium and execute the cross-scale optoelectronic device rapid optical simulation method according to any one of claims 1-3.

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