A method for designing and preparing a faraday rotator, a magneto-optical device, an apparatus and an equipment

Abstract

This invention provides a method for designing and fabricating a Faraday rotator, a magneto-optical device, an apparatus, and equipment, relating to the field of magneto-optical device technology. The method includes: S1, performing proton irradiation resistance simulation evaluation on candidate materials and iteratively screening to obtain target components; S2, performing phase diagram design and stability analysis on the target components to determine the process window; S3, based on the process window, fabricating a proton irradiation-resistant Faraday rotator using liquid-phase epitaxy. This invention abandons the existing technology's reliance on empirical trial-and-error component screening mode, not only solving the problem that existing technologies cannot simultaneously consider the radiation resistance performance, phase stability, and process feasibility of components, but also solving the problem of the disconnect between design and fabrication processes in existing technologies, thus efficiently producing Faraday rotators that meet the requirements for proton irradiation resistance.

Description

Technical Field

[0001] This invention relates to the field of magneto-optical device technology, and more specifically, to a method for designing and fabricating a Faraday rotator, a magneto-optical device, an apparatus, and equipment. Background Technology

[0002] Faraday rotators are key functional components in optical isolators, laser systems, optical communication devices, and special optical systems. With increasing demands for radiation resistance in applications such as space optical communication and aerospace payloads, the requirements for their proton radiation resistance have significantly increased. Existing Faraday rotators exhibit damage structures such as vacancies and defect clusters under proton radiation, leading to decreased transmittance, reduced optical rotation performance, and increased insertion loss, thus hindering engineering applications.

[0003] In related technologies, existing research mostly focuses on magneto-optical or optical performance optimization, with insufficient dedicated design for proton irradiation resistance and service stability. Furthermore, component screening relies entirely on empirical judgment and repeated experiments, resulting in long development cycles, high trial-and-error costs, and difficulty in achieving a synergistic balance between proton irradiation resistance, phase stability, and process feasibility. Summary of the Invention

[0004] The present invention aims to solve at least one of the above-mentioned problems.

[0005] To address the above problems, this invention provides a method for designing and fabricating a Faraday rotator, a magneto-optical device, an apparatus, and equipment.

[0006] In a first aspect, the present invention provides a method for designing and fabricating a Faraday rotator, comprising: S1. Conduct proton irradiation resistance simulation evaluation of candidate materials and iteratively screen to obtain target components; S2. Perform phase diagram design and stability analysis on the target component to determine the process window; S3. Based on the process window, a proton-resistant Faraday rotator is prepared by liquid phase epitaxy.

[0007] Optionally, step S1, performing proton irradiation resistance simulation evaluation on candidate materials and iteratively screening to obtain target components, includes: S11. Generate the candidate materials based on the candidate material system and element ratio range; S12. Perform a proton irradiation resistance simulation evaluation on the candidate materials to obtain the simulation evaluation results; S13. The simulation evaluation results are comprehensively evaluated and iteratively screened to obtain the target component.

[0008] Optionally, the simulation evaluation results include particle transport parameters, irradiation damage parameters, and performance parameters; S12, performing a proton irradiation resistance simulation evaluation on the candidate material to obtain the simulation evaluation results, including: S121. Perform particle transport simulation on the candidate material to obtain the particle transport parameters; S122. Based on the particle transport parameters, perform irradiation damage calculation on the candidate material to obtain the irradiation damage parameters; S123. Based on the irradiation damage parameters, the performance loss of the candidate material is simulated to obtain the performance parameters.

[0009] Optionally, step S13, which involves comprehensively evaluating and iteratively screening the simulation evaluation results to obtain the target component, includes: S131. Perform a comprehensive evaluation on the simulation evaluation results to obtain a comprehensive evaluation score; S132. Based on the comprehensive evaluation score, the target components are sorted, and the target components within a preset ranking range are extracted to obtain a candidate group set; S133. Based on the candidate group set, adjust the element ratio range to generate the next round of candidate component set, and substitute the next round of candidate component set into step S12 for iterative iteration until the comprehensive evaluation score meets the stopping iteration condition to obtain the target component.

[0010] Optionally, step S2, performing phase diagram design and stability analysis on the target component to determine the process window, includes: S21. Perform phase equilibrium calculations on the target component to obtain phase equilibrium data; S22. Based on the phase equilibrium data, perform phase stability screening to obtain a composition window; S23. Perform process window inversion based on the component window to obtain the process window.

[0011] Optionally, step S3, based on the process window, involves preparing a proton-irradiation-resistant Faraday rotator using liquid-phase epitaxy, comprising: S31. Based on the process window, generate a set of liquid phase epitaxial parameters; S32. Using the liquid phase epitaxy method, based on the liquid phase epitaxy parameter set, a target magneto-optical epitaxial layer is generated on the substrate material; S33. Post-process the target magneto-optical epitaxial layer to obtain the proton-resistant Faraday rotator.

[0012] Optionally, the Faraday rotator design and fabrication method further includes: S4. Perform device verification on the proton-resistant Faraday rotator. If the verification result of the proton-resistant Faraday rotator does not meet the verification conditions, execute step S1 and / or step S2 based on the optical sheet parameters in the verification result.

[0013] In a second aspect, the present invention provides a magneto-optical device, including a proton-resistant Faraday rotator prepared by the Faraday rotator design and preparation method described above.

[0014] Thirdly, the present invention provides a Faraday rotator design and fabrication apparatus, comprising: The screening module is used to simulate and evaluate the proton irradiation resistance of candidate materials and iteratively screen to obtain the target components; The analysis module is used to design phase diagrams and perform stability analysis on the target components to determine the process window; The preparation module is used to prepare a proton-resistant Faraday rotator using liquid phase epitaxy based on the process window.

[0015] Fourthly, the present invention provides an electronic device, including a memory and a processor; The memory is used to store computer programs; The processor is configured to implement the Faraday rotator design and fabrication method as described in the first aspect when executing the computer program.

[0016] The beneficial effects of the Faraday rotator design and fabrication method, magneto-optical device, apparatus, and equipment of the present invention are: This method obtains target components by conducting proton irradiation resistance simulation evaluation and iterative screening of candidate materials. It abandons the component screening mode of existing technologies that relies on experience-based trial and error. Based on the proton irradiation resistance simulation evaluation, it selects target components that meet the irradiation resistance requirements in a targeted manner, solving the problems of lack of irradiation damage-oriented design and high trial and error costs in existing component screening technologies. This lays a solid foundation for the preparation of proton irradiation resistant components. For the target component, phase diagram design and stability analysis are performed to determine the process window. The target component is combined with phase stability and process adaptability, solving the problem that existing technologies cannot simultaneously consider the radiation resistance performance of components, phase stability, and process feasibility. This provides precise and feasible process support for liquid phase epitaxy preparation. Based on this process window, a proton irradiation resistant Faraday rotator is prepared by liquid phase epitaxy, realizing a smooth connection from component design to process preparation. This solves the problem of the disconnect between design and preparation process in existing technologies and efficiently produces Faraday rotators that meet the requirements of proton irradiation resistance. Attached Figure Description

[0017] Figure 1 A schematic flowchart illustrating the design and fabrication method of a Faraday rotator provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of particle transport simulation provided in an embodiment of the present invention; Figure 3 A schematic diagram of the kinetic energy evolution curve over time and the defect number evolution curve over time provided in the embodiments of the present invention; Figure 4 This is a schematic diagram of phase diagram analysis provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of the Faraday rotator design and fabrication apparatus provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0018] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the accompanying drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0019] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0020] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to"; the term "based on" means "at least partially based on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; and the term "optionally" means "optional embodiments". Definitions of other terms will be given in the description below. It should be noted that the concepts of "first," "second," etc., mentioned in this invention are used only to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0021] It should be noted that the terms "one" and "more" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0022] The names of the messages or information exchanged between the multiple devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0023] like Figure 1 As shown in the figure, an embodiment of the present invention provides a method for designing and fabricating a Faraday rotator, comprising: S1. Perform proton irradiation resistance simulation evaluation on candidate materials and iteratively screen to obtain target components.

[0024] Specifically, this embodiment focuses on the candidate material system of Faraday rotation plates, performs a simulated evaluation operation on proton irradiation resistance, quantitatively evaluates the candidate material components through preset anti-irradiation performance evaluation rules, continuously eliminates components that do not meet the performance standards and narrows the range of preferred components according to iterative optimization logic, and finally accurately selects the target components that simultaneously meet the basic proton irradiation resistance performance requirements.

[0025] S2. Perform phase diagram design and stability analysis on the target component to determine the process window.

[0026] Specifically, this embodiment takes the selected target components as the core processing object, carries out phase diagram design and phase stability analysis, and accurately defines the process parameter boundaries that can be directly used for subsequent preparation based on the crystal structure stability characteristics, high temperature phase equilibrium law and liquid phase epitaxial growth adaptability requirements of the target components, and finally determines the process window that takes into account both phase stability and process feasibility.

[0027] S3. Based on the process window, a proton-resistant Faraday rotator is prepared by liquid phase epitaxy.

[0028] Specifically, this embodiment uses the determined process window as the sole basis for execution, adopts liquid phase epitaxy as the core preparation process, grows the target magneto-optical functional layer on the matching substrate material, and then shapes it through standard post-processing to finally prepare a Faraday rotator with proton irradiation resistance.

[0029] In this embodiment, the method obtains the target component by conducting proton irradiation resistance simulation evaluation and iterative screening of candidate materials. This method abandons the component screening mode of existing technologies that relies on experience-based trial and error. Based on the proton irradiation resistance simulation evaluation, the method selects the target component that meets the irradiation resistance requirements, solving the problems of lack of irradiation damage-oriented design and high trial and error costs in existing component screening. This lays a solid foundation for the subsequent preparation of proton irradiation-resistant components. For the target component, phase diagram design and stability analysis are performed to determine the process window. The target component is combined with phase stability and process adaptability, solving the problem that existing technologies cannot simultaneously consider the radiation resistance performance of components, phase stability, and process feasibility. This provides precise and feasible process support for liquid phase epitaxy preparation. Based on this process window, a proton irradiation-resistant Faraday rotator is prepared by liquid phase epitaxy, realizing a smooth connection from component design to process preparation. This solves the problem of the disconnect between design and preparation process in existing technologies, and efficiently produces a Faraday rotator that meets the requirements for proton irradiation resistance.

[0030] Optionally, step S1, performing proton irradiation resistance simulation evaluation on candidate materials and iteratively screening to obtain target components, includes: S11. Generate the candidate materials based on the candidate material system and element ratio range; S12. Perform a proton irradiation resistance simulation evaluation on the candidate materials to obtain the simulation evaluation results; S13. The simulation evaluation results are comprehensively evaluated and iteratively screened to obtain the target component.

[0031] Specifically, S11 automatically generates candidate materials to be evaluated based on a preset candidate material system, namely, a candidate Faraday optical rotation material system and an elemental ratio range. The candidate material system is a garnet-type magneto-optical material with the general chemical formula A3B5O. 12 The A-site element is selected from at least one of Y, Bi, Gd, Tb, Dy, Ho, Lu, Sm, Eu, Er, and Yb. The B-site element includes Fe, and may also be doped with at least one of Ga, Al, Sc, and In. It is preferably a rare-earth iron garnet type magneto-optical material with the general chemical formula A3Fe5-xMxO. 12 (A is selected from at least one of Y, Bi, Gd, and Tb, and M is selected from at least one of Ga, Al, Sc, and In, where 0 < x ≤ 2.5), more specifically "(Y1-a-bBiaGdb)3Fe5-xMxO 12(0≤a≤1.5, 0≤b≤1.5, 0≤a+b≤2.0, M is Ga / Al), the element ratio range includes the types and ratios of rare earth elements at site A, and the types and amounts of substituted elements at site B (Fe). The generated candidate materials can be generated through artificial proportioning, random algorithms, or orthogonal experiments. S12 conducts a comprehensive proton irradiation simulation evaluation of all candidate materials generated in S11, outputting complete simulation evaluation results covering particle transport, irradiation damage, and macroscopic performance. S13, based on the simulation evaluation results of S12, constructs a multi-dimensional comprehensive evaluation system, continuously narrowing the component range through iterative optimization to finally obtain the optimal target component. The characteristic relationships between the steps are: S11 is the starting point of the process, providing the basic research object for subsequent simulations; S12 is the core data acquisition stage, providing quantitative basis for iterative screening; S13 is the result convergence stage, achieving precise locking of the target component through comprehensive evaluation and iteration. These three steps form a complete closed loop of "candidate material generation - simulation evaluation - iterative screening".

[0032] Optionally, the simulation evaluation results include particle transport parameters, irradiation damage parameters, and performance parameters; S12, performing a proton irradiation resistance simulation evaluation on the candidate material to obtain the simulation evaluation results, including: S121. Perform particle transport simulation on the candidate material to obtain the particle transport parameters; S122. Based on the particle transport parameters, perform irradiation damage calculation on the candidate material to obtain the irradiation damage parameters; S123. Based on the irradiation damage parameters, the performance loss of the candidate material is simulated to obtain the performance parameters.

[0033] Specifically, S121 performs particle transport simulations on candidate materials, using one or more software programs such as SRIM, TRIM, and Geant4, and sets proton irradiation resistance conditions (proton energy from 0.1 MeV to 200 MeV, preferably from 0.5 MeV to 100 MeV; irradiation flux of 1 × 10⁻⁶). 9 cm -2 Up to 1×10 16 cm -2 1×10 is preferred 10 cm -2 Up to 1×10 15 cm -2 Incident angle 0° to 75°, preferably 0° to 60°; absorbed dose 10 Gy to 1 × 10⁻⁶ 6 Gy, preferably 100 Gy to 1×10 5Geant4 (Gy) can be used to obtain at least one particle transport parameter from the following: proton range distribution, depth distribution, energy deposition characteristics, ion energy loss, non-ion energy loss, terminal Bragg peak position, and differences in deposition distribution under different incident angles. Among them, SRIM / TRIM can be used to calculate the range, ion energy loss, non-ion energy loss, energy deposition, and displacement-related parameters of protons in materials, while Geant4 can be used to analyze the transport trajectory, energy deposition distribution, depth distribution, and impact of incident angle of protons in complex material systems and complex geometric structures. S122 takes particle transport parameters as input and combines one or more of the following: displacement damage model, defect statistical model, molecular dynamics, and first-principles calculations. Using LAMMPS (molecular dynamics) and VASP (first-principles) software, it obtains irradiation damage parameters such as displacement damage parameters, vacancy generation parameters, atomic displacement parameters, defect distribution parameters, defect cluster formation tendency, and / or structural stability-related parameters. Specifically, statistical calculations based on the displacement damage model can be used to obtain results such as dpa, vacancy generation number, and displacement distribution. Molecular dynamics software can be used to simulate irradiation cascade processes, defect evolution, and local structural rearrangements. First-principles calculation software can be used to evaluate defect formation energy, defect stability, and changes in local electronic structure. LAMMPS is preferred as the molecular dynamics software, and VASP is preferred as the first-principles calculation software. More specifically, the energy deposition parameters, ion energy loss parameters, and non-ion energy loss parameters in the particle transport parameters are imported into the displacement damage model to obtain the displacement damage distribution of the candidate formulation under the set proton irradiation resistance conditions; then, the motion evolution of different atoms in the irradiation cascade process is simulated by molecular dynamics simulation to obtain the number of vacancies generated, the number of atomic depletions, and the formation of defect clusters; if necessary, first-principles calculations are further combined to evaluate the formation energy and stability of typical defects under different element substitution conditions. S123 establishes the correlation between irradiation damage results and the macroscopic service performance of Faraday rotators, thereby evaluating the impact of proton irradiation resistance on material transmittance, Faraday rotation angle, insertion loss, and related device performance. Irradiation damage parameters are converted into equivalent optical parameters, which can be achieved using multiphysics coupling simulation software or electromagnetic / optical simulation software, such as COMSOL and Ansys Lumerical. The defect concentration, absorption center density, refractive index change, extinction coefficient change, and / or scattering loss change in the irradiation damage parameters are converted into equivalent optical parameters. The equivalent optical parameters are then imported into the light propagation or device response model to obtain performance parameters such as transmittance attenuation trend, Faraday rotation angle loss trend, insertion loss increase trend, and device performance change trend. The performance parameters can characterize the macroscopic performance retention ability of different components under proton irradiation resistance conditions. COMSOL can be used to map changes in absorption coefficient, refractive index, and thermal parameters caused by irradiation to the light field propagation process, thereby analyzing transmittance, power loss, and device response. Ansys Lumerical can be used for light propagation, mode field distribution, loss, and device-level optical response analysis. Other electromagnetic or optical simulation platforms can also be used to calculate performance degradation under material parameter perturbation conditions. The characteristic correlation between the steps is as follows: S121 obtains the basic physical data of proton-material interaction, providing the core input for S122; S122 analyzes the microscopic damage mechanism of the material, establishing the microscopic-macroscopic correlation for S123; S123 predicts macroscopic performance degradation, forming a continuous data chain of "particle transport - microscopic damage - macroscopic performance" in three steps.

[0034] Optionally, step S13, which involves comprehensively evaluating and iteratively screening the simulation evaluation results to obtain the target component, includes: S131. Perform a comprehensive evaluation on the simulation evaluation results to obtain a comprehensive evaluation score; S132. Based on the comprehensive evaluation score, the target components are sorted, and the target components within a preset ranking range are extracted to obtain a candidate group set; S133. Based on the candidate group set, adjust the element ratio range to generate the next round of candidate component set, and substitute the next round of candidate component set into step S12 for iterative iteration until the comprehensive evaluation score meets the stopping iteration condition to obtain the target component.

[0035] Specifically, this embodiment uses the radiation resistance performance evaluation rules described above. S131 performs threshold screening and comprehensive scoring on the simulation evaluation results. The threshold screening rules are as follows: components with transmittance retention rate < 70%, Faraday rotation angle retention rate < 75%, insertion loss increment > 3 dB, non-ionic energy loss > 1.10 times the average of the candidate set, displacement damage parameter > 1.10 times the average of the candidate set, or defect concentration > 1.10 times the average of the candidate set are directly eliminated; then, the comprehensive evaluation function S = w1 is constructed. Tn+w2 Rn-w3 ILn-w4 NIELn-w5 DPAn-w6 Cn, where Tn is the normalized value of transmittance retention, Rn is the normalized value of Faraday rotation angle retention, ILn is the normalized value of insertion loss increment, NIELn is the normalized value of non-ionic energy loss, DPAn is the normalized value of displacement damage parameter, and Cn is the normalized value of defect concentration. The weights w1=0.25, w2=0.25, w3=0.20, w4=0.10, w5=0.10, and w6=0.10, and the sum is 1. The normalization method is as follows: positive indicators (transmittance, rotation angle) use Xn=(X-Xmin) / (Xmax-Xmin), and negative indicators (insertion loss, energy loss, displacement damage, defect concentration) use the same formula but are included with a negative sign. Finally, a comprehensive evaluation score is obtained. S132 sorts the components from high to low according to the comprehensive evaluation score, extracts the top 20% of the components as the candidate group molecular set, and the components with a score >0.60 are judged as the preferred formulation and automatically retained. S133 adjusts and generates the next round of candidate component sets based on the extreme values ​​of the statistical element ratios in the candidate group molecular sets. For example, it calculates the minimum and maximum values ​​of the proportions of rare earth elements at position A and the proportions of substituted elements at position B in the candidate group molecular sets to update the element ratio range for the next round. It then returns to S12 for iterative iteration. Iteration stops when the change in the score of the optimal component between two adjacent rounds is <0.02, or the shrinkage of the ratio interval is <5%. The candidate component with the highest comprehensive evaluation function S in the current round is determined as the target component. This embodiment can automatically generate candidate components using Python scripts, schedule simulation software using the Snakemake / FireWorks workflow management program, and complete the automatic scoring and screening using the Optuna / pymoo optimization program, achieving full-process automation. The feature relationships between steps are as follows: S131 score calculation is the core basis for ranking; S132 subset extraction is the screening criterion for iterative optimization; S133 iterative iteration achieves automatic convergence of the component interval, ensuring the optimal target component. For example, alternative solutions include: replacing the comprehensive evaluation method with the weighted scoring method, fuzzy comprehensive evaluation method, or TOPSIS method; replacing the iteration stopping condition with a fixed number of iterations (10-20 rounds); and adjusting the ranking range to 15%-25%.

[0036] Optionally, step S2, performing phase diagram design and stability analysis on the target component to determine the process window, includes: S21. Perform phase equilibrium calculations on the target component to obtain phase equilibrium data; S22. Based on the phase equilibrium data, perform phase stability screening to obtain a composition window; S23. Perform process window inversion based on the component window to obtain the process window.

[0037] Specifically, S21 employs thermodynamic calculations and the CALPHAD method, combined with phase diagram analysis software such as Thermo-Calc, FactSage, and Pandat, to perform phase equilibrium calculations on the target component. Input data includes the types and proportions of rare earth elements at the A-site, the types and amounts of substituted elements at the B-site, and the corresponding proton irradiation resistance simulation evaluation results. Under given oxygen partial pressure conditions, it calculates the equilibrium phase composition, phase fraction, and liquid phase range for different temperatures and compositions, obtaining phase equilibrium data such as the single-phase stable region, impurity phase precipitation boundary, liquid phase region, solid-liquid coexistence region, liquidus temperature, solidus temperature, and main crystalline phase range. Thermo-Calc can be used for thermodynamic equilibrium, phase composition, and temperature-composition relationship analysis of multi-component systems; FactSage can be used for phase equilibrium calculations, phase stability range prediction, and thermodynamic property evaluation of complex oxide systems; and Pandat can be used for phase diagram construction, phase boundary analysis, and composition window optimization for multi-component systems. S22 uses phase equilibrium data to screen for phase stability, eliminating components that easily precipitate impurities, have excessively narrow liquid phase regions, or whose main crystalline phase deviates from the garnet phase. This yields a compositional window that characterizes both the maintenance of the garnet single-phase structure and suitability for liquid-phase epitaxial growth under given temperature and oxygen partial pressure conditions: For systems with Bi and Gd co-doping at the A site, the Bi substitution amount a = 0.1 to 1.2, the Gd substitution amount b = 0 to 1.0, and a + b ≤ 2.0; for systems with Ga and Al substitution at the B site, the Ga substitution amount x1 = 0 to 1.5, the Al substitution amount x2 = 0 to 1.0, and x1 + x2 ≤ 2.5. This window balances radiation resistance, phase stability, and the feasibility of liquid-phase epitaxy. By analyzing the phase distribution under different elemental compositions and ratios, it is possible to determine whether the target material can maintain a single-phase garnet structure within a given temperature range, and whether impurity phases, second phases, or non-target structural phases are easily precipitated during liquid-phase epitaxial growth. This allows for the selection of candidate ratio ranges that meet both proton irradiation resistance requirements and phase stability. S23 performs process window inversion based on the composition window, obtaining parameters such as melt composition, growth temperature range, supercooling range, growth interval, and cooling path, forming a process window that can be directly used for preparation. Furthermore, only components that simultaneously meet the proton irradiation resistance threshold, single-phase stability requirements, and liquid-phase epitaxial growth window requirements are retained and proceed to step S3. This achieves automated secondary screening and continuous data transfer from "simulated formulation screening" to "phase diagram process determination." Through four stages—component input, phase equilibrium calculation, phase stability screening, and process window inversion—the transformation from target element ratios to feasible epitaxial growth processes can be completed before the material is formally prepared. This ensures that the target components obtained based on simulation are no longer limited to theoretical screening but are further defined as preparation windows with clear phase stability criteria and process boundary conditions. Figure 4The phase diagram analysis results for the Ho₂O₃-Fe₂O₃-O₂ and Eu₂O₃-Fe₂O₃-O₂ systems are shown. The horizontal axis represents the molar ratio of rare earth oxides to iron oxides, and the vertical axis represents temperature. HoFe₅O is clearly marked in the figure. 12 / EuFe5O 12 The single-phase stable region, impurity phase precipitation boundary, liquid phase region, and solid-liquid coexistence region visually reflect the influence of different rare earth elements on phase stability, providing a direct basis for composition window screening. The inter-step characteristics are as follows: S21 phase equilibrium calculation is the data foundation for screening; S22 composition window screening is a prerequisite for process inversion; S23 process window inversion realizes the transformation from theoretical composition to actual preparation parameters. Alternative solutions: phase diagram calculation software can be replaced with other phase equilibrium analysis tools; phase stability screening can be replaced by manual verification instead of automatic screening; process window inversion can be replaced by empirical fitting instead of data inversion.

[0038] Optionally, step S3, based on the process window, involves preparing a proton-irradiation-resistant Faraday rotator using liquid-phase epitaxy, comprising: S31. Based on the process window, generate a set of liquid phase epitaxial parameters; S32. Using the liquid phase epitaxy method, based on the liquid phase epitaxy parameter set, a target magneto-optical epitaxial layer is generated on the substrate material; S33. Post-process the target magneto-optical epitaxial layer to obtain the proton-resistant Faraday rotator.

[0039] Specifically, S31 automatically generates a liquid phase epitaxial parameter set based on the process window. The data in the process window includes one or more of the following: melt composition range, growth temperature range, supercooling range, effective growth range, cooling path, and substrate matching conditions. The liquid phase epitaxial parameter set includes melt composition, growth temperature of 650℃ to 1050℃ (preferably 700℃ to 950℃), growth time of 1min to 180min (preferably 5min to 120min), supercooling of 1℃ to 50℃ (preferably 3℃ to 25℃), cooling rate of 0.1℃ / min to 10℃ / min (preferably 0.2℃ / min to 5℃ / min), substrate crystal orientation (111) / (110) / (100), and cooling conditions. For different target components within the input process window range, the system can automatically select the corresponding combination of melt composition, growth temperature, growth time, supercooling, and cooling rate, thereby reducing manual trial and error and reliance on experience. More specifically, it automatically determines the melt ratio for preferential precipitation of the target garnet phase based on the melt composition range given in the process window; it automatically determines the liquid phase epitaxial growth temperature and holding time based on the growth temperature range given in the process window; it automatically determines the substrate immersion timing, growth time, and cooling rate based on the supercooling range and effective growth range given in the process window; and it automatically determines the liquid ejection, slow cooling, and annealing conditions after growth based on the cooling path given in the process window. S32 uses the liquid phase epitaxy method to grow a target magneto-optical epitaxial layer with a thickness of 0.1μm to 500μm (preferably 0.5μm to 100μm) on a single crystal substrate such as GGG or SGGG that has a lattice matching / thermal expansion coefficient similar to the target magneto-optical material. The material is a garnet-type magneto-optical material, preferably rare earth iron garnet. S33 involves cutting, grinding, and polishing the target magneto-optical epitaxial layer, followed by annealing according to a matched cooling path. Annealing reduces growth stress, minimizes surface defects, and improves optical quality, ultimately producing a proton-resistant Faraday rotator. The key relationships between these steps are: S31, the parameter set, serves as the standard for epitaxial growth; S32, epitaxial growth is the core step in obtaining the magneto-optical functional layer; and S33, post-processing, is crucial for enhancing the optical and structural performance of the rotator. Alternative solutions include: replacing the substrate with a lattice-matched garnet-type single-crystal substrate; replacing the annealing process with vacuum annealing or oxygen atmosphere annealing; and adding an optical coating step in post-processing, or omitting the annealing step as needed.

[0040] Optionally, the Faraday rotator design and fabrication method further includes: S4. Perform device verification on the proton-resistant Faraday rotator. If the verification result of the proton-resistant Faraday rotator does not meet the verification conditions, execute step S1 and / or step S2 based on the optical sheet parameters in the verification result.

[0041] Specifically, the proton-irradiation-resistant Faraday rotator fabricated in S3 was validated. Tests included transmittance, Faraday rotation angle, insertion loss, and device-level stability. Validation conditions were: transmittance retention ≥ 70%, Faraday rotation angle retention ≥ 75%, and insertion loss increment ≤ 3dB. The rotator was then assembled into magneto-optical devices such as optical isolators, magneto-optical modulation units, and radiation-resistant optical systems to complete device-level performance testing. If the validation results did not meet the above conditions, the rotator parameters were synchronously fed back to the component iteration screening step in S1 and the phase diagram analysis and process window step in S2 to correct the target component range, component window, and process window parameters for re-simulation optimization and fabrication. If the validation results met the standards, the current component and process were confirmed as the optimal solution, forming a closed-loop optimization system encompassing "simulation design - phase diagram optimization - process fabrication - device validation - feedback correction." The beneficial effects of this step are: through actual device-level verification, it ensures that the theoretical design matches the actual service performance, continuously optimizes materials and processes, completely solves the problems of performance degradation and poor stability of Faraday rotators under proton irradiation, and improves the long-term service reliability of magneto-optical devices.

[0042] For example, this embodiment uses the Bi-Eu-Ho-Fe-Ga-O system as the actual application object for explanation and illustration: First, an initial candidate stoichiometric range for the Bi-Eu-Ho-Fe-Ga-O system was defined, where Bi, Eu, and Ho occupy the A-sites, and Ga partially substitutes for the Fe-sites. Several candidate stoichiometric models, i.e., candidate materials, were established within this preset range. Then, the first round of particle transport simulations was conducted. Particle transport simulation software was used to analyze the process of each candidate stoichiometric model with 1 MeV proton incidence, obtaining parameters such as the proton transport trajectory, depth distribution, ion distribution, energy deposition characteristics, ion energy loss, and non-ion energy loss in the material. These parameters were denoted as the first round output data A1, i.e., the particle transport parameters. Figure 2(a) shows the particle transport simulation results of the target candidate system under 1 MeV proton incident conditions, where the left figure is the distribution of proton transport trajectories in the material, and the right figure is the ion distribution. Based on the first round output data A1, the different candidate ratios are compared in terms of proton deposition concentration, transport depth, and energy deposition uniformity. Candidate ratios with more stable transport distribution and lower non-ion energy loss are prioritized, while candidate ratios with excessively concentrated energy deposition or unfavorable incident response are eliminated, thus obtaining the candidate ratio range after the first round of screening. Based on the first round of particle transport simulation, the first round of irradiation damage analysis is further performed. Using the candidate ratio range after the first round of screening as input, the irradiation damage behavior of each candidate ratio is compared to obtain displacement damage parameters, vacancy generation parameters, atomic displacement parameters, defect distribution parameters, and structural stability-related parameters, which are denoted as the first round output data B1, i.e., irradiation damage parameters. Specifically, taking the screened Bi-Eu-Ho-Fe-Ga-O candidate system as the object, three representative atoms of Fe, Bi, and O were selected to study the kinetic energy decay behavior and defect evolution law of different atoms under different initial incident energies. The results are as follows: Figure 3 As shown. Figure 3 The top row shows the kinetic energy evolution curves of Fe, Bi, and O atoms under different initial incident energies over time; the bottom row shows the defect number evolution curves of Fe, Bi, and O atoms under different initial incident energies over time. Figure 3 It can be seen that the kinetic energy decays relatively slowly, and the number of defects induced by light atoms is greater, indicating that light atoms are more likely to cause the continuous accumulation of local defects during the irradiation cascade process. Based on the first round output data B1, the different candidate ratios were compared in terms of the number of defects, the degree of structural perturbation, and irradiation sensitivity. Candidate ratios with fewer defects and weaker structural perturbation were prioritized and retained, and the ratio range of Bi, Eu, Ho, and Ga was further narrowed down.

[0043] Based on the first round of particle transport simulation and the first round of irradiation damage analysis, phase diagram analysis was further performed. Using the candidate stoichiometry ranges retained after the first two rounds of screening as input, phase equilibrium analyses were conducted on the Eu and Ho related systems to determine the phase stability, growth window, and feasibility of the target material. Specifically, phase equilibrium analyses were performed on the Ho₂O₃-Fe₂O₃-O₂ system and the Eu₂O₃-Fe₂O₃-O₂ system, and the results are as follows: Figure 4 As shown. Figure 4 The left figure shows the phase diagram of the Ho₂O₃-Fe₂O₃-O₂ system, and the right figure shows the phase diagram of the Eu₂O₃-Fe₂O₃-O₂ system. Figure 4It can be seen that there are differences in the phase region distribution, single-phase stability region range, and impurity phase precipitation boundary of the Ho and Eu related oxide systems, indicating that Eu and Ho elements have a direct impact on the phase stability and growth window of the target system. Based on the phase diagram analysis results, candidate ratios that have certain proton irradiation resistance potential but lack phase stability, are prone to impurity phase precipitation, or are unfavorable for liquid phase epitaxial growth were further screened out, resulting in the candidate ratio range after the second round of screening, denoted as output data C1, i.e., the composition window.

[0044] Subsequently, iterative simulation optimization was performed again on the candidate ratio range after the second round of screening. Specifically, the output data C1 was re-input into the particle transport simulation and irradiation damage analysis process to perform a second round of particle transport simulation and irradiation damage analysis on the narrowed candidate ratios, obtaining the second round output data A2 and the second round output data B2, respectively. By comparing the differences in proton transport behavior, defect accumulation degree, and structural stability of different candidate ratios in the second round output data A2 and the second round output data B2, and combining the phase stability boundary obtained from the aforementioned phase diagram analysis, the candidate ratios were further fine-tuned and converged. After the above iterative optimization process, Bi was finally determined. 1.2 Eu 0.4 Ho 1.4 Fe 4.5 Ga 0.5 O 12 As a target material composition that balances proton irradiation resistance and phase stability, and based on phase diagram analysis results, the composition window and temperature window required for its liquid phase epitaxial growth are determined and denoted as the final output data D, i.e., the process window.

[0045] Finally, liquid phase epitaxy was performed based on the final output data D. Bi₂O₃, Eu₂O₃, Ho₂O₃, Fe₂O₃, and Ga₂O₃ were weighed as raw materials. A PbO-B₂O₃ flux was used to prepare the melt system required for liquid phase epitaxial growth, and a (111) oriented GGG single crystal substrate was selected as the growth substrate. The liquid phase epitaxial growth temperature was set to 865℃. After holding at this temperature for 30 min, the substrate was immersed in the melt. The supercooling was controlled at 12℃, the growth time was 18 min, and the cooling rate was controlled at 0.5℃ / min. After growth, the substrate was rotated at 60 rpm for 30 s to remove the sample and allow it to cool slowly to room temperature. Subsequently, the sample was cut, ground, polished, and annealed at 650℃ for 40 min to obtain Bi₂O₃. 1.2 Eu 0.4 Ho 1.4 Fe 4.5 Ga 0.5 O 12 Faraday plate.

[0046] This embodiment demonstrates that by performing multiple rounds of iterative simulations on the Bi-Eu-Ho-Fe-Ga-O candidate element system, gradual convergence from the initial candidate ratio range to the target formulation can be achieved. Specifically, the first round of particle transport simulation yields first-round output data A1, the first round of irradiation damage analysis yields first-round output data B1, and phase diagram analysis yields output data C1. Subsequently, based on output data C1, a second round of particle transport simulation and a second round of irradiation damage analysis are performed to obtain second-round output data A2 and B2, and finally, the target material composition corresponding to output data D is determined to be Bi. 1.2 Eu 0.4 Ho 1.4 Fe 4.5 Ga 0.5 O 12 This forms a complete iterative screening, optimization, and preparation process.

[0047] For example, this embodiment uses the Bi-Tb-Fe-Al-O system as the actual application object for explanation and illustration: After simulation analysis and phase diagram constraints, the target material composition ratio was determined to be Bi1Tb2Fe. 4.2 Al 0.8 O 12 The particle transport simulation results are as follows: Figure 2 As shown in (b), the remaining simulation analysis process is the same as in the previous embodiment. In the liquid phase epitaxial preparation stage, Bi2O3, Tb4O7, Fe2O3 and Al2O3 were weighed as raw materials, and a melt system was prepared with PbO-B2O3 flux. A (111) oriented GGG single crystal substrate was selected as the growth substrate. The liquid phase epitaxial growth temperature was set to 845℃. After holding at this temperature for 25 min, the substrate was immersed in the melt. The supercooling was controlled at 10℃, the growth time was 15 min, and the cooling rate was controlled at 0.4℃ / min. After the growth was completed, the sample was rotated and spun for 20 s. The sample was then removed and slowly cooled to room temperature. Subsequently, it was cut, ground, polished, and annealed at 620℃ for 30 min to obtain BiTb2Fe 4.2 Al 0.8 O 12 Faraday plate.

[0048] For example, this embodiment uses the Bi-Tb-Yb-Fe-O system as an example for explanation: After simulation analysis and phase diagram constraints, the target material composition ratio was determined to be Bi. 1.4 Tb 1.1 Yb 0.5 Fe5O 12 The particle transport simulation results are as follows: Figure 2As shown in (c), the remaining simulation analysis process is the same as in the previous embodiment. In the liquid phase epitaxial preparation stage, Bi2O3, Tb4O7, Yb2O3 and Fe2O3 were weighed as raw materials, and a melt system was prepared with PbO-B2O3 flux. A (111) oriented GGG single crystal substrate was selected as the growth substrate. The liquid phase epitaxial growth temperature was set to 878℃. After holding at this temperature for 35 min, the substrate was immersed in the melt. The supercooling was controlled at 14℃, the growth time was 20 min, and the cooling rate was controlled at 0.6℃ / min. After the growth was completed, the sample was rotated and spun for 25 s. The sample was then removed and slowly cooled to room temperature. Subsequently, it was cut, ground, polished, and annealed at 680℃ for 45 min to obtain Bi 1.4 Tb 1.1 Yb 0.5 Fe5O 12 Faraday plate.

[0049] For example, this embodiment uses the Bi-Tm-Fe-Ga-O system as a practical application for explanation: After simulation analysis and phase diagram constraints, the target material composition ratio was determined to be Bi. 2.2 Tm 0.8 Fe 4.5 Ga 0.5 O 12 The particle transport simulation results are as follows: Figure 2 As shown in (d), the remaining simulation analysis process is basically the same as in Example 1. In the liquid phase epitaxial preparation stage, Bi2O3, Tm2O3, Fe2O3 and Ga2O3 were weighed as raw materials, and a melt system was prepared with PbO-B2O3 flux. A (111) oriented GGG single crystal substrate was selected as the growth substrate. The liquid phase epitaxial growth temperature was set to 852℃. After holding at this temperature for 28 min, the substrate was immersed in the melt. The supercooling was controlled at 11℃, the growth time was 16 min, and the cooling rate was controlled at 0.5℃ / min. After the growth was completed, the liquid was rotated and spun for 20 s. The sample was then taken out and slowly cooled to room temperature. Subsequently, it was cut, ground, polished, and annealed at 640℃ for 35 min to obtain Bi 2.2 Tm 0.8 Fe 4.5 Ga 0.5 O 12 Faraday plate.

[0050] This invention provides a magneto-optical device, including a proton-resistant Faraday rotator prepared by the Faraday rotator design and preparation method described above.

[0051] Specifically, magneto-optical devices are magneto-optical functional elements in optical isolators, magneto-optical modulation units, or radiation-resistant optical systems.

[0052] like Figure 5As shown, an embodiment of the present invention provides a Faraday rotator design and fabrication apparatus, comprising: The screening module is used to simulate and evaluate the proton irradiation resistance of candidate materials and iteratively screen to obtain the target components; The analysis module is used to design phase diagrams and perform stability analysis on the target components to determine the process window; The preparation module is used to prepare a proton-resistant Faraday rotator using liquid phase epitaxy based on the process window.

[0053] like Figure 6 As shown, an electronic device 600 provided in this embodiment of the invention includes a memory 610 and a processor 620; the memory 610 is used to store a computer program; the processor 620 is used to implement the Faraday rotator design and fabrication method as described above when the computer program is executed.

[0054] Alternatively, an electronic device 600 includes a memory 610 and a processor 620 coupled to the memory 610; the memory 610 is configured to store a computer program; and the processor 620 is configured to perform the following operations when the computer program is executed: S1. Conduct proton irradiation resistance simulation evaluation of candidate materials and iteratively screen to obtain target components; S2. Perform phase diagram design and stability analysis on the target component to determine the process window; S3. Based on the process window, a proton-resistant Faraday rotator is prepared by liquid phase epitaxy.

[0055] This invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the Faraday rotator design and fabrication method described above.

[0056] Alternatively, a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the following operations: S1. Conduct proton irradiation resistance simulation evaluation of candidate materials and iteratively screen to obtain target components; S2. Perform phase diagram design and stability analysis on the target component to determine the process window; S3. Based on the process window, a proton-resistant Faraday rotator is prepared by liquid phase epitaxy.

[0057] Electronic device 600, which can serve as a server or client of the present invention, is described below as an example of a hardware device applicable to various aspects of the present invention. Electronic device 600 is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic device 600 can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0058] Electronic device 600 includes a computing unit that can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) or a computer program loaded from a storage unit into random access memory (RAM). The RAM may also store various programs and data required for device operation. The computing unit, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0059] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. In this application, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention according to actual needs. Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units can be implemented in hardware or as software functional units.

[0060] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A method for designing and fabricating a Faraday rotator, characterized in that, include: S1. Conduct proton irradiation resistance simulation evaluation of candidate materials and iteratively screen to obtain target components; S2. Perform phase diagram design and stability analysis on the target component to determine the process window; S3. Based on the process window, a proton-resistant Faraday rotator is prepared by liquid phase epitaxy.

2. The method for designing and fabricating a Faraday rotator according to claim 1, characterized in that, S1 involves conducting proton irradiation resistance simulation evaluations on candidate materials and iteratively screening to obtain target components, including: S11. Generate the candidate materials based on the candidate material system and element ratio range; S12. Perform a proton irradiation resistance simulation evaluation on the candidate materials to obtain the simulation evaluation results; S13. The simulation evaluation results are comprehensively evaluated and iteratively screened to obtain the target component.

3. The method for designing and fabricating a Faraday rotator according to claim 2, characterized in that, The simulation evaluation results include particle transport parameters, irradiation damage parameters, and performance parameters; S12, performing a proton irradiation resistance simulation evaluation on the candidate material to obtain the simulation evaluation results, including: S121. Perform particle transport simulation on the candidate material to obtain the particle transport parameters; S122. Based on the particle transport parameters, perform irradiation damage calculation on the candidate material to obtain the irradiation damage parameters; S123. Based on the irradiation damage parameters, the performance loss of the candidate material is simulated to obtain the performance parameters.

4. The method for designing and fabricating a Faraday rotator according to claim 2, characterized in that, S13, performing comprehensive evaluation and iterative screening on the simulation evaluation results to obtain the target component, including: S131. Perform a comprehensive evaluation on the simulation evaluation results to obtain a comprehensive evaluation score; S132. Based on the comprehensive evaluation score, the target components are sorted, and the target components within a preset ranking range are extracted to obtain a candidate group set; S133. Based on the candidate group set, adjust the element ratio range to generate the next round of candidate component set, and substitute the next round of candidate component set into step S12 for iterative iteration until the comprehensive evaluation score meets the stopping iteration condition to obtain the target component.

5. The method for designing and fabricating a Faraday rotator according to claim 1, characterized in that, S2, performing phase diagram design and stability analysis on the target component to determine the process window, includes: S21. Perform phase equilibrium calculations on the target component to obtain phase equilibrium data; S22. Based on the phase equilibrium data, perform phase stability screening to obtain a composition window; S23. Perform process window inversion based on the component window to obtain the process window.

6. The method for designing and fabricating a Faraday rotator according to claim 1, characterized in that, S3, based on the process window, uses liquid phase epitaxy to prepare a proton-irradiation-resistant Faraday rotator, including: S31. Based on the process window, generate a set of liquid phase epitaxial parameters; S32. Using the liquid phase epitaxy method, based on the liquid phase epitaxy parameter set, a target magneto-optical epitaxial layer is generated on the substrate material; S33. Post-process the target magneto-optical epitaxial layer to obtain the proton-resistant Faraday rotator.

7. The method for designing and fabricating a Faraday rotator according to claim 1, characterized in that, Also includes: S4. Perform device verification on the proton-resistant Faraday rotator. If the verification result of the proton-resistant Faraday rotator does not meet the verification conditions, execute step S1 and / or step S2 based on the optical sheet parameters in the verification result.

8. A magneto-optical device, characterized in that, Including the proton-resistant Faraday rotator prepared by the Faraday rotator design and preparation method as described in any one of claims 1 to 7.

9. A device for designing and fabricating a Faraday rotator, characterized in that, include: The screening module is used to simulate and evaluate the proton irradiation resistance of candidate materials and iteratively screen to obtain the target components; The analysis module is used to design phase diagrams and perform stability analysis on the target components to determine the process window; The preparation module is used to prepare a proton-resistant Faraday rotator using liquid phase epitaxy based on the process window.

10. An electronic device, characterized in that, Including memory and processor; The memory is used to store computer programs; The processor is configured to implement the Faraday rotator design and fabrication method as described in any one of claims 1 to 7 when executing the computer program.

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