Method for calculating and predicting self-recovery mechanoluminescence performance of material based on first principle

Abstract

The invention provides a method for calculating and predicting the self-recovery mechanoluminescence performance of a material based on a first principle. According to the method for calculating and predicting the self-recovery mechanoluminescence performance of the material based on the first principle, a luminescent material and an elastomer material monomer (such as PDMS) serve as objects, an interface model of the luminescent material and the elastomer material monomer (such as PDMS) is firstly constructed, charge density calculation is completed with the help of first principle calculation tools such as CP2K and VASP, then difference operation is conducted on charge density distribution, a difference charge density map is generated, and the self-recovery mechanoluminescence performance of the material is predicted. Then three-dimensional visual analysis is carried out through visual analysis tools such as VESTA and VMD, a result is obtained, and finally a target material meeting a preset screening condition is obtained through result evaluation. According to the method for calculating and predicting the self-restoring force luminescence performance of the material based on the first principle, efficient prediction of the self-restoring force luminescence performance of the material is achieved by combining first principle calculation and visual analysis, and the method has the advantages that complex experimental operation is not needed, the material screening period is greatly shortened, the prediction result is high in accuracy and the like; and an important theoretical support is provided for design and development of the self-recovery mechanoluminescent material.

Description

Technical Field

[0001] This invention relates to the field of predicting the properties of mechanoluminescent materials and first-principles calculations, and particularly to a method for predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations. Background Technology

[0002] Mechanoluminescence refers to the phenomenon where certain materials emit light when subjected to external mechanical stresses such as friction, tension, compression, impact, or vibration. Mechanoluminescence has two unique properties: First, it is excited by external stress, unlike photoluminescence or electroluminescence, it does not require an irradiation source or power supply. Second, the intensity of mechanoluminescence is linearly dependent on the magnitude of the stress, thus it can directly reflect the stress distribution on the material. Due to its unique force-light conversion characteristics, mechanoluminescence has attracted much attention from researchers in recent years and has been widely studied and applied in fields such as sensing, anti-counterfeiting, display, lighting, storage, and smart wearable devices.

[0003] Self-recovering mechanoluminescence refers to the property of mechanoluminescence to recover itself with each stress. With its ability to continuously emit light under cyclic stress, self-recovering mechanoluminescent materials have shown great application potential in wearable devices, visual sensing, encryption and anti-counterfeiting. However, although mechanoluminescence is very common, self-recovering mechanoluminescence is a very rare property of materials. Currently, only a few highly efficient self-recovering mechanoluminescent materials induced by contact electrostatics have been reported. It can be seen that the rarity of self-recovering mechanoluminescent materials is the key to restricting the development and application of mechanoluminescence.

[0004] Currently, there is no effective pre-screening mechanism. The main method is to determine the self-healing mechanoluminescence properties of materials by preparing phosphor / PDMS composite materials and detecting their mechanoluminescence properties. This method is complicated by experimental procedures, has a long material screening cycle, and has low accuracy in prediction results, which seriously affects the development of self-healing mechanoluminescence.

[0005] Therefore, it is necessary to provide a method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations to solve the above-mentioned technical problems. Summary of the Invention

[0006] This invention provides a method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations. This method solves the problems of the current lack of a pre-screening mechanism for self-restoring mechanoluminescence materials, reliance on the preparation of composite materials for performance testing, and the complexity, long cycle, and low accuracy of the operation, which hinders the development of this method.

[0007] To address the aforementioned technical problems, the present invention provides a method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations, comprising the following steps:

[0008] S1: Constructing the interface model of luminescent material-PDMS monomer (or monomers such as polyurethane and natural rubber, taking PDMS as an example here): Based on the crystal structure parameters of the target luminescent material, a typical low-index crystal plane of the luminescent material is selected to construct a surface supercell model; using the polydimethylsiloxane monomer molecular (PDMS) structure model, according to the interface contact state when the luminescent material and PDMS are actually combined, the surface supercell model and the PDMS monomer molecular structure model are geometrically optimized to form a luminescent material-PDMS monomer interface model containing luminescent central atomic sites;

[0009] S2: Based on first principles, the charge density of the luminescent material-PDMS monomer interface model constructed in S1 was calculated using software such as CP2K and VASP. The charge density of the supercell model of the luminescent material surface, the molecular structure model of the PDMS monomer, and the overall model in S1 were calculated separately to keep the calculation parameters consistent.

[0010] S3: Calculate the differential charge density: based on the formula ,in For differential charge density, The overall charge density of the interface model. The charge density of a single luminescent material surface supercell model. The charge density of the individual PDMS monomer molecular structure model is obtained by numerical calculation, and the differential charge density of the interface model is obtained.

[0011] S4: Differential charge density visualization analysis: Import the differential charge density file obtained in S3 into software such as VESTA or VMD, set the isosurface level and color mapping rules, and generate a three-dimensional differential charge density visualization image of the interface model.

[0012] S5: Determination of self-restoring mechanoluminescence performance: In the visualization image of S4, the interface region between the luminescent material and the PDMS monomer exhibits a positive and negative charge separation characteristic. That is, the area around the luminescent central atom on the luminescent material side is a negative charge accumulation area, and the area on the PDMS monomer side is a positive charge accumulation area. When the charge accumulation is greater than a preset threshold, the luminescent material is determined to be suitable for self-restoring mechanoluminescence; otherwise, it is determined to be unsuitable.

[0013] Preferably, the luminescent material in S1 is selected from any one or a combination of all types of luminescent materials, including fluorides, oxides, sulfides, halides, nitrides, phosphates, and silicates. The geometry optimization in S1 includes structural relaxation of the surface supercell model and the PDMS monomer model until the total energy of the system converges to an acceptable level.

[0014] Preferably, the first-principles calculations in S2 employ methods including but not limited to PBE functional methods, Hartree-Fockequation methods, hybrid functional methods, and dispersion-corrected Gaussian group methods. The differential charge density calculations in S3 are performed using numerical difference methods to ensure that each submodel performs charge density subtraction operations within the same mesh density and spatial range.

[0015] Preferably, in S4, the isosurface color mapping uses different color gradients, corresponding to positive and negative charge accumulation and the neutral region, respectively. In S5, the preset threshold setting is not a specific value, but is set independently according to the material composition. For example, the threshold for wide bandgap fluorides is higher than that for low bandgap sulfide materials.

[0016] A method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations, wherein the computer prediction system in the method includes a mounting frame;

[0017] A storage cabinet is fixedly connected to the top of the mounting base. A heat dissipation protection frame is installed inside the storage cabinet. A partition is installed inside the heat dissipation protection frame. A mains power monitoring and switching device, a power consumption adaptation device, and a computer host are installed on the top of the partition. An energy storage structure is installed at the bottom of the inner wall of the heat dissipation protection frame. Thermal conductive substrates are installed on both sides of the heat dissipation protection frame.

[0018] The top and bottom of the heat dissipation protection frame are connected to the top and bottom of the storage cabinet's inner wall via brackets, ensuring a gap between the heat dissipation protection frame and the storage cabinet. The front of the heat dissipation protection frame and the storage cabinet are flush. The mains power monitoring and switching device monitors the voltage stability of the external mains power in real time through a voltage sensor. When a mains power interruption or voltage fluctuation exceeds the safe range (e.g., below 180V or above 250V), the built-in relay switch will complete the switching within 50 milliseconds. The power consumption adapter 10 switches the power source from the mains power to the backup power supply to ensure uninterrupted power supply. The power consumption adapter 10 is designed with multiple voltage output interfaces (12V, 24V, and 220V) to meet the power consumption requirements of different system components, such as the computer host power consumption of approximately 300W, the charge computing unit power consumption of approximately 500W, and the data storage unit power consumption of approximately 100W.

[0019] Preferably, the storage cabinet has a door on the front, an external box on one side, and a display screen on the front of the door.

[0020] Preferably, multiple rows of air inlets are provided on the front of the cabinet door near both sides, and filter components are installed on the front of the cabinet door near both sides, the filter components including filter frames and interception components;

[0021] The filter components and air inlets are positioned correspondingly, the interceptor components can filter dust, and the air inlets and heat dissipation protection frames are positioned correspondingly to the storage cabinet.

[0022] Preferably, a monitoring component is installed on the front of the cabinet door. The monitoring component includes a fixed base and a monitoring part. The fixed base is used to install the monitoring part on the front of the cabinet door.

[0023] Preferably, the mounting base includes a base plate, a mounting structure, and an adjustment structure, wherein the mounting structure is used to mount the adjustment structure to the bottom of the base plate;

[0024] The threaded connection of the mounting and adjusting structure allows for adjustment of the stability of the base plate as needed.

[0025] Preferably, heat dissipation components are installed on the back of the storage cabinet near both sides. The heat dissipation components include a heat dissipation frame and an exhaust component, with the exhaust component installed at the outlet of the heat dissipation frame.

[0026] Compared with related technologies, the method for predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations provided by this invention has the following beneficial effects:

[0027] This invention provides a method for predicting the self-restoring mechanoluminescence (SEM) properties of materials based on first-principles calculations. It establishes a standardized "modeling-calculation-visualization-judgment" process through first-principles calculations and interface charge analysis, enabling "virtual screening" of commercially available luminescent materials. This eliminates the need for composite sample preparation, significantly shortening the performance prediction cycle for single materials and reducing labor and material costs. It effectively addresses key issues in the field of SEM, such as the lack of pre-screening mechanisms, complex operations, long cycles, and low prediction accuracy. Furthermore, it focuses on the fundamental mechanism of mechanoluminescence—interfacial electron transitions induced by contact electrification—and establishes judgment indicators based on charge density data, achieving high performance judgment accuracy. The predicted results closely match actual experimental phenomena, avoiding empirical speculation errors. This method also exhibits strong compatibility, covering not only mainstream luminescent materials such as fluorides and oxides but also extending to novel luminescent systems by adjusting calculation parameters, providing a unified tool for predicting the performance of all types of luminescent materials. In addition, this method provides clear direction for performance optimization, accurately locating problems in materials that fail the judgment through visualization, guiding the modification of inert luminescent materials, avoiding the drawbacks of blindly adjusting formulations in traditional R&D, and significantly shortening the material optimization cycle. Attached Figure Description

[0028] Figure 1 A flowchart of a first embodiment of the method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations provided by the present invention;

[0029] Figure 2This is a schematic diagram of a second embodiment of the method for predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations provided by the present invention.

[0030] Figure 3 A schematic diagram of the installation structure is provided for this invention;

[0031] Figure 4 A schematic diagram of the heat dissipation component is provided for this invention;

[0032] Figure 5 Provided for the present invention Figure 3 An enlarged view of point A shown;

[0033] Figure 6 Provided for the present invention Figure 4 A magnified view of point B shown.

[0034] The diagram is labeled as follows: 1. Mounting frame, 101. Base plate, 102. Mounting structure, 103. Adjustment structure, 2. Storage cabinet, 3. External box, 4. Display screen, 5. Monitoring components, 501. Fixed base, 502. Monitoring components, 6. Cabinet door, 7. Filtering components, 701. Filter frame, 702. Interception components, 8. Air inlet, 9. Mains power monitoring and switching equipment, 10. Power consumption adaptation equipment, 11. Heat dissipation protection frame, 12. Heat dissipation components, 121. Heat dissipation frame, 122. Exhaust components, 13. Computer host, 14. Thermal conductive substrate, 15. Partition, 16. Energy storage structure. Detailed Implementation

[0035] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0036] First Embodiment

[0037] Please refer to the following: Figure 1 ,in, Figure 1 This is a flowchart of a first embodiment of the method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations provided by the present invention. The method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations includes the following steps:

[0038] S1: Constructing the interface model of luminescent material-PDMS monomer (or monomers such as polyurethane and natural rubber, taking PDMS as an example here): Based on the crystal structure parameters of the target luminescent material, a typical low-index crystal plane of the luminescent material is selected to construct a surface supercell model; using the polydimethylsiloxane monomer molecular (PDMS) structure model, according to the interface contact state when the luminescent material and PDMS are actually combined, the surface supercell model and the PDMS monomer molecular structure model are geometrically optimized to form a luminescent material-PDMS monomer interface model containing luminescent central atomic sites;

[0039] S2: Based on first principles, the charge density of the luminescent material-PDMS monomer interface model constructed in S1 was calculated using software such as CP2K and VASP. The charge density of the supercell model of the luminescent material surface, the molecular structure model of the PDMS monomer, and the overall model in S1 were calculated separately to keep the calculation parameters consistent.

[0040] S3: Calculate the differential charge density: based on the formula ,in For differential charge density, The overall charge density of the interface model. The charge density of a single luminescent material surface supercell model. The charge density of the individual PDMS monomer molecular structure model is obtained by numerical calculation, and the differential charge density of the interface model is obtained.

[0041] S4: Differential charge density visualization analysis: Import the differential charge density file obtained in S3 into software such as VESTA or VMD, set the isosurface level and color mapping rules, and generate a three-dimensional differential charge density visualization image of the interface model.

[0042] S5: Self-recovering mechanoluminescence performance determination: In the visualization image of S4, the interface region between the luminescent material and the PDMS monomer exhibits a positive and negative charge separation characteristic, that is, the area around the luminescent central atom on the luminescent material side is a negative charge accumulation area, and the PDMS monomer side is a positive charge accumulation area. When the charge accumulation is greater than a preset threshold, the luminescent material is determined to be suitable for self-recovering mechanoluminescence; otherwise, it is determined to be unsuitable.

[0043] This method addresses the key issues in the field of self-restoring mechanoluminescence (SLM) where there is no effective pre-screening mechanism. The current method primarily relies on preparing phosphor / PDMS composites and testing their mechanoluminescence properties to determine the SLM performance, which involves complex experimental procedures, long material screening cycles, and low prediction accuracy. This new method is applicable to any interface formed by a luminescent material and PDMS, offering broad applicability and enabling the prediction of SLM performance. This improves the efficiency of SLM research and development. The first-principles calculation method for predicting SLM performance is suitable for predicting the interfacial charge transfer behavior between luminescent materials and flexible substrates such as PDMS, polyurethane, and natural rubber. It can also guide the screening and performance optimization of SLM materials. Without experimental synthesis and performance testing, rapid prediction and evaluation of SLM performance can be achieved solely through computational simulation.

[0044] S1 includes: S1.1 After obtaining the structure of each material, perform full relaxation on each material. Full relaxation is calculated based on methods including but not limited to the exchange correlation function of the generalized gradient approximation; S1.2 Based on the principles of low-exponential surface stability and low-surface-energy surface stability, cut a section from each relaxed material. Since different materials have different lattice constants, there is lattice mismatch after the section. Therefore, cell expansion and changing the lattice vector are used to reduce the mismatch; S1.3 The vacuum layer can be used to isolate the interaction between adjacent atoms. A vacuum layer that is too thick will increase the calculation time, while a vacuum layer that is too thin is insufficient to isolate the interaction between atoms. Therefore, a vacuum layer with a thickness of 1 mm is required. The vacuum layer thickness is tested, and the static energy is calculated using interface test models with different vacuum layer thicknesses. The static energy converges during the vacuum layer thickness test, and the corresponding vacuum layer thickness is considered the optimal vacuum layer thickness. S1.4 After determining the vacuum layer thickness, different interface distances are used to find the energy minimum point; the corresponding interface distance is the optimal interface distance. S1.5 Based on the relaxed surface model, the surface energy is calculated using the first-principles calculation method of density functional theory. Atomic relaxation and self-consistent calculation are performed, and a suitable energy convergence criterion is set. The atomic convergence criterion is set to indicate that the lower the surface energy, the more stable the surface.

[0045] The luminescent material in S1 is selected from any one or a combination of all types of luminescent materials including fluorides, oxides, sulfides, halides, nitrides, phosphates, and silicates. The geometry optimization in S1 includes structural relaxation of the surface supercell model and the PDMS monomer model until the total energy of the system converges to an acceptable level.

[0046] The first-principles calculations in S2 employ methods including, but not limited to, the PBE functional method, the Hartree-Fockequation method, the hybrid functional method, and the dispersion-corrected Gaussian group method. The differential charge density calculations in S3 are performed through numerical difference to ensure that each submodel performs charge density subtraction operations within the same mesh density and spatial range.

[0047] In S4, the isosurface color mapping uses different color gradients, corresponding to positive and negative charge accumulation and neutral regions, respectively. In S5, the preset threshold setting is not a specific value, but is set independently according to the material composition. For example, the threshold for wide bandgap fluorides is higher than that for low bandgap sulfide materials.

[0048] The working principle of the method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations provided by this invention is as follows:

[0049] First, a luminescent material-PDMS monomer interface model was constructed. Based on the crystal structure parameters of the target luminescent material, a typical low-index crystal plane was selected to construct a surface supercell model. Simultaneously, a polydimethylsiloxane monomer molecular structure model was used. According to the actual interface contact state during the composite process, the surface supercell model and the PDMS monomer molecular structure model were geometrically optimized to form an interface model containing the luminescent central atomic sites. Then, based on first-principles calculations, the charge density of the constructed interface model was calculated using software such as CP2K and VASP. The charge densities of the individual luminescent material surface supercell model, the individual PDMS monomer molecular structure model, and the overall model were obtained, while maintaining parameter consistency throughout the calculations. Finally, the differential charge density formula ∆ρ=ρ was applied. 总 -ρ 发光材料 -ρ PDMS单体， Where ∆ρ is the differential charge density, ρ_total is the overall charge density of the interface model, ρ_luminescent material is the charge density of the supercell model on the surface of the individual luminescent material, and ρ_luminescent material is the charge density of the supercell model on the surface of the individual luminescent material. PDMS The charge density of the PDMS monomer molecular structure model is obtained by numerical calculation. The differential charge density of the interface model is then obtained by importing the obtained differential charge density file into software such as VESTA or VMD, setting the isosurface level and color mapping rules, and generating a three-dimensional differential charge density visualization image of the interface model. Finally, the self-healing mechanoluminescence performance is judged. If the interface region between the luminescent material and the PDMS monomer in the visualization image shows the separation of positive and negative charges, that is, the area around the luminescent central atom on the luminescent material side is a negative charge accumulation area and the PDMS monomer side is a positive charge accumulation area, and the charge accumulation is greater than a preset threshold, then the luminescent material is judged to be suitable for self-healing mechanoluminescence; otherwise, it is judged to be unsuitable.

[0050] Compared with related technologies, the method for predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations provided by this invention has the following beneficial effects:

[0051] By constructing a standardized process for modeling, calculation, visualization, and judgment through first-principles calculations and interface charge analysis, this method enables virtual screening of commercially viable luminescent materials. It eliminates the need for complex sample preparation, significantly shortening the performance prediction cycle for individual materials and reducing labor and material costs. This effectively addresses key issues in the field of self-restoring mechanoluminescence, such as the lack of pre-screening mechanisms, complex operations, long cycles, and low prediction accuracy. Furthermore, it focuses on the fundamental mechanism of mechanoluminescence—interfacial electron transitions induced by contact electrification—and establishes judgment indicators based on charge density data, achieving high performance judgment accuracy. The predicted results closely match actual experimental phenomena, avoiding empirical speculation errors and exhibiting strong compatibility. It not only covers mainstream luminescent materials such as fluorides and oxides but can also be extended to novel luminescent systems by adjusting calculation parameters, providing a unified tool for predicting the performance of all types of luminescent materials. In addition, this method provides clear direction for performance optimization, accurately locating problems in materials that fail the judgment through visualization, guiding the modification of inert luminescent materials, avoiding the drawbacks of blindly adjusting formulations in traditional R&D, and significantly shortening the material optimization cycle.

[0052] Second Embodiment

[0053] Please refer to the following: Figures 2-3 - Figures 4-5 - Figure 6 , Figure 2 This is a schematic diagram of a second embodiment of the method for predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations provided by the present invention. Figure 3 A schematic diagram of the installation structure is provided for this invention; Figure 4 A schematic diagram of the heat dissipation component is provided for this invention; Figure 5 Provided for the present invention Figure 3 An enlarged view of point A shown; Figure 6 Provided for the present invention Figure 3 The enlarged view at point B shows a method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations provided in the first embodiment of this application. The second embodiment of this application proposes another method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations. The second embodiment is merely a preferred embodiment of the first embodiment, and its implementation will not affect the individual implementation of the first embodiment.

[0054] Specifically, the difference between the method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first principles provided in the second embodiment of this application is that the computer prediction system in the method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first principles includes a mounting base 1.

[0055] Storage cabinet 2 is fixedly connected to the top of mounting base 1. A heat dissipation protection frame 11 is installed inside the storage cabinet 2. A partition 15 is installed inside the heat dissipation protection frame 11. A mains power monitoring and switching device 9, a power consumption adapter 10 and a computer host 13 are installed on the top of the partition 15. An energy storage structure 16 is installed at the bottom of the inner wall of the heat dissipation protection frame 11. Heat-conducting substrates 14 are installed on both sides of the heat dissipation protection frame 11.

[0056] The top and bottom of the heat dissipation protection frame 11 are connected to the top and bottom of the inner wall of the storage cabinet 2 via brackets, ensuring a gap between the heat dissipation protection frame 11 and the storage cabinet 2. The front of the heat dissipation protection frame 11 and the storage cabinet 2 are flush. The mains power monitoring and switching device 9 monitors the voltage stability of the external mains power in real time through a voltage sensor. When a mains power interruption or voltage fluctuation exceeding the safe range (e.g., below 180V or above 250V) is detected, the built-in relay switch will complete the switching within 50 milliseconds. The power consumption adapter 10 switches the power source from the mains power to the backup power supply to ensure uninterrupted power supply. The power consumption adapter 10 is designed to meet the power consumption requirements of different components of the system, such as the computer host which consumes approximately 300W. The charge calculation unit consumes approximately 500W, and the data storage unit consumes approximately 100W. It features multiple voltage output interfaces (12V, 24V, 220V) and provides stable voltage matching to each component via DC-DC-DC-AC conversion circuits, ensuring normal operation of each module even with backup power. The energy storage structure 16 stores electrical energy. The top structure of the mounting base 1 forms a complete computer prediction system. The heat-conducting substrate 14 runs through both sides of the heat dissipation protection frame 11, with welded connections. The heat dissipation protection frame 11 also uses the same heat sink material, utilizing the space between the heat dissipation protection frame 11 and the storage cabinet 2 for heat dissipation, reducing the amount of dust entering the interior of the heat dissipation protection frame 11.

[0057] Please refer to Figure 2 The storage cabinet 2 has a cabinet door 6 installed on its front side, an external box 3 installed on one side of the storage cabinet 2, and a display screen 4 installed on the front of the cabinet door 6.

[0058] The external box 3 has an external connector inside, which facilitates the connection of external data. The display screen 4 is connected to the computer host 13. The display screen 4 can be a touch screen or used with a keyboard and mouse. If a keyboard and mouse are used, a stand needs to be installed.

[0059] Please refer to Figure 2 and Figure 3 The cabinet door 6 has multiple rows of air inlets 8 on the front side near both sides, and filter components 7 are installed on the front side of the cabinet door 6 near both sides. The filter components 7 include filter frames 701 and interception components 702.

[0060] The filter assembly 7 and the air inlet 8 are positioned correspondingly. The interceptor 702 can filter dust. The air inlet 8, the heat dissipation protection frame 11, and the storage cabinet 2 are positioned correspondingly.

[0061] Please refer to Figure 2 and Figure 3 The front of the cabinet door 6 is equipped with a monitoring component 5, which includes a fixed base 501 and a monitoring component 502. The fixed base 501 is used to install the monitoring component 502 on the front of the cabinet door 6.

[0062] The monitoring component 502 can monitor the temperature inside the heat dissipation protection frame 11.

[0063] Please refer to Figure 2 and Figure 3 The mounting base 1 includes a base plate 101, a mounting structure 102, and an adjustment structure 103. The mounting structure 102 is used to mount the adjustment structure 103 to the bottom of the base plate 101.

[0064] The threaded connection between the mounting structure 102 and the adjusting structure 103 allows for adjustment of the stability of the base plate 101 as needed.

[0065] Please refer to Figure 4 and Figure 6 The storage cabinet 2 has heat dissipation components 12 installed on the back near both sides. The heat dissipation components 12 include heat dissipation frames 121 and exhaust components 122. The exhaust components 122 are installed at the outlet of the heat dissipation frames 121.

[0066] The inlet of the heat dissipation frame 121 is connected to the back of the storage cabinet 2, and the connection is interconnected. The exhaust component 122 includes a housing and a cooling fan.

[0067] Compared with related technologies, the method for predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations provided by this invention has the following beneficial effects:

[0068] To ensure the predictive system continues to operate normally after a sudden power outage, an energy storage structure 16 is installed inside the storage cabinet 2 via a heat dissipation protection frame 11. This, along with the mains power monitoring and switching device 9 and the power consumption adapter 10, allows the predictive system to be powered directly from the mains power when available. In the event of a sudden power outage, the mains power monitoring and switching device 9 can quickly switch the power supply mode to the energy storage structure 16, ensuring the predictive system's normal operation. During this process, the heat dissipation component 12 provides suction, working with the filter component 7, air inlet 8, and multiple thermally conductive substrates 14 to expel heat from the inside of the heat dissipation protection frame 11, preventing high internal temperatures. This design ensures the predictive system continues to operate during a sudden power outage, sufficient to complete any unfinished calculations, avoiding computational interruptions and data loss due to power failure, saving time and computing power costs associated with repetitive calculations. Simultaneously, the heat dissipation structure assists in heat dissipation, ensuring the stability of the power supply equipment.

[0069] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations, characterized in that, Includes the following steps: S1: Constructing the interface model of luminescent material-PDMS monomer (or monomers such as polyurethane and natural rubber, taking PDMS as an example here): Based on the crystal structure parameters of the target luminescent material, a typical low-index crystal plane of the luminescent material is selected to construct a surface supercell model; using the polydimethylsiloxane monomer molecular (PDMS) structure model, according to the interface contact state when the luminescent material and PDMS are actually combined, the surface supercell model and the PDMS monomer molecular structure model are geometrically optimized to form a luminescent material-PDMS monomer interface model containing luminescent central atomic sites; S2: Based on first principles, the charge density of the luminescent material-PDMS monomer interface model constructed in S1 was calculated using software such as CP2K and VASP. The charge density of the supercell model of the luminescent material surface, the molecular structure model of the PDMS monomer, and the overall model in S1 were calculated separately to keep the calculation parameters consistent. S3: Calculate the differential charge density: based on the formula ,in For differential charge density, The overall charge density of the interface model. The charge density of a single luminescent material surface supercell model. The charge density of the individual PDMS monomer molecular structure model is obtained by numerical calculation, and the differential charge density of the interface model is obtained. S4: Differential charge density visualization analysis: Import the differential charge density file obtained in S3 into software such as VESTA or VMD, set the isosurface level and color mapping rules, and generate a three-dimensional differential charge density visualization image of the interface model. S5: Determination of self-restoring mechanoluminescence performance: In the visualization image of S4, the interface region between the luminescent material and the PDMS monomer exhibits a positive and negative charge separation characteristic. That is, the area around the luminescent central atom on the luminescent material side is a negative charge accumulation area, and the area on the PDMS monomer side is a positive charge accumulation area. When the charge accumulation is greater than a preset threshold, the luminescent material is determined to be suitable for self-restoring mechanoluminescence; otherwise, it is determined to be unsuitable.

2. The method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations according to claim 1, characterized in that, The luminescent material in S1 includes, but is not limited to, any one or a combination of all types of luminescent materials such as fluorides, oxides, sulfides, halides, nitrides, phosphates, and silicates. The geometry optimization in S1 includes structural relaxation of the surface supercell model and the PDMS monomer model until the total energy of the system converges to an acceptable level.

3. The method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations according to claim 1, characterized in that, The first-principles calculations in S2 employ methods including, but not limited to, the PBE functional method, the Hartree-Fockequation method, the hybrid functional method, and the dispersion-corrected Gaussian group method. The differential charge density calculations in S3 are performed through numerical difference to ensure that each submodel performs charge density subtraction operations within the same mesh density and spatial range.

4. The method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations according to claim 1, characterized in that, In S4, the isosurface color mapping uses different color gradients, corresponding to positive and negative charge accumulation and the neutral region, respectively. In S5, the preset threshold setting is not a specific value, but is set independently according to the material composition. For example, the threshold for wide bandgap fluorides is higher than that for low bandgap sulfide materials.

5. The method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations according to claim 1, characterized in that, The method described herein is applicable to predicting the interfacial charge transfer behavior between luminescent materials and flexible substrates (such as PDMS, polyurethane, natural rubber, etc.), and can be used to guide the screening and performance optimization of self-healing mechanoluminescent materials.

6. The method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations according to claim 1, characterized in that, The method described above can achieve rapid prediction and evaluation of the self-restoring mechanoluminescence properties of materials based solely on computational simulation without experimental synthesis and performance testing.

7. A method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations, characterized in that, The computer prediction system in the method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations includes a mounting frame; A storage cabinet is fixedly connected to the top of the mounting base. A heat dissipation protection frame is installed inside the storage cabinet. A partition is installed inside the heat dissipation protection frame. A mains power monitoring and switching device, a power consumption adaptation device, and a computer host are installed on the top of the partition. An energy storage structure is installed at the bottom of the inner wall of the heat dissipation protection frame. Thermal conductive substrates are installed on both sides of the heat dissipation protection frame.

8. The method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations according to claim 7, characterized in that, The storage cabinet has a door on the front, an external box on one side, and a display screen on the front of the door.

9. The method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations according to claim 8, characterized in that, Multiple rows of air inlets are provided on the front of the cabinet door near both sides. Filter assemblies are installed on the front of the cabinet door near both sides. Each filter assembly includes a filter frame and an interception component. A monitoring assembly is installed on the front of the cabinet door. The monitoring assembly includes a fixed base and a monitoring component. The fixed base is used to install the monitoring component on the front of the cabinet door.

10. The method for calculating and predicting the self-restoring mechanoluminescence properties of materials based on first-principles calculations according to claim 7, characterized in that, The mounting base includes a base plate, a mounting structure, and an adjustment structure. The mounting structure is used to install the adjustment structure at the bottom of the base plate. Heat dissipation components are installed on both sides of the back of the storage cabinet. The heat dissipation components include a heat dissipation frame and an exhaust component. The exhaust component is installed at the outlet of the heat dissipation frame.

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