Oled Simulation Software

[Paul]

Withthe rapid development of information age, the information display technology has become an important branch of the information industry. As information carriers, display devices are attracting more and more attention [1]. People have higher requirements with respect to power consumption, volume, softness, and other aspects of display devices. Display devices originated from cathode ray tubes (CRTs). In a CRT, electron flow bombards the screen, so that R, G, and B phosphors give out light in proportion, thus producing different colors. Since the birth of the CRT technology in 1897, CRTs were applied in radar display and electronic oscilloscopes at first, and then they were popularized in TVs and computers, becoming the most mainstream display terminals in the twentieth century [2]. Although CRTs have strong advantages in terms of cost and image quality, their weight, volume, radiation, and energy consumption limit their development. The dominant position of CRTs is gradually replaced by flat panel displays (FPDs). Compared with the traditional CRTs, FPDs have many advantages, such as small size, light weight, and low energy consumption. In recent years, FPDs have developed rapidly. Liquid crystal displays (LCDs) and plasma display panels (PDPs) are the most representative display devices. A pixel in an LCD panel is composed of three LCD units. Each LCD unit contains a red filter, green filter, or blue filter. Different colors can be generated by controlling the light in different units [3]. An LCD is thinner than a CRT, which greatly saves space and avoids the radiation problem. In the aspect of screen refresh rate, a CRT kinescope adopts light-emitting materials. No matter how high the refresh frequency is, it will lead to the flicker problem. Direct imaging technology for LCDs does not cause flicker, so it is more suitable for human eyes. In addition, an LCD is a form of flat screen, and the display effect is much better than that of a CRT. However, LCDs also have some disadvantages in terms of resolution, viewing angle, color saturation, brightness, and reaction speed [4]. A pixel in a PDP is a plasma tube. The plasma gas discharges in the plasma tube, producing ultraviolet light and exciting the phosphor on the fluorescent screen. A PDP is a kind of self-luminous display technology without backlight, which overcomes the problems of visual angle and brightness of LCDs. It is easy to manufacture large-scale screens with excellent performance. However, PDPs have some problems in terms of service life, power consumption, and cost.

Although LCDs, PDPs, and other displays solve the problems of CRTs in terms of volume, weight, radiation, and screen refresh rate, they still need to be improved in the aspects of energy consumption, viewing angle, and brightness. In recent years, LCDs and PDPs have been unable to meet the growing demand for display functionality, especially flexible displays [5].

The uniaxial tensile test and simple shear test were used to determine the hyperelasticity of materials. Dynamic mechanical analysis (DMA) was applied to the uniaxial tensile test. A rotational rheometer was applied in the simple shear test.

The stress and strain formulas of different strain energy density function models under uniaxial tension mode and simple shearing mode are obtained by derivation. The derivation formulas are comparable with experimental data, and the hyperelastic parameter fitting can be achieved [1].

We can see that the simple shear test data are basically consistent with the simple shear fitting result. There is a slight difference between the data of the uniaxial tensile test and the uniaxial tensile fitting results, but they are consistent in the overall trend. On the whole, the fitting effect is very good. After the fitting, relevant parameters of the strain energy density function are obtained. The fitting parameters are shown in Table 3 [12].

Then, the simple shearing experiment is carried out. A 5% instantaneous shear deformation is given to the specimen. It is unchanged, and the change of stress is recorded. The data are normalized using equation (3), and then the data are input into Abaqus for fitting. The result is shown in Figure 2 [14].

where g(t) is the relaxed modulus of elasticity after normalization, t is the relaxation time, N is the number of terms of the Prony series, g i and τ i are the parameters in the model, e is the shear threshold, and i is a constant.

It can be seen that the fitting curve basically coincides with the experimental data curve after the normalization. The fitting quality is very good. After fitting, Prony parameters g i and τ i are obtained (Table 5).

The structure of the OLED bending area is mainly composed of an organic photoresist, metal wiring, and a polyimide (PI) substrate. The metal wiring at the end of the structure is deposited in the organic photoresist. The metal wiring at the end of the bending area is used to transmit and control the electric signal of the light-emitting diodes in the OLED display area. There are huge amounts of metal wires deposited in the organic photoresist [15]. The structure of the bending area is shown in Figure 3.

In order to simplify the OLED bending area, meso-structure information is introduced to characterize the properties of the bending area. The micromechanics of materials are based on the relationship between the macromechanical properties of materials and the microstructure. Therefore, the macroproperties can be achieved by optimizing the design of the microstructure. The structure region at the end of the OLED has obvious periodic characteristics [16]. According to the characterization of the microstructure, the microstructure of the end structure of the OLED can be composed of an organic photoresist, single metal wire, substrate material, and PI substrate. Thus, the 3D model of the bending area is built as shown in Figure 5.

A HyperMesh platform with powerful finite element preprocessing ability is used for the OLED bending area. A hexahedron mesh method is used to divide the metal wires and other areas. This can effectively reduce the number of meshes. On this basis, progressive grid division is adopted to ensure the accuracy of the calculated structure and thus to reduce the calculation time. All units in the model are linear hexahedron elements with complete integration [19].

Generally, the accuracy of grid division directly influences the accuracy of the result. The finer the mesh division is, the more accurate the result is. When the grid is too dense, the computer overhead will increase and the computing time will also increase. For the explicit dynamics, the consumption of computer memory and computing time are directly proportional to the number of grid units. The computing cost increases with the improvement of grid subdivision, so that we can directly predict the cost change caused by grid subdivision. For the implicit dynamics, the computing cost is roughly proportional to the square of the number of freedom degrees. The consumption of memory and computing time will have an exponential relationship with the number of grid units. It is difficult to predict the cost. The change is obvious. On the basis of accuracy, a reasonable grid density can greatly optimize the computing cost. For the structure of the OLED bending area, on the premise of reflecting the structural features of the metal wire, we must refine the grid as much as possible, so that the grid size can ensure the computing accuracy without consuming too much computing resource [20]. Due to the ratio of the length and thickness of the OLED bending area after bending, the number of metal wiring meshes is still huge on the basis of accuracy, consuming too much computer resource. In order to improve the accuracy of calculation and analysis, a sub-model is used to divide the structure of the OLED bending area after bending. There are 26 30 divided finite element grids, as shown in Figure 9.

Refined finite element meshes are used to build the three-dimensional bending simulation finite element model of the OLED bending area. During the finite element simulation, the setting of boundary condition directly influences the success of simulation. This is also an extremely important part of finite element simulation. In the finite element simulation, there are two ways to realize the periodic boundary: (1) coupling corresponding surface nodes. This method has higher requirements for serial number of nodes, but it can reduce constraints and improve calculation accuracy. (2) A penalty function is introduced. The implementation of this method is simple, but it is easy to cause a numerical difference. Therefore, the periodic boundary constraints can be achieved by combining these two methods. The special boundary constraint needs to divide the whole model into two independent models: a global model and a sub-model. The global model includes a geometric constraint, displacement constraint, and boundary constraint. The sub-model is a part of the whole model, so we cannot analyze the global features of the model, such as cracks. In the global model, the displacement corresponding to the sub-model is the boundary condition of the sub-model. Therefore, the grid of the global model is relatively coarse. If the global model corresponds to the sub-model, the calculation results will be more accurate [21].

The basic implementation steps of special boundary constraints in the finite element analysis include the following: global model analysis: the global model is divided with coarse meshes without considering the local structure details, and then the global structure is analyzed to calculate the displacement at a specific location (near the boundary of the sub-model).

boundary condition interpolation value: the displacement boundary of the global model obtained in the first step is taken as the boundary condition. Then, it is automatically loaded to the corresponding position in the sub-model by the linear interpolation method (the displacement interpolation result determines the computing accuracy of the sub-model).

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