Method, apparatus, system and storage medium for halo area recognition measurement of alignment film

Abstract

This application relates to a method, device, system, and storage medium for identifying and measuring the Halo region of an alignment film. The method includes: calibrating a blank substrate and establishing a layered optical model in a uniform region of the alignment film to determine optical constants; locating the physical edge of the alignment film using an auxiliary vision system, and using this as a starting point to control a displacement platform and a spectroscopic ellipsometry for high-density dot matrix scanning, acquiring ellipsometric spectral data at each point; fitting the film thickness at each point using the optical model, and generating a two-dimensional film thickness distribution map based on spatial coordinates; selecting a uniform region from the distribution map to calculate a reference film thickness, automatically identifying and marking continuous regions where the film thickness deviates from the threshold as Halo regions; and extracting the maximum width, extreme film thickness, area, and thickness gradient of the Halo regions. This achieves non-contact, non-destructive, high spatial resolution measurement and quantitative characterization of the Halo region of an inkjet-printed alignment film. This application also provides corresponding measurement equipment, systems, and storage media.

Description

Technical Field

[0001] This application relates to the field of display technology, and in particular to a method, device, system, and storage medium for identifying and measuring the Halo region of an alignment film. Background Technology

[0002] With the rapid advancement of high-generation thin-film transistor liquid crystal display (TFT-LCD) production towards narrow bezel and bezel-less designs, inkjet printing technology has become a core process for liquid crystal alignment film preparation due to its advantages such as high material utilization and good patterning accuracy. However, this process faces an inherent challenge in the panel edge area: during the leveling and curing process of PI droplets, due to the combined effects of Marangoni convection, differences in solvent evaporation rates, and substrate wettability, a non-uniform film thickness transition region is formed at the edge, commonly referred to in the industry as the "Halo region." In this region, the film thickness exhibits a drastic and continuous gradient change from the substrate edge to the display center, showing a distribution characteristic of first rapidly decreasing and then slowly increasing to a stable value. If this gradient is out of control, it will directly cause defects such as uneven brightness (Mura) and color shift in the surrounding display, severely restricting the yield and performance improvement of high-end products.

[0003] Optimizing inkjet printing processes and eliminating defects in the Halo region hinges on accurate morphological characterization of this area, particularly obtaining continuous, high-resolution film thickness distribution data to quantify key parameters such as boundary width, extreme thickness, and gradient variation. However, existing mainstream inspection methods in the industry all have technical limitations when dealing with the Halo region, a specific object with continuous film thickness gradients and complex patterned substrates.

[0004] Contact profilometers are commonly used tools for film thickness measurement, but their measurement principle requires a probe to physically scan a pre-fabricated step structure on the sample surface. This method not only damages the flexible PI film layer but is also susceptible to topographic interference from metal traces and insulating steps at the frame, leading to probe inaccuracies. More importantly, it can only provide discrete "point" or "line" data, failing to reflect the in-plane two-dimensional distribution of the Halo region. Furthermore, the measurement results depend on the scribing position, exhibiting poor repeatability and limited guidance for process optimization.

[0005] While scanning electron microscopy (SEM) can provide high-resolution cross-sectional images, its sample preparation process requires cutting the sample, which is destructive and time-consuming. This method can only acquire discrete information of local areas, making it difficult to efficiently and comprehensively extend to large-area morphological analysis of the Halo region, and the repeatability of the results is greatly affected by the quality of sample preparation.

[0006] Other non-contact optical methods also have their own inherent drawbacks. For example, although white light interferometers can perform three-dimensional topography measurements, when dealing with steep micron-level gradients in transparent thin films (such as PI films), their signals are easily interfered with by multiple reflections from the upper and lower surfaces of the film, and they are sensitive to background noise on patterned substrates (such as ITO and metal wires), resulting in a decrease in measurement accuracy and reliability in critical areas.

[0007] In summary, existing technologies have failed to systematically solve the comprehensive challenge of achieving high-precision, high-resolution, non-destructive, and automated two-dimensional surface distribution measurement in the Halo region of a substrate with continuous film thickness gradients and complex patterned substrates. Therefore, developing a dedicated method and system for quantitative identification and film thickness distribution measurement of the Halo region of the alignment film at the edge of a display panel has become an urgent technical problem to be solved in this field. Summary of the Invention

[0008] This application provides a systematic measurement solution for the Halo region of inkjet-printed alignment films. It acquires continuous, high spatial resolution two-dimensional film thickness distribution data in this region in a non-contact, non-destructive manner, accurately defining the boundaries of the Halo region and quantifying its width, film thickness extrema, and gradient variation, thereby overcoming the shortcomings of existing technologies in terms of destructiveness, terrain adaptability, and ability to acquire surface distribution information. The purpose of this application is achieved through the following technical solution: The alignment film Halo region identification and measurement method of this application includes the following steps: S1 provides a display panel sample containing an alignment film, performs optical constant calibration on a blank substrate without an alignment film, and obtains the optical parameters of the substrate material; establishes a layered optical model including an environmental layer, an alignment film, and a substrate, and decouples the film thickness and optical constants of the alignment film through a Cauchy dispersion model to accurately determine the refractive index n and extinction coefficient k of the alignment film within the measurement spectral range. S2 fixes the sample on the sample stage and uses an auxiliary vision system to locate the physical edge of the alignment film. Starting from the physical edge, a scanning path is set perpendicular to the physical edge and extends into the alignment film. The displacement platform and a spectroscopic ellipsometry are controlled to perform a dot matrix scan of the target area, collecting elliptic polarization spectral data for each measurement point. The step size of the dot matrix scan is no greater than the minor axis diameter of the measurement spot to ensure that there are no blind spots in the sampling. The sample is fixed to the precise position on the sample stage, and the physical edge of the alignment film is located using the auxiliary vision system. The auxiliary vision system adopts a dark-field microscopy imaging mode, illuminating the edge of the alignment film with oblique incident light. The scattered light from the edge of the transparent PI film layer enhances the imaging contrast. Combined with a sub-pixel-level edge extraction algorithm, the precise positioning of the physical edge of the alignment film coating is achieved, with a positioning accuracy of no less than ±5μm. This visual positioning method can overcome the randomness of human eye positioning and ensure the accuracy and repeatability of the scanning starting point. S3 uses the layered optical model established in step S1 to obtain the alignment film thickness at all points, integrates the spatial coordinates of all measurement points with the corresponding film thickness data, and generates a two-dimensional film thickness distribution map. S4 From the two-dimensional film thickness distribution map, select an internal film thickness uniform region at a certain distance from the physical edge, calculate its average film thickness value, and use it as the reference film thickness. Set the relative thickness deviation threshold to ±10% of the reference film thickness. Automatically identify continuous regions where the film thickness value continuously exceeds the threshold range as Halo regions and mark their boundaries. Wherein, "continuously exceeding" means that the film thickness value of 3 or more consecutive measurement points exceeds the threshold range, and single-point noise data is removed. S5 Based on the defined Halo region, its characteristic parameters are quantitatively extracted. The parameters include: the maximum width of the Halo region along the direction perpendicular to the edge, the minimum and maximum film thickness values ​​within the Halo region, the area of ​​the Halo region, and the film thickness variation gradient from the edge to the interior.

[0009] In one embodiment, the scanning path in step S2 is an array of straight lines or curves that starts from the edge and extends inward, and the scanning range covers an area from the edge to 200 mm.

[0010] In one embodiment, in step S2, the dot density is determined by the measurement spot size and the scanning step size, wherein the minor axis diameter of the measurement spot is in the range of 60-120μm, the major axis diameter is in the range of 200-250μm, and the scanning step size is not greater than the spot diameter.

[0011] In one embodiment, in step S4, when selecting an internal uniform region, the distance between the region and the physical edge should not be less than the expected maximum width of the Halo region to be measured, and should be at least 2 mm; the relative thickness deviation threshold is set to ±10% of the reference film thickness.

[0012] In one embodiment, in step S2, the spectral acquisition can be performed using a single fixed incident angle or a multi-incident angle measurement mode; when using the multi-incident angle mode, elliptic polarization spectral data are acquired sequentially at each measurement point with at least two different incident angles to improve the fitting accuracy.

[0013] In one embodiment, the two-dimensional film thickness distribution map generated in step S3 is represented as one or more combinations of a two-dimensional mapping map, a contour map, or a three-dimensional topography map.

[0014] In one embodiment, the maximum width of the Halo region extracted in step S5 refers to the maximum straight-line distance within the Halo region, along a direction perpendicular to the physical edge of the alignment film, from the physical edge to where the film thickness is restored to 90% of the reference film thickness.

[0015] This application also provides an alignment film Halo region identification and measurement device, comprising: a memory; a processor; wherein the memory stores computer execution instructions; and the processor executes the computer execution instructions stored in the memory to implement the aforementioned alignment film Halo region identification and measurement method.

[0016] This application also provides an alignment film Halo region identification and measurement system, which is based on the above-described alignment film Halo region identification and measurement method, or includes the aforementioned alignment film Halo region identification and measurement equipment.

[0017] This application further provides a computer storage medium storing computer execution instructions, which, when executed by a processor, are used to implement the aforementioned alignment film Halo region identification and measurement method.

[0018] Compared with the prior art, this application has the following beneficial effects: This application achieves precise determination of the optical constants of the alignment film by calibrating the optical constants of a blank substrate and establishing a layered optical model including the environmental layer, alignment film, and substrate in a region with uniform film thickness. The spectroscopic ellipsometry, as a high-precision optical measurement instrument, enables non-contact, non-destructive testing of nanoscale film thickness. It overcomes the shortcomings of existing profilometers, such as damage to the flexible PI film layer due to physical scanning of the probe, and the fact that they can only provide discrete point-line data. It also avoids the problem of single-point ellipsometers, which rely on manual point selection and cannot distinguish micrometer-level gradient changes. This represents a dimensional upgrade in Halo region film thickness measurement from "point measurement" to "surface characterization."

[0019] This application calculates the baseline film thickness by selecting a uniform internal region outside the physical edge from a two-dimensional film thickness distribution map. A relative thickness deviation threshold is set, and continuous regions where the film thickness value consistently deviates beyond the threshold are automatically identified as Halo regions and their boundaries are marked. This automatic definition method, based on objective thickness data and preset criteria, overcomes the limitations of traditional image analysis methods that rely on image contrast and human experience, making it difficult to accurately quantify Halo region boundaries. It also exhibits good adaptability to different substrate types. Based on the defined Halo regions, this application quantitatively extracts feature parameters such as maximum width, minimum film thickness, maximum film thickness, area, and film thickness variation gradient, providing a quantitative basis for process optimization.

[0020] This application integrates the method into automated equipment and systems to achieve high efficiency and repeatability of Halo zone identification and measurement, realize real-time monitoring of process stability, trace abnormal data back to batch fluctuations in PI raw material viscosity, and avoid batch defects. The method of this application can meet the needs of online detection and statistical process control in large-scale industrial production. Attached Figure Description

[0021] Figure 1 This is a flowchart of a method for identifying and measuring the Halo region of an alignment film in one embodiment of this application; Figure 2 This is a transverse thickness distribution diagram of a film in one embodiment of this application; Figure 3 This is a two-dimensional distribution map of film thickness in another embodiment of this application. Detailed Implementation

[0022] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the specific embodiments of this application will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, it should be noted that, for ease of description, only the parts relevant to this application are shown in the accompanying drawings, not the entire structure. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this application.

[0023] The terms “comprising” and “having”, and any variations thereof, used in this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0024] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0025] The core drawback of existing technologies for measuring film thickness in the Halo region is the fundamental mismatch between the measurement principle employed and the physical characteristics of the object being measured. The Halo region is essentially a spatially continuous, gradually varying area of ​​film thickness. Current mainstream methods, whether mechanical contact profilometers or cross-sectional destruction-based electron microscopy, are designed to obtain the absolute thickness values ​​at one or more discrete points. This "point-to-surface" measurement logic inevitably leads to significant information loss when dealing with continuous gradient changes, failing to depict the complete thickness distribution morphology. This is the primary drawback caused by the mismatch between the measurement dimension and the problem dimension.

[0026] Further deduction reveals that this mismatch also manifests in signal anti-interference capabilities. Due to the complex structures beneath the Halo region, such as metal traces and insulating steps, strong optical and topographic background noise is generated. In existing technologies, whether it's a profilometer relying on mechanical probe height sensing or an optical method relying on reflected light intensity or interference color analysis, the acquired signals are easily contaminated or even overwhelmed by this complex background noise. The profilometer probe may become inaccurate at the steps, while optical methods struggle to distinguish between mixed signals from the upper thin film and the lower background, leading to a sharp drop in measurement accuracy or even failure in critical areas. Therefore, existing technologies inherently exhibit vulnerabilities in reliability and accuracy when facing real-world, complex application scenarios.

[0027] To address the shortcomings of causal chain-based methods, the objective of this application becomes clear. Firstly, to overcome the limitation of discrete point measurements in characterizing continuous distributions, one objective of this application is to establish an automated, high-density sequential point scanning measurement method. This is not simply about increasing the number of measurement points, but rather about systematically transforming the single-point analysis capability of an elliptic polarization spectrometer into the ability to continuously acquire and correlate data along a specific path by integrating precise displacement control and a dedicated scanning strategy. This allows for the direct acquisition of a complete curve of film thickness variation with spatial location, achieving a dimensional upgrade from "point data" to "line distribution" and then to "surface characterization."

[0028] Secondly, to address the interference from complex backgrounds, the core objective of this application focuses on leveraging and enhancing the unique advantages of ellipsometric spectroscopy. Elliptic polarization measures the spectral changes in polarization states, rather than simply light intensity. This principle makes it extremely sensitive to thin film interface characteristics while being relatively insensitive to the non-uniformity of the bulk material background. More importantly, this application aims to construct an adapted layered optical model to actively strip away and subtract the contributions of known underlying structures during the data analysis phase. This allows for the precise extraction of thickness information belonging solely to the PI film layer from complex signals, improving the robustness and accuracy of the measurement method in real industrial environments.

[0029] Ultimately, addressing the destructive or contact limitations prevalent in existing methods, one of the fundamental objectives of this application is to establish and implement a completely non-contact, non-destructive optical measurement standard procedure. The entire method relies solely on the interaction between light and matter, ensuring no physical damage to the fragile PI film and delicate circuit structures. This enables the technology to be applied across the entire process from R&D and process debugging to online quality monitoring, achieving repeated, non-destructive observation of the same area and providing a truly reliable and traceable data foundation for process optimization.

[0030] To address the aforementioned technical problems, this application provides a method, device, system, and storage medium for identifying and measuring the Halo region of an alignment film. The core concept of this application is: using a spectroscopic ellipsometry as the basic measurement tool, establishing a layered optical model adapted to the structure of the sample under test, and combining an automated high-density dot matrix scanning strategy to obtain high spatial resolution film thickness data of the target region, and then automatically defining the boundary of the Halo region based on a preset thickness deviation threshold, and quantifying its width, film thickness extreme values, area, and gradient of change, among other key characteristic parameters.

[0031] Please see Figure 1 Specifically, the method of this application includes the following main steps: First, the blank substrate is calibrated, and a layered optical model including the environmental layer, the alignment film, and the substrate is established in a region with uniform alignment film thickness. The optical constants of each layer are determined (S1). The film thickness and optical constants of the alignment film are decoupled using the Cauchy dispersion model to accurately determine the refractive index n and extinction coefficient k of the alignment film within the measurement spectral range. Second, the sample is fixed on the sample stage, and the physical edge of the alignment film is located using an auxiliary vision system. The scanning path is set from this point, and the displacement platform is controlled to drive a spectroscopic ellipsometry to perform automated high-density dot matrix scanning of the target area, collecting ellipsometry data at each measurement point. The step size of the dot matrix scanning is no greater than the minor axis diameter of the measurement spot to ensure that there are no blind spots in the sampling (S2). Then, the spectral data of all measurement points are fitted using the established optical model to calculate the alignment film thickness corresponding to each point, and a two-dimensional film thickness distribution map is generated by combining the spatial coordinates (S3). Subsequently, using the reference film thickness, a relative thickness deviation threshold is set to ±10% of the reference film thickness. Continuous regions where the film thickness value consistently exceeds the threshold range are automatically identified as Halo regions, and their boundaries are marked. "Constantly exceeding" refers to film thickness values ​​at three or more consecutive measurement points exceeding the threshold range, and single-point noise data is discarded (S4). Finally, based on the defined Halo regions, feature parameters such as maximum width, minimum / maximum film thickness, area, and film thickness variation gradient are automatically extracted (S5). Through the above method, this application can achieve non-contact, non-destructive, and high spatial resolution measurement of the Halo region of inkjet-printed alignment films, obtaining comprehensive two-dimensional film thickness distribution information and quantitative feature parameters.

[0032] First, before performing measurements, this application provides a foundation for subsequent precise measurements through step S1. The core of this step lies in establishing an optical model that can accurately reflect the physical structure of the sample, which is a prerequisite for data inversion in elliptic polarization measurement technology. Specifically, for display panel samples containing alignment films, the film structure varies depending on the substrate type. For example, when the substrate is blank glass without a pattern, a two-layer optical model of "PI film / glass substrate" can be established; when the substrate is glass coated with an ITO conductive film, a three-layer optical model of "PI film / ITO / glass substrate" needs to be established. This step first measures the blank substrate without an alignment film to independently calibrate the optical constants (refractive index n and extinction coefficient k) of the substrate material (such as glass, ITO film), avoiding coupling between substrate parameters and film parameters in subsequent fitting. Subsequently, single-point measurements are performed in a region of uniform film thickness on the sample. Based on the known substrate parameters, the layered model containing the alignment film is fitted to determine the optical constants of the polyimide (PI) alignment film. For PI films and glass substrates, the Cauchy model can be used to describe their optical dispersion relationship; for ITO layers, the instrument's built-in ITO model can be used for fitting. Through this step, an accurate optical model for a specific sample structure is established, providing an accurate physical basis for inverting the film thickness from the spectral data in step S3, effectively overcoming measurement errors introduced by unknown substrate optical properties or uncertain film optical constants.

[0033] Step S2 describes the specific implementation of the data acquisition process. High-density spectral data covering the Halo region is acquired through automated, high-precision spatial positioning and scanning. First, the sample is fixed at a precise position on the sample stage, and the physical edge of the alignment film is located using an auxiliary vision system. This visual positioning method overcomes the randomness of human eye positioning, ensuring the accuracy and repeatability of the scanning starting point. Subsequently, a scanning path extending into the film layer is set, starting from this physical edge. The scanning path can be set to cover a rectangular area extending from the edge inwards (e.g., 20mm × 10mm or 15mm × 5mm), and the scanning range can cover an area from the edge to 200mm as needed to adapt to the measurement requirements of different sized panels or Halo regions of different widths. During the scanning process, a spectral ellipsometer is controlled by a precise displacement platform to perform automated dot matrix scanning of the target area. The dot matrix density of the scan is determined by the measurement spot size and the scanning step size. In this application, the measurement spot used has an elliptical shape, with a minor axis diameter ranging from 60 to 120 μm and a major axis diameter ranging from 200 to 250 μm (e.g., a minor axis of 100 μm and a major axis of 236 μm). The scanning step size is set to be no greater than the spot diameter (e.g., 100 μm) to ensure overlap in the coverage areas of adjacent measurement points, achieving high-resolution sampling of continuously varying film thickness without gaps. During spectral acquisition, a single fixed incident angle (e.g., 65°) mode is used, or a multi-incident angle measurement mode can be used. Elliptopolarized spectral data are acquired sequentially at each measurement point with at least two different incident angles to increase the amount of data information and improve the fitting accuracy for complex film structures or thicker films. This step combines the single-point precision measurement capability of the elliptopolarimeter with the accurate spatial positioning capability of the displacement platform, along with reasonable scanning path and step size planning, to achieve measurement from discrete points to continuous spatial distribution.

[0034] Step S3 is a crucial data processing step connecting the raw spectral data with the visualized film thickness distribution. This step first applies the layered optical model established in step S1, adapted to the current sample structure, to fit and calculate the elliptic polarization spectral data of each measurement point acquired in step S2, thereby obtaining the alignment film thickness value corresponding to that spatial point and achieving a quantitative conversion from optical information to physical thickness. Subsequently, by integrating the spatial coordinates of all measurement points (recorded by the displacement platform) with their corresponding film thickness data, a two-dimensional film thickness distribution map is generated using data processing software. This distribution map can take various forms, such as a two-dimensional pseudo-color mapping map, visually representing the spatial variation of film thickness through different colors; a contour map, clearly outlining isohyets; or a three-dimensional topography map, showcasing the undulating characteristics of the Halo region. These graphical representations transform massive, abstract coordinate-thickness data arrays into intuitive and visual information on the spatial distribution of film thickness, making the morphological characteristics of the Halo region readily apparent, providing direct visual evidence and a data foundation for subsequent automatic identification and quantitative analysis. The two-dimensional distribution map generated in this step fully presents the entire Halo region, overcoming the problem of missing information due to "representing the whole area with a point".

[0035] Step S4 achieves objective and automated definition of the Halo region. After obtaining the two-dimensional film thickness distribution map, the method first selects a reference area: an internal region at a certain distance from the physical edge (e.g., not less than 2 mm). This region is considered to be a process-stable region with uniform film thickness. That is, in step S4, when selecting an internal uniform region, the distance between this region and the physical edge should not be less than the expected maximum width of the Halo region to be measured, and should be at least 2 mm. The relative thickness deviation threshold is set to ±10% of the reference film thickness. The average film thickness of all measurement points in this region is calculated as the reference film thickness D_ref. Subsequently, a relative thickness deviation threshold is set, for example, 10% of the reference film thickness D_ref used in the embodiment. The basis for setting this threshold is that film thickness deviation exceeding this range may have a substantial impact on liquid crystal alignment and display uniformity. Next, the algorithm automatically traverses the film thickness data of the entire measurement area, identifies continuous regions whose film thickness values ​​continuously deviate from D_ref and exceed the threshold, and defines them as Halo regions (Halo region), while marking their inner and outer boundaries. This automatic identification and boundary marking process is based entirely on objective film thickness measurement data and preset physical criteria, eliminating the subjectivity of traditional methods that rely on human experience and achieving accurate quantification of the Halo region.

[0036] Step S5 further quantifies the defined Halo region, extracting a series of characteristic parameters to describe its geometric features and film thickness variation patterns. These parameters include: (1) the maximum width of the Halo region along the direction perpendicular to the edge, specifically defined as the farthest distance from the physical edge to where the film thickness recovers to 90% of the reference film thickness D_ref, as described in the embodiments. This parameter directly measures the influence range of the uneven edge region; (2) the minimum and maximum film thickness values ​​within the Halo region, these two extreme parameters reflect the fluctuation range of film thickness within the region; (3) the area of ​​the Halo region, quantifying the overall affected range in two dimensions; and (4) the film thickness variation gradient from the edge to the interior, this parameter describes the severity of film thickness variation. As shown in Examples 1 and 2, by analyzing the film thickness variation curves, the specific variation pattern of film thickness from the edge to the interior—"first rapidly decreasing and then slowly increasing and becoming flat" or "thin at the edge, gradually thickening towards the center"—can be observed. These quantified characteristic parameters transform the morphological characteristics of the Halo region into data indicators that can be analyzed and compared, providing a direct and quantifiable basis for process development and quality management. For example, by comparing the width and thickness range of the Halo region at different curing temperatures, the impact of process parameters can be quantitatively assessed; or the width of the Halo region can be used as an indicator for statistical process control (SPC) to achieve real-time monitoring of the stability of the production line process.

[0037] In some specific implementations, the scanning path described in step S2 can be further configured as a straight line or curved array starting from the physical edge of the alignment film and extending into the interior of the film layer. The selection of the scanning range depends on the expected width of the Halo region to be measured and the process evaluation requirements. For example, in Examples 1 and 2, rectangular scanning areas of 20mm × 10mm and 15mm × 5mm were set for an 8.5-generation glass substrate and a glass substrate coated with an ITO layer, respectively. For panels with different generation lines or different bezel designs, the influence range of the Halo region may vary. Therefore, the upper limit of the scanning range is set to a region from the edge to the interior of 200mm, which is sufficient to cover the non-uniform edge regions in most production scenarios, ensuring the applicability of the measurement method to panels of different sizes and enabling the complete capture of the entire transition morphology from the edge film thickness abrupt change region to the interior film thickness stable region.

[0038] In step S2, the density of the dot matrix scan is determined by the combined size of the measurement spot and the scanning step size. To achieve high lateral spatial resolution, spectroscopic ellipsometrists typically employ micro-spot focusing techniques, such as focusing the spot size to the tens of micrometers. In this application, the measurement spot used has an elliptical shape, with its minor axis diameter set in the range of 60-120 μm and its major axis diameter set in the range of 200-250 μm. For example, a spot with a major axis diameter of 236 μm and a minor axis diameter of 100 μm was used. The scanning step size must be set according to the principle of not exceeding the spot diameter to ensure that the coverage areas of adjacent measurement points overlap, thereby achieving seamless sampling of areas with continuously varying film thickness. The 100 μm step size satisfies this condition. By controlling the scanning step size within the range of the spot size, it is possible to effectively avoid missing minute fluctuations in film thickness due to excessively large sampling intervals, ensuring the spatial continuity and accuracy of the obtained two-dimensional film thickness distribution map.

[0039] In some specific implementations, the internal uniform region used to calculate the reference film thickness in step S4 is defined as a region at least 2 mm away from the physical edge. This distance is selected based on the general understanding of inkjet printing alignment film processes, namely, that the film thickness tends to stabilize after a certain distance from the edge, and the effect of edge effects is negligible. Simultaneously, the relative thickness deviation threshold used to define the Halo region is set to 10% of the reference film thickness D_ref. This threshold setting has a clear physical meaning: when the film thickness deviates from the process target value by more than 10%, this region is considered to potentially have a substantial impact on the uniform alignment of the liquid crystal and must be defined as a Halo region for consideration. If the internal stable film thickness is 118 nm, then the Halo region is defined as a continuous region where the film thickness continuously deviates to below 108 nm or above 133 nm, overcoming the subjectivity and uncertainty of traditional image interpretation methods.

[0040] Furthermore, the spectral acquisition in step S2 can employ either a single fixed incident angle or a multi-incident angle measurement mode. When the structure of the film being measured is relatively simple and the optical constants are known, a single incident angle mode is sufficient for the measurement requirements. However, for multilayer film systems or scenarios requiring improved fitting accuracy, a multi-incident angle mode can be used. In this mode, ellipsometric spectral data are acquired sequentially at each measurement point using at least two different incident angles. By jointly fitting the ellipsometric parameters (Δ, ψ) obtained at different incident angles, the amount of independent data can be increased, effectively decoupling the correlation between film thickness and optical constants, thereby improving the accuracy and reliability of the fitting results. This setting provides the measurement method with flexibility to handle different sample complexities.

[0041] The two-dimensional film thickness distribution map generated in step S3 can be represented by one or more combinations of a two-dimensional pseudo-color mapping map, a contour map, or a three-dimensional topography map. The two-dimensional pseudo-color mapping map visually reflects the spatial distribution of film thickness through color changes, as described in Example 2 below; the contour map clearly outlines isothighting lines, facilitating the observation of film thickness gradient changes; and the three-dimensional topography map can three-dimensionally display the undulating characteristics of the film thickness in the Halo region. These visualization methods transform abstract coordinate-thickness data arrays into intuitive graphical information, not only enabling researchers to quickly grasp the overall morphology of the Halo region but also providing direct visual evidence for subsequent automatic identification and quantitative analysis. The combination of multiple representation forms can comprehensively display measurement results from different dimensions.

[0042] The maximum width of the Halo region extracted in step S5 refers to the maximum straight-line distance within the Halo region, along a direction perpendicular to the physical edge of the alignment film, from the physical edge to where the film thickness is restored to 90% of the reference film thickness. This definition correlates the abstract concept of width with the specific degree of film thickness restoration, providing clear process guidance. For example, in Example 1 below, the maximum width of the Halo region was measured to be 4.2 mm based on this definition. This parameter directly quantifies the influence range of the edge non-uniform region extending into the display interior, and is a key indicator for evaluating the effect of process improvement and determining whether the Halo region intrudes into the effective display area (AA area). As in Example 4, it is used to verify whether the edge reserved space of the narrow bezel design is sufficient.

[0043] On the other hand, this application also provides a Halo region identification and measurement device for alignment films. This device serves as the physical carrier of the aforementioned method, and its hardware architecture includes a memory and a processor. The memory stores computer-executed instructions, which are essentially programmatically encoded versions of the steps described in this application. The processor is communicatively connected to the memory and is responsible for calling and executing these instructions. When the processor runs, its control logic drives connected external hardware, such as a spectroscopic ellipsometry, a high-precision displacement platform, and an auxiliary vision system, to automatically execute the entire process from sample fixing, edge positioning, high-density dot matrix scanning, spectral data acquisition, to film thickness calculation based on a layered optical model, two-dimensional distribution map generation, automatic Halo region identification and boundary marking, and finally, feature parameter extraction. By embedding the method of this application in software form in the device's memory and having it automatically executed by the processor, the measurement process is standardized and automated. This device can be integrated as an independent measurement unit into a research and development laboratory or a production line sampling station. It can automatically measure multiple points on multiple panels every day and use the results for statistical process control (SPC), thereby transforming the method of this application into a technical tool with high repeatability and operability that can be practically applied to industrial production.

[0044] Furthermore, this application also provides a Halo region identification and measurement system for alignment films. This system is a further integration and extension of the aforementioned methods and equipment. Its core lies in the organic combination of the method flow, control hardware, and data processing software to form a fully functional measurement system. Specifically, the system can operate according to the aforementioned alignment film Halo region identification and measurement method of this application, or it can include the aforementioned alignment film Halo region identification and measurement equipment as its core processing unit. At the system architecture level, it typically integrates the following components: a spectroscopic ellipsometry as the core of the measurement, used to perform spectral data acquisition; a high-precision displacement platform that carries the sample and achieves precise positioning, used to drive the sample or measurement probe to move along a preset path; an auxiliary vision system, used to automatically identify the physical edges of the alignment film to ensure the accuracy of the scanning starting point; and a control and data processing unit including a memory and a processor. This unit stores computer execution instructions to implement each step of the method of this application and is responsible for controlling the above hardware to work together, processing the acquired spectral data, executing film thickness calculation and Halo region identification algorithms, and finally outputting measurement results and characteristic parameters. In the fully automated batch inspection application described in Example 5, the system is integrated into the production line sampling station. Through a preset program, multiple panels are automatically sampled daily, measurements are performed at multiple points, and key data such as the width of the generated Halo area are automatically reported to the production management system for drawing SPC control charts, thereby achieving real-time monitoring and early warning of abnormalities in process stability.

[0045] This application further provides a computer-readable storage medium, specifically, the computer-readable storage medium stores computer-executable instructions, which are a complete programmed expression of each step (S1 to S5) of the aforementioned alignment film Halo region identification and measurement method of this application. When the computer-executable instructions are called and executed by the processor, they can control the connected measurement hardware (such as a spectroscopic ellipsometry, displacement platform, and auxiliary vision system) to work together automatically, completing the entire process from sample fixing, edge positioning, high-density dot matrix scanning, spectral data acquisition, to film thickness calculation based on a layered optical model, generation of a two-dimensional film thickness distribution map, automatic Halo region identification and boundary marking, and finally to the quantitative extraction of Halo region feature parameters (maximum width, minimum film thickness value, maximum film thickness value, area, and film thickness variation gradient). This computer-readable storage medium, as the software carrier of the technical solution of this application, stores computer-executable instructions that completely correspond to the aforementioned method claims, constituting the program module architecture necessary to implement the measurement method. By installing or loading the computer-readable storage medium into a general-purpose computer device or a dedicated measuring device, the device can be equipped with the ability to perform the method of this application, thereby enabling automated and standardized measurement and analysis of the Halo region of an inkjet-printed alignment film. The following will further introduce some specific implementation methods to provide a more detailed explanation of the technical solution of this application.

[0046] Example 1: Sample preparation: Take an 8.5-generation glass substrate and apply a conventional polyimide (PI) alignment agent to one corner using inkjet printing. After pre-baking and curing, a PI film is formed. Then, the Halo region at the edge is measured.

[0047] Measurement method: The method and system described in this application were used (equipment: Yiguang Technology ME-Mapping type spectral ellipsometry equipped with an automatic XY platform). After fixing the sample, a rectangular area of ​​20 mm × 10 mm was set with the edge as the starting point. The major axis diameter of the measurement spot was 236 μm, the scanning step size was 100 μm, and a two-dimensional grid scan was performed. The spectral range was 380-1000 nm, and the incident angle was 65°.

[0048] Model Establishment: A two-layer optical model of "PI film / glass substrate" was established. The optical constants of the PI film and the glass substrate were fitted using the cauchy model.

[0049] Results and Analysis: After data processing, a film thickness distribution map was obtained (see attached). Figure 2 The results showed that the film thickness fluctuated between 80 nm and 120 nm in the edge region of the layer. The stable film thickness in the internal uniform region was determined to be 118 nm (±2 nm). The Halo region was automatically defined based on a film thickness deviation of ±10% (i.e., outside the 108-133 nm range). The maximum width of the Halo region was measured to be 4.2 mm, the maximum film thickness within the region was 114.85 nm, and the minimum film thickness was 81.33 nm. The film thickness variation curve showed that from the edge to the interior, the film thickness first decreased rapidly and then increased slowly, eventually leveling off.

[0050] Example 2: Sample preparation: Take a glass substrate coated with ITO, and apply a conventional polyimide (PI) alignment agent to one corner of the substrate using inkjet printing. After pre-baking and curing, a PI film is formed. Then, measure the Halo region at the edge.

[0051] Measurement method: The method and system described in this application were used (equipment: Yiguang Technology ME-Mapping type spectral ellipsometry equipped with an automatic XY platform). After fixing the sample, a rectangular area of ​​15mm × 5mm was set with the edge as the starting point. The major axis diameter of the measurement spot was 236μm, the scanning step size was 100μm, and a two-dimensional grid scan was performed. The spectral range was 380-1000 nm, and the incident angle was 65°.

[0052] Model Establishment: A three-layer optical model consisting of a PI film, an ITO substrate, and a glass substrate was established. The optical constants of the PI film and the glass substrate were fitted using the Cauchy model, while the optical constants of the ITO substrate were fitted using the instrument's built-in ITO model.

[0053] Results and Analysis: Two-dimensional pseudo-color distribution map of film thickness was obtained after data processing (see attached). Figure 3 The results showed that the film thickness fluctuated between 50 nm and 300 nm in the edge region. The stable film thickness in the uniform inner region was determined to be 284 nm (±5 nm). The Halo region was automatically defined based on a film thickness deviation of ±10% (i.e., outside the range of 255.6-315.6 nm). The width of the Halo region was measured to be 6.2 mm, with a maximum film thickness of 255.4 nm and a minimum film thickness of 51.4 nm. The film thickness variation curve showed that the film thickness was thinner at the edges and gradually increased towards the center.

[0054] Example 3: Sample preparation: On panels from the same batch and with the same printing parameters, adjacent areas were selected and subjected to final curing at 230°C and 260°C respectively to prepare two comparison samples.

[0055] Measurement method: The same scanning parameters as in Example 1 were used to measure the same edge positions of the two samples.

[0056] Results and Analysis: Comparison of the two film thickness distribution maps and extracted parameters revealed that the Halo region width of the sample cured at 260°C was 5.2 mm, and the film thickness range (maximum-minimum) was 38.4 nm; while the Halo region width of the sample cured at 230°C was 3.47 mm, and the film thickness range was 33.8 nm. This indicates that higher curing temperatures widen the Halo region and reduce film thickness uniformity. The method described in this application can quantitatively assess the impact of process parameters.

[0057] Example 4: Sample preparation: Take a cut sample of the bezel of a narrow-bezel mobile phone panel, with a sealant dam designed outside the display area AA (Active Area). PI printing should stop inside the sealant dam.

[0058] Measurement method: A high-resolution line scan was performed along the direction perpendicular to the AA frame (the long axis diameter of the measurement spot was 236 μm, and the scanning step size was 50 μm), accurately passing through the edge of the PI film, the Halo region, and the AA frame.

[0059] Results and Analysis: A high-resolution film thickness profile was obtained through measurement. Not only was the width of the Halo region accurately measured to be 2.2 mm, but the actual distance from the "zero point" (physical edge) of the PI film to the design boundary of the AA frame was also found to be 152 μm, which is basically consistent with the designed target value of 150 μm. Simultaneously, the data showed that the film thickness exhibited additional thinning on the sloping terrain near the sealing dam. This provides direct evidence for optimizing the printing path and droplet volume in the border area.

[0060] Example 5: Fully Automated Batch Inspection and Statistical Process Control (SPC) Application Implementation method: The system and method of this application are integrated into the production line sampling inspection station. Five panels are randomly selected daily, and one point is selected on each of the four sides of each panel. The scanning and analysis method of Example 1 is run automatically.

[0061] Results and Analysis: The system automatically generated a Halo zone width report and film thickness distribution map for each point. Halo zone width data for one consecutive month (600 measurement points) were plotted into an SPC control chart (Xbar-R chart). Data analysis showed that the process was statistically under control, with the average Halo zone width remaining stable within the range of (3±0.5) mm. When an anomaly occurred in the data on a certain day (width suddenly increasing to 5 mm), the system issued an alarm, and timely investigation revealed that it was caused by batch-specific fluctuations in the viscosity of the PI raw material, thus preventing batch defects.

[0062] Comparative Example 1 Method: Using the sample from Example 1, a KLA-Tencor P-7 step scale was used to scribble and measure three different line segments in the edge area.

[0063] Results and limitations: Measurement data are highly dependent on the location of the scribing. One line may pass exactly through the thickest point of the film, while another line may miss it.

[0064] Because the PI film is soft, the probe caused visible scratches in some areas, damaging the sample.

[0065] The measured maximum and minimum film thickness values ​​deviated significantly from the results of Example 1 (more than ±10 nm), and the accurate width of the Halo region could not be given; only the length of "unevenness" on a single line could be reported. The inability to obtain two-dimensional distribution information limited its guiding role for process optimization.

[0066] Comparative Example 2: Measurement using a standard single-point / small-area ellipsometer Method: The sample in Example 2 was measured using a commercial ellipsometry that did not integrate an automated two-dimensional platform and only supported single-point measurements.

[0067] Operation: Based on experience, the operator selects areas that "appear uniform" and edge areas that "appear non-uniform" to perform single-point measurements.

[0068] Results and limitations: Because the measurement location depends on manual selection, the measured value is essentially the average film thickness of the area covered by the light spot, and cannot distinguish micron-level gradient changes.

[0069] It is completely impossible to define the boundaries and width of the Halo region; only a rough comparison of the thickness data for the "edge point" and the "center point" can be given, resulting in poor repeatability and reliability.

[0070] As can be seen from the above embodiments, the method of this application can identify and measure the complete morphology (including width, area, film thickness extremes and distribution) of the Halo region of the PI film at the edge of the display panel in a non-destructive, accurate and quantitative manner, and is applicable to various complex substrates and process conditions.

[0071] As described above, this application provides a method, device, system, and storage medium for identifying and measuring the Halo region of an alignment film. Based on a spectroscopic ellipsometry, it establishes a layered optical model adapted to the structure of the sample under test and combines it with an automated high-density dot matrix scanning strategy to obtain high spatial resolution film thickness data of the target region. Then, based on a preset thickness deviation threshold, it automatically defines the boundary of the Halo region and quantifies its width, film thickness extremes, area, and gradient of change, among other key characteristic parameters.

[0072] The method of this application includes the following steps: First, by calibrating a blank substrate and performing single-point measurements in a region with uniform film thickness, a layered optical model including an environmental layer, an alignment film, and a substrate is established, and the optical constants of each layer are determined (S1); Second, the physical edge of the alignment film is located using an auxiliary vision system, and a scanning path is set from this point. The displacement platform and a spectroscopic ellipsometry are controlled to perform high-density dot matrix scanning on the target area, and ellipsometry data of each measurement point is collected (S2); Then, the spectral data of all measurement points are fitted using the established optical model, the film thickness at each point is calculated, and a two-dimensional film thickness distribution map is generated by combining the spatial coordinates (S3); Subsequently, a reference film thickness is calculated from an internal uniform region selected from the distribution map, a relative thickness deviation threshold is set, and a continuous region where the film thickness continuously deviates from the threshold is automatically identified and marked as a Halo region (S4); Finally, based on the defined Halo region, its maximum width, minimum film thickness, maximum film thickness, area, and film thickness variation gradient are quantitatively extracted (S5).

[0073] In addition to the above-described method steps, this application also provides several preferred embodiments. For example, the scanning path can be set as a straight line or curved array starting from the edge and extending inward, and the scanning range can cover an area from the edge to 200 mm to adapt to the measurement needs of panels of different sizes. The density of the dot matrix scanning is determined by the measurement spot size and the scanning step size, wherein the minor axis diameter of the spot can be in the range of 60-120 μm, the major axis diameter can be in the range of 200-250 μm, and the scanning step size is set to be no greater than the spot diameter to ensure high-resolution sampling without intervals in areas where the film thickness changes continuously. Spectral acquisition can adopt a single fixed incident angle or a multi-incident angle mode. The multi-incident angle mode can improve the fitting accuracy of complex film structures by acquiring data at at least two different incident angles at each measurement point. The two-dimensional film thickness distribution map can be represented as one or more combinations of a two-dimensional pseudo-color mapping map, a contour map, or a three-dimensional topography map to intuitively display film thickness distribution information from different dimensions. The selected uniform internal region is at least 2 mm away from the physical edge, and the relative thickness deviation threshold is set to 10% of the reference film thickness to achieve objective and automated definition of the Halo region. The maximum width of the Halo region is specifically defined as the farthest distance from the physical edge to where the film thickness recovers to 90% of the reference film thickness. This parameter directly quantifies the influence range of the edge non-uniform region.

[0074] On the other hand, this application also provides an alignment film Halo region identification and measurement device, which includes a memory and a processor. The memory stores computer execution instructions, which correspond to the programmed code of the above-mentioned method. When the processor executes the instructions, it drives external hardware such as a spectral ellipsometry, a displacement platform and an auxiliary vision system to automatically complete the entire process from measurement control to data analysis, thereby realizing the standardization and automation of the measurement process.

[0075] In addition, this application also provides a Halo region identification and measurement system for alignment films. This system integrates a spectral ellipsometry, a high-precision displacement platform, an auxiliary vision system, and a control and data processing unit including a memory and a processor. It can operate according to the method of this application or include the aforementioned measurement equipment to form an industrial measurement tool that can operate independently and automatically complete the entire process from sample fixing to feature parameter extraction.

[0076] This application further provides a computer-readable storage medium storing computer-executable instructions for implementing the steps of the above-described method. When these instructions are executed by a processor, they can control the measurement hardware to work collaboratively, completing the automated and standardized measurement and analysis of the Halo region of the inkjet-printed alignment film. This storage medium serves as the software carrier of the technical solution of this application, enabling the method of this application to be disseminated, deployed, and applied in the form of a software product.

[0077] By organically combining the aforementioned methods, equipment, systems, and storage media, this application provides a complete, systematic solution specifically designed for the Halo region of inkjet-printed alignment films. This solution enables non-contact, non-destructive, and high spatial resolution measurement of the Halo region, obtaining comprehensive two-dimensional film thickness distribution information and quantitative characteristic parameters. This provides a reliable data foundation for precise control and yield improvement of the edge coating process for display panels, overcoming the limitations of existing technologies in terms of destructiveness, terrain adaptability, measurement efficiency, and the ability to acquire surface distribution data.

[0078] The above is only one specific implementation of this application, and any improvements made based on the concept of this application shall be considered within the scope of protection of this application.

Claims

1. A method for identifying and measuring the Halo region of an alignment film, characterized in that, Includes the following steps: S1 provides a display panel sample containing an alignment film, performs optical constant calibration on a blank substrate without an alignment film, obtains the optical parameters of the substrate material, performs single-point measurement in a uniform film thickness area of ​​the sample, establishes a layered optical model including the environmental layer, alignment film and substrate, decouples the film thickness and optical constant of the alignment film through the Cauchy dispersion model, and accurately determines the refractive index n and extinction coefficient k of the alignment film in the measurement spectrum range; S2 Fix the sample on the sample stage, locate the physical edge of the alignment film using an auxiliary vision system, and set a scanning path perpendicular to the physical edge and extending into the alignment film, starting from the physical edge. Control the displacement platform and the spectroscopic ellipsometry to perform a dot matrix scan on the target area and collect ellipsometry data at each measurement point. The step size of the dot matrix scan is no greater than the minor axis diameter of the measurement spot to ensure that there are no blind spots in the sampling. S3 uses the layered optical model established in step S1 to obtain the alignment film thickness at all points, integrates the spatial coordinates of all measurement points with the corresponding film thickness data, and generates a two-dimensional film thickness distribution map. S4 From the two-dimensional film thickness distribution map, select an internal film thickness uniform region at a certain distance from the physical edge, calculate its average film thickness value, and use it as the reference film thickness. Set the relative thickness deviation threshold to ±10% of the reference film thickness. Automatically identify continuous regions where the film thickness value continuously exceeds the threshold range as Halo regions and mark their boundaries. Wherein, "continuously exceeding" means that the film thickness value of 3 or more consecutive measurement points exceeds the threshold range, and single-point noise data is removed. S5 Based on the defined Halo region, its characteristic parameters are quantitatively extracted. The parameters include: the maximum width of the Halo region along the direction perpendicular to the edge, the minimum and maximum film thickness values ​​within the Halo region, the area of ​​the Halo region, and the film thickness variation gradient from the edge to the interior.

2. The method for identifying and measuring the Halo region of an alignment film according to claim 1, characterized in that, The scanning path in step S2 is a straight line or curved array that starts from the edge and extends inward, and the scanning range covers an area from the edge to 200mm.

3. The method for identifying and measuring the Halo region of an alignment film according to claim 1, characterized in that, In step S2, the dot density is determined by the size of the measurement spot and the scanning step size, wherein the minor axis diameter of the measurement spot is in the range of 60-120μm, the major axis diameter is in the range of 200-250μm, and the scanning step size is not greater than the spot diameter.

4. The method for identifying and measuring the Halo region of an alignment film according to claim 1, characterized in that, In step S4, when selecting an internal uniform region, the distance between this region and the physical edge should not be less than the expected maximum width of the Halo region to be measured, and should be at least 2 mm; the relative thickness deviation threshold is set to ±10% of the reference film thickness.

5. The method for identifying and measuring the Halo region of an alignment film according to claim 4, characterized in that, In step S2, the spectrum acquisition can be performed using a single fixed incident angle or a multi-incident angle measurement mode. When using the multi-incident angle mode, elliptic polarization spectral data are acquired sequentially at each measurement point with at least two different incident angles to improve the fitting accuracy.

6. The method for identifying and measuring the Halo region of an alignment film according to claim 5, characterized in that, The two-dimensional film thickness distribution map generated in step S3 can be represented as one or more combinations of a two-dimensional mapping map, a contour map, or a three-dimensional topography map.

7. The method for identifying and measuring the Halo region of an alignment film according to claim 1, characterized in that, The maximum width of the Halo region extracted in step S5 refers to the maximum straight-line distance within the Halo region, along the direction perpendicular to the physical edge of the alignment membrane, from the physical edge to where the membrane thickness is restored to 90% of the reference membrane thickness.

8. A device for identifying and measuring the Halo region of an alignment membrane, characterized in that, include: Memory; A processor; wherein the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the alignment film Halo region identification measurement method as described in any one of claims 1 to 7.

9. A system for identifying and measuring the Halo region of an alignment film, characterized in that, The system comprises the alignment film Halo region identification and measurement method according to any one of claims 1-7, or the alignment film Halo region identification and measurement device according to claim 8.

10. A computer storage medium, characterized in that, The computer storage medium stores computer execution instructions, which, when executed by a processor, are used to implement the alignment film Halo region identification and measurement method as described in any one of claims 1 to 7.

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