Wafer for monitoring the thickness of a photoresist deposition, monitoring method and storage medium

Abstract

The application relates to a monitoring wafer for monitoring the deposition thickness of photoresist, a monitoring method and a storage medium. The monitoring wafer comprises sensor modules distributed in regions on the surface of the wafer, the sensor modules comprise an integrated coplanar interdigital capacitive sensor and a temperature sensor, and the sensor modules are used for acquiring the capacitance value and the temperature value of a point in each region. The method comprises the following steps: in the process of coating the monitoring wafer according to initial formula parameters, the capacitance value and the temperature value of each point on the monitoring wafer at each moment are acquired through the sensor modules; the spatial distribution of the photoresist film thickness with time is obtained according to the capacitance value and the temperature value, the distance from each point to the center of the monitoring wafer, and a pre-established photoresist film thickness model; a dynamic response relationship between the spatial distribution of the photoresist film thickness with time and the initial formula parameters is established; and based on the dynamic response relationship, the change of the photoresist film thickness with time is visually displayed. Real-time acquisition of film thickness data can be realized without affecting the operation of the coating process.

Description

Technical Field

[0001] This application relates to the field of semiconductor technology, and specifically designs a wafer, monitoring method, and storage medium for monitoring photoresist deposition thickness. Background Technology

[0002] In semiconductor photolithography, the photolithography process is a key process for fabricating various device patterns. Its quality directly affects the stability and improvement of parameters such as device yield, reliability, device performance, and lifespan. During spin-coating of photoresist, the liquid photoresist undergoes drastic thickness changes and solvent evaporation during high-speed rotation. Different photoresist thicknesses result in different reflectivities during exposure, thus affecting the photolithographic resolution and ultimately the size of the pattern formed by the photolithography process.

[0003] However, current technologies for measuring photoresist film thickness only cover the final film thickness measurement, and generally cannot achieve real-time acquisition of film thickness data throughout the coating process. This results in a lack of clear correlation between the measured data and key process parameters such as material application rate and rotation speed, hindering precise optimization of subsequent processes. Furthermore, the integration complexity of related measurement systems is high, and the coupling between the measurement equipment and the lithography unit is extremely strong, significantly increasing the difficulty of equipment reusability and portability. Summary of the Invention

[0004] Based on this, it is necessary to provide a monitoring wafer, monitoring method, and storage medium for photoresist deposition thickness to address the above-mentioned technical problems. This should enable real-time acquisition of film thickness data without affecting the coating process, and be applicable to various coating and developing equipment (Track).

[0005] In a first aspect, this application provides a method for monitoring the photoresist deposition thickness of a wafer. The monitored wafer includes sensor modules distributed in various regions on the wafer surface. Each sensor module includes an integrated coplanar interdigitated capacitance sensor and a temperature sensor. The sensor modules are used to acquire the capacitance and temperature values ​​of points in each region. The method includes:

[0006] During the coating process of the monitoring wafer according to the initial formula parameters, the sensor module obtains the capacitance and temperature values ​​of each point on the monitoring wafer at each moment.

[0007] Based on the capacitance and temperature values, the distance from each point to the center of the monitored wafer, and the pre-established photoresist film thickness model, the spatial distribution of the photoresist film thickness over time is obtained.

[0008] Establish the dynamic response relationship between the spatial distribution of photoresist film thickness over time and the initial formulation parameters;

[0009] Based on the dynamic response relationship, the change in photoresist film thickness over time can be visualized.

[0010] In some embodiments, each region includes a plurality of annular regions arranged sequentially in a radial direction;

[0011] The sensor modules are located at the center of the monitoring wafer and are distributed circumferentially in various annular regions, with the same circumferential spacing between each sensor module.

[0012] In some embodiments, the spatial distribution of the photoresist film thickness over time is obtained based on the capacitance and temperature values, the distance from each point to the center of the monitoring wafer, and a pre-established photoresist film thickness model, including:

[0013] Based on the capacitance value, temperature value, and photoresist film thickness function of each point on the wafer at each moment, the photoresist film thickness at each point at each moment is obtained.

[0014] Based on the photoresist film thickness model of the annular region and the photoresist film thickness at each point at each time, the spatial distribution of the photoresist film thickness at the center and multiple annular regions over time is obtained.

[0015] In some embodiments, the method for determining the photoresist film thickness function includes:

[0016] Based on the electric field strength characteristics of coplanar interdigital capacitors, a sensitivity function is established;

[0017] Based on the sensitivity function, the saturation index model of the coplanar interdigital capacitive sensor is obtained;

[0018] Multiple standard samples with known film thicknesses were prepared using monitored wafers, and the capacitance values ​​at different temperature points were obtained during the preparation process and recorded as initial experimental data.

[0019] Based on the initial experimental data, the baseline capacitance, saturation gain, and attenuation coefficient of the saturation index model after temperature compensation were obtained by nonlinear fitting, and the photoresist film thickness function was obtained by inverse solution.

[0020] In some embodiments, the expression for the photoresist film thickness model of the annular region is:

[0021] ;

[0022] Where M represents the number of annular regions, r k h(r) is the inner radius of the k-th annular region, and Δr is the width of the annular region; k ,t) is the photoresist film thickness of the k-th annular region at time t.

[0023] In some embodiments, the method for confirming the photoresist film thickness model includes:

[0024] Based on radial basis function interpolation and Gaussian function, the discrete photoresist film thickness function at each point is reconstructed into a continuous wafer radial thickness field.

[0025] Obtain the weights of the coplanar interdigital capacitive sensors at each point at each time moment;

[0026] A photoresist film thickness model for the annular region is constructed based on weights and the wafer radial thickness field.

[0027] In some embodiments, establishing the dynamic response relationship between the spatial distribution of photoresist film thickness over time and the initial formulation parameters includes:

[0028] Import process logs from the same batch, the process logs including at least the initial formulation steps and the time points corresponding to the initial formulation steps;

[0029] In conjunction with the time points of the initial formulation steps, the spatial distribution of photoresist film thickness in each region over time is correlated with the formulation parameters to form a dynamic response relationship between photoresist film thickness and initial formulation parameters.

[0030] Secondly, this application also provides a storage medium storing a computer program, wherein the computer program is configured to execute the monitoring method described in any of the above embodiments when running.

[0031] Thirdly, this application also provides a monitoring wafer, including: a substrate, and a power supply layer, a data acquisition layer, a sensing layer and a hydrophobic coating arranged sequentially in a direction away from the substrate;

[0032] The power supply layer is used to power the data acquisition layer and the sensing layer;

[0033] The data acquisition layer is used to control the sampling frequency and add timestamps, and caches the capacitance and temperature values ​​acquired by the sensing layer in the internal memory;

[0034] The sensing layer includes sensor modules distributed in various regions of the wafer surface. The sensor modules include an integrated coplanar interdigitated capacitance sensor and a temperature sensor, used to acquire the capacitance and temperature values ​​of points in each region.

[0035] Hydrophobic coatings are used to simulate the surface of a real wafer.

[0036] In some embodiments, the power supply layer and the data acquisition layer further include:

[0037] The communication transmission layer is used to transmit photoresist film thickness data to the external control system in real time.

[0038] The monitoring wafer, monitoring method, and storage medium for photoresist deposition thickness provided in this application have the following technical advantages:

[0039] By using a monitoring wafer that integrates a coplanar interdigital capacitance sensor and a temperature sensor that do not require opposing electrodes, real-time acquisition of film thickness change data is achieved throughout the entire photoresist spin coating process without significantly altering the existing coating equipment structure. This data is then combined with a pre-established photoresist film thickness model to deduce the spatial distribution of film thickness over time and establish the dynamic response relationship between this distribution and the initial formulation parameters. Finally, a visual animation is generated according to the time series, allowing process engineers to intuitively identify process steps that lead to film thickness deviation or abnormal morphology.

[0040] Meanwhile, the monitoring wafer adopts a reusable structure with self-powered power supply, wireless communication and hydrophobic coating, which is suitable for various types of coating equipment. It has good reusability and portability, which helps to reduce the dependence on offline measurement or destructive analysis, reduce the trial and error cost of transferring process parameters between different machines, and provide a solid data foundation for the establishment of material behavior fingerprint database and machine behavior fingerprint database. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a schematic diagram of the structure of a monitoring wafer provided in one embodiment;

[0043] Figure 2 This is a schematic diagram showing the distribution of the monitoring wafer sensor module in one embodiment;

[0044] Figure 3 This is a flowchart illustrating a monitoring method for photoresist thickness deposition on a monitored wafer in one embodiment.

[0045] Figure 4 This is a flowchart illustrating step S103 in one embodiment;

[0046] Figure 5 This is a flowchart illustrating step S104 in one embodiment.

[0047] Figure labels and descriptions:

[0048] 1. Substrate; 2. Power supply layer; 3. Communication transmission layer; 4. Data acquisition layer; 5. Sensing layer; 6. Hydrophobic coating. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0050] Related technologies for measuring deposition thickness include: external equipment (such as ellipsometers and reflectivity probes), built-in sensors, and testing wafers combined with offline analysis. External equipment can only measure offline and cannot reflect the actual process; built-in sensors are only supported by some high-end coating equipment, and their installation location is limited and maintenance costs are high; testing wafers combined with offline analysis is inefficient and cannot accurately reflect the dynamic behavior of the process.

[0051] Please see Figure 1 Based on this, this application provides a monitoring wafer, comprising: a substrate 1, and a power supply layer 2, a data acquisition layer 4, a sensing layer 5, and a hydrophobic coating 6 arranged sequentially along a direction away from the substrate 1.

[0052] Specifically, the power supply layer 2 includes a battery for powering the data acquisition layer 4 and the sensing layer 5, providing the power required for 1-2 hours of continuous measurement without the need for external contact with the electrodes. This application does not specify a particular battery type.

[0053] The data acquisition layer 4 includes a capacitive circuit board, a microcontroller, and a clock circuit. The flexible circuit structure is used to connect the various sensors and transmit signals, such as a double-sided flexible FPC cable (polyimide + copper). The microcontroller is used to control the sampling frequency and data processing, such as an STM32 ultra-small MCU. The clock circuit is used to add timestamps to the acquired data, such as a clock chip RTC.

[0054] Sensing layer 5 includes sensor modules distributed across various regions of the wafer surface. Each sensor module includes an integrally packaged coplanar interdigital capacitance sensor and a temperature sensor, used to acquire the capacitance and temperature values ​​at points in each region. The sensor modules are located at the center of the monitored wafer and are distributed circumferentially in various annular regions, with the circumferential spacing between each sensor module being the same. The specific distribution is as follows: Figure 2 As shown.

[0055] The hydrophobic coating 6 is used to simulate the surface of a real wafer and has solvent resistance and anti-fouling properties. The materials for the hydrophobic coating can include, but are not limited to, silicon dioxide (SiO2).

[0056] In the above embodiments, the monitoring wafer structure simulates the actual wafer morphology during the entire process of photoresist spraying and spin-coating, recording film thickness change data in real time. It employs a coplanar interdigital capacitance sensor, which can acquire capacitance values ​​without relying on opposing electrodes. The data acquisition layer can control the sampling frequency, add timestamps, and cache data, recording the capacitance and temperature values ​​at each point and at each moment in real time during the spin-coating process.

[0057] Meanwhile, the hydrophobic coating ensures that the wafer surface characteristics remain consistent with the actual process conditions. This structure is suitable for various track devices, enabling full-process film thickness detection, feedback, and analysis at a low cost without altering existing equipment, and without affecting the normal operation of the coating process.

[0058] Furthermore, in some embodiments, the monitoring wafer also includes:

[0059] The communication transmission layer 3 is used for high-speed transmission of photoresist film thickness and rotation speed data, and supports stable communication under rotation conditions. Low-power Bluetooth or LoRa can be used for wireless data transmission.

[0060] To better match the correspondence between film thickness data and process flow, the monitoring wafer may also include a rotation speed sensing layer (not shown) for real-time acquisition of rotational speed and acceleration data, which can then be paired with the film thickness variation curve for modeling. This rotation speed sensing layer can employ a gyroscope (e.g., an ICM-42688 gyroscope) and an integrated accelerometer chip to achieve accurate acquisition of dynamic parameters during rotation.

[0061] Based on this, please refer to Figure 3 In some embodiments, this application provides a monitoring method for photoresist thickness deposition on a monitored wafer, including the following steps S1 to S4.

[0062] In step S1: During the process of coating the monitoring wafer with adhesive according to the initial formula parameters, the capacitance and temperature values ​​of each point on the monitoring wafer at each moment are obtained through the sensor module.

[0063] Step S2: Based on the capacitance and temperature values, the distance from each point to the center of the monitored wafer, and the pre-established photoresist film thickness model, obtain the spatial distribution of the photoresist film thickness over time.

[0064] Step S3: Establish the dynamic response relationship between the spatial distribution of photoresist film thickness over time and the initial formulation parameters.

[0065] Step S4: Based on the dynamic response relationship, visualize the change of photoresist film thickness over time.

[0066] In the above embodiments, by using a monitoring wafer that integrates a coplanar interdigital capacitance sensor and a temperature sensor, the point capacitance value and temperature value can be obtained without the need for opposing electrodes. Then, combined with a pre-established photoresist film thickness model, the spatial distribution of film thickness over time is inverted, and the dynamic response relationship between this distribution and the initial formula parameters is established. Finally, a visual animation is generated according to the time series.

[0067] Therefore, the above method can collect film thickness variation data at different spatial locations throughout the coating process in real time without changing the original structure of the coating machine, and align the film thickness evolution with specific formulation steps in time, which helps to fully understand the dynamic characteristics of photoresist during spin coating. Simultaneously, the generated visualization animation can intuitively show the spatiotemporal evolution of film thickness on the wafer surface, providing convenient data support for process engineers to analyze the causes of film thickness deviation, optimize formulation parameters, and compare process consistency across different machines. This reduces reliance on offline measurements and destructive analysis, and also reduces actual trial-and-error costs.

[0068] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0069] In an exemplary embodiment, in the extended step of step S1, the specified initial formulation parameters are selected to perform the coating operation. During the entire coating process, the wafer is monitored to synchronously collect the capacitance and temperature values ​​detected by the sensor modules at each point according to a preset sampling frequency (e.g., a sampling frequency of 1 ms), and the collected raw data is timestamped and cached in the internal memory.

[0070] For example, let C be the capacitance value at each capacitor bit i and at each time t. i (t), the temperature value is denoted as T. i (t).

[0071] In practical applications, before performing the coating operation, the monitoring wafer must be pre-processed to check for scratches on the surface of the monitoring wafer to ensure the integrity of the sensor area; the remaining power of the power supply layer must be checked to ensure that it can support the data acquisition of the entire coating process cycle; the internal memory (such as Flash) in the data acquisition layer must be cleared to release storage space; and the multi-channel sensors distributed in various areas of the wafer surface (such as coplanar interdigitated capacitance sensors and temperature sensors located at the center, middle ring and edge) must be confirmed to be able to respond normally.

[0072] This method monitors the process of the wafer rotating together with the liquid photoresist to form a film, and obtains the capacitance and temperature values ​​at each sampling point in real time, providing a data foundation for subsequent film thickness inversion calculation and dynamic response analysis.

[0073] In one exemplary embodiment, please refer to Figure 4 Step S2 includes steps S21-S22:

[0074] Step S21: Based on the capacitance value C of each point on the monitored wafer at each moment... i (t), temperature value T i The photoresist film thickness at each point is obtained by using (t) and the photoresist film thickness function h(t). The photoresist film thickness function h(t) of the sensor module at point i on the monitoring wafer at time t is used to obtain the photoresist film thickness at each time. i The expression for (t) is:

[0075]

[0076] Among them, C i (t) is the actual capacitance value measured by the sensor module located at monitoring wafer point i at time t, C0(T) i (t)), K(T) i (t)), α(T) i (t) represents the sensor module at point i at time t and temperature T, respectively. i The baseline capacitance, saturation gain, and attenuation coefficient obtained after calibration under (t).

[0077] In an optional embodiment, the method for confirming the photoresist film thickness function includes: steps S211-S214.

[0078] Step S211: Establish the sensitivity function based on the electric field strength characteristics of the coplanar interdigital capacitor.

[0079] Since the electric field lines of a coplanar interdigitated capacitor originate from a finger electrode and terminate at an adjacent electrode, the electric field distribution follows Maxwell's equations. Its electric field lines exhibit an arched distribution, directly inducing and monitoring the dielectric at the wafer surface without the need for opposing electrodes. The electric field intensity decreases exponentially with height. Therefore, the contribution weight of a unit thickness of dielectric at height z to the total capacitance is defined as a sensitivity function, expressed as:

[0080]

[0081] Where S0 is the surface sensitivity coefficient, α is the attenuation coefficient which is related to the electrode geometry, and z is the height from the sensor surface. It is important to note that the sensitivity function S(z) is an electric field distribution function with dimensionless units, which differs from the traditional performance parameters that refer to sensor gain coefficients or crosstalk suppression capabilities.

[0082] Step S212: Based on the sensitivity function, obtain the saturation index model of the coplanar interdigital capacitive sensor.

[0083] Substituting the sensitivity function S(z) into the integral of the total capacitance corresponding to the photoresist layer with thickness h, and rearranging, we obtain the general saturation index model expression for the coplanar interdigital capacitive sensor as follows:

[0084]

[0085] Where C0 is the baseline capacitance, which represents the capacitance value of the coplanar interdigital capacitive sensor when h=0; K is the saturation gain, which represents the maximum change in the coplanar interdigital capacitive sensor as h increases from 0 to ∞; α is the attenuation coefficient, which controls the saturation rate of capacitance as thickness increases, and is related to the electrode geometry and the dielectric constant of the film.

[0086] Since the dielectric constant and electrode size change with temperature, a saturation index model is obtained by further introducing temperature compensation:

[0087]

[0088] Step S213: Prepare multiple standard samples with known film thickness using the monitoring wafer, and obtain the capacitance values ​​corresponding to different temperature points during the preparation process, which are recorded as initial experimental data.

[0089] A series of standard samples with known film thickness h (e.g., 0 μm, 100 μm, 500 μm, 1000 μm and 2000 μm) were prepared, and the capacitance values ​​of each coplanar interdigital capacitive sensor were measured at different temperature points T.

[0090] Step S214: Based on the initial experimental data, the baseline capacitance, saturation gain and attenuation coefficient after temperature compensation are obtained by nonlinear fitting of the saturation index model, and the photoresist film thickness function is obtained by inverse solution.

[0091] Using nonlinear least squares fitting, the optimal baseline capacitance C0(t), saturation gain K(t), and attenuation coefficient α(t) parameters for each sensor module at time t are found. This is achieved by inversely solving the capacitance formula:

[0092]

[0093] The photoresist film thickness function for the sensor module at each point i at time t is obtained as follows:

[0094]

[0095] In the above embodiments, a saturation index model is established based on the electric field sensitivity function of the coplanar interdigital capacitance, and nonlinear fitting is performed by combining the calibration data of standard samples with known film thickness at different temperatures. After temperature compensation is introduced, the film thickness function is solved inversely. This process helps to improve the measurement accuracy under different temperatures and different film thickness ranges, and makes the model more adaptable to the actual process environment.

[0096] In addition, since coplanar interdigitated capacitors do not require opposing electrodes, the sensor module can be fully integrated inside the monitoring wafer without relying on the original electrode structure of the coating machine or additional wiring. This makes the monitoring wafer highly reusable across different models of Track equipment, and can be flexibly deployed on multiple machines, reducing the complexity and implementation cost of cross-equipment process matching.

[0097] Step S22: Based on the photoresist film thickness model of the annular region and the photoresist film thickness at each point at each time, obtain the spatial distribution of the photoresist film thickness at the center and multiple annular regions over time.

[0098] Sensor modules are distributed at the center of the circle, and the photoresist film thickness at time t can be directly calculated. The expression for the photoresist film thickness model in the annular region is:

[0099] ;

[0100] Where M represents the number of annular regions, r k h(r) is the inner radius of the k-th annular region, and Δr is the width of the annular region; k ,t) is the photoresist film thickness of the k-th annular region at time t; where k is the sequence of annular regions, and the sequence number gradually increases in the direction away from the center.

[0101] In an optional embodiment, the method for confirming the photoresist film thickness model includes: steps S221-S223.

[0102] Step S221: Based on radial basis function interpolation and Gaussian function, reconstruct the discrete photoresist film thickness function at each point into a continuous wafer radial thickness field.

[0103] Specifically, since the wafer is circularly symmetric during monitoring, and the film thickness distribution mainly exhibits radial symmetry (centrosymmetry) during rotation, a radial thickness field h(r,t) is preferentially constructed. The expression for the wafer radial thickness field is:

[0104]

[0105] Where h(r, t) is the estimated thickness at radius r and time t, and r is the distance from the target position to the center of the circle. j Let W be the distance from the j-th sensor module to the center of the circle. j (t) represents the weight of the j-th sensor module relative to the target position at time t, where j is the sequence of each sensor module.

[0106] Radial basis functions , , representing the Euclidean distance from radius r to the j-th sensor module, and β is the shape parameter of the coplanar interdigital capacitive sensor, expressed as follows:

[0107]

[0108] in, It is the average nearest neighbor distance between each sensor module.

[0109] Step S222: Obtain the weights of the coplanar interdigitated capacitive sensors at each point at each time moment.

[0110] The radial thickness field of the sensor module at point i and time t. Expanding this into a matrix equation, we get:

[0111]

[0112] Where λ and I are the regularization coefficient and identity matrix, respectively; H(t) is an N×1 vector containing the thicknesses [h1(t), h2(t), ..., h] measured by N sensor modules at time t. N [(t)];Φ is an N×N matrix with elements as ;Φ ij This represents the degree of influence of the j-th sensor module relative to the i-th sensor module. For example, when j=i, the radial basis function is 1, meaning the influence of this sensor on its own position is 1, and so on. w(t) is an N×1 vector containing the weights to be solved, including [w1(t), w2(t), ..., w NTherefore, given the sensor modules, the weight coefficient of point i corresponding to time t for each sensor module can be obtained by solving the above formula.

[0113] Step S223: Based on the weights and the wafer radial thickness field, construct a photoresist film thickness model for the annular region.

[0114] The integral from thickness to volume is: .

[0115] Using numerical integration, the monitoring wafer is divided radially from 0 to R into M small rings, each with a width of Δr. The average thickness of the ring is then obtained by the interpolation function:

[0116]

[0117] Among them, V on-wafer (t) represents the photoresist film thickness volume in the annular region at time t, R is the radius of the monitoring wafer, M represents the number of annular regions, and r k h(r) is the inner radius of the k-th annular region, and Δr is the width of the annular region; k Let ,t) be the photoresist film thickness of the k-th annular region at time t. Therefore, given the known capacitance values ​​C at each point... i (t), temperature value T i (t) can be used to obtain the continuous thickness of photoresist deposition at each time point and in each region of the wafer.

[0118]

[0119] In the above embodiments, radial basis function interpolation and Gaussian function are used to reconstruct the discrete point film thickness into a continuous wafer radial thickness field. The positive definiteness of the Gaussian function ensures the stability and uniqueness of the interpolation solution, and its infinite differentiability ensures the smoothness and continuity of the reconstructed surface, matching the natural morphology of the fluid surface. Its rapid decay characteristics limit the range of local influence, reduce far-field interference, and make the film thickness reconstruction result more realistically reflect the local variation characteristics of the wafer surface.

[0120] In one exemplary embodiment, such as Figure 5 As shown, step S3 includes steps S31-S32: establishing the dynamic response relationship between the spatial distribution of the photoresist film thickness over time and the initial formulation parameters, including:

[0121] Step S31: Import the process logs for the same batch. The process logs must contain at least the initial formulation steps and their corresponding time points.

[0122] Specifically, the process log for the same batch as this coating operation is obtained from the coating machine. This process log records each step of the initial formulation parameters (such as the glue spraying step, the uniform coating step, the solvent evaporation step, etc.) and their corresponding start and end times. The process log is imported into the data processing system for subsequent timeline alignment with the film thickness data.

[0123] Step S32: In conjunction with the time nodes of the initial formulation step, perform correlation analysis between the spatial distribution of photoresist film thickness in each region over time and the formulation parameters to form a dynamic response relationship between photoresist film thickness and initial formulation parameters.

[0124] Specifically, the study analyzes the film thickness variation trend, convergence characteristics, and thickness differences between different regions during each formulation step. Through correlation analysis, it is possible to identify which formulation steps have a significant impact on film thickness evolution, such as the effect of the spin coating acceleration stage on the film thickness in the central region and the effect of edge evaporation phenomena on the film thickness in the edge region, thereby establishing a dynamic response relationship between film thickness changes and specific formulation parameters.

[0125] In the above embodiments, the outputs of all the aforementioned steps are used to generate a continuous thickness field in a time sequence and synthesized into a dynamic animation, intuitively reproducing the entire process from dropping, spreading, and splashing to film formation. This helps process engineers to intuitively identify key nodes in film thickness evolution, locate process steps affecting thickness uniformity, and provide a visual basis for optimizing formulation parameters. It also establishes a photoresist behavior library and a process fingerprint library for behavior comparison and reference between different machines.

[0126] The following is combined with Figures 1-5 The monitoring method provided in this application will be further described in terms of specific application scenarios:

[0127] First, the monitoring wafer undergoes preprocessing, including checking its surface condition, confirming sufficient power, clearing internal memory, and verifying normal sensor response in each area. Then, the monitoring wafer is fed into a coating machine, and the specified coating formula is selected for the coating operation. Throughout the entire process, the monitoring wafer records the capacitance changes at each point in real time at a high-speed sampling frequency and stores the data in its internal memory.

[0128] After coating is completed, the monitoring wafer is removed, and the capacitance data collected during the coating process is wirelessly exported. This data, combined with the built-in photoresist thickness model, is used to obtain the spatial distribution of photoresist thickness over time in each region. Furthermore, the formulation steps and time points in the process log of the same batch are correlated to form a dynamic response relationship. Finally, regional film thickness distribution maps and film thickness variation curves are output, and the data is written into the photoresist behavior library and process fingerprint library for subsequent process optimization and equipment comparison.

[0129] In some embodiments, this application also provides a storage medium storing a computer program, wherein the computer program is configured to execute the monitoring method described above during runtime. Using this storage medium, the monitoring method can be deployed as software in existing data processing terminals or process control systems, making the monitoring and optimization of the photoresist coating process more flexible and highly reusable.

[0130] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0131] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0132] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for monitoring the photoresist deposition thickness on a wafer, characterized in that, The monitoring wafer includes sensor modules distributed across various regions of the wafer surface. Each sensor module includes an integrated coplanar interdigitated capacitance sensor and a temperature sensor. The sensor modules are used to acquire the capacitance and temperature values ​​of points in each region. The method includes: During the coating process of the monitoring wafer according to the initial formula parameters, the sensor module acquires the capacitance and temperature values ​​of each point on the monitoring wafer at each moment. Based on the capacitance and temperature values, the distance from each point to the center of the monitoring wafer, and the pre-established photoresist film thickness model, the spatial distribution of the photoresist film thickness over time is obtained. Establish the dynamic response relationship between the spatial distribution of the photoresist film thickness over time and the initial formulation parameters; Based on the dynamic response relationship, the change in the thickness of the photoresist film over time is visualized.

2. The monitoring method according to claim 1, characterized in that, Each region includes multiple annular regions arranged sequentially along the radial direction; The sensor modules are located at the center of the monitoring wafer and are distributed circumferentially in various annular regions, with the circumferential spacing between each sensor module being the same.

3. The monitoring method according to claim 2, characterized in that, The step of obtaining the spatial distribution of photoresist film thickness over time based on the capacitance and temperature values, the distance from each of the points to the center of the monitored wafer, and a pre-established photoresist film thickness model includes: The photoresist film thickness at each point at each moment is obtained based on the capacitance value, temperature value, and photoresist film thickness function at each point on the monitoring wafer at each moment. Based on the photoresist film thickness model of the annular region and the photoresist film thickness at each point at each time, the spatial distribution of the photoresist film thickness at the center and multiple annular regions over time is obtained.

4. The monitoring method according to claim 3, characterized in that, The method for confirming the photoresist film thickness function includes: Based on the electric field strength characteristics of coplanar interdigital capacitors, a sensitivity function is established; Based on the sensitivity function, the saturation index model of the coplanar interdigital capacitive sensor is obtained; Multiple standard samples with known film thicknesses were prepared using the monitored wafer, and the capacitance values ​​corresponding to different temperature points were obtained during the preparation process and recorded as initial experimental data. Based on the initial experimental data, the baseline capacitance, saturation gain, and attenuation coefficient of the saturation index model after temperature compensation are obtained by nonlinear fitting, and the photoresist film thickness function is obtained by inverse solution.

5. The monitoring method according to claim 3, characterized in that, The expression for the photoresist film thickness model of the annular region is: ； Among them, V on-wafer (t) represents the photoresist film thickness volume in the annular region at time t, M represents the number of annular regions, and r k h(r) is the inner radius of the k-th annular region, and Δr is the width of the annular region; k ,t) is the photoresist film thickness of the k-th annular region at time t.

6. The monitoring method according to claim 5, characterized in that, The methods for confirming the photoresist film thickness model include: Based on radial basis function interpolation and Gaussian function, the discrete photoresist film thickness function at each point is reconstructed into a continuous wafer radial thickness field. Obtain the weights of the coplanar interdigital capacitive sensors at each point at each time moment; Based on the weights and the wafer radial thickness field, a photoresist film thickness model for the annular region is constructed.

7. The monitoring method according to claim 1, characterized in that, The establishment of the dynamic response relationship between the spatial distribution of the photoresist film thickness over time and the initial formulation parameters includes: Import process logs from the same batch, the process logs including at least the initial formulation steps and the time points corresponding to the initial formulation steps; In conjunction with the time points of the initial formulation steps, the spatial distribution of photoresist film thickness in each region over time is correlated with the formulation parameters to form a dynamic response relationship between photoresist film thickness and initial formulation parameters.

8. A storage medium, characterized in that, The storage medium stores a computer program, wherein the computer program is configured to execute the monitoring method according to any one of claims 1-7 when it runs.

9. A monitoring wafer, characterized in that, The monitoring method according to any one of claims 1-7 includes: a substrate, and a power supply layer, a data acquisition layer, a sensing layer and a hydrophobic coating arranged sequentially in a direction away from the substrate; The power supply layer is used to supply power to the data acquisition layer and the sensing layer; The data acquisition layer is used to control the sampling frequency and add timestamps, and caches the capacitance and temperature values ​​acquired by the sensing layer in the internal memory; The sensing layer includes sensor modules distributed in various regions of the wafer surface. The sensor modules include an integrated coplanar interdigital capacitance sensor and a temperature sensor, used to acquire the capacitance value and temperature value of points in each of the regions. The hydrophobic coating is used to simulate the surface of a real wafer.

10. The monitoring wafer according to claim 9, characterized in that, Between the power supply layer and the data acquisition layer, there is also: The communication transmission layer is used to transmit photoresist film thickness data to the external control system in real time.

Images