Semiconductor production line inline delivery energy prediction method and storage medium

Abstract

The invention discloses a semiconductor production line inline delivery energy prediction method and a storage medium, the semiconductor production line inline delivery energy prediction method comprises the following steps: S1, determining the critical size of a mask; s2, establishing a relational expression between the key size of the mask and the inline passing energy; and S3, an inline delivery condition is pre-judged according to the relational expression, and the purpose of not carrying out Pilot run is achieved. The production efficiency can be improved, resources are saved, and the product circulation speed is increased.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of semiconductors, and in particular to a method for predicting inline overexposure energy in a semiconductor production line and a storage medium. BACKGROUND

[0002] For the same platform and different products in the photolithography process, the defined overexposure energy pattern is generally consistent. In the semiconductor production process, under the condition of new product going offline or mask revision, in order to determine the optimal overexposure condition, photolithography generally applies for pilot time for key levels, which usually takes 10-14 hours per layer. This approach not only affects production efficiency, but also causes waste of resources.

[0003] Therefore, under the condition of new product going offline or mask revision, how to quickly determine the corresponding inline overexposure energy is an urgent technical problem to be solved to improve production efficiency and save resources.

[0004] Glossary

[0005] Inline refers to the direct integration of a device, process, or task into a production system, which is executed and controlled by the production system (such as manufacturing execution system, MES) in real time. In the inline state, the device or process is part of the production line and directly handles the tasks assigned by the system

[0006] Mask CD (mask critical dimension) is an important parameter in semiconductor manufacturing, which directly affects the performance and yield of chips. By precisely controlling Mask CD and studying its relationship with Wafer CD, the photolithography process can be optimized to improve production efficiency and product quality.

[0007] Wafer CD (wafer critical dimension) is an important parameter in semiconductor manufacturing, which directly affects the performance and yield of chips.

[0008] Engineering Pilot (EPR) refers to a small-scale production test phase in the new product development process to verify whether the product design and production process meet the expected requirements. This phase usually follows product design verification (DVT) and precedes mass production verification test (PVT). SUMMARY

[0009] A series of simplified concepts are introduced in the part of the summary of the invention, which are simplified from the prior art in the field, which will be described in detail in the part of the specific embodiments. The part of the summary of the invention does not mean to try to limit the key features and necessary technical features of the claimed technical solutions, and does not mean to try to determine the protection scope of the claimed technical solutions.

[0010] The technical problem to be solved by the present application is to provide a semiconductor production line inline overage energy prediction method which can quickly determine the corresponding inline overage energy under the condition of new product off-line or mask revision.

[0011] To solve the above technical problems, the semiconductor production line inline overage energy prediction method provided by the present application comprises the following steps:

[0012] S1, determining the key size (mask CD) of the mask plate;

[0013] S2, establishing a relationship between the key size (mask CD) of the mask plate and the inline overage energy;

[0014] S3, judging the inline overage condition according to the relationship, and realizing no pilot run.

[0015] Preferably, the semiconductor production line inline overage energy prediction method is further improved, and the relationship is EE=a*mask CD+b, a and b are specified coefficients.

[0016] Preferably, the semiconductor production line inline overage energy prediction method is further improved, and the relationship is EE=-1.4871*mask CD+100.86, EE is Exposure Energy, that is, exposure energy.

[0017] The relationship represents the relationship between the key size (mask CD) of the mask plate and the exposure energy (EE). Through this relationship, the required exposure energy under a specific mask plate key size can be predicted, so that the best overage energy condition can be quickly determined without pilot run (engineering test).

[0018] Reference Figure 1 and Figure 2 As shown in the figure, through the 22 platform MX layer, the relationship between mask CD and inline energy (EE=-1.4871*mask CD+100.86) is established

[0019] From the test results of 54pcs mask from 9 products, the inline overpass energy predicted by mask CD is within 0.5mj compared with the energy value set after pilot run.

[0020] Preferably, the semiconductor production line inline overpass energy prediction method is further improved to be applicable to at least one of the following process platforms: 28nm or below complementary metal-oxide-semiconductor transistor or high-k dielectric gate.

[0021] Preferably, the semiconductor production line inline overpass energy prediction method is further improved to be applicable to immersion lithography process.

[0022] To solve the above technical problems, the application provides a computer readable storage medium, which internally stores a computer program, the computer program is executed to implement the steps of the semiconductor production line inline overpass energy prediction method.

[0023] The working principle of the application is described as follows:

[0024] For the same platform of lithography process, the graph of overpass energy is generally consistent between different products. In the case of the same process, the inline overpass energy is largely affected by mask CD. The correlation between wafer CD and mask CD is studied, and it is found that mask CD and wafer CD have strong correlation. Therefore, the critical dimension of the mask (mask CD) and the inline overpass energy have strong correlation. Therefore, by establishing the relationship between the two, the inline overpass condition can be directly predicted according to the critical dimension of the mask, without pilot run.

[0025] The application can at least achieve the following technical effects

[0026] 1. Improve production efficiency: avoid pilot run, save 10-14 hours of engineering time.

[0027] 2. Save resources: reduce the resources consumed due to pilot run.

[0028] 3. Speed up product circulation: quickly predict the inline overpass condition, so that the product can enter the production process faster. BRIEF DESCRIPTION OF DRAWINGS

[0029] The drawings of the present application are intended to illustrate the general characteristics of the methods, structures and / or materials used in accordance with particular example embodiments of the present application, and to supplement the description of the present application in the specification. However, the drawings of the present application are schematic and not drawn to scale, and thus can not accurately reflect the precise structural or performance characteristics of any given embodiment, and the drawings of the present application should not be interpreted as limiting or restricting the scope of the values or attributes encompassed by example embodiments in accordance with the present application. The present application is further described in detail below with reference to the drawings and specific embodiments.

[0030] Figure 1 is a schematic diagram of the relationship between mask CD and inline energy.

[0031] Figure 2 is a schematic diagram of the relationship between inline energy predicted using mask CD and the energy value set after the pilot run. DETAILED DESCRIPTION

[0032] The embodiments of the present application are described below through specific specific embodiments, and those skilled in the art can fully understand other advantages and technical effects of the present application from the disclosure of the present specification. The present application can also be implemented or applied through different specific embodiments, and each detail in the present specification can be applied based on different viewpoints, and various modifications or changes can be made without departing from the general design idea of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. The following example embodiments of the present application can be implemented in various forms, and should not be interpreted as being limited to the specific embodiments described herein. It should be understood that these embodiments are provided to make the disclosure of the present application complete and complete, and to fully convey the technical solutions of these example embodiments to those skilled in the art.

[0033] First embodiment;

[0034] The present application provides a semiconductor production line inline energy prediction method, comprising the following steps:

[0035] S1, determining the mask CD of the mask plate; using a high-precision measuring device (such as CD-SEM or optical measuring tool) to measure the critical dimension on the mask plate; measuring multiple positions to ensure the accuracy and consistency of the measurement results;

[0036] S2, establishing the relationship between the mask CD of the mask plate and the inline energy;

[0037] The relationship can also be determined by the following steps: using the selected mask to perform photolithography experiments, recording the exposure energy (EE) of each experiment, measuring the wafer after lithography, determining the critical dimension (wafer CD) on the wafer, repeating the experiment several times; and drawing a graph of the mask critical dimension (mask CD) and the exposure energy (EE).

[0038] The relationship between the mask critical dimension (mask CD) and the exposure energy (EE) is established using a mathematical analysis method (for example, a regression analysis method). The relationship can be expressed as: EE = a*mask CD + b, where a and b are regression coefficients.

[0039] For example, the relationship is EE = -1.4871*mask CD + 100.86.

[0040] S3, according to the relationship, the inline overage condition is predicted, and the pilot run is not performed.

[0041] The critical dimension (mask CD) of the current mask is input, and the required exposure energy (EE) is calculated. According to the calculation result, the exposure parameter of the photolithography machine is set to ensure that the photolithography process meets the predicted overage condition, so that the pilot run is not required.

[0042] Optionally, the first embodiment is applicable to a 22 platform MX layer.

[0043] Optionally, the first embodiment is applicable to at least one of the following process platforms: a complementary metal-oxide-semiconductor transistor or a high-k gate with a critical dimension of less than 28 nm.

[0044] Optionally, the first embodiment is applicable to an immersion photolithography process.

[0045] Second embodiment

[0046] The application provides a computer-readable storage medium, which internally stores a computer program. When the computer program is executed, it is used to implement the steps of the semiconductor production line inline overage energy prediction method of the first embodiment.

[0047] The computer-readable medium includes both permanent and non-permanent, removable and non-removable media, which can store information by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include non-transitory computer-readable media, such as modulated data signals and carrier waves.

[0048] Unless otherwise defined, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It will also be understood that, unless expressly defined herein, terms such as those defined in a general dictionary shall be interpreted as having the meaning consistent with their meaning in the relevant field context, and not as having an idealized or overly formal meaning.

[0049] The present invention has been described in detail above through specific embodiments and examples, but these are not intended to limit the invention. Many modifications and improvements can be made by those skilled in the art without departing from the principles of the invention, and these should also be considered within the scope of protection of the present invention.

Claims

1. A method for predicting inline throughput capacity in semiconductor production lines, characterized in that, Includes the following steps: S1, Determine the critical dimensions of the photomask; S2, establish the relationship between the key dimensions of the mask and the inline throughput capacity; S3, based on the aforementioned relationship, predict the inline shipment conditions to achieve pilot run without performing the pilot run.

2. The semiconductor production line inline throughput prediction method as described in claim 1, characterized in that: The relationship is EE = a * mask CD + b, where a and b are specified coefficients.

3. The semiconductor production line inline throughput prediction method as described in claim 2, characterized in that: The relationship is EE = -1.4871 * mask CD + 100.

86.

4. The semiconductor production line inline throughput prediction method as described in claim 1, characterized in that: It is applicable to the MX layer of the 22 platform.

5. The semiconductor production line inline throughput prediction method as described in claim 1, characterized in that: It is applicable to at least one of the following process platforms: complementary metal-oxide-semiconductor transistors below 28nm or high-k dielectric gates.

6. The semiconductor production line inline throughput prediction method as described in claim 1, characterized in that: It is applicable to immersion lithography processes.

7. A computer-readable storage medium, characterized in that: It internally stores a computer program, which, when executed, implements the steps of the semiconductor production line inline throughput energy prediction method according to any one of claims 1-6.

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