Characterizing interlayer edge placement with SEM contours

Weisbuch, François; Schatz, Jirka; Ruhm, Matthias

doi:10.1117/1.jmm.18.2.021203

Cited by 6 publications

(8 citation statements)

References 26 publications

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“…The definition of the EPE has been discussed extensively 16 – 18 To improve the clarity, the EPE is defined as the deviation of the measured edge-to-edge distance from the design value in this work. Figure 9 displays the statistic histogram for D 1 to D 8 and the simulated results after the application of the above three models.…”

Section: Resultsmentioning

confidence: 99%

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Process window improvement for fin cut layer in self-aligned double-patterning process based on backscattered electron imaging

Zhang

Bian

Liu

et al. 2022

J. Micro/Nanopattern. Mats. Metro.

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Background: The self-aligned double-patterning (SADP) process is being used extensively to overcome the lithographic resolution limit in the manufacture of integrated circuits. One use case is fin definition in a fin field-effect transistor. Fin cut layers are applied to modify the fins to the requirements of the device designs.Aim: The traditional secondary electron (SE) imaging exhibits a disadvantage in the process controlling the fin cut layers, and fin damage defects were observed. This work aims to improve the monitoring and controlling capabilities for the process quality of fin cut layers.Approach: A specially designed fin cut process flow and a backscattered electron (BSE) imaging technique are applied to check the process quality. The patterns formed through the fin cut etch and the fin structures are identified and measured simultaneously in one BSE image.Results: By measuring the edge-to-edge distance, pitch walking (PW) of fins, and overlay (OV), the root cause of the fin damage is revealed. The linear fitting model and third-order fitting model are applied to reduce the edge placement error (EPE). The edge distance protecting the "at risk" fin is enlarged from 5.6 to 11.6 nm. The range of the distance is reduced from 11.6 to 8.1 nm, and the improvement in standard deviation is about 33%. Conclusions:This work shows the capability of the BSE imaging technique in the characterization of fin cut layers and the potential in process window improvement restricted to fin damage defects.

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Section: Resultsmentioning

confidence: 99%

“…To evaluate the process of the fin cut layer, the edge placement error (EPE) metric is introduced, and the contributions of the above process indexes to the EPE are analyzed 16 – 18 The abnormal phenomena observed in CD, OV, and PW are corrected by linear and high-order fitting models to improve the process window.…”

Section: Introductionmentioning

confidence: 99%

Process window improvement for fin cut layer in self-aligned double-patterning process based on backscattered electron imaging

Zhang

Bian

Liu

et al. 2022

J. Micro/Nanopattern. Mats. Metro.

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“…As it is, the contour extraction results in the transformation of the grayscale image into a list of shapes or polygons that can be further processed to produce standard, new or advantageous metrics. SEM contour metrology brought new opportunities not only in OPC modeling but in cycle time improvement [13], process assessment [14][15][16][17][18], overlay metrology [19][20] or defect inspection [21].…”

Section: Introductionmentioning

confidence: 99%

Can remote SEM contours be used to match various SEM tools in fabs?

Pradelles

Perraud

Sezestre

et al. 2023

Metrology, Inspection, and Process Control XXXVII

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CD-SEM is one of the workhorse metrology tools for evaluating the patterning performances in the semiconductor industry. With the continuous shrink of device feature sizes, measurement uncertainty, of such devices should improve accordingly, including tool-to-tool matching. Great efforts are made in fabs to ensure matching between CD-SEMs. Basically, there are two approaches : tool matching based on statistical CD measurements and tool matching based on physical tool parameters. The first methods require long recipe run on each tool for data collection while the second methods require dedicated maintenance tool time. In parallel, the emergence of SEM contour metrology brought new opportunities, for example in OPC modeling, process assessment or overlay metrology. Recently, a step has been made to demonstrate that offline SEM contour metrology can be matched with standard CD-SEM. In this paper we evaluate the possibility to use SEM contour metrology to perform a remote CD matching on images coming from two different CD-SEM. A large set of patterns of various dimensions and shapes (both 1D and 2D) is imaged with two different CD-SEM after etch process step. For each image the contours are extracted using a remote software. A matching model is calibrated to match contour measurements of the same pattern imaged with the two CD-SEMs. The matching model can be calibrated using either one or both inline SEM measurement or using additional metrology data (typically AFM measurement or any reference metrology measurement). The matching model parameters include both parameters for the contour extraction calibration and measurement matching parameters. Two modeling approaches are compared : one matching model averaging multiple measurement matching sites and a multiple (per pattern type) contour calibrations/ measurement matching sites model. These different matching models are assessed using as main metrics the remaining CD difference between SEM contour measurements on images coming from the two CD-SEM (ΔCDmatching) and TMU analysis. We show that an overall ΔCDmatching variability of 0.6 nm and a TMU below 2 nm can be obtained with the dataset. We evaluated a strategy to achieve matching of two CD-SEM using a remote contour extraction solution and a matching model.

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“…SEM-contours are a very rich data source for any machine learning application [7,8]. In addition, SEM-contours from different images can be combined to characterize the evolution of a pattern upon different process conditions, like microlens reflow [9], litho-etch bias [10] or perform in-situ overlay between patterns measured on different layers during the manufacturing [11]. Another advantage is that the contours represented with polygons can be merged with design.…”

Section: Introductionmentioning

confidence: 99%

“…Another advantage is that the contours represented with polygons can be merged with design. Hence, the nature of the contours offers new metrics for the metrology like Edge Placement Error [11], the measure of a pattern shift [12] or even characterization of pattern topography by considering contours measured at different heights in a material [13]. Even more fascinating applications are to come that stress the necessity to address the many challenges of handling SEM-contours, like edge extraction complexity with noisy or multi-pattern images, like contour post processing to align, clean and average contours, like bringing new concepts for pattern sampling and dedicated test pattern generation in the context of model calibration…An additional challenge, that we propose to discuss specifically in this work, is the question of the matching of SEM-contour to standard SEM-CD [10,14].…”

Section: Introductionmentioning

confidence: 99%

Investigating SEM-contour to CD-SEM matching

Weisbuch

Schatz

Mattick

et al. 2021

Metrology, Inspection, and Process Control for Semiconductor Manufacturing XXXV

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Background:The control and the characterization of semiconductor very fine devices on a wafer are commonly performed by mean of a scanning electron microscope (SEM) to derive a critical dimension (CD) from a pair of parallel edges extracted from the images. However, this approach is often not very reliable when dealing with complex 2D patterns. An alternative is to use SEM contour technique to extract all the edges of the image. This method is more versatile and robust but before being implemented in a manufacturing environment, it must demonstrate that it can be matched well with traditional CD-SEM. Aim:The objective of this work is to present a method to evaluate and optimize the CD matching between a reference standard SEM-CD and SEM-Contours. Approach:After describing the metric used to assess the matching performance, we propose to screen some important influent parameters to give an evaluation of the best matching that we achieved with our experimental data. Results:After optimizing the matching calibration parameters and optimizing the selection of the best anchor pattern for the matching we could achieve a 3s-Total Measurement Uncertainty of 0.8 nm and 3.2 nm for 1D and 2D patterns. Conclusions:We established a method to achieve good matching performance that should facilitate the introduction of SEM contour in a manufacturing environment.

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Characterizing interlayer edge placement with SEM contours

Cited by 6 publications

References 26 publications

Process window improvement for fin cut layer in self-aligned double-patterning process based on backscattered electron imaging

Process window improvement for fin cut layer in self-aligned double-patterning process based on backscattered electron imaging

Can remote SEM contours be used to match various SEM tools in fabs?

Investigating SEM-contour to CD-SEM matching

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