Overlay Error Research Articles

Enhancing Parameters Tuning of Overlay Models with Ridge Regression: Addressing Multicollinearity in High-Dimensional Data

The extreme ultraviolet (EUV) photolithography process is a cornerstone of semiconductor manufacturing and operates under demanding precision standards realized via nanometer-level overlay (OVL) error modeling. This procedure allows the machine to anticipate and correct OVL errors before impacting the wafer, thereby facilitating near-optimal image exposure while simultaneously minimizing the overall OVL error. Such models are usually high dimensional and exhibit rigorous statistical phenomena such as collinearities that play a crucial role in the process of tuning their parameters. Ordinary least squares (OLS) is the most widely used method for parameters tuning of overlay models, but in most cases it fails to compensate for such phenomena. In this paper, we propose the usage of ridge regression, a widely known machine learning (ML) algorithm especially suitable for datasets that exhibit high multicollinearity. The proposed method was applied in perturbed data from a 300 mm wafer fab, and the results show reduced residuals when ridge regression is applied instead of OLS.

Lithography mask thermal and stress effect for the machine overlay compensation

With the continuous advancement of integrated circuit technology nodes, the degree of chip integration is increasing, and the requirements for critical dimensions and overlay errors are becoming more and more stringent. In recent years, near-field lithography technologies such as nanoimprint lithography and plasmonic lithography have made rapid progress; however, the challenge of compensating for their overlay has yet to be solved or systematic reports are lacking. This work offers an overlay compensation approach based on the theory of overlay and mask stress mechanics and thermodynamics by providing stress to the mask. The overlay analysis model and correction feedback mechanism based on mask compensation technology is carried out theoretically. This work establishes the relationship between the overlay compensation parameters and the mask stress by using strict calculation methods, quantitative characterization, and combining sensitivity analysis methods. Theoretical verification of various overlay distribution patterns demonstrates the efficiency of this feedback compensation strategy as well as the quantitative analytical calculation. It is verified that, under ideal conditions, the feedback technique may minimize the overlay error caused by mask thermal effects to ∼1.5 nm. This research presents a quantitative control mechanism for reducing overlay for near-field lithography, and it has substantial guiding implications for traditional lithography quantitative research on the influence of mask stress or temperature on overlay.

IMMERSIVE AUGMENTED REALITY APPLICATIONS IN JAW AND KNEE REPLACEMENT SURGERY: ACCURACY AND PROCESSING TIME RESULTS

In medicine and healthcare, augmented reality (AR) has been used by physicians during surgical procedures. It has provedhelpful in preoperative planning and procedure navigation by allowing them to display in-depth information and visualizedetails in real time during surgery, prioritizing patient safety and healthcare. Due to the critical nature of surgical procedures,extreme accuracy is required when using ar technology to maintain patients' health. A few years ago, ar faced severalchallenges and limitations in surgeries, such as noise in real-time images, cutting errors, navigation errors, wrong implantplacement, overlay errors, navigating narrow areas, geometric accuracy limitations, image alignment, image registration,and occlusion handling. This paper reviews several recently published articles exploring ar technology usage in jaw andknee replacement surgery, focusing on identifying the newest technologies, methods, and solutions for the abovementionedlimitations. Based on data collected from the published papers, the results were compared for each problem solved in eacharticle regarding accuracy and processing time.

Analysis and modeling of the influence of gate leakage current on threshold voltage and subthreshold swing in p-GaN gate AlGaN/GaN high electron mobility transistors

In this paper, the p-GaN gate AlGaN/GaN high electron mobility transistors (HEMTs) with varying combinations of gate metal work function and gate geometry are fabricated and investigate the influence of gate leakage current (IGS) on the threshold voltage (VTH) and subthreshold swing (SS). The unique dependence of VTH and SS on gate geometry for different metals is observed, which is different from traditional field-effect transistors. A novel hybrid physics model, consisting of the traditional capacitance divider model and hole injection model, is proposed to explain this phenomenon, and the results exhibit an excellent agreement with the experimental data. The holes traverse the gate/p-GaN Schottky barrier by thermal emission or tunneling and inject into the p-GaN layer, generating the IGS. Expanding upon the traditional capacitance divider model, a portion of the injected holes accumulate at the p-GaN/AlGaN interface and induce the corresponding electrons at the AlGaN/GaN heterojunction, which promotes channel conduction. Hence, the transfer curves display the correlation between IGS and VTH as well as SS. The results show that high IGS can alleviate the instability of VTH caused by the lithographic overlay error, and simultaneously optimize SS. This work offers a novel perspective for examining the turn-on mechanism of p-GaN HEMTs, thereby contributing to device design.

Distortion measurement of a lithography projection lens based on multichannel grating lateral shearing interferometry.

The optical distortion of the lithographic projection lens can reduce imaging quality and cause overlay errors in lithography, thus preventing the miniaturization of printed patterns. In this paper, we propose a technique to measure the optical distortion of a lithographic projection lens by sensing the wavefront aberrations of the lens. A multichannel dual-grating lateral shearing interferometer is used to measure the wavefront aberrations at several field points in the pupil plane simultaneously. Then, the distortion at these field points is derived according to the proportional relationship between the Z 2 and Z 3 Zernike terms (the tilt terms) and the image position shifts. Without the need for additional devices, our approach can simultaneously retrieve both the wavefront aberrations and the image distortion information. Consequently, it improves not only measurement speed and accuracy but also enables accounting for displacement stage positioning error. Experiments were conducted on a lithographic projection lens with a numerical aperture of 0.57 to verify the feasibility of the proposed method.

Using Outlier Control Technology with Feedforward Lithography to Address Die Shifting and Pattern Distortion Challenges in Fan-Out Panel-Level Packaging

Fan-out panel-level packaging (FOPLP) is a packaging technology able to meet the requirements of heterogeneous integration while reducing costs for manufacturers. However, FOPLP faces several significant process challenges. One of these is die shifting, which is a result of the reconstitution process in die-first FOPLP. Pattern distortion is another challenge, one caused by panel deformation in redistribution layer-first FOPLP. These issues cause die and patterns to move away from their nominal positions. If die shifting and pattern distortion are not well addressed during the lithography process, they will result in overlay errors and low overlay yield. Outlier control technology with feedforward lithography is proposed to address these die-shifting and pattern-distortion challenges. Outlier control is based on site-by-site corrections and uses an algorithm to recognize outliers in the substrate, eliminate their negative impacts and optimize overlay corrections to ensure good overlay yield. Additionally, feedforward lithography can further reduce the negative impact to throughput caused by the time lost addressing site-by-site corrections. In this study, we will discuss how die shifting and pattern distortion result in yield and throughput challenges for FOPLP. Then we will demonstrate outlier control technology with feedforward lithography on a test vehicle and how the integration of these two technologies addresses the challenges. We will also review the results of the demonstration and discuss the advantages of this strategy.

Registration of preoperative temporal bone CT-scan to otoendoscopic video for augmented-reality based on convolutional neural networks.

Patient-to-image registration is a preliminary step required in surgical navigation based on preoperative images. Human intervention and fiducial markers hamper this task as they are time-consuming and introduce potential errors. We aimed to develop a fully automatic 2D registration system for augmented reality in ear surgery. CT-scans and corresponding oto-endoscopic videos were collected from 41 patients (58 ears) undergoing ear examination (vestibular schwannoma before surgery, profound hearing loss requiring cochlear implant, suspicion of perilymphatic fistula, contralateral ears in cases of unilateral chronic otitis media). Two to four images were selected from each case. For the training phase, data from patients (75% of the dataset) and 11 cadaveric specimens were used. Tympanic membranes and malleus handles were contoured on both video images and CT-scans by expert surgeons. The algorithm used a U-Net network for detecting the contours of the tympanic membrane and the malleus on both preoperative CT-scans and endoscopic video frames. Then, contours were processed and registered through an iterative closest point algorithm. Validation was performed on 4 cases and testing on 6 cases. Registration error was measured by overlaying both images and measuring the average and Hausdorff distances. The proposed registration method yielded a precision compatible with ear surgery with a 2D mean overlay error of mm for the incus and mm for the round window. The average Hausdorff distance for these 2 targets was mm and mm respectively. An outlier case with higher errors (2.3 mm and 1.5 mm average Hausdorff distance for incus and round window respectively) was observed in relation to a high discrepancy between the projection angle of the reconstructed CT-scan and the video image. The maximum duration for the overall process was 18s. A fully automatic 2D registration method based on a convolutional neural network and applied to ear surgery was developed. The method did not rely on any external fiducial markers nor human intervention for landmark recognition. The method was fast and its precision was compatible with ear surgery.

Novel T-Shaped Gate Structure of AlGaN/GaN HEMTs on Si for RF Application

Due to the high electron saturation velocity and breakdown electric field, GaN-based high electron mobility transistors (HEMTs) have been widely used in high frequency and power application, such as telecommunication, satellite communication, and radar system [1]. Since first demonstration of AlGaN/GaN HEMTs in 1993 [2], the RF performance of these device has continuously improved by the progress on epitaxy and device scaling technology [3].The current gain cut-off frequency (fT) and the maximum oscillation frequency (fmax) from the small-signal equivalent circuit of the HEMT are derived by the following equations [4].From these equations, it can be concluded that in order to achieve high frequency operation, HEMTs should be designed with a T-shaped gate structure that simultaneously achieves low gate resistance (Rg) and low parasitic capacitance (Cgs and Cgd). However, there are complex fabrication processes to form the T-shaped gate. Typically, the T-shaped gate structure is implemented through electron beam lithography process using a tri-layer resist such as PMMA/PMGI/PMMA, which requires multiple exposures or developments. Multiple exposures can cause overlay errors that can significantly affect the T-shaped gate with smaller gate lengths [5]. Also, it is difficult to obtain an undercut structure that enables a good lift-off and guarantees a high yield due to the need for precise dose control. In addition, since the T-shaped gate has an unstable structure in which a narrow foot supports the weight of a wide head, the gate may collapse during a subsequent process.In this work, we fabricated a novel T-shaped gate using the negative e-beam resist HSQ, which offers a simple T-shaped gate fabrication process. The HSQ that was exposed to e-beam is located underneath the gate head and on both sides of the gate foot in our novel T-shaped gate design, providing a robust structure. The HSQ-assisted gate HEMTs exhibit comparable DC/RF performance compared to conventional T-shaped gate HEMTs. Acknowledgement This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MIST) (No. NRF-2021M3C13097672).

Enhanced Precision in Genioplasty: A Novel Intraoperative Spatial Repositioning Using Computer-Aided Design and Manufacturing Technology and a Holographic Mixed Reality Application

Genioplasty is performed for the orthognathic surgical correction of dentofacial deformities. This article reports a safe and accurate method for genioplasty combining a novel three-dimensional (3D) device with mixed reality (MR)-assisted surgery using a registration marker and a head-mounted display. Four types of devices were designed based on the virtual operation: a surgical splint with a connector; an osteotomy device; a repositioning device; and a registration marker. Microsoft HoloLens 2 and Holoeyes MD were used to project holograms created using computed tomography (CT) data onto the surgical field to improve the accuracy of the computer-aided designed and manufactured (CAD/CAM) surgical guides. After making an incision on the oral vestibule, the splint was fitted on the teeth and the osteotomy device was mounted at the junction site, placed directly on the exposed mandible bone surface. Temporary screws were fixed into the screw hole. An ultrasonic cutting instrument was used for the osteotomy. After separating the bone, a repositioning device was connected to the splint junction and bone segment, and repositioning was performed. At the time of repositioning, the registration marker was connected to the splint junction, and mandible repositioning was confirmed three-dimensionally through HoloLens 2 into the position specified in the virtual surgery. The rate of overlay error between the preoperative virtual operation and one-month postoperative CT data within 2 mm was 100%. CAD/CAM combined with MR enabled accurate genioplasty.

Mixed reality in surgical telepresence: a novel extended mean value cloning with automatic trimap generation and accurate alpha matting for visualization

The aim of this research is to propose an extended mean value cloning algorithm with automatic trimap generation and accurate alpha matting. This implementation improves the visualization accuracy of the merged video by reducing the discolored and smudging artefacts of the remote surgeon’s boundary. It also makes the merge robust for the illumination changes by taking less processing time in real time surgery. The proposed system uses automatic trimap generation from the source video for accurate foreground extraction. Extended mean value cloning with gradient mixing is then applied for the cloning with optimized alpha matting for accurate and realistic video composition. The proposed system improved the visualization accuracy by providing almost 99.7% visibility of the pixels compared to the state-of-the-art solution, which provides 99.1% visibility of pixels. The overlay error was reduced from 0.93 mm to 0.63 mm. The processing time was also reduced. The proposed solution processed 8 frames per second, which is less time than the state-of-the-art solution, which processed 5 frames per second. The extended mean value cloning smooths the differences that presented in the target and source frames for seamless and realistic blending of pixels. The automatic trimap generation reduced the risk of false foreground selection and the generated optimal trimaps improved the alpha matte quality, which is optimized to reduce the smudging artefacts completely and to produce accurate visualization of the final merged image.

Enhanced and Efficient Guiding Template Design for Lamellar DSA With Graph Monomorphism

Lamellar directed self-assembly (DSA) technology in combination with the self-aligned via (SAV) process has emerged as a novel and promising choice for via/contact layer fabrication, where a via between Metal-x and Metal-(x+1) is generated at the intersection of a wire segment on Metal-(x+1) and a rectangular and perpendicular guiding template. Compared to the highly investigated cylindrical DSA, lamellar DSA does not suffer from the overlay error of generated holes and thus can have better yield, and it also benefits from the better flexibility of various via pitches a single template can produce. A state-of-the-art work has addressed the guiding template design problem for the new process, and an integer linear programming (ILP) formulation that can optimally solve the problem as well as a simple heuristic approach are proposed. However, solving the ILP formulation is time-consuming, and the heuristic method suffers from unignorable degradation in solution quality due to several algorithm deficiencies. In this paper, we propose an enhanced and efficient template design algorithm flow for the lamellar DSA and SAV process by using graph monomorphism for pattern conflict check in multiple patterning lithography. Experimental results show that the proposed flow can greatly reduce the numbers of conflicts and short templates and is almost as efficient as the existing heuristic approach.

Multi-spectral snapshot diffraction-based overlay metrology.

Diffraction-based overlay (DBO) metrology has been successfully introduced to deal with the tighter overlay control in modern semiconductor manufacturing. Moreover, DBO metrology typically needs to be performed at multiple wavelengths to achieve accurate and robust measurement in the presence of overlay target deformations. In this Letter, we outline a proposal for multi-spectral DBO metrology based on the linear relation between the overlay errors and the combinations of off-diagonal-block Mueller matrix elements ΔM = Mij - ( - 1)jMji (i = 1, 2; j = 3, 4) associated with the zeroth-order diffraction of overlay target gratings. We propose an approach that can realize snapshot and direct measurement of ΔM over a broad spectral range without any rotating or active polarization component. The simulation results demonstrate the capability of the proposed method for multi-spectral overlay metrology in a single shot.

On the origin and evolution of hotspots in multipatterning processes

Understanding the origins and propagation of defects and hotspots in patterning processes used for semiconductor fabrication is of paramount importance in managing yield. In this paper, results from physics-based simulators to model lithography and dry etch processes are presented and compared to experimental results. These models are used to study different types of hotspots and defects observed in a litho-etch-litho-etch (LELE) multipatterning process. At each pass of the LELE flow, patterns are printed into a SiO2 collecting layer using a trilayer film stack comprised of a negative tone photoresist layer, a spin-on-glass layer (SOG), and a spin-on-carbon layer (SOC). After both passes of the LELE process, the patterns in the SiO2 collecting layer will be transferred to a TiN hardmask prior to final etch into an underlying dielectric. The SOG and SiO2 layers are etched using fluorocarbon plasma, while the SOC layer is etched with an H2/N2 plasma generated in a capacitively coupled plasma source. A pinching hotspot is observed during the single litho-etch pass in a region where two features are placed very close and the image contrast is low. However, for some lithography process conditions, this hotspot is rectified by subsequent etch steps and does not always transfer as a defect into the SiO2 layer. The quenching of the hotspot occurs primarily during the etching of the SOC layer due to the aspect ratio-dependent etching (ARDE) effect. A bridging hotspot is also observed at lithography during the single litho-etch pass at high exposure doses. This hotspot, on the other hand, is exacerbated by the etch steps because of the ARDE effect. Hotspots are also identified that originate from overlay errors between photomasks exposed during first and second passes of the LELE process. The etch bias generated during etching of the SOG layer is crucial to ensure that the overlay-related hotspot does not translate to the SiO2 layer. The extent of etch bias in the SOG etch step is critical and can be tuned by adjusting the neutral to ion flux ratio during that etch step. Increasing the flux ratio improves the process window for the overlay defect; however, when the ratio is higher than approximately 20% of the nominal value, a different defect type is formed in the SOG layer due to the inverse ARDE effect that propagates downstream to the SiO2 layer.

Designing Highly Precise Overlay Targets for Asymmetric Sidewall Structures Using Quasi-Periodic Line Widths and Finite-Difference Time-Domain Simulation.

The present study introduces an optimized overlay target design to minimize the overlay error caused by asymmetric sidewall structures in semiconductor manufacturing. To achieve this goal, the overlay error formula was derived by separating the asymmetric bottom grating structure into symmetric and asymmetric parts. Based on this formula, it was found that the overlay target design with the linewidth of the bottom grating closed to the grating period could effectively reduce the overlay error caused by the sidewall asymmetry structure. Simulation results demonstrate that the proposed design can effectively control the measurement error of different wavelengths within ±0.3 nm, even under varying sidewall angles and film thicknesses. Overall, the proposed overlay target design can significantly improve the overlay accuracy in semiconductor manufacturing processes.

HoloLens augmented reality system for transperineal free-hand prostate procedures.

An augmented reality (AR) system was developed to facilitate free-hand real-time needle guidance for transperineal prostate (TP) procedures and to overcome the limitations of a traditional guidance grid. The HoloLens AR system enables the superimposition of annotated anatomy derived from preprocedural volumetric images onto a patient and addresses the most challenging part of free-hand TP procedures by providing real-time needle tip localization and needle depth visualization during insertion. The AR system accuracy, or the image overlay accuracy ( ), and needle targeting accuracy ( ) were evaluated within a 3D-printed phantom. Three operators each used a planned-path guidance method ( ) and free-hand guidance ( ) to guide needles into targets in a gel phantom. Placement error was recorded. The feasibility of the system was further evaluated by delivering soft tissue markers into tumors of an anthropomorphic pelvic phantom via the perineum. The image overlay error was , and needle targeting error was . The planned-path guidance placements showed similar error compared to the free-hand guidance ( versus , ). The markers were successfully implanted either into or in close proximity to the target lesion. The HoloLens AR system can provide accurate needle guidance for TP interventions. AR support for free-hand lesion targeting is feasible and may provide more flexibility than grid-based methods, due to the real-time 3D and immersive experience during free-hand TP procedures.

Machine Learning-Based Edge Placement Error Analysis and Optimization: A Systematic Review

As the semiconductor manufacturing process is moving towards the 3 nm node, there is a crucial need to reduce the edge placement error (EPE) to ensure proper functioning of the integrated circuit (IC) devices. EPE is the most important metric that quantify the fidelity of fabricated patterns in multi-patterning processes, and it is the combination of overlay errors and critical dimension (CD) errors. Recent advances in machine learning have enabled many new possibilities to improve the performance and efficiency of EPE optimization techniques. In this paper, we conducted a survey of recent research work that applied machine learning/ deep learning techniques for the purposes of enhancing virtual overlay metrology, reducing overlay error, and improving mask optimization methods for EPE reduction. Thorough discussions about the objectives, datasets, input features, models, key findings, and limitations are provided. In general, the results of the review work show a great potential of machine learning techniques in aiding the improvement of EPE in the field of semiconductor manufacturing.

Robust control of maximum photolithography overlay error in a pattern layer

This paper presents a novel method for control of overlay errors in photolithography processes in semiconductor manufacturing. It minimizes the largest overlay error across all measurement markers on a pattern layer, and this minimization is done for the worst-case scenario regarding bounded process bias and modeling noise terms. This large-scale robust optimization problem was formulated as a linear program which can be solved within seconds to generate optimal control commands. Simulations based on wafer data obtained from a major 300 mm semiconductor fab illustrate consistent and significant advantages of this approach over the benchmark control strategies.

(Invited) Nm-Scale Patterns and Selectivity: A Blessing or a Curse

Area-selective deposition (ASD) is a promising technique for semiconductor device manufacturing. The replication of nanoscale patterns by ASD can simplify device fabrication process flows by reducing the number of lithography, etch and chemical-mechanical polishing steps. In addition, ASD could eliminate pattern overlay errors. ASD is of special interest as device dimensions scale and has recently been shown as viable approach for the fully self-aligned via, to enable interconnect scaling beyond the 3 nm node [1]. However, the dependence of the selectivity of ALD and CVD processes on the patterning process and pattern dimensions is poorly documented. This aspect will be investigated in the current presentation. We will discuss the fundamental mechanisms of ALD growth mechanisms and how they influence selectivity. Next, we will discuss an example of Ru ASD with defect mitigation in nm-scale patterns on full 300-mm wafers [2].[1] Chen et al., IEDM21, 486-489.[2] Clerix et al., Adv. Mater. Interfaces 2021, 2100846.

713 The Application of Artificial Intelligence for Digital Imaging in the Operating Theatre: A Systematic Review and Narrative Synthesis

Abstract Introduction Promising applications of artificial intelligence (AI) in healthcare are emerging. This systematic review aims to identify and synthesise applications of digital-imaging AI in surgery and inform future work. Method Systematic database searches (Medline, Embase, CENTRAL) were undertaken. Studies concerning digital-imaging AI within the operating theatre were identified from title and abstract screening. Selection was further refined to identify video-based AI models with direct supportive output to the surgeon within the operating theatre. Results 48 studies were included. Studies spanned 13 specialty groupings, with n=42 utilising a pre-specified dataset and the remaining n=6 using AI with human participants. The most common field using AI was urology (n=9 studies). Applications were most commonly for navigation and visualisation support (n=26 studies across 10 surgical specialties) and AI-based intelligent detection systems, intended to identify and highlight useful surgical information using computer-vision pattern recognition (n=18 articles across n=6 specialties). Other applications included video-processing algorithms (n=3 studies across 2 specialties), and a novel imaging modality for visualising blood perfusion (n=1 study), proposing operating theatre-based application. High-performance models were identified across a range of pathologies. This manifested as minimal overlay errors and acceptable frame rates for navigation tools, and high diagnostic performance for detection systems (determined by area-under-the-receiver-operating-characteristic-curve, sensitivity/specificity, negative/positive predictive values). Conclusions There is evidence to suggest AI for intraoperative surgeon-support has potential, particularly through augmented-reality navigation and AI-enabled information awareness. Further research and optimisations are required to produce clinically robust models, which remain high-performance despite case variability. Such AI may support improved surgical access, efficiency, and outcomes.

Errata to "Parallax Free Registration for Augmented Reality Optical See-Through Displays in the Peripersonal Space" [1] (DOI: 10.1109/TVCG.2020.3021534).

In the original article, there was a mistake in the content of Table 2 page 8 column 1 as published. The values of the mean and standard deviation of the virtual-to-real overlay error in visual angles, which are reported for different checkerboard distances, are to be corrected. Due to a typing error within the data analysis code, we mistakenly considered an erroneous value of the average angular resolution for the eye-replacement camera. This scale factor is used to pass from the original registration errors (expressed in pixel) to the angular registration errors (in arcmin). The value of the average angular resolution is $\approx 2.67$≈2.67 arcmin/pixel. The corrected Table 2 appears below.