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Overlay (OVL) has become a critical process control and metrology challenge for current and future process nodes of logic as well as memory devices. Especially with the advent of EUV lithography and the accompanying use of two lithographical techniques (EUV and 193nm immersion) for patterning of critical layers, there is an increased need for identifying variability and its root cause in the overlay signatures. Current variability analysis uses pre-defined models mostly related to describe variability and allocating them in standard categories. These models are usually tied to the applicable exposure capabilities. As the EUV to immersion layers undergo exposure with vastly different conditions, there is a need to analyze OVL without associating to specific models. In this paper, we report on a novel model-less method for analyzing overlay data containing complex intra-field signatures. The method can identify and quantify intra-field signatures variation within a wafer as well as across wafers. These signatures enable root cause analysis of contributors to overlay variability. We applied the method on data sets of long-term overlay data of an EUV to a 193-immersion layer. While, several applications of the method with respect to identifying exposure conditions are demonstrated specific to the EUV to immersion layer, it should be noted that the method is universally applicable to any imaging wavelength for current and reference layer.

The importance of traditionally acceptable sources of variation has started to become more critical as semiconductor technologies continue to push into smaller technology nodes. New metrology techniques are needed to pursue the process uniformity requirements needed for controllable lithography. Process control for lithography has the advantage of being able to adjust for cross-wafer variability, but this requires that all processes are close in matching between process tools/chambers for each process. When this is not the case, the cumulative line variability creates identifiable groups of wafers1 . This cumulative shape based effect is described as impacting overlay measurements and alignment by creating misregistration of the overlay marks. It is necessary to understand what requirements might go into developing a high volume manufacturing approach which leverages this grouping methodology, the key inputs and outputs, and what can be extracted from such an approach. It will be shown that this line variability can be quantified into a loss of electrical yield primarily at the edge of the wafer and proposes a methodology for root cause identification and improvement. This paper will cover the concept of wafer shape based grouping as a diagnostic tool for overlay control and containment, the challenges in implementing this in a manufacturing setting, and the limitations of this approach. This will be accomplished by showing that there are identifiable wafer shape based signatures. These shape based wafer signatures will be shown to be correlated to overlay misregistration, primarily at the edge. It will also be shown that by adjusting for this wafer shape signal, improvements can be made to both overlay as well as electrical yield. These improvements show an increase in edge yield, and a reduction in yield variability.

Process-induced overlay errors from outside the litho cell have become a significant contributor to the overlay error budget including non-uniform wafer stress. Previous studies have shown the correlation between process-induced stress and overlay and the opportunity for improvement in process control, including the use of patterned wafer geometry (PWG) metrology to reduce stress-induced overlay signatures. Key challenges of volume semiconductor manufacturing are how to improve not only the magnitude of these signatures, but also the wafer to wafer variability. This work involves a novel technique of using PWG metrology to provide improved litho-control by wafer-level grouping based on incoming process induced overlay, relevant for both 3D NAND and DRAM. Examples shown in this study are from 19 nm DRAM manufacturing.

Ultrasound computed tomography (USCT) holds great promise for improving the detection and management of breast cancer. Because they are based on the acoustic wave equation, waveform inversion-based reconstruction methods can produce images that possess improved spatial resolution properties over those produced by ray-based methods. However, waveform inversion methods are computationally demanding and have not been applied widely in USCT breast imaging. In this work, source encoding concepts are employed to develop an accelerated USCT reconstruction method that circumvents the large computational burden of conventional waveform inversion methods. This method, referred to as the waveform inversion with source encoding (WISE) method, encodes the measurement data using a random encoding vector and determines an estimate of the speed-of-sound distribution by solving a stochastic optimization problem by use of a stochastic gradient descent algorithm. Computer-simulation studies are conducted to demonstrate the use of the WISE method. Using a single graphics processing unit card, each iteration can be completed within 25 seconds for a 128 × 128 mm2 reconstruction region. The results suggest that the WISE method maintains the high spatial resolution of waveform inversion methods while significantly reducing the computational burden.

Iterative image reconstruction algorithms can model complicated imaging physics, compensate for imperfect data acquisition systems, and exploit prior information regarding the object. Hence, they produce higher quality images than do analytical image reconstruction algorithms. However, three-dimensional (3D) iterative image reconstruction is computationally burdensome, which greatly hinders its use with applications requiring a large field-of-view (FOV), such as breast imaging. In this study, an improved GPU-based implementation of a numerical imaging model and its adjoint have been developed for use with general gradient-based iterative image reconstruction algorithms. Both computer simulations and experimental studies are conducted to investigate the efficiency and accuracy of the proposed implementation for optoacoustic tomography (OAT). The results suggest that the proposed implementation is more than five times faster than the previous implementation.

In this work, we introduce an improved prototype of the imaging system that combines three-dimensional optoacoustic tomography (3D-OAT) and laser ultrasound tomography slicer (2D-LUT) to obtain coregistered maps of tissue optical absorption and speed of sound (SOS). The imaging scan is performed by a 360 degree rotation of a phantom/mouse with respect to a static arc-shaped array of ultrasonic transducers. A Q-switched laser system is used to establish optoacoustic illumination pattern appropriate for deep tissue imaging with a tunable (730-840 nm) output wavelengths operated at 10 Hz pulse repetition rate. For the LUT slicer scans, the array is pivoted by 90 degrees with respect to the central transducers providing accurate registration of optoacoustic and SOS maps, the latter being reconstructed using waveform inversion with source encoding (WISE) technique. The coregistered OAT-LUT modality is validated by imaging a phantom and a live mouse. SOS maps acquired in the imaging system can be employed by an iterative optoacoustic reconstruction algorithm capable of compensating for acoustic wavefield aberrations. The most promising applications of the imaging system include 3D angiography, cancer research, and longitudinal studies of biological distributions of optoacoustic contrast agents (carbon nanotubes, metal plasmonic nanoparticles, fluorophores, etc.).

In this work we introduce an improved prototype of three-dimensional imaging system that combines optoacoustic tomography (OAT) and laser ultrasound tomography (LUT) to obtain coregistered maps of tissue optical absorption and speed of sound (SoS). The OAT scan is performed by a 360 degree rotation of a mouse with respect to an arc-shaped array of ultrasonic transducers. A Q-switched laser system is used to establish optoacoustic illumination pattern appropriate for deep tissue imaging with a tunable (730-840 nm) output wavelengths operated at 10 Hz pulse repetition rate. A 532 nm wavelength output, being mostly absorbed within a narrow superficial layer of skin, is used to outline the visualized biological object. Broadband laser ultrasound emitters are arranged in another arc pattern and are positioned opposite and orthogonal to the array of transducers. This imaging geometry allows reconstruction of volumes that depict SoS distributions from the measured time of flight data. The reconstructed LUT images can subsequently be employed by an optoacoustic reconstruction algorithm to compensate for acoustic wavefield aberration and thereby improve accuracy of the reconstructed images of the absorbed optical energy. The coregistered OAT-LUT imaging is validated in a phantom and live mouse using a single-slice system prototype.

In this work, we investigate a novel reconstruction method for laser-induced ultrasound computed tomography (USCT) breast imaging that circumvents limitations of existing methods that rely on ray-tracing. There is currently great interest in developing hybrid imaging systems that combine optoacoustic tomography (OAT) and USCT. There are two primary motivations for this: (1) the speed-of-sound (SOS) distribution reconstructed by USCT can provide complementary diagnostic information; and (2) the reconstructed SOS distribution can be incorporated in the OAT reconstruction algorithm to improve OAT image quality. However, image reconstruction in USCT remains challenging. The majority of existing approaches for USCT breast imaging involve ray-tracing to establish the imaging operator. This process is cumbersome and can lead to inaccuracies in the reconstructed SOS images in the presence of multiple ray-paths and/or shadow zones. To circumvent these problems, we implemented a partial differential equation-based Eulerian approach to USCT that was proposed in the mathematics literature but never investigated for medical imaging applications. This method operates by directly inverting the Eikonal equation without ray-tracing. A numerical implementation of this method was developed and compared to existing reconstruction methods for USCT breast imaging. We demonstrated the ability of the new method to reconstruct SOS maps from TOF data obtained by a hybrid OAT/USCT imager built by our team.

We developed the ¯rst prototype of dual-modality imager combining optoacoustic t omography (OAT) and laserultrasound tomography (UST) using computer models followed by experimental va lidation. The system designedfor preclinical biomedical research can concurrently yield images depicting both the abs orbed optical energydensity and acoustic properties (speed of sound) of an object. In our design of the UST imager, we seek toreplace conventional electrical generation of ultrasound waves by laser-induced ultra sound (LU). While earlierstudies yielded encouraging results [Manohar, et al., Appl. Phys. Lett, 131911, 2 007], they were limited totwo-dimensional (2D) geometries. In this work, we conduct computer-simulation st udies to investigate di®erentdesigns for the 3D LU UST imager. The number and location of the laser ultrasound emitters, which areconstrained to reside on the cylindrical surface opposite to the arc of detectors, are optimized. In addition tothe system parameters, an iterative image reconstruction algorithm was o ptimized. We demonstrate that highquality volumetric maps of the speed of sound can be reconstructed when only 32 emitt ers and 128 receivingtransducers are employed to record time-of-°ight data at 360 tomographic view ang les. The implications of theproposed system for small animal and breast-cancer imaging are discussed.Keywords: Laser ultrasound tomography, optoacoustic tomography, iterative ima ge reconstruction

In this work, we introduce a novel three-dimensional imaging system for in vivo high-resolution anatomical and functional whole-body visualization of small animal models developed for preclinical or other type of biomedical research. The system (LOUIS-3DM) combines a multi-wavelength optoacoustic and ultrawide-band laser ultrasound tomographies to obtain coregistered maps of tissue optical absorption and acoustic properties, displayed within the skin outline of the studied animal. The most promising applications of the LOUIS-3DM include 3D angiography, cancer research, and longitudinal studies of biological distribution of optoacoustic contrast agents (carbon nanotubes, metal plasmonic nanoparticles, etc.).