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3D scanning technology can be used to analyze gross damages to packages subjected to regulatory testing.
MEMS fabrication processes are as diverse as their applications.
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The measurement accuracy is becoming one of the major components that have to be controlled in order to guarantee sufficient production yield. Already at the R and D level, we have to come up with the accurate measurements of sub-40 nm dense trenches and contact holes coming from 193 immersion lithography or E-Beam lithography. Current production CD (Critical Dimension) metrology techniques such as CD-SEM (CD-Scanning Electron Microscope) and OCD (Optical Critical Dimension) are limited in relative accuracy for various reasons (i.e electron proximity effect, outputs parameters correlation, stack influence, electron interaction with materials...). Therefore, time for R and D is increasing, process windows degrade and finally production yield can decrease because you cannot manufactured correctly if you are unable to measure correctly. A new high volume manufacturing (HVM) CD metrology solution has to be found in order to improve the relative accuracy of production environment otherwise current CD Metrology solution will very soon get out of steam.In this paper, we will present a potential Hybrid CD metrology solution that smartly tuned 3D-AFM (3D-Atomic Force Microscope) and CD-SEM data in order to add accuracy both in R and D and production. The final goal for 'chip makers' is to improve yield and save R and D and production costs through real-time feedback loop implement on CD metrology routines. Such solution can be implemented and extended to any kind of CD metrology solution. In a 2{sup nd} part we will discuss and present results regarding a new AFM3D probes breakthrough with the introduction of full carbon tips made will E-Beam Deposition process. The goal is to overcome the current limitations of conventional flared silicon tips which are definitely not suitable for sub-32 nm nodes production.
We propose a superresolution technique to resolve dense clusters of blinking emitters. The method relies on two basic assumptions: the emitters are statistically independent, and a model of the imaging system is known. We numerically analyze the performance limits of the method as a function of the emitter density and the noise level. Numerical simulations show that five closely packed emitters can be resolved and localized to a precision of 17nm. The experimental resolution of five quantum dots located within a diffraction limited spot confirms the applicability of this approach.
Measuring the mechanical coupling and rigidity of a large apparatus presents unique challenges for 3D metrology. In this case the motion of well separated points attached to a rotor blade must be rapidly and repeatedly measured and the resulting data synchronized. This presentation describes the methodology and results for the mechanical coupling test of the magnetic field mapping system (FMS) for the Mu2e experiment at Fermi National Accelerator Laboratory (Fermilab). Three laser trackers, 2 API Radians and an API TIII, simultaneously measured the position of three cylindrical corner cube reflectors mounted on the FMS while the system was in motion and after coming to rest. The laser trackers took measurements at 83Hz for the T3 and 100Hz for the Radians, with fine spatial resolution, resulting in over 20,000 points measured per instrument in observation cycle. The laser tracker hardware and utilized software are unable to synchronize the three independent data streams directly during the measurement process. Instead a custom software program was developed to perform this synchronization of the data sequences during post-processing using features of the targets motion common to all three fiducial locations.
X-ray phase-contrast imaging has become indispensable for visualizing samples with low absorption contrast. In this regard, speckle-based techniques have shown significant advantages in spatial resolution, phase sensitivity, and implementation flexibility compared with traditional methods. However, the computational cost associated with data inversion has hindered their wider adoption. By exploiting the power of deep learning, we developed a speckle-based phase-contrast imaging neural network (SPINNet) that significantly improves the imaging quality and boosts the phase retrieval speed by at least 2 orders of magnitude compared to existing methods. To achieve this performance, we combined SPINNet with a coded-mask-based technique, an enhanced version of the speckle-based method. Using this scheme, we demonstrate the simultaneous reconstruction of absorption and phase images on the order of 100 ms, where a traditional correlation-based analysis would take several minutes even with a cluster. In addition to significant improvement in speed, our experimental results show that the imaging and phase retrieval quality of SPINNet outperform existing single-shot speckle-based methods. Furthermore, we successfully demonstrate SPINNet application in x-ray optics metrology and 3D x-ray phase-contrast tomography. Our result shows that SPINNet could enable many applications requiring high-resolution and fast data acquisition and processing, such as in situ and in operando 2D and 3D phase-contrast imaging and real-time at-wavelength metrology and wavefront sensing.
The principle of structured light and triangulation is used in a wide range of 3D optical metrology applications, such as mechanical engineering, industrial monitoring, computer vision, and biomedicine. Among a multitude of techniques based on this principle, phase shifting pro lometry (PSP) plays a dominant role due to its high attainable measurement accuracy, spatial resolution, and data density. Over the past few decades, many PSP algorithms have been proposed in the literature in order to achieve higher measurement accuracy, lower pattern count, and/or better robustness to different error sources. Besides, many unconventional PSP codification techniques address the problem of absolute phase recovery with few projected patterns, allowing for high-efficiency measurement of objects containing isolated regions or surface discontinuities. In this paper, we present an overview of these state-of-the-art phase shifting algorithms for implementing 3D surface pro lometry. Typical error sources in phase measure- ment for a phase shifting system are discussed, and corresponding solutions are reviewed. The advantages and drawbacks of different PSP algorithms are also summarized to provide a useful guide to the selection of the most appropriate phase shifting technique for a particular application.
At the same time as research in 3D TSV technology is advancing quickly, the analytical techniques used in the evaluation of 3D stacks must also advance in capability. Microscopy techniques for which silicon is opaque such as scanning acoustic microscopy (SAM) and confocal infrared (IR) microscopy are capable of inspecting the interface between bonded wafer pairs, while high resolution X-ray computed tomography (XCT) is used to detect voids in TSVs. With nano-XCT, voids in copper TSVs with sub-100 nm size can be visualized. For more detailed failure characterization, a target Focused Ion Beam (FIB) cross-section through the localized region of interest (defect) and subsequent scanning electron microscopy (SEM) imaging is proposed. Currently, the most important requirement is to reduce the so-called time-to-data, e. g. for defect localization using nano-XCT and for cross-section characterization.
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High-accuracy surface metrology is vitally important in manufacturing ultra-high-quality free-form mirrors designed to manipulate x-ray light with nanometer-scale wavelengths. The current and potential capabilities of x˗ray mirror manufacturing are limited by inherent imperfections of the integrated metrology tools. Metrology tools are currently calibrated with super-polished flat test-standard/reference mirrors. This is acceptable for fabrication of slightly curved x-ray optics. However, for even moderately curved aspherical x-ray mirrors the flat-reference calibration is not sufficiently accurate. For micro-stitching interferometry developed for surface measurements with curved x-ray mirrors, the tool aberration errors are known to be transferred into the optical surface topography of x-ray mirrors. Our approach to improving metrology is to thoroughly calibrate the measuring tool and apply the results of the calibration to deconvolution of the measured data. Here we explore the application of a recently developed technique for calibrating the instrument transfer function (ITF) of 3D optical surface profilers to metrology with significantly curved x-ray optics. The technique, based on test standards patterned with two-dimensional (2D) binary pseudo-random arrays (BPRAs), employs the unique properties of the BPRA patterns in the spatial frequency domain. The inherent 2D power spectral density of the pattern has a deterministic white-noise-like character that allows direct determination of the ITF with uniform sensitivity over the entire spatial frequency range and field of view of an instrument. The high efficacy of the technique has been previously demonstrated in application to metrology with flat and slightly curved optics. Here, we concentrate on development of an efficient fabrication process for production of highly randomized (HR) BPRA test standards on flat and 500-mm spherical optical substrates. We also compare and discuss the results of the ITF calibration of an interferometric microscope when using the HR BPRA standards on flat and curved substrates.
High-accuracy metrology is vitally important in manufacturing ultra-high-quality free-form mirrors designed to manipulate X-ray light with nanometer-scale wavelengths. The current capabilities and possibility for improvements in X-ray mirror manufacturing are limited by inherent imperfections of the integrated metrology tools. In the case of Fizeau interferometry, metrology tools are currently calibrated with super-polished flat test-standard/reference mirrors. This is acceptable for measuring slightly curved X-ray optics. However, for even moderately curved aspherical X-ray mirrors the flat-reference calibration is not sufficiently accurate and stitching Fizeau interferometer-based surface metrology is used to mitigate the problem. But still, the retrace and aberration errors, as well as the limited spatial resolution, described with the instrument transfer function (ITF), can be transferred into the optical surface topography of X-ray mirrors obtained in stitching metrology. For ITF calibration, we have developed an original technique, based on test standards structured as two-dimensional (2D) highly-randomized (HR) binary pseudo-random arrays (BPRAs). The technique employs the unique properties of the HR BPRA patterns in the spatial frequency domain., i.e. the inherent 2D power spectral density of the HR BPRA pattern has a deterministic white-noise-like character that allows direct determination of the ITF with uniform sensitivity over the entire spatial frequency range and field-of-view of an instrument. Here, we explore technological, metrological, and analytical aspects essential for calibration of the retrace and aberration errors of Fizeau interferometers using different types of tilted test samples, including a super-polished reference mirror for the re-trace calibration and the uniformly redundant array (URA) BPRA standards for the geometrical distortion (aberration) calibration. While the first method was previously demonstrated by researchers at DIAMOND Light Source, a method based on the URA BPRA is described and demonstrated here for the first time. We outline the design and fabrication process used in fabrication of URA BPRA test standards, and present the results of application of the URA BPRA standards demonstrating the high efficacy of our approach to geometrical distortion calibration of Fizeau interferometers. We also discuss the possible sources of unexpected peculiarities of the systematic errors, including an astigmatic character of the retrace error, observed with Fizeau interferometers at the Advanced Light Source X-Ray Optics Laboratory.
CMM (Coordinate Measuring Machine) metrology provides simple, 3D (three dimensional) surface data used for prescription retrieval, figure error, and alignment with high accuracy without null-correctors. Two freeform mirrors for a compact telescope were successfully characterized and aligned using the CMM.
Micro- and nanomanufacturing capabilities have rapidly expanded over the past decade to include complex three-dimensional (3D) structure fabrication; however, the metrology required to accurately assess these processes via part inspection and characterization has struggled to keep pace. X-ray computed tomography (CT) is considered an ideal candidate for providing the critically needed metrology on the smallest scales, especially internal features, or inaccessible regions. X-ray CT supporting micro- and nanomanufacturing often push against the poorly understood resolution and variation limits inherent to the machines, which can distort or hide fine structures. In this study, we have developed and experimentally verify a comprehensive analytical uncertainty propagation signal variation flow graph (SVFG) model for X-ray radiography in this work to better understand resolution and image variability limits on the small scale. The SVFG approach captures, quantifies, and predicts variations occurring in the system that limit metrology capabilities, particularly in the micro/nanodomain. This work is the first step to achieving full uncertainty modeling of CT reconstructions and provides insight into improving X-ray attenuation imaging systems. The SVFG methodology framework is applied to generate a complete basis set of functions describing the major sources of variation in radiographs. Five models are identified, covering variation in energy, intensity, length, blur, and position. Radiographic system experiments are defined to measure the parameters required by the SVFGs. Best practices are identified for these measurements. The SVFG models are confirmed via direct measurement of variation to predict variation within 30% on average.
Two-photon lithography (TPL) is a high-resolution additive manufacturing (AM) technique capable of producing arbitrarily complex three-dimensional (3D) microstructures with features 2–3 orders of magnitude finer than human hair. This process finds numerous applications as a direct route toward the fabrication of novel optical and mechanical metamaterials, miniaturized optics, microfluidics, biological scaffolds, and various other intricate 3D parts. As TPL matures, metrology and inspection become a crucial step in the manufacturing process to ensure that the geometric form of the end product meets design specifications. X-ray-based computed tomography (CT) is a nondestructive technique that can provide this inspection capability for the evaluation of complex internal 3D structure. However, polymeric photoresists commonly used for TPL, as well as other forms of stereolithography, poorly attenuate X-rays due to the low atomic number (Z) of their constituent elements and therefore appear relatively transparent during imaging. We present the development of optically clear yet radiopaque photoresists for enhanced contrast under X-ray CT. We have synthesized iodinated acrylate monomers to formulate high-Z photoresist materials that are capable of forming 3D microstructures with sub-150 nm features. In addition, we have developed a formulation protocol to match the refractive index of the photoresists to the immersion medium of the objective lens so as to enable dip-in laser lithography, a direct laser writing technique for producing millimeter-tall structures. Our radiopaque photopolymer then resists increase X-ray attenuation by a factor of more than 10 times without sacrificing the sub-150 nm feature resolution or the millimeter-scale part height. Thus, our resists can successfully replace existing photopolymers to generate AM parts that are suitable for inspection via X-ray CT. By providing the “feedstock” for radiopaque AM parts, our resist formulation is expected to play a critical role in enabling fabrication of functional polymer parts to tight design tolerances.
Different statistical methods are used in various fields to qualify processes and products, especially in emerging technologies like Additive Manufacturing (AM) or 3D printing. Since several statistical methods are being employed to ensure quality production of the 3D-printed parts, an overview of these methods used in 3D printing for different purposes is presented in this paper. The advantages and challenges, to understanding the importance it brings for design and testing optimization of 3D-printed parts are also discussed. The application of different metrology methods is also summarized to guide future researchers in producing dimensionally-accurate and good-quality 3D-printed parts. Here, this review paper shows that the Taguchi Methodology is the commonly-used statistical tool in optimizing mechanical properties of the 3D-printed parts, followed by Weibull Analysis and Factorial Design. In addition, key areas such as Artificial Intelligence (AI), Machine Learning (ML), Finite Element Analysis (FEA), and Simulation require more research for improved 3D-printed part qualities for specific purposes. Future perspectives are also discussed, including other methods that can help further improve the overall quality of the 3D printing process from designing to manufacturing.
Measuring the three-dimensional (3D) distribution of chemistry in nanoscale matter is a longstanding challenge for metrological science. The inelastic scattering events required for 3D chemical imaging are too rare, requiring high beam exposure that destroys the specimen before an experiment is completed. Even larger doses are required to achieve high resolution. Thus, chemical mapping in 3D has been unachievable except at lower resolution with the most radiation-hard materials. Here, high-resolution 3D chemical imaging is achieved near or below one-nanometer resolution in an Au-Fe 3 O 4 metamaterial within an organic ligand matrix, Co 3 O 4 -Mn 3 O 4 core-shell nanocrystals, and ZnS-Cu 0.64 S 0.36 nanomaterial using fused multi-modal electron tomography. Multi-modal data fusion enables high-resolution chemical tomography often with 99% less dose by linking information encoded within both elastic (HAADF) and inelastic (EDX/EELS) signals. We thus demonstrate that sub-nanometer 3D resolution of chemistry is measurable for a broad class of geometrically and compositionally complex materials.