A coded source imaging system has been developed to improve resolution for neutron radiography through magnification and demonstrated at the High Flux Isotope Reactor (HFIR) CG-1D instrument. Without magnification, the current resolution at CG-1D is 80μm using a charge-coupled device (CCD) equipped with a lens. As for all neutron imaging instruments, magnification is limited by a large source size. At CG-1D the size is currently limited to 12mm with a circular aperture. Coded source imaging converts this large aperture into a coded array of smaller apertures to achieve high resolution without the loss of flux for a single pinhole aperture, but requires a decoding step. The developed system has demonstrated first magnified radiographic imaging at magnifications as high as 25x using coded apertures with holes as small as 10μm. Such a development requires a team with a broad base of expertise including imaging systems design, neutron physics, microelectronics manufacturing methods, reconstruction algorithms, and high performance computing. The paper presents the system design, discusses implementation challenges, and presents imaging results.
Geothermal systems extract heat energy from the interior of the earth using a working fluid, typically water. Three components are required for a commercially viable geothermal system: heat, fluid, and permeability. Current commercial electricity production using geothermal energy occurs where the three main components exist naturally. These are called hydrothermal systems. In the US, there is an estimated 30 GW of base load electrical power potential for hydrothermal sites. Next generation geothermal systems, named Enhanced Geothermal Systems (EGS), have an estimated potential of 4500 GW. EGSs lack in-situ fluid, permeability or both. As such, the heat exchange system must be developed or “engineered” within the rock. The envisioned method for producing permeability in the EGS reservoir is hydraulic fracturing, which is rarely practiced in the geothermal industry, and not well understood for the rocks typically present in geothermal reservoirs. High costs associated with trial and error learning in the field have led to an effort to characterize fluid flow and fracturing mechanisms in the laboratory to better understand how to design and manage EGS reservoirs. Neutron radiography has been investigated for potential use in this characterization. An environmental chamber has been developed that is suitable for reproduction of EGS pressures and temperatures and has been tested for both flow and precipitations studies with success for air/liquid interface imaging and 3D reconstruction of precipitation within the core.
The limitations in neutron flux and resolution (1/D) of current neutron imaging systems can be addressed with a Coded Source Imaging system with magnification (xCSI). More precisely, the multiple sources in an xCSI system can exceed the flux of a single pinhole system for several orders of magnitude, while maintaining a higher 1 / D with the small sources. Moreover, designing for an xCSI system reduces noise from neutron scattering, because the object is placed away from the detector to achieve magnification. However, xCSI systems are adversely affected by correlated noise such as non-uniform illumination of the neutron source, incorrect sampling of the coded radiograph, misalignment of the coded masks, mask transparency, and the imperfection of the system Point Spread Function (PSF). We argue that a model-based reconstruction algorithm can overcome these problems and describe the implementation of a Simultaneous Iterative Reconstruction Technique algorithm for coded sources. Design pitfalls that preclude a satisfactory reconstruction are documented.
Since the first application of neutron radiography in the 1930s, the field of neutron radiography has matured
enough to develop several applications. However, advances in the technology are far from concluded. In general,
the resolution of scintillator-based detection systems is limited to the 10μm range, and the relatively low neutron
count rate of neutron sources compared to other illumination sources restricts time resolved measurement.
One path toward improved resolution is the use of magnification; however, to date neutron optics are inefficient,
expensive, and difficult to develop. There is a clear demand for cost-effective scintillator-based neutron
imaging systems that achieve resolutions of 1μm or less. Such imaging system would dramatically extend the
application of neutron imaging. For such purposes a coded source imaging system is under development. The
current challenge is to reduce artifacts in the reconstructed coded source images. Artifacts are generated by
non-uniform illumination of the source, gamma rays, dark current at the imaging sensor, and system noise from
the reconstruction kernel. In this paper, we describe how to pre-process the coded signal to reduce noise and
non-uniform illumination, and how to reconstruct the coded signal with three reconstruction methods correlation,
maximum likelihood estimation, and algebraic reconstruction technique. We illustrates our results with
We present a machine vision system for automatic identification of the class of firearms by extracting and analyzing two
significant properties from spent cartridge cases, namely the Firing Pin Impression (FPI) and the Firing Pin Aperture
Outline (FPAO). Within the framework of the proposed machine vision system, a white light interferometer is employed
to image the head of the spent cartridge cases. As a first step of the algorithmic procedure, the Primer Surface Area
(PSA) is detected using a circular Hough transform. Once the PSA is detected, a customized statistical region-based
parametric active contour model is initialized around the center of the PSA and evolved to segment the FPI.
Subsequently, the scaled version of the segmented FPI is used to initialize a customized Mumford-Shah based level set
model in order to segment the FPAO. Once the shapes of FPI and FPAO are extracted, a shape-based level set method is
used in order to compare these extracted shapes to an annotated dataset of FPIs and FPAOs from varied firearm types. A
total of 74 cartridge case images non-uniformly distributed over five different firearms are processed using the
aforementioned scheme and the promising nature of the results (95% classification accuracy) demonstrate the efficacy of
the proposed approach.
Coded aperture techniques have been applied to neutron radiography to address limitations in neutron flux and
resolution of neutron detectors in a system labeled coded source imaging (CSI). By coding the neutron source, a
magnified imaging system is designed with small spot size aperture holes (10 and 100μm) for improved resolution
beyond the detector limits and with many holes in the aperture (50% open) to account for flux losses due to the
small pinhole size. An introduction to neutron radiography and coded aperture imaging is presented. A system
design is developed for a CSI system with a development of equations for limitations on the system based on the
coded image requirements and the neutron source characteristics of size and divergence. Simulation has been
applied to the design using McStas to provide qualitative measures of performance with simulations of pinhole array
objects followed by a quantitative measure through simulation of a tilted edge and calculation of the modulation
transfer function (MTF) from the line spread function. MTF results for both 100μm and 10μm aperture hole
diameters show resolutions matching the hole diameters.
Registration of radiographic and computed tomography (CT) data has the potential to allow automated metrology and defect detection. While registration of the three-dimensional reconstructed data is a common task in the medical industry for registration of data sets from multiple detection systems, registration of projection sets has only seen development in the area of tomotherapy. Efforts in projection registration have employed a method named Fourier phase matching (FPM). This work discusses implementation and results for the application of the FPM method to industrial applications for the nondestructive testing (NDT) community. The FPM method has been implemented and modified for industrial application. Testing with simulated and experimental x-ray CT data shows excellent performance with respect to the resolution of the imaging system.
Interferometric imaging has the potential to extend the usefulness of optical microscopes by encoding small phase shifts
that reveal information about topology and materials. At the Oak Ridge National Laboratory (ORNL), we have
developed an optical Spatial Heterodyne Interferometry (SHI) method that captures reflection images containing both
phase and amplitude information at a high rate of speed. By measuring the phase of a wavefront reflected off or
transmitted through a surface, the relative surface heights and some materials properties can be measured. In this paper
we briefly review our historical application of SHI in the semiconductor industry, but the focus is on new research to
adapt this technology to the inspection of MEMS devices, in particular to the characterization of motion elements such
as microcantilevers and deformable mirror arrays.
Interferometric imaging has the potential to extend the usefulness of optical microscopes by encoding small phase shifts that reveal information about topology and materials. At the Oak Ridge National Laboratory (ORNL), we have developed an optical Spatial Heterodyne Interferometry (SHI) method that captures reflection or transmission
images containing both phase and amplitude information at a high rate of speed. By measuring the phase of a wavefront reflected off or transmitted through a surface, the relative surface heights and some materials properties can be determined. In this paper we briefly review a variety of application areas where this technology has been applied including semiconductor wafer inspection, photolithographic mask metrology and inspection, and we conclude with a discussion regarding future work to apply SHI to MEMS device characterization.
Spatial heterodyning is an interferometric technique that allows a full complex optical wavefront to be recorded and quickly reconstructed with a single image capture. Oak Ridge National Laboratory (ORNL) has combined a high-speed, image capture technique with a Fourier reconstruction algorithm to produce a method for recovery of both the phase and magnitude of the optical wavefront. Single frame spatial heterodyne interferometry (SHI) enables high-speed inspection applications such as those needed in the semiconductor industry. While the wide range of materials on wafers make literal interpretation of surface topology difficult, the wafers contain multiple copies of the same die and die-to-die comparisons are used to locate defects in high-aspect-ratio structures such as contacts, vias, and trenches that are difficult to detect with other optical techniques. Metrology with SHI has also been investigated by ORNL, in particular the use of SHI to perform metrology of line widths and heights on photolithographic masks for semiconductor wafer production. Several types of masks are currently in use with phase shifting techniques being employed to extend the wafer printing resolution. With the ability to measure the phase of the wavefront, SHI allows a more complete inspection and measurement of the phase shifting regions.
For process control, linewidth measurements are commonly performed on semiconductor wafers using top-down images from critical dimension measurement scanning electron microscopes (CD-SEMs). However, a measure of the line sidewall shape will be required as linewidths continue to shrink. Sidewall shape can be measured by physically cleaving the device and performing an SEM scan of the cross section, but this process is time consuming and results in destruction of product wafers. We develop a technique to estimate sidewall shape from top-down SEM images using pattern recognition based on historical cross section/top-down image pairs. Features are computed on subimages extracted from the top-down images. Several combinations of principal component analysis (PCA) and flavors of linear discriminant analysis (LDA) are employed to reduce the dimensionality of the feature vectors and maximize the spread between different sidewall shapes. Direct, weighted LDA (DW-LDA) results in a feature set that provides the best sidewall shape estimation. Experimental testing of the sidewall estimation system shows a root mean square error of approximately 1.8% of the linewidth, showing that this system is a viable method for estimating sidewall shape with little impact on the fabrication process (no new hardware and a minimal increase in process setup).
Phase shift techniques introduced in photolithography to further improve resolution produce a new set of challenges for inspection. Unlike the high contrast provided by patterned and unpatterned areas on a binary mask, phase errors do not provide significant contrast changes, since the phase change is imparted by a difference in material thickness. Surface topology measurements can be used to identify phase defects, but methods for surface topology inspection are typically slow or can damage the surface to be measured. In this study, Spatial Heterodyne Interferometry (SHI) has been considered as a possible method for high-speed non-contact phase defect detection. SHI is an imaging technique developed at Oak Ridge National Laboratory that acquires both phase and amplitude information from an optical wavefront with a single high-speed image capture. Using a reflective SHI system, testing has been performed with a mask containing programmed phase defects of various sizes and depths. In this paper, we present an overview of the SHI measurement technique, discuss issues such as phase wrapping associated with using SHI for phase defect detection on photolithographic masks, and present phase defect detection results from die-to-die comparisons on a 248 nm alternating aperture phase shift mask with intentional phase defects.
Spatial heterodyne interferometry (SHI) is an imaging technique that captures both the phase and amplitude of a complex wavefront in a single high-speed image. This technology was developed at the Oak Ridge National Laboratory (ORNL) and is currently being implemented for semiconductor wafer inspection by nLine Corporation. As with any system that measures phase, metrology and inspection of surface structures is possible by capturing a wavefront reflected from the surface. The interpretation of surface structure heights for metrology applications can become very difficult with the many layers of various materials used on semiconductor wafers, so inspection (defect detection) has been the primary focus for semiconductor wafers. However, masks used for photolithography typically only contain a couple well-defined materials opening the doors to high-speed mask metrology in 3 dimensions in addition to inspection. Phase shift masks often contain structures etched out of the transparent substrate material for phase shifting. While these structures are difficult to inspect using only intensity, the phase and amplitude images captured with SHI can produce very good resolution of these structures. The phase images also provide depth information that is crucial for these phase shift regions.
Preliminary testing has been performed to determine the feasibility of SHI for high-speed non-contact mask metrology using a prototype SHI system with 532 nm wavelength illumination named the Visible Alpha Tool (VAT). These results show that prototype SHI system is capable of performing critical dimension measurements on 400nm lines with a repeatability of 1.4nm and line height measurements with a repeatability of 0.26nm. Additionally initial imaging of an alternating aperture phase shift mask has shown the ability of SHI to discriminate between typical phase shift heights.
In semiconductor device manufacturing, critical dimension (CD) metrology provides a measurement for precise line-width control during the lithographic process. Currently scanning electron microscope (SEM) tools are typically used for this measurement, because the resolution requirements for the CD measurements are outside the range of optical microscopes. While CD has been a good feedback control for the lithographic process, line-widths continue to shrink and a more precise measurement of the printed lines is needed. With decreasing line widths, the entire sidewall structure must be monitored for precise process control. Sidewall structure is typically acquired by performing a destructive cross sectioning of the device, which is then imaged with a SEM tool. Since cross sectioning is destructive and slow, this is an undesirable method for testing product wafers and only a small sampling of the wafers can be tested. We have developed a technique in which historical cross section/top down image pairs are used to predict sidewall shape from top down SEM images. Features extracted from a new top down SEM image are used to locate similar top downs within the historical database and the corresponding cross sections in the database are combined to create a sidewall estimate for the new top down. Testing with field test data has shown the feasibility of this approach and that it will allow CD SEM tools to provide cross section estimates with no change in hardware or complex modeling.
Scanning electron microscope (SEM) images for semiconductor line-width measurements are generally acquired in a top-down configuration. As semiconductor dimensions continue to shrink, it has become increasingly important to characterize the cross-section, or sidewall, profiles. Cross-section imaging, however, requires the physical cleaving of the device, which is destructive and time-consuming. The goal of this work is to examine historical top-down and cross-section image pairs to determine if the cross-section profiles might be estimated by analyzing the corresponding top-down images. We present an empirical pattern recognition approach aimed at solving this problem. We compute feature vectors from sub-images of the top-down SEM images. Principal component analysis (PCA) and linear discriminant analysis (LDA) are used to reduce the dimensionality of the feature vectors, where class labels are assigned by clustering the cross-sections according to shape. Features are extracted from query top-downs and compared to the database. The estimated cross-section of the query is computed as a weighted combination of cross-sections corresponding to the nearest top-down neighbors. We report results obtained using 100nm, 180nm, and 250nm dense and isolated line data obtained by three different SEM tools.
We describe an automated image processing approach for detecting and characterizing cavitation pits on stainless steel surfaces. The image sets to be examined have been captured by a scanning electron microscope (SEM). Each surface region is represented by a pair of SEM images, one captured before and one after the cavitation-causing process. Unfortunately, some required surface preparation steps between pre-cavitation and post-cavitation imaging can introduce artifacts and change image characteristics in such a way as to preclude simple image-to-image differencing. Furthermore, all of the images were manually captured and are subject to rotation and translation alignment errors as well as variations in focus and exposure. In the presented work, we first align the pre- and post- cavitation images using a Fourier-domain technique. Since pre-cavitation images can often contain artifacts that are very similar to pitting, we perform multi-scale pit detection on each pre- and post-cavitation image independently. Coincident regions labeled as pits in both pre- and post-cavitation images are discarded. Pit statistics are exported to a text file for further analysis. In this paper we provide background information, algorithmic details, and show some experimental results.
We present modifications to a feature-based, image-retrieval approach for estimating semiconductor sidewall (cross-section) shapes using top-down images. The top-down images are acquired by a critical dimension scanning electron microscope (CD-SEM). The proposed system is based upon earlier work with several modifications. First, we use only line-edge, as opposed to full-line, sub-images from the top-down images. Secondly, Gabor filter features are introduced to replace some of the previously computed features. Finally, a new dimensionality reduction algorithm - direct, weighted linear discriminant analysis (DW-LDA) - is developed to replace the previous two-step principal component analysis plus LDA method. Results of the modified system are presented for data collected across several line widths, line spacings, and CD-SEM tools.
A method for recording true holograms directly to a digital video medium in a single image has been invented. This technology makes the amplitude and phase for every pixel of the target object wave available. Since phase is proportional wavelength, this makes high-resolution metrology an implicit part of the holographic recording. Measurements of phase can be made to one hundredth or even one thousandth of a wavelength, so the technology is attractive for dining defects on semiconductor wafers, where feature sizes are now smaller than the wavelength of even deep UV light.