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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Deep learning‑based metal artefact reduction in X-ray computed tomography of TRISO fuel compacts

TRISO (TRi-structural ISOtropic) – compact-type micro-particle fuels – are next generation nuclear fuel compacts designed with safety in mind. Structural integrity and characterisation before and after irradiation are important to determine the performance of the fuel compacts under real reactor conditions. X-ray computed tomography can be an important tool for non-destructive evaluation of these fuel compacts. The fuel particles are highly attenuating for X-rays which creates metal artefact, rendering the images unusable. Our artefact correction can mitigate these artefacts significantly. The proposed method works by first segmenting highly-attenuating structures (metal) and forward projecting to localise the source of artefacts in the projection domain, then, using a traditional or U-net-based deep learning architecture, contextually interpolating those regions to remove the artefacts. Finally the reconstruction from the modified projection is fused with the segmented metal. The proposed method shows a significant improvement in the image quality while significantly reducing the reconstruction time compared to the standard technique.

Rahman, Obaid [ORNL] (ORCID:0000000277810840)↗
DOE OSTI2025

Selection of high-redshift Lyman-Break Galaxies from broadband and wide photometric surveys

Here, in this paper, we investigate the possibility of selecting high-redshift Lyman-Break Galaxies (LBG) using current and future broadband wide photometric surveys, such as the Ultraviolet Near Infrared Optical Northern Survey (UNIONS) or the Vera C. Rubin Legacy Survey of Space and Time (LSST), using a Random Forest algorithm. This work is conducted in the context of future large-scale structure spectroscopic surveys like DESI-II, the next phase of the Dark Energy Spectroscopic Instrument (DESI), which will start around 2029. We use deep imaging data from the Hyper Suprime Camera (HSC) and the Canada-France-Hawaii Telescope Large Area U-band Deep Survey (CLAUDS) on the COSMOS and XMM-LSS fields. To predict the selection performance of LBGs with image quality similar to UNIONS, we degrade the u,g,r,i and z bands to UNIONS depth. The Random Forest algorithm is trained with the u,g,r,i and z bands to classify LBGs in the 2.5 < z < 3.5 range. We find that fixing a target density budget of 1,100 deg -2 , the Random Forest approach gives a density of z > 2 targets of 873 deg -2 , and a density of 493 deg -2 of confirmed LBGs after spectroscopic confirmation with DESI. This UNIONS-like selection was tested in a dedicated spectroscopic observation campaign of 1,000 targets with DESI on the COSMOS field, providing a safe spectroscopic sample with a mean redshift of 3. This sample is used to derive forecasts for DESI-II, assuming a sky coverage of 5,000 deg 2 . We predict uncertainties on Alcock-Paczynski parameters α ⊥ and α ∥ to be 0.7% and 1% for 2.6 < z < 3.2, resulting in a potential 2% measurement of the dark energy fraction at high redshift. Additionally, we estimate the uncertainty in local non-Gaussianity and predict σ fNL ≈ 7, which would be comparable to the current best precision achieved by Planck. The latter forecast suggests that achieving the precision required to place stringent constraints on inflationary models (σ fNL ≈ 1) using spectroscopic galaxy surveys necessitates the development of a next-generation (Stage V) spectroscopic survey.

cosmological parameters from LSS↗
DOE OSTI2023

Color Transformations of Photometric Measurements of Galaxies in Optical and Near-infrared Wide-field Imaging Surveys*

Abstract Over the past 2 decades, wide-field photometric surveys in optical and infrared domains reached a nearly all-sky coverage thanks to numerous observational facilities operating in both hemispheres. However, subtle differences among exact realizations of Johnson and SDSS photometric systems require one to convert photometric measurements into the same system prior to analysis of composite data sets originating from multiple surveys. It turns out that the published photometric transformations lead to substantial biases when applied to integrated photometry of galaxies from the corresponding catalogs. Here we present photometric transformations based on piece-wise linear approximations of integrated photometry of galaxies in the optical surveys SDSS, DECaLS, BASS, MzLS, DES, DELVE, KiDS, VST ATLAS, and the near-infrared surveys UKIDSS, UHS, VHS, and VIKING. We validate our transformations by constructing k -corrected color–magnitude diagrams of non-active galaxies and measuring the position and tightness of the “red sequence.” We also provide transformations for aperture magnitudes and show how they are affected by the image quality difference among the surveys. We present the implementation of the derived transformations in python and idl and also a web-based color transformation calculator for galaxies. By comparing DECaLS and DES, we identified systematic issues in DECaLS photometry for extended galaxies, which we attribute to the photometric software package used by DECaLS. As an application of our method, we compiled two multi-wavelength photometric catalogs for over 200,000 low- and intermediate-redshift galaxies originating from CfA FAST and Hectospec spectral archives.

Astronomy & Astrophysics↗
DOE OSTI2024

The Impact of Bias Row Noise to Photometric Accuracy: Case Study Based on a Scientific CMOS Detector

Abstract We tested a new model of CMOS detector manufactured by the Gpixel Inc, for potential space astronomical application. In laboratory, we obtain some bias images under the typical application environment. In these bias images, clear random row noise pattern is observed. The row noise also contains some characteristic spatial frequencies. We quantitatively estimated the impact of this feature to photometric measurements, by making simulated images. We compared different bias noise types under strict parameter control. The result shows the row noise will significantly deteriorate the photometric accuracy. It effectively increases the readout noise by a factor of 2–10. However, if it is properly removed, the image quality and photometric accuracy will be significantly improved.

Astronomy & Astrophysics↗
DOE OSTI2023

A TOPAS model for lens-based proton radiography

Abstract Objective. Proton Radiography can be used in conjunction with proton therapy for patient positioning, real-time estimates of stopping power, and adaptive therapy in regions with motion. The modeling capability shown here can be used to evaluate lens-based radiography as an instantaneous proton-based radiographic technique. The utilization of user-friendly Monte Carlo program TOPAS enables collaborators and other users to easily conduct medical- and therapy- based simulations of the Los Alamos Neutron Science Center (LANSCE). The resulting transport model is an open-source Monte Carlo package for simulations of proton and heavy ion therapy treatments and concurrent particle imaging. Approach. The four-quadrupole, magnetic lens system of the 800-MeV proton beamline at LANSCE is modeled in TOPAS. Several imaging and contrast objects were modelled to assess transmission at energies from 230–930 MeV and different levels of particle collimation. At different proton energies, the strength of the magnetic field was scaled according to βγ, the inverse product of particle relativistic velocity and particle momentum. Main results. Materials with high atomic number, Z, (gold, gallium, bone-equivalent) generated more contrast than materials with low-Z (water, lung-equivalent, adipose-equivalent). A 5-mrad collimator was beneficial for tissue-to-contrast agent contrast, while a 10-mrad collimator was best to distinguish between different high-Z materials. Assessment with a step-wedge phantom showed water-equivalent path length did not scale directly according to predicted values but could be mapped more accurately with calibration. Poor image quality was observed at low energies (230 MeV), but improved as proton energy increased, with sub-mm resolution at 630 MeV. Significance. Proton radiography becomes viable for shallow bone structures at 330 MeV, and for deeper structures at 630 MeV. Visibility improves with use of high-Z contrast agents. This modality may be particularly viable at carbon therapy centers with accelerators capable of delivering high energy protons and could be performed with carbon therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

The merger fraction of post-starburst galaxies in UNIONS

ABSTRACT Post-starburst galaxies (PSBs) are defined as having experienced a recent burst of star formation, followed by a prompt truncation in further activity. Identifying the mechanism(s) causing a galaxy to experience a post-starburst phase therefore provides integral insight into the causes of rapid quenching. Galaxy mergers have long been proposed as a possible post-starburst trigger. Effectively testing this hypothesis requires a large spectroscopic galaxy survey to identify the rare PSBs as well as high-quality imaging and robust morphology metrics to identify mergers. We bring together these critical elements by selecting PSBs from the overlap of the Sloan Digital Sky Survey and the Canada–France Imaging Survey and applying a suite of classification methods: non-parametric morphology metrics such as asymmetry and Gini-M20, a convolutional neural network trained to identify post-merger galaxies, and visual classification. This work is therefore the largest and most comprehensive assessment of the merger fraction of PSBs to date. We find that the merger fraction of PSBs ranges from 19 per cent to 42 per cent depending on the merger identification method and details of the PSB sample selection. These merger fractions represent an excess of 3–46× relative to non-PSB control samples. Our results demonstrate that mergers play a significant role in generating PSBs, but that other mechanisms are also required. However, applying our merger identification metrics to known post-mergers in the IllustrisTNG simulation shows that 70 per cent of recent post-mergers (≲200 Myr) would not be detected. Thus, we cannot exclude the possibility that nearly all PSBs have undergone a merger in their recent past.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The satellite population around luminous red galaxies in the 25 deg2 DESI Legacy Imaging Surveys Early Data Release

ABSTRACT Luminous red galaxies, or LRGs, are representative of the most massive galaxies and were originally selected in the Sloan Digital Sky Survey as good tracers of large-scale structure. They are dominated by by uniformly old stellar populations, have low star formation rates, early type morphologies, and little cold gas. Despite having old stellar populations and little in situ star formation, studies have shown that they have grown their stellar mass since z = 1, implying that they grow predominantly via the accretion of satellites. Tests of this picture have been limited because of the lack of deep imaging data sets that both covers a large enough area of the sky to contain substantial numbers of LRGs and that also is deep enough to detect faint satellites. We use the 25 deg2 Early Data Release (EDR) of the DESI Legacy Imaging Surveys to characterize the satellite galaxy population of LRGs out to z = 0.65. The DESI Legacy Imaging Surveys are comprised of grz imaging to 2–2.5 mag deeper than SDSS and with better image quality. We use a new statistical background technique to identify excess populations of putative satellite galaxies around 1823 LRGs at 0.2 < z < 0.65. In three redshift and luminosity bins we measure the numbers of satellite galaxies and their r−z colour distribution down to rest-frame g-band luminosity limits at least 3.6 times fainter than L*. In addition, we develop a forward modeling technique and apply it to constrain the mean number of satellites in each of our redshift and luminosity bins. Finally, we use these estimates to determine the amount of stellar mass growth in LRGs down to the local Universe.

Astronomy & Astrophysics↗
DOE OSTI2022

King Ghidorah Supercluster: Mapping the light and dark matter in a new supercluster at z = 0.55 using the subaru hyper suprime-cam

ABSTRACT This paper reports our discovery of the most massive supercluster, termed the King Ghidorah Supercluster (KGSc), at z = 0.50–0.64 in the Third Public Data Release of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP PDR3) over 690 deg2, as well as an initial result for a galaxy and dark matter mapping. The primary structure of the KGSc comprises triple broad weak-lensing (WL) peaks over 70 comoving Mpc. Such extensive WL detection at z > 0.5 can only currently be achieved using the wide-field high-quality images produced by the HSC-SSP. The structure is also contiguous with multiple large-scale structures across a ∼400 comoving Mpc scale. The entire field has a notable overdensity (δ = 14.7 ± 4.5) of red-sequence clusters. Additionally, large-scale underdensities can be found in the foreground along the line of sight. We confirmed the overdensities in stellar mass and dark matter distributions to be tightly coupled and estimated the total mass of the main structure to be 1 × 1016 solar masses, according to the mock data analyses based on large-volume cosmological simulations. Further, upcoming wide-field multi-object spectrographs such as the Subaru Prime Focus Spectrograph may aid in providing additional insights into distant superclusters beyond the 100 Mpc scale.

Shimakawa, Rhythm (ORCID:0000000344422750)↗
DOE OSTI2024

GALAXY CRUISE: Spiral and ring classifications for bright galaxies at z = 0.01–0.3

Abstract This paper presents a morphology classification catalog of spiral and ring features of 59854 magnitude-limited galaxies (r < 17.8 mag, and additional 628005 subsamples down to r = 20 mag) at z = 0.01–0.3 based on the Third Public Data Release of the Hyper Suprime-Cam Subaru Strategic Program. We employ two deep-learning classifiers to determine the spiral and ring structures separately based on GALAXY CRUISE Data Release 1, which is dedicated to Hyper Suprime-Cam data. The number of spiral and ring galaxies contain 31864 and 8808 sources, respectively, which constitute 53% and 15% of the sample. A notable result of this study is the construction of a large sample of ring galaxies utilizing high-quality imaging data delivered by the Subaru Hyper Suprime-Cam. However, the accurate identification of ring galaxies remains difficult at a limited seeing resolution. Additionally, we confirm that most spiral galaxies are located on the star-forming main sequence, whereas ring galaxies preferentially reside in the green valley at stellar masses of 1010.5–1011 solar mass. Furthermore, decreasing fractions of spiral and ring galaxies are observed toward the centers of the galaxy clusters. The obtained morphology catalog is publicly available on the GALAXY CRUISE website.

Shimakawa, Rhythm (ORCID:0000000344422750)↗
DOE OSTI2020

Quantifying the line-of-sight halo contribution to the dark matter convergence power spectrum from strong gravitational lenses

Galaxy-galaxy strong gravitational lenses have become a popular probe of dark matter (DM) by providing a window into structure formation on the smallest scales. In particular, the convergence power spectrum of subhalos within lensing galaxies has been suggested as a promising observable to study DM. However, the distances involved in strong-lensing systems are vast, and we expect the relevant volume to contain line-of-sight (LOS) halos that are not associated with the main lens. We develop a formalism to calculate the effect of LOS halos as an effective convergence power spectrum. Here, the multilens plane equation couples the angular deflections of consecutive lens planes, but by assuming that the perturbations due to the LOS halos are small, we show that they can be projected onto the main-lens plane as effective subhalos. We test our formalism by simulating lensing systems using the full multiplane lens equation and find excellent agreement. We show how the relative contribution of LOS halos and subhalos depends on the source and lens redshift, as well as the assumed halo and subhalo mass functions. For a fiducial system with fraction of DM halo mass in substructure f sub = 0.4% for subhalo masses [10 5 –10 8 ]M ⊙ , the interloper contribution to the power spectrum is at least several times greater than that of subhalos for source redshifts z s ≳ 0.5. Furthermore, it is likely that for the SLACS and BELLS lenses the interloper contribution dominates: f sub ≳ 2% (4%) is needed for subhalos to dominate in SLACS (BELLS), which is higher than current upper bounds on f sub for our mass range. Since the halo mass function is better understood from first principles, the dominance of interlopers in galaxy-galaxy lenses with high-quality imaging can be seen as a significant advantage when translating this observable into a constraint on DM.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Development of electron source feedback for enhanced X-ray beam stability at NSLS-II

Future synchrotron light sources are being designed to deliver significantly higher brightness and coherence, enabling faster scanning and more advanced imaging techniques. However, realizing these capabilities requires improved X-ray beam stability, as vibrations directly limit measurement accuracy and image quality. At the NSLS-II Hard X-ray Nanoprobe (HXN), a local mechanical feedback system mitigates low-frequency motion but provides only limited suppression of dominant vibrations at 27 Hz and 120 Hz. To address this limitation, this work explores the use of the electron beam itself as the actuator for feedback by integrating X-ray beam position monitor signals into the fast orbit feedback system through a dedicated electrometer. Experimental results show that this approach effectively suppresses the dominant vibration peaks and enhances stability at the focusing point. Benchmark ptychography measurements further confirm that electron-beam-based feedback reduces background fluctuations and mitigates vibration-induced artifacts under fast-scanning conditions. These results establish the feasibility of using the electron beam as a feedback actuator for next-generation synchrotron applications and provide an experimental assessment of its potential and limitations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Characterization of a Pixelated Cadmium Telluride Detector System Using a Polychromatic X-Ray Source and Gold Nanoparticle-Loaded Phantoms for Benchtop X-Ray Fluorescence Imaging

In this paper, the imaging dose and scan time have been considered as the two major constraints for routine benchtop x-ray fluorescence computed tomography (XFCT) imaging. One way to address this issue is to acquire x-ray fluorescence (XRF) signals in parallel through a 2D array of single-crystal detectors or a pixelated detector along with the cone-beam x-ray source. To identify a detector system suitable for this purpose, a commercially available, fully spectroscopic cadmium telluride (CdTe) pixelated detector, HEXITEC (High-Energy X-ray Imaging Technology), was tested under the experimental conditions optimized for benchtop XFCT imaging of gold nanoparticles (GNPs). Specifically, two different parallel-hole stainless steel collimators were fabricated and coupled with the detector for seamless integration into our existing benchtop cone-beam XFCT system. After the detector deployment, this benchtop XFCT system was used to detect XRF photons from GNP-loaded phantoms. A pixel-merging algorithm was introduced to enhance the sensitivity of XRF photon detection thereby minimizing the scan time. The effect of pixel-level charge sharing correction algorithms was investigated within the context of benchtop XFCT imaging. The detector energy resolution, in terms of the full width at half maximum (FWHM) values at different gold K-shell XRF energies, was also determined. Of the two charge sharing correction algorithms examined, the charge sharing addition gave better sensitivity than the charge sharing discrimination (csd). On the other hand, under the current experimental conditions, the energy resolution of the HEXITEC detector was the best with the csd and estimated to be 1.56 keV FWHM at 66-69 keV photon energy. Overall, despite some degradation of the detector energy resolution (compared with typical single crystal CdTe detectors), the HEXITEC detector enabled parallel data acquisition under the experimental conditions typical of benchtop XFCT imaging and operated well within our benchtop XFCT setup.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Ringing Artifact Reduction Method for Ultrasound Reconstruction Using Multi-Agent Consensus Equilibrium

Non-destructive characterization of multi-layered structures that can be accessed from only a single side is important for applications such as well-bore integrity inspection. Existing methods related to Synthetic Aperture Focusing Technique (SAFT) rapidly produce acceptable results but with significant artifacts. Recently, ultrasound model-based iterative reconstruction (UMBIR) approaches have shown significant improvements over SAFT. However, even these methods produce ringing artifacts due to the high fractional-bandwidth of the excitation signal.In this paper, we propose a ringing artifact reduction method for ultrasound image reconstruction that uses a multi-agent consensus equilibrium (RARE-MACE) framework. Our approach integrates a physics-based forward model that accounts for the propagation of a collimated ultrasonic beam in multi-layered media, a spatially varying image prior, and a denoiser designed to suppress the ringing artifacts that are characteristic of reconstructions from high-fractional bandwidth ultrasound sensor data. We test our method on simulated and experimental measurements and show substantial improvements in image quality compared to SAFT and UMBIR.

Alanazi, Abdulrahman M↗
DOE OSTI2024

Long-Range Biometric Identification in Real World Scenarios: A Comprehensive Evaluation Framework Based on Missions

The considerable body of data available for evaluating biometric recognition systems in Research and Development (R&D) environments has contributed to the increasingly common problem of target performance mismatch. Biometric algorithms are frequently tested against data that may not reflect the real world applications they target. From a Testing and Evaluation (T&E) standpoint, this domain mismatch causes difficulty assessing when improvements in State-of-the-Art (SOTA) research actually translate to improved applied outcomes. This problem can be addressed with thoughtful preparation of data and experimental methods to reflect specific use-cases and scenarios.To that end, this paper evaluates research solutions for identifying individuals at ranges and altitudes, which could support various application areas such as counterterrorism, protection of critical infrastructure facilities, military force protection, and border security. We address challenges including image quality issues and reliance on face recognition as the sole biometric modality. By fusing face and body features, we propose developing robust biometric systems for effective long-range identification from both the ground and steep pitch angles. Preliminary results show promising progress in whole-body recognition. This paper presents these early findings and discusses potential future directions for advancing long-range biometric identification systems based on mission-driven metrics.

Aykac, Deniz↗
DOE OSTI2020

DECT-MULTRA: Dual-Energy CT Image Decomposition With Learned Mixed Material Models and Efficient Clustering

Dual-energy computed tomography (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Image-domain decomposition operates directly on CT images using linear matrix inversion, but the decomposed material images can be severely degraded by noise and artifacts. This paper proposes a new method dubbed DECT-MULTRA for image-domain DECT material decomposition that combines conventional penalized weighted-least squares (PWLS) estimation with regularization based on a mixed union of learned transforms (MULTRA) model. Our proposed approach pre-learns a union of common-material sparsifying transforms from patches extracted from all the basis materials, and a union of cross-material sparsifying transforms from multi-material patches. The common-material transforms capture the common properties among different material images, while the cross-material transforms capture the cross-dependencies. The proposed PWLS formulation is optimized efficiently by alternating between an image update step and a sparse coding and clustering step, with both of these steps having closed-form solutions. The effectiveness of our method is validated with both XCAT phantom and clinical head data. The results demonstrate that our proposed method provides superior material image quality and decomposition accuracy compared to other competing methods.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

X-ray and Neutron Radiography for Quantitative Material Reconstructions

Radiography is a powerful tool to determine the interior structure of objects. X-ray radiography is widely used and provides high-resolution images, though X-rays have limited transmission through materials of high atomic number (Z) and density. In contrast, neutrons can penetrate many materials that are heavily attenuating to X-rays, such as metals, providing contrast in the inner layers of highly attenuating items. Past work has shown the value in using both X-ray and neutron radiography for estimating material thicknesses, though that work was limited to simulated data. Here, we demonstrate quantitative material reconstructions using experimental X-ray and neutron radiography data from lab-based systems, accurately modeling radiography system responses to within a few percent to enable quantitative measures of material thickness. We demonstrate the utility of neutron radiography and X-ray radiography for these quantitative reconstructions and introduce methods for using their complementarity to improve image quality and optimize experimental design.

Gilbert, Andrew J.↗
DOE OSTI2025

Deep Learning Super-Resolution X-Ray Computed Tomography Algorithms for Additive Manufacturing

Industrial X-ray computed tomography (XCT) is a nondestructive method for inspection and characterization of additively manufactured (AM) materials and parts. In practice, the resolution of XCT can be limited by factors such as detector binning, restricted field of view for large-scale objects, system blur, motion during scanning, and acquisition settings. These limitations can reduce the detectability of critical flaws such as pores, cracks, and lack of fusion. Super-resolution (SR) techniques offer a promising solution for improving the effective resolution and image quality of XCT reconstructions without the need for expensive hardware upgrades or laborious, time-consuming scans. In particular, deep learning-based SR methods have garnered attention in recent years as powerful tools for reconstructing high-resolution volumes from low-resolution inputs. In this work, a novel deep learning-based SR method is proposed for XCT scans of AM parts, and compared against several existing state-of-the-art (SOTA) methods. The proposed method, Simurgh-SR, is built on the pre-existing Simurgh framework and consists of a 2.5D U-Net trained to map low-quality inputs containing noise and artifacts to high-quality reconstructions characterized by higher flaw contrast, better noise texture, and reduced artifacts. The experimental results demonstrate superior performance of Simurgh-SR in performing 4× SR on real industrial XCT scans of thick 316L components, enhancing the structural similarity score and peak signal-to-noise ratio (>7dB) compared to the LR counterpart while improving the F1-score for flaw detection by more than 2.3× when compared to alternative SOTA SR methods. This improvement enables more accurate and significantly faster characterization of metal AM components. Additionally, Simurgh-SR was trained for both 2X and 4X SR and performs effectively at both levels, enabling the use of a single model for various SR factors.

Rahman, Obaid [ORNL] (ORCID:0000000277810840)↗
DOE OSTI2021

Picometer sensitivity metrology for EUV absorber phase

With growing interest in EUV attenuated phase-shift masks due to their superior image quality for applications such as dense contact and pillar arrays, it is becoming critical to model, measure, and monitor the intensity and relative phase of multilayer and absorber reflections. We present a solution based on physical modeling of reflectometry data, which can achieve single picometer phase precision and sensitivity to changes in average film thickness below one atomic monolayer. We measure absorber and multilayer reflectivity to determine thin-film parameters with a multidimensional optimization and then acquire a new measurement of either multilayer or absorber to determine perturbations in surface contamination thickness. While it is difficult to assess the accuracy of the first step, the simplicity of the second step allows us to characterize our sensitivity to changes in contamination thickness. Thus, we apply this analysis using an initial set of measurements and repeated measurements after a period of storage. For the multilayer, the total contamination growth was 1068 pm, which occurred almost exclusively during storage (1085 pm) and decreased very slightly during repeated measurements (-17 pm). For the absorber, the behavior was quite different, with a total growth of 126 pm, which occurred much less during storage (28 pm) and primarily during repeated measurements (98 pm). Ultimately, the change in relative phase (absorber minus multilayer) was -0.86 deg for the multilayer and -1.12 deg for the absorber. We estimate the precision of the surface contamination measurement to be 3σ < 6 pm for measuring thickness and 3σ < 0.2 deg for measuring phase.

36 MATERIALS SCIENCE↗