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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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69 records · Page 4

On-Wafer S-Parameter Measurements in the 325-508-GHz Band

New circuits have been designed and fabricated with operating frequencies over 325 GHz. In order to measure S-parameters of these circuits, an extensive process of wafer dicing and packaging, and waveguide transition design, fabrication, and packaging would be required. This is a costly and time-consuming process before the circuit can be tested in waveguide. The new probes and calibration procedures will simplify the testing process. New on-wafer probes, and a procedure for their calibration, have been developed that allow fast and inexpensive S-parameter characterization of circuits in the 325 -508 -GHz frequency band. The on-wafer probes transition from rectangular waveguide to coplanar waveguide probe tips with 40- m nominal signal-to-ground pin pitch so as to allow for probing circuits on a wafer. The probes with bias tees have been optimized for minimal insertion loss and maximum return loss when placed on 50-ohm structures to allow for calibration. The calibration process has been developed using the Thru-Reflect-Line Agilent algorithm with JPL determined calibration structures and calibration coefficients for the algorithm. This new test capability is presently unique to JPL. With it, researchers will be able to better develop circuits such as low-noise amplifiers, power amplifiers, multipliers, and mixers for heterodyne receivers in the 325-508-GHz frequency band for remote sensing/spectroscopy.

Fung, King Man↗

A Framework for Robust Multivariable Optimization of Integrated Circuits in Space Applications

Application Specific Integrated Circuit (ASIC) design for space applications involves multiple challenges of maximizing performance, minimizing power and ensuring reliable operation in extreme environments. This is a complex multidimensional optimization problem which must be solved early in the development cycle of a system due to the time required for testing and qualification severely limiting opportunities to modify and iterate. Manual design techniques which generally involve simulation at one or a small number of corners with a very limited set of simultaneously variable parameters in order to make the problem tractable are inefficient and not guaranteed to achieve the best possible results within the performance envelope defined by the process and environmental requirements. What is required is a means to automate design parameter variation, allow the designer to specify operational constraints and performance goals, and to analyze the results in a way which facilitates identifying the tradeoffs defining the performance envelope over the full set of process and environmental corner cases. The system developed by the Mixed Signal ASIC Group (MSAG) at the Goddard Space Flight Center is implemented as framework of software modules, templates and function libraries. It integrates CAD tools and a mathematical computing environment, and can be customized for new circuit designs with only a modest amount of effort as most common tasks are already encapsulated. Customization is required for simulation test benches to determine performance metrics and for cost function computation. Templates provide a starting point for both while toolbox functions minimize the code required. Once a test bench has been coded to optimize a particular circuit, it is also used to verify the final design. The combination of test bench and cost function can then serve as a template for similar circuits or be re-used to migrate the design to different processes by re-running it with the new process specific device models. The system has been used in the design of time to digital converters for laser ranging and time-of-flight mass spectrometry to optimize analog, mixed signal and digital circuits such as charge sensitive amplifiers, comparators, delay elements, radiation tolerant dual interlocked (DICE) flip-flops and two of three voter gates.

DuMonthier, Jeffrey↗

Using Markov Models of Fault Growth Physics and Environmental Stresses to Optimize Control Actions

A generalized Markov chain representation of fault dynamics is presented for the case that available modeling of fault growth physics and future environmental stresses can be represented by two independent stochastic process models. A contrived but representatively challenging example will be presented and analyzed, in which uncertainty in the modeling of fault growth physics is represented by a uniformly distributed dice throwing process, and a discrete random walk is used to represent uncertain modeling of future exogenous loading demands to be placed on the system. A finite horizon dynamic programming algorithm is used to solve for an optimal control policy over a finite time window for the case that stochastic models representing physics of failure and future environmental stresses are known, and the states of both stochastic processes are observable by implemented control routines. The fundamental limitations of optimization performed in the presence of uncertain modeling information are examined by comparing the outcomes obtained from simulations of an optimizing control policy with the outcomes that would be achievable if all modeling uncertainties were removed from the system.

Bole, Brian↗

Large-aperture Wide-bandwidth Antireflection-coated Silicon Lenses for Millimeter Wavelengths

The increasing scale of cryogenic detector arrays for submillimeter and millimeter wavelength astrophysics has led to the need for large aperture, high index of refraction, low loss, cryogenic refracting optics. Silicon with n 3.4, low loss, and high thermal conductivity is a nearly optimal material for these purposes but requires an antireflection (AR) coating with broad bandwidth, low loss, low reflectance, and a matched coefficient of thermal expansion. We present an AR coating for curved silicon optics comprised of subwavelength features cut into the lens surface with a custom three-axis silicon dicing saw. These features constitute a metamaterial that behaves as a simple dielectric coating.We have fabricated silicon lenses as large as 33.4 cm in diameter with micromachined layers optimized for use between 125 and 165 GHz. Our design reduces average reflections to a few tenths of a percent for angles of incidence up to 30deg with low cross polarization.We describe the design, tolerance, manufacture, and measurements of these coatings and present measurements of the optical properties of silicon at millimeter wavelengths at cryogenic and room temperatures. This coating and lens fabrication approach is applicable from centimeter to submillimeter wavelengths and can be used to fabricate coatings with greater than octave bandwidth.

thermal expansion↗

Large-Aperture Wide-Bandwidth Anti-Reflection-Coated Silicon Lenses for Millimeter Wavelengths

The increasing scale of cryogenic detector arrays for sub-millimeter and millimeter wavelength astrophysics has led to the need for large aperture, high index of refraction, low loss, cryogenic refracting optics. Silicon with n = 3.4, low loss, and relatively high thermal conductivity is a nearly optimal material for these purposes, but requires an antireflection (AR) coating with broad bandwidth, low loss, low reflectance, and a matched coffecient of thermal expansion. We present an AR coating for curved silicon optics comprised of subwavelength features cut into the lens surface with a custom three axis silicon dicing saw. These features constitute a metamaterial that behaves as a simple dielectric coating. We have fabricated and coated silicon lenses as large as 33.4 cm in diameter with coatings optimized for use between 125-165 GHz. Our design reduces average reflections to a few tenths of a percent for angles of incidence up to 30 deg. with low cross-polarization. We describe the design, tolerance, manufacture, and measurements of these coatings and present measurements of the optical properties of silicon at millimeter wavelengths at cryogenic and room temperatures. This coating and lens fabrication approach is applicable from centimeter to sub-millimeter wavelengths and can be used to fabricate coatings with greater than octave bandwidth.

millimeter wavelength astrophysics↗

Automated Cardiovascular Pathology Assessment using Semantic Segmentation and Ensemble Learning

Cardiac magnetic resonance imaging provides high spatial resolution, enabling improved extraction of important functional and morphological features for cardiovascular disease staging. Segmentation of ventricular cavities and myocardium in cardiac cine sequencing provides a basis to quantify cardiac measures such as ejection fraction. A method is presented that curtails the expense and observer bias of manual cardiac evaluation by combining semantic segmentation and disease classification into a fully automatic processing pipeline. The initial processing element consists of a robust dilated convolutional neural network architecture for voxel-wise segmentation of the myocardium and ventricular cavities. The resulting comprehensive volumetric feature matrix captures diagnostic clinical procedure data and is utilized by the final processing element to model a cardiac pathology classifier. Our approach evaluated anonymized cardiac images from a training data set of 100 patients (4 pathology groups, 1 healthy group, 20 patients per group) examined at the University Hospital of Dijon. The top average Dice index scores achieved were 0.940, 0.886, 0.849 for structure segmentation of the left ventricle (LV), myocardium and right ventricle (RV) respectively. A 5-ary pathology classification accuracy of 90% was recorded on an independent test set using the trained model. Performance results demonstrate potential for advanced machine learning methods to deliver accurate, efficient and reproducible cardiac pathological assessment.

Semantic Segmentation↗

Automated Semantic Segmentation for Volumetric Cardiovascular Feature Quantification and Pathology Assessment

We present a pipeline method that curtails the expense and observer bias of manual cardiac evaluation by combining semantic segmentation and disease classification as a fully automatic processing pipeline. The initial element consists of a 2D U-Net convolutional neural network architecture for voxel-wise segmentation of the myocardium and ventricular cavities. The results of the segmentation were used to compute a comprehensive volumetric feature matrix that captured diagnostic clinical procedure data and that was used to model a cardiac pathology classifier.Our approach evaluated anonymized parasternal MRI cardiac images from a database of 100 patients (4 pathology groups, 1 healthy group, 20 patients per group) examined at the University Hospital of Dijon. We achieved top average Dice index scores of 0.939, 0.849, 0.886 for structure segmentation of the left ventricle (LV), right ventricle (RV) and myocardium respectively. A 5-ary pathology classification accuracy of 90% was recorded on an independent test set using our trained model.

Lindsey, Tony↗

Micron MT29F1T08CMHBBJ4 1Tb NAND Flash Memory Single Event Effect Characterization Test Report

The purpose of this testing is to characterize the Single-Event Effect (SEE) response of the Micron MT29F1T08CMHBBJ4 3D NAND Flash memory. The MT29F1T08CMHBBJ4 is a 1Tb NAND Flash memory, consisting of a four-die stack of 256Gb MLC dice packaged in a 132-ball VBGA package. All data presented is the result of testing only the top die (256Gb) of the package. Testing was performed at two heavy-ion cyclotron facilities with an identical test setup, over the course of four test trips from 2017-2019.

Single Event Effect (SEE)↗

1.6-μm Er:YGG Waveguide Amplifiers

We report on the fabrication and characterization of Er:YGG films suitable for waveguide amplifiers that could in principle be used in integrated path differential absorption lidar systems. Presented is our fabrication technique, comprising pulsed-laser-deposition growth of ~10 μm-thick crystalline films, their channeling via ultraprecision ductile dicing with a diamond-blade, producing optical quality facets and sidewalls, and amplifier performance. Net gain at 1572 nm and 1651 nm is obtained for the first time in Er-doped YGG waveguide amplifiers. Additionally, in a channel waveguide a maximum internal gain of 3.5 dB/cm at the 1533nm peak was realized. Recent crystal film quality improvements promise further performance enhancements needed for the intended application for high-peak power sources in the 1.6-μm spectral region targeting Earth observation systems for monitoring greenhouse gases.

greenhouse gases; planar waveguide amplifiers↗

Verification of the Uniformly-Ordered Binary Decision Algorithm in Correlated-Benchmark Whisper Calculations

Whisper is a nuclear criticality safety code package that aids analysts in validation exercises by computing upper subcritical limits (USL) for applications of interest. To obtain statistically meaningful, significant, and conservative USLs, the analyst must ensure that Whisper selects a sufficient number of benchmarks that are neutronically similar to the application. Many of the available benchmarks are correlated but are currently treated as independent, leading to an artificially small sample size, as their individual information contributions will be overestimated. To aid the analyst in obtaining a sufficient sample size, prior work [2] demonstrated application of the Uniformly-Ordered Binary Decision (UOBD) algorithm in adjusting benchmark weights to account for benchmark correlations. This work provides verification of the Whisper implementation and considers the impact of updated benchmark correlations compared to those available previously. We demonstrate that the UOBD algorithm performs as expected with an analytic example. With HEU-SOL-THERM-001 cases 1 through 10 as the applications, we compare the USLs computed with benchmark correlations available in the Whisper 1.1 release only to those computed with additional benchmark correlations from DICE 2023 and demonstrate substantive differences.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

SHF: Symmetrical Hierarchical Forest with Pretrained Vision Transformer Encoder for High-Resolution Medical Segmentation

This paper presents a novel approach to addressing the long-sequence problem in high-resolution medical images for Vision Transformers (ViTs). Using smaller patches as tokens can enhance ViT performance, but quadratically increases computation and memory requirements. Therefore, the common practice for applying ViTs to high-resolution images is either to: (a) employ complex sub-quadratic attention schemes or (b) use large to medium-sized patches and rely on additional mechanisms within the model to capture the spatial hierarchy of details. We propose Symmetrical Hierarchical Forest (SHF), a lightweight approach that adaptively patches the input image to increase token information density and encode hierarchical spatial structures into the input embedding. We then apply a reverse depatching scheme to the output embeddings of the transformer encoder, eliminating the need for convolution-based decoders. Unlike previous methods that modify attention mechanisms or use a complex hierarchy of interacting models, SHF can be retrofitted to any ViT model to allow it to learn the hierarchical structure of details in high-resolution images without requiring architectural changes. Experimental results demonstrate significant gains in computational efficiency and performance: on the PAIP WSI dataset, we achieved a 3∼32×speedup or a 2.95%∼7.03% increase in accuracy (measured by Dice score) at a 64K2 resolution with the same computational budget, compared to state-of-the-art production models. On the 3D medical datasets BTCV and KiTS, training was 6×faster, with accuracy gains of 6.93% and 5.9%, respectively, compared to models without SHF.

Zhang, Enzhi [Hokkaido University, Japan]↗

Electronic correlations and topology in Kondo insulator PuB 6

Utilizing a combination of dynamical mean field theory (DMFT) and density functional theory, it has been theoretically proposed that PuB 6 is a strongly correlated topological insulator characterized by nontrivial 𝐙 2 topological invariants and metallic surface states [X. Deng et al., Phys. Rev. Lett. 111, 176404 (2013)]. Here, we demonstrate through low-temperature magnetotransport measurements and first-principles calculations that PuB 6 exhibits characteristics of a topological Kondo insulating state. These features include a transition in electrical resistivity from high-temperature, thermally activated behavior with a narrow gap at the Fermi level (Δ⁢𝜌 ∼ 20 meV) to a distinctive low-temperature plateau, as well as a surface-to-volume dependence of electrical resistivity at low temperatures. The topological nature of PuB 6 is further supported by the theoretical calculations, which show that GGA + 𝑈 is capable of capturing electronic, topological, and lattice properties of PuB 6 with much lower computational cost than DMFT.

36 - MATERIALS SCIENCE↗

EDS Analysis of FCCI in AFC-FAST Fuel Pins

The Advanced Fuel Campaign’s Fission Accelerated Steady-state Testing (FAST) program uses metallic fuel pins with small diameters to reach a desired burnup more quickly. This enables accelerated testing of advanced fuel designs and decreases the time between idea conception and commercial usage. Post-irradiation examination is critical in this process, especially with respect to the fuel-cladding chemical interactions (FCCI). In this work, energy dispersive X-ray spectroscopy (EDS) is used to track how elements from the fuel and fission products have diffused through the cladding. Elemental redistribution along the fuel-cladding interface is mapped and FCCI region thicknesses are measured. The correlations between geometry, temperature, burnup, and FCCI thickness are presented.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗