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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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Decoding the Pair Distribution Function of Uranium in Molten Fluoride Salts from X-Ray Absorption Spectroscopy Data by Machine Learning

Thermal properties of actinides in molten salts are linked to the strongly disordered local environment of actinide ions. Here, we illustrate both the limitations of the commonly used fitting method for analysis of extended X-ray absorption fine structure (EXAFS) spectra in molten UF 4 and a possible solution using an "objective neural network - EXAFS" (ONNE) method. ONNE provides both extraction of the pair distribution function, as validated by its application to the EXAFS spectra calculated on molecular dynamics trajectory, and the EXAFS data reconstruction. The ONNE analysis of the molten UF4 has revealed reduction of the first nearest neighbor U-F coordination number, expansion of the U-F bond length and smaller contribution to the second shell compared to its crystalline counterpart. This method is therefore an attractive alternative to conventional EXAFS analysis and molecular dynamics simulations for studies of disordered environment of actinides in molten salts.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Light-powered end-to-end neutron detection and imaging with an edge-deployed optical AI chip

Neutron detection is widely used in many applications including nuclear physics, nuclear energy, nuclear technologies and nuclear safeguards. Developing an end-to-end neutron detection and imaging workflow paves way towards fully automated processes for many applications. We implemented an automated workflow for neutron detection experiments which use a solid state image sensor to capture neutron hits as a digital image. We deploy the workflow to an edge-based optical neural network (ONN) to increase the radiation-hardness and lifetime of neutron detection instruments. We present a two-stage neural network framework for detection of neutrons at sub-pixel resolution. The first stage uses a region proposal network to efficiently detect and extract neutron hits from the input camera image. The second stage feeds the extracted hits into a fully connected neural network to predict the sub-pixel hit position. The performance of the two-stage framework is evaluated using the edge-based ONN. The results show that we can achieve above 96% neutron detection accuracy as well as sub-pixel and sub-micron position resolution, while enjoying the advantages of the ONN hardware including radiation-hardness, low energy consumption and high computing speed for integrated edge camera and hardware deployment, when compared with electronic counterparts.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Femtojoule optical nonlinearity for deep learning with incoherent illumination

Optical neural networks (ONNs) are a promising computational alternative for deep learning due to their inherent massive parallelism for linear operations. However, the development of energy-efficient and highly parallel optical nonlinearities, a critical component in ONNs, remains an outstanding challenge. Here, we introduce a nonlinear optical microdevice array (NOMA) compatible with incoherent illumination by integrating the liquid crystal cell with silicon photodiodes at the single-pixel level. We fabricate NOMA with more than half a million pixels, each functioning as an optical analog of the rectified linear unit at ultralow switching energy down to 100 femtojoules per pixel. With NOMA, we demonstrate an optical multilayer neural network. Our work holds promise for large-scale and low-power deep ONNs, computer vision, and real-time optical image processing.

36 MATERIALS SCIENCE↗

Neural network methods for radiation detectors and imaging

Recent advances in image data proccesing through deep learning allow for new optimization and performance-enhancement schemes for radiation detectors and imaging hardware. This enables radiation experiments, which includes photon sciences in synchrotron and X-ray free electron lasers as a subclass, through data-endowed artificial intelligence. We give an overview of data generation at photon sources, deep learning-based methods for image processing tasks, and hardware solutions for deep learning acceleration. Most existing deep learning approaches are trained offline, typically using large amounts of computational resources. However, once trained, DNNs can achieve fast inference speeds and can be deployed to edge devices. A new trend is edge computing with less energy consumption (hundreds of watts or less) and real-time analysis potential. While popularly used for edge computing, electronic-based hardware accelerators ranging from general purpose processors such as central processing units (CPUs) to application-specific integrated circuits (ASICs) are constantly reaching performance limits in latency, energy consumption, and other physical constraints. These limits give rise to next-generation analog neuromorhpic hardware platforms, such as optical neural networks (ONNs), for high parallel, low latency, and low energy computing to boost deep learning acceleration (LA-UR-23-32395).

edge computing↗

Associations between hormone therapy use and tau accumulation in brain regions vulnerable to Alzheimer’s disease

Elucidating the downstream impact of exogenous hormones on the aging brain will have far-reaching consequences for understanding why Alzheimer’s disease (AD) predominates in women almost twofold over men. We tested the extent to which menopausal hormone therapy (HT) use is associated with later-life amyloid-β (Aβ) and tau accumulation using PET onN = 146 baseline clinically normal women, aged 51 to 89 years. Women were scanned over a 4.5-year (SD, 2.1; range, 1.3 to 10.4) and 3.5-year (SD, 1.5; range, 1.2 to 8.1) period for Aβ and tau, respectively, ~14 years after the initiation of HT. In older women (aged >70 years), HT users exhibited faster regional tau accumulation relative to non-users, localized to the entorhinal cortex and the inferior temporal and fusiform gyri, with an indirect effect of HT on cognitive decline through regional tau accumulation. In younger women (aged <70 years), HT associations with tau accumulation were negligible. Findings are relevant for optimizing menopausal treatment guidelines.

Science & Technology - Other Topics↗

Microcomputer-based doppler systems for weather monitoring

Ground-based microcomputer determines geographical positions of beacons using Doppler data from weather satellites. System requires onnly 7 W and incorporates least-squares iteration to compute positions. Results are printed out in alphanumerics either on CRT or on teletype. 6502 CPU was used, although equivalent processor could be substituted (with appropriate modifications to hardware).

Schmid, P. E.↗

Refractory Materials for Flame Deflector Protection System Corrosion Control: Similar Industries and/or Launch Facilities Survey

A trade study and litera ture survey of refractory materials (fi rebrick. refractory concrete. and si licone and epoxy ablatives) were conducted to identify candidate replacement materials for Launch Complexes 39A and 398 at Kennedy Space Center (KSC). In addition, site vis its and in terviews with industry expens and vendors of refractory materials were conducted. As a result of the si te visits and interviews, several products were identified for launch applications. Firebrick is costly to procure and install and was not used in the si tes studied. Refractory concrete is gunnable. adheres well. and costs less 10 install. Martyte. a ceramic fi lled epoxy. can protect structural stccl but is costly. difficullto apply. and incompatible with silicone ablatives. Havanex, a phenolic ablative material, is easy to apply but is costly and requires frequent replacement. Silicone ablatives are ineJ[pensive, easy to apply. and perl'onn well outside of direct rocket impingement areas. but refractory concrete and epoxy ablatives provide better protection against direcl rocket exhaust. None of the prodUCIS in this trade study can be considered a panacea for these KSC launch complexes. but the refractory products. individually or in combination, may be considered for use provided the appropriate testing requirements and specifications are met.

Calle, Luz Marina↗

Fabrication of Large-Area Metal-on-Carbon Catalytic Condensers for Programmable Catalysis

Catalytic condensers stabilize charge on either side of a high-k dielectric film to modulate the electronic states of a catalytic layer for the electronic control of surface reactions. Here, carbon sputtering provided for fast, large-scale fabrication of metal–carbon catalytic condensers required for industrial application. Carbon films were sputtered on HfO 2 dielectric/p-type Si with different thicknesses (1, 3, 6, and 10 nm), and the enhancement of conductance and capacitance of carbon films was observed upon increasing the carbon thickness following thermal treatment at 400 °C. After Pt deposition on the carbon films, the Pt catalytic condenser exhibited a high capacitance of ∼210 nF/cm 2 that was maintained at a frequency ∼1000 Hz, satisfying the requirement for a dynamic catalyst to implement catalytic resonance. Temperature-programmed desorption of carbon monoxide yielded CO desorption peaks that shifted in temperature with the varying potential applied to the condenser (−6 or +6 V), indicating a shift in the binding energy of carbon monoxide on the Pt condenser surface. A substantial increase in capacitance (∼2000 nF/cm 2 ) of the Pt-on-carbon devices was observed at elevated temperatures of 400 °C that can modulate ∼10% of charge per metal atom when 10 V potential was applied. A large catalytic condenser of 42 cm 2 area Pt/C/HfO 2 /Si exhibited a high capacitance of 9393 nF with a low leakage current/capacitive current ratio (<0.1), demonstrating the practicality and versatility of the facile, large-scale fabrication method for metal–carbon catalytic condensers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Grand Challenges and Opportunities in Stimulated Dynamic and Resonant Catalysis

Traditional heterogeneous catalysis is constrained by kinetic and thermodynamic limits, such as the Sabatier principle and reaction equilibrium. Dynamic and resonant catalysts hold promise to overcome these limitations by actively oscillating a catalyst’s physical or electronic structure at the time scale of the catalytic cycle, allowing programmable control over reaction pathways, and leading to improved rate and selectivity. External stimuli such as temperature swing, mechanical strain, electric charge, and light can perturb catalyst surfaces in different ways, altering adsorbate coverage, binding energies, and transition states beyond what steady-state catalysis allows. This work surveys the current state of dynamic catalysis, introduces the concept of “ stimulando ” characterization for observing transient dynamics, and outlines key modeling, mechanistic, and benchmarking strategies to advance the field toward improved chemical transformation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Alumina–Titania Nanolaminate Condensers for Hot Programmable Catalysis

Nanolaminates composed of thin alternating layers of Al2O 3 and TiO 2 (ATO) were engineered by using atomic layer deposition as the dielectric material for a Pt-on-carbon catalytic condenser. Investigation assessed synthesis parameters including the deposition temperature, Al 2 O 3 and TiO 2 layer thicknesses, total number of layers, and a capping Al 2 O 3 layer on the maximum charge accumulation in the Pt catalyst. The highest capacitance ATO configuration demonstrated a specific capacitance of ∼1200 nF/cm 2 with working voltages of ±5 V, enabling the storage of 4 × 10 13 electrons or holes per cm 2 at room temperature. The ATO devices exhibited enhanced capacitance at elevated temperatures of up to 400 °C, suggesting the suitability of these materials for high-temperature applications. Adsorption of carbon monoxide on the Pt/C-ATO device characterized by grazing incidence infrared spectroscopy showed changes in the surface binding energy of 13.1 ± 0.8 kJ/mol for an applied external voltage bias of ±1 V.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Flexible and Extensive Platinum Ion Gel Condensers for Programmable Catalysis

Catalytic condensers composed of ion gels separating a metal electrode from a platinum-on-carbon active layer were fabricated and characterized to achieve more powerful, high surface area dynamic heterogeneous catalyst surfaces. Ion gels comprised of poly(vinylidene difluoride)/1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide were spin coated as a 3.8 μm film on a Au surface, after which carbon sputtering of a 1.8 nm carbon film and electron-beam evaporation of 2 nm Pt clusters created an active surface exposed to reactant gases. Electronic characterization indicated that most charge condensed within the Pt nanoclusters upon application of a potential bias, with the condenser device achieving a capacitance of ∼20 μF/cm 2 at applied frequencies of up to 120 Hz. The maximum charge of ∼10 14 |e – | cm –2 was condensed under stable device conditions at 200 °C on catalytic films with ∼10 15 sites cm –2 . Grazing incidence infrared spectroscopy measured carbon monoxide adsorption isobars, indicating a change in the CO* binding energy of ∼19 kJ mol –1 over an applied potential bias of only 1.25 V. Condensers were also fabricated on flexible, large area Kapton substrates allowing stacked or tubular form factors that facilitate high volumetric active site densities, ultimately enabling a fast and powerful catalytic condenser that can be fabricated for programmable catalysis applications.

Catalysis↗

Catalytic Hydrogenation of Alkylphenols for Renewable Caprolactone

Selective hydrogenation of lignin-derived alkyl-phenol to alkyl-cyclohexanone is a key step in the synthesis of renewable caprolactone from lignin-derived monomers. Selective hydrogenation of p-cresol, a model compound for lignin-derived monomers, to 4-methyl-cyclohexanone was conducted using Pd/γ-Al 2 O 3 in a continuous three-phase flow reactor with side products of 4-methyl cyclohexanol. High conversion (85%) and selectivity (>93%) were demonstrated at ambient reaction pressure. Evaluation of the hydrogenation at different reaction parameters showed that the reaction selectivity was determined by the surface coverage of p-cresol and 4-methyl cyclohexanone. Furthermore, high selectivity to 4-methyl cyclohexanone was also attributed to the lower apparent activation barrier of p-cresol hydrogenation (67 ± 2 kJ mol –1 ) compared to that of hydrogenation 4-methyl cyclohexanone (92 ± 11 kJ mol –1 ), with a faster rate of initial hydrogenation of p-cresol relative to carbonyl hydrogenation of 4-methyl-cyclohexanone.

36 MATERIALS SCIENCE↗

Multi-window spectrum estimation - A linear algebraic approach

The purpose of this paper is to elucidate the multi-window method for spectral estimation and sinusoid detection. The multi-window method, devised by D.J. Thomson, has many features that distinguish it from other spectrum estimation techniques. It has an elegant derivation, starting from first principles and using optimality arguments. It lends itself to performance analysis and provides a built-in measure of its reliability. In contrast to Thomson's integral equation derivation, we use linear algebraic methods both to treat the problem and to develop the solution. In addition to the tutorial, we present an overview of published generalizations and analyses of the method.

Onn, Ruth↗