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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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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Smelly-Odor Webtool (Smelly) v1

Smelly is an interactive webtool displaying odor dispersion from various potential waste-to-energy sites across California. It currently displays data for dry anaerobic digestion technology with organic waste intake of 90,000 tons per year. The model addresses meteorological and geographical differences in offsite odor impacts (Jin et al. 2019). In addition to interactive display of odor dispersions, the embedded emission calculator provides two additional functionalities: (1) determine the impact distance for given onsite odor emission rates; and (2) determine allowable odor emission rates at given separation distance between the facility and its downwind communities. Please note that data and model is preliminary at this point and serve as a Proof of Concept. Additional data collection, modeling and research is needed for final application.

Jin, Ling↗
DOE OSTI2024

Acoustic-based monitoring and machine learning of component status for microreactor applications

This report provides a description and assessment of recent efforts to couple acoustic-based experimental measurements and characterization with machine learning models in order to enhance structural health monitoring capabilities for nuclear microreactors. With resilient embedded sensors in development by others supported by programs funded by the US Department of Energy’s Office of Nuclear Energy, the work described herein builds upon ongoing efforts to improve non-destructive testing technology that relates measured acoustic signatures to component stresses and/or structural defects, using a combination of new experimental measurements and machine learning architectures. The experimental procedure remained similar to that developed for the previous year’s demonstration of damage detection by the authors, with the same damaged sample tested under similar applied stress conditions. Notably, a new mounting fixture was designed and implemented to improve measurement consistency and a more sophisticated laser Doppler vibrometer was employed to make high-fidelity vibration measurements. Two nominally identical sets of training data were collected for each experimental setup to better understand the repeatability of the experiment and to better test the generality of trained neural network models. Additionally, we obtained new high-quality 3D mode shapes of the damaged test article at various stress and excitation levels, providing greater insights into the physical response of the sample during testing. Previously, we demonstrated that a machine learning model based on a convolutional neural network can predict structural details of an artificially introduced interface (intact, rough cut, smooth cut), and the applied torque level. In this study, we have transitioned to graph-based neural network architectures to better develop and test a flexible framework that is more suitable to being transferred away from controlled benchtop experiments and into more applied settings where less-structured data inputs may be expected. In general, performance testing of a graph neural network on frequency-domain representations of the data indicates strong and consistent identification of test conditions for datasets recorded on damaged components. With goals of predicting damage location and other changing experimental conditions using limited datasets, predictive models using a graph neural network architecture correctly predicted the applied torque level with an accuracy of 85% using only a single measurement point and predicted within one torque level in 95% of test windows. Predictions of damage location had limited success due to the symmetry and minimal number of the damage scenarios presented during model training. Results were ambiguous as to whether the model could detect the location of the artificial damage, or if it was instead learning the location of a given measurement point on the part and subsequently detecting which points were closest to the location of the damage. This finding will be factored into upcoming planned work on damaged graphite components, where new experimental tests with a larger number and variety of damage scenarios are expected to provide improved validation of recent developments in monitoring methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

A 20 Gbps Data Transmitting ASIC with PAM4 for Particle Physics Experiments

We present the design principle and test results of a data transmitting ASIC, GBS20, for particle physics experiments. The goal of GBS20 will be an ASIC that employs two serializers each from the 10.24 Gbps lpGBT SerDes, sharing the PLL also from lpGBT. A PAM4 encoder plus a VCSEL driver will be implemented in the same die to use the same clock system, eliminating the need of CDRs in the PAM4 encoder. This way the transmitter module, GBT20, developed using the GBS20 ASIC, will have the exact lpGBT data interface and transmission protocol, with an output up to 20.48 Gbps over one fiber. With PAM4 embedded FPGAs at the receiving end, GBT20 will halve the fibers needed in a system and better use the input bandwidth of the FPGA. A prototype, GBS20v0 is fabricated using a commercial 65 nm CMOS technology. This prototype has two serializers and a PAM4 encoder sharing the lpGBT PLL, but no user data input. An internal PRBS generator provides data to the serializers. GBS20v0 is tested barely up to 20.48 Gbps. With lessons learned from this prototype, we are designing the second prototype, GBS20v1, that will have 16 user data input channels each at 1.28 Gbps. We present the design concept of the GBS20 ASIC and the GBT20 module, the preliminary test results, and lessons learned from GBS20v0 and the design of GBS20v1 which will be not only a test chip but also a user chip with 16 input data channels.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

The MIST-1 and MIST-2 multicusp ion sources for high-current $H$$^{+}_{2}$ beams

We present two iterations of the Multicusp Ion Source Technology at MIT (MIST) sources, designed to fulfill the requirements of the HCHC-XX cyclotron design. The HCHC-XX is a novel compact cyclotron accelerating $H$$^{+}_{2}$. Beam is injected through a radio-frequency quadrupole buncher-accelerator (embedded in the cyclotron yoke) and utilizes so-called vortex motion during acceleration. If successful, it will deliver 10 mA of protons at 60 MeV in CW mode. This scheme requires a low-emittance, high-current initial beam with high $H$$^{+}_{2}$ purity. We briefly summarize the design and previous results of the MIST-1 ion source and, for the first time, the detailed design of the new and improved MIST-2, including the mechanical, electrical, and control system design. We further show experimental results of using the MIST-2 backplate on the MIST-1 body, present a study using different types of permanent magnets for confinement (including no magnets), and finally, we present first results of the MIST-2 in full operation. In this first commissioning run, we were able to increase the total extracted current from the MIST-2 to 7 mA—a factor of 2 over the MIST-1.

Winklehner, D. [Massachusetts Institute of Technol↗
DOE OSTI2021

Actinide Molten Salts: A Machine-Learning Potential Molecular Dynamics Study

We know that actinide molten salts represent a class of important materials in nuclear energy. Understanding them at a molecular level is critical to proper and optimal design of relevant technological applications. Yet, owing to the complexity of electronic structure due to the 5f orbitals, computational studies of heavy elements in condensed phases using ab initio potentials to study the structure and dynamics of these elements embedded in molten salts are difficult. This lack of efficient computational protocols makes it difficult to obtain information on properties that require extensive statistical sampling like transport. To tackle this problem, we adopted a machine-learning approach to study ThCl 4 -NaCl and UCl 3 -NaCl binary systems. The machine-learning potential, with the density functional theory accuracy, allows us to obtain long molecular dynamics trajectories (ns) for large systems (10 3 atoms) at a considerably low computing cost, thereby efficiently gaining information about their bonding structures, thermodynamics, and dynamics at a range of temperature. We observed a considerable change in the coordination environments of actinide elements and their characteristic coordination-sphere lifetime. Our study also suggests that actinides in molten salts may not follow well known entropy-scaling laws.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Divertor Component Testing

Power exhaust is an immense challenge in tokamaks. Commonwealth Fusion Systems (CFS), in collaboration with MIT and others, is working on the design of a compact (R 0 = 1.85 m), high-field (B 0 = 12 T) tokamak for the demonstration of net fusion energy, called SPARC. Empirical scaling laws indicate that the unmitigated heat flux in the boundary plasma will exceed 10 GW/m 2 . Such high heat fluxes will be a formidable challenge. The scope of this work is to utilize the HHF testing expertise maintained by ORNL, used in support of NSTX-U and to demonstrate the thermal performance of tungsten-coated graphitic foam targets, to help CFS and its collaborators to assess the performance of (1) base materials (tungsten and its alloys) and (2) divertor mockups under SPARC-like divertor heat flux conditions. These activities will be performed by ORNL personnel using electron beam exposure facilities at the Pennsylvania State University’s Applied Research Laboratory (ARL). ARL is a Department of Defense University Affiliated Research Center where ORNL has successfully executed NSTX-U and graphitic foam high heat flux testing using electron beam (e-beam) facilities, which is a nonstandard service. For the assessment of base materials, CFS will do an initial thermal analysis, in consultation with ORNL, to understand under what scenarios the materials are most likely to fail. CFS will supply to ORNL various tungsten-based material samples to test with testing taking 3 weeks. ORNL will thermally stress the samples under SPARC divertor-like conditions to either failure or to a prescribed number of pulses. ORNL will record experimental data, including IR surface temperature and embedded thermocouple readings, and report results to CFS

36 MATERIALS SCIENCE↗
DOE OSTI2026

Carbon-Based Quantum Information Science with Symmetry Protected Topological States (Final Report, DOE-BES award DE-SC0023105)

This research program established the scientific foundation for the rational, bottom-up design, synthesis, isolation, and investigation of symmetry-protected topological (SPT) electron spin qubits embedded in graphene nanoribbons (GNRs). The work focused on integrating atomically precise low-dimensional carbon nanostructures with emerging quantum logic architectures, providing a pathway toward scalable quantum materials for next-generation computing and sensing technologies. A central component of the program was the elucidation of fundamental relationships between real-space molecular architecture, local spin density distributions, electronic band dispersion, and energy level alignment in atomically precise GNR systems. These correlations define key operational parameters of SPT qubits and were systematically investigated to establish quantitative benchmarks against established molecular and solid-state spin qubit platforms. Attention was given to properties critical for quantum device performance, e.g. decoherence times, spectral sharpness of energy transitions, and tunable exchange interactions between spin states. The research demonstrated that these parameters can be engineered with atomic precision through scalable bottom-up synthetic strategies. Theory-guided design played a central role in identifying candidate structures hosting topologically protected spin states. Experimental validation was performed using both ensemble measurements and single-molecule characterization. In addition to advances in quantum materials synthesis, the program developed and applied spin-sensitive scanning probe microscopy techniques capable of directly probing quantum states and dynamic processes with atomic-scale spatial resolution. These capabilities enabled direct observation and characterization of quantum structures at the single-atom level. While the research activities were primarily hypothesis-driven fundamental investigations, the program adopted a comprehensive materials-by-design framework aimed at translating scientific discoveries into technological concepts compatible with scalable and intelligent manufacturing approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Enhanced nonlinear interaction of polaritons via excitonic Rydberg states in monolayer WSe 2 .

Strong optical nonlinearities play a central role in realizing quantum photonic technologies. Exciton-polaritons, which result from the hybridization of material excitations and cavity photons, are an attractive candidate to realize such nonlinearities. While the interaction between ground state excitons generates a notable optical nonlinearity, the strength of such interactions is generally not sufficient to reach the regime of quantum nonlinear optics. Excited states, however, feature enhanced interactions and therefore hold promise for accessing the quantum domain of single-photon nonlinearities. Here we demonstrate the formation of exciton-polaritons using excited excitonic states in monolayer tungsten diselenide (WSe 2 ) embedded in a microcavity. The realized excited-state polaritons exhibit an enhanced nonlinear response ~[Formula: see text] which is ~4.6 times that for the ground-state exciton. The demonstration of enhanced nonlinear response from excited exciton-polaritons presents the potential of generating strong exciton-polariton interactions, a necessary building block for solid-state quantum photonic technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

CIE Curriculum Guide (V.2.0)

The Cyber-Informed Engineering (CIE) Curriculum Guide offers a comprehensive framework, guidance, and resources for integrating CIE into university-level engineering programs and related educational activities. The primary goal is to help educators adopt CIE principles into their teaching to produce future engineers and technicians who understand digital risks in modern engineered systems, thereby addressing the nation’s infrastructure resilience needs. This guide outlines practical integration examples, links to resources to accelerate CIE adoption, and shares insights from partner academic institutions on various implementation strategies. CIE is a framework for embedding engineered controls that mitigate the impact of cyber-attacks in any cyber-physical system used in critical energy infrastructure and other sectors. Developed by the U.S. Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER), the National Cyber-Informed Engineering Strategy emphasizes embedding CIE into formal education, training, and credentialing. This guide supports this strategic objective by providing examples of integrating CIE concepts into engineering curricula, from class activities to new courses and certificate programs. The importance of educating cyber-informed engineers is underscored by the evolving cybersecurity threats facing engineered systems. As industrial control systems (ICS) increasingly incorporate digital technologies, the responsibility for security extends to both cyber professionals and engineers. CIE addresses critical gaps in designing and protecting physical systems with digital components against cyber risks, ensuring engineers consider digital risk throughout the engineering design lifecycle. Currently, engineering education does not routinely include cyber-informed principles, highlighting a gap in addressing modern engineering system risks. This guide advocates for updating engineering curricula to include digital risk management as a fundamental element. By doing so, future engineers will be equipped to design resilient systems that mitigate digital risks from the outset. Through this guide, engineering faculty can integrate CIE into their curricula, bridging the gap between digital risk and engineering. This approach prepares a cyber-informed workforce capable of safeguarding the cyber-physical systems crucial to national security and public welfare. By embedding CIE into education and training, institutions can produce engineers and technicians who can effectively mitigate cyber impacts throughout the engineering design lifecycle, resulting in more secure critical infrastructures.

42 - ENGINEERING↗
DOE OSTI2025

Multimetallic Layered Composites (MMLCs) for Rapid, Economical Advanced Reactor Deployment (Final Report)

This project focused on the development of multi-metallic layered composites (MMLCs) for advanced fission reactor technologies. There are many instances where one alloy or material simply cannot meet all the demands thrown at it by a reactor system, or cannot allow it to perform as strongly as one would like. Instead of focusing all our effort on developing one perfect alloy, we seek to leverage the design principle of “separation of functionality,” used in many other arenas in design, to boost performance beyond single alloys alone. One illustrative example shows the power of this approach for molten salt-cooled reactors: A three meter tall, three meter diameter reactor vessel made of Incoloy 800 was quoted at $\$$500k in 2018. A Hastelloy N vessel was quoted at $\$$5M. An MMLC vessel, in which a layer of Hastelloy N would be weld-overlaid onto Incoloy 800, was quoted at $\$$700k, and it would achieve the same performance. The potential economic gains of leveraging this approach are therefore substantial. At a minimum, each MMLC would contain one core structural layer and one coolant-facing corrosion-resistant layer. Sometimes, MMLCs required buffer layers, as the structural and corrosion-resistant layers were metallurgically incompatible. In other words, they didn’t always play nice, thus separating layers compatible with both functioned as intermediaries to keep the composite together. However, in doing so we inevitably produce new interfaces, where new issues can arise. Therefore, this project focused on what happens at these interfaces from a combination of high temperatures, irradiation, corrosion, and time. After all, a reactor makes money when it is operating, and outages of any kind erode its economic viability. First, we set out to experimentally prove that MMLCs for at least two advanced reactor systems can be made, today, in US domestic facilities. In this respect we were successful – one MMLC (a Ni-201/Incoloy 800H composite) was successfully made and drawn into two-inch coolant piping. Others were attempted, though new issues relating to cracking in vanadium layers for one and radiation damage performance of the corrosion-resistant layer in another prevented us from moving further in those specific arenas – these are engineering problems which deserve continued focus after this project. Additional experimental work focused on long-term corrosion testing of the outermost layers of the salt-cooled and liquid lead-cooled MMLC concepts, which would then be fed into predictions of how long the MMLCs could last. Next, computational (thermodynamics and atomistic) simulation studies studied how much we expect the interfaces to “blend,” due to the mixing action of neutron irradiation. This eats into both the margin for the structural layer of each MMLC, as dilution from the corrosion-resistant layer into the structural layer would decrease the total load-bearing capacity of an MMLC of finite size. On the other hand, dilution of the corrosion-resistant layer into the structural layer further reduced the margin of corrodible material, reducing the lifetime of the MMLC or necessitating extra thickness to be imparted to the MMLC to meet its functional requirements. Work here focused on irradiation-induced segregation to predict new phases which may embrittle the MMLCs, as well as quantifying irradiation-induced mixing at each interface. The results showed that mixing is expected, but it is both steady and therefore predictable, and not lifetime-limiting for most MMLC concepts – it simply has to be accounted for in calculations of reactor performance when utilizing an MMLC. Then, full-core simulations using the experimentally-derived corrosion data, the computationally discovered irradiation-induced mixing data (partially validated by experiment), and existing, benchmarked core designs for large and small sized reactor concepts (one salt-cooled, one lead-cooled) were conducted to quantify any expansion of reactor operating envelopes achieved by utilizing these MMLCs. This new framework, called REX (Reactor Envelope Expansion), incorporates a combination of core neutronics, thermal hydraulics, and the material performance data derived from this project to see how using an MMLC expands advanced fission reactor operating envelopes. It was discovered that in some cases, MMLC utilization does indeed increase the maximum operating temperatures and cycle lengths of reactor concepts, while in other cases it does not. Finally, our tech-to-market (T2M) strategy was not necessarily to create specific embodiments of MMLCs for immediate sale (because getting into the nuclear market is incredibly slow and laden with regulation, this is a long-term goal), but rather immediate stimulation of US industry using the design approach of MMLCs derived from this project. In this respect we were successful, as one of the PhD students funded on this project co-founded Allium Engineering, Inc., which created a stainless steel / low-alloy steel MMLC to function as chloride corrosion-resistant rebar for embedding into concrete structures. Allium Engineering continues to be successful, having recently opened their first factory as of this writing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

FastML Science Benchmarks: Accelerating Real-Time Scientific Edge Machine Learning

Applications of machine learning (ML) are growing by the day for many unique and challenging scientific applications. However, a crucial challenge facing these applications is their need for ultra low-latency and on-detector ML capabilities. Given the slowdown in Moore's law and Dennard scaling, coupled with the rapid advances in scientific instrumentation that is resulting in growing data rates, there is a need for ultra-fast ML at the extreme edge. Fast ML at the edge is essential for reducing and filtering scientific data in real-time to accelerate science experimentation and enable more profound insights. To accelerate real-time scientific edge ML hardware and software solutions, we need well-constrained benchmark tasks with enough specifications to be generically applicable and accessible. These benchmarks can guide the design of future edge ML hardware for scientific applications capable of meeting the nanosecond and microsecond level latency requirements. To this end, we present an initial set of scientific ML benchmarks, covering a variety of ML and embedded system techniques.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Strain gauge for testing microreactor hexagonal core blocks in the Single Primary Heat Extraction and Removal Emulator

To support the development and deployment of microreactor technologies, experiments that help verify and validate reactor systems and components are performed at non-nuclear test facilities. The Single Primary Heat Extraction Removal Emulator at Idaho National Laboratory is one of these test facilities and was used to monitor a test article that has a prototypic geometry of a heat-pipe cooled microreactor core block. To collect crucial temperature and strain data during testing, temperature and strain sensing fiber optics were embedded to the surface of the test article using an ultrasonic additive manufacturing technique. To support and provide benchmark strain data for the embedded sensors, a commercial resistive strain gauge was attached. This report will discuss the results from the deployment of the commercial strain gauge which includes the setup/attachment strategies, data acquisition, and analysis of the strain data.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Force-Triggered, Biobased Sealants for Prefabricated Building Components: Toward Improved Efficiency and Performance

The prefabricated building construction industry has made extensive progress in expediting the manufacture of prefabricated components at off-site plants. However, the sealing of joints between these components, which is crucial to ensuring the weatherproofing of the assembly, still represents a labor-intensive, on-site effort that relies on the manual installation of tapes and caulks. Here, to reduce work at the jobsite and improve the airtightness and waterproofness of building envelopes, we developed a sealant that can be installed at the plant on prefab components and have the curing reaction triggered at the jobsite by using microencapsulation technology to separate the reactive agents. A series of force-triggered, high-strength, and fast-curing sealants derived from biobased feedstocks were developed, which consist of a biobased epoxy agent encapsulated in a polymer shell, embedded in a biobased amine curing agent. The shell of the microcapsules allows an effective separation of the reactive species in the one-part sealant, allowing shelf stability to an otherwise fast-curing system as well as improving the hydrophobicity of the whole system. When force activates and breaks the microcapsules, the highly reactive epoxy and amine mix and cure, exhibiting peel strength values of up to 143 ppi (pounds per inch). The hydrophobicity of the sealants allows them to retain up to 94% of the original peel strength after complete submersion in water for 24 h, showcasing the water resistivity of the sealant system. The open-air shelf stability of the sealant complex is demonstrated by the obtention of peel strength values of ∼16 ppi when triggering the curing reaction even after being exposed 8 months to open air and humidity. The successful on-demand triggering of curing reactions and the shelf stability provide efficacy of these force-triggered sealants for installation on prefabricated components, storage for months prior to delivery, and assembly at a jobsite. These force-triggered biobased sealants for prefabricated buildings can result in lower installation time and cost and better performance than tapes and caulks at the jobsite.

biobased↗
DOE OSTI2025

T3CO-Go: A web-based dashboard for the Transportation Technology Total Cost of Ownership tool [SWR-25-38]

T3CO-Go is a web-based dashboard with a user interface to modify input assumptions, run the T3CO tool, and visualize results. The dashboard, built using Python, can be run on a local server when installed from PyPI or hosted on the cloud and embedded in a webpage. T3CO-Go allows even non-Python-proficient users to customize their T3CO experience and gain insights from results customized for their analysis purpose. See also, PyPI Package: https://pypi.org/project/t3co-go/

Panneer Selvam, Harish [National Renewable Energy ↗
DOE OSTI2026

3D printed water-stable Cd-doped Cs 4 MnBi 2 Cl 12 /polylactic acid perovskite/polymer composites for high-flux X-ray scintillation

Stable and efficient X-ray scintillators are crucial for medical diagnostics, industrial, and defense applications. However, conventional scintillator technologies face a trade-off between stability, optimal performance, and sustainability. Herein, we introduce 3D-printed Cs 4 MnBi 2 Cl 12 (Pero1) and Cs 4 Cd 0.68 Mn 0.32 Bi 2 Cl 12 (Pero2) perovskite microcrystals embedded within a polylactic acid (PLA) polymer composite as X-ray scintillators, combining efficiency, stability, and sustainability. The orange luminescent perovskite powder phosphors exhibited poor water stability, which was successfully addressed through incorporation into PLA via filament extrusion and fused deposition modeling (FDM) 3D printing. The resulting composite films demonstrated remarkable water stability while maintaining uniform orange emission throughout the polymer matrix, as confirmed by 3D topography scanning and X-ray fluorescence mapping. Structural characterization revealed minimal chemical interaction between the perovskite and PLA matrix, with the composites retaining their crystalline properties. The PLA-Pero2 composite exhibited superior optical properties, with a photoluminescence quantum yield of 47%, nearly 17 times higher than that of PLA-Pero1 (2.8%), attributed to the effective suppression of non-radiative decay pathways through Cd 2+ doping. Under hard X-ray irradiation at synchrotron beamlines, both composites exhibited excellent radioluminescence, with emission peaks at 605 nm, a linear response across a wide X-ray flux range, and remarkable radiation stability, showing less than 3% intensity degradation after 600 seconds of continuous high-dose exposure. The PLA-Pero2 composite achieved a spatial resolution of 5 line pairs per millimeter and a contrast ratio of 0.255. These performance metrics, combined with the polymer's biodegradability and scalability through additive manufacturing, position PLA-based composites as a more sustainable alternative to conventional petroleum-based polymer scintillators for next-generation medical imaging, radiation monitoring, and industrial radiography applications.

3D Printing↗