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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Regulatory Considerations in the Development of Radiation-Drug Combinations

Radiation therapy remains a fundamental treatment for patients with cancer. Despite an increasing number of targeted molecular therapies that are US Food and Drug Administration (FDA)-approved for the treatment of patients with metastatic disease, there has been very little progress made in terms of drugs used concurrently with radiation. This article reviews the existing regulatory framework in which cancer drugs may be developed for use in combination with radiation therapy from the perspective of the FDA. To briefly summarize: (1) nonclinical studies are a critical first step to ensure that drugs are safe for use in humans; however, additional nonclinical studies of a drug with radiation may not be required before a clinical trial in combination with radiation as long as the safety profile of the drug has been characterized in humans. The FDA determines the quality of evidence required before studying a drug in combination with radiation on a case-by-case basis. (2) Although often impractical to consider late toxicities during dose-escalation, late adverse events should be captured and taken into consideration when determining the final dose and schedule to take forward during drug development. (3) There are a number of expedited programs for cancer drug development, including accelerated approval, a conditional approval that allows for use of earlier clinical endpoints when the data suggests a clinically meaningful improvement over available therapy. (4) The Agency encourages sponsors to discuss their development plan with the appropriate FDA review division in formal regulatory meetings.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Unraveling transition-metal-mediated stability of spinel oxide via in situ neutron scattering

The energy materials performance is intrinsically determined by structures from the average lattice structure to the atom arrangement, valence, and distribution of the containing transition metal (TM) elements. Understanding the mechanism of the structure transition and atom rearrangement via synthesis or processing is key to expediting the exploration of excellent energy materials. In this work, in situ neutron scattering is employed to reveal the real-time structure evolution, including the TM-O bonds, lattice, TM valence and the migration of the high-voltage spinel cathode LiNi 0.5 Mn 1.5 O 4 . The transition-metal-mediated spinel destabilization under the annealing at the oxygen-deficient atmosphere is pinpointed. Additionally, the formation of Mn 3+ is correlated to the TM migration activation, TM disordered rearrangement in the spinel, and the transition to a layered-rocksalt phase. The further TM interdiffusion and Mn 2+ reduction are also revealed with multi-stage thermodynamics and kinetics. The mechanisms of phase transition and atom migrations as functions of temperature, time and atmosphere present important guidance on the synthesis in various-valence element containing oxides.

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

Logistics simulation of a remediation effort for a hypothetical radiological contamination scenario

To mitigate the effects following a large-scale nuclear or radiological material release in an urban environment and to expedite recovery, the Integrated Wash-Aid Treatment Emergency Reuse System (IWATERS) was developed. IWATERS consists of three operations: washing contaminated surfaces with an ionic wash solution, collecting, and treating the contaminated wash solution on-site to remove contaminants, and reusing the treated solution throughout operations to preserve the clean water resource. This study develops a framework to simulate the logistics of IWATERS deployment, thereby gaining an understanding of the timeline for decontamination operations. For this purpose, the Analysis of Mobility Platform and GoldSim were leveraged for a hypothetical contamination scenario covering 65,200 m 2 of an urban center. The framework reveals that remediation progress is limited by several resources, notably the availability of vermiculite, a reactive clay that is required to treat the contaminated wash solution. Further, this study also presents how the simulation approach can be used to characterize alternatives to reduce the influence of limited resources on operational progress. Overall, this work lays the foundation for evaluating different decontamination methods through detailed logistics simulation, i.e., by refining simulation assumptions and expanding the range of scenarios the simulation can depict.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Fast permeability measurement for tight reservoir cores using only initial data of the one chamber pressure pulse decay test

Here, in this study, a mathematical model for fast determination of the permeabilities of tight rocks using measurements taken from the initial period of the One Chamber Pressure Pulse Decay (OC-PPD) test is presented. The model applies to measurements taken both before and after the pressure pulse front has reached the downstream end of the specimen. The analytical solutions for the pressure decay in the upstream chamber are derived based on a parabolic arc approximation of pore pressure distribution along the test specimen. This approximation allows converting the initial–boundary value problem of fluid diffusion in the specimen, governed by partial differential equations, to a system of ordinary differential equations that can be easily solved by explicit formulae. Thus, an explicit formula for the pressure decay rate is obtained, which enables inverse analysis of the initial experimental data to estimate the rock permeability. The proposed method expedites the pulse decay test as it does not require the system to reach equilibrium. The method is validated with three sets of experimental data of the OC-PPD test using helium as the diffusing fluid, for which the relative error of the permeability is found to be less than 6%. This method is particularly useful if the equilibrium time of the pulse decay test for rock specimens with permeabilities in the range of nano-Darcy takes hours or days.

early-time solution↗
DOE OSTI2025

Natural isotopic compositions of titanium, iron, and nickel observed in commercial fuel pellets – Promising candidate elements for stable isotope tagging

Stable isotope taggants would constitute unique identifiers for nuclear fuel cycle materials, resulting in expedited timelines and high confidence provenance assessments for nuclear forensics investigations. However, reliably identifying and interpreting stable isotope taggants in nuclear materials recovered from outside of regulatory control will largely be predicated on the assumption that the taggant element intrinsic to the untagged nuclear material exhibits natural isotopic ratios. Here, we present high-precision Ti, Fe, and Ni isotope compositions in 13 commercial low-enriched uranium (LEU) fuel pellets to assess the suitability of these transition metals as stable isotope taggants. Our investigations reveal limited isotope variations among the fuel pellets in all three elements, which are consistent with small mass-dependent isotope fractionations, comparable to variations previously reported for natural samples. In practice, isotopically tagged nuclear materials are expected to fall along isotopic mixing lines, since intrinsic background levels of taggant elements dilute the taggant towards natural isotope compositions. Furthermore, the observation that Ti, Fe, and Ni isotope compositions in a suite of LEU fuel pellets are close to or indistinguishable from estimates for the Bulk Silicate Earth demonstrates that a two end-member mixing assumption would be valid for these transition metals, indicating that all three are promising candidate elements for stable isotope tagging. Finally, we present mass balance calculations to quantify isotopic perturbations expected from admixing isotopically anomalous Ti, Fe, and Ni taggants to assess the interplay between elemental and taggant concentrations and find favorable compromises for facilitating successful taggant identification with current analytical methods.

Intentional forensics↗
DOE OSTI2022

Overcoming the disconnect between energy system and climate modeling

Energy system models underpin decisions by energy system planners and operators. Energy system modeling faces a transformation: accounting for changing meteorological conditions imposed by climate change. To enable that transformation, a community of practice in energy-climate modeling has started to form that aims to better integrate energy system models with weather and climate models. In this work, we evaluate the disconnects between the energy system and climate modeling communities, then lay out a research agenda to bridge those disconnects. In the near-term, we propose interdisciplinary activities for expediting uptake of future climate data in energy system modeling. In the long-term, we propose a transdisciplinary approach to enable development of (1) energy-system-tailored climate datasets for historical and future meteorological conditions and (2) energy system models that can effectively leverage those datasets. This agenda increases the odds of meeting ambitious climate mitigation goals by systematically capturing and mitigating climate risk in energy sector decision-making.

17 WIND ENERGY↗
DOE OSTI2021

Thermodynamics and kinetics of 2D g-GeC monolayer as an anode materials for Li/Na-ion batteries

Development of high capacity anode materials is one of the essential strategies for next-generation high-performance Li/Na-ion batteries. Rational design, using density functional theory, can expedite the discovery of these anode materials. Here, we propose a new anode material, germanium carbide, g-GeC, for Li/Na-ion batteries. Our results show that g-GeC possesses both benefits of the high stability of graphene and the strong interaction between Li/Na and germanene. The single-layer germanium carbide, g-GeC, can be lithiated/sodiated on both sides yielding Li 2 GeC and Na 2 GeC with a storage capacity as high as 633 mA h/g. Besides germagraphene’s 2D honeycomb structure, fast charge transfer, and high (Li/Na)-ion diffusion and negligible volume change further enhance the anode performance. These findings provide valuable insights into the electronic characteristics of newly predicted 2D g-GeC nanomaterial as a promising anode for (Li/Na)-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

Adaptive learning-driven high-throughput synthesis of oxygen reduction reaction Fe–N–C electrocatalysts

Reducing human reliance on inefficient energy systems and fossil fuels has become more urgent due to the consequences of global climate change. However, traditional trial-and-error approaches have hampered our ability to accelerate the discovery and implementation of functional materials for efficient energy conversion devices, such as polymer electrolyte fuel cells (PEFCs). To address this, we develop an adaptive learning framework that integrates machine learning and state-of-the-art capabilities in high-throughput synthesis to achieve expedited optimization of iron-nitrogen-carbon PEFC oxygen reduction reaction (ORR) electrocatalysts. We use statistical inference, uncertainty quantification, and global optimization to build a computational design-of-experiment tool that identifies the optimum compositions to be investigated next to reduce the demands placed on experimental materials discovery. We benchmark the ability of the proposed strategy to discover optimum catalyst synthesis conditions in a six-dimensional search space when starting with a thirty-six-sample database. By following the adaptive learning strategy, we synthesize fourteen new catalysts from approximately ten billion unique compositions and discover four catalysts that outperform all original samples. The best machine learning-optimized catalyst is 33% more active than the highest-performing one in the initial database, showing an ORR activity seven times larger than those typically reported for the same class of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Development of a rapid viability RT-PCR (RV-RT-PCR) method to detect infectious SARS-CoV-2 from swabs

Since the rapid onset of the COVID-19 pandemic, its causative virus, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), continues to spread and increase the number of fatalities. To expedite studies on understanding potential surface transmission of the virus and to aid environmental epidemiological investigations, here we developed a rapid viability reverse transcriptase PCR (RV-RT-PCR) method that detects viable (infectious) SARS-CoV-2 from swab samples in <1 day compared to several days required by current gold-standard cell-culture-based methods. The method integrates cell-culture-based viral enrichment in a 96-well plate format with gene-specific RT-PCR-based analysis before and after sample incubation to determine the cycle threshold (C T ) difference (ΔC T ). An algorithm based on ΔC T ≥ 6 representing ~ 2-log or more increase in SARS-CoV-2 RNA following enrichment determines the presence of infectious virus. The RV-RT-PCR method with 2-hr viral infection and 9-hr post-infection incubation periods includes ultrafiltration to concentrate virions, resulting in detection of <50 SARS-CoV-2 virions in swab samples in 17 h (for a batch of 12 swabs), compared to days typically required by the cell-culture-based method. The SARS-CoV-2 RV-RT-PCR method may also be useful in clinical sample analysis and antiviral drug testing, and could serve as a model for developing rapid methods for other viruses of concern.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Basin scale distributions of dissolved manganese, nickel, zinc and cadmium in the Mediterranean Sea

Samples for dissolved trace metal concentrations were collected during GEOTRACES expedition GA04-N in summer/spring in the Mediterranean Sea, starting in the Atlantic Ocean and sampling both deep basins of the Mediterranean Sea. Outflow of Mediterranean Outflow Water leads to elevated concentrations of Mn, Ni and Zn in the Atlantic Ocean, but a concentration minimum in the Atlantic distribution of Cd. Nevertheless, when comparing the in- and outflow, the Mediterranean is a net source of Cd to the Atlantic Ocean. Surface concentrations of Mn, Ni, Zn and Cd are elevated in the Mediterranean relative to the Atlantic Ocean where Ni and Cd gradually increased along the eastward surface water flow path, Zn reached a homogenous concentration in the order of 1 to 1.5 nM, and Mn displayed a patchy surface distribution. The observed differences are attributable to the different dynamics of their biogeochemical cycling, notably the partitioning between the dissolved and particulate phases due to biological uptake, scavenging and possibly organic complexation. The elevated surface concentrations of Mn, Ni, Zn and Cd in the Mediterranean are derived from atmospheric deposition, where most likely Zn and Cd are mainly sourced from anthropogenic origin, Mn mostly from lithogenic origin and Ni from both anthropogenic and lithogenic origin. Dissolved Zn and Cd, as well as phosphate and nitrate, display striking inter-basin fractionations with elevated concentrations in the deep water of the western basin compared to the deep eastern basin, without a coinciding increase in the apparent oxygen utilization. Given that physical circulation or contribution from biogenic particulate metals cannot explain the elevated dissolved concentrations, an external non-biological source is required. This source is most likely a vertical flux of metal laden particles dissolving through the water column of the western Mediterranean where these particles, most likely from anthropogenic origin, are derived from either atmospheric deposition or particulate material deposited on the continental shelves that makes its way into the deep basin. Furthermore, to confirm or detect trends in dissolved metal concentrations in the deep basin, regular basin wide assessments of the trace metal distributions in the Mediterranean are needed. The distributions of Mn, Ni, Zn and Cd in the Sea of Marmara illustrate that all of these metals can be affected by anthropogenic surface sources and highlight the different susceptibilities of the dissolved metal distributions to supply from remineralization, and to removal through scavenging. This study provides a first baseline to assess future changes and underlines that the Mediterranean marine environment is susceptible to anthropogenic disturbances, with varying effects for different metals due to differing source strengths and biogeochemical cycles.

58 GEOSCIENCES↗
DOE OSTI2026

RU-net for automatic characterization of TRISO fuel cross sections

During irradiation, phenomena such as kernel swelling and buffer densification may impact the performance of tristructural isotropic (TRISO) particle fuel. Post-irradiation microscopy is often used to identify these irradiation-induced morphologic changes. However, each fuel compact generally contains thousands of TRISO particles. Manually performing the work to get statistical information on these phenomena is cumbersome and subjective. Here, to reduce the subjectivity inherent in that process and to accelerate data analysis, we used convolutional neural networks (CNNs) to automatically segment cross-sectional images of microscopic TRISO layers. CNNs are a class of machine-learning algorithms specifically designed for processing structured grid data. They have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we generated a large irradiated TRISO layer dataset with more than 2,000 microscopic images of cross-sectional TRISO particles and the corresponding annotated images. Based on these annotated images, we used different CNNs to automatically segment different TRISO layers. These CNNs include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net performs best in terms of Intersection over Union (IoU). Using CNN models, we can expedite the analysis of TRISO particle cross sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Additive manufacturing and applications of nanomaterial-based sensors

Nanoscale materials possess distinct physical and chemical attributes including size-dependent properties, quantum confinement, high surface-to-volume ratio, and superior catalytic activity. These unique qualities enable sensors with high sensitivity, robustness, and fast time response. As the emergence of the Internet of Things (IoT) demands increased production of sensors, it also provides an impetus for concentrated nanomaterial-based sensor research. Meanwhile, additive manufacturing (AM) of nanomaterial-based sensors is critical to bridge the gap between one-off, lab-scale fabrication and cost-effective, industrial-scale production with high reproducibility. By applying the design flexibility and cost savings of AM techniques, a new generation of nanomaterial-based sensing platforms can be integrated with IoT devices in the consumer space. Furthermore, emergent research in human-machine interfaces, food safety, and point-of-care diagnostics will be expedited by the development of sensors that can be printed with irregular form factors. In this Review, the relative strengths and weaknesses of printed sensor systems based on zero-, one-, and two-dimensional nanomaterials are discussed. In addition, sensors enabled by printable soft nanomaterials, heterostructures, and nanocomposites are surveyed due to their synergistic advantages for wearable healthcare monitoring and soft robotics. Lastly, a roadmap for the next decade of research on this topic is provided.

36 MATERIALS SCIENCE↗
DOE OSTI2026

In situ studies on heavy ion irradiation and partial oxidation induced stacking faults and nanograins in tungsten nanolaminates

Understanding the microstructural evolution of tungsten (W) under extreme irradiation environments is critical for its application as a plasma-facing material in future fusion reactors. Heavy ion irradiation study offers expedited damage accumulation and thus allows irradiation tolerance property prediction in a short period of time. In this study we explore in situ Kr ion irradiation of W nanolaminates at 800 °C and uncover a complex interplay of irradiation-induced transformations, including the emergence of stacking faults, nanograin formation, and generation of thickened grain boundaries defined as GB regions with the thickness of up to 15 nm. High-resolution transmission electron microscopy studies reveal the formation of extended planar faults and a metastable hexagonal close-packed (hcp) phase within the body-centered cubic (bcc) matrix. These structural transitions are facilitated by irradiation-induced shear. They are further stabilized by the presence of oxygen, which promotes stacking fault formation and vacancy trapping. Elevated temperatures enhance defect mobility, enabling dynamic recrystallization into ultrafine grains and the thickening of GBs due to defect absorption and impurity segregation. These findings unravel non-equilibrium phase transformation pathways in heavy ion irradiated W and highlight the critical role of impurity-mediated defect dynamics in governing its radiation tolerance properties.

Wazeer, Adil [Purdue University]↗
DOE OSTI2024

Heteroatom anchoring to enhance electrochemical reversibility for high-voltage P2-type oxide cathodes of sodium-ion batteries

P2-type cathode has received extensive attention due to its faster Na+ diffusion and a high theoretical capacity in sodium-ion batteries (SIBs). However, undesirable phase transformations have induced dramatic capacity decay of SIBs during the cycling process. In this study, heteroatom anchoring through Cu/Mg dual doping is introduced into P2-type Na 0.67 Ni 0.33 Mn 0.67 O 2 cathode to enhance high-voltage electrochemical reversibility and modulate interfacial Na + kinetics. Further, the as-prepared Na 0.67 Ni 0.23 Mg 0.05 Cu 0.05 Mn 0.67 O 2 exhibits an outstanding capacity retention (83.4% after 2000 cycles at 10C) and rate performance (73 mAh g -1 at 10C, accounting for 58.7% of that at 0.1 C) over the voltage range of 2.5–4.4 V. Intensive explorations further manifest that the modified mechanism of dual-ion doping strategy is attributed to the synergistic coupling effect of a substantial change in Na occupancy distribution and an increase in oxygen vacancy buffer. Thus, the optimized cathode expedites Na + diffusion and reduces detrimental phase transformation, which favors high-rate performance and long-term cycling stability. This study develops a route to rationally design high-voltage cathode materials for SIBs.

25 ENERGY STORAGE↗
DOE OSTI2026

Alchemy: A Model-Based Approach for 2D to 3D Autonomous Nuclear System Design

Engineering design of nuclear power plant (NPP) piping and equipment systems frequently bypasses crucial 2D system planning, instead moving straight to 3D modeling. This often leads to designs that exceed building envelope constraints, forcing expensive and time-consuming redesigns. When 2D modeling is employed, it typically involves labor-intensive manual workflows that convert 2D drawings into 3D models, resulting in inefficiencies and errors across design iterations. These workflows further suffer from poor software interoperability and dependence on proprietary software ecosystems, thereby contributing to schedule delays and cost overruns. This paper presents Alchemy, an autonomous framework that transforms 2D system definitions into Industry Foundation Classes (IFC)-compliant 3D building information models (BIMs) for expediting nuclear facility design at the conceptual preliminary phase. Using a model-based approach, the framework treats the 2D system diagram as the central reference model employed to automatically generate all subsequent outputs, ensuring consistency between the system definition and the resulting physical design. A web-based interface enables engineers to define hierarchical system topologies including associated equipment, geometric properties, and connectivity requirements. A two-phase equipment layout optimization algorithm automatically computes collision-free spatial configurations within predefined building envelopes. An artificial intelligence (AI)-assisted pipe routing module then generates orthogonal, collision-free routing paths, allowing the user to select either an A* search-based method or an Ant Colony Optimization (ACO)-based method. All outputs are authored natively in IFC format, relying on open-source technologies and standardized formats in order to ensure extensibility and eliminate proprietary software dependencies. The proposed framework is validated on two representative pressurized-water reactor (PWR)-based case studies, for which it autonomously generates IFC-compliant 3D models in minutes, drastically reducing workflows that typically require hours of manual effort. The generated model demonstrates topologically correct equipment placement, physically plausible spatial relationships, and collision-free pipe routing consistent with known PWR loop configurations. This work represents a foundational step toward digital engineering for nuclear facility preliminary design, with future ongoing development targeting design code compliance and expanded system complexity.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Subscale maturation of advanced reactor technologies (SMART): A path forward for nuclear thermal propulsion fuel and reactor development

Nuclear Thermal Propulsion (NTP) systems are actively being developed for future crewed missions to Mars. NTP systems excel in missions where both high thrust and high specific impulse are required, but modern NTP systems currently do not have a Technology Readiness Level (TRL) high enough for use in crewed space exploration. TRLs are used to demonstrate the level of rigor with which a component/system has been tested/demonstrated for its intended use. While space systems technology in general must be qualified as a unit, nuclear technology must be first demonstrated to meet qualification level requirements both at the fuel (component) level and the reactor (subsystem) level. Here, in this paper, historic NTP development programs are surveyed to identify a testing and development strategy that can be effectively implemented to allow for NTP reactor development. Based on this strategy, required facilities to enable such activities are identified. Current domestic experimental capabilities to support NTP qualification are limited to separate effects testing of individual components. Separate effects testing is found extensively in historic NTP development efforts but is not sufficient for full fuel and reactor qualification. Combined effects testing allows for an accurate assessment of fuel performance but is not achievable for NTP conditions in existing facilities. Assessment of historic development programs suggests that an intermediate, subscale test facility is necessary to advance NTP TRLs. A solution to meet this need is proposed, namely the Subscale Maturation of Advanced Reactor Technologies (SMART) facility. SMART will mitigate risk to NTP development by enabling performance and reactor physics demonstrations of NTP subsystems. A SMART facility could be built by modifying existing nuclear test facilities, which may potentially enable schedule and cost savings. To pursue reactor qualification beyond the subscale, a new ground test facility will be necessary. This ground test facility should be developed concurrently with SMART to allow for the facility to be operational in time for expedited NTP engine demonstration.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Customized open source renewable energy models validated through PHIL lab experiments

Energy models for power systems require ongoing updates to reflect advancements in equipment technology and the increasing complexity of power electronic devices. This study utilizes a Power Hardware-in-the-Loop (PHIL) experimental setup to validate custom photovoltaic (PV) inverter models, aiming to enhance and expedite the development of advanced renewable energy models. The research compares the performance of a physical inverter with generic Renewable Energy Source (RES) models recommended by the Western Electricity Coordinating Council (WECC). As inverter-based renewable energy sources become more prevalent in modern electrical grids, it is crucial that dynamic models accurately represent their real-world behavior. Accurate models improve our understanding of these energy resources and their interactions with the grid. The proposed model enhancements are designed to better reflect real inverter performance, based on insights from PHIL experiments. These models are developed using the open source Modelica language and the OpenIPSL Modelica Library, allowing integration across various simulation tools without re-implementation. The paper concludes with a thorough assessment, comparing the enhanced models with PHIL experiments on a real PV inverter in a controlled laboratory setting. As a result, the study provides the enhanced WECC RES models and validation data as open source resources, facilitating further research and development.

Modelica↗