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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Structure and Flow-Viscosity of Filled-Polymer-Based 3D Printing Ink: Exploration through Coarse-Grained Molecular Dynamics

The addition of nanofiller particles to a polymer matrix has long been known to enhance or modify the composite’s mechanical and rheological properties. However, quantitatively capturing such changes with molecular level simulations remains computationally challenging. Toward that goal, we performed coarse-grained molecular dynamics of a nanocomposite system at a fixed (25 vol %) filler loading under nonspecific, weak polymer–filler interactions representative of a broad class of technologically important materials. We report several interesting results, including: (1) the equilibrium chain-configuration remains Gaussian-like as in an unfilled melt; (2) smaller filler particles display a stronger tendency to cluster; (3) larger fillers act as plasticizers by reducing the entanglement density and accelerating the chain mobility; and (4) fillers enhance the tensile response modulus, with the effect being stronger for larger particles. We also simulate cluster breakup, yielding, and elongational flow under an applied time-linear tensile strain and study the flow viscosity as a function of filler-size and chain-length.

Materials science↗
DOE OSTI2025

Harnessing ionic complexity: A modeling approach for hierarchical ionic circuit design

Since the 1950s, soft ionic devices have evolved from individual components to an expanding library of sensors, actuators, signal transmitters, and processors. However, integrating these components into complex, multifunctional systems remains challenging due to the nonintuitive and nonlinear interactions between ionic elements. In this work, we address these fundamental challenges by developing a lumped element model that enables interrogation of the physics that governs ionic circuits, as well as rapid design and optimization. Our model captures features specific to ionic charge carriers, while preserving the hierarchical design flexibility and computational efficiency of traditional circuit modeling. We demonstrate that our model can not only fit individual device behavior but also accurately predict the behavior of larger circuits formed by combining those devices. Additionally, we show how our tool utilizes the intrinsic nonlinearities of ionic systems to enable extended functionality, revealing how factors such as ion enrichment, ion leakage, and polymer charge density influence performance. Lastly, we present a fully ionic power supply, sensor, control system, and actuator for a soft robot that adapts its motion in response to environmental salt, illustrating the tool’s potential to accelerate advancements in chemical sensing, biointerfacing, biomimetic systems, and adaptive materials.

42 ENGINEERING↗
DOE OSTI2024

Concurrent Measurement of O 2 Production and Isoprene Emission During Photosynthesis: Pros, Cons and Metabolic Implications of Responses to Light, CO 2 and Temperature

Traditional leaf gas exchange experiments have focused on net CO 2 exchange (A net ). Here, using California poplar (Populus trichocarpa), we coupled measurements of net oxygen production (NOP), isoprene emissions and δ 18 O in O 2 to traditional CO 2 /H 2 O gas exchange with chlorophyll fluorescence, and measured light, CO 2 and temperature response curves. This allowed us to obtain a comprehensive picture of the photosynthetic redox budget including electron transport rate (ETR) and estimates of the mean assimilatory quotient (AQ = A net /NOP). We found that A net and NOP were linearly correlated across environmental gradients with similar observed AQ values during light (1.25 ± 0.05) and CO 2 responses (1.23 ± 0.07). In contrast, AQ was suppressed during leaf temperature responses in the light (0.87 ± 0.28), potentially due to the acceleration of alternative ETR sinks like lipid synthesis. A net and NOP had an optimum temperature (Topt) of 31°C, while ETR and δ 18 O in O2 (35°C) and isoprene emissions (39°C) had distinctly higher T opt . The results confirm a tight connection between water oxidation and ETR and support a view of light-dependent lipid synthesis primarily driven by photosynthetic ATP/NADPH not consumed by the Calvin–Benson cycle, as an important thermotolerance mechanism linked with high rates of (photo)respiration and CO 2 /O 2 recycling.

H218O labelling↗
DOE OSTI2024

Unveiling the effect of composition on nuclear waste immobilization glasses’ durability by nonparametric machine learning

Abstract Ensuring the long-term chemical durability of glasses is critical for nuclear waste immobilization operations. Durable glasses usually undergo qualification for disposal based on their response to standardized tests such as the product consistency test or the vapor hydration test (VHT). The VHT uses elevated temperature and water vapor to accelerate glass alteration and the formation of secondary phases. Understanding the relationship between glass composition and VHT response is of fundamental and practical interest. However, this relationship is complex, non-linear, and sometimes fairly variable, posing challenges in identifying the distinct effect of individual oxides on VHT response. Here, we leverage a dataset comprising 654 Hanford low-activity waste (LAW) glasses across a wide compositional envelope and employ various machine learning techniques to explore this relationship. We find that Gaussian process regression (GPR), a nonparametric regression method, yields the highest predictive accuracy. By utilizing the trained model, we discern the influence of each oxide on the glasses’ VHT response. Moreover, we discuss the trade-off between underfitting and overfitting for extrapolating the material performance in the context of sparse and heterogeneous datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Platform for Automated Anomaly Detection in the Mercury Process System at the Target System in the Spallation Neutron Source

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory accelerates proton beams, which are directed toward a mercury target to generate the world’s most intense neutron beams via spallation. The target system consists of several interconnected subsystems and accounts for a major share of the facility’s overall downtime. Early detection of anomalies in the target system response can thus provide the possibility of taking corrective actions to reduce downtime. Accelerator facilities have largely focused on the beam side for data-driven fault prognostics. On the target side, SNS relies on operational shift technicians (OSTs), who respond to alarms and manually flag anomalies onto the System Tracking and Reliability (STAR) platform. This paper presents one of the first studies of using machine learning (ML) to automate anomaly detection in the target system. The study focused on the mercury process system as the first use case and employed reconstruction-based anomaly detection on minutely sampled time series signals. The pipeline was integrated into the STAR platform to autonomously rank and flag anomalies every week. The STAR platform provides a user interface for the OSTs to evaluate the flagged anomalies, thereby incorporating human feedback.

Anomaly detection↗
DOE OSTI2022

Differentiable Preisach Modeling for Characterization and Optimization of Particle Accelerator Systems with Hysteresis

Future improvements in particle accelerator performance are predicated on increasingly accurate online modeling of accelerators. Hysteresis effects in magnetic, mechanical, and material components of accelerators are often neglected in online accelerator models used to inform control algorithms, even though reproducibility errors from systems exhibiting hysteresis are not negligible in high precision accelerators. Here, we combine the classical Preisach model of hysteresis with machine learning techniques to efficiently create nonparametric, high-fidelity models of arbitrary systems exhibiting hysteresis. We experimentally demonstrate how these methods can be used in situ, where a hysteresis model of an accelerator magnet is combined with a Bayesian statistical model of the beam response, allowing characterization of magnetic hysteresis solely from beam-based measurements. Finally, we explore how using these joint hysteresis-Bayesian statistical models allows us to overcome optimization performance limitations that arise when hysteresis effects are ignored.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

FOXO3 targets are reprogrammed as Huntington's disease neural cells and striatal neurons face senescence with p16 INK4a increase

Neurodegenerative diseases (ND) have been linked to the critical process in aging-cellular senescence. However, the temporal dynamics of cellular senescence in ND conditions is unresolved. Here, we show senescence features develop in human Huntington's disease (HD) neural stem cells (NSCs) and medium spiny neurons (MSNs), including the increase of p16 INK4a , a key inducer of cellular senescence. We found that HD NSCs reprogram the transcriptional targets of FOXO3, a major cell survival factor able to repress cell senescence, antagonizing p16 INK4a expression via the FOXO3 repression of the transcriptional modulator ETS2. Additionally, p16 INK4a promotes cellular senescence features in human HD NSCs and MSNs. These findings suggest that cellular senescence may develop during neuronal differentiation in HD and that the FOXO3-ETS2-p16 INK4a axis may be part of molecular responses aimed at mitigating this phenomenon. Our studies identify neuronal differentiation with accelerated aging of neural progenitors and neurons as an alteration that could be linked to NDs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Is Mini Beam Ready for Human Trials? Results of Randomized Study of Treating De-Novo Brain Tumors in Canines Using Linear Accelerator Generated Mini Beams

The main challenge in treating malignant brain neoplasms lies in eradicating the tumor while minimizing treatmentrelated damage. Conventional radiation treatments are associated with considerable side effects. Synchrotron generated micro-beam radiation (SMBRT) has shown to preserve brain architecture while killing tumor cells, however physical characteristics and limited facility access restrict its use. We have created a new clinical device which produces mini beams on a linear accelerator, to provide a new type of treatment called mini-beam radiation therapy (MBRT). The objective of this study is to compare the treatment outcomes of linear accelerator based MBRT versus standard radiation treatment (SRT), to evaluate the tumor response and the treatment-related changes in the normal brain with respect to each treatment type. Pet dogs with de-novo brain tumors were accrued for treatment. Dogs were randomized between standard fractionated stereotactic (9 Gy in 3 fractions) radiation treatment vs. a single fraction of MBRT (26 Gy mean dose). Dogs were monitored after treatment for clinical assessment and imaging. When the dogs were euthanized, a veterinary pathologist assessed the radiation changes and tumor response. We accrued 16 dogs, 8 dogs in each treatment arm. In the MBRT arm, 71% dogs achieved complete pathological remission. The radiation-related changes were all confined to the target region. Structural damage was not observed in the beam path outside of the target region. In contrast, none of the dogs in control group achieved remission and the treatment related damage was more extensive. Therapeutic superiority was observed with MBRT, including both tumor control and the normal structural preservation. The MBRT findings are suggestive of an immune related mechanism which is absent in standard treatment. These findings together with the widespread availability of clinical linear accelerators make MBRT a promising research topic to explore further treatment and clinical trial opportunities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Plasma flow generation and particle acceleration from expanding magnetic bubbles

Impulsive plasma dynamics in the laboratory are often driven by rising electric currents, yet their quantitative plasma response has not been well established. By means of fully kinetic particle-in-cell simulations and laser-driven capacitor-coil experiments, we show that a rising current expels plasma, forming an expanding magnetic bubble and accelerating particles. The expansion front velocity scales with the Alfvén speed determined by the magnetic field at its inner edge and the plasma density at its outer edge. This mechanism establishes impulsive current drive as a fundamental way that generates plasma flows and accelerates particles in laboratory plasmas, with potential relevance to astrophysics.

Zhang, Yang [Princeton University, NJ (United Stat↗
DOE OSTI2022

Characterization and description of a spectrum unfolding method for the $\mathrm{CATRiNA}$ neutron detector array

We report the CATRiNA deuterated neutron detector array at Florida State University consists of 16 2" x 2" and 16 $" x 2" EJ-315 detectors with characteristic light output and pulse-shape discrimination capabilities. The unique properties of the detectors, in part due to the anisotropic nature of (d,n) scattering, are used to extract the energy of neutrons via pulse-height spectrum unfolding. The unfolding method uses the light output and response matrix of the detectors to extract neutron energies, independent of the traditional time-of-flight (ToF) technique. Detailed response matrices of the CATRiNA detectors were measured at the Edwards Accelerator Laboratory at Ohio University via the 9 Be(d,n) and 27 Al(d,n) reactions. Full characterization of the detectors using digital electronics, as well as a description of the unfolding method are reported.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Operational optimization for multi-functional charging station with electric and hydrogen-powered vehicles

The rapid adoption of electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs), combined with global efforts to reduce carbon emissions, has accelerated the development of EV charging and hydrogen refueling stations. In response to this demand, this paper introduces the concept of Multi-Functional Charging Station (MFCS) that integrates power generation, EV charging, battery swapping, and hydrogen refueling. A comprehensive operational model is developed for the MFCS that couples electricity and hydrogen conversion and storage technologies to enhance infrastructure utilization and improve overall system efficiency. The model also considers multiple revenue streams, including participation in energy and ancillary markets. To validate the effectiveness of the proposed model and evaluate its performance, a series of numerical experiments are conducted with different charger numbers, different electricity purchase limits, and different charger allocations. Numerical results demonstrate that shared charger configurations can lead to 8.11 % improvement in operational profit by improving resource utilization and reducing the number of depleted batteries at the end of operations compared to allocated charger setups. By varying the number of chargers, sensitivity analysis identifies diminishing marginal returns beyond about 45 chargers, suggesting it as an optimal sizing point under current settings. The integration of electricity and hydrogen conversion is also explored under scenarios with limited external electricity purchases. In conclusion, these findings indicate that optimizing charger allocation and energy management can significantly enhance station productivity and profitability, ultimately supporting the broader adoption of electrified and hydrogen-based transportation solutions.

Charging station↗
DOE OSTI2020

Quantum Computing for Neutrino-Nucleus Scattering

Neutrino-nucleus cross section uncertainties are expected to be a dominant systematic in future accelerator neutrino experiments. The cross sections are determined by the linear response of the nucleus to the weak interactions of the neutrino, and are dominated by energy and distance scales of the order of the separation between nucleons in the nucleus. These response functions are potentially an important early physics application of quantum computers. Here we present an analysis of the resources required and their expected scaling for scattering cross section calculations. The current estimates of Trotter steps needed to achieve an energy resolution of 10 MeV and the number of CNOT gates for analyzing Ar40 highlights the need for significant improvements in algorithms. We also examine simple small-scale neutrino-nucleus models on modern quantum hardware. In this paper, we use variational methods to obtain the ground state of a three nucleon system (the triton) and then implement the relevant time evolution. To tame the errors in present-day NISQ devices, we explore the use of different error-mitigation techniques to increase the fidelity of the calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Sensor Enabled Coatings for Methane Release Mitigation

Methane as a greenhouse gas is as much as 30 times more efficient than carbon dioxide. Given the increasing reliance on natural gas, methane release mitigation has become an increasingly important issue to address. In this investigation, PPG, RTI, and GTI focused on the exploration of resonant frequency identification (RFID) sensors embedded in natural gas pipeline coatings and their ability to detect coating damage at an early stage. Various coating formulations and their respective physical properties were examined to determine their effect on sensor performance in various accelerated aging environments. Overall, it was found that the RFID sensor responses could not be correlated to the coating properties and formulation variables examined in this investigation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Genomic approaches to accelerate American chestnut restoration

More than a century after two introduced pathogens killed billions of American chestnut trees, introgression of resistance alleles from Chinese chestnuts has contributed to the recovery of self-sustaining populations. However, progress has been slow because of the complex genetic architecture of resistance. To better understand blight resistance, we compared reference genomes, gene expression responses, and stem metabolite profiles of the resistant Chinese and susceptible American chestnut species. To accelerate resistance breeding, we conducted large-scale phenotyping and genotyping in hybrids of these species. Simulation and inoculation experiments suggest that significant resistance gains are possible through selectively breeding trees with an average of 70 to 85% American chestnut ancestry. In conclusion, the resources developed in this work are foundational for breeding to create diverse restoration populations with sufficient disease resistance and competitive growth.

Westbrook, Jared W. [The American Chestnut Foundat↗
DOE OSTI2025

Investigation of new superconducting materials for the next generation high-performance RF superconducting cavities for particle accelerators

In this DOE-funded project DE-SC0010081-020 Old Dominion University (ODU) in collaboration with University of Wisconsin (UW) and Jefferson Laboratory have investigated both experimentally and theoretically electromagnetic response and losses in multilayered superconducting structures made of new SRF materials which can push the field and Q performance limits of accelerating cavities.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Dataset for Cruz-O'Byrne et al (2026): "Divergent biogeochemical responses in upland coastal forest soils to repeated flooding and shifts in water chemistry"

Hydrologic disturbances from accelerated sea-level rise and the increasing frequency and intensity of storms and tidal flooding are altering biogeochemical processes in upland coastal forests, transforming these ecosystems into wetlands. However, the initial effects of flooding on belowground biogeochemistry and the mechanisms driving greenhouse gas dynamics and soil organic matter stability during the early stages of this transition remain poorly understood. This dataset presents the results of a mesocosm experiment conducted in a controlled, highly instrumented laboratory environment, in which freshwater and brackish water pulses were applied to intact soil monoliths from a temperate upland coastal forest to examine how floodwater chemistry influences soil biogeochemistry and organo-mineral interactions. All data files are plain-text CSV (comma-separated value), and no special software is required to read them. Details about the content of each file are available in the document “Dataset_readme”. The dataset consists of the following data: • rcruzobyrne_moisture: Soil volumetric water content (VWC) • rcruzobyrne_GHG: Headspace greenhouse gas (GHG) concentration and fluxes • rcruzobyrne_methane_isotopes: Headspace methane isotope signature • rcruzobyrne_porewater: Porewater chemistry • rcruzobyrne_CDOM: Porewater colored dissolved organic matter (CDOM) • rcruzobyrne_FTIR: Soil Fourier-transform infrared (FTIR) spectroscopy Details of the experimental setup, data collection, and data analysis are provided in the manuscript by Cruz-O’Byrne et al (2026) Divergent biogeochemical responses in upland coastal forest soils to repeated flooding and shifts in water chemistry. Biogeochemistry. https://doi.org/10.1007/s10533-026-01340-0

EARTH SCIENCE > ATMOSPHERE > GREENHOUSE GAS↗
DOE OSTI2023

Cost‐Responsive Optimization of Nickel Nanoparticle Synthesis

Abstract Early‐stage cost evaluation during catalyst development holds the potential to accelerate the commercialization and deployment of advanced catalytic materials for sustainable chemical processes. The modeling and assessment of manufacturing costs as early as the laboratory synthesis scale, for example, focusing on materials costs and synthesis performance metrics, can support the development of an experimental–economic feedback loop that enables rapid insight into cost drivers associated with catalyst synthesis and highlights areas that require focused research and development effort. Ultimately, this feedback loop supports the realization of an economic understanding of the overall synthetic process and highlights opportunities to reduce costs, serving as the foundation for the scale‐up of catalyst manufacturing. Herein, a case study is presented utilizing CatCost, a free and publicly available estimation tool for the evaluation of catalyst manufacturing costs, to perform a cost‐responsive optimization of the synthesis of nickel nanoparticles (Ni NPs). It is demonstrated that reagent substitutions with more cost‐effective analogs, coupled with stoichiometric optimization, afford a 58% reduction in raw materials cost without changing the product yield or properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A Spatially Resolved Evaluation of Accelerated Environmental Aging on Emerging Polypropylene-Based Photovoltaic Backsheets Using Raman Spectroscopy

For this work, accelerated aging was used to assess environmental degradation in emerging co-extruded polypropylene (PP)-based backsheets under three different environmental conditions (65°C/20% relative humidity (RH), 75°C/20% RH, and 75°C/50% RH). Although differential scanning calorimetry did not measure crystallinity changes with exposure, spatially resolved Raman spectroscopy identified crystallinity increases in the core layer of aged samples, indicating a heterogeneous postcrystallization process. The Raman results were in agreement with synchrotron-based microfocused wide-angle X-ray scattering measurements. Cross-sectional nanoindentation was used to correlate localized crystallinity shifts with changes in Young's modulus. A similar trend was found where increased modulus was measured in the core layer, supporting the relationship between modulus and crystallinity. Finally, dielectric characterization was used to assess the impact of these material property changes on performance. While changes in the backsheet material properties and dielectric performance were observed with accelerated aging, these shifts generally equilibrated with time, indicating overall stability in response to environmental stressors. Additionally, the identified heterogeneous material property changes indicate that spatially resolved crystallinity measurements may be a valuable early failure indicator to be used in the assessment of PV backsheet long-term durability.

36 MATERIALS SCIENCE↗