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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Using Flory–Huggins-informed human-in-the-loop Bayesian optimization to map the phase diagram of polymer blends

Mapping the phase diagram of polymer blends is an essential step in controlling the structure–property relationship of polymer-based materials. However, traditional grid-based approaches are inefficient and rely on subjective judgements for terminating the experimental campaign. Artificial intelligence-guided experimentation offers a compelling alternative, especially when data-driven decision-making is interfaced with established polymer thermodynamics to improve efficiency and interpretability. Here, we introduce a physics-informed Bayesian optimization approach to guide the mapping of the phase diagram of a model blend containing poly(methyl methacrylate) and poly(styrene-ran-acrylonitrile). Physical information is derived from a Flory–Huggins representation of the spinodal curve, which is integrated into the Bayesian optimization process as a structured prior mean that acts as a soft constraint. Implemented as a human-in-the-loop workflow, the approach leverages optical imaging of film cloudiness with iterative Gaussian process surrogate modeling and a parameter selection decision policy to identify the composition-temperature conditions for sequential iterations. Convergence of kernel and Flory–Huggins-based hyperparameters provided a stopping criterion, ensuring an objective and interpretable termination of the experimental campaign. The framework recovered the known lower critical solution temperature (∼160 °C), while increasing material efficiency through targeted sampling. This work establishes a proof-of-concept for the application of Bayesian optimization workflows to study polymer blend miscibility.

36 MATERIALS SCIENCE↗
DOE OSTI2021

RF surface resistance tuning of superconducting niobium via thermal diffusion of native oxide

Recently, Nb superconducting radio frequency cavities vacuum heat treated between 300 and 400°C for a few hours have exhibited very high quality factors (~5 × 10 10 at 2.0 K). Secondary ion mass spectrometry measurements of O, N, and C show that this enhancement in RF surface conductivity is primarily associated with interstitial O alloying via dissolution and diffusion of the native oxide. We use a theory of oxide decomposition and O diffusion to quantify previously unknown parameters crucial in modeling this process. RF measurements of a vacuum heat-treated Nb superconducting radio frequency cavity confirm the minimized surface resistance (higher Q 0 ) previously expected only from 800 °C diffusive alloying with N.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Grad–Shafranov equilibria via data-free physics informed neural networks

A large number of magnetohydrodynamic (MHD) equilibrium calculations are often required for uncertainty quantification, optimization, and real-time diagnostic information, making MHD equilibrium codes vital to the field of plasma physics. In this paper, we explore a method for solving the Grad–Shafranov equation by using physics-informed neural networks (PINNs). For PINNs, we optimize neural networks by directly minimizing the residual of the partial differential equation as a loss function. We show that PINNs can accurately and effectively solve the Grad–Shafranov equation with several different boundary conditions, making it more flexible than traditional solvers. This method is flexible as it does not require any mesh and basis choice, thereby streamlining the computational process. We also explore the parameter space by varying the size of the model, the learning rate, and boundary conditions to map various tradeoffs such as between reconstruction error and computational speed. Additionally, we introduce a parameterized PINN framework, expanding the input space to include variables such as pressure, aspect ratio, elongation, and triangularity in order to handle a broader range of plasma scenarios within a single network. Parameterized PINNs could be used in future work to solve inverse problems such as shape optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

DeepMC: a deep learning method for efficient Monte Carlo beamlet dose calculation by predictive denoising in magnetic resonance-guided radiotherapy

Abstract Emerging magnetic resonance (MR) guided radiotherapy affords significantly improved anatomy visualization and, subsequently, more effective personalized treatment. The new therapy paradigm imposes significant demands on radiation dose calculation quality and speed, creating an unmet need for the acceleration of Monte Carlo (MC) dose calculation. Existing deep learning approaches to denoise the final plan MC dose fail to achieve the accuracy and speed requirements of large-scale beamlet dose calculation in the presence of a strong magnetic field for online adaptive radiotherapy planning. Our deep learning dose calculation method, DeepMC, addresses these needs by predicting low-noise dose from extremely noisy (but fast) MC-simulated dose and anatomical inputs, thus enabling significant acceleration. DeepMC simultaneously reduces MC sampling noise and predicts corrupted dose buildup at tissue-air material interfaces resulting from MR-field induced electron return effects. Here we demonstrate our model’s ability to accelerate dose calculation for daily treatment planning by a factor of 38 over traditional low-noise MC simulation with clinically meaningful accuracy in deliverable dose and treatment delivery parameters. As a post-processing approach, DeepMC provides compounded acceleration of large-scale dose calculation when used alongside established MC acceleration techniques in variance reduction and graphics processing unit-based MC simulation.

Engineering↗
DOE OSTI2022

Exploring extreme magnetization phenomena in directly driven imploding cylindrical targets

Abstract This paper uses extended-magnetohydrodynamics (MHD) simulations to explore an extreme magnetized plasma regime realizable by cylindrical implosions on the OMEGA laser facility. This regime is characterized by highly compressed magnetic fields (greater than 10 kT across the fuel), which contain a significant proportion of the implosion energy and induce large electrical currents in the plasma. Parameters governing the different magnetization processes such as Ohmic dissipation and suppression of instabilities by magnetic tension are presented, allowing for optimization of experiments to study specific phenomena. For instance, a dopant added to the target gas-fill can enhance magnetic flux compression while enabling spectroscopic diagnosis of the imploding core. In particular, the use of Ar K-shell spectroscopy is investigated by performing detailed non-LTE atomic kinetics and radiative transfer calculations on the MHD data. Direct measurement of the core electron density and temperature would be possible, allowing for both the impact of magnetization on the final temperature and thermal pressure to be obtained. By assuming the magnetic field is frozen into the plasma motion, which is shown to be a good approximation for highly magnetized implosions, spectroscopic diagnosis could be used to estimate which magnetization processes are ruling the implosion dynamics; for example, a relation is given for inferring whether thermally driven or current-driven transport is dominating.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A quantitative comparison between velocity dependent SIDM cross-sections constrained by the gravothermal and isothermal models

One necessary step for probing the nature of self-interacting dark matter (SIDM) particles with astrophysical observations is to pin down any possible velocity dependence in the SIDM cross-section. Major challenges for achieving this goal include eliminating, or mitigating, the impact of the baryonic components and tidal effects within the dark matter halos of interest – the effects of these processes can be highly degenerate with those of dark matter self-interactions at small scales. In this work, we select 9 isolated galaxies and brightest cluster galaxies (BCGs) with baryonic components small enough such that the baryonic gravitational potentials do not significantly influence the halo gravothermal evolution processes. We then constrain the parameters of Rutherford and Møller scattering cross-section models with the measured rotation curves and stellar kinematics through the gravothermal fluid formalism and isothermal method. Cross-sections constrained by the two methods are consistent at $1\sigma$ confidence level, but the isothermal method prefers cross-sections greater than the gravothermal approach constraints by a factor of ~ 3.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Exploring the partonic collectivity in small systems at energies available at the CERN Large Hadron Collider

Using the Hydro-Coal-Frag model that combines hydrodynamics at low p T , quark coalescence at intermediate p T , and the LBT transport model at high p T , we study the spectra and elliptic flow of identified hadrons in high multiplicity p–Pb and p–p collisions at the CERN Large Hadron Collider (LHC). In p–Pb collisions, the Hydro-Coal-Frag model gives a good description of the differential elliptic flow over the p T range from 0 to 6 GeV and the approximate number of constituent quark (NCQ) scaling at intermediate p T . Although the Hydro-Coal-Frag model can also roughly describe the elliptic flow in high multiplicity p–p collisions with the quark coalescence process, the larger contribution from the string fragmentations leads to a notable violation of the NCQ scaling of v 2 at intermediate p T as observed in the experiment. Comparison runs of the Hydro-Frag model without the coalescence process demonstrate that regardless the parameter adjustments, the Hydro-Frag model cannot simultaneously describe the p T spectra and the elliptic flow of identified hadrons in either p–Pb collisions or p–p collisions. In conclusion, the calculations in this paper thus provide support for the existence of partonic degrees of freedom and the possible formation of the QGP in the small systems created at the LHC.

Wang, Yuanyuan [Peking University, Beijing (China)↗
DOE OSTI2021

A Novel Machine Learning Algorithm for Planetary Boundary Layer Height Estimation Using AERI Measurement Data

Accurately determining the height of the planetary boundary layer (PBL) is important since it can affect the climate, weather, and air quality. Ground-based infrared hyperspectral remote sensing is an effective way to obtain this parameter. Compared with radiosonde measurements, its temporal resolution is much higher. In this study, a method to retrieve the PBL height (PBLH) from the ground-based infrared hyperspectral radiance data is proposed based on machine learning. In this method, the channels that are sensitive to temperature and humidity profiles are selected as the feature vectors, and the PBLHs derived from radiosonde are taken as the true values. The support vector machine (SVM) is applied to train and test the data set, and the parameters are optimized in the process. The data set collected at the Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) from 2012 to 2015 is analyzed. The instruments used in this letter include Atmospheric Emitted Radiance Interferometer (AERI), Vaisala CL31 ceilometer, and radiosonde. It shows that the root mean square error (RMSE) between the PBLHs calculated by the proposed method using AERI data and those from radiosonde data can be within 370 m, and the square correlation coefficient (SCC) is greater than 0.7. Compared with the PBLHs derived from the ceilometer, it can be found that the new method is more stable and less affected by clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Testing of a Line Driver With Configurable Pre-Emphasis on Lossy Transmission Lines

Rare-event physics experiments such as the Deep Underground Neutrino Experiment (DUNE) or the next Enriched Xenon Observatory (nEXO) experiment search for rare, low-energy events, detected by sensitive detectors immersed in a cryogenic noble liquid (e.g., liquid argon or xenon). Readout electronics used within such detectors must consume minimal power while operating reliably in cryogenic environments. Furthermore, in the case of nEXO, maximizing the radiopurity of the environment is vital to minimize background noise, thus placing strict limits on the volume of dielectric materials, leading to high-loss data cables spanning distances up to 12 m. Such cables cause high attenuation and intersymbol interference (ISI), resulting in a high bit-error rate (BER). These issues were addressed by developing an integrated line driver with configurable pre-emphasis in a 65-nm CMOS process. The pre-emphasis parameters can be programmed to minimize BER for specific cables and data rates under power constraints. Here, the driver was tested at both room and cryogenic temperatures. In both cases, the output BER was found to be strongly correlated with the pre-emphasis settings. Furthermore, analysis and simulation showed that adapting the pre-emphasis settings based on the incoming bit sequence can further improve performance with minimal changes to the current solution.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Leveraging Additive Manufacturing to Fabricate High Temperature Alloys With Co-Designed Mechanical Properties and Environmental Resistance

A paradigm shift in the traditional sequential design approaches is critically essential to create application-specific hierarchical and multifunctional materials with superior long-term performance for next-generation energy technologies involving extreme environments. In the current work, we aim to leverage the flexibility and geometric/compositional complexity offered by additive manufacturing to demonstrate this new approach by codesigning a compositionally graded Ni-based alloy for molten salts\sCO 2 heat exchangers to enable mitigation of environmental degradation of surfaces exposed to molten halide salts, while simultaneously suppressing the consequent deterioration in mechanical stability. Further, thermokinetic modeling describing the underlying physics of thermally- and environmentally induced spatiotemporal compositional and microstructural evolution will be employed to predict the parameter space of material deposition processes and precisely identify the required composition gradient. Preliminary corrosion and mechanical testing of the dual material demonstrated the potential of the material to replace existing solid solution strengthened materials for this application.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Yeast Transformation on Hamilton Vantage (YT Vantage) v1

Our software program is designed for the Hamilton Vantage liquid handling robot, automating the Build step in the Design-Build-Test-Learn (DBTL) cycle for Saccharomyces cerevisiae. This program minimizes human intervention, enabling rapid identification of pathway bottlenecks and genes that enhance verazine production. The program takes competent yeast and plasmid DNA as input and generates an output library of engineered strains compatible with automated colony picking, high-throughput culturing, and chemical extraction for downstream LC-MS analysis. A user-friendly interface, developed using the Hamilton Method Editor software, allows for on-demand parameter customization. By automating this process, our program streamlines the construction of Saccharomyces cerevisiae, reducing manual labor and increasing efficiency. While the manual process is well-documented, integration with robotic automation is less common, making our program a valuable tool for researchers. With this software, we achieved 2-5 fold increases in verazine production, demonstrating its potential to accelerate research in this field.

Louie, Randy [Lawrence Berkeley National Laborator↗
DOE OSTI2024

Insights into Designing an Efficient and Reliable Microwave-Assisted Methane Dehydroaromatization Process: Effect of Microwave Absorber on Catalyst Performance

Microwave-assisted methane dehydroaromatization has the potential to address challenges of traditional dehydroaromatization reactions. However, catalysts for microwave-enhanced reaction systems require effective coupling of fields with the catalyst to produce heat and reach reaction temperatures. Here, this work presents an in-depth understanding of the effect of the addition of silicon carbide as a microwave absorber on catalyst performance among other variables, the viability of the microwave reactor configuration, and insights into designing an effective and reliable microwave-based methane dehydroaromatization process. The effect of other parameters including temperature, weight hourly space velocity, role of microwave absorber, and methane concentration during microwave-assisted methane dehydroaromatization reaction are studied. Mo/ZSM-5 was found to suffer from low permittivity and nonuniform heating under microwave conditions. Mixing silicon carbide powder as a microwave absorber with the catalyst was found to provide more uniform heating. When assessing the catalytic performance of the mixture, it was found that higher methane partial pressures at 2000 cc/g cat .h and a temperature range of 500-600°C produced the highest amount of benzene. The formation of graphitic carbon on the spent catalyst increased with temperature, gas-solid contact period, and methane concentration, which resulted in higher methane conversion and benzene selectivity. The study indicates that under microwave heating the presence of localized carbon enhanced catalyst life by coupling with microwave energy, leading to localized heating, and improving benzene selectivity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Three Approaches for Complete Measurement of the Transverse Beam Optics Along the Fermilab Muon Campus Extraction Line

Traditionally, the process of measuring the optical parameters of a beamline has employed the use of one of two standard methods, namely the three-screen method or a quadrupole magnet scan. Both require either an area of zero dispersion to perform the measurements or knowledge of the dispersion function and momentum spread beforehand in order to provide accurate results. There is however a third method that can be used to measure the standard optical parameters, the beam parameters, the dispersion function, and the momentum spread simultaneously. This method, aptly named the six-screen method, is an extension of the more standard three-screen method. Utilizing the simulation environment of G4beamline, we simulated the 8 GeV proton beam in the M4 beamline and measured the optical and beam parameters using the two standard approaches. Those results were then used as a reference to check the viability of employing the less standard six-screen method in the M4 line. If shown to be a viable option, the six-screen method could be used to retrieve the dispersion function and momentum spread of the beam without needing to change the energy of the beam.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Polarized electron injector for positron production at CEBAF

As a part of the effort to expand the capabilities of CE-BAF 12 GeV (Continuous Electron Beam Accelerator Facility) at Jefferson Lab, the addition of a polarized positron source is considered. This capability would provide acceleration of high duty-cycle polarized posi-trons, with spin >60% polarization, through the same main CEBAF accelerator machine with appropriate mag-net field reversals and linac phasing to the four CEBAF experimental halls. To produce this positron beam, a high average current (3-10 mA) highly polarized electron beam with energy of 100 ? 150 MeV is required at the positron source target. The focus of this paper is the de-sign of that polarized electron beam injector. We will describe the production and delivery of a >3 mA highly polarized electron beam. We will discuss different aspects of the design, the photocathode gun, beam dynamics simulation results, spin manipulation, bunching and accelerating process and final electron beam parameters.

Kazimi, R.↗
DOE OSTI2022

DECOVALEX-2023, Task F Specification, Revision 8

This report is the revised (Revision 8) Task F specification for DECOVALEX-2023. Task F is a comparison of the models and methods used in deep geologic repository performance assessment. The task proposes to develop a reference case for a mined repository in a fractured crystalline host rock and a reference case for a mined repository in a salt formation. Teams may choose to participate in the comparison for either or both of the reference cases. For each reference case, a common set of conceptual models and parameters describing features, events, and processes that impact performance will be given, and teams will be responsible for determining how best to implement and couple the models. The comparison will be conducted in stages, beginning with a comparison of key outputs of individual process models, followed by a comparison of a single deterministic simulation of the full reference case, and moving on to uncertainty propagation and uncertainty and sensitivity analysis. This report provides background information, a summary of the proposed reference cases, and a staged plan for the analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

DECOVALEX-2023 Task F Specification (Rev. 9)

This report is the revised (Revision 9) Task F specification for DECOVALEX-2023. Task F is a comparison of the models and methods used in deep geologic repository performance assessment. The task proposes to develop a reference case for a mined repository in a fractured crystalline host rock (Task F1) and a reference case for a mined repository in a salt formation (Task F2). Teams may choose to participate in the comparison for either or both reference cases. For each reference case, a common set of conceptual models and parameters describing features, events, and processes that impact performance will be given, and teams will be responsible for determining how best to implement and couple the models. The comparison will be conducted in stages, beginning with a comparison of key outputs of individual process models, followed by a comparison of a single deterministic simulation of the full reference case, and moving on to uncertainty propagation and uncertainty and sensitivity analysis. This report provides background information, a summary of the proposed reference cases, and a staged plan for the analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

DECOVALEX-2023: Task F Specification (Revision 10)

This report is the revised (Revision 10) Task F specification for DECOVALEX-2023. Task F is a comparison of the models and methods used in deep geologic repository performance assessment. The task proposes to develop a reference case for a mined repository in a fractured crystalline host rock (Task F1) and a reference case for a mined repository in a salt formation (Task F2). Teams may choose to participate in the comparison for either or both reference cases. For each reference case, a common set of conceptual models and parameters describing features, events, and processes that impact performance will be given, and teams will be responsible for determining how best to implement and couple the models. The comparison will be conducted in stages, beginning with a comparison of key outputs of individual process models, followed by a comparison of a single deterministic simulation of the full reference case, and moving on to uncertainty propagation and uncertainty and sensitivity analysis. This report provides background information, a summary of the proposed reference cases, and a staged plan for the analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Design Methods, Tools, and Data for Ceramic Solar Receivers

This report presents the development of tools and methods for evaluating the reliability and performance of ceramic materials in high temperature solar receivers. As Concentrating Solar Power (CSP) technologies aim for higher operating temperatures to enhance efficiency and meet industrial process heat requirements, current high temperature metallic materials face challenges in maintaining structural integrity. This report explores advanced ceramics as a promising alternative, given their superior high temperature strength and lower thermal expansion, compared to metals. To address the need for effective ceramic receiver design tools, this report integrates statistical failure models of ceramics into the existing srlife tool: an open-source software package designed to estimate the life of high temperature CSP components. These failure models account for the inherent variability and flaw distribution in ceramics, as well as the impact of subcritical crack growth under high temperature cyclic loads. The report also presents experimental data collected for a commercially available ceramic material, SiC, and details the process of estimating reliability model parameters from these data. A comparative design analysis is then performed between ceramic (SiC) and metallic (current nickel-based superalloys A740H and A282) receiver. This comparison demonstrates that SiC receivers can achieve service life exceeding 30 years under high incident heat flux conditions, compared to just a few years for metallic receivers.

14 SOLAR ENERGY↗