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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Role of Histidine‐Containing Peptoids in Accelerating the Kinetics of Calcite Growth

Carbonate mineralization, the conversion of CO 2 into stable, thermodynamically favorable carbonate minerals, offers a promising strategy for permanent and environmentally friendly carbon storage, with minimal risk of long-term leakage and minimal monitoring requirements. Drawing inspiration from carbonic anhydrase (CA), a family of zinc-containing metalloenzymes that catalyze the hydration of CO 2 to bicarbonate and promote carbonate precipitation, a class of histidine-containing peptoids was designed that is capable of coordinating with Zn 2+ ions to act as CA mimetics for accelerating calcite step growth. In situ atomic force microscopy (AFM) measurements reveal that these peptoids significantly enhance step advancement, with a more pronounced effect observed when combined with Zn 2+ ions and under higher calcium-to-carbonate activity ratios, indicating that peptoids facilitate the incorporation of CO 3 2− ions at step edges. Solution NMR and 3D atomic force microscopy (3D AFM) analyses show that the coordination of peptoids with Zn 2+ promotes both the deprotonation of HCO 3 − to CO 3 2− and restructures the interfacial hydration layers of calcite, collectively lowering the activation barrier for step growth. These findings establish a design framework for sequence-defined polymers to regulate carbonate mineralization, offering promising applications in CO 2 capture and long-term storage.

CO2 mineralization↗
DOE OSTI2022

Design of the PIP-II 650 MHz Low Beta Cryomodule

The Proton Improvement Plan II (PIP-II) that will be installed at Fermilab is the first U.S. accelerator project that will have significant contributions from international partners. CEA joined the international collaboration in 2018, and is responsible of the 650 MHz low-beta section made of 9 cryomodules, with the design of the cryostat (i.e the cryomodule without the cavities, the power couplers and the frequency tuning systems) and the manufacturing of its components, the assembly and tests of the pre-production cryomodule and the 9 series ones. This paper will present the design of the 650 MHz low-beta cryomodule.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Development of Accelerated Steady-state Test Capsule Experiments to Replicate EBR-II Fuel Behavior Using BISON Fuel Performance Analysis

Here in this work, BISON fuel performance calculations were performed to predict the fuel behavior of accelerated burnup U-Pu-Zr fuel, with temperature operation conditions of the fuel and the cladding mirroring conditions within EBR-II fuel pins. The temperature operating conditions within the FAST accelerated burnup rods were aimed at replicating EBR-II X447/X447A fuel surface and inner cladding surface temperatures. Due to the FAST capsule design, these temperatures can be replicated with fission rate densities being significantly increased. fuel performance modeling has not been assessed for novel experiments such as accelerated burnup utilizing the FAST capsule within ATR. This is an important step in understanding accelerated irradiation methods as many performance models are empirical models conforming to the results of PIE but do not always include physical models that would represent the changes in irradiation tests.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

IImprove hydrogen sorption kinetics of MgH2 by doping carbon-encapsulated iron-nickel nanoparticles

Magnesium hydride (MgH2) with excellent hydrogen storage kinetics is important for the wide application of hydrogen energy. Herein, to accelerate the sorption kinetics of MgH2 and lower its dehydrogenation temperature, we design and prepare a carbon film coated dual transition metal alloy, the Fe0.64Ni0.36@C composite with a coreshell structure, and employ it as an additive to synthesize MgH2–Fe0.64Ni0.36@C system by ball-milling and hydriding combustion method. In contrast to pure MgH2, the initial hydrogen release temperature of the MgH2–Fe0.64Ni0.36@C composite lowers to 250°C from 480°C and the composite can absorb 5.18 wt% H2 within 20 min (150°C, 3 MPa H2). More importantly, the apparent activation energy of the dehydrogenation for decomposition of Fe0.64Ni0.36@C-doped MgH2 reduced from 162.8 ± 8.3 kJ/mol to 86.9 ± 4.6 kJ/mol. It is believed that the Fe@C and Mg2Ni/Mg2NiH4 formed on the surface of Mg/MgH2 act as intermediates of electron transfer between Mg2+ and H–, which synergistically enhanced the hydrogen absorption and desorption kinetics properties of the MgH2. Moreover, the MgH2 co-doped with the multiple in-situ formed active particles shows excellent cycling performance, indicative of potential application in practical hydrogen storage in the near future.

Ding, Zhenmin↗
DOE OSTI2025

Autonomous alloy composition optimization using molecular dynamics guided by a large language model

Here, we present an autonomous materials discovery framework that couples a large language model (LLM) with molecular dynamics (MD) simulations to optimize Fe–Cr–Mn alloy compositions for tensile strength. Starting from six distinct compositions, the LLM operated as an intelligent agent, iteratively proposing changes based on prior simulation results and constraints. Over 50 iterations per case, the LLM adaptively explored the composition space, identifying high-strength regions, not easily accessible by conventional methods. The highest strength, 18.7 GPa, was achieved with Fe 71 Cr 25 Mn 4 composition, identified from a Fe 75 Cr 20 Mn 5 starting point. The LLM autonomously adjusted its strategy in real time, demonstrating closed-loop decision-making using commodity hardware. This approach showcases the potential of LLMs as scientific co-pilots, capable of accelerating materials discovery and generalizable to other domains like biology and drug design.

Autonomy↗
DOE OSTI2026

Recent advances in chemical recycling and upcycling of plastic waste into valuable materials, chemicals, and energy: a comprehensive review

The global plastic waste crisis has increased in severity in recent years: annual plastic production is projected to reach 500 million metric tons by 2025, and plastic waste accumulation is expected to surpass 12 billion metric tons. Despite these growing volumes, only ∼9% of plastic waste is currently recycled; the majority is either landfilled, incinerated, or mismanaged, contributing to escalating greenhouse gas emissions—from 1.7 Gt carbon dioxide equivalent (CO 2 -eq.) in 2015 to an estimated 6.5 Gt CO 2 -eq. by 2050—and physical environmental pollution. This review provides a comprehensive overview of advanced plastic upcycling strategies to address this issue and recover value from diverse plastic waste streams. Recent developments in solvent-based dissolution, chemical depolymerization, and thermochemical conversions are examined for major plastic types, including polyolefins, polycondensation polymers, and PVC. Underlying reaction pathways, catalyst designs, and processing parameters that govern product selectivity, efficiency, and conversion yields are discussed in depth. Emerging techniques such as microwave-assisted depolymerization, tandem catalysis, and co-processing approaches are highlighted for their potential to enhance efficiency under milder conditions. Emphasis is also placed on the production of high-value products such as monomers, naphtha-range hydrocarbons, and syngas, and discussion is provided on catalyst stability, contaminant removal, scalability, life cycle effects on the environment, and technoeconomic viability. Finally, the review outlines future research directions focused on catalyst innovation, integrated process design, supportive policy frameworks, and interdisciplinary collaboration. All recommendations are aimed at accelerating large-scale implementation of plastic upcycling technologies and advancing the global circular plastics economy.

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

Hydra: An AI-Based Framework for Interpretable and Portable Data Quality Monitoring

Hydra is an advanced framework designed for training and managing AI models for near real time data quality monitoring at Jefferson Lab. Deployed in all four experimental halls, Hydra has analyzed over 2 million images and has extended its capabilities to offline monitoring and validation. Hydra utilizes computer vision to continually analyze sets of images of monitoring plots generated 24/7 during experiments. Generally, these sets of images are produced at a rate and quantity that is exceedingly difficult for shift crews to effectively monitor. Significant effort has been devoted to enhancing Hydra’s user interface, to ensure that it provides clear, actionable insights for shift workers and other users. Gradient Weighted Class Activation Maps (GradCAM) provide added interpretability, allowing users to visualize important regions of the image for classification. Hydra has been containerized to enable the creation of portable demos and seamless integration with container-based technologies such as Kubernetes and Docker. With the user interface enhancements and containerization, Hydra can be rapidly deployed for new use cases and experiments. This talk will describe the Hydra framework, its user interface and experience, and the challenges inherent in its design and deployment.

Britton, Thomas [Thomas Jefferson National Acceler↗
DOE OSTI2023

Variation of effective filament diameter, irreversibility field, anisotropy, and pinning efficiency in Bi-2212 round wires

Abstract In recent years Bi 2 Sr 2 CaCu 2 O x (Bi-2212) received increasing attention due to its round wire multifilamentary architecture, a unique feature in high- T c superconductor. In fact, round wires are preferable for magnet designs, including solenoids for nuclear magnetic resonance (NMR) or research purpose and accelerator magnets. However, due to the narrow over-pressure heat treatment conditions necessary to obtain high J c and to the peculiar microstructure of Bi-2212 wires, a full understanding of the correlations between the different properties has not yet been developed. In this paper we investigate the effect of a vital part of Bi-2212 optimization, the maximum heat-treatment temperature T max in the range of 885 °C–896 °C, on the variations of J c , effective filament diameter d eff , anisotropy γ , INTER- and intra-grain irreversibility fields and pinning energies U 0 , all critical parameters in unravelling the complex mix of vortex pinning and connectivity that ultimately determines the critical current density. We found that d eff of the higher J c wires heat-treated at lower temperature is much smaller than for the lower J c wires. Moreover, a systematic increase of the irreversibility field and a decrease of the intrinsic Bi-2212 anisotropy underpins the higher J c . The analysis of the pinning energies reveals that there is little sample-to-sample variation in the INTER-grain pinning, whereas in all samples the intra-grain pinning has an enhancement below ∼40–45 K becoming more and more evident with increasing J c . These results suggest that the overall J c performance are not only related to the wire microstructure and connectivity, which obviously affect the INTER-grain properties, but they are also intimately related to the intrinsic and intra-grain properties such as γ and U 0 .

Physics↗
DOE OSTI2021

ATLAS toward the High Luminosity era: challenges on electronic systems

To maximize the physics reach, the Large Hadron Collider (LHC) plans to increase its instantaneous luminosity to $7.5×10^{34} cm^{-2} s^{-1}$ and deliver $3 - 4 ab^{-1}$ of data at a center-of-mass energy of 14 TeV. To profit from this high-luminosity LHC operation with a pile-up up to 200 inelastic collisions per bunch crossing, performance of the ATLAS detector needs to be maintained and in many systems, improved. The upgraded detector will have an unprecedented output data rate of up to 200 TB/s. Real-time processing of this large data volume in a short time period is extremely challenging. New sets of both front-end and back-end electronics are required for all sub-detectors. The large number of detector channels, huge volumes of input and output data, short time available to process and transmit data, harsh radiation environment, and the need of low power consumption all impose great challenges on the designs of electronic systems.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Test Results of the First Pre-Series Quadrupole Magnets for the LHC Hi-Lumi Upgrade

The future high luminosity (Hi-Lumi) upgrade of the Large Hadron Collider (LHC) at CERN will include eight (plus two spares) 10.2 m-long Cryo-assemblies which will be components of the triplets for two LHC insertion regions. Each cold mass in the Cryo-assemblies will consist of two 4.2 m-long Nb 3 Sn high gradient quadrupole magnets, designated MQXFA, with aperture 150 mm and operating gradient 132.2 T/m, for a total of twenty magnets. Before assembling and testing the final cold masses at Fermilab, the component quadrupoles are being tested first at the vertical superconducting magnet test facility of the Superconducting Magnet Division (SMD) at Brookhaven National Laboratory (BNL), in superfluid He at 1.9 K and up to 18.0 kA, in accordance with operational requirements of the LHC. The tests of the first two full-length prototype quadrupole magnets MQXFAP1 and MQXFAP2 at BNL have been reported previously. The first two pre-series magnets, the first two that will be used in the LHC, have also now been tested. This paper reports on the quench test and training results of these two magnets. The test results of these magnets will be important for validating the final MQXFA design for operational magnets.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Improvement and generalization of ABCD method with Bayesian inference

To find New Physics or to refine our knowledge of the Standard Model at the LHC is an enterprise that involves many factors, such as the capabilities and the performance of the accelerator and detectors, the use and exploitation of the available information, the design of search strategies and observables, as well as the proposal of new models. We focus on the use of the information and pour our effort in re-thinking the usual data-driven ABCD method to improve it and to generalize it using Bayesian Machine Learning techniques and tools. We propose that a dataset consisting of a signal and many backgrounds is well described through a mixture model. Signal, backgrounds and their relative fractions in the sample can be well extracted by exploiting the prior knowledge and the dependence between the different observables at the event-by-event level with Bayesian tools. We show how, in contrast to the ABCD method, one can take advantage of understanding some properties of the different backgrounds and of having more than two independent observables to measure in each event. In addition, instead of regions defined through hard cuts, the Bayesian framework uses the information of continuous distribution to obtain soft-assignments of the events which are statistically more robust. To compare both methods we use a toy problem inspired by pp\to hh\to b\bar b b \bar b p p → h h → b b ‾ b b ‾ , selecting a reduced and simplified number of processes and analysing the flavor of the four jets and the invariant mass of the jet-pairs, modeled with simplified distributions. Taking advantage of all this information, and starting from a combination of biased and agnostic priors, leads us to a very good posterior once we use the Bayesian framework to exploit the data and the mutual information of the observables at the event-by-event level. We show how, in this simplified model, the Bayesian framework outperforms the ABCD method sensitivity in obtaining the signal fraction in scenarios with 1% and 0.5% true signal fractions in the dataset. We also show that the method is robust against the absence of signal. We discuss potential prospects for taking this Bayesian data-driven paradigm into more realistic scenarios.

Alvarez, Ezequiel↗
DOE OSTI2020

Report on Oak Ridge National Laboratory Testing of Ambient Cure TransPowr E3X®

A key to industry acceptance of a new technology is extensive validation in field trials. The Powerline Conductor Accelerated Test facility (PCAT) at Oak Ridge National Laboratory (ORNL) is specifically designed to evaluate the performance and reliability of novel overhead conductor and conductor instrumentation under field conditions. The facility is set up to capture large amounts of data during testing. General Cable used the ORNL PCAT facility to validate the performance of TransPowr® with Ambient Cure E3X™ Technology—a standard overhead conductor with a high emissivity, low absorptivity ambient cure surface coating. Extensive testing has demonstrated a significant improvement in conductor performance across a wide range of operating temperatures with respect to uncoated conductor of the same type, indicating that E3X Technology can provide a reduction in temperature, a reduction in sag, and an increase in ampacity when applied to the surface of any overhead conductor. This report provides results of that testing.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Time- and Energy-Resolved Coupled Saturn Radiation Environments Simulations Using the Integrated Tiger Series (ITS) Code

Using a newly developed coupling of the ElectroMagnetic Plasma In Realistic Environments (EMPIRE) code with the Integrated Tiger Series (ITS) code, radiation environment calculations have been performed. The effort was completed as part of the Saturn Recapitalization (Recap) program that represents activities to upgrade and modernize the Saturn accelerator facility. The radiation environment calculations performed provide baseline results with current or planned hardware in the facility. As facility design changes are proposed and implemented as part of Saturn Recap, calculations of the radiation environment will be performed to understand how the changes impact the output of the Saturn accelerator.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Phase-Field Modeling of Thermally-Grown Oxide and the Induced Damage Evolution in Environmental Barrier Coatings

The advent of next-generation hydrogen-based engines necessitates materials capable of withstanding temperatures beyond the reach of current superalloys. SiC-based ceramic matrix composites, augmented with environmental barrier coatings (EBCs), present a promising materials solution. Given the active search for effective and durable EBCs, there is a pressing need for modeling tools to understand and predict damage evolution in these materials to help accelerate their development. This study introduces a phase-field model (PFM) designed to simulate the critical role of thermally grown oxides (TGO) in the degradation and failure of EBCs. The model accounts for the severe volume expansion due to oxidation, alongside phase transformations and microstructural evolution during thermal cycling, offering a comprehensive view of the damage processes. Simulation results are validated against experimental findings reported in the literature, establishing the model's potential as a significant tool for understanding and improving the resilience of EBCs in cyclic oxidative environments.

Cheng, Tianle↗
DOE OSTI2024

Low Power, Radiation Resilient Synchronous Edge Processing for Remote Monitoring

Next-generation space remote sensing systems may be equipped with imaging arrays that sense data at a rate that outstrips the processing capability of any computing hardware that can operate within a satellite’s power budget. This project developed novel convolutional and recurrent neural networks to detect and estimate point-like events amid clutter, and investigated their efficient and accurate implementation on analog in-memory computing systems that are 10-1000× more energy-efficient than digital processors. This project leveraged two memory devices at different levels of technological maturity: a large-scale analog computing prototype using commercial SONOS charge-trap memory, and electrochemical memory (ECRAM) with intrinsic radiation hardness. We experimentally demonstrated end-to-end analog processing of our neural networks on SONOS and characterized the radiation response of both SONOS and ECRAM. We advanced the state-of-the-art in ECRAM precision and reliability, and developed co-design methods to enable accurate long-term operation of SONOS analog accelerators in space radiation environments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

New Measurement of Electron Neutrino Interactions on Argon in MicroBooNE

MicroBooNE, located at the Fermi National Accelerator Laboratory, is an 85-tonne liquid argon time-projection chamber designed to study neutrinos from the Booster Neutrino Beam and Neutrinos at the Main Injector (NuMI) beam. Understanding neutrino-nucleon interactions is essential for improving the accuracy of neutrino event generators, which are critical for modelling neutrino behaviour and interpreting data from oscillation experiments. The NuMI beam's high electron neutrino flux relative to its muon neutrino flux makes it particularly suited to probe these interactions. This poster presents new single-differential cross-section measurements of charged-current electron-neutrino interactions on argon with protons and no pions in the final state. These results use data from NuMI beam operations in both neutrino and antineutrino modes. Cross sections are reported as functions of key kinematic observables, including electron energy, total visible energy, and the opening angle between the electron and leading proton. Interaction rates as a function of proton multiplicity are also shown. These results are compared to theoretical predictions generated by widely used neutrino event generators.

Barnard, Abbey G. [Oxford U.] (ORCID:0000000161171↗
DOE OSTI2025

Phase Field Modeling of Chemical Reaction Related Damage Evolution in Environmental Barrier Coatings

The advent of next-generation engines necessitates materials capable of withstanding temperatures beyond the reach of current superalloys. SiC-based ceramic matrix composites, augmented with environmental barrier coatings (EBCs), present a promising materials solution. Given the active search for effective and durable EBCs, there is a pressing need for modeling tools to understand and predict damage evolution in these materials to help accelerate their development. This study introduces a phase-field model (PFM) designed to simulate the thermally grown oxides (TGO) and phase transformation in the degradation and failure of EBCs. The model accounts for the severe volume expansion due to oxidation, alongside phase transformations and porosity evolution during thermal cycling, offering a comprehensive view of the damage processes. Simulation results are validated against experimental findings reported in the literature, establishing the model's potential as a significant tool for understanding and improving the resilience of EBCs in cyclic oxidative environments.

fast-diffusion path↗
DOE OSTI2026

Solar Forecasting, Net Load Forecasting, and Data-Driven Distributed Solar Visibility Prizes (Final Technical Report)

The American-Made Solar Forecasting Prize, Net Load Forecasting Prize, and Data-Driven Distribution (3D) Solar Visibility Prize is a multimillion-dollar prize competition designed to energize U.S. solar innovation through a series of contests that accelerate the entrepreneurial process from years to months. The activities incentivized by these three prizes will support the governmentwide approach to increase American energy dominance by promoting innovation and early deployment of energy technologies, resulting in wider adoption, which is critical for secure, affordable, and reliable solar energy.

14 SOLAR ENERGY↗