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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Process development for recovering critical elements from acid mine drainage

The rapid development of advanced technologies has increased the demand for critical elements, such as Mn, Co, and Ni. For this work, a systematic study was conducted to develop a process for producing high-purity Mn, Co, and Ni products from an acid mine drainage (AMD). As major contaminants, Fe and Al in the solution were sequentially precipitated and eliminated by elevating the pH to around 4.00 and 6.50, respectively. After that, a pre-concentrated slurry containing 3,794 mg/L Mn, 59 mg/L Co, 127 mg/L Ni, and 300 mg/L Zn was obtained by collecting the precipitates formed in the pH range of 6.50 to 10.00. The pH of the pre-concentrated slurry was decreased to around 5.00 by adding HCl to re-dissolve Co, Ni, and Zn for further purification. At this pH, greater than 50% of Mn remained undissolved, and filtration of the undissolved material resulted in a product with around 30 wt.% Mn. Sodium sulfide was added into the re-dissolved solution to selectively precipitate Co, Ni, and Zn while remaining Mn in the solution. Almost 100% of Co, Ni, and Zn but only around 15% of Mn were precipitated using a sulfur to metal molar ratio of 1 at pH 4.00. The sulfide precipitate was calcined at 200 °C for 2 h and then completely dissolved in 1.2 M HCl. The critical elements existing in the dissolved solution were efficiently separated using a two-stage solvent extraction process. Ultimately, Co and Ni products with almost 94% and 100% purity were obtained by sulfide and alkaline precipitation, respectively.

42 ENGINEERING↗
DOE OSTI2023

Dielectric Relaxation by Quantum Critical Magnons

We report the experimental observation of dielectric relaxation by quantum critical magnons. Complex capacitance measurements reveal a dissipative feature with a temperature-dependent amplitude due to low-energy lattice excitations and an activation behavior of the relaxation time. The activation energy softens close to a field-tuned magnetic quantum critical point at H = H c and follows single-magnon energy for H > H c , showing its magnetic origin. Furthermore, our study demonstrates the electrical activity of coupled low-energy spin and lattice excitations, an example of quantum multiferroic behavior.

1-dimensional spin chains↗
DOE OSTI2025

Critical Clearing Time for Droop-Controlled Grid-Forming Inverters With Circular Current Limiting and Virtual Impedance Current Limiting

The critical clearing time is a crucial parameter for assessing the large-signal stability of grid-forming (GFM) inverters. Variations in current limiters can significantly impact an inverter's transient behavior during large disturbances. Here, this letter introduces a method based on the power-angle relationship to evaluate the fault recovery of a droop-controlled GFM inverter under a three-phase bolted fault scenario, considering both the circular current limiter and the virtual impedance method. High-fidelity simulations validate the accuracy of the proposed formulas in estimating the critical clearing time of the GFM inverter.

42 ENGINEERING↗
DOE OSTI2020

Design of a Critical Experiment to Validate Yttrium Hydride at Varying Temperatures

As microreactors become an emerging nuclear energy source for remote applications, designers are looking at the use of high temperature moderator material to reduce the fuel mass in the core by up to a factor of two. The microreactor community is in constant search of the best moderator material to retain hydrogen at high temperatures while optimizing neutronic performance. Recent simulation work has shown that materials which have a high and low Z component are optimal for this application. Material properties studies have further shown that yttrium hydride maintains hydrogen and stays as a solid until well over the needed temperatures, and thus retains hydrogen. A critical experiment is planned at the National Criticality Experiments Research Center (NCERC) to test the reactivity behavior of yttrium hydride at standard and elevated temperatures.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

ORNL S/U Capabilities for Critical Experiment Design [Slides]

This presentation is on the Oak Ridge National Labatory (ORNL) S/U capabilities for critical experiment design. It covers a brief intro to TSUNAMI analysis for NCS validation. Additionally, it shows similarity indices and historical use of TSUNAMI for critical experiment design. It concludes with recent designs: IER-441, IER-304, and IER-554 (on-going).

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

Scalable and Regenerable Fibrous Amine-functionalized Matrix (FAM) sorbent for Efficient Enrichment of Critical Minerals from Coal Wastewaters

The poster presents the latest progress on utilizing a commercially scalable flat sheet sorbent for the effective enrichment of critical minerals from coal wastewater. It highlights the performance, scalability, and potential for industrial applications, addressing key challenges in critical recovery from complex wastewater streams.

critical metals↗
DOE OSTI2022

Design Optimization for EUROPA Critical Experiment

The Experiment for Unresolved Region Of Plutonium Actinides (EUROPA) is an integral critical experiment currently being designed to target the intermediate energy region of plutonium. Intermediate energies, those between 0.625 eV - 100 keV, contain the end of resolved and beginning of the unresolved resonance region, making experiments in this energy range prudent for validating the representation of cross sections in this transition region. Below is the preliminary design of the experiment to be performed at the National Criticality Experiments Research Center (NCERC). Experiment optimization required an exhaustive down selection of several moderating, absorbing, and reflecting materials using Particle Swarm Optimization (PSO) in order to achieve maximum sensitivity to the intermediate energy region.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Polymer Compositions in Critical Experiments: Possibly Not What You Think

The Chlorine Worth Study (CWS) Experiment was performed at the National Criticality Experiments Research Center (NCERC) in December 2021. Its goal was to provide a validation benchmark experiment with chlorine and plutonium in the thermal neutron spectrum. This purpose is necessary to reduce the margin of subcriticality in aqueous chloride operations at the Los Alamos National Laboratory Plutonium Facility (PF-4). Reducing the margin of subcriticality will enable higher throughput, required to meet NNSA mission needs. The experiment used layers of plutonium plates, polyethylene (HDPE), aluminum, and polyvinyl chloride (PVC) or chlorinated polyvinyl chloride (CPVC). They were optimized to match plutonium-chloride solutions of 30 g/L, 300 g/L, and 600 g/L. Upon completion of the experiment, a International Criticality Safety Benchmark Evaluation Program (ICSBEP) report was immediately started. The compositions of all materials were assumed pure unless additional information was known (such as for the plutonium plates). During the benchmark analysis, the assumed CPVC composition was questioned. The follow-on work led to lessons learned on compositions in benchmarks. Materials, and specifically polymers, are often much more complex than a basic chemical formula. The CWS experiment is used as an example in this paper to document the lessons learned.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Impact of Higher Fidelity Design Iterations on Critical System Criteria

Nuclear criticality experiments are effective at informing the performance of nuclear data libraries across many applications. This work explores the implications of refining critical experiment MCNP models from their low fidelity optimization phase to penultimate neutronic models. Specifically, this work is focused on two series of plutonium fueled experiments funded through internal programs at Los Alamos National Laboratory building off previous efforts under the EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) collaboration. Thales, the first of the two collaborations, is a fast spectrum Ta-reflected plutonium experiment to support operations at PF-4. The second experiment are twin configurations designed to target the intermediate energy cross sections in 239 Pu. Motivation for this experiment stems from the PARallel Approach of Differential and InteGral Measurements (PARADIGM) collaboration which hopes to achieve a significant reduction in 239 Pu cross section uncertainties in the intermediate region.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Reactive Transport Modeling with Physics-Informed Machine Learning for Critical Minerals Applications

This study presents a physics-informed neural network (PINN) framework for reactive transport modeling for simulating fast bimolecular reactions in porous media. Accurate characterization of cAhemical interactions and product formation in surface and subsurface environments is essential for advancing critical mineral extraction and related geoscience applications. The proposed methodology sequentially addresses the flow and diffusion–reaction subproblems. The flow field is computed using a mixed formulation, while the diffusion–reaction system is modeled via two uncoupled tensorial diffusion equations reformulated in terms of chemical invariants. PINNs are employed to solve the governing equations, enabling data-efficient, mesh-free prediction of chemical concentration fields. The framework is validated through a series of benchmark problems involving flow in heterogeneous porous media. Initial verification is conducted using patch tests for the flow field, followed by validation of the transport problem with emphasis on preserving non-negativity of concentrations. The complete fast bimolecular reaction scenario is then solved, yielding spatial distributions of reactants and product species. Results demonstrate that the PINNs-based approach effectively captures sharp, mixing-limited reaction fronts and dispersive mixing behavior, offering reliable predictions of reactive plume evolution. These capabilities are crucial for evaluating long-term subsurface behavior in applications such as fluid storage, energy extraction, and efficient extraction of critical minerals.

42 ENGINEERING↗
DOE OSTI2021

Investigating the relation between instantaneous driving decisions and safety critical events in naturalistic driving environment

The availability of large-scale naturalistic driving data provides enormous opportunities for studying relationships between instantaneous driving decisions prior to involvement in safety critical events (SCEs). This study investigates the role of driving instability prior to involvement in SCEs. While past research has studied crash types and their contributing factors, the role of pre-crash behavior in such events has not been explored as extensively. The research demonstrates how measures and analysis of driving volatility can be leading indicators of crashes and contribute to enhancing safety. Highly detailed microscopic data from naturalistic driving are used to provide the analytic framework to rigorously analyze the behavioral dimensions and driving instability that can lead to different types of SCEs such as roadway departures, rear end collisions, and sideswipes. Modeling results reveal a positive association between volatility and involvement in SCEs. Specifically, increases in both lateral and longitudinal volatilities represented by Bollinger bands and vehicular jerk lead to higher likelihoods of involvement in SCEs. Further, driver behavior related factors such as aggressive driving and lane changing also increases the likelihood of involvement in SCEs. Driver distraction, as represented by the duration of secondary tasks, also increases the risk of SCEs. Likewise, traffic flow parameters play a critical role in safety risk. The risk of involvement in SCEs decreases under free flow traffic conditions and increases under unstable traffic flow. Further, the model shows prediction accuracy of 88.1 % and 85.7 % for training and validation data. These results have implications for proactive safety and providing in-vehicle warnings and alerts to prevent the occurrence of such SCEs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

The role of driver head pose dynamics and instantaneous driving in safety critical events: Application of computer vision in naturalistic driving

This paper investigates the role of driver behavior especially head pose dynamics in safety–critical events (SCEs). Using a large dataset collected in a naturalistic driving study, this paper analyzes the head pose dynamics and driving behavior in moments leading up to crashes or near-crashes. The study uses advanced computer vision and mixed logit modeling techniques to identify patterns and relationships between drivers’ head pose dynamics and crash involvement. The results suggest that driver-head pose dynamics, especially poses that indicate distraction and movement volatility, are important factors that can contribute to undesirable safety outcomes. Marginal effects show that angular deviation for head pose dynamics indicated by yaw, pitch and roll increase the likelihood of crash intensity by 4.56%, 4.92% and 8.26% respectively. Furthermore, traffic flow and lane changing also contribute to increase in likelihood of crash intensity. These findings provide new insights into pre-crash factors, especially human factors and safety–critical events. The study highlights the importance of considering human factors in designing driver assistance systems and developing safer vehicles. This research contributes by examining naturalistic driving data at the microscopic level with early detection of behaviors that lead to SCEs and provides a basis for future research on automation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Physics-based hybrid machine learning for critical heat flux prediction with uncertainty quantification

Critical heat flux (CHF) is a key quantity in nuclear system modeling due to its impact on heat transfer, safety margins, and reactor performance. This study develops and validates an uncertainty-aware hybrid modeling approach that combines machine learning with physics-based models to predict CHF in cases of dryout. The Biasi and Bowring empirical correlations were paired with three ML uncertainty quantification (UQ) techniques: deep neural network (DNN) ensembles, Bayesian neural networks (BNNs), and deep Gaussian processes (DGPs). A pure ML model without a base model was evaluated for comparison. Model performance was assessed under plentiful (7,350 points) and limited (9 points) training data scenarios using parity, uncertainty distributions, and calibration curves. Results show that the Biasi hybrid DNN ensemble achieved the best overall performance, with a mean absolute relative error of 1.846%, and well-calibrated uncertainty estimates. The BNN-based hybrids showed slightly higher error (2.14%) but superior uncertainty calibration. DGP models underperformed, with over 6% error and poor uncertainty calibration. All hybrid models outperformed pure machine learning configurations, demonstrating resistance against data scarcity. These findings indicate that hybrid modeling significantly improves predictive accuracy, interpretability, and resilience to data scarcity. The integration of uncertainty awareness provides actionable confidence in CHF predictions, which is vital for safety-critical decisions in nuclear applications. This hybrid approach offers a viable pathway for deploying ML models in reactor analysis tools while preserving domain knowledge and physical consistency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Characterization and recovery of rare earth elements and other critical metals (Co, Cr, Li, Mn, Sr, and V) from the calcination products of a coal refuse sample

Here, the impacts of calcination on the leaching recovery of rare earth elements (REEs) and other critical metals from a Baker seam coal refuse material were investigated. Acid leaching test results showed that leaching recovery of the REEs, especially the light REEs, was increased significantly from around 24% to 80–90% after calcination under 600–750 °C for two hours. By considering the major element leaching kinetics and the mineralogical changes of the dominant minerals caused by calcination, two mechanisms were proposed for the improved leaching performance: (1) decomposition of difficult-to-dissolve REE-bearing minerals into soluble forms; and (2) liberation of REE-bearing minerals encapsulated in clays after calcination due to the dehydration and disintegration of the layered clay structure. Sequential chemical extraction tests showed that a significant fraction (around 75%) of the REEs in the raw material were present in an insoluble form. After calcination under proper temperatures (600–800 °C), the majority of the insoluble light REEs (LREEs) were converted into soluble forms. Changes in the modes of occurrence of the LREEs and phosphorous based on leaching rate and sequential leaching correlated well as a function of the calcination temperature. This finding in addition to SEM-EDX results tends to indicate the potential that the LREEs occur primarily as rare earth phosphates such as monazite in the untreated coal refuse material. The acid leaching and sequential chemical extraction results show that co-extraction of REEs and other critical metals such as Co, Mn, and Li is possible using a calcination-acid leaching procedure.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Effect of oxidative breakers on organic matter degradation, contaminant mobility and critical mineral release during shale-fracturing fluid interactions in the Marcellus Shale

Oil and gas production from organic-rich shale formations has become viable through advancements in multistage hydraulic fracturing. However, fluctuations in oil and gas prices, coupled with the sharp decline in gas production after the initial days of fracturing operations, drive operators to devise strategies for enhancing hydrocarbon production. The use of highly reactive fracturing fluids that include strong oxidizing agents, also known as breakers, can potentially increase well productivity. The oxidative breakers are used to reduce the viscosity of gel-based fluids after the proppant is transported into fracture zones of the target formation. These breakers can also degrade the organic matter, enhancing the release of hydrocarbons. However, chemical byproducts generated by the interaction of oxidative breakers with the shale matrix have not been extensively studied. Here, this study investigated the fluid-rock interactions between Marcellus Shale and synthetic hydraulic fracturing fluid (HFF) solutions comprising three different oxidative breakers, i.e., ammonium persulfate, sodium bromate, and sodium hypochlorite, commonly used in the Appalachian Basin, USA. Our results demonstrate that the type of oxidizing breakers used in the HFF controlled the type and amount of volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) produced. In all HFF reacted effluents, we observed the transformation of VOCs and the presence of organic acids in variable amounts. However, effluents from HFF containing sodium bromate and sodium hypochlorite breakers showed the presence of several halogenated organic compounds. Changes in major ions and mineralogy indicate that carbonate dissolution and barite precipitation were ubiquitous in all shale reacted effluents. Our results also demonstrate that the addition of oxidative breakers increased the concentration of several major and trace elements in the effluents. These elements fall under the critical mineral (CM) or critical element category due to their high demand in emerging technologies and susceptibility to supply chain disruption due to variety of factors. However, before oxidative breakers can be used at a larger field scale to enhance the release and recovery of CM and hydrocarbons, a better understanding is required of the potential environmental impacts associated with the generation and transformation of contaminants during breaker-fluid-rock interaction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Adaptive critic design-based reinforcement learning approach in controlling virtual inertia-based grid-connected inverters

In this report, an adaptive critic design (ACD) approach is proposed to control the phase and voltage of a grid-connected virtual synchronous generator (VSG). The penetration of fast responding inertia-less power converters significantly affect the stability of the power system, especially weak systems such as micro grids. The concept of virtual inertia addresses this concern by virtually emulating the behavior of a synchronous generator. However, the conventional VSG is designed based on two conditions: (i) fixed operating point and (ii) inductive grid connections. The performance of VSGs in low-voltage semi-resistive microgrids is far from optimal. To overcome the aforementioned concerns, a heuristic dynamic programing (HDP) approach is proposed to optimally control grid-connected VSGs. The neural-network-based inherence of the HDP enables the proposed technique to adapt to any impedance angle. The HDP controller includes two subnetworks: (i) the action network that controls the system optimally and (ii) the critic network, which evaluates the effectiveness of the action network. The simulation and experimental results are provided to evaluate the effectiveness of the proposed technique. As shown, the HDP-based approach illustrates a better performance in comparison with the conventional PI-based VSG in various operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Fatigue life prediction of powder bed fused–laser beam AlSi10Mg: Incorporating critical defects via crystal plasticity modelling

The current study provides a microstructurally-based computational framework to predict the fatigue life of additive manufactured (AM), i.e., powder bed fused–laser beam (PBF-LB), AlSi10Mg specimens using the crystal plasticity finite element method (CPFEM). The fractography analysis, electron backscatter diffraction (EBSD), uniaxial and cyclic responses, and fatigue life of specimens were used to inform the computational framework. CPFE simulation was used to compute fatigue indicator parameters (FIPs) as fatigue driving forces. A new fatigue criterion is introduced based on FIPs, which was calibrated using experimental fatigue data. The proposed fatigue measure was evaluated versus the specimens with critical defects of various sizes and locations subjected to different stress amplitudes. The results show that the developed framework can capture the fatigue life of samples with different critical defect locations and sizes along with different stress amplitudes for both high-cycle fatigue (HCF) and very high-cycle fatigue (VHCF) regimes.

Additive manufacturing↗
DOE OSTI2024

Critical mineral substitutions in IN617: A combined computational and experimental approach to performance evaluation and feasibility

Addressing the escalating demand for critical minerals (CMs) driven by global climate change initiatives, this study explores compositional modifications to Inconel 617 (IN617) by substituting cobalt (Co) with manganese (Mn) across various atomic percentages. Here, we conducted a computational feasibility study employing Molecular Dynamics (MD) simulations to provide strategic guidance for experimental validation. The simulations analyzed tensile strength and corrosion resistance for five modified compositions (M1 to M5) to identify optimal properties. Tensile tests on cubic simulation cells were performed to generate stress-strain curves, revealing the impact of Co replacement with Mn on tensile strength—a metric correlated with hardness. Oxygen penetration simulations were conducted to evaluate corrosion resistance, indicating that reduced oxygen penetration depth corresponds to enhanced resistance. Promising compositions underwent phase diagram calculations for assessing phase stability. The optimal composition (M1), characterized by high tensile strength and minimal oxygen penetration, was chosen for experimental validation using induction melting and friction stir consolidation techniques. The materials were further characterized using SEM-EDS, XRD, and Vickers hardness testing. Our findings suggest that Mn substitution in IN617 can yield mechanical performance at par with high-Co alloys in energy-critical applications.

36 MATERIALS SCIENCE↗