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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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Using ai-GCMC simulations,operandoWAXS, and kinetics analysis, we found that the high-rate performance of Sb as an alloy anode in Na-ion batteries is due to the presence of an amorphous intermediate phase formed during sodiation and desodiation.
Abstract Cellulosic materials offer sustainable advantages for building energy conservation. However, their development has been hindered by reduced thermal performance, often caused by structural collapse during the transition from solution to solid. Inspired by natural goose down, a bio‐based, lightweight insulation foam derived from agricultural waste straw is presented. Through in situ synthesis, bio‐silica fibers with branched structures capable of supporting hollow silica microspheres are fabricated. After steam‐mediated processing, the resulting foam exhibit low density (95 mg cm − 3 ), high porosity (95.5%), low thermal conductivity (0.03 ± 0.003 W mK −1 ), and a cyclic compressive strength of 90 kPa at 50% strain. Owing to the synergistic microstructure formed by branched bio‐fibers and hollow silica spheres, the bio‐silica foam exhibit outstanding thermal insulation performance relative to other bio‐based foams prepared by ambient drying. A passivated insulation panel is further developed by incorporating this material as the core component, achieving a thermal conductivity of 0.0275 W mk −1 and flexural strength of 6.85 MPa. The panel demonstrated durability with stable thermal performance throughout a 60‐day outdoor test. Moreover, the bio‐silica foam shows a carbon footprint of 7.50 kgCO₂ kg −1 at 70.2 wt.% silica, highlighting its promise as a sustainable insulation solution for green buildings.
An Alabama community coalition received technical assistance through the U.S. Department of Energy's Communities Local Energy Action Program (LEAP) to expand awareness of alternative transportation fuels through stakeholder engagement efforts. Phase 1 of the project centered on outreach, relationship-building, and the identification of community priorities. Through two workshops held in October and December 2024, the coalition engaged over 120 stakeholders - including county commissioners, school district representatives, and public and private fleet operators. These sessions included presentations from technical experts and industry partners, as well as a vehicle showcase and structured discussions to assess stakeholder needs and concerns. This report summarizes these efforts and identifies three key priority areas for Phase 2 of the project.
Understanding the corrosion behavior of steels in supercritical carbon dioxide (S-CO2) is essential for ensuring the safe application of S-CO2 as a heat-transfer fluid in high-temperature energy systems, including advanced nuclear reactors. In this work, molecular dynamics (MD) simulations using ReaxFF potential are performed to explore the atomic-scale corrosion mechanisms of body-centered cubic iron (BCC-Fe) in S-CO2. The results show that CO2 molecules in S-CO2 decompose at the Fe surface, generating free C and O atoms that form Fe-C and Fe-O bonds and subsequently produce oxides and carbides. Concurrently, Fe atoms dissolve from the surface and diffuse into the S-CO2 region, resulting in interdiffusion of Fe, C and O atoms at the interface. The corrosion-layer thickness calculations show that high pressure and temperature induced by S-CO2 have stronger effects than surface orientation on the corrosion process. In addition, surface Fe atoms undergo substantial displacement under S-CO2 exposure, further accelerating corrosion. When a radiation-induced void is introduced near the Fe surface, the corrosion is enhanced. The void-matrix interface expands the reaction surface area and simultaneously induces corrosion reactions inside the bulk, resulting in a deeper penetration of C and O and thicker corrosion layers. All these results indicate that high-temperature, high-pressure and radiation-induced voids can seriously affect the corrosion of Fe in S-CO2, and must be considered to better use S-CO2 in nuclear facilities.
This article surveys our present understanding of the internal structure of the fully developed quark-gluon plasma at temperatures outside the crossover region. The theoretical part of the review covers perturbative and nonperturbative approaches to quark-gluon plasma structure, in particular, hard-thermal loop effective theory, lattice QCD and the functional renormalization group. The phenomenological part of the review scrutinizes the information that has been derived from bulk observables and hard probes in relativistic heavy ion collisions in terms of how it informs our knowledge about the structure of the quark-gluon plasma. The final section lists possible avenues for future progress.
Maximizing the amount of work harvested from an environment is important for a wide variety of biological and technological processes, from energy-harvesting processes such as photosynthesis to energy storage systems such as fuels and batteries. Here, we consider the maximization of free energy—and by extension, the maximum extractable work—that can be gained by a classical or quantum system that undergoes driving by its environment. We consider how the free energy gain depends on the initial state of the system while also accounting for the cost of preparing the system. We provide simple necessary and sufficient conditions for increasing the gain of free energy by varying the initial state. We also derive simple formulae that relate the free energy gained using the optimal initial state rather than another suboptimal initial state. Finally, we demonstrate that the problem of finding the optimal initial state may have two distinct regimes, one easy and one difficult, depending on the temperatures used for preparation and work extraction. We illustrate our results on a simple model of an information engine.
This report summarizes FY26 progress under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program's high-temperature gas-cooled reactor (HTGR) application driver work, covering a wide range of activities such as code validation and multi-physics code assessment. 1) A detailed SAM model of the High-Temperature Engineering Test Reactor (HTTR) was developed using a unique-block grouping approach, with an extended parallel thermal network method to capture block-to-block conduction and radiation heat transfer, and applied to steady-state simulations of the HTTR 30~MW and 9~MW cases. 2) In another activity, SAM's newly implemented multi-component gas flow model was validated against the Natural convection Shutdown heat removal Test Facility (NSTF) argon ingress experiment, correctly capturing the density-driven suppression and thermal recovery of natural circulation observed when argon is introduced into the air-cooled Reactor Cavity Cooling System (RCCS) loop. 3) For the OECD/NEA High Temperature Test Facility (HTTF) benchmark, we co-led the international benchmark activities as well as the OECD/NEA final benchmark report to be released at the end of this year. 4) Finally, the coupled Griffin-SAM modeling capability for pebble-bed HTGRs was advanced by verifying the Griffin neutronics solution against Serpent Monte Carlo for a realistic non-uniform temperature distribution, resolving several deficiencies in the SAM-to-Griffin temperature transfer scheme, and enabling distinct fuel kernel, moderator, and coolant temperatures for cross section feedback. These new features were demonstrated in a PBR load-following transient.
Thermoelectric materials have the ability to convert waste heat into electricity, offering a valuable solution for energy harvesting. However, their widespread use is hindered by low conversion efficiency, the reliance on expensive rare earth elements, and the environmental and regulatory concerns associated with lead-based materials. A fast and cost-effective way to identify highly efficient thermoelectric materials is through data-driven methods. These approaches rely on robust and comprehensive datasets to train models. Although there are several databases on thermoelectric materials, there is still a need to collect and integrate experimental data from peer-reviewed research articles to capture diverse compositions and properties of materials. Here, in this work, we developed a comprehensive database of 7,123 thermoelectric compounds, containing key information such as chemical composition, structural detail, seebeck coefficient, electrical and thermal conductivity, power factor, and figure of merit (ZT). We used the GPTArticleExtractor workflow, powered by large language models (LLM), to extract and curate data automatically from the scientific literature published in Elsevier journals. This process enabled the creation of a structured database that addresses the challenges of manual data collection. The open access database could stimulate data-driven research and advance thermoelectric material analysis and discovery.
In order to fully utilize the technological potential of unconventional superconductors, an enhanced understanding of the superconducting mechanism is necessary. In the best performing superconductors, the cuprates, superconductivity is intimately linked with magnetism, although the details of this coupling remain elusive. Here, we address this gap by studying the electron-doped cuprate Nd 1.85 Ce 0.15 CuO 4−δ that has an antiferromagnetic ground state when synthesized and only becomes superconducting after a reductive annealing process. Using neutron spectroscopy, we show that the as-grown crystal exhibits a large spin pseudogap in the magnetic fluctuation spectrum. Annealing removes defects introduced by the commonly employed synthesis method and significantly reduces the spin pseudogap. While the spin pseudogap in the annealed sample likely arises from superconductivity, in the as-grown sample it results from the absence of long-wavelength spin waves. These results reveal a direct connection between defects, magnetism, and superconductivity, offering new insight into the mechanisms underlying high-temperature superconductivity and guiding the design of improved superconducting materials.
Emergent macroscopic descriptions of matter, such as hydrodynamics, are central to our description of complex physical systems across a wide spectrum of energy scales. The conventional understanding of these many-body phenomena has recently been shaken by a number of experimental findings. Collective behavior of matter has been observed in mesoscopic systems, such as high-energy hadron–hadron collisions, or ultracold gases with only a few strongly interacting fermions. In such systems, the separation of scales between macroscopic and microscopic dynamics (at the heart of any effective theory) is inapplicable. To address the conceptual challenges that arise from these observations and explore the universality of emergent descriptions of matter, the EMMI Rapid Reaction Task Force was assembled. This document summarizes the RRTF discussions on recent theoretical and experimental advances in this rapidly developing field. Leveraging technological breakthroughs in the control of quantum systems, we can now quantitatively explore what it means for a system to exhibit behavior beyond the sum of its individual parts. In particular, the report highlights how the (in)applicability of hydrodynamics and other effective theories can be probed across three principal frontiers: the size frontier, the equilibrium frontier, and the interaction frontier.
Oversizing, the common engineering practice of specifying devices with capacity exceeding the actual load requirement, is a widespread practice across virtually all building technologies end-use categories, including HVAC, electrical systems, lighting, appliances, and plug loads. This practice, driven by factors like design uncertainty, institutional pressures, and risk aversion, results in wasted capital investment, control difficulties, and excessive energy consumption due to inefficient part-load operation. Part-load operation, where devices run below maximum capacity, is the dominant operating mode in most energy systems and presents a complex design challenge. Solutions to match output to load fall into three broad categories: constraining the output, adjusting the device’s internal behavior, and linking output to energy storage or other waste-heat reuse applications. The energy implications of part-load are critical, as efficiency often drops sharply as load decreases across a wide diversity of devices. To quantify the extent of this problem, we derive a dimensionless Part-Load Metric (PLM) based on device efficiency and its frequency distribution of operating hours at various output levels. The PLM quantifies the deviation of a device's actual efficiency from its maximum design efficiency. This metric also serves as a measure of "capital inefficiency," enabling engineers to compare the impact of different part-load solutions and providing a unified framework for evaluating performance across various devices and systems.
The accurate prediction of pressure drop in tightly packed, low–Reynolds number (Re) bare rod bundles is essential for the thermal-hydraulic design of the Microreactor Applications Research Validation and EvaLuation (MARVEL) reactor and other microreactor concepts. However, existing friction factor correlations, particularly the upgraded Cheng-Todreas (UCTD) correlation, have limited validation for the small pitch-to-diameter ratios (P/Ds) and transitional flow conditions characteristic of these systems. In this work, we perform high-fidelity large-eddy simulations (LESs) of both an infinite bare rod bundle and a finite bare 37-pin scalloped rod bundle across the range 1000≤ 𝑅𝑒 ≤5500. The simulations reveal strong gap vortex–driven transitional behavior and indicate that the UCTD may underpredict the friction factor by up to 28% at 𝑃/𝐷 = 1.05. Using the LES-calculated pressure drops, we formulate a new friction factor correlation that follows the Cheng-Todreas functional form but is calibrated for low-Re and tightly packed geometries representative of a MARVEL-like reactor. The correlation is implemented in the MOOSE (Multiphysics Object-Oriented Simulation Environment) subchannel module and compared against both the LES and UCTD predictions. Across all subchannel types, the proposed model reduces the streamwise velocity differences from as high as 44% (UCTD) to below 9%, and decreases the pressure gradient differences from 13% to 25% (UCTD) to 0.7% to 7% relative to the LES results. These results suggest that the new correlation has the potential to improve the pressure drop and flow field predictions for such geometries, highlighting the importance of high-fidelity simulations in supporting microreactor thermal-hydraulic model development and motivating future pressure drop experiments for compact rod bundles to further validate these findings.
Imines are of interest in the combustion modeling of nitrogen-based fuels such as ammonia, as intermediates in atmospheric oxidation of amines, and may offer a new class of environmentally benign substitutes for perhalogenated reagents. Elementary gas-phase rate constants for the consumption of H atoms by 1,1,1,3,3,3-hexafluoro-2-propanimine were measured over 294–736 K using the laser flash photolysis/atomic resonance fluorescence technique. The results are summarized as 3.0 × 10 –11 exp(−14.5 kJ mol –1 /RT) cm 3 molecule –1 s –1 with a confidence interval of ±13%. These are the first temperature-dependent kinetic experiments on an imine of the form R 2 C═NH and thereby provide the only validation of transition-state modeling for such systems. Several pathways are feasible; comparison of theory and experiment suggests the dominant channel is addition of H atoms to the nitrogen atom. On this basis, the observations are rationalized quantitatively. Computations also yield the thermochemistry of (CF 3 ) 2 CNH, with Δ f H 298 = −1232 kJ mol –1 .
Recognizing the potential of polymer-to-polymer transformations for plastics valorization, a new electrochemical strategy for the decarboxylative functionalization of polyacrylates has been developed. In contrast to most electrochemical approaches to plastic waste valorization that use small-molecule mediators or only form deconstruction products, this report describes one of the first direct electrochemical redox upconversions of a commodity polymer and involves activation of poly(acrylic acid), a material commonly found in disposable diapers and other personal hygiene products. Via electrochemical decarboxylation, poly(acrylic acid) is converted to methyl ether-containing copolymers. Although methods to prepare the 1:1 regularly alternating poly(vinyl methyl ether-alt-maleic anhydride) are known, routes to generate copolymers with variable levels of vinyl methyl ether and acrylate moieties are unknown, but such polymers may have utility in similar applications, such as dentifrices. Tunable conversions with up to 62 mol% vinyl methyl ether content were achieved via controlled-current electrolyses at >100 mA. This approach enables efficient access to copolymers with broad range of comonomer content from a common waste polymer starting material.
The diffusion of hydrogen in metals and alloys induces embrittlement that can adversely affect the structural properties. We examine the adsorption and diffusion of hydrogen in Inconel-718 (IN-718), and scrutinize the ensuing effects on the dislocation behavior in the alloy to elucidate the fundamental mechanisms of hydrogen-microstructure interactions from classical molecular simulations. Hydrogen adsorption increases with time until the surface saturates, while hydrogen diffusion exhibits strong temperature dependence, with diffusion coefficients converging above 1300 K regardless of the initial hydrogen concentration in the alloy. The diffusion in IN-718 is significantly sluggish than in pure Ni, Fe, or Cr, and is strongly impacted by hydrogen concentrations, resulting in an order of magnitude higher diffusion coefficient for hydrogen (10-14 m2/s relative to 10-15 m2/s) at high concentrations, especially below 600 K. Hydrogen diffusion coefficient varies from 10-12 to 10-15 m2/s in IN-718 depending on temperature (500–1400 K). More critically, our results reveal that increasing hydrogen concentration induces microstructural changes in the alloy, transforming perfect dislocations into stair-rods and Shockley partials, with higher temperatures favoring the latter. The results are significant for hydrogen fuel applications to gain insights into the materials chemistry for designing safer and more efficient propulsion systems, particularly in high-performance environments related to controlled hydrogen combustion applications.
An important validation of nucleosynthesis models of core-collapse supernovae is the comparison of radioisotope predictions to abundances inferred from observations of 𝛾 rays emitted in remnants. One such isotope, 44 Ti, is especially sensitive to the 57 Ni (𝑝,𝛾) 58 Cu reaction rate. Despite this importance, no experimentally constrained rate exists for this reaction. It is thus crucial to determine this rate. GRETINA ORRUBA: Dual Detectors for Experimental Structure Studies (GODDESS) was used along with the first use of the Enge split-pole spectrograph at Notre Dame to measure structure properties of 58 Cu via the 58 Ni ( 3 He,𝑡) 58 Cu reaction. Here, the combined analysis of these complementary data sets allows for precise determination of 58 Cu level energies, and spins are constrained from analysis of the 𝛾-ray decay. 44 Ti yields were found to change by over 25% compared to previous estimates in model calculations using the new experimentally constrained reaction rate.
Printing techniques have been instrumental in developing flexible and stretchable electronics, including organic light-emitting diode displays, organic thin film transistor arrays, electronic skins, organic electrochemical transistors for biosensors and neuromorphic computing, as well as flexible solar cells with low-cost processes such as inkjet printing, ultrasonic nozzle, roll-to-roll coating. The rise of additive manufacturing provides even more opportunities to print electronics in automated and customizable ways. In this work, we will review the current technologies of printing electronics (including printed batteries, supercapacitors, fuel cells, and sensors), especially with 3D printing. In this age of ongoing AI revolution, the application of AI algorithms is discussed in terms of combining them with 3D printing and electronics printing for a future with automated optimization, sustainable design, and customizable and scalable manufacturing.
Nuclear power plants (NPPs) are assessed for safety and security using separate models that cannot capture how an attacker's decisions and a plant's response unfold together in real time, leaving regulators and operators without a complete picture of true plant vulnerability. Traditional probabilistic risk assessment (PRA) methods treat adversarial events as fixed initiators with predetermined outcomes, and are structurally incapable of representing the time-dependent interplay between physical security events, safety system response, and operator mitigative actions. At Idaho National Laboratory (INL), I contributed to the development and validation of Modeling and Analysis for Safety and Security using the Dynamic EMRALD Framework (MASS-DEF). Where static PRA relies on event-tree logic that cannot evolve mid-scenario, MASS-DEF couples a time-dependent dynamic PRA tool EMRALD (Event Modeling Risk Assessment using Linked Diagrams) with attack simulation software, allowing attacker behavior, plant system states, and operator actions to interact across time. My work focused on validating a general Pressurized Water Reactor (PWR) model. I traced model logic against PWR plant to identified errors in logic and confirm accuracy. I then built and tested attack scenarios against a general PWR model to verify that the model produced expected outcomes across all logical pathways. I also contributed a section to a related technical paper applying the same EMRALD platform to radiation dose modeling. Results show that MASS-DEF can quantitatively demonstrate that many plants exceed their regulatory security thresholds. This demonstrated margin provides a technically defensible basis for reducing the number of guards without compromising regulatory compliance. Physical security costs represent roughly 10% of annual operating budgets, making such reductions directly meaningful to INL's mission of sustaining existing commercial NPPs. This internship strengthened my understanding of nuclear systems, probabilistic modeling, and technical writing, and has solidified my pursuit of a career at a national laboratory.