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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High-temperature nanoindentation creep studies on castable and sintered nanostructured low-activation ferritic-martensitic alloys

In this article, we present the creep characteristics of two reduced activation ferritic-martensitic steels of identical starting compositions formed by different fabrication routes: a nanostructured ferritic alloy commonly referred to as a castable nanostructured alloy (CNA) and a sintered nanostructured alloy (SNA) variant. Through a series of nanoindentation experiments spanning a temperature range of 25 °C to 650 °C, with a maximum load of 100 mN, we find creep behaviors in the cast and sintered materials to be remarkably similar. The creep stress exponent (n) for CNA and SNA were found to be in the range of 8–35 and the activation volume was ∼14–42b 3 , underscoring a dominance of dislocation-mediated mechanisms in both alloys. Notably, we observed a decline in the creep stress exponent with increasing temperature, attributable to the heightened influence of thermally activated dislocations. This phenomenon suggests a potential transition in the deformation mechanism towards a thermally activated dislocation climb process, significantly impacting the observed creep behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Realizing "Net-Zero-Carbon" Sustainable Aviation Fuel

The aviation industry needs renewable and fungible jet fuel - commonly referred to as sustainable aviation fuel (SAF) - to minimize emissions and increase efficiencies. SAF can displace the same, if not more, CO2 equivalent emissions (CO2eq), reduce contrail formation, and increase engine-aircraft efficiencies. Flight represents ~10% of transportation greenhouse gas emissions, with the global consumption of ~400 billion liters of fossil jet fuel in 2019 releasing over 900 million tons of CO2eq. Even with impacts from the COVID-19 global pandemic, the aviation sector is projected to grow with passenger miles expected to double by 2050, relative to 2010. As such, there is an urgent need to produce drop-in aviation fuel from renewables with a dramatically lower carbon footprint.

biojet↗
DOE OSTI2021

Microstructural Progression of Shear-Induced Mixing in a CuNi Alloy

Shear deformation has been highlighted in multiple research efforts for its ability to impart mechanical properties improvements and unique microstructures. When used to process and densify powdered material, these shear-based consolidation techniques are commonly referred to as friction consolidation (FC). In this paper, we have examined the microstructural evolution from compacted Cu and Ni powders to a consolidated Cu0.5Ni0.5 alloy. We have shown various stages of porosity reduction and preferential deformation being accommodated by the more ductile material early in the process, leading to formation of a tortuous microstructural zone. Porosity reduction was extensive, decreasing from ~65% in the unprocessed powder to ~1% in the fully consolidated alloy. The final consolidated alloy showed roughly a 2X hardness improvement over the unalloyed, compacted material. Unique aspects of this work include demonstration of the ability to use FC processing to produce a submicron and equiaxed grain size in samples within a 0.5 to 2 minute processing time.

Overman, Nicole R.↗
DOE OSTI2024

2D analysis of tokamak divertor-plasma detachment-bifurcation with operational parameters and geometries

UEDGE simulations with density scans for various input power, transport coefficients and outer poloidal leg length are performed to study the conditions for the existence of a bifurcation-like drop of T e at the outer strike point, commonly referred to as a detachment cliff, when transitioning to a detached plasma from an attached plasma in the outer divertor as the upstream density increases (McLean et al., 2015). The simulation results show that a detachment cliff tends to occur with a higher power input regardless of diffusivities and leg length. Further analysis of change of plasma profiles at a cliff indicate that, in addition to the sharp reduction of the E x B drift fluxes in the outer divertor studied in Jaervinen et al., (2018), the substantial change of the Mach number in the outer divertor and the decrease of the outer mid-plane T e due to the radiation front moving across the separatrix into the confinement region above the X-point consistently occur for all UEDGE density scans that have a detachment cliff. UEDGE time-dependent simulation of the evolution of a detachment cliff shows that the rapid increase of radiation above the X-point occurs in a time scale of ~0.3–0.5, which could possibly be the trigger for the formation of a detachment cliff, quicker than the Mach number change in a time scale of ~1 ms and the drop of T e in a time scale of ~2–3 ms in the outer divertor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

ν-point energy correletors with F AST EEC: Small-x physics from LHC jets

In recent years, energy correlators have emerged as a powerful tool for studying jet substructure, with promising applications such as probing the hadronization transition, analyzing the quark-gluon plasma, and improving the precision of top quark mass measurements. The projected N-point correlator measures correlations between N final-state particles by tracking the largest separation between them, showing a scaling behavior related to DGLAP splitting functions. These correlators can be analytically continued in N, commonly referred to as ν-correlators, allowing access to non-integer moments of the splitting functions. Of particular interest is the ν → 0 limit, where the small momentum fraction behavior of the splitting functions requires resummation. Originally, the computational complexity of evaluating ν-correlators for M particles scaled as 2 2M , making it impractical for real-world analyses. However, by using recursion, we reduce this to M 2M , and through the FastEEC method of dynamically resolving subjets, M is replaced by the number of subjets. This breakthrough enables, for the first time, the computation of ν-correlators for LHC data. In practice, limiting the number of subjets to 16 is sufficient to achieve percent-level precision, which we validate using known integer-ν results and convergence tests for non-integer ν. We have implemented this in an update to FastEEC and conducted an initial study of power-law scaling in the perturbative regime as a function of ν, using CMS Open Data on jets. The results agree with DGLAP evolution, except at small ν, where the anomalous dimension saturates to a value that matches the BFKL anomalous dimension.

Energy correlators↗
DOE OSTI2023

Modeling, analysis, and optimization of complex nuclear processes and facilities via computational methods: The HALEU process case study

Improving and adapting industrial systems to timely meet changing programmatic and market demands is an important goal to achieve, including when operating and maintaining complex nuclear processes and facilities. However, changes to these complex systems are costly, particularly when they are already in place and bounded to stringent requirements and constraints such as when handling radioactive material and contaminated equipment. These conditions often exist when treating spent nuclear fuel remotely within shielded nuclear radiation chambers, commonly referred as hot cells, to condition nuclear material and/or fabricate products for utilization in other nuclear enterprises such as in the manufacture of advanced nuclear fuel. The illustrative case considered here is the production of high assay low enriched uranium (HALEU) products supporting the deployment of advanced nuclear reactors. For the HALEU program, resources invested were and are being systematically analyzed so that these investments are maximized in a facility that is nearly 60 years old. A methodology that has effectively enabled optimized and improvements in the Spent Fuel Treatment (SFT) program, and consequently the HALEU program, involves discrete event simulation as addressed in this article. Here, the quantification of multiple productivity metrics, including material processing rates, cycle times, bottlenecks, number of material transfers as well as equipment, workstation, and material handling utilization, has resulted in a myriad of diverse discoveries and data-informed decisions regarding process layout and constituent, labor levels and schedules, selection of new process units, storage needs, and other critical process configurations. This article describes such a computational capability being applied for decision-making, illustrates its application to an actual process and program, provides illustrative results, and argues how computational methods for the modeling, analysis, and optimization of complex processes and facilities does lead to informed decisions derived from data and not only from intuition.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Reducing ridesourcing empty vehicle travel with future travel demand prediction

Ridesourcing services provide alternative mobility options in several cities. Their market share has grown exponentially due to the convenience they provide. The use of such services may be associated with car-light or car-free lifestyles. However, there are growing concerns regarding their impact on urban transportation operations performance due to empty, unproductive miles driven without a passenger (commonly referred to as deadheading). This paper is motivated by the potential to reduce deadhead mileage of ridesourcing trips by providing drivers with information on future ridesourcing trip demand. Future demand information enables the driver to wait in place for the next rider’s request without cruising around and contributing to congestion. A machine learning model is employed to predict hourly and 10-minute future interval travel demand for ridesourcing at a given location. Using future demand information, we propose algorithms to (i) assign drivers to act on received demand information by waiting in place for the next rider, and (ii) match these drivers with riders to minimize deadheading distance. Real-world data from ridesourcing providers in Austin, TX (RideAustin) and Chengdu, China (DiDi Chuxing) are leveraged. Results show that this process achieves 68%–82% and 53%–60% reduction of trip-level deadheading miles for the RideAustin and DiDi Chuxing sample operations respectively, under the assumption of unconstrained availability of short-term parking. Deadheading savings increase slightly as the maximum tolerable waiting time for the driver increases. Further, it is observed that significant deadhead savings per trip are possible, even when a small percent of the ridesourcing driver pool is provided with future ridesourcing demand information.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Spectroscopic Investigation into P(NDI2OD-T2) Charge Localization

P(NDI2OD-T2), commonly referred to as N2200, stands out as a promising electron-transporting (n-type) polymer for low-cost, flexible (photo)electrochemical applications due to its reversible two-electron reduction and high electron mobility. UV–vis spectroelectrochemistry in the tetrabutyl ammonium hexafluorophosphate/acetonitrile electrolyte shows two sets of chemically reversible redox signals in the cyclic voltammetry corresponding to the reduction of the neutral polymer film to polaronic and bipolaronic species. These electrochemical signatures suggest a distinct electronic reorganization upon reduction (polaron/bipolaron formation), highlighting the need for molecular-level insights into how charges are accommodated within the polymer backbone. While it has been previously hypothesized that charge predominantly localizes on the naphthalene diimide (NDI) unit during reductive charging, specific changes in atomic environments that confirm this localization have not been characterized in n-type polymers. Herein, we use near-edge X-ray absorption fine structure (NEXAFS) spectroscopy to probe electronic transitions in an electrochemically charged polymer to deduce charge localization. The O K-edge (1s) spectra exhibit two distinct π* peaks; the intensity of the lower-energy π* a peak that corresponds to an excitation to a largely localized carbonyl state decreases with reductive potentials relative to the higher-energy π* b peak. We corroborate this with Raman spectroscopy at different potentials, which shows a decrease in intensity on the C–C/C═C and C═O stretching bands of NDI as well as a red shift of the carbonyl band due to the formation of a polaron on the NDI. Additionally, new Raman active NDI signals associated with elongated C═O and C═C bonds are observed at lower energy during the formation of charged states. Together with theoretical calculations, these findings show that the injected charge spatially localizes on the NDI units and is dominantly distributed on the carbonyl groups. In conclusion, the combination of NEXAFS, optical and vibrational spectroscopies, and theoretical calculations is generalizable to other pi-conjugated polymers and can identify charge localization for the further development of organic semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Colloidal Semiconductor Nanocrystal Lasers and Laser Diodes

Lasers and optical amplifiers based on solution-processable materials have been long-desired devices for their compatibility with virtually any substrate, scalability, and ease of integration with on-chip photonics and electronics. These devices have been pursued across a wide range of materials including polymers, small molecules, perovskites, and chemically prepared colloidal semiconductor nanocrystals, also commonly referred to as colloidal quantum dots. The latter materials are especially attractive for implementing optical-gain media as in addition to being compatible with inexpensive and easily scalable chemical techniques, they offer multiple advantages derived from a zero-dimensional character of their electronic states. These include a size-tunable emission wavelength, low optical gain thresholds, and weak sensitivity of lasing characteristics to variations in temperature. Here we review the status of colloidal nanocrystal lasing devices, most recent advances in this field, outstanding challenges, and the ongoing progress toward technological viable devices including colloidal quantum dot laser diodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Role of Solvent Rearrangement on Mg2+ Solvation Structures in Dimethoxyethane Solutions Using Multimodal NMR Analysis

One of the main impediments faced for predicting important emergent properties of a multivalent electrolyte (such as conductivity and electrochemical stability) is the lack of quantitative analysis of ion-ion and ion-solvent interactions, which manifest in solvation structures and dynamics. In particular, the role of ion-solvent interactions is still unclear in cases where the strong electric field from multivalent cations can influence structural evolution of lower permittivity organic solvent molecules on solvation structure. These influences are commonly refered to as electrostriction pheonmena. Using quantitative 1H, 19F, 17O, and 25Mg NMR together with 19F nuclear spin relaxation and diffusion measurments, we find an unusual correlation between ion concentration and solvation structure of Mg(TFSI)2 salt in dimethoxyethane (DME) solution. The domiant solvation structure evolves from contact ion pairs (i.e. [Mg(TFSI)(DME)1-2]+) to fully solvated clusters (i.e. [Mg(DME)3]2+) as salt concentration increases or as temperature decreases. This transition is coupled to a phase separation, which we study here between 0.06 M and 0.36 M. Subsequent analysis is based on an explanation of the electrostriction phenomena and the competion between solvent molecules and TFSI anions for cation coordination.

Chen, Ying↗
DOE OSTI2023

Stability Criteria for Self-Propagating Reaction Waves in Co/Al Multilayers

The propagation of self-sustained formation reactions in sputter-deposited Co/Al multilayers is known to exhibit a design-dependent instability. Multilayers having thin bilayers (<55 nm period) exhibit stable propagating waves, whereas those with a larger period react unstably. The specific two-dimensional (2D) instability observed involves the transverse propagation of a band in front of a stalled front commonly referred to as a “spin band.” Previous finite-element studies have shown that these instabilities are thermodynamically driven by the forward conduction of heat away from the flame front. However, the magnitude of that loss is inherently tied to the bilayer design in traditional bimetallic multilayers, which couples any proposed stability criteria to a varying critical diffusion distance. Here, this work utilizes a recently developed class of materials known as “inert-mediated reactive multilayers” to decouple the thermodynamic and kinetic contributions to propagating wave stability by reducing the stored chemical energy density in normally stable bilayer designs. By depositing an inert product phase (B2-CoAl) within the mid-plane of Co and Al reactant layers, spin instabilities arise as a function of both diluted volume and critical diffusion distance. From there, a stability criterion is determined for Co/Al multilayers based on enthalpy loss from the reaction zone, and its physical significance is explored.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Neuromorphic intermediate representation: A unified instruction set for interoperable brain-inspired computing

Abstract Spiking neural networks and neuromorphic hardware platforms that simulate neuronal dynamics are getting wide attention and are being applied to many relevant problems using Machine Learning. Despite a well-established mathematical foundation for neural dynamics, there exists numerous software and hardware solutions and stacks whose variability makes it difficult to reproduce findings. Here, we establish a common reference frame for computations in digital neuromorphic systems, titled Neuromorphic Intermediate Representation (NIR). NIR defines a set of computational and composable model primitives as hybrid systems combining continuous-time dynamics and discrete events. By abstracting away assumptions around discretization and hardware constraints, NIR faithfully captures the computational model, while bridging differences between the evaluated implementation and the underlying mathematical formalism. NIR supports an unprecedented number of neuromorphic systems, which we demonstrate by reproducing three spiking neural network models of different complexity across 7 neuromorphic simulators and 4 digital hardware platforms. NIR decouples the development of neuromorphic hardware and software, enabling interoperability between platforms and improving accessibility to multiple neuromorphic technologies. We believe that NIR is a key next step in brain-inspired hardware-software co-evolution, enabling research towards the implementation of energy efficient computational principles of nervous systems. NIR is available atneuroir.org

Science & Technology - Other Topics↗
DOE OSTI2025

Ferroaxial density wave from intertwined charge and orbital order in rare-earth tritellurides

The discovery of the axial amplitude mode—commonly referred to as the Higgs mode—in charge density wave systems, such as rare-earth tritellurides, indicates the presence of a hidden order. A theoretical study proposed that this axial Higgs mode arises from a hidden orbital texture of the charge density wave, which produces a ferroaxial charge order. However, experimental evidence for the specific hidden order has been lacking. Here, we demonstrate a ferroaxial order of electronic origin throughout the rare-earth tritellurides. In ErTe 3 and HoTe 3 , which exhibit two distinct charge density waves with different ordering temperatures, a detailed investigation shows that the high-temperature charge order phase breaks translational, rotational and all vertical as well as diagonal mirror symmetries. Furthermore, this phase produces an axial Higgs mode and an axial electronic gap. By contrast, the low-temperature phase breaks only translational symmetry and gives rise to a scalar Higgs mode. Notably, both phases preserve the space inversion and time-reversal symmetries. These findings are consistent with a ferroaxial phase driven by coupled orbital and charge orders, highlighting the role of Higgs modes in revealing hidden orders in systems with intertwined charge density waves.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nodal hybridization in a two-dimensional heavy-fermion material

Metals with partially filled core atomic shells can form quasiparticles at a low temperature arising from the hybridization of the core level and conduction electrons. The thermodynamic and spectroscopic properties of these metals can be understood as those of a simple metal, but with a significant mass enhancement over the free electron mass—commonly referred to as heavy fermions. In most heavy-fermion materials, the hybridization is approximately isotropic in position and momentum space. However, a combination of low dimensionality and symmetry properties of the core-level wavefunctions can give rise to highly anisotropic electronic interactions with the conduction electrons. Here, in this study, we demonstrate anisotropic hybridization that vanishes along specific directions in momentum space—referred to as nodes—in a lanthanide-based two-dimensional van der Waals heavy-fermion compound, CeSiI. Quasiparticle interference measurements reveal a set of discrete hotspots with high spectral intensity on the Fermi surface. Theoretical modelling and comparison with the quasiparticle interference pattern of the non-heavy-fermion isostructural analogue LaSiI suggest that these features arise from an unconventional electron interaction involving hybridization nodes unique to CeSiI. As a result, the effective mass of the quasiparticles varies by orders of magnitude depending on their direction in momentum space.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Three-dimensional characterization of modifications in sapphire exposed to laser-induced damage using multimodal spectral microimaging

Sapphire (Al 2 O 3 ) is a commonly used dielectric material with many applications in lasers and optical systems. Owing to its high resistivity to laser induced damage, it is particularly suitable for use in high power laser systems. This work focuses on developing techniques to characterize material modifications in sapphire. These techniques were applied following localized laser induced ablation, commonly referred to as laser-damage, resulting from exposure to single 100-ps and 6-ns pulses. Measurements of fluorescence-based piezospectroscopy and confocal Raman microscopy were performed with spatial resolution on the order of 1 μ m. Raman microscopy reveals that the relaxation of material exposed to the rapid laser heating, elastic and viscoplastic deformation, melting, and solidification leads to the formation of a polycrystalline material phase. In addition, narrowband fluorescence lines, referred to as R 1 and R 2 , exhibit pressure-sensitive changes to their spectral profiles, allowing 3D internal stresses to be recorded with spatial resolution of the order of a few micrometers.

Laser-damage↗
DOE OSTI2022

Resonant anomalous X-ray reflectivity for revealing ion distributions near electrodes

Energy storage devices–batteries, for example–consist of an electrolyte sandwiched between two charged electrodes through which current can pass. The metal ion organization at the electrode–electrolyte interface, commonly referred to as the electric double layer, determines the efficiency and stability of the device. There are two major challenges with experimentally characterizing the metal ion distribution at the interface.

42 ENGINEERING↗
DOE OSTI2024

Security constrained optimal power shutoff for wildfire risk mitigation

Abstract Electric grid faults are increasingly the source of ignition for major wildfires. To reduce the likelihood of such ignitions in high risk situations, utilities use preemptive de‐energization of power lines, commonly referred to as Public Safety Power Shutoffs (PSPS). Besides raising challenging trade‐offs between power outages and wildfire safety, PSPS removes redundancy from the network at a time when component faults are likely to happen. This may leave the network particularly vulnerable to unexpected line faults that may occur while the PSPS is in place. Previous works have not explicitly considered the impacts of these outages. To address this gap, the Security Constrained Optimal Power Shutoff problem is proposed which uses post‐contingency security constraints to model the impact of unexpected line faults when planning a PSPS. This model enables, for the first time, the exploration of a wide range of trade‐offs between both wildfire risk and pre‐ and post‐contingency load shedding when designing PSPS plans, providing useful insights for utilities and policy makers considering different approaches to PSPS. The efficacy of the model is demonstrated using the EPRI 39‐bus system as a case study. The results highlight the potential risks of not considering security constraints when planning PSPS and show that incorporating security constraints into the PSPS design process improves the resilience of current PSPS plans.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗