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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Effects of Minor Alloying Elements and Impurities on Long-Range Ordering in Ni-Cr-Based Alloys

There is growing concern about long-range ordered Ni2Cr phase forming during thermal aging of Ni-Cr-based alloys (e.g., 690, 625), which leads to lattice contraction, hardening, and embrittlement, possibly limiting the service life of light water reactor components. The timespan when this phase transformation occurs can vary in orders of magnitude between model and commercial alloys and is likely related to the presence of major (e.g., Fe, Mo) and minor alloying elements (e.g., Ti, Si, Nb). These minor alloying elements have been hypothesized to bind with vacancies and therefore limit diffusion. Contrarily, impurities (e.g., P, S) are believed to enhance vacancy diffusion and accelerate the Ni2Cr phase transformation because of a vacancy drag mechanism. This study implements experimental isothermal aging of model Ni-Cr binary and Ni-Cr-X ternary alloys, where X is Ti, Si, Nb, and P to help understand how each minor alloying element affects the Ni2Cr phase transformation timeline. Synchrotron-based X-ray diffraction and hardness measurements are used to quantify the evolution of the Ni2Cr phase transformation through a variety of short aging times to identify the onset of long-range order. These experimental results are compared to first principles simulations from literature to understand the mechanism by which each element impacts vacancy diffusion and the formation of the long-range ordered phase, Ni2Cr.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Search for diphoton resonances in the 66 to 110 GeV mass range using pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search is performed for light, spin-0 bosons decaying into two photons in the 66 to 110 GeV mass range, using 140 fb −1 of proton-proton collisions at $\sqrt{s}$ = 13 TeV produced by the Large Hadron Collider and collected by the ATLAS detector. Multivariate analysis techniques are used to define event categories that improve the sensitivity to new resonances beyond the Standard Model. A model-independent search for a generic spin-0 particle and a model-dependent search for an additional low-mass Higgs boson are performed in the diphoton invariant mass spectrum. No significant excess is observed in either search. Mass-dependent upper limits at the 95% confidence level are set in the model-independent scenario on the fiducial cross-section times branching ratio into two photons in the range of 8 fb to 53 fb. Similarly, in the model-dependent scenario upper limits are set on the total cross-section times branching ratio into two photons as a function of the Higgs boson mass in the range of 19 fb to 102 fb.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Solute clustering in polycrystals: Unveiling the interplay of grain boundary junction and long-range solute attraction effects

Spectral analysis of local atomic environments has become a powerful tool for studying solute atom segregation and interactions at grain boundaries in nanocrystalline alloys. When applied to individual grain boundaries, the spectral analysis has shown that solute-solute interaction can be either attractive or repulsive, with long-range relative attraction enhancing the likelihood for solute atoms to begin clustering. In this article, we combine this analysis with a new grain-boundary structure descriptor based on grain-boundary atom coordination, to investigate the impact of grain-boundary junctions on solute atom segregation in polycrystals. Specifically, we systematically characterize the tendency of solute clusters to begin forming at various types of ordinary grain boundaries, triple junctions, and high-order junctions in Ag polycrystals containing either Ni or Cu solute atoms. Our findings demonstrate that the formation of solute clusters at grain boundaries is primarily driven by long-range relative solute attraction, rather than short-range solute-solute interactions. Furthermore, this effect is most pronounced near grain-boundary junctions. Our study highlights the multiscale nature of solute segregation at crystalline interfaces and provides new insights into the complex phenomena governing heterogeneous solute segregation in grain-boundary networks.

Grain-boundary junction↗
DOE OSTI2026

Explainable machine learning reveals that local structural motifs encode the thermodynamic state across the CuZr metallic glass-forming range

Metallic glasses derive their properties from the statistics of local atomic motifs rather than from long-range order, yet a quantitative, chemistry-specific link between motif populations and the underlying glassy state has remained elusive. In this work we combine large-scale molecular dynamics, Voronoi tessellation, deep neural networks, and SHapley Additive exPlanations (SHAP) to identify which local structural motifs define the glassy state of Cu—Zr metallic glasses. A dataset of 17,180 atomistic configurations spanning ten compositions (Cu 20 Zr 80 –Cu 80 Zr 20 ) and four quench rates (10 9 –10 12 K/s) is used to train a feed-forward neural network that regresses temperature across the 50–2000 K liquid–supercooled–glass range, achieving a mean absolute error of 19.89 K and R 2 = 0.9974, confirming that the local structural state is faithfully encoded in motif-level structure. SHAP analysis then reveals that a tightly coupled near-icosahedral family of motifs (coordination numbers (CN) 11–13, including the full icosahedron 001200 and its single-atom-perturbation sibling 10930) collectively encodes the thermodynamic state of the system across the full glass-forming range. The CN = 11–13 ordered members carry negative SHAP values at high populations, tracking the most deeply-quenched configurations, while 10930 shows the reversed signature consistent with its role as a soft-spot host whose population shrinks as the icosahedral network deepens. The analysis demonstrates that explainable machine learning can isolate the minimal motif vocabulary defining the glassy state and recovers the near-icosahedral building blocks previously identified by data-driven analyses of Cu—Zr. The approach provides a general, chemistry-specific route for characterizing the structural state of disordered materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Automated workflow for non-empirical Wannier-localized optimal tuning of range-separated hybrid functionals

Here, we introduce an automated workflow for generating non-empirical Wannier-localized optimally-tuned screened range-separated hybrid (WOT-SRSH) functionals. WOT-SRSH functionals have been shown to yield highly accurate fundamental band gaps, band structures, and optical spectra for bulk and 2D semiconductors and insulators. Our workflow automatically and efficiently determines the WOT-SRSH functional parameters for a given crystal structure and composition, approximately enforcing the correct screened long-range Coulomb interaction and an ionization potential ansatz. In contrast to previous manual tuning approaches, our tuning procedure relies on a new search algorithm that only requires a few hybrid functional calculations with minimal user input. We demonstrate our workflow on 23 previously studied semiconductors and insulators, reporting the same high level of accuracy. By automating the tuning process and improving its computational efficiency, the approach outlined here enables applications of the WOT-SRSH functional to compute spectroscopic and optoelectronic properties for a wide range of materials.

Gant, Stephen E. [University of California, Berkel↗
DOE OSTI2024

Properties and Autoignition Reactivity of Diesel Boiling Range Ethers Produced from Guerbet Alcohols

We examine the properties of diesel boiling range ethers made from coupling of alcohols produced by oligomerization of ethanol (Guerbet alcohols) for their utility as low-carbon liquid fuel blendstocks. Basic properties of boiling point, flash point, freezing point, density and viscosity are well suited for blending into diesel fuels. For the mixture of ethers the lightest component, di-n-butyl ether, can be present at up to 20 vol% while still having adequately high flashpoint for safe handling. Soot formation tendency (as yield sooting index) is well below that of conventional diesel. The ethers have similar compatibility with elastomers as conventional diesel, based on Hansen solubility parameter analysis. Oxidation stability was assessed for 30 vol% blends of individual ethers in a conventional diesel fuel using a long-term storage test. Over 6 weeks we observed no formation of peroxides or degradation. n-alkyl ethers with carbon number of 8 or higher have cetane number over 100, which is outside the defined range of cetane number, while branched ethers are over 70. The ethers also blend antagonistically into conventional diesel for cetane number, meaning that the blend cetane value is lower than predicted based on a linear by volume, mass, or mole model. We show that aromatics and naphthenes likely act as radical scavengers to slow or shut down autoignition of the highly reactive ethers at low to medium blend levels. Overall, diesel boiling range ethers show significant promise as high quality low-net carbon diesel blendstocks.

09 BIOMASS FUELS↗
DOE OSTI2026

Temporal and spatial separations between spin glass and short-range order

Broken-symmetry-induced order parameters account for many phenomena in physics. For spin glasses, this framework dictates the theoretical construction, whereas experiments have only established dynamical behaviors but not the physical entity. Experimental techniques have limitations when the spin glass is probed as an isolated state. Here, we create an evolution from a long-range order using well-controlled non-magnetic substitution on a sublattice. Neutron magnetic diffuse scattering of pico-second timescale reveals that the dynamics of short- and long-range order formation are not affected by disorder, but their spatial ranges are. Across all specimens, the inflection point of spin correlation length’s temperature dependence fully matches with the peak in heat capacity, while spin glass can freeze at millisecond timescale either above or below this characteristic temperature of spin-order formation. Our results identify the spin glass as single, uncorrelated spins at domain walls between spin clusters, and an uncorrelated coexistence of the two.

Dronova, Margarita G [Okinawa Institute of Science↗
DOE OSTI2025

Inclusive studies of two- and three-nucleon short-range correlations in 3 H and 3 He

Inclusive electron scattering at carefully chosen kinematics can isolate scattering from the high-momentum nucleons in short-range correlations (SRCs). SRCs are produced by the hard, short-distance interactions of nucleons in the nucleus, and because the two-nucleon (2N) SRCs arise from the same N-N interaction in all nuclei, the cross section in the SRC-dominated regime is identical up to an overall scaling factor. This scaling behavior has been used to identify SRC dominance and to measure the contribution of SRCs in a wide range of nuclei. We examine this scaling behavior over a range of momentum transfers using new data on 2 H, 3 H, and 3 He, and find an expanded scaling region compared to heavy nuclei. Motivated by this improved scaling, we examine the 3 H and 3 He data in kinematics where three-nucleon SRCs may play an important role. The data for the largest struck nucleon momenta are consistent with isolation of scattering from three-nucleon SRCs, and suggest that the very highest momentum nucleons in 3 He have a nearly isospin-independent momentum configuration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Machine Learning a Simple Interpretable Short-Range Potential for Silica

A wide array of models, spanning from computationally expensive ab initio methods to a spectrum of force-field approaches, have been developed and employed to probe silica polymorphs and understand growth processes and atomic-level dynamical transitions in silica. However, the quest for a model capable of making accurate predictions with high computational efficiency for various silica polymorphs is still ongoing. Recent developments in short-range machine-learned models, such as GAP and NNPScan, have shown promise in providing reasonable descriptions of silica, but their computational cost remains high compared to force fields such as BKS which are based on simple interpretable functional forms. Here, in this study, we build on the recent success of our reinforcement learning (RL) workflow to derive a new set of optimal parameters for a promising short-range BKS-based model proposed by Soules. We use RL to navigate the eight-dimensional parameter space of the Soules potential using an experimental training data set that includes both local and global structural features from approximately 21 experimentally realized silica polymorphs, including high density phases and porous zeolites. We compare the performance of our machine-learned ML-Soules model with other high quality models including our recent machine-learned parametrization of BKS (ML-BKS), a machine-learned potential (GAP), as well as predictions of ab initio calculations with the highly fidelity SCAN functional. The ML-Soules accurately captures the relative energetic ordering of various polymorphs as well as their structural features at a significantly reduced computational expense. The ML-Soules model also reasonably captures the structure, density, and elastic constants of quartz, as well as metastable silica polymorphs. We further discuss the limitations of the Soules functional form and propose potential enhancements, including the incorporation of additional three-body terms and/or the utilization of different short-ranged functional forms to achieve greater accuracy for both global and local features in the modeling of silica while retaining low computational cost.

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

Data-Driven Recommendation of Optimal Tuning Scheme for Range-Separated Hybrid Functionals in Solution-Phase UV/Vis Absorption Energy Prediction

Time-dependent density functional theory (TDDFT) combined with range-separated hybrid (RSH) functionals and a tuned range-separation parameter γ offers a computationally economical approach for high-throughput excited- state property predictions. The γ-tuning procedure in the gas phase is well established. However, no agreement on the best γ- tuning procedure has been made when considering the solvent effect with implicit solvent models like the polarizable continuum model (PCM). To answer that question, this study created a diverse dataset with 937 molecules with experimental solutionphase UV/vis absorption spectra. Three γ-tuning methods, the gasphase γ-tuning (GPγT), the partial vertical γ-tuning (PVγT), and the strict vertical γ-tuning (SVγT), were evaluated for the ωPBEh functional over the entire dataset. Additional benchmarks are done for the optimally tuned screened range-separated hybrid combined with the PCM approach (SRSH-PCM) and the solvation-mediated tuning procedure (sol-med-OT). Our findings revealed that the optimal γ-values obtained by the PVγT and the SVγT are significantly smaller than the GPγT. This trend holds consistently across all molecules in our dataset, and we explained the origin of this phenomenon. TDDFT calculations with PVγTand SVγT-tuned γ-values and default global Fock exchange fraction achieve superior performance compared to those using GPγTtuned or default γ and slightly outperform SRSH-PCM and sol-med-OT with similar or lesser computational cost. Furthermore, we found that the smaller γ-values from SVγT captured the expected 1/(εR) asymptotic behavior in the solution phase, resulting in accurate prediction of solution-phase CT excitations, consistent with the screened asymptote behavior encoded in SRSH-PCM. These results show that SVγT is the best scheme for high-throughput UV/vis absorption spectrum calculations using the ωPBEh functional from a data-driven perspective.

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

Highly Elliptic Circular Dichroism of Copper Aspartate One-Dimensional Nanostructures across the Ultraviolet to Terahertz Ranges

Since the discovery of chirality, circular dichroism (CD) of mirror-asymmetric molecules has been studied across the ultraviolet, visible, and near-infrared ranges. Recently, chiroptical activity studies have expanded to the terahertz (THz) range, where resonance peaks originate from collective vibrations of tens and hundreds of atoms. Here, in this study, we synthesized Cu 2+ coordination complexes with L- and D-aspartic acid as nanowires and nanorods and characterized their chiroptical activity across multiple frequency ranges. Both chiral nanostructures exhibit strong electronic CD (ECD), primarily from Cu 2+ d-d transitions, while vibrational CD (VCD) spectra show sharp C=O, C–H, and O–H vibronic peaks, indicating higher atomic defect densities in nanorods than nanowires. Although THz CD (TCD) spectra are broad, they exhibit ∼1000× greater ellipticity than ECD and VCD, perhaps warranting previous references to circular dichroism of nanostructures as giant. Comparative TCD analysis highlights strong chiral phonon sensitivity, underscoring its potential for probing defect densities and structural changes for various chiral nanostructures and (bio)crystals.

THz spectroscopy↗
DOE OSTI2025

Solvent-Free Dimerization of Isoprene at Ambient Temperature: A Green Route to Biofuel-Range Hydrocarbons

In order to achieve a net-zero carbon footprint by 2050, the global aviation industry must reduce its dependence on fossil fuels. In this regard, there is a global challenge to produce sufficient sustainable aviation fuel (SAF) from renewable sources. Isoprene is an intermediate molecule that can be derived from multiple biomass-based or biosynthetic routes. Here, in this work, we report a green route for the catalytic conversion of isoprene to hydrocarbons that are suitable for aviation fuel. By using an Amberlyst-15 catalyst without metal loading at ambient temperature (19–23 °C), as well as 40 °C, 50 °C, and 60 °C, isoprene was converted into olefinic precursors for SAF and/or blending with conventional aviation fuels. Specifically, at ambient temperature, the process achieved approximately 70 wt % conversion of isoprene with over 50 mol % carbon selectivity toward the aviation fuel range. The resulting SAF-range hydrocarbons were composed of iso-alkenes, branched olefinic monocyclic compounds, and bicyclic compounds, covering a wide range of aviation fuel components. Our work demonstrates, for the first time, the formation of diverse hydrocarbon families for SAF and/or aviation fuel blending at ambient temperature from isoprene.

09 BIOMASS FUELS↗
DOE OSTI2025

Reversible long-range domain wall motion in an improper ferroelectric

Reversible ferroelectric domain wall movements beyond the 10 nm range associated with Rayleigh behavior are usually restricted to specific defect-engineered systems. Here, we demonstrate that such long-range movements naturally occur in the improper ferroelectric ErMnO 3 during electric-field-cycling. We study the electric-field-driven motion of domain walls, showing that they readily return to their initial position after having traveled distances exceeding 250 nm. By applying switching spectroscopy band-excitation piezoresponse force microscopy, we track the domain wall movement with nanometric spatial precision and analyze the local switching behavior. Phase field simulations show that the reversible long-range motion is intrinsic to the hexagonal manganites, linking it to their improper ferroelectricity and topologically protected structural vortex lines, which serve as anchor point for the ferroelectric domain walls. Our results give new insight into the local dynamics of domain walls in improper ferroelectrics and demonstrate the possibility to reversibly displace domain walls over much larger distances than commonly expected for ferroelectric systems in their pristine state, ensuring predictable device behavior for applications such as tunable capacitors or sensors.

Zahn, Manuel [Norwegian Univ. of Science and Techn↗
DOE OSTI2025

Long-range optical coupling with epsilon-near-zero materials

Long-range resonant quantum tunneling of electrons happens across potential barriers when the wavefunction interferes constructively outside the barrier. Here we demonstrate an analogy in optical systems based on epsilon-near-zero materials, achieving phase-modulated, long-range optical interactions between transparent semiconducting oxide layers beyond the evanescent photonic coupling. Distinct from weak thin-film interference, intense electromagnetic fields confined within the epsilon-near-zero thin films show anti-correlated intensity oscillations as a function of interlayer separation up to hundreds of microns. The oscillatory, anti-correlated electromagnetic field intensities were probed by second harmonic generation from wedged indium tin oxide multilayers. Such a system that hosts subwavelength mode footprint and simultaneously long-range radiative coupling offers prospects for long-distance optical communication, large-scale photonic circuits, and hybrid quantum photonic systems.

Wang, Danqing [Fudan University, Shanghai (China);↗
DOE OSTI2026

Revealing short- and long-range Li-ion diffusion in Li 2 MnO 3 from finite-temperature dynamical mean field theory

Li 2 MnO 3 is a key component of Li-excess layered cathodes of the form (1 − x), LiMO 2 + x, Li 2 MnO 3 (M = Mn, Ni, Co, …), yet its role in setting Li-ion transport limitations remains under debate. Here, in this study, we combine DFT+U, finite-temperature DFT+DMFT with a continuous-time quantum Monte Carlo impurity solver, and nudged-elastic-band (NEB) calculations to study Li + migration in paramagnetic Li 2 MnO 3 in the presence of a single Li vacancy. Evaluating DMFT total energies along the DFT+U NEB geometries reveals that dynamical correlations strongly renormalize the lowest-barrier processes, reducing the activation energies to E a = 0.18 eV for the shortest-range hop and E a = 0.50 eV for the next-lowest (transport-controlling) step. The 0.18 eV barrier quantitatively reproduces the short-range activation energy from µ+SR, while the 0.50 eV barrier is consistent with the long-range transport scale extracted from ac-impedance measurements. This single-vacancy, paramagnetic DMFT description thus provides a unified interpretation of local and macroscopic probes without invoking clustered vacancy configurations or strong extrinsic disorder, consistent with nearly stoichiometric Li 2 MnO 3 powders. More broadly, our results highlight finite-temperature dynamical correlations as an essential ingredient for predicting ionic migration energetics in correlated oxide electrodes.

Lee, Alex Taekyung [University of Illinois, Chicag↗
DOE OSTI2025

RANGE: A robust adaptive nature-inspired global explorer of potential energy surfaces

With the growing demand for realistic representations of chemical structures and the advent of exascale computing, the intelligent sampling of potential energy surfaces and efficient identification of global minima have become more essential but also more feasible. Building on prior studies demonstrating the efficiency of the Artificial Bee Colony (ABC) swarm intelligence algorithm, we report a hybrid metaheuristic framework that integrates the adaptive exploration capabilities of ABC coupled with the exploitation strengths of genetic algorithms (GA) in a scalable, Python-based implementation. The resulting tool, RANGE (Robust Adaptive Nature-inspired Global Explorer), provides seamless interfaces to multiple potential energy evaluators, either directly or via widely used Python libraries, and is designed for high-performance computing environments. We describe the implementation details of RANGE and evaluate its performance, relative to ABC- or GA-alone based algorithms, on a variety of chemical systems, including molecular clusters and heterogeneous surfaces. In conclusion, our results demonstrate RANGE’s efficiency, robustness, and broad applicability in addressing challenging global optimization problems in computational chemistry and materials science.

Algorithms and data structure↗
DOE OSTI2026

Burn mode signatures enabled by high dynamic range fusion reaction history

The evolution of the fusion burn of a compressed inertial confinement fusion (ICF) implosion gives information about the evolution of the temperature, mass, and volume of the hot spot. Currently, the fusion reaction history has been measured with about a decade of dynamic range, giving information about just the peak of the fusion burn. There are proposals for extending the dynamic range to 1000×, measuring the rising edge of the burn earlier in time. Using fusion hot spot theory and a set of ICF simulations, we identify and categorize different stages of fusion burn and what signatures could be measured. For ice layered implosions, the details, conditions, and dynamics of the fusion burn propagation could be observed. For double shell and OMEGA scale implosions, the evolution of the final compression and rebounding shock before ignition could be observed. Higher dynamic range expands investigation into the logarithmic derivative, α, as a signature of various mechanisms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Annihilation-limited long-range exciton transport in high-mobility conjugated copolymer films

A combination of ultrafast, long-range, and low-loss excitation energy transfer from the photoreceptor location to a functionally active site is essential for cost-effective polymeric semiconductors. Delocalized electronic wavefunctions along π-conjugated polymer (CP) backbone can enable efficient intrachain transport, while interchain transport is generally thought slow and lossy due to weak chain–chain interactions. In contrast to the conventional strategy of mitigating structural disorder, amorphous layers of rigid CPs, exemplified by highly planar poly(indacenodithiophene-co-benzothiadiazole) (IDT-BT) donor-accepter copolymer, exhibit trap-free transistor performance and charge-carrier mobilities similar to amorphous silicon. Here, we report long-range exciton transport in HJ -aggregated IDTBT thin-film, in which the competing exciton transport and exciton–exciton annihilation (EEA) dynamics are spectroscopically separated using a phase-cycling-based scheme and shown to depart from the classical diffusion-limited and strong-coupling regime. In the thin film, we find an annihilation-limited mechanism with ≪100% per-encounter annihilation probability, facilitating the minimization of EEA-induced excitation losses. In contrast, excitons on isolated IDTBT chains diffuse over 350 nm with 0.56 cm 2 s −1 diffusivity, before eventually annihilating with unit probability on first contact. We complement the pump–probe studies with temperature-dependent photocurrent and EEA measurements from 295 K to 77 K and find a remarkable correspondence of annihilation rate and photocurrent activation energies in the 140 K to 295 K temperature range.

Shi, Yuping (ORCID:0000000318289415)↗