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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Gamma-Ray Bursts and Kilonovae from the Accretion-induced Collapse of White Dwarfs

Abstract We present the first seconds-long 2D general relativistic neutrino magnetohydrodynamic simulations of accretion-induced collapse (AIC) in rapidly rotating, strongly magnetized white dwarfs (WDs), which might originate as remnants of double-WD mergers. This study examines extreme combinations of magnetic fields and rotation rates, motivated both by the need to address the limitations of 2D axisymmetric simulations and to explore the physics of AIC under rare conditions that, while yet to be observationally confirmed, may be consistent with current theoretical models and account for unusual events. Under these assumptions, our results demonstrate that, if realizable, such systems can generate relativistic jets and neutron-rich outflows with properties consistent with long gamma-ray bursts (LGRBs) accompanied by kilonovae, such as GRB 211211A and GRB 230307A. These findings highlight the potential role of AIC in heavy r -process element production and offer a framework for understanding rare LGRBs associated with kilonova emission. Longer-duration 3D simulations are needed to fully capture magnetic field amplification, resolve instabilities, and determine the fate of the energy retained by the magnetar at the end of the simulations.

Cheong 張, Patrick Chi-Kit 志杰 (ORCID:00000003144933↗
DOE OSTI2026

Corundum Discovered by SuperCam and the Perseverance Rover at Jezero Crater, Mars

Minerals provide clues to the type of geologic environments in which they form. The primary types of minerals that have been identified on Mars indicate a history dominated by volcanism followed by interaction with water. However, other minerals are sometimes found. Here we present results from the SuperCam instrument on the Perseverance rover in which the mineral corundum (α-Al2O3) has been identified using a technique called time-resolved luminescence spectroscopy. Corundum has a unique light-emitting (luminescence) feature based on two well-known peaks as well as the time it takes for this light to fade after being excited by a laser, which is referred to as the lifetime. Corundum forms in specific environments that are enriched in aluminum and depleted in silicon and have been subjected to high temperature and pressure. Such places include deep subsurface magmas or shallower locations that have been exposed to high temperature through tectonic processes or meteorite impacts. Given their small size, association with a mineral called plagioclase, and location on the heavily impacted crater rim, we propose that these corundum minerals formed through impact processes.

58 GEOSCIENCES↗
DOE OSTI2024

High-speed X-ray imaging of droplet-powder interaction in binder jet additive manufacturing

Binder jetting (BJ) is an additive manufacturing process that uses a powder feedstock in a layer wise process to print parts by selectively depositing a liquid binder into the powder bed using inkjet technology. This study presents findings from high-speed synchrotron imaging of binder droplet-interaction during the BJ printing process. A custom laboratory-scale BJ test platform was used for testing which enabled control of relevant process parameters including powder material, print geometry, spacing between droplets, powder bed density, and powder moisture content. Powder ejection was observed above the powder bed surface and powder relocation due to droplet impact was observed below the powder bed surface. Powder relocation was observed to be sensitive to powder material, powder bed density, powder bed moisture, droplet spacing, and print geometry. Increasing powder bed density was found to increase particle ejection velocity but reduce the total number of particles ejected. Process parameters that increase binder / moisture content in the powder bed were found to reduce powder ejection. The number of ejected powder particles was reduced for lower droplet spacings. Both powder ejection and powder relocation below the powder bed were reduced by treating the surface of the powder bed with a water/triethylene glycol (TEG) mixture before printing. In conclusion, results from this study help to build understanding of the physical mechanisms in the BJ printing process that may contribute to formation of defects observed in final parts.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Studies of Cherenkov photon production in PbF 2 crystals using proton beams at Fermilab

Future lepton colliders such as the FCC-ee, CEPC, ILC, or a muon collider will collect large data samples that allow precision physics studies with unprecedented accuracy, especially when the data is collected by innovative state-of-the-art detectors. An electromagnetic calorimeter based on scintillating crystals, designed to separately record Cherenkov and scintillation light, can achieve precision measurements of electrons and photons without sacrificing jet energy resolution, given adequate light collection efficiency and separation. This paper presents initial measurements from a program aimed at developing such a calorimeter system for future colliders. Finally, we focus on using PbF 2 crystals to enhance the understanding of Cherenkov light collection, marking the first step in this endeavor.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Porous reaction-bonded silicon nitride: Size effects for pressureless nitriding of binder jet additively manufactured silicon

The direct nitridation of binder jet additively manufactured silicon to produce porous reaction-bonded silicon nitride was explored to determine the maximum thickness of the sample that could be converted to >99% silicon nitride. The maximum thickness that could be nitrided was investigated by nitriding cubes of increasing physical size on the millimeter scale. Highly porous samples with high conversion ( > 99%) to silicon nitride were achieved in cubes with 35 mm edge length. It was shown that the silicon nitride phase content changes with increasing sample size.

Aguirre, Trevor [ORNL] (ORCID:0000000281469630)↗
DOE OSTI2024

Helium plasma operations on ASDEX Upgrade and JET in support of the non-nuclear phases of ITER

For its initial operational phase, ITER has until recently considered using non-nuclear hydrogen (H) or helium (He) plasmas to keep nuclear activation at low levels. To this end, the Tokamak Exploitation Task Force of the EUROfusion Consortium carried out dedicated experimental campaigns in He on the ASDEX Upgrade (AUG) and JET tokamaks in 2022, with particular emphasis put on the ELMy H-mode operation and plasma-wall interaction processes as well as comparison to H or deuterium (D) plasmas. Both in pure He and mixed He + H plasmas, H-mode operation could be reached but more effort was needed to obtain a stable plasma scenario than in H or D. Even if the power threshold for the LH transition was lower in He, entering the type-I ELMy regime appeared to require equally much or even more heating power than in H. Suppression of ELMs by resonant magnetic perturbations was studied on AUG but was only possible in plasmas with a He content below 19%; the reason for this unexpected behaviour remains still unclear and various theoretical approaches are being pursued to properly understand the physics behind ELM suppression. The erosion rates of tungsten (W) plasma-facing components were an order of magnitude larger than what has been reported in hydrogenic plasmas, which can be attributed to the prominent role of He 2+ ions in the plasma. For the first time, the formation of nanoscale structures (W fuzz) was unambiguously demonstrated in H-mode He plasmas on AUG. However, no direct evidence of fuzz creation on JET was obtained despite the main conditions for its occurrence being met. The reason could be a delicate balance between W erosion by ELMs, competition between the growth and annealing of the fuzz, and coverage of the surface with co-deposits.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Conditional deep generative models for simultaneous simulation and reconstruction of entire events

We extend the particle-flow neural assisted simulations (arnassus) framework of fast simulation and reconstruction to entire collider events. In particular, we use two generative artificial intelligence tools, continuous normalizing flows and diffusion models, to create a set of reconstructed particle-flow objects conditioned on truth-level particles from CMS Open Simulations. While previous work focused on jets, our updated methods now can accommodate all particle-flow objects in an event along with particle-level attributes like particle type and production vertex coordinates. This approach is fully automated, entirely written in Python, and GPU-compatible. Using a variety of physics processes at the LHC, we show that the extended arnassus is able to generalize beyond the training dataset and outperforms the standard, public tool elphes.

Dreyer, Etienne [Weizmann Institute of Science, Re↗
DOE OSTI2025

JENSA: Past, present, and future

Nuclear reaction studies rely on three main physical components: the beam of nuclei provided by the facility, the detector systems used to measure the outgoing particles of interest, and the target. Target fabrication is thus a critical aspect of studying the reactions that power stars and probe the evolution of nuclear structure. The Jet Experiments in Nuclear Structure and Astrophysics (JENSA) gas jet target is the most dense helium jet target for rare isotope beam reaction studies in the world, providing targets of gaseous elements such as helium, nitrogen, and neon. A brief overview of the design and operation of JENSA, including commissioning and recent science experiments, and a discussion the future of JENSA coupled to the dedicated recoil separator SECAR, are presented.

Chipps, Kelly [ORNL] (ORCID:0000000330501298)↗
DOE OSTI2025

Measurement of photonuclear jet production in ultraperipheral Pb + Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV with the ATLAS detector

In ultrarelativistic heavy ion collisions at the LHC, each nucleus acts a sources of high-energy real photons that can scatter off the opposing nucleus in ultraperipheral photonuclear (𝛾 + 𝐴) collisions. Hard scattering processes initiated by the photons in such collisions provide a novel method for probing nuclear parton distributions in a kinematic region not easily accessible to other measurements. ATLAS has measured production of dijet and multijet final states in ultraperipheral Pb + Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV using a dataset recorded in 2018 with an integrated luminosity of 1.72 nb −1 . Photonuclear final states are selected by requiring a rapidity gap in the photon direction; this selects events where one of the outgoing nuclei remains intact. Jets are reconstructed using the anti-𝑘 t algorithm with radius parameter, 𝑅 = 0.4. Triple-differential cross sections, unfolded for detector response, are measured and presented using two sets of kinematic variables. The first set consists of the total transverse momentum (𝐻 T ), rapidity, and mass of the jet system. The second set uses 𝐻 T and particle-level nuclear and photon parton momentum fractions, 𝑥 A and 𝑧 𝛾 , respectively. The results are compared with leading-order perturbative QCD calculations of photonuclear jet production cross sections, where all leading order predictions using existing fits fall below the data in the shadowing region. More detailed theoretical comparisons will allow these results to strongly constrain nuclear parton distributions, and these data provide results from the LHC directly comparable to early physics results at the planned Electron-Ion Collider.

Parton distribution functions↗
DOE OSTI2025

Universality in the Near-Side Energy-Energy Correlator

We investigate the energy-energy correlator (EEC) of hadrons produced on the same side in e + e − annihilation or in leading jets in p p collisions. We observe a remarkable universality of the correlator. Using a nonperturbative transverse momentum dependent (TMD) fragmentation function to model the transition from the “free-hadron” region to the perturbative collinear region, we are able to describe the near-side shapes and peaks over a wide range of energy for both the e + e − annihilation and the p p jet substructure measurements in terms of just two parameters. We present further predictions for the ratio of the projected three-point energy correlator to the EEC. The excellent agreement between our calculations and the experimental data may provide new insights into the role of nonperturbative physics for EECs, and suggests the possibility of exploring nonperturbative TMDs using theoretical tools developed for the energy correlators. Published by the American Physical Society 2025

Liu, Xiaohui (ORCID:0000000277011205)↗
DOE OSTI2026

Identified charged hadron production in Au+Au collisions at $\sqrt{s_{NN}}$ = 54.4 GeV with the STAR detector

Here, we present results on the production of 𝜋±, 𝐾±, 𝑝, and $\bar{𝑝}$ in Au+Au collisions at $\sqrt{𝑠_{N⁢N}}$ = 54.4~GeV using the STAR detector at RHIC, at mid-rapidity (|𝑦|< 0.1). Invariant yields of these particles as a function of transverse momentum are shown. We determine bulk properties such as integrated particle yields (𝑑 ⁢𝑁 /𝑑 ⁢𝑦 ), mean transverse momentum (⟨𝑝 𝑇 ⟩), particle ratios, which provide insight into the particle production mechanisms. Additionally, the kinetic freeze-out parameters (𝑇 kin and ⟨𝛽 𝑇 ⟩), which provide information about the dynamics of the system at the time of freeze-out, are obtained. The Bjorken energy density (𝜖 𝐵⁢𝐽 ), which gives an estimate of the energy density in the central rapidity region of the collision zone at the formation time 𝜏, is calculated and presented as a function of multiplicity for various energies. The results are compared with those from the models such as A Multi-Phase Transport (AMPT) and Heavy Ion Jet INteraction Generator (HIJING) for further insights.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Comments on the paper “Eliminating beam-induced depolarizing effects in the hydrogen jet target for high-precision proton beam polarimetry at the Electron-Ion Collider” (Part I)

A critical review of the methodology used in F. Rathmann et al., Phys. Rev. Accel. Beams 29, 021001 (2026), to evaluate beam-induced depolarization of the Atomic Polarized Hydrogen Gas Jet (HJET) target at the Electron–Ion Collider (EIC) is presented. It is shown that several key assumptions underlying that analysis—including the introduction of a photon emission threshold, the application of Fermi’s Golden Rule to coherent hyperfine transitions, the interpretation of power broadening as a physical linewidth increase, and the treatment of spatial magnetic fields—are either incorrect or internally inconsistent. As a consequence, the predicted large depolarization effects are demonstrated to be artifacts of the adopted methodology rather than genuine physical phenomena. A consistent quantum-mechanical treatment based on the time-dependent Schrödinger equation shows that beam-induced depolarization probabilities at the EIC are negligibly small.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Dimorphos’s Material Properties and Estimates of Crater Size from the DART Impact

On 2022 September 26, the Double Asteroid Redirection Test (DART) spacecraft intentionally collided with Dimorphos, the moon of the binary asteroid system 65803 Didymos. This collision provided the first full-scale test of a kinetic impactor for planetary defense. Images from DART’s DRACO camera revealed Dimorphos to be an oblate spheroid covered in boulders of varying sizes and shapes. Very little was known about Dimorphos prior to DART’s impact, including its shape, structure, and material properties. Approach observations and those following the DART impact have provided crucial knowledge that narrows the parameter space relevant to modeling the impact into Dimorphos. Here we present the results of a suite of hydrocode simulations of the DART impact on Dimorphos. Despite remaining uncertainties, initial models of DART’s kinetic impact provide important information about the results of DART (e.g., potential crater size and morphology, ejecta mass) and the properties of Dimorphos. Simulations here suggest that Dimorphos has near-surface strength ranging from a few Pascals to tens of kPa, which corresponds to crater sizes of ~40–60 m. Simulated crater sizes provide a crucial comparison metric for the European Space Agency Hera mission when it arrives at the Didymos system. Hera’s measurement of crater size in combination with measurement of Dimorphos’s mass will allow us to assess our simulations and provide the information needed to make the DART impact experiment both the first test of a planetary defense mitigation mission and the first full-scale planetary defense simulation validation exercise.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Cycloalkane-rich sustainable aviation fuel production via hydrotreating lignocellulosic biomass-derived catalytic fast pyrolysis oils

Sustainable aviation fuel (SAF) produced from lignocellulosic biomass is emerging as an ideal alternative to conventional jet fuel for aviation sector decarbonization. Catalytic fast pyrolysis (CFP) can convert lignocellulosic biomass into relatively stable bio-oil that can be selectively transformed to various transportation fuels through hydroprocessing under conditions of different severities. In this contribution, two CFP oils produced from pine-based feedstocks over different types of catalysts (i.e., ZSM-5 and Pt/TiO 2 catalysts) were hydrotreated at 125 bar in a non-isothermal process with a maximum temperature of 385 °C over a sulfided NiMo/Al 2 O 3 catalyst to produce SAF with high cycloalkane concentrations of 89–92 wt%. Cycloalkanes are an important component of jet fuel with advantageous fuel properties, such as high energy density, low sooting, and potential for replacing aromatic hydrocarbons to provide good seal swelling properties. The hydrotreating process successfully converted 91–92% of the biogenic carbon in the CFP oil intermediates to liquid-phase hydrotreated products. Through distillation, 39–40 wt% of the hydrotreated oils were collected in the jet-fuel range as SAF fractions. The rest of the hydrotreated product could be valorized as fuels (e.g., diesel) or chemicals. The SAF fractions with oxygen contents below the detection limit (<0.01 wt%) met ASTM D7566 finished fuel blend and D4054 Tier 1 specifications with respect to density, lower heating value (LHV), volatility, flash point, and freeze point. These results indicate hydrotreating lignocellulosic biomass-derived CFP oil as a promising pathway to produce high-quality SAF rich in cycloalkanes. Continued research is required to increase the SAF yield by process improvements, such as increased CFP oil yields, and an enhanced production of SAF-range molecules via e.g., cracking of high-molecular weight compounds either during CFP or hydrotreating, as well as evaluation of a broader range of jet fuel properties and performance requirements.

09 BIOMASS FUELS↗
DOE OSTI2026

Performance of modern color decompositions for standard candle LHC tree amplitudes

In the last decade, developments of matrix element and phase space generators have focused on providing good efficiency and maximal flexibility and automation for a wide range of physical processes. However, as recent studies have shown, they are a major bottleneck in the established Monte Carlo event generator toolchains. With the advent of the HL-LHC and ever rising precision requirements, future developments will need to focus on computational performance, especially at intermediate to large jet multiplicities. We present the novel BlockGen family of fast matrix element algorithms that are amenable for GPU acceleration, making use of modern, minimal color decompositions. Moreover, we discuss the performance achieved for standard candle processes such as V +jets and tt̄+jets production.

Bothmann, E. [Gottingen U.]↗
DOE OSTI2026

The quantum evolutions of the diffractive transverse-momentum dependent gluon distribution

Using the Colour Glass Condensate description of electron-nucleus collisions at high energy, we study the diffractive production of a pair of jets with transverse momenta much larger than the nuclear saturation momentum Q s . At leading order in the QCD coupling, the di-jet cross-section exhibits transverse-momentum dependent (TMD) factorisation, with a gluon diffractive TMD distribution (DTMD) which is controlled by gluon saturation and describes the transverse-momentum imbalance between the produced jets. The next-to-leading corrections generate the various quantum evolutions of the diffractive gluon distribution. We focus on the Collins-Soper-Sterman (CSS) evolution which describes the change in the gluon DTMD when increasing the “hard scale” (the typical transverse momentum of the di-jets). We consider two different representations for this equation, one in transverse-momentum space, the other one in transverse-coordinate space. They are not fully equivalent with each other (despite being related by a Fourier transform) because of the respective boundary conditions. These conditions encode the essential physics of gluon saturation together with the effects of two other types of quantum evolution: the BK/JIMWLK evolution over the rapidity gap (“inside the Pomeron”) and the DGLAP evolution outside the rapidity gap (“within the diffractive system”). We demonstrate that, due to gluon saturation, one can compute both the boundary conditions and the CSS solutions mostly from first principles, without the need for a non-perturbative Sudakov. We numerically find a good agreement between the CSS solutions in the two aforementioned representations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Data-based filtered dissipation rate modelling for multi-modal turbulent combustion: evaluating a priori model generalizability

Manifold-based models offer a computationally efficient alternative to directly transporting the thermochemical state in computational simulations of turbulent reacting flows, projecting the high-dimensional thermochemical state-space onto a low-dimensional manifold. Recent efforts have yielded a manifold-based model applicable to multi-modal combustion, enabling reconstruction of the thermochemical state from solutions to two-dimensional manifold equations in mixture fraction and generalized progress variable that are parameterised by three scalar dissipation rates. In coarse-grained simulations such as Large Eddy Simulation (LES), closure of the multi-modal manifold equations and subfilter variances/covariance requires closure of three filtered scalar dissipation rates. Here, the present work adopts a data-based approach, providing closure for the three filtered scalar dissipation rates via deep neural networks (DNNs). High-fidelity datasets corresponding to an autoigniting n-dodecane jet flame and a bluff body swirl-stabilized confined lifted spray flame of two aviation fuels (Jet-A and C1) with different ignition propensities are leveraged to generate training data that spans a diverse range of thermodynamic conditions and combustion modes, including low- and high-temperature ignition regimes in addition to premixed and nonpremixed behaviour. A final DNN model is trained to enforce inherent physical constraints by learning nonlinear functional transformations of the three filtered scalar dissipation rates. The generalizability of this constrained DNN model is demonstrated a priori via conditional statistics evaluated on the lifted spray flame with C1–a configuration that had not been included in the training data. Excellent DNN agreement with conditional DNS statistics is observed, and integrated gradients are computed to identify the most sensitive input variables. The similarity of the marginal PDFs of the most informative input variables and outputs across configurations are quantified via the Wasserstein metric, demonstrating that data-based models may successfully generalize to unseen parametric conditions so long as the most informative input variables share similar distributions across training and testing datasets.

Data-based modelling↗