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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Conservative projection-based data-driven model order reduction of a fluid-kinetic spectral solver

Kinetic simulations are computationally intensive due to six-dimensional phase space discretization. Many kinetic spectral solvers use the asymmetrically weighted Hermite expansion due to its conservation and fluid-kinetic coupling properties, i.e., the lower-order Hermite moments capture and describe the macroscopic fluid dynamics, and higher-order Hermite moments describe the microscopic kinetic dynamics. We leverage this structure by developing a parametric data-driven reduced-order model based on the proper orthogonal decomposition, which projects the higher-order kinetic moments while retaining the fluid moments intact. We demonstrate analytically and numerically that the method ensures local and global mass, momentum, and energy conservation. The numerical results show that the proposed method effectively replicates the high-dimensional spectral simulations at a fraction of the computational cost and memory, as validated on the weak Landau damping and two-stream instability benchmark problems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Non-local transport in radiation-hydrodynamics codes for ICF by efficient coupling to an external Vlasov–Fokker–Planck code

Accurately incorporating non-local transport into radiation-hydrodynamics codes, and indeed any fluid system, has long been elusive. To date, a simplified and accurate theory that can be easily integrated has not been available. This limitation affects modeling in inertial confinement fusion (ICF) and magnetic confinement fusion systems, among others, where non-local transport is well-known to be present. Here, we present a coupling methodology between a full Vlasov–Fokker–Planck (VFP) electron kinetic code and radiation-hydrodynamics (rad-hydro) codes. The VFP code is used to adjust native electron transport in the rad-hydro code, thus enabling improved transport without the need to integrate a full electron VFP solver into the rad-hydro code. This approach necessitates only occasional invocation of the VFP code, reducing computational intensity compared to following the dynamic evolution entirely with the VFP code on fluid time scales. We illustrate that the methodology is more accurate than other simplified methods in thermal decay systems relevant to ICF and can replicate standard theoretical results with high accuracy.

Electronic transport↗
DOE OSTI2026

Proton beam enhancements from ultrafast laser interactions with compound parabolic concentrators

Target normal sheath acceleration (TNSA) is among the most widely studied laser–plasma ion acceleration mechanisms. In this Letter, we report on studies of proton acceleration from flat Cu targets with cone-like focusing structures called compound parabolic concentrators (CPCs) coupled to their front surface. The CPC acts as a non-imaging focusing optic that enhances the laser intensity at the target's front surface by ∼2×, from 9 × 10 18 to 2 × 10 19 W/cm 2 . This effect drives a reduction in the particle source size from the typical laser spot size of 120 μm to the CPC tip size of 65 μm and significant enhancements in the peak energy and temperature (2.6 × increase) of the resulting TNSA proton beam. We also observe increased opening angle of the beam. 2D PIC simulations have been conducted and replicate the experimental behavior. These increases have implications for long focal length facilities that require higher energy proton beams, which now can be achieved without significant infrastructure changes.

3D printing↗
DOE OSTI2026

Measurements of the inert Hugoniot and observation of mechanical ignition in Ni(V) + Al reactive multilayers via x-ray diffraction

This study investigates the inert Hugoniot response, mechanical ignition, and reaction dynamics of Ni(V)+Al multilayers during longitudinal, laser-driven shock compression experiments. Ni(V)+Al multilayers, known for their self-propagating exothermic reactions, were subjected to longitudinal stresses exceeding 50 GPa using the laser shock facility within the Dynamic Compression Sector (DCS) at the Advanced Photon Source (APS). In situ x-ray diffraction (XRD) revealed that Ni(V) and Al were not in equilibrium during compression, with stress discrepancies attributed to twinning, grain structure effects, and/or dislocation density. However, the measured inert Hugoniot closely matched prior experimental and computational studies, confirming the utility of XRD for measuring the equation of state of thin, complex materials. Additionally, reaction was observed at significantly higher stresses than reported previously using laser-launched flyers. This discrepancy suggests a strong influence of externally imposed shear stress on reaction thresholds, which likely arose from deviations in flyer planarity during past experiments. Full reaction of the multilayer occurred within 40 ns after shock-wave passage, evidenced by complete melting of the constituents. Eulerian hydrocode simulations replicated experimental conditions, providing insights into equilibrium dynamics and experimental artifacts. The results highlight how even small shear forces facilitate ignition in Ni(V)+Al multilayers at lower stresses.

Crystallography↗
DOE OSTI2024

The kinetics of SARS-CoV-2 infection based on a human challenge study

Studying the early events that occur after viral infection in humans is difficult unless one intentionally infects volunteers in a human challenge study. Here, we use data about severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in such a study in combination with mathematical modeling to gain insights into the relationship between the amount of virus in the upper respiratory tract and the immune response it generates. We propose a set of dynamic models of increasing complexity to dissect the roles of target cell limitation, innate immunity, and adaptive immunity in determining the observed viral kinetics. We introduce an approach for modeling the effect of humoral immunity that describes a decline in infectious virus after immune activation. We fit our models to viral load and infectious titer data from all the untreated infected participants in the study simultaneously. We found that a power-law with a power h < 1 describes the relationship between infectious virus and viral load. Viral replication at the early stage of infection is rapid, with a doubling time of ~2 h for viral RNA and ~3 h for infectious virus. We estimate that adaptive immunity is initiated ~7 to 10 d postinfection and appears to contribute to a multiphasic viral decline experienced by some participants; the viral rebound experienced by other participants is consistent with a decline in the interferon response. Altogether, we quantified the kinetics of SARS-CoV-2 infection, shedding light on the early dynamics of the virus and the potential role of innate and adaptive immunity in promoting viral decline during infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Protecting scientific integrity in an age of generative AI

Revolutionary advances in AI have brought us to a transformative moment for science. AI is accelerating scientific discoveries and analyses. At the same time, its tools and processes challenge core norms and values in the conduct of science, including accountability, transparency, replicability, and human responsibility (1–3). These difficulties are particularly apparent in recent advances with generative AI. Future innovations with AI may mitigate some of these or raise new concerns and challenges.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Mechanism-guided engineering of a minimal biological particle for genome editing

The widespread application of genome editing to treat and cure disease requires the delivery of genome editors into the nucleus of target cells. Enveloped delivery vehicles (EDVs) are engineered virally derived particles capable of packaging and delivering CRISPR-Cas9 ribonucleoproteins (RNPs). However, the presence of lentiviral genome encapsulation and replication proteins in EDVs has obscured the underlying delivery mechanism and precluded particle optimization. Here, we show that Cas9 RNP nuclear delivery is independent of the native lentiviral capsid structure. Instead, EDV-mediated genome editing activity corresponds directly to the number of nuclear localization sequences on the Cas9 enzyme. EDV structural analysis using cryo-electron tomography and small molecule inhibitors guided the removal of ~80% of viral residues, creating a minimal EDV (miniEDV) that retains full RNP delivery capability. MiniEDVs are 25% smaller yet package equivalent amounts of Cas9 RNPs relative to the original EDVs and demonstrated increased editing in cell lines and therapeutically relevant primary human T cells. These results show that virally derived particles can be streamlined to create efficacious genome editing delivery vehicles with simpler production and manufacturing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Structural switching dynamically controls the doubly pseudoknotted Rous sarcoma virus–programmed ribosomal frameshifting element

A hallmark of retrovirus replication is the translation of two different polyproteins from one RNA through programmed –1 frameshifting. This is a mechanism in which the actively translating ribosome is induced to slip in the 5′ direction at a defined codon and then continues translating in the new reading frame. Programmed frameshifting controls the stoichiometry of viral proteins and is therefore under stringent evolutionary selection. Forty years ago, the first frameshifting stimulatory element was discovered in the Rous sarcoma virus. The ~120 nt RNA segment was predicted to contain a pseudoknot, but its 3D structure has remained elusive. Now, we have determined cryoEM and X-ray crystallographic structures of this classic retroviral element, finding that it adopts a butterfly-like double-pseudoknot fold. One “wing” contains a dynamic pyrimidine-rich helix, observed crystallographically in two conformations and in a third conformation via cryoEM. The other wing encompasses the predicted pseudoknot, which interacts with a second unexpected pseudoknot through a toggle residue, A2546. This key purine switches conformations between structural states and tunes the stability of interacting residues in the two wings. We find that its mutation can modulate frameshifting by as much as 50-fold, likely by altering the relative abundance of different structural states in the conformational ensemble of the RNA. Taken together, our structure–function analyses reveal how a dynamic double pseudoknot junction stimulates frameshifting by taking advantage of conformational heterogeneity, supporting a multistate model in which high Shannon entropy enhances frameshifting efficiency.

Science & Technology - Other Topics↗
DOE OSTI2025

The Q226L mutation can convert a highly pathogenic H5 2.3.4.4e virus to bind human-type receptors

H5Nx viruses continue to wreak havoc in avian and mammalian species worldwide. The virus distinguishes itself by the ability to replicate to high titers and transmit efficiently in a wide variety of hosts in diverse climatic environments. Fortunately, transmission to and between humans is scarce. Yet, if such an event were to occur, it could spark a pandemic as humans are immunologically naïve to H5 viruses. A significant determinant of transmission to and between humans is the ability of the influenza A virus hemagglutinin (HA) protein to shift from an avian-type to a human-type receptor specificity. Here, we demonstrate that a 2016 2.3.4.4e virus HA can convert to human-type receptor binding via a single Q226L mutation, in contrast to a cleavage-modified 2016 2.3.4.4b virus HA. Using glycan arrays, X-ray structural analyses, tissue- and direct glycan binding, we show that L133a Δ and 227Q are vital for this phenotype. Thus, whereas the 2.3.4.4e virus HA only needs a single amino acid mutation, the modified 2016 2.3.4.4b HA was not easily converted to human-type receptor specificity.

Science & Technology - Other Topics↗
DOE OSTI2025

Enhanced chloroplast FtsZ-ring constriction by the ARC6–ARC3 module in Arabidopsis

Chloroplast division, a process tightly linked to the energy demands of plants, is initiated by the formation of the stromal filamenting temperature-sensitive Z (FtsZ) ring. The Z ring is highly dynamic, and its constriction provides the essential force for chloroplast division. However, the regulatory mechanisms governing Z-ring dynamics and constriction remain poorly understood. Here, we report that the chloroplast inner envelope membrane (IEM) protein ACCUMULATION AND REPLICATION OF CHLOROPLASTS6 (ARC6) interacts with the chloroplast stromal protein ARC3, and this interaction is negatively regulated by the conserved J-like domain of ARC6. ARC3 is found both distributed throughout the stroma and localized to a ring-like structure at the chloroplast division site. We demonstrate that ARC6 recruits ARC3 to the division site to form a ring-like structure, likely through direct interaction. This ARC6–ARC3 interaction enables ARC3 to bind FtsZs. Furthermore, we show that the ARC6–ARC3 complex significantly promotes the dynamics of chloroplast Z rings reconstituted in a heterologous system. Finally, the constriction of these reconstituted Z rings is markedly enhanced by ARC6–ARC3. Our findings reveal a regulatory mechanism that governs Z-ring dynamics and constriction, shedding light on the molecular mechanisms underlying chloroplast division.

Science & Technology - Other Topics↗
DOE OSTI2025

Nonenzymatic RNA copying with a potentially primordial genetic alphabet

Nonenzymatic RNA copying is thought to have been responsible for the replication of genetic information during the origin of life. However, chemical copying with the canonical nucleotides (A, U, G, and C) strongly favors the incorporation of G and C and disfavors the incorporation of A and especially U because of the stronger G:C vs. A:U base pair and the weaker stacking interactions of U. Recent advances in prebiotic chemistry suggest that the 2-thiopyrimidines were precursors to the canonical pyrimidines, raising the possibility that they may have played an important early role in RNA copying chemistry. Furthermore, 2-thiouridine (s 2 U) and inosine (I) form by deamination of 2-thiocytidine (s 2 C) and A, respectively. We used thermodynamic and crystallographic analyses to compare the I:s 2 C and A:s 2 U base pairs. We find that the I:s 2 C base pair is isomorphic and isoenergetic with the A:s 2 U base pair. The I:s 2 C base pair is weaker than a canonical G:C base pair, while the A:s 2 U base pair is stronger than the canonical A:U base pair, so that a genetic alphabet consisting of s 2 U, s 2 C, I, and A generates RNA duplexes with uniform base pairing energies. Consistent with these results, kinetic analysis of nonenzymatic template-directed primer extension reactions reveals that s 2 C and s 2 U substrates bind similarly to I and A in the template, and vice versa. Our work supports the plausibility of a potentially primordial genetic alphabet consisting of s 2 U, s 2 C, I, and A and offers a potential solution to the long-standing problem of biased nucleotide incorporation during nonenzymatic template copying.

Science & Technology - Other Topics↗
DOE OSTI2026

Nuclear Data Adjustment for Nonlinear Applications in the OECD/NEA WPNCS SG14 Benchmark—A Bayesian Inverse UQ-Based Approach for Data Assimilation

The Organisation for Economic Co-operation and Development Working Party on Nuclear Criticality Safety has proposed a benchmark exercise to assess the performance of current nuclear data adjustment techniques applied to nonlinear applications and experiments with low correlation to applications. This work introduces Bayesian inverse uncertainty quantification (IUQ) employing scientific machine learning surrogate models as a method for nuclear data adjustments in this benchmark, and compares IUQ to the more traditional methods of generalized linear least squares (GLLS) and Monte Carlo Bayes (MOCABA). Posterior predictions from IUQ showed agreement with GLLS and MOCABA for linear applications. Here, when comparing GLLS, MOCABA, and IUQ posterior predictions to computed model responses using adjusted parameters, we observe that the GLLS predictions failed to replicate the computed response distributions for nonlinear applications, while MOCABA showed near agreement, and IUQ used the computed model responses directly. We also discuss observations on why experiments with low correlation to applications can be informative to nuclear data adjustments and identify some properties useful in selecting experiments for inclusion in nuclear data adjustment. Performance in this benchmark indicates potential for Bayesian IUQ in nuclear data adjustments.

Bayesian calibration↗
DOE OSTI2025

Design and Analysis of an Integrated Additively Manufactured Test Article for Plasma-Facing Components

Current plasma-facing components (PFCs) used in helium-cooled divertor modules are complex structures with tungsten tile, steel sleeve components, and cartridges, all assembled in a helium-cooled multiple jet (HEMJ) structure. The goal of this project is to simplify the complex PFC design using additive manufacturing techniques to create a single integrated tungsten test article. Apart from the flexibility this opens up in exploring a wide array of geometries for the article, having a single integrated article significantly reduces the number of joints and parts in the article, thus reducing chances of leaks. A process called electron beam melting has shown to produce very high-density samples and unique geometries, enabling HEMJ or similar designs. To validate and optimize this novel design, the model underwent a series of computational fluid dynamics and finite element analysis simulations to replicate steady-state heat flux in the divertors. The simulations presented in this study consider a steady-state base heat flux of 5 MW/m 2 , with water serving as the coolant. Future research will explore the use of helium as a coolant, simulate edge-localized-mode conditions, and include experimental validation. Since 3D-printed tungsten is anisotropic, the build direction versus build plane of the article are taken into consideration for the test article strength. Because of the high operating temperatures and low ductility of tungsten, thermal creep and brittle fracture are important failure mechanisms to consider. In conclusion, the cap is evaluated with various flow velocities and nozzle diameters, and an optimal design choice is made for which this cap will survive the divertor conditions with a conservative safety margin.

Divertor↗
DOE OSTI2025

High-Fidelity CFD Modeling of Cryogenic Hydrogen Isotope Extrusion for Fusion Reactor Pellet Fueling

This study investigates the extrusion processes of deuterium and protium using ANSYS-Polyflow. The geometries and computational fluid dynamics (CFD) settings closely replicate the experimental setups and data acquired from the extruder experiments at Oak Ridge National Laboratory (ORNL) for validation purposes. We explore the impacts of (1) slip versus non-slip boundary conditions and (2) the use of constant, temperature-, and shear rate–dependent viscosities, concluding that the implementation of non-slip wall boundary conditions combined with shear rate–dependent viscosity produced more accurate predictions. The simulations achieved excellent agreement with the experimental data, with relative differences of only 5% for deuterium, and 3% to 6% for protium. This is the first time that experimental extrusion data at ORNL have been accurately predicted through high-fidelity CFD modeling. In conclusion, the advancements offer valuable insights and a foundational modeling tool for optimizing pellet injectors for ITER and other future reactor-scale devices.

ANSYS-Polyflow↗
DOE OSTI2024

Image-based novel fault detection with deep learning classifiers using hierarchical labels

One important characteristic of modern fault classification systems is the ability to flag the system when faced with previously unseen fault types. This work considers the unknown fault detection capabilities of deep neural network-based fault classifiers. Specifically, we propose a methodology on how, when available, labels regarding the fault taxonomy can be used to increase unknown fault detection performance without sacrificing model performance. To achieve this, we propose to utilize soft label techniques to improve the state-of-the-art deep novel fault detection techniques during the training process and novel hierarchically consistent detection statistics for online novel fault detection. Lastly, we demonstrated increased detection performance on novel fault detection in inspection images from the hot steel rolling process, with results well replicated across multiple scenarios and baseline detection methods.

42 ENGINEERING↗
DOE OSTI2025

Inertial Confinement Fusion Design Search Using Bayesian Optimization

Inertial confinement fusion (ICF) experiments rely on complex multi-physics simulation codes such as the Lawrence Livermore National Laboratory-developed HYDRA to guide design work. However, these simulations have several dozen tunable parameters and can be computationally expensive. This makes searching the parameter space challenging and time-consuming. Recently developed automated tools utilize Bayesian optimization to search these high-dimensional parameter spaces for optimal designs. The optimization tools run 2D integrated simulations in HYDRA to converge on a design that produces specified scalar or vector outputs. In this paper, we apply the Bayesian optimization tools to two common tuning scenarios. First, we tune simulation inputs to match measurements of a well-characterized experiment at the National Ignition Facility. This type of tuning is commonly performed to compensate for the use of simplified simulation settings (e.g. reduced resolution) or to account for missing physics in the simulations. Second, we search for an ICF simulation design that has a particular radiation drive profile. These optimizations replicate the kinds of tuning researchers routinely perform, but do so with significantly reduced manual effort. This approach demonstrates a powerful and efficient pathway toward autonomous, high-fidelity design optimization for future ICF experiments.

Bayesian optimization↗
DOE OSTI2024

Effect of rotation on negative triangularity plasmas in DIII-D

At the DIII-D tokamak, plasmas with negative triangularity (NT) have been found to have similar energy confinement times as H-mode plasmas with positive triangularity. These NT plasmas also have a stable edge that inhibits H-mode, lacks dangerous edge transients, and has naturally low impurity confinement. For these reasons, NT plasmas have the potential to be a transformative reactor scenario. To determine the importance of strong co-current neutral beam torque for NT performance at DIII-D, scans of neutral beam torque at constant neutral beam power have been performed. These scans have shown that the energy confinement time for a basic, inductive NT scenario (q 95 ≈ 2.8) decreases by 16% when torque is reduced to reactor levels. This reduction in confinement can be replicated with gyrofluid modeling that isolates the role of E x B shear in the change in transport. In a separate set of discharges with lower plasma current (q 95 ≈ 2.5), no significant correlation between confinement time and rotation was found. Throughout this investigation, excellent MHD stability was observed, even with very low toroidal rotation. Further, low impurity confinement was found at multiple rotation levels. Throughout the campaign, rotation near the edge was counter-current, consistent with the measurement of counter-current intrinsic edge rotation, and these observations agree with NT results from the TCV tokamak.

confinement↗
DOE OSTI2026

Dynamics of argon metastables in Ar–CH 4 radio frequency capacitively-coupled plasma: real-time monitoring with neural network-augmented broadband optical emission spectroscopy

In moderate-pressure radio frequency (RF) capacitively coupled plasmas generated in argon–methane mixtures, the density of argon metastable atoms (Ar 1 s 5 ) exhibits a non-monotonic dependence on methane (CH 4 ) concentration. Laser-induced fluorescence (LIF) was used to measure and compare local Ar 1 s 5 densities in Ar and Ar–CH 4 plasmas at 2.6 Torr and RF powers of 17–117 W. The addition of 1% CH 4 increases the metastable density, and 2% CH 4 triggers a strong depletion by an order of magnitude, compared to 1% CH 4 case. This non-monotonic behavior demonstrates the sensitivity of metastable populations to small gas admixtures, which is critical for processes where metastables drive precursor dissociation. For real-time monitoring of metastable population, broadband optical emission spectroscopy (OES) is augmented with a feedforward neural network (NN) to predict Ar s1 5 densities from spectral features. When trained on LIF data, the NN replicates the absolute densities and the dynamic trends of Ar 1 s 5 density variation. The NN-augmented broadband OES approach can be used as a simple and cost-effective tool for tracking Ar metastables in Ar-rich plasmas, facilitating industrial-scale optimization.

Yatom, Shurik [Princeton Plasma Physics Laboratory↗