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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Examining the Impact of Local Constraint Violations on Energy Computations in DFT

ABSTRACT This work examines the impact of locally imposed constraints in Density Functional Theory (DFT). Using a metric referred to as the extent of violation index (EVI), we quantify how well exchange‐correlation functionals adhere to local constraints. Applying EVIs to a diverse set of molecules for GGA functionals reveals constraint violations, particularly for semi‐empirical functionals. We leverage EVIs to explore potential connections between these violations and errors in chemical properties. While no correlation is observed for atomization energies, a significant statistical correlation emerges between EVIs and total energies. Similarly, the analysis of reaction energies suggests weak positive correlations for specific constraints. However, definitive conclusions about error cancellation mechanisms cannot be made at this time. These observations revealed by EVIs may be useful for consideration when designing future generations of semilocal functionals.

Khanna, Vaibhav [Department of Chemistry Universit↗
DOE OSTI2024

Phase Selection During Solidification and Solid-State Phase Transformations in an Al-10Ce-8Mn (wt pct) Alloy

In multicomponent Al-Ce alloys, and especially after additive manufacturing (AM), complex and metastable solidification microstructures are frequently observed. Here, in this research, the relationship between solidification conditions and phase selection are explored for an Al-10Ce-8Mn (wt pct) alloy using a systematic study of laser melting conditions. Three solidification modes were observed: primary Al 10 Mn 2 Ce; primary Al 20 Mn 2 Ce; and eutectic FCC Al + Al 20 Mn 2 Ce. These solidification modes were correlated to specific liquid-solid interface velocities using a simple thermal model, showing the change in primary solidification phase for low (< 6.8 × 10 −4 m/s), moderate (between 8.2 × 10 −4 and 5.9 × 10 −2 m/s) and high solidification velocities (> 6.2 x 10 −2 m/s) for the above three solidification microstructures, respectively. These results were rationalized by using interface response function (IRF) theory to describe the solidification undercooling for the possible primary intermetallic phases. The implication of the local phase selection from differing solidification conditions is summarized by a comparison of hardness which demonstrates the potential variance of Vickers hardness from 101 to 242 (VHV) by changing the laser velocity from 1 to 83 mm/s. Interestingly, on heat treatment at 400°C, the decomposition pathways of the solidification microstructure and hardness were also found to be different, thereby opening multiple pathways for spatial microstructure and property control within AM components.

Sisco, Kevin↗
DOE OSTI2025

MX precipitate behavior in an irradiated advanced Fe-9Cr steel: Helium effects on phase stability

As part of an ongoing series aimed at optimizing Fe-9Cr reduced activation ferritic/martensitic (RAFM) alloys for fusion energy systems, this study explores MX precipitate behavior under dual-ion irradiations, specifically examining correlations between helium transmutation and irradiation-induced damage. Utilizing single and dual-beam ion irradiation, the research explores the combined effects of helium (10–25 appm He/dpa), temperature (400–600 °C), and damage levels (15–100 dpa) on the microstructural evolution of CNA9 steel, a variant of Castable Nanostructured Alloys (CNAs). The study demonstrates that helium co-implantation hinders radiation-enhanced coarsening of MX-TiC precipitates at 500 and 600 °C, maintaining MX-TiC precipitate stability at moderate damage levels (15 dpa) but failing to prevent complete precipitate dissolution at higher damage levels (≥50 dpa) when irradiated at 500 °C. Here, a generalized precipitate stability model suggests that helium-induced suppression of diffusion alters the balance between recoil resolution and back diffusion for MX-TiC precipitates, enhancing the current understanding of precipitate behavior under damage and transmutation simulated dual-ion irradiation conditions.

Characterization↗
DOE OSTI2023

Estimating the economic value of hydropeaking externalities in regulated rivers

Hydropower is a flexible form of electricity generation providing both baseload and balancing power to accommodate intermittent renewables in the energy mix. However, hydropower also generates various externalities. This study investigates individuals' preferences for policies aiming to reduce short-term regulations (i.e., hydropeaking in regulated rivers) while accounting for associated externalities with a discrete choice experiment. This is the first valuation study focusing on hydropeaking that considers both negative and positive externalities. The results imply that most individuals prefer stronger restrictions on short-term regulations to mitigate local environmental impacts. Individuals especially value improvements in recreational use, fish stocks, and the ecological state. On the other hand, potential increases in CO 2 emissions are linked with a clear disutility. The estimated benefits obtained from an improved state of the river environment due to such restrictions exceed the disutility caused by increased CO 2 emissions. Furthermore, the results also reveal unobserved preference heterogeneity among individuals, which should be accounted for in the willingness-to-pay (WTP) estimation using a model specification with correlated utility coefficients. Overall, the findings can inform policy-makers and environmental managers on the economic value of hydropeaking externalities and further guide the sustainable management of rivers regulated for hydropower generation.

13 HYDRO ENERGY↗
DOE OSTI2020

Extracting a mixing parameter from 2D radiographic imaging of variable-density turbulent flow

We extract a suitably averaged fluctuating density from the two-dimensional radiographic image of a flow. The X-ray attenuation is given by the Beer–Lambert law which exponentially damps the incident beam intensity by a factor proportional to the density, opacity and thickness of the target. By making reasonable assumptions for the mean density, opacity and effective thickness of the target flow, we estimate the density fluctuation contribution to the attenuation. The extracted density fluctuations averaged across the thickness of the flow in the direction of the beam may be used to form the density–specific-volume correlation $b$. In a statistical description of variable-density turbulence, $b$ quantifies the degree of mixedness. The ability to extract a measure of mixedness from experimental data would be a powerful tool that could be used in the validation of mix models. The scheme proposed is tested for DNS data computed for variable density buoyancy-driven mixing. We quantify the deficits in the extracted value of $b$ due to target thickness, Atwood number and modeled signal noise. This analysis justifies using the proposed scheme to infer the mix parameter from thin targets at moderate to low Atwood numbers. Furthermore, to illustrate how the scheme might be used in a practical problem, we demonstrate its application to a radiographic image of counter-shear flow obtained from experiments at the National Ignition Facility.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Microbial potentiometric sensor: A new approach to longstanding challenges

The underlying hypothesis of this study is that simple potentiometric measurements between sensing electrodes and a shared reference electrode - Microbial Potentiometric Sesnor (MPS) system - can be employed in a long-term, continuous mode of operation to resolve the spatial and temporal changes in environmental systems. To address the hypothesis, (1) a conceptual description of the MPS system and its postulated principle of operation are provided; (2) the MPS system performance is documented under controlled laboratory conditions; and (3) the capabilities of the MPS system are documented under quiescent and dynamic field condition. In a laboratory setting, the variability among different MPS signals was insignificant confirming the postulated high accuracy and reproducibility of the sensor performance. It also demonstrated statistically significant correlations with dissolved oxygen (DO) and oxidation-reduction potential (ORP) sensors, while showing capabilities of operating under anoxic and anaerobic conditions. Regardless of their locations in the model wetland system, three MPS sensors functioned without interruption and cleaning for a period >2 years, and thus demonstrating long-term durability of the MPS technology. In real batch-wastewater treatment facility, the deployed MPS system signals were able to describe the organic carbon trends and correlate with each treatment phase in a cycle. Data reproducibility and reliability exceeded the expectations better describing the carbon treatment levels than the DO and ORP sensors (p < 4.4 × 10 –162 vs phase adjusted p < 3.0 × 10 –58 ). While MPS signals correlate with specific parameters that describe the local process or environments, it is more prudent to employ both the magnitude and pattern of a composite signal like the MPS signal describe the change to reflect any shift in the local environment. Finally, when compared to a baseline pattern, this change in signal magnitude and pattern reveals important information that can be employed to tailor and optimize any condition or process which involves microorganisms.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Chemodiversity of riverine dissolved organic matter: Effects of local environments and watershed characteristics

Riverine dissolved organic matter (DOM) is crucial to global carbon cycling and aquatic ecosystems. However, the geographical patterns and environmental correlates of DOM chemodiversity remain elusive especially in surface waters and sediments of global rivers. Here, we systematically analyzed DOM molecular diversity and composition in surface waters and sediments across 97 globally distributed rivers using data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium. Here, we further examined the associations of molecular richness and composition with geographical, climatic, physicochemical variables, as well as the watershed characteristics. We found that molecular richness significantly decreased toward higher latitudes, but only in sediments (r = -0.24, P < 0.001). The environmental variables like precipitation and non-purgeable organic carbon showed strong associations with DOM molecular richness and composition. Interestingly, we identified that less-documented factors like watershed characteristics were also related to DOM molecular richness and composition, and were stronger in waters than sediments. Such associations were further supported by the fact that 11 out of 13 watershed characteristics (e.g., land cover variables) showed more positive than negative correlations with molecular abundance especially in waters. The molecules positively and negatively correlated with specific watershed characteristics had distinct traits, such as stoichiometric ratios and aromaticity. Land covers shifted from natural (e.g., forests) to human-modified (e.g., impervious area) were associated with systematic changes in DOM molecular chemistry. Our findings imply that it may be possible to use a small set of broadly available data types to predict DOM molecular richness and composition across diverse river systems. Elucidation of mechanisms underlying these relationships will provide further enhancements to such predictions, especially when extrapolating to unsampled systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Earth Mover’s Distance as a Metric to Evaluate the Extent of Charge Transfer in Excitations Using Discretized Real-Space Densities

This paper presents a novel theoretical measure, μ EMD , based on the earth mover's distance (EMD), for quantifying the density shift caused by electronic excitations in molecules. As input, the EMD metric uses only the discretized ground- and excited-state electron densities in real space, rendering it compatible with almost all electronic structure methods used to calculate excited states. The EMD metric is compared against other popular theoretical metrics for describing the extent of electron-hole separation in a wide range of excited states (valence, Rydberg, charge transfer, etc.). Further, the results showcase the EMD metric's effectiveness across all excitation types and suggest that it is useful as an additional tool to characterize electronic excitations. The study also reveals that μ EMD can function as a promising diagnostic tool for predicting the failure of pure exchange-correlation functionals. Specifically, we show statistical relationships among the functional-driven errors, the exact exchange content within the functional, and the magnitude of μ EMD values.

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

Pomeranchuk instability from electronic correlations in CsTi 3 Bi 5 kagome metal

Electronic nematicity, the spontaneous breaking of rotational symmetry, has emerged as a key instability in correlated quantum systems. CsTi 3 Bi 5 , a kagome metal of the AV 3 Sb 5 (A = K, Rb, Cs) family, hosts rich unconventional electronic phases, yet the origin of its nematicity remains unsettled. Here, we combine polarization-dependent angle-resolved photoemission spectroscopy with functional renormalization group calculations on a fully interacting ab initio model. We reveal an orbital-selective nematic deformation in the low-energy band structure and identify a finite angular momentum (d-wave) Pomeranchuk instability driven by electronic correlations in specific orbital channels and detuning from Van Hove singularities. Our results establish a direct link between orbital selectivity and symmetry-breaking instabilities in CsTi 3 Bi 5 , providing a microscopic framework for nematic order in kagome systems.

Bigi, Chiara [Synchrotron SOLEIL, Saint-Aubin (Fra↗
DOE OSTI2026

Revealing the Hidden Third Dimension of Point Defects in Two-Dimensional MXenes

Point defects govern many important functional properties of two-dimensional (2D) materials. However, resolving the three-dimensional (3D) arrangement of these defects in multi-layer 2D materials remains a fundamental challenge, hindering rational defect engineering. Here, we overcome this limitation using an artificial intelligence-guided electron microscopy workflow to map the 3D topology and clustering of atomic vacancies in Ti3C2TX MXene. Our approach reconstructs the 3D coordinates of vacancies across hundreds of thousands of lattice sites, generating robust statistical insight into their distribution that can be correlated with specific synthesis pathways. This large-scale data enables us to classify a hierarchy of defect structures-from isolated vacancies to nanopores-revealing their preferred formation and interaction mechanisms, as corroborated by molecular dynamics simulations. This work provides a generalizable framework for understanding and ultimately controlling point defects across large volumes, paving the way for the rational design of defect-engineered functional 2D materials.

2D materials↗
DOE OSTI2022

Ab initio calculations in atoms, molecules, and solids, treating spin–orbit coupling and electron interaction on an equal footing

We incorporate explicit, non-perturbative treatment of spin–orbit coupling into ab initio auxiliary-field quantum Monte Carlo (AFQMC) calculations. The approach allows a general computational framework for molecular and bulk systems in which material specificity, electron correlation, and spin–orbit coupling effects can be captured accurately and on an equal footing, with favorable computational scaling vs system size. We adopt relativistic effective-core potentials that have been obtained by fitting to fully relativistic data and that have demonstrated a high degree of reliability and transferability in molecular systems. This results in a two-component spin-coupled Hamiltonian, which is then treated by generalizing the ab initio AFQMC approach. We demonstrate the method by computing the electron affinity in Pb, the bond dissociation energy in Br 2 and I 2 , and solid Bi.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Machine learning–driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins

Significance Here we present an unprecedented multiscale simulation platform that enables modeling, hypothesis generation, and discovery across biologically relevant length and time scales to predict mechanisms that can be tested experimentally. We demonstrate that our predictive simulation-experimental validation loop generates accurate insights into RAS-membrane biology. Evaluating over 100,000 correlated simulations, we show that RAS–lipid interactions are dynamic and evolving, resulting in: 1) a reordering and selection of lipid domains in realistic eight-lipid bilayers, 2) clustering of RAS into multimers correlating with specific lipid fingerprints, 3) changes in the orientation of the RAS G-domain impacting its ability to interact with effectors, and 4) demonstration that RAS–RAS G-domain interfaces are nonspecific in these putative signaling domains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A Better Method to Calculate Fuel Burnup in Pebble Bed Reactors Using Machine Learning

Burnup measurement is an important step in material control and accountancy (MC&A) at nuclear reactors, and may be done by examining gamma spectra of fuel samples. Traditional approaches rely on known correlations to specific photopeaks (e.g. 137 Cs) and operate via a standard linear regression method. However, the quality of these regression methods is limited even in the best case, and is significantly poorer at short fuel cool-down times, due to the elevated radiation background by short life-time isotopes, and self-shielding effect of the fuel. For practical operation of pebble bed reactors (PBRs), quick measurements (in minutes) and short cooling times (in hours) are required from a safety and security perspective. We investigated the efficacy and performance of machine learning (ML) methods to predict the burnup of the pebble fuel from full gamma spectra (rather than specific discrete photopeaks) and found a full-spectrum ML approach to far outperform baseline regression predictions in all measurement and cooling conditions - including in operational-like measurement conditions. We also performed model and data ablation experiments to determine the relative performance impact of our ML methods' capacity to model data nonlinearities and the inherent additional information in full spectra. Applying our ML methods, we found a number of surprising results, including improved accuracy at shorter fuel cooling times (the opposite of the norm), remarkable robustness to spectrum compression (via rebinning), and competitive burnup predictions even when using background signal only (i.e. explicitly omitting known isotope photopeaks).

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2026

Experimental considerations and applications for time-resolved impedance on silicon-anode battery systems

Dynamic electrochemical impedance spectroscopy (dEIS) utilizes a superimposed multi-sinusoidal waveform and enables temporally resolved investigations on various electrochemical processes; however, the signal-to-noise ratio must be maximized while retaining linearity and stationarity within the system. In the present work, we probe the impact of the waveform’s total amplitude as well as the waveform and phase profiles. The equal amplitude multi-sinusoidal waveform with 35 mV total amplitude (<1 mV per frequency) and random phase profile exhibits the lowest impedance noise. This input signal is sufficient in avoiding the high frequency signal attenuation from the potentiostat’s low-pass filter. Additionally, we demonstrate the optimized dEIS waveform’s utility in investigating surface passivation within thin-film and composite silicon (Si) anodes. Within a two-electrode Si-lithium metal coin cell, the charge transfer resistance (RCT) associated with alloying kinetics dominates the overall impedance. RCT increases with state of charge indicating a kinetic bottleneck at higher lithiation states. To explore this further, we utilize a three-electrode Si-LiNi0.8Mn0.1Co0.1O2 pouch cell to deconvolute the Si impedance contributions. The evolution of the solid electrolyte interphase (SEI) and charge transfer resistances correlate to specific Li–Si alloy phases. We attribute this to the influence of Si particle volume expansion on SEI instabilities and a kinetic bottleneck at higher lithiation states.

Lam, Steven [ORNL]↗
DOE OSTI2021

Simultaneous velocity and density measurements of fully developed Rayleigh-Taylor mixing

Here, the dynamics of molecular mixing and the energy transfer process in the Rayleigh-Taylor instability (RTI) are studied through the collection of simultaneous density-velocity measurements. These experiments provide simultaneous density-velocity field measurements, in contrast to previous point measurements. Statistically stationary experiments are performed in a “convective-type” gas tunnel facility, with density contrast achieved through the injection of helium into the bottom stream. Three experiments at Atwood number ≈ 0.1 are captured at three outer scale Reynolds numbers Re = 520, 2260, and 4050. Particle image velocimetry and laser induced fluorescence are employed simultaneously. Statistics of the density and velocity show self-similar collapse of RTI profiles at large Reynolds number Re >2000. Flat velocity profiles indicate homogeneous turbulence characteristics in the core of the mixing region. Significant anisotropy develops in the flow, with horizontal velocity fluctuations being only 60% of the vertical velocity fluctuations. The turbulent mass flux is found to be asymmetric about the centerline, with increased peak towards the spike. Measurements of the molecular mixing show that mixing is maximized at the core of the flow and increases with increased Reynolds number. The transport equation of density-specific-volume correlation b shows that it is mostly produced in the core of the mixing region, and that the spatial evolution of its profile is the result of transport by bulk motion of the bubble and spike. Energy transfer from gravitational potential energy to turbulent kinetic energy and viscous dissipation is observed to occur in the experiment with a ratio of dissipated energy to potential energy released of 38%. The analysis of the turbulent kinetic energy transport equation budget reveals that production is the primary mechanism towards the growth of turbulent kinetic energy in the core of the flow, and is asymmetrically slightly skewed towards the spike. However, it is through the transport that the strong advection at the edges of the mixing region is maintained.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Scavenging organic nitrogen and remodelling lipid metabolism are key survival strategies adopted by the endophytic fungi, Serendipita vermifera and Serendipita bescii to alleviate nitrogen and phosphorous starvation in vitro

Summary Serendipitaceae represents a diverse fungal group in the Basidiomycota that includes endophytes and lineages that repeatedly evolved ericoid, orchid and ectomycorrhizal lifestyle. Plants rely upon both nitrogen and phosphorous, for essential growth processes, and are often provided by mycorrhizal fungi. In this study, we investigated the cellular proteome of Serendipita vermifera MAFF305830 and closely related Serendipita vermifera subsp. bescii NFPB0129 grown in vitro under (N) ammonium and (P) phosphate starvation conditions. Mycelial growth pattern was documented under these conditions to correlate growth‐specific responses to nutrient starvation. We found that N‐starvation accelerated hyphal radial growth, whereas P‐starvation accelerated hyphal branching. Additionally, P‐starvation triggers an integrated starvation response leading to remodelling of lipid metabolism. Higher abundance of an ammonium transporter known to serve as both an ammonium sensor and stimulator of hyphal growth was detected under N‐starvation. Additionally, N‐starvation led to strong up‐regulation of nitrate, amino acid, peptide, and urea transporters, along with several proteins predicted to have peptidase activity. Taken together, our finding suggests S. bescii and S. vermifera have the metabolic capacity for nitrogen assimilation from organic forms of N compounds. We hypothesize that the nitrogen metabolite repression is a key regulator of such organic N assimilation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Influence of Correlations on the Thermal Performance Modeling of Parabolic Trough Collectors

The influence of correlations on the thermal performance modeling of parabolic trough collectors was analyzed in this work. A versatile model for a parabolic trough collector was developed that allows one- and two-dimensional analysis and enables the use of correlations to calculate thermophysical properties and convection heat transfer coefficients. The model also allows the use of constant values for properties and/or coefficients obtained from the evaluation correlations at a specific temperature. The effect of each correlation was evaluated independently, and the results were compared with a reference case that considered a two-dimensional approach and used all the correlations. For the analyzed cases, the correlation for the absorber emittance has the strongest impact on the collector efficiency, leading to a lower error when used. Based on the results, a one-dimensional model approach considering a correlation for the absorber emittance leads to efficiency errors below 3% for collector lengths of up to 243.6 m. Compared with the reference case, a one-dimensional approach using all correlations for a collector with a length of 500 m, and operating with an inlet temperature of 773 K, can result in errors around 9%. However, using constant values for properties and heat transfer coefficients could lead to errors of up to 50%. Multiple thermal models for parabolic trough collectors proposed in the literature rely on a one-dimensional approach, estimated values for the heat transfer coefficients, and constant thermophysical properties. The errors associated with those approaches are analyzed and quantified in this work as a function of the collector length and operation temperature.

absorber emittance↗
DOE OSTI2020

Application of entropy and signal energy for ultrasound-based classification of three-dimensional printed polyetherketoneketone components

This paper describes a preliminary method for the classification of annealed and unannealed polyetherketoneketone (PEKK) components manufactured using a material extrusion three-dimensional (3D) printing process. PEKK is representative of a class of high-performance thermoplastics that are increasingly employed as feedstocks for use in 3D printing. PEKK components may be used continuously at elevated temperatures, are chemically resistant, and able to withstand large mechanical loads. These properties render PEKK suitable as a metal component replacement in aerospace applications, high-temperature industrial applications, and surgical implants. The structure of PEKK is semi-crystalline with the specific crystallinity correlating to the final properties during application, making determination of this property crucial. This study compares three different signal processing techniques intended to distinguish annealed (high crystallinity) from unannealed (low crystallinity) components using backscattered ultrasound. The first is energy-based and is unable to detect annealing. The second two are based on different entropies of the backscattered signal: a limiting form of Renyi's entropy and a limiting form of joint entropy. The joint entropy values for the annealed and unannealed specimens fall into two non-overlapping intervals and have a statistical separation of two standard deviations.

36 MATERIALS SCIENCE↗