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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Simons Observatory: validation of reconstructed power spectra from simulated filtered maps for the small aperture telescope survey

We present a transfer function-based method to estimate angular power spectra from filtered maps for cosmic microwave background (CMB) surveys. This is especially relevant for experiments targeting the faint primordial gravitational wave signatures in CMB polarisation at large scales, such as the Simons Observatory (SO) small aperture telescopes. While timestreams can be filtered to mitigate the contamination from low-frequency noise, usual methods that calculate the mode coupling at individual multipoles can be challenging for experiments covering large sky areas or reaching few-arcminute resolution. The method we present here, although approximate, is more practical and faster for larger data volumes. We validate it through the use of simulated observations approximating the first year of SO data, going from half-wave plate-modulated timestreams to maps, and using simulations to estimate the mixing of polarisation modes induced by an example of time-domain filtering. We show its performance through an example null test and with an end-to-end pipeline that performs inference on cosmological parameters, including the tensor-to-scalar ratio r. The performance demonstration uses simulated observations at multiple frequency bands. We find that the method can recover unbiased parameters for our simulated noise levels.

CMBR experiments↗
DOE OSTI2026

Comparative Analysis of Model Predictive Control and MPC-Informed Rule-Based Control for Thermal Storage Operation in Ultra-Low Temperature 4th Generation District Heating Networks

The integration of thermal storage and heat pumps in district heating networks (DHNs) can significantly enhance operational flexibility and energy efficiency; however, the practical deployment of advanced control strategies is often hindered by forecasting requirements and computational complexity. This study presents a comparative analysis of thermal storage control strategies in an ultra-low-temperature fourth-generation DHN, focusing on the development of a simplified rule-based control (RBC) explicitly informed by Model Predictive Control (MPC) behavior. The proposed methodology systematically analyzes the charging and discharging decisions of an MPC-controlled system under ideal forecasting conditions and extracts recurrent control patterns as a function of key system variables, including outdoor temperature, thermal demand, and electricity price. These patterns are translated into a set of structured time- and condition-based rules, resulting in an MPC-informed RBC that embeds predictive insights while preserving implementation simplicity and operational transparency. The approach is validated on a realistic mixed-use urban district in Denver, Colorado, USA, equipped with a centralized air-source heat pump, distributed water-to-water heat pumps, and a central thermal storage unit. Results show that the tuned RBC attains approximately 96% of ideal MPC economic performance (-27% of costs), preserves values of technical and environmental indicators (reduction only of 2-3%), and substantially reduces complexity. Sensitivity analyses further demonstrate the robustness of the RBC under varying operational conditions (i.e., ambient temperature, electricity price). Overall, the study demonstrates that MPC-informed rule-based control represents an effective trade-off between control performance and real-world applicability, enabling the integration of additional system components while maintaining simplicity, robustness, and ease of implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Augmenting Molecular Graphs with Geometries via Machine Learning Interatomic Potentials

Accurate molecular property predictions require 3D geometries, which are typically obtained using expensive methods such as density functional theory (DFT). Here, we attempt to obtain molecular geometries by relying solely on machine learning interatomic potential (MLIP) models. To this end, we first curate a large-scale molecular relaxation dataset comprising 3.5 million molecules and 300 million snapshots. Then MLIP pre-trained models are trained with supervised learning to predict energy and forces given 3D molecular structures. Once trained, we show that the pre-trained models can be used in different ways to obtain geometries either explicitly or implicitly. First, it can be used to obtain approximate low-energy 3D geometries via geometry optimization. While these geometries do not consistently reach DFT-level chemical accuracy or convergence, they can still improve downstream performance compared to non-relaxed structures. To mitigate potential biases and enhance downstream predictions, we introduce geometry fine-tuning based on the relaxed 3D geometries. Second, the pre-trained models can be directly fine-tuned for property prediction when ground truth 3D geometries are available. Our results demonstrate that MLIP pre-trained models trained on relaxation data can learn transferable molecular representations to improve downstream molecular property prediction and can provide practically valuable but approximate molecular geometries that benefit property predictions. Our code is publicly available at: https://github.com/divelab/AIRS/.

Fu, Cong [Texas A & M Univ., College Station, TX (↗
DOE OSTI2024

Machine learning in materials research: Developments over the last decade and challenges for the future

The number of studies that apply machine learning (ML) to materials science has been growing at a rate of approximately 1.67 times per year over the past decade. In this review, I examine this growth in various contexts. First, I present an analysis of the most commonly used tools (software, databases, materials science methods, and ML methods) used within papers that apply ML to materials science. The analysis demonstrates that despite the growth of deep learning techniques, the use of classical machine learning is still dominant as a whole. It also demonstrates how new research can effectively build upon past research, particular in the domain of ML models trained on density functional theory calculation data. Next, I present the progression of best scores as a function of time on the matbench materials science benchmark for formation enthalpy prediction. In particular, a dramatic improvement of 7 times reduction in error is obtained when progressing from feature-based methods that use conventional ML (random forest, support vector regression, etc.) to the use of graph neural network techniques. Finally, I provide views on future challenges and opportunities, focusing on data size and complexity, extrapolation, interpretation, access, and relevance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The reference genome for the northeastern Pacific bull kelp, Nereocystis luetkeana

Bull kelp, Nereocystis luetkeana, is a northeastern Pacific kelp with broad distribution from Alaska to central California. Its population declines have caused severe concerns in northern California, the Salish Sea in Washington, and recently in some populations in Oregon. Despite bull kelp's accumulated ecological and physiological studies, an assembled and annotated genomic reference was still unavailable. Here, we report the complete and annotated genome of Nereocystis luetkeana, produced by the California Conservation Genomics Project (CCGP), which aims to reveal genomic diversity patterns across California by sequencing the complete genomes of approximately 150 carefully selected species. The genome was assembled into 1562 scaffolds with 449.82 Mb, 80x of coverage and 22 952 gene models. BUSCO assembly showed a completeness score of 72% for the stramenopiles gene set. The mitochondria and chloroplast genome sequences have 37 Kb and 131 Mb, respectively. The orthology analysis between 10 Phaeophycean genomes showed 1065 expanded and 286 unique orthogroups for this species. Pairwise comparisons showed 542 orthogroups present only in N. luetkeana and M. pyrifera, another large-body kelp. The enrichment analysis of these orthogroups showed important functions related to central metabolism and signaling due to ATPases enrichment in these two species. This genome assembly will provide an essential resource for the ecology, evolution, conservation, and breeding of bull kelp.

California Conservation Genomics Project—CCGP↗
DOE OSTI2026

Reference floating wind array designs for three representative regions

This work presents the systematic development of three open-source reference floating wind array designs. The designs are tailored to representative site conditions for three regions of the United States: Humboldt Bay off the coast of California, the Gulf of Maine, and the Gulf of America. We adopted existing reference designs for the individual 15 MW turbines, semisubmersible floating platforms, substations, mooring systems, and power cables – integrating and adapting them as needed for each location. We adapted existing dynamic cable designs to use larger conductor sizes to meet the arrays' power transmission requirements, and we set up redundant mooring systems for each substation. The layout of each array is a uniform-grid design optimized to approximately minimize the levelized cost of energy (LCOE) within a square lease area while satisfying spatial constraints. These constraints ensure adequate clearances between adjacent turbines and between underwater components during the layout optimization to prevent clashing and ensure that all components reside within the lease boundaries. Substations are included to allow accounting for intra-array cable costs. They are placed within the uniform grid to maintain the navigability of the arrays. For each feasible layout considered, annual energy production and cable routing costs are calculated and updated in the LCOE objective function. After the optimization, we refined the cable routing with a mix of algorithmic and manual methods to ensure that the cables avoid mooring system components and approach the substation with adequate clearances. We confirmed the suitability of each reference array's layout by comparing the wake losses at each wind heading angle to the wind rose, observing that the optimized layouts largely avoid wake losses in the predominant wind directions. These reference arrays provide open-source baseline designs to enable future research and innovation of floating wind technology at the array scale.

17 WIND ENERGY↗
DOE OSTI2025

Correspondence between Color Glass Condensate and High-Twist Formalism

The color glass condensate (CGC) effective theory and the collinear factorization at high twist (HT) are two well-known frameworks describing perturbative QCD multiple scatterings in nuclear media. It has long been recognized that these two formalisms have their own domain of validity in different kinematic regions. Taking direct photon production in proton-nucleus collisions as an example, we clarify for the first time the relation between CGC and HT at the level of a physical observable. We show that the CGC formalism beyond shock-wave approximation, and with the Landau-Pomeranchuk-Migdal interference effect is consistent with the HT formalism in the transition region where they overlap. Such a unified picture paves the way for mapping out the phase diagram of parton density in nuclear medium from dilute to dense region.

Parton distribution functions↗
DOE OSTI2024

Scale sensitivity of ethanol production via consolidated bioprocessing with consideration of feedstock cost

We examine feedstock cost and minimum selling price for ethanol production from corn stover as a function of scale, stover yield, participation rate, and price incentives for two conversion technologies: a conventional base case featuring thermochemical pretreatment with added cellulase, and an advanced case featuring consolidated bioprocessing with cotreatment (C-CBP). Delivered feedstock cost ranged from $\$85$ Mg −1 at small (10 million gallons year −1 or ~38 million L year −1 ) scale with high yield and participation rates to $\$124$ Mg −1 at large scale (60 million gallons year −1 or 227 million L year −1 ) and low yield and participation rates. The minimum ethanol selling price (MESP) was approximately twofold lower for the advanced case compared with the base case. The payback period was several times lower for the advanced case compared with the base case, with increasing disparity at smaller scales, and was highly sensitive to ethanol price supports. For both C-CBP and the conventional processing paradigm, MESP decreased with increasing scale, indicating that the cost penalty due to higher feedstock transport distances was more than outweighed by lower capital costs. However, the cost penalty for operation at small scale, expressed in $ gallon −1 ethanol, is lower for C-CBP than for the conventional paradigm by roughly twofold. Particularly for initial applications of C-CBP, we speculate that this cost penalty will likely be modest compared with the anticipated benefits of small-scale operation such as increased opportunity to use existing infrastructure, easier plant siting and supply chain establishment, and lower total investment required.

biorefinery scale↗
DOE OSTI2025

Observing differential spin currents by resonant inelastic X-ray scattering

Controlling spin currents, that is, the flow of spin angular momentum, in small magnetic devices, is the principal objective of spin electronics, a main contender for future energy-efficient information technologies. A pure spin current has never been measured directly because the associated electric stray fields and/or shifts in the non-equilibrium spin-dependent distribution functions are too small for conventional experimental detection methods optimized for charge transport. Here we report that resonant inelastic X-ray scattering (RIXS) can bridge this gap by measuring the spin current carried by magnons—the quanta of the spin wave excitations of the magnetic order—in the presence of temperature gradients across a magnetic insulator. This is possible due to the sensitivity of the momentum- and energy-resolved RIXS intensity to minute changes in the magnon distribution under non-equilibrium conditions. Furthermore, we use the Boltzmann equation in the relaxation time approximation to extract transport parameters, such as the magnon lifetime at finite momentum, essential for the realization of magnon spintronics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Composition and Plume Gas Interaction Control Iron Fractional Solubility More Than Particle Size in Volcanic Ash: Implications for Fertilization of the North Atlantic

Deposition of volcanic ash is thought to impact marine biogeochemical cycling by adding soluble iron (Fe) to the surface ocean. The magnitude of this input is a function of the amount of ash deposited, the total Fe content in the ash, and ash‐derived Fe's fractional solubility. However, the relative importance of chemical composition, acidic processing by the volcanic plume, and ash particle size in determining solubility is unclear. We paired an aerosol leach meant to provide an upper limit for fractional Fe solubility with chemical analyses of ash from the Cumbre Vieja (CV) and La Soufrière eruptions, which both impacted the North Atlantic in 2021. Fe in the ash samples is <6% soluble, but Fe fractional solubility in CV ash is approximately triple that of La Soufrière ash. Compared to La Soufrière, a larger proportion of the Fe in CV ash is in silicate rather than oxide minerals, which release more soluble Fe. Elevated levels of surficial fluorine (F) also suggest that CV ash was subjected to a more fluorine‐rich eruption plume and underwent more acidic processing. Particle size does not appear to be a primary control on Fe release. We estimate that the CV eruption had a much larger impact on dissolved Fe (DFe) concentration in the surface ocean than the La Soufrière eruption because of differences in soluble Fe content and particle deposition velocity. These differences may help explain why some eruptions elicit a biological response in the ocean while others do not.

Elliott, Hope E. [Univ. of Miami, FL (United State↗
DOE OSTI2025

Superspin renormalization and slow relaxation in random spin systems

We develop an excited-state real-space renormalization group (RSRG-X) formalism to describe the dynamics of conserved densities in randomly interacting spin-12 systems. Our formalism is suitable for systems with U(1) and Z2 symmetries, and we apply it to chains of randomly positioned spins with dipolar XX+YY interactions, as arise in Rydberg quantum simulators and other platforms. The formalism generates a sequence of effective Hamiltonians that provide approximate descriptions for dynamics on successively smaller energy scales. These effective Hamiltonians involve “superspins”: two-level collective degrees of freedom constructed from (anti)aligned microscopic spins. Conserved densities can then be understood as relaxing via coherent collective spin flips. For the well-studied simpler case of randomly interacting nearest-neighbor XX+YY chains, the superspins reduce to single spins. Our formalism also leads to a numerical method capable of simulating the dynamics up to an otherwise inaccessible combination of large system size and late time. Focusing on disorder-averaged infinite-temperature autocorrelation functions, in particular the spin survival probability Sp¯(t), we demonstrate quantitative agreement between our algorithm and exact diagonalization (ED) at low but nonzero frequencies. Such agreement holds for chains with nearest-neighbor, next-nearest-neighbor, and long-range dipolar interactions. Our results indicate decay of Sp¯(t) slower than any power law and feature no significant deviation from the ∼1/ln2(t) asymptote expected from the infinite-randomness fixed-point of the nearest-neighbor model. We also apply the RSRG-X formalism to two-dimensional long-range systems of moderate size and find slow late-time decay of Sp¯(t).

Zhao, Yi J↗
DOE OSTI2024

Effects of mosaic crystal instrument functions on x-ray Thomson scattering diagnostics

Mosaic crystals, with their high integrated reflectivities, are widely employed in spectrometers used to diagnose high energy density systems. X-ray Thomson scattering (XRTS) has emerged as a powerful diagnostic tool of these systems, providing in principle direct access to important properties such as the temperature via detailed balance. However, the measured XRTS spectrum is broadened by the spectrometer instrument function (IF), and without careful consideration of the IF one risks misdiagnosing system conditions. Here, we consider in detail the IF of 40 and 100 μm mosaic Highly Annealed Pyrolytic Graphite crystals, and how the broadening varies across the spectrometer in an energy range of 6.7–8.6 keV. Notably, we find a strong asymmetry in the shape of the IF toward higher energies. As an example, we consider the effect of the asymmetry in the IF on the temperature inferred via XRTS for simulated 80 eV CH plasmas and find that the temperature can be overestimated if an approximate symmetric IF is used. We, therefore, expect a detailed consideration of the full IF will have an important impact on system properties inferred via XRTS in both forward modeling and model-free approaches.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Helium-4 gravitational form factors: Exchange currents

We evaluate the leading exchange corrections to the helium-4 gravitational form factors (GFFs) to momenta of the order of the nucleon mass. We use both the K-harmonic method with simple pair nucleon potential, and a Jastrow trial function using the Argonne 𝑣 14 potential, to evaluate the helium-4 GFFs. The exchange current contributions include the pair interaction, plus the seagull and the pion exchange interactions, modulo the recoil corrections. To estimate the off-shellness of the pion nucleon coupling in this momenta range, we discuss the results using either the pseudoscalar (PS) or pseudovector (PV) pion-nucleon couplings. When the PV coupling is used, the pair diagram contribution is higher order in the nonrelativistic expansion. The results for the helium-4 A-GFF are comparable to those given by the impulse approximation, especially for the PS coupling using both the K-harmonic method and variational method. The exchange current contributions with the PS coupling for the charge form factor of helium-4, yield better agreement with the existing data over a broad range of momenta, especially when the Argonne 𝑣 14 potential including the D-wave admixture is used.

A ≤ 5↗
DOE OSTI2025

Acceptance dependence of factorial cumulants, long-range correlations, and the antiproton puzzle

We analyze joint factorial cumulants of protons and antiprotons in relativistic heavy-ion collisions and point out that they obey the scaling Ĉnmp,p¯∝〈Np〉n〈Np¯〉m as a function of acceptance when only long-range correlations are present in the system, such as global baryon conservation and volume fluctuations. This hypothesis can be directly tested experimentally without the need for corrections for volume fluctuations. We show that if correlations among protons and antiprotons are driven by global baryon conservation and volume fluctuations only, the equality Ĉ2p/〈Np〉2=Ĉ2p¯/〈Np¯〉2 holds for large systems created in central collisions. We point out that the experimental data of the STAR Collaboration from phase I of the Relativistic Heavy Ion Collider (RHIC) beam energy scan (BES) are approximately consistent with the scaling Ĉnmp,p¯∝〈Np〉n〈Np¯〉m, but the normalized antiproton correlations are stronger than those of protons, −Ĉ2p¯/〈Np¯〉2>−Ĉ2p/〈Np〉2. Existing theoretical baselines, based on global baryon conservation and volume fluctuations, cannot explain the data, which we refer to as the antiproton puzzle. We also discuss high-order factorial cumulants which can be measured with sufficient precision within phase II of RHIC-BES.

Bzdak, Adam↗
DOE OSTI2024

Electron impact ionization in dense plasmas

Here, the distorted-wave with exchange (DWE) method is employed to evaluate electron impact ionization cross sections in dense electron–ion plasmas. Bound and continuum electron wave functions are obtained from a non-relativistic average-atom code. Plots of DWE cross sections are presented for 1s electrons in Li and Be plasmas and 2p electrons in Na and Mg plasmas. For each of these elements, cross sections are evaluated at metallic density in a range of temperatures from 10 to 100 eV and at their respective melting points. Resonances in the cross sections appear near the incident energy threshold at high temperatures. The origin of these resonances is discussed. In general, the distorted wave (DW) method without exchange is found to be a good approximation to the DWE method for electron impact ionization calculations. In the resonance region, however, exchange effects are found to be very important and cannot be neglected.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Robustness of the smartpixels classifier for different simulated sensor geometries and non-ideal detector conditions

Pixel tracking detectors at upcoming collider experiments will see unprecedented charged-particle densities. Real-time data reduction on the detector will enable higher granularity and faster readout, possibly enabling the use of the pixel detector in high-rate online event selection, such as the ATLAS or CMS first-level trigger systems. This data reduction can be accomplished with a neural network (NN) in the readout chip bonded with the sensor that recognizes and rejects tracks with low transverse momentum (p T ) based on the geometrical shape of the charge deposition (“cluster”). To design viable detectors for deployment, the dependence of the NN as a function of the sensor geometry, external magnetic field, irradiation, and noise must be understood. In this paper, we present first studies of the efficiency and data reduction for planar pixel sensors exploring these parameters. For the CMS HL-LHC sensor geometry, we obtain a signal efficiency of (91.9 ± 0.7)% and a data reduction of (29.7 ± 1.0)%. A smaller sensor pitch in the bending direction improves the p T discrimination, but a larger pitch can be partially compensated with detector thickness. Any accumulated radiation damage also changes the cluster shape, reducing the signal efficiency compared to the baseline by approximately 30–60% in absolute terms, but nearly all of the performance can be recovered through retraining of the network and updating the weights. Finally, the impact of noise was investigated, and retraining the network on noise-injected datasets was found to maintain performance within 6% of the baseline network trained and evaluated on noiseless data. •ASIC-compatible track-momentum classifier is robust in realistic detector conditions.•About 90% signal efficiency and 30% data reduction per layer for CMS HL-LHC geometry.•Single-layer signal efficiency increases for smaller pixel pitch or thicker sensors.•Performance with noise or after radiation damage mostly recovered by retraining.

Shekar, Danush [Illinois U., Chicago] (ORCID:00000↗
DOE OSTI2024

Voltage-Dependent First-Principles Barriers to Li Transport within Li-Ion Battery Solid Electrolyte Interphases

Charging a Li-ion battery requires Li-ion transport between the cathode and the anode. This Li-ion transport is dependent on (among other factors) the electrostatic environment that the ion encounters within the solid electrolyte interphase (SEI), which separates the anode from the surrounding electrolyte. A previous first-principles work has illuminated the reaction barriers through likely atomistic SEI environments but has had difficulty accurately reflecting the larger electrostatic potential landscape that an ion encounters moving through the SEI. In this work, we apply the recently developed quantum continuum approximation (QCA) technique to provide an equilibrium electronic potentiostat for first-principles interface calculations. Using QCA, we calculate the potential barrier for Li-ion transport through LiF, Li 2 O, and Li 2 CO 3 SEIs along with LiF–LiF and LiF–Li 2 O grain boundaries, all paired with Li metal anodes. Here, we demonstrate that the SEI potential barrier is dependent on the electrochemical potentials of the anode in each system. Finally, we use these techniques to estimate the change in the diffusion barrier for a Li ion moving in a LiF SEI as a function of the anode potential. We find that properly accounting for interface and electronic voltage effects significantly lowers reaction barriers compared with previous literature results.

25 ENERGY STORAGE↗
DOE OSTI2025

High-dynamic-range quantum sensing of magnons and their dynamics using a superconducting qubit

Magnons, the quanta of collective spin excitations in magnetic materials, may enable functionalities, such as nonreciprocity and transduction in hybrid quantum devices. To assess the potential of such applications, it is necessary to understand magnon dynamics beyond the simple harmonic oscillator regime, where theory predicts effects like population-dependent damping and quantum fluctuations in the form of magnon shot noise. Probing these phenomena requires sensors with high sensitivity and the ability to resolve magnon properties across different excitation regimes. Here, we demonstrate accurate and sensitive detection of magnon population and decay over a wide range of occupation numbers. We use a superconducting qubit to probe magnons in a ferrimagnet over approximately 2000 excitations. Using qubit control and parametrically induced qubit-magnon interactions, we demonstrate few-excitation sensitive detection of magnons with a dynamic range of approximately 30 dB, and are able to accurately resolve their decay with few-ns sensitivity. These capabilities offer a powerful and practical technique for probing magnon dynamics in or beyond the linear regime over a wide range of excitations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗