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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

3D Printing ofThermally Responsive Shape Memory LiquidCrystalline Epoxy Networks

Abstract A two-component liquid crystalline epoxy network (LCEN) with shape memory behavior was developed and evaluated as a candidate material for 3D printing. The cure kinetics of the uncured material and the shape memory properties of the cured LCEN were investigated by using parallel plate rheology and dynamic mechanical analysis, respectively. A commercially available fumed silica additive was introduced to the neat, uncured material to improve the rheological properties for 3D printing. The addition of fumed silica was found to increase the yield stress, shear-thinning behavior, and toughness of the uncured epoxy ink. Polarized light microscopy, differential scanning calorimetry, and wide-angle X-ray scattering measurements between the neat and additive-modified LCEN suggested a reduction in liquid crystalline alignment in the modified LCEN, owing to interactions between crystalline domains and fumed silica, which in turn influenced the mechanical behavior. Overall, the additive was found to be successful in preserving the shape memory properties of LCEN while improving its printability.

Chemistry↗
DOE OSTI2023

AutoSourceID-Classifier: Star-galaxy classification using a convolutional neural network with spatial information

Aims.Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification’s reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images. Methods.The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results. Results.We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C’s direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy.

Astronomy & Astrophysics↗
DOE OSTI2026

Phase diagram and spectroscopic signatures of a supersolid in the quantum ising magnet K 2 Co(SeO 3 ) 2

Supersolid phases are quantum-entangled states of matter exhibiting the dual characteristics of superfluidity and solidity. Theory predicts that hard-core bosons on a triangular lattice can form such phases at half filling and near complete filling. Leveraging an exact mapping between bosons and spin-$\frac{1}{2}$ degrees of freedom, here we show that these phases are realized in the triangular-lattice antiferromagnet K 2 Co(SeO 3 ) 2 . At zero field, neutron diffraction reveals the development of quasi-two-dimensional $\sqrt3$ x $\sqrt3$ magnetic order with Z 3 translational symmetry breaking (solidity), though with reduced amplitude indicating strong quantum fluctuations. These fluctuations manifest as equidistant bands of continuum neutron scattering, where the lowest-energy mode is gapless at K ($\frac{1}{3}$ $\frac{1}{3}$), consistent with broken U(1) spin rotational symmetry (superfluidity). For c-axis-oriented magnetic fields near saturation, we find a second phase consistent with a high-field supersolid. These two supersolids are separated by a pronounced 1/3 magnetization plateau phase that supports coherent spin waves, from which we determine the underlying spin Hamiltonian.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Envelope-driven comfort risk in residential demand response

Residential demand response (DR) is a valuable resource for grid reliability, but remains challenging because the highly heterogeneous residential building stock leads to widely varying and hard-to-predict load and comfort responses during DR events. Although prior research has estimated the technical potential of DR-capable technologies for achieving energy demand savings, little is known about how they affect thermal comfort. In particular, it remains unclear how indoor thermal conditions due to DR depend on the thermal envelope characteristics of the housing stock. To address this gap, this study provides a systematic, location-specific assessment of indoor thermal performance during DR-events across the US housing stock using both typical DR weather data and detailed building metadata. We evaluate how envelope characteristics influence indoor temperatures during realistic simulated summer and winter DR events across 37 US locations, applying both temperature threshold and rate of temperature change criteria to estimate region-level probabilities of discomfort. Additionally, we show the impact of distinct weather patterns that intensify or abate thermal stress on comfort outcomes. Results show a near-universal overheating risk in summer DR events, where comfort outcomes are strongly influenced by rapid risk of comfort violations. In contrast, overall winter DR discomfort risk is lower, risk escalation is more gradual and shows greater sensitivity to event duration. These findings offer a data-driven quantification of comfort risk across diverse climates and building envelopes, demonstrating the need for region-specific DR scheduling and discomfort mitigation strategies tailored to local weather patterns and the performance of existing residential buildings.

Demand response↗
DOE OSTI2026

Aerosol-deep convection interaction based on joint cell-thermal tracking in Large Eddy Simulations during the TRACER campaign

In cumulus clouds, aerosol concentrations control cloud droplet concentrations, modifying cloud radiative properties, precipitation processes, and cloud electrification. However, mechanisms of aerosol-deep convection interactions are not well understood due to complex cloud dynamics and microphysics. We investigate the interaction of aerosols with isolated deep convection using Large Eddy Simulations of two cases during the TRacking Aerosol Convection interactions ExpeRiment (TRACER) near Houston, Texas, using a joint cell-thermal tracking algorithm. Cumulus thermals are droplet generators, since supersaturation and droplet nucleation coincide with thermal centers, where the strongest updrafts occur. Primary ice crystal formation does not take place inside thermals, but at layers where previous thermals detrained moisture. As subsequent thermals containing supercooled droplets penetrate these layers, hail and graupel form at or near these thermals. Higher aerosol concentrations result in higher droplet concentrations that suppress drizzle, delay warm rain processes, and transport more moisture aloft. This increases snow and ice amount, as well as graupel and hail, leading to more lightning. Polluted thermals initiate at slightly higher altitudes, and are slightly larger and faster, suggesting a weak invigoration. We also find more thermals per cell, but fewer isolated cells, since convection is more aggregated and intense, especially near the end of the 24 h simulation. Non-linear mesoscale feedback likely triggered by temperature and moisture responses to aerosol-thermal interactions causes the aggregation. Time-lagged aerosol-reinitialization experiments show that the mesoscale response is the predominant forcing for the invigoration. These changes happen within one day, on a smaller scale than previously suggested.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Three-dimensional dispersion in the type-II Dirac semimetals PtTe 2 and PdTe 2 revealed through circular dichroism in angle-resolved photoemission spectroscopy

PtTe 2 and PdTe 2 are among the first transition metal dichalcogenides that were predicted to host type-II Dirac fermions, exotic particles prohibited in free space. These materials are layered and air stable, which makes them top candidates for technological applications that take advantage of their anisotropic magnetotransport properties. Here, in this work, we provide a detailed characterization of the electronic structure of PtTe 2 and PdTe 2 using angle-resolved photoemission spectroscopy (ARPES) and density functional theory calculations, offering an alternative interpretation for one of the Dirac-like dispersions in these materials. Through the use of circularly polarized light, we report a different behavior of such dispersion in PdTe 2 compared to PtTe 2 , that we relate to a symmetry analysis of the dipole matrix element. Such analysis reveals a link between the observed circular dichroism and the different momentum-dependent terms in the dispersion of these two compounds, despite their close similarity in crystal structure. Additionally, our data show a clear difference in the circular dichroic signal for the type-II Dirac cones characteristic of these materials, compared to their topologically protected surface states. Our paper provides a useful reference for the ARPES characterization of other transition metal dichalcogenides with topological properties and illustrates the use of circular dichroism as a guide to identify the topological character and attributes of two otherwise equivalent band dispersions.

angle-resolved photoemission spectroscopy↗
DOE OSTI2026

A Permanently Porous Chalcogen-Bonded Organic Framework

The nature of connectivity between constituent atomic or molecular building blocks is fundamental in shaping the properties and functionality of materials. The extrapolation of emergent interatomic interactions to enable functional materials has driven transformative technological advancements. However, the bonding interactions used in material design have been largely static since the emergence of dynamic covalent chemistry ~30 years ago. Here we demonstrate that non-covalent chalcogen bonding (Ch-bonding) is a distinct mode of interatomic connectivity for constructing functional materials by design. This is established by leveraging self-complementary assembly of 1,2,5-telluradiazole moieties to construct a honeycomb-type permanently porous Ch-bonded organic framework, assembled and stabilized solely through non-covalent Te...N contacts. Empirical and computational studies of electronic structure, structural healing and lattice dynamics highlight the pi-type electronic communication, controlled assembly and modulated lattice dynamics in Trip3Tez-I arising directly from the unique nature of the Te...N Ch-bonding that holds substantial implications for next generation crystalline semiconductors. In addition to introducing a distinct class of permanently porous frameworks, this work establishes Ch-bonding as a programmable molecular tool for constructing functional materials with distinct properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Assembly bias and local Primordial non-Gaussianity from DESI DR1 quasars

The analysis of the large-scale clustering of quasars (QSO) observed by the Dark Energy Spectroscopic Instrument (DESI) represents a promising avenue for constraining local Primordial non-Gaussianity (PNG), parameterized by f NL . The signal to be constrained is the scale-dependent bias induced in the 2-point clustering of the considered tracer sample. The resulting constraints on f NL , however, are fully degenerate with the local PNG bias parameter b ϕ , dependent on the assembly bias parameter p. Using IllustrisTNG hydrodynamical simulations, we select a QSO sample reflecting the selection criteria and properties of DESI QSOs, and provide a robust prior for p, and thus for b ϕ , building on the findings of Fondi et al. 2024. We find a distribution with mean p̅ ≃ 1.4 with weak redshift dependence, stable to selection noise and consistent with the expected recent merger history typical of quasar-hosting halos. By comparing with the CAMELS simulations we demonstrate that this prior is robust to astrophysical assumptions and cosmic variance. Finally, applying this prior to the DESI DR1 dataset, we derive updated constraints on local PNG, obtaining f NL = -3.3±9.2.

cosmological parameters from LSS↗
DOE OSTI2025

Ultra-light antennas via charge programmed deposition additive manufacturing

Abstract The demand for lightweight antennas in 5 G/6 G communication, wearables, and aerospace applications is rapidly growing. However, standard manufacturing techniques are limited in structural complexity and easy integration of multiple material classes. Here we introduce charge programmed multi-material additive manufacturing platform, offering unparalleled flexibility in antenna design and the capability for rapid printing of intricate antenna structures that are unprecedented or necessitate a series of fabrication routes. Demonstrating its potential, we present a transmitarray antenna composed of an interconnected, multi-layered array of dielectric/conductive S-ring unit cells, reducing 94% mass of conventional antenna configurations. A fully printed circular polarized transmitarray system fed by a source and a Risley prism antenna system operating at 19 GHz both show close alignment between testing results and numerical simulations. This printing method establishes a universal platform, propelling discovery of new antenna designs and enabling data-driven design and optimizations where rapid production of antenna designs is crucial.

Science & Technology - Other Topics↗
DOE OSTI2024

Development of Electrolytes under Lean Condition in Lithium–Sulfur Batteries

Lithium–sulfur (Li–S) batteries stand out as one of the promising candidates for next-generation electrochemical energy storage technologies. A key requirement to realize high-specific-energy Li–S batteries is to implement low amount of electrolyte, often characterized by the electrolyte/sulfur (E/S) ratio. Low E/S ratio aggravates the known challenges for Li–S batteries and introduces new ones originated from the high concentration of polysulfides in limited electrolyte reservoir. Here, in this review, the connections between the fundamental properties of electrolytes and the electrochemical/chemical reactions in Li–S batteries under lean electrolyte condition are elucidated. The emphasis is on how the solvating properties of the electrolyte affect the fate of polysulfides. Built upon the mechanistic analysis, different strategies to design lean electrolytes to improve the overall process of Li–S reactions and Li anode protection are discussed.

25 ENERGY STORAGE↗
DOE OSTI2024

The Active Asteroids Citizen Science Program: Overview and First Results

Abstract We present the Citizen Science program Active Asteroids and describe discoveries stemming from our ongoing project. Our NASA Partner program is hosted on the Zooniverse online platform and launched on 2021 August 31, with the goal of engaging the community in the search for active asteroids—asteroids with comet-like tails or comae. We also set out to identify other unusual active solar system objects, such as active Centaurs, active quasi-Hilda asteroids (QHAs), and Jupiter-family comets (JFCs). Active objects are rare in large part because they are difficult to identify, so we ask volunteers to assist us in searching for active bodies in our collection of millions of images of known minor planets. We produced these cutout images with our project pipeline that makes use of publicly available Dark Energy Camera data. Since the project launch, roughly 8300 volunteers have scrutinized some 430,000 images to great effect, which we describe in this work. In total, we have identified previously unknown activity on 15 asteroids, plus one Centaur, that were thought to be asteroidal (i.e., inactive). Of the asteroids, we classify four as active QHAs, seven as JFCs, and four as active asteroids, consisting of one main-belt comet (MBC) and three MBC candidates. We also include our findings concerning known active objects that our program facilitated, an unanticipated avenue of scientific discovery. These include discovering activity occurring during an orbital epoch for which objects were not known to be active, and the reclassification of objects based on our dynamical analyses.

Astronomy & Astrophysics↗
DOE OSTI2024

Direct Visualization of Defect‐Controlled Diffusion in van der Waals Gaps

Abstract Diffusion processes govern fundamental phenomena such as phase transformations, doping, and intercalation in van der Waals (vdW) bonded materials. Here, the diffusion dynamics of W atoms by visualizing the motion of individual atoms at three different vdW interfaces: hexagonal boron nitride (BN)/vacuum, BN/BN, and BN/WSe 2 , by recording scanning transmission electron microscopy movies is quantified. Supported by density functional theory (DFT) calculations, it is inferred that in all cases diffusion is governed by intermittent trapping at electron beam‐generated defect sites. This leads to diffusion properties that depend strongly on the number of defects. These results suggest that diffusion and intercalation processes in vdW materials are highly tunable and sensitive to crystal quality. The demonstration of imaging, with high spatial and temporal resolution, of layers and individual atoms inside vdW heterostructures offers possibilities for direct visualization of diffusion and atomic interactions, as well as for experiments exploring atomic structures, their in situ modification, and electrical property measurements of active devices combined with atomic resolution imaging.

Chemistry↗
DOE OSTI2026

Visualizing Millisecond Atomic Dynamics of Nanocrystals in Liquid

Atomic structures of nanomaterials are inherently dynamic and continuously reshaped through interactions with chemical species and external stimuli. Such dynamics are further amplified as the size and dimensionality of nanomaterials decrease. Despite advances in analytical methods, it remains challenging to capture the structural dynamics of nanomaterials in reactive environments with both atomic spatial resolution and commensurate temporal resolution. Here, in this study, we directly visualize atomic-scale dynamics of gold (Au) nanocrystals in reactive liquid environments with millisecond-speed liquid-cell electron microscopy (EM) and deep-learning denoising. We uncover reversible fluctuations in the local crystallinity of Au nanocrystals dependent on the surrounding chemical environment. These transient fluctuations, driven by interactions at nanocrystal–liquid interfaces, critically influence the dissolution kinetics and grain boundary relaxation. By overcoming the spatiotemporal limitations in conventional liquid-cell EM, our findings provide insights into how transient nanoscale structures dictate the stability and reactivity of nanomaterials.

Kang, Sungsu [University of Chicago, IL (United St↗
DOE OSTI2026

Adapting High-Resolution X-Ray Microcalorimeter Spectrometers to Transform MFE Plasma Diagnostics

The aim of this project was to begin the transformation of magnetic fusion energy (MFE) X-ray diagnostics by applying detector technology developed over the past several decades by the astrophysics community. We installed and operated an X-ray microcalorimeter detector system under fusion-relevant plasma conditions at the Madison Symmetric Torus (MST). X-ray microcalorimeter spectrometers combine the best characteristics of instrumentation currently available on fusion devices: the high spectral resolution of crystal spectrometers (2 eV) and broadband coverage provided by pulse-height analysis systems. These spectrometers have small port-access requirements, a key advantage for future MFE experiments. This new plasma diagnostic technique will satisfy the need for multispecies impurity ion data by providing absolute measurements of impurity core accumulation, and it will provide the core impurity ion temperature. This project was a joint effort between Lawrence Livermore National Laboratory (LLNL) and researchers at the Wisconsin Plasma Physics Laboratory (WiPPl) at the University of Wisconsin–Madison (UW–Madison). Megan E. Eckart is the principal investigator at LLNL, which is funded separately from UW–Madison. This final report fulfills the reporting obligation of the UW–Madison effort.

Den Hartog, Daniel J. [Department of Physics, Univ↗
DOE OSTI2026

Visualization of the surface distribution of photocatalytic activity at the anatase/rutile TiO2 interface using X-ray photoelectron emission microscopy

We applied X-ray photoelectron emission microscopy (XPEEM) to visualize the surface distribution of photocatalytic activity at the anatase/rutile (A/R) interface of titanium dioxide. Acetic acid was adsorbed on the surface, and its decomposition and desorption reactions under ultraviolet light irradiation were monitored by observing C 1s spectra, enabling direct observation of the spatial distribution of photocatalytic activity. Complementary crystal structure information was obtained using spatially resolved low-energy electron diffraction, low-energy electron microscopy, X-ray absorption spectroscopy, and micro-focused Raman spectroscopy. Comparison with these structural data allowed for the evaluation of the photocatalytic activity as a function of the distance from the A/R interface. The activity is enhanced in the vicinity of the interface and gradually decreases toward both the anatase and rutile regions. These results demonstrate that XPEEM is an effective technique for spatially resolved mapping of photocatalytic activity, which has\\r\\npreviously been inaccessible using conventional characterization techniques.

25 ENERGY STORAGE↗
DOE OSTI2025

Exact block encoding of imaginary time evolution with universal quantum neural networks

We develop a constructive approach to generate quantum neural networks capable of representing the exact thermal states of all many-body qubit Hamiltonians. The Trotter expansion of the imaginary time propagator is implemented through an exact block encoding by means of a unitary, restricted Boltzmann machine architecture. Marginalization over the hidden-layer neurons (auxiliary qubits) creates the nonunitary action on the visible layer. Then, we introduce a unitary deep Boltzmann machine architecture in which the hidden-layer qubits are allowed to couple laterally to other hidden qubits. We prove that this wave-function is closed under the action of the imaginary time propagator and, more generally, can represent the action of a universal set of quantum gate operations. We provide analytic expressions for the coefficients for both architectures, thus enabling exact network representations of thermal states without stochastic optimization of the network parameters. In the limit of large imaginary time, the yields the ground state of the system. The number of qubits grows linearly with the number of interactions and total imaginary time for a fixed interaction order. Both networks can be readily implemented on quantum hardware via midcircuit measurements of auxiliary qubits. If only one auxiliary qubit is measured and reset, the circuit depth scales linearly with imaginary time and number of interactions, while the width is constant. Alternatively, one can employ a number of auxiliary qubits linearly proportional to the number of interactions, and circuit depth grows linearly with imaginary time only. Every midcircuit measurement has a postselection success probability, and the overall success probability is equal to the product of the probabilities of the midcircuit measurements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Storing Affordability: Battery Storage as an Asset to Reduce Data Center Cost Shifts

This report examines how battery energy storage systems (BESS) can help utilities accommodate large load growth while protecting affordability for existing ratepayers. Rapid growth in electricity demand from artificial intelligence (AI) data centers is straining the U.S. grid. Furthermore, many new data centers are entering rural markets, which could offer economic benefits but may also pose implementation challenges for smaller utilities. At the same time, retail electricity prices are increasing faster than inflation, elevating customer affordability as a key challenge. While data centers have not been the primary driver of increases in residential prices to date, they have pushed wholesale energy and capacity prices higher in several markets. Fundamental utility cost-allocation principles show that data center growth can be rate-positive for existing customers only if new peak demand grows faster than the costs a utility must incur to serve it. Several factors, including a utility’s degree of wholesale market exposure, forecast uncertainty and stranded-asset risk, and tariff design can determine the outcome of load growth on retail rates. Energy storage can make several affordability contributions in the face of this landscape of uncertainty and market volatility, including deferral of higher-cost grid investments through improved utilization of existing assets and flexibility of new large loads, insulation from volatile wholesale prices through peak shaving, and reliability support to address grid risks stemming from the behavior of AI data center loads. Different potential BESS deployment pathways—utility-scale front-of-the-meter systems, aggregated small-scale storage installations, and data center-sited behind-the-meter storage—are compared against each other and against conventional capacity alternatives. This framework is intended as a conceptual resource to utilities, particularly smaller public utilities with rural service territories, who may be considering the role that energy storage can play in insulating existing ratepayers from data center cost shifts.

25 ENERGY STORAGE↗
DOE OSTI2025

Environmental drivers of spatial variation in tropical forest canopy height: Insights from NASA’s GEDI spaceborne LiDAR

Forest canopy height is a fundamental ecosystem property—influencing patterns of forest carbon storage and forest ecosystem responses to climate variability and change. Previous studies have analyzed environmental drivers influencing spatial variation in canopy height at landscape-to-regional scales; however, far less is known about the environmental determinants underlying regional and global scale variation in forest canopy height. Using the canopy height metrics products from Global Ecosystem Dynamics Investigation (GEDI), a space-borne Light Detection and Ranging (LiDAR) instrument specifically designed to characterize forest structure, we analyze the environmental correlates of spatial variation of global tropical forest canopy height. Our study demonstrates that climate, topography, and soil properties account for 75% of the variation in tropical forest canopy height. Elevation, dry season length, and solar radiation are the most important drivers in determining canopy height both locally and regionally. These results emphasize the vulnerability of tropical forest structure to ongoing changes in the earth’s climate and provide a valuable empirical baseline for tropical forest management.

Science & Technology - Other Topics↗