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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 OSTI2026

Prime Time for Model-Predictive Control? Assessing the Technical and Market Readiness of Advanced Controls in Buildings

Despite three decades of extensive research and field testing that have consistently validated the benefits of Model Predictive Control (MPC) in building applications, the technology has seen limited market adoption. This paper evaluates the readiness of MPC for widespread deployment, showcases recent demonstrations and field tests across diverse building types, including residential, small commercial, large commercial, and campus settings. Our results demonstrate that MPC can optimize system operations to achieve load shifting, minimize curtailment of on-site generation, and reduce energy costs by up to 80 %, while maintaining or improving occupant comfort. We also show that MPC can effectively control large assets, such as MW-sized thermal storage systems, and respond to dynamic pricing signals. However, achieving scale remains difficult due to labor-intensive workflows, reliance on a “PhD-in-the-loop” for MPC design and maintenance, susceptibility to fragile data infrastructure, and persistent workforce education and acceptance barriers. To bridge this gap, we outline a transition from bespoke, labor intensive prototypes toward streamlined, segment-targeted deployment strategies that leverage model templates, semantic tools, and generative AI. By automating control configuration and reducing engineering effort, these recommendations provide a pathway for transforming successful research demonstrations into scalable, market ready solutions for MPC-based controls.

Pritoni, Marco↗
DOE OSTI2026

Linking Community‐Climate Disequilibrium to Ecosystem Function

Turnover in species composition often lags behind the pace of climate change, resulting in mismatches between climate and communities. However, the impact of these community‐climate disequilibria on ecosystem functions is rarely considered, and current methods for measuring disequilibria assume that species ranges were, until recently, in equilibrium with climate. Here, in this work, we develop a simple theoretical model to address both of these problems by linking community‐climate disequilibrium with ecosystem functioning. We show how disequilibrium can impair functioning in the near‐term even when climate change is expected to enhance functioning in the long‐term. Responses are most likely to change over time in communities where turnover is slow, the impact of disequilibrium counteracts the direct effects of climate on ecosystem function, and pre‐existing disequilibrium is large. These findings emphasise the importance of precise and unbiased estimates of community‐climate disequilibria for improving ecological forecasts. By fitting our model to time series of both climate and ecosystem function from a metacommunity simulation, we show the potential for community‐climate disequilibrium to be inferred without direct knowledge about species' distributions or climatic tolerances. We end by outlining a research agenda to apply dynamic disequilibrium concepts and test novel hypotheses across diverse ecosystems.

climate change↗
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 OSTI2026

Multi-modal dynamic radiography using short-pulse laser-generated probe beams

Radiography is an important tool for the interrogation of dynamic experiments in the fields of dynamic properties of materials, and in condensed matter, high explosive, and high-energy-density physics. Multi-modal radiography advances the hypothesis that combining the information delivered by multiple radiographic modalities can lead to more constrained (improved) “reconstruction” of the scene than can be obtained from a single probe. We identify four modalities: multi-probe, time sequence, multi-view, and multi-messenger. Multi-probe radiography is a promising candidate for a next-generation dynamic radiographic facility. High-energy X-rays are the most frequently used probe for dynamic radiography, although recent developments show the utility of proton (pRad), electron (eRad), and neutron probe beams. Because each probing species interacts with material in the radiographic scene through quantitatively different mechanisms, each returns independent information about the scene, which can add extra constraints to the reconstruction process. How to conduct detailed, quantitative “co-analysis” of multiple data streams remains an area of active research. Multi-beam, short-pulse, laser-generated probes offer sufficient dose, an appropriate spectrum, and appropriate spatio-temporal resolution to produce high-quality dynamic radiographs. This paper reports on technology development to advance the state of the art of multi-modal/multi-probe radiography and the pursuit of both deterministic and inferential (AI/ML assisted) co-analysis methodologies to produce more constrained reconstructions from multi-modal data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Polarized target nuclear magnetic resonance measurements with deep neural networks

Continuous-wave Nuclear Magnetic Resonance (CW-NMR) operated in constant-current mode has served as a foundational technique for polarization measurement in solid-state dynamically polarized targets within nuclear and high-energy physics experiments for several decades, and it remains an essential tool. Conventional Q-meter-based phase-sensitive detection is critical for precise real-time determination of target polarization during scattering runs. However, the accuracy and reliability of these measurements are frequently compromised by elevated noise levels, baseline drift, and systematic uncertainties arising from signal isolation and fitting, ultimately degrading the overall experimental figure of merit. In this work, we report the first successful application of neural network architectures to continuous-wave NMR polarization metrology. By leveraging advanced machine learning techniques for signal extraction and denoising, we achieve a substantial reduction of fitting uncertainties under a variety of realistic simulated and experimental conditions. These improvements translate directly into more robust real-time (online) polarization monitoring and higher precision in subsequent offline analysis. By reducing analysis-induced uncertainty, the resulting methodology can improve the effective figure of merit for scattering experiments employing dynamically polarized targets and provides a new toolset for NMR-based polarimetry in high-energy and nuclear physics.

Metrology↗
DOE OSTI2025

Advanced Model Development for Large Eddy Simulation of Oxy-Combustion and Supercritical Carbon Dioxide Power Cycles

A joint experimental and numerical study is performed to observe the characteristics of a supercritical carbon dioxide turbulent mixing layer in the presence of strong nonlinearities in the thermodynamic and transport properties. A bespoke experimental setup is designed and employed for this purpose and provides insight into macroscopic mixing behavior. The mixing is experimentally observed using two techniques: shadowgraphy and spontaneous Raman scattering. Qualitative and quantitative intensity fields obtained via these techniques yield instantaneous and mean density data. Spanwise temperature data is also collected using analogue resistance temperature detectors. These measurements are used to quantify the level of mixed material within the field. The experimental data are supplemented by a companion high-fidelity numerical study. The numerical results are obtained through fully resolved, three-dimensional direct numerical simulation. The numerical dataset permits observation of the near-field mixing characteristics, which are difficult to measure experimentally due to the rapid dynamics and sharp thermophysical gradients in this area. Qualitative field visualizations are presented, followed by quantitative mixed material results and observations regarding thermodynamic property trends at select locations within the field. One-dimensional spectra of the turbulent kinetic energy and solenoidal dissipation are provided to observe the spectral characteristics of the flow. Reynolds stress anisotropy is analyzed graphically through anisotropy invariance maps (Lumley triangles). The mixing quantification, spectral data and anisotropy analysis of a flow at these thermodynamic conditions represent the main outcomes of the work.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

Anomalous lattice expansion of bcc Ta in helium-loaded diamond anvil cells

Anomalous lattice expansion of bcc Ta is observed in helium-loaded diamond anvil cell (DAC) experiments near 6 GPa and above 400 K, while co-loaded W, Mo, and Au exhibit normal thermal expansion. The Ta volume expansion increases with temperature, reaching ~14% near 650 K before plateauing, and is largely retained after recovery to ambient conditions. Time-resolved measurements at 500 K reveal progressive expansion over several hours, consistent with gradual, thermally activated He incorporation. The largely retained expansion during subsequent cooling and holding at 400 K indicates that the incorporated He is predominantly kinetically trapped. The data reveal two distinct regimes: below ~550 K, modest and spatially uniform expansion consistent with interstitial He trapping at isolated, randomly distributed vacancies; above ~550 K, He-vacancy cluster growth producing dramatically larger expansion, peak broadening, and a core–shell microstructure revealed by micron-resolution X-ray diffraction mapping. These results demonstrate that He is not always a passive pressure medium in DAC experiments and reveal a previously unrecognized regime of He-mediated lattice modification in Ta, complementing conventional ion-implantation studies relevant to nuclear and fusion structural materials.

Diamond anvil cell↗
DOE OSTI2026

Insights into elevated temperature tensile deformation mechanisms and kink banding in additively manufactured tungsten

Additive manufacturing (AM) potentially enables fabrication and repair of plasma facing components (PFCs) of tungsten. However, deformation mechanisms in AM-fabricated tungsten under service-relevant thermomechanical conditions remain unknown majorly due to challenges in achieving crack-free W. This study reveals the deformation mechanisms operative under tension at 800 °C and 1200 °C in the electron beam melting powder bed fusion (EBM-PBF) fabricated W. Textured columnar grains with mixed <001 >/<111 >|| build-direction were observed. Strong anisotropy in tensile properties persisted across test temperatures, and all specimens exhibited extensive deformation-induced banding phenomena. Grain boundary character analysis of the deformed specimens indicated that these deformation bands were kink bands with tilt grain boundaries prominently present at the band-matrix interface. Interestingly, the material within the kink bands rotated toward higher resolved shear stress, providing insights into the origins of kink band formation in body-centered cubic refractory metals. Intragranular misorientation axis analysis revealed that plasticity was dominated by {110} <111 > slip at 800 °C, whereas additional (213)[11⁢̄1] and (112)[11⁢̄1] slip systems activated at 1200 °C. A dense low-angle boundary networks observed near fractured surface indicated the onset of dynamic recrystallization. Results reveal plasticity governing mechanisms in AM-fabricated W under power plant-relevant conditions, and provide insights into kink band attributes in refractory metals.

Mayes, Riley [ORNL] (ORCID:000900089307010X)↗
NASA NTRSDate not supplied

A Radiometric Consistent Spectral Fingerprinting Algorithm for Continuity Products of Hyperspectral Sounders

A radiometric consistent climate fingerprinting methodology has been developed to derive long-term temperature, water vapor, cloud, trace gases, and surface skin temperature anomaly time series from the hyper-spectral sounder measurements of multiple platforms. The spectral fingerprinting methodology requires the use of radiative kernels that are radiometrically consistent with observations. Radiative kernels are built using space-time averaged Jacobians that are physically retrieved from observations under all sky conditions. The physical retrieval algorithm uses the Principal Component based Radiative Transfer Model (PCRTM) for the forward simulation. The incorporation of multiple scattering simulation in PCRTM allows the direct radiative relationship between single field-of-view (FOV) radiance observations and corresponding thermal dynamic variables including cloud properties to be established. Therefore, radiance ?closure? can be achieved under all-sky conditions by the fingerprinting scheme. This methodology has been used to derive climate anomalies from the space-time averaged spectra of AIRS/AMSU and CrIS/ATMS. The use of a consistent fingerprinting scheme provides an effective mean of generating continuity product by merging observations from different platforms and therefore facilitating the long-term climate trend study.

Wan Wu↗
DOE OSTI2026

Mechanisms of Alkali Ionic Transport in Amorphous Oxyhalides Solid State Conductors

Amorphous oxyhalides have attracted significant attention due to their relatively high ionic conductivity (1 mS cm –1 ), excellent chemical stability, mechanical softness, and facile synthesis routes via standard solid‐state reactions. These materials exhibit an ionic conductivity that is almost independent of the underlying chemistry, in stark contrast to what occurs in crystalline conductors. In this work, we employ machine learning interatomic potentials to construct large‐scale molecular dynamics trajectories encompassing hundreds of nanoseconds to obtain statistically converged transport properties. We find that the amorphous state consists of chain fragments of metal‐anion tetrahedra of various lengths. By analyzing the residence time of alkali cations migrating around tetrahedrally‐coordinated metals, we find that oxygen anions limit alkali diffusion. By computing the full Einstein expression of the ionic conductivity, we demonstrate that the alkali transference number of these materials is strongly influenced by distinct‐particles correlations, while alkali transport is dictated by uncorrelated self‐diffusion. By extending this analysis to chemical compositions AMX 2.5 O 0.75 , spanning different alkaline (A = Li, Na, K), metallic (M = Al, Ga, In), and halogen (X = Cl, Br, I) species, we clarify why the diffusion properties of these materials remain largely insensitive to variations in atomic isovalent chemistry.

amorphous materials↗
NASA NTRS2026

X-Ray Polarization of Z-Type Neutron Star Low-Mass X-Ray Binaries II. Spectropolarimetric Analysis

IXPE has provided for the first time detailed energy- and time-resolved X-ray polarimetry of Z-type neutron star low-mass X-ray binaries (NS-LMXBs) as they move along their color-color diagrams (CCDs). These sources can reach the highest polarization observed for NS-LXMBs in the 2–8 keV range when they move along the horizontal branch. In a previous paper, we characterized the spectral state of a sample of Z-sources using the CCD and estimated the polarization with model-independent analysis. Here, we present detailed spectropolarimetric analysis for each source on each branch using data from IXPE, NICER, and NuSTAR. The continuum X-ray emission of all the sources is well described with a combination of thermal accretion disk emission plus a harder Comptonized component. In addition, reflection features, in particular the relativistically broadened Fe Kα line, are observed for our sources, except GX 5–1. For most of the sources and branches, the main contribution to the X-ray emission and polarization is due to Comptonization: moving from the horizontal branch (HB) to the normal branch (NB), the polarization degree (PD) in the 2–8 keV band varies from about 6% to 3–4%, while the PD is loosely constrained in the flaring branch (FB), due to the shorter exposures. These PD values are significantly higher than theoretical expectations for typical spreading or boundary layer configurations. The polarization of the disk is generally lower (below 3%) but still higher than predictions for an electron scattering-dominated, plane-parallel atmosphere above the disk observed at the corresponding inclination. Moreover, the polarization angle (PA) of the disk seems to be significantly misaligned and not perpendicular to that of Comptonization. We find no correlation between the polarization signal and the inclination, nor with the contribution of reflected photons throughout the Z-track.

accretion↗
NASA NTRSDate not supplied

Pinned in Microgravity: How Colloidal Suspensions Inhibit Droplet Motion

Understanding the fundamental behavior of colloidal fluids in microgravity is critical for advancing material science, manufacturing, and biological processes. In this study we investigate the dynamics of a droplet containing colloidal suspension when ejected in short term microgravity. These conditions are generated using a 2.2 second drop tower. A custom droplet generator was designed to produce consistent size-controlled droplets containing passive colloidal particles. The particles are suspended in water and subsequently ejected out of a hydrophobic wedge under microgravity conditions, where the droplet ejection time can be predicted [Torres & Weislogel, 2021]. The ejection times will be compared with de-ionized water ejected from the same system to investigate the effects of change in density and surface tension caused by the colloids. Successful passive colloidal ejection will lay the foundation for active colloid research in the future.

colloids↗
DOE OSTI2024

Machine learning the electric field response of condensed phase systems using perturbed neural network potentials

Abstract The interaction of condensed phase systems with external electric fields is of major importance in a myriad of processes in nature and technology, ranging from the field-directed motion of cells (galvanotaxis), to geochemistry and the formation of ice phases on planets, to field-directed chemical catalysis and energy storage and conversion systems including supercapacitors, batteries and solar cells. Molecular simulation in the presence of electric fields would give important atomistic insight into these processes but applications of the most accurate methods such as ab-initio molecular dynamics (AIMD) are limited in scope by their computational expense. Here we introduce Perturbed Neural Network Potential Molecular Dynamics (PNNP MD) to push back the accessible time and length scales of such simulations. We demonstrate that important dielectric properties of liquid water including the field-induced relaxation dynamics, the dielectric constant and the field-dependent IR spectrum can be machine learned up to surprisingly high field strengths of about 0.2 V Å −1 without loss in accuracy when compared to ab-initio molecular dynamics. This is remarkable because, in contrast to most previous approaches, the two neural networks on which PNNP MD is based are exclusively trained on molecular configurations sampled from zero-field MD simulations, demonstrating that the networks not only interpolate but also reliably extrapolate the field response. PNNP MD is based on rigorous theory yet it is simple, general, modular, and systematically improvable allowing us to obtain atomistic insight into the interaction of a wide range of condensed phase systems with external electric fields.

Science & Technology - Other Topics↗
DOE OSTI2026

Thermal Reservoir Networks for Modularly Expandable Thermal Microgrids

The Department of Defense (DoD) faces the substantial challenge of cost-effectively retrofitting one to two installations per month, each comprising approximately 1,000 buildings, to improve resilience, reduce energy consumption, and enhance energy supply security. Achieving these objectives requires optimal system selection and effective risk mitigation during system integration. To address this need, we introduce Platform-Based Design (PBD), a structured, hierarchical methodology adapted from other industrial sectors to the domain of energy system retrofits. We demonstrate the effectiveness of PBD through a techno-economic feasibility study comparing geothermal-coupled thermal energy networks (TENs) with conventional energy systems for heating, cooling, and powering 17 buildings at Joint Base Andrews (JBA) in Maryland. Our analysis illustrates that the PBD approach enables rigorous, data-driven, sequential decision making, resulting in a family of Pareto-optimal systems, among which the TEN emerged as the most promising solution. The selected TEN design integrates geothermal borefields, heat recovery heat pumps, photovoltaic (PV) arrays, and battery storage. Compared to the baseline system – gas heating combined with air-source chillers – the proposed TEN reduces annual imported energy by 74% and peak electricity demand by 45%, achieves a levelized cost of energy of $\$0.210$/kWh, and substantially enhances resilience. Life-cycle costs increase by approximately 6%, and initial investment costs are about 2.5 times higher than the baseline. However, if central plant infrastructure, district loops, and utility-scale PV and battery systems are privately funded and operated, the initial investment would fall below the baseline system cost. Critical to achieving these significant performance improvements were detailed nonlinear dynamic simulations coupling geothermal heat transfer, energy system operation, and realistic feedback control logic. These simulations identified essential design modifications and control strategy refinements that substantially reduced energy use, peak demand, and compressor shortcycling, thereby improving durability and reliability—issues that would have been significantly more expensive to resolve during operation. Additionally, the verification step highlighted sensitivities to key design parameters that could reduce initial investment by approximately $\$2$ million and reduce annual life-cycle costs more than $\$300,000$. We recommend adopting the PBD methodology for future feasibility studies and TEN pilot projects to gain valuable operational experience. Furthermore, we recommend that DoD invest in transferring and scaling the PBD methodology to other installations. This entails developing standardized computational frameworks and component libraries as well as training industry in conducting PBD. Such investments would enable rapid, robust, reliable, and cost-effective retrofits, supporting DoD’s ambitious energy system modernization goals.

Wetter, Michael [Lawrence Berkeley National Labora↗
NASA NTRSDate not supplied

Early Progress Toward the Feasibility of the Centrifugal Nuclear Thermal Rocket

The Centrifugal Nuclear Thermal Rocket (CNTR) is a Nuclear Thermal Propulsion (NTP) concept designed to heat propellant directly by the reactor fuel. The primary difference between the CNTR concept and traditional NTP systems is that rather than using traditional solid fuel elements, the CNTR uses liquid fuel with the liquid contained in rotating cylinders by centrifugal force. If the concept can be successfully realized, the CNTR would have a high specific impulse (~1800 seconds) at high thrust, which may enable (i) viable near-term human Mars exploration by reducing round-trip times to 420 days and (ii) direct injection orbits for scientific missions to the Solar System outer planets and potentially Kuiper Belt objects. The CNTR could also use storable propellants such as ammonia, methane, or hydrazine at an Isp of ~900 seconds, enabling long-term in-space storage of a dormant system. Significant engineering challenges must be addressed to establish the technical viability of the CNTR. Research is presently underway to determine resolutions for these engineering challenges. In particular, research has begun on the analytical modeling and simulation of the two-phase heat transfer between the liquid metallic uranium fuel and the gaseous propellant. A paper was presented at the 2021 IAC which described these challenges and the study plan to address them. This paper describes the analytical and experimental progress to date toward resolving these challenges and establishing the engineering feasibility of the CNTR technology.

Nuclear Thermal Propulsion↗
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 OSTI2024

Probing room temperature indirect and minimum direct band gaps of h-BN

Abstract Hexagonal boron nitride (h-BN) has attracted considerable interest as an ultrawide bandgap (UWBG) semiconductor. Experimental studies focused on the detailed near band-edge structure of h-BN at room temperature are still lacking. We report a direct experimental measurement of the near band-edge structure performed on h-BN quasi-bulk wafers via photocurrent excitation spectroscopy (PES). PES resolved the band-to-band transitions near M- and K-points in the Brillion zone (BZ), from which the room temperature indirect band gap of E g M K ∼6.02 eV, minimum direct bandgap at M-point of E g M = 6.36 eV and next lowest direct energy bandgap at K-point of E g K = 6.56 eV , have been simultaneously determined for the first time experimentally. The measured energy differences between K- and M-points in the conduction band minimum (CBM) and valence band maximum (VBM) are Δ E C M K = 0.54 eV and Δ E V M K = 0.34 eV, respectively, in good agreement with the calculation results. Significantly differing from its III-nitride wurtzite counterparts, in which only electrons and holes in the conduction and valence band extremes at the Γ-point are predominantly involved in the optical and transport processes, the results highlighted that charge carriers associated with both M- and K-valleys control to the optical excitation, recombination and charge transport processes in h-BN.

Physics↗
DOE OSTI2024

Quantifying concentration distributions in redox flow batteries with neutron radiography

Abstract The continued advancement of electrochemical technologies requires an increasingly detailed understanding of the microscopic processes that control their performance, inspiring the development of new multi-modal diagnostic techniques. Here, we introduce a neutron imaging approach to enable the quantification of spatial and temporal variations in species concentrations within an operating redox flow cell. Specifically, we leverage the high attenuation of redox-active organic materials (high hydrogen content) and supporting electrolytes (boron-containing) in solution and perform subtractive neutron imaging of active species and supporting electrolyte. To resolve the concentration profiles across the electrodes, we employ an in-plane imaging configuration and correlate the concentration profiles to cell performance with polarization experiments under different operating conditions. Finally, we use time-of-flight neutron imaging to deconvolute concentrations of active species and supporting electrolyte during operation. Using this approach, we evaluate the influence of cell polarity, voltage bias and flow rate on the concentration distribution within the flow cell and correlate these with the macroscopic performance, thus obtaining an unprecedented level of insight into reactive mass transport. Ultimately, this diagnostic technique can be applied to a range of (electro)chemical technologies and may accelerate the development of new materials and reactor designs.

Science & Technology - Other Topics↗