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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 109 records · Page 6

Glancing Angle Deposition in Gas Sensing: Bridging Morphological Innovations and Sensor Performances

Glancing Angle Deposition (GLAD) has emerged as a versatile and powerful nanofabrication technique for developing next-generation gas sensors by enabling precise control over nanostructure geometry, porosity, and material composition. Through dynamic substrate tilting and rotation, GLAD facilitates the fabrication of highly porous, anisotropic nanostructures, such as aligned, tilted, zigzag, helical, and multilayered nanorods, with tunable surface area and diffusion pathways optimized for gas detection. This review provides a comprehensive synthesis of recent advances in GLAD-based gas sensor design, focusing on how structural engineering and material integration converge to enhance sensor performance. Key materials strategies include the construction of heterojunctions and core–shell architectures, controlled doping, and nanoparticle decoration using noble metals or metal oxides to amplify charge transfer, catalytic activity, and redox responsiveness. GLAD-fabricated nanostructures have been effectively deployed across multiple gas sensing modalities, including resistive, capacitive, piezoelectric, and optical platforms, where their high aspect ratios, tailored porosity, and defect-rich surfaces facilitate enhanced gas adsorption kinetics and efficient signal transduction. These devices exhibit high sensitivity and selectivity toward a range of analytes, including NO2, CO, H2S, and volatile organic compounds (VOCs), with detection limits often reaching the parts-per-billion level. Emerging innovations, such as photo-assisted sensing and integration with artificial intelligence for data analysis and pattern recognition, further extend the capabilities of GLAD-based systems for multifunctional, real-time, and adaptive sensing. Finally, current challenges and future research directions are discussed, emphasizing the promise of GLAD as a scalable platform for next-generation gas sensing technologies.

Chemistry↗

Seasonal Sulfur Redox Cycling in Two Constructed Wetlands with Insight on How They Age

Long-term metal remediation in wetland treatment systems (WTSs) involves facilitating dissimilatory sulfate reduction to produce sulfide and mineralize metals in deep sediments. We evaluated seasonal sulfur cycling in two constructed wetlands (Maintained WTS constructed in 2007, and the Unmaintained WTS constructed in 2000) on the Savannah River Site in Aiken, South Carolina, USA. Significant interactions in sulfide concentration were observed between sediment depth, season, and wetland (F = 4.64, df = 11, P = 3.28 × 10 − 5). In the Maintained WTS, dissimilatory sulfate reduction dominated the surface sediments during the warm season (0–2 cm depth, t=-2.66, P = 9.70 × 10 − 3), unlike the Unmaintained system. Sulfate concentrations in pore waters increased in the warm season (F = 7.84, df = 1, P = 6.50 × 10 − 3), contrary to expectations. Sulfur limitation in the Unmaintained WTS during the warm season correlated with increased sulfur assimilation in giant bulrush. Lower sulfide concentrations in surface sediments of the Unmaintained WTS illustrated aging effects. The Maintained WTS shows potential for managing erosion, pH reduction, and sulfur limitation observed in the older Unmaintained WTS.

Biogeochemistry↗

Beneficial Use of Harvested Ponded Fly Ash and Landfilled FGD Materials for High-Volume Surface Mine Reclamation

The overall motivation of this project was to demonstrate at laboratory, bench-scale, and full-scale demonstration levels that (a) coal ash surface impoundments can go through closure by removal as per USEPA and state regulations so that the material can be used as is (other than draining free water using CCRs piles) in high-volume beneficial applications, (b) FGD material from closed out FGD facilities can be excavated and recompacted for coal mine reclamation, and (c) harvested CCRs can be beneficially utilized (providing a net environmental gain) in large-volumes for reclamation at abandoned coal mine sites across the US, especially in the Eastern and Midwest coal mining regions. The objectives of this project were to: 1) promote the safe and cost-effective closure by removal of coal ash impoundments, 2) harvest landfilled FGD, and 3) promote the high-volume beneficial use of these harvested CCRs in the reclamation of abandoned surface coal mine sites across the eastern and midwestern coal mining regions of the United States. The major tasks carried out for this project are summarized below: 1) Conesville Full-Scale Demonstration Project: About 2 million tons of harvested CCR materials from the closure by removal of an inactive fly ash pond and an adjacent old FGD landfill were used for the full-scale demonstration project to fully reclaim a nearby partially completed abandoned surface coal mine. Site monitoring for the project duration was carried out and results are discussed. 2) Laboratory Testing: Geotechnical and environmental testing of harvested ponded fly ash and landfilled FGD material at the former Conesville power plant were carried out. Completing the laboratory testing allowed for QA/QC for the full-scale site construction and informed the formulation of the risk analysis. 3) Risk Analysis: We developed a reliable computational model for fate and transport. We used these models and the rich set of monitored data for the Conesville site to analyze risks to human health and ecological risks associated with high-volume surface mine reclamation using harvested CCRs. 4) GIS Siting Study: A Geographic Information System (GIS) study was carried out for three states in the Eastern coal mining region and two states in the Midwest coal region. This effort provided site specific GIS information for five states and allowed us to establish protocols that other states can follow in implementing their own state specific GIS study.

01 COAL, LIGNITE, AND PEAT↗

FLARE: field line analysis and reconstruction for 3D boundary plasma modeling

The FLARE code is a magnetic mesh generator that is integrated within a suite of tools for the analysis of the magnetic geometry in toroidal fusion devices. A magnetic mesh is constructed from field line segments and permits fast reconstruction of field lines in 3D boundary plasma codes such as EMC3-EIRENE. Both intrinsically non-axisymmetric configurations (stellarators) and those with symmetry breaking perturbations of an axisymmetric equilibrium (tokamaks) are supported. The code itself is written in Modern Fortran with MPI support for parallel computing, and it incorporates object-oriented programming for the definition of the magnetic field and the material surface geometry. Extended derived types for a number of different magnetohydrodynamic equilibrium and plasma response models are implemented. The core element of FLARE is a field line tracer with adaptive step-size control, and this is integrated into tools for the construction of Poincaré maps and invariant manifolds of X-points. A collection of high-level procedures that generate output files for visualization is build on top of that. The analysis modules are build with Python frontends that facilitate customization of tasks and/or scripting of parameter scans.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High-Throughput Microstructural Characterization and Process Correlation Using Automated Electron Backscatter Diffraction

The need to optimize the processing conditions of additively manufactured (AM) metals and alloys has driven advances in throughput capabilities for material property measurements such as tensile strength or hardness. High-throughput (HT) characterization of AM metal microstructure has fallen significantly behind the pace of property measurements due to intrinsic bottlenecks associated with the artisan and labor-intensive preparation methods required to produce highly polished surfaces. This inequality in data throughput has led to a reliance on heuristics to connect process to structure or structure to properties for AM structural materials. In this study, we show a transformative approach to achieve laser powder bed fusion (LPBF) printing, HT preparation using dry electropolishing and HT electron backscatter diffraction (EBSD). This approach was used to construct a library of > 600 experimental EBSD sample sets spanning a diverse range of LPBF process conditions for AM Kovar. This vast library is far more expansive in parameter space than most state-of-the-art studies, yet it required only approximately 10 labor hours to acquire. Build geometries, surface preparation methods, and microscopy details, as well as the entire library of >600 EBSD data sets over the two sample design versions, have been shared with intent for the materials community to leverage the data and further advance the approach. Using this library, we investigated process–structure relationships and uncovered an unexpected, strong dependence of microstructure on location within the build, when varied, using otherwise identical laser parameters.

Characterization and Analytical Technique↗

Bioproduction, bioprotection, and biocontainment in multi-kingdom microbial systems with 3D spatial control

Engineered living materials (ELMs) are a class of hybrid materials that include engineered microbes encapsulated by a polymer matrix. The biotic and abiotic components define the ELMs design space and can be altered to improve performance and function. While current synthetic materials in the field display robust biocompatibility with both native and engineered living systems, we have a limited understanding of how to leverage three-dimensional (3D) form factors to spatially organize and control microbial dynamics within the material. Motivated by this knowledge gap, we employed extrusion-based 3D printing to fabricate multi-kingdom hydrogel constructs for the encapsulation of both single and multi-kingdom microbial systems. Core–shell cubic constructs enabled the spatial organization of a constitutive multi-kingdom system of levodopa (L-DOPA)-producing E. coli and betaxanthins (BXN)-producing S. cerevisiae. This spatial organization in 3D materials can introduce precise control over bioproduction, bioprotection, and biocontainment features that are critical to the efficacy of current ELMs. The relative spatial organization of the organisms, as well as the surface area-to-volume ratio were investigated to determine how these design elements impact microbial behavior (metabolite production, growth, expression, and cell distribution) over time. We demonstrated that F127-bis-urethane methacrylate (F127-BUM) core–shell geometries enable the hierarchical 3D printing of multi-kingdom constructs, offering customizable control over bioproduction, bioprotection, and biocontainment. With the optimization of these core–shell structures for continuous bioproduction, these ELMs could be deployed as compact and sustainable bioreactors in remote environments.

additive manufacturing↗

Advancing Mass Timber Buildings: Novel Methods Improve Thermal Assessment and Material Use

For nearly a century, thermal demand calculations for buildings have relied on simplified models developed to match the technical constraints of their era. The first standards, introduced in Germany and Austria in 1929, established climate zones and material conductivity coefficients that, with only incremental updates, still underpin many current assessments. Yet, methods such as Hot box testing, originally designed for lightweight insulation, continue to be applied for mass timber buildings, overlooking thermodynamic characteristics confer real-world advantages. Recent research at Oak Ridge National Laboratory incorporates updated methodologies, aligned with ASHRAE Standard 55 (ASHRAE, 2023) accounting for factors such as thermal inertia, inner surface temperatures, emissivity, solar gains, and dynamic outdoor conditions. These factors better reflect observed heating and cooling loads and highlight opportunities for efficient use of materials in mass timber construction. This work provides a framework for designing comfortable, resilient, and resource-efficient buildings while aligning with performance expectations in energy codes.

Pickett, Robert [International Mass Timber Allianc↗

Enabling the broader adoption of fusion simulation on complex geometry

This project addressed a key barrier to advanced fusion and nuclear simulation: the difficulty of performing high-fidelity Monte Carlo neutronics directly on complex, real-world CAD geometry. Traditional workflows require engineers to rebuild CAD models as simplified constructive solid geometry, a time-consuming and error-prone process that limits design iteration and broader adoption of simulation tools. The goal of this Phase I SBIR was to make CAD-based neutronics practical, accessible, and robust for industrial and research users. During the project, Coreform significantly enhanced the Direct Accelerated Geometry Monte Carlo (DAGMC) workflow and fully integrated it into Coreform Cubit as a first-class capability. Major achievements include optimized material assignment and surface meshing workflows, substantial performance improvements to geometry imprinting and preparation, native export of DAGMC models, and new visualization tools to support OpenMC source definition and lost-particle debugging. Coreform also expanded Cubit’s capabilities as a full OpenMC preprocessor, including the ability to convert OpenMC constructive solid geometry models back into CAD for visualization, multiphysics coupling, and debugging. In collaboration with Argonne National Laboratory, the project delivered comprehensive new DAGMC documentation and training materials, transforming DAGMC from a research-oriented tool into a production-ready workflow. Results were disseminated through tutorials, conference training, and multiple well-attended webinars demonstrating integrated CAD-based neutronics and multiphysics workflows. Overall, this project demonstrated that high-fidelity Monte Carlo simulations can be performed directly on complex CAD geometry, reducing setup time, improving usability, and enabling faster, more informed design decisions for fusion and nuclear energy systems.

42 ENGINEERING↗

Accelerating Embedding Potential Optimization by Reconstructing the Pseudo-Valence Electron Density

Density functional embedding theory (DFET) enables use of electronic structure methods with higher accuracy than density functional theory in a local region, with applications thus far ranging from (photo/electro)catalysis to reactions in solution. DFET partitions a large collection of atoms into smaller groups that interact via a shared embedding (interaction) potential V emb , determined via functional optimization. The optimized effective potential (OEP) process used to optimize V emb is time-consuming and becomes a computational bottleneck due to sharp, oscillating features of V emb near nuclei. Here, similar to pseudopotential theory, by reconstructing electron densities used in the OEP process from smoother pseudo-valence-only (PVO) electron densities as proxies for total densities of the full system and subsystems, we can retain accuracy in the embedded electronic structure calculations while potentially reducing the overhead of V emb construction, within the projector augmented-wave (PAW) formalism. We explore three different chemical reactions as exemplars to test PVO–DFET, namely, H 2 dissociative adsorption on a Cu(111) surface, H 2 O adsorption on a Pt(111) surface, and aqueous [Ca 2+ –SO 4 2– ] ion-pair formation. The PVO approximation works well for all three systems with minimal loss of accuracy (∼10–70 meV error relative to the original exact-derivative (ED) approach) while accelerating V emb generation for the Cu and Pt systems respectively by 20× and 5×. Given proper numerical convergence parameters, the spatial distributions of differences between PVO- and ED-based V emb outside the core regions are small, explaining the exceptional agreement between the two approaches. Finally, we anticipate that this more efficient PVO–DFET approximation will be useful whenever computation of V emb is much more expensive than subsequent embedded high-level electron correlation calculations.

approximation↗

The development of thermodynamically consistent and physics-informed equation-of-state model through machine learning

Ab initio molecular dynamics (AIMD) simulations have become an important tool used in the construction of equations of state (EOS) tables for warm dense matter. Due to computational costs, only a limited number of system state conditions can be simulated, and the remaining EOS surface must be interpolated for use in radiation-hydrodynamic simulations of experiments. In this work, we develop a thermodynamically consistent EOS model that utilizes a physics-informed machine learning approach to implicitly learn the underlying Helmholtz free-energy from AIMD generated energies and pressures. The model, referred to as PIML-EOS, was trained and tested on warm dense polystyrene producing a fit within a 1% relative error for both energy and pressure and is shown to satisfy both the Maxwell and Gibbs–Duhem relations. In addition, we provide a path toward obtaining thermodynamic quantities, such as the total entropy and chemical potential (containing both ionic and electronic contributions), which are not available from current AIMD simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗

A new perspective on density and strength loss profiles at the surface of thermally oxidized nuclear graphite

Oxidation of graphite components could influence their designed life in a high-temperature nuclear reactor. The oxidized regions could potentially lower the allowed stress capacity. The American Society of Mechanical Engineers rules for the design and construction of graphite-moderated reactors recommend that subsurface regions that might become excessively damaged by oxidation during reactor operation be identified and excluded from geometry and stress calculations. Identification of oxidation-affected regions is possible, in principle, through complex modeling exercises of reactor behavior during hypothetical accident scenarios coupled with graphite oxidation models, but this procedure may not have the precision needed for informed decisions. Here, this paper proposes an alternate method, based on interpretation of a series of well-designed oxidation experiments, which could augment the designer's tools. The procedure is illustrated by data on oxidation by air of several graphite grades (NBG-18, PCEA, IG-110, R4-650) that are corroborated with independent literature information, when available. The Wichner model for graphite oxidation used for this analysis provides conservative results that could be quickly implemented in the design process.

36 MATERIALS SCIENCE↗

Finite deformation implementation of a mixed-mode single-integral type cohesive zone with reorienting surfaces of separation

To model material ductile failure and crack propagation, cohesive zone elements can be embedded along potential fracture paths in a finite element simulation. When damage criteria are met, elements in the mesh decohere, simulating the formation and propagation of a crack. In this paper, we present a novel computational algorithm based on finite deformation theory, essential to modeling crack initiation and growth in solids undergoing large deformations. This new algorithm was formulated within a Lagrangian frame of reference to extend previous cohesive zone algorithms to include modeling crack growth in finite deformation contexts. The local coordinate system, necessary for defining an embedded cohesive zone, is constructed based upon the current configuration and is updated within the nonlinear iteration process, thereby resulting in the convergence of the solution for a growing crack in a large deformation quasi-static setting. The model’s accuracy was demonstrated by comparing finite element model simulation results with the analytic case of a constant surface separation, as shown in the verification examples. The power and efficacy of the algorithm to capture large deformations during crack growth were then demonstrated with a double cantilever beam example case. It indicates that the model can be applied to a variety of physical circumstances for predicting crack initiation and growth with delamination and fracture.

42 ENGINEERING↗

Data-Driven Invertible Neural Surrogates of Atmospheric Transmission

We present Data-Driven Invertible Neural Surrogates of Atmospheric transmission, or DINSAT. DINSAT is a novel framework for inferring an atmospheric transmission profile from a spectral scene. This framework leverages a lightweight, physics-based simulator that is automatically tuned -- by virtue of autodifferentiation and differentiable programming -- to construct a surrogate atmospheric profile to model the observed data. The framework has utility in (i) performing atmospheric correction, (ii) recasting spectral data between various modalities (e.g. radiance and reflectance at the surface and at the sensor), and (iii) inferring atmospheric transmission profiles, such as absorbing bands and their relative magnitudes. We demonstrate the utility of these methods by performing a canonical atmospheric correction task for the purposes of further analysis - in this case, target detection within a scene.

Koch, James V.↗

Measurement of spin-polarized photoemission from wurtzite and zinc blende gallium nitride photocathodes

Spin-polarized photoemission from wurtzite and zinc blende gallium nitride (GaN) photocathodes has been observed and measured. The p-doped GaN photocathodes were epitaxially grown and activated to negative electron affinity with a cesium monolayer deposited on their surfaces. A field-retarding Mott polarimeter was used to measure the spin polarization of electrons photoemitted from the top of the valence band. A spectral scan with a tunable optical parametric amplifier constructed to provide low-bandwidth light revealed peak spin polarizations of 17% and 29% in the wurtzite and zinc blende photocathodes, respectively. Zinc blende GaN results are analyzed with a spin polarization model accounting for experimental parameters used in the measurements, while possible mechanisms influencing the obtained spin polarization values of wurtzite GaN are discussed.

Physics↗

Search for a diffuse flux of photons with energies above tens of PeV at the Pierre Auger Observatory

Diffuse photons of energy above 0.1 PeV, produced through the interactions between cosmic rays and either interstellar matter or background radiation fields, are powerful tracers of the distribution of cosmic rays in the Galaxy. Furthermore, the measurement of a diffuse photon flux would be an important probe to test models of super-heavy dark matter decaying into gamma-rays. In this work, we search for a diffuse photon flux in the energy range between 50 PeV and 200 PeV using data from the Pierre Auger Observatory. For the first time, we combine the air-shower measurements from a 2 km 2 surface array consisting of 19 water-Cherenkov surface detectors, spaced at 433 m, with the muon measurements from an array of buried scintillators placed in the same area. Using 15 months of data, collected while the array was still under construction, we derive upper limits to the integral photon flux ranging from 13.3 to 13.8 km -2 sr -1 yr -1 above tens of PeV. We extend the Pierre Auger Observatory photon search program towards lower energies, covering more than three decades of cosmic-ray energy. This work lays the foundation for future diffuse photon searches: with the data from the next 10 years of operation of the Observatory, this limit is expected to improve by a factor of ∼20.

cosmic rays detectors↗

Water4Energy Tier-1 Raw Observations for TVA Seasonal Prediction, Version 1

Tier-1 (Step-1) raw observation staging collection for the Water4Energy Genesis Task-1 project on weeks-to-years prediction of Tennessee Valley temperature and precipitation. This data-only deposit includes CPC/PSL teleconnection indices, NOAA OISST monthly and ERSST sea-surface temperature, ERA5-derived daily 1° fields (t2m, tp, msl for 1980–2024), CFSv2 NMME ensemble-mean seasonal baselines, and a TVA boundary mask. The product supports seasonal teleconnection diagnostics and construction of AI ready-to-train packs published separately. Multi-terabyte hourly archives are excluded from this version.

54 ENVIRONMENTAL SCIENCES↗

Bench-scale Development of a Transformational Graphene Oxide-based Membrane Process for Post-combustion CO 2 Capture

Graphene-based materials, such as graphene and graphene oxide (GO), have been considered as next-generation membrane materials. GTI Energy and The State University of New York at Buffalo (UB) have been developing a transformational GO-based membrane process (designated as GO2) that integrates a high CO 2 /N 2 selectivity membrane (GO-1) and a high CO 2 flux membrane (GO-2) for post-combustion CO 2 capture. An innovative membrane structure, consisting of GO nanochannels intercalated by single-walled carbon nanotube (SWCNT), was developed. The membrane prepared on hollow fiber substrate showed CO 2 permeance as high as 1,300 GPU with CO 2 /N 2 selectivity >200. The membranes were successfully scaled up to effective area of 50-100 cm 2 . The 50-100 cm 2 membranes showed CO 2 /N 2 selectivity ≥200 and CO 2 permeance ≥1,000 GPU for the GO-1 type, and CO 2 /N 2 selectivity ≥20 and CO 2 permeance ≥2,500 GPU for the GO-2 type. The CO 2 capture performance of the GO-based membranes was tested using a simulated flue gas. The testing results indicate that the GO-based membranes are stable in the presence of flue gas contaminants. The GO-based membranes were then further scaled up to a surface area of 1,000 cm 2 . Good stability was achieved during an integrated testing with GO-1 and GO-2 membranes using simulated flue gas. A bench-scale system was designed, constructed, and tested at the National Carbon Capture Center (NCCC). Good stability was achieved during testing of a single-stage process with >10 shutdowns/startups at NCCC. During the integrated testing, the membranes showed good stability at 50°C and 57°C. 70-90% CO 2 removal efficiencies and ≥95% CO 2 purity were validated during the steady state operation at NCCC. Techno-economic analysis indicates the GO2 membrane-based process technology provides a reduction in both the levelized cost of electricity (LCOE) and cost of capture when compared to the reference B12B case presented in the Cost and Performance Baseline for Fossil Energy Plants Volume 1: Bituminous Coal and Natural Gas to Electricity study prepared by the National Energy Technology Laboratory (NETL), before considering any system optimization or improvement opportunities. The benefits are primarily driven by a reduction in the equipment costs of the CO 2 capture process vs. the solvent-based reference process in NETL Case B12B as well as a decrease in the base plant size.

20 FOSSIL-FUELED POWER PLANTS↗

Fine-scale vegetation composition and structure shape spatiotemporal variation in surface albedo across a low Arctic tundra landscape

The unprecedented rate of warming in the Arctic is driving changes in the structure and composition of tundra vegetation. Increases in deciduous tall shrub cover, height, and density are of particular concern, as these changes alter local surface albedo in ways that could amplify effects on the regional surface energy budget (SEB). Despite this importance, significant uncertainties remain in understanding the interplay between fine-scale vegetation patterns and emergent albedo dynamics across space and time. Here, we address these uncertainties by (1) quantifying spatiotemporal variation in surface shortwave albedo and (2) determining the relative influence of fine-scale vegetation composition, structure, and environmental conditions on albedo across a representative low-Arctic tundra landscape on Alaska’s Seward Peninsula. To do this, we synthesized multi-scale, multi-platform remote sensing observations, including a novel Landsat-derived albedo time series, a fine-scale map of Arctic plant functional type (PFT) fractional cover, and airborne LiDAR estimates of canopy height and topography. We show that there are substantial reductions in winter albedo for pixels dominated by tall, woody PFTs (28.13%) relative to pixels dominated by non-woody vegetation, but almost no change in summer albedo (3% increase). Further, we identified a unimodal trend in the relationship between canopy height and the timing of the springtime transition from high (snowy) to low (leafy) albedo (peak at 5.5 m), possibly because of competing ‘snow-fence’ and ‘protrusion’ snow-shrub interactions. To explore the primary drivers of albedo, we constructed a random forest model and found that canopy height and the fractional cover of woody PFTs were as- or more important predictors of winter albedo than topographic features. These findings provide strong evidence for the impacts of local vegetation characteristics on regional surface albedo, highlighting the need for better quantification of snow-shrub interactions to accurately predict the Arctic’s SEB under future environmental change.

Arctic↗