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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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933 records · Page 17

Thermally Stable Co@C3N4 Single-Atom Catalysts for CO Oxidation: Atomic-Level Insights into Structure and Activity

Single Co atoms supported on C3N4 (Co@C3N4) have demonstrated high activity and selectivity in photocatalysis. However, the investigation of structure–function relationships and reaction mechanisms under photocatalytic conditions is very challenging due to the complex conditions of light absorption, charge transfer, and catalysis. In this study, we employed thermal CO oxidation as a prototypical probe reaction to benchmark the intrinsic catalytic performance and track the active-site evolution of Co@C3N4. Single Co atoms were identified and shown to be the catalytically active sites for CO oxidation based on control experiments and isotope-labeling experiments. The Co sites remained atomically dispersed before, during, and after the reaction with temperatures up to 400 °C, as established by in situ X-ray absorption fine structure (XAFS) combined with density functional theory (DFT), FDMNES simulations, and dynamic-time-warping (DTW)-assisted X-ray absorption near edge structure (XANES) matching. Together with theoretical calculations, the integrated analysis reveals a stable coordination environment under reaction conditions, which correlates with sustained activity, establishing Co@C3N4 single-atom catalysts as thermally stable CO oxidation catalysts. Beyond these findings, the current study provides a workflow for unambiguously assigning active sites in Co@C3N4 for thermal CO oxidation. This workflow will aid the understanding of their behavior in photocatalysis in the future, where light-driven dynamics obscure direct structure–function links. Notably, this study provides fundamental insights for the rational design of robust single-atom catalysts and a foundation for the broader application of Co@C3N4 catalysts in oxidation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Fast, Nondestructive and Precise Biomass Measurements Are Possible Using Lidar-Based Convex Hull and Voxelization Algorithms

Light detection and ranging (lidar) scanning tools are available that can make rapid digital estimations of biomass. Voxelization and convex hull are two algorithms used to calculate the volume of the scanned plant canopy, which is correlated with biomass, often the primary trait of interest. Voxelization splits the scans into regular-sized cubes, or voxels, whereas the convex hull algorithm creates a polygon mesh around the outermost points of the point cloud and calculates the volume within that mesh. In this study, digital estimates of biomass were correlated against hand-harvested biomass for field-grown corn, broom corn, and energy sorghum. Voxelization (r = 0.92) and convex hull (r = 0.95) both correlated well with plant dry biomass. Lidar data were also collected in a large breeding trial with nearly 900 genotypes of energy sorghum. In contrast to the manual harvest studies, digital biomass estimations correlated poorly with yield collected from a forage harvester for both voxel count (r = 0.32) and convex hull volume (r = 0.39). However, further analysis showed that the coefficient of variation (CV, a measure of variability) for harvester-based estimates of biomass was greater than the CV of the voxel and convex-hull-based biomass estimates, indicating that poor correlation was due to harvester imprecision, not digital estimations. Overall, results indicate that the lidar-based digital biomass estimates presented here are comparable or more precise than current approaches.

Environmental Sciences & Ecology

Fast Active-Set Thresholding Method for Nonnegative Least Squares

Nonnegative Least Squares (NNLS) is a fundamental constrained optimization problem encountered in many applications such as image deblurring, signal processing, nonnegative matrix factorization, magnetic microscopy, and hyperspectral imaging. Active-set based methods are a common class of algorithms for solving NNLS which identify the optimal variable set of the NNLS solution. They do so by iteratively solving a series of unconstrained least squares problems, identifying which variables violate the nonnegativity constraints, and then swapping variables in/out of consideration until the optimal set of variables is found. Several variations improving upon this method exist in the literature. In this work, we propose an active-set swap heuristic which further improves upon existing active-set based methods for NNLS. Our optimizations are based upon adding multiple variables to the passive set within a threshold of the smallest gradient value and removing variables within a similar threshold of the closest boundary constraint. We leverage these optimizations to yield a Fast Active-Set Thresholding NNLS (FAST-NNLS) algorithm which significantly outperforms the existing state-of-the-art NNLS algorithms for a wide range of problems. Rigorous convergence guarantees are proven for the proposed method. We demonstrate the effectiveness of our proposed method on multiple synthetic datasets and two realworld text analysis applications. In doing so, we present the most comprehensive NNLS solver comparison in the literature to date.

Cobb, Benjamin [Georgia Institute of Technology]

The Effects of Gravity on Combustion and Structure Formation During Combustion Synthesis in Gasless Systems

There have been relatively few publications examining the role of gravity during combustion synthesis (CS), mostly involving thermite systems. The main goal of this research was to study the influence of gravity on the combustion characteristics of heterogeneous gasless systems. In addition, some aspects of microstructure formation processes which occur during gasless CS were also studied. Four directions for experimental investigation have been explored: (1) the influence of gravity force on the characteristic features of heterogeneous combustion wave propagation (average velocity, instantaneous velocities, shape of combustion front); (2) the combustion of highly porous mixtures (with porosity greater than that for loose powders), which cannot be obtained in normal gravity; (3) the effect of gravity on sample expansion during combustion, in order to produce highly porous materials under microgravity conditions; and (4) the effect of gravity on the structure formation mechanism during the combustion synthesis of poreless composite materials.

Arvind Varma

Nuclear Structure and Decay Data for A=35 Isobars

Here, this work presents a comprehensive and critical evaluation of experimental nuclear spectroscopic data from reactions and decays for all 11 known nuclides with mass number 35 (Ne, Na, Mg, Al, Si, P, S, Cl, Ar, K, Ca). Recommended values are produced for level energies, spins and parities, half-lives, and radiation properties including energies, branching ratios, and multipolarities of γ rays, as well as characteristics of β radiation decays, based on a rigorous assessment of all available experimental data. Discrepancies among existing results are carefully addressed. This work supersedes earlier full evaluations of A=35 published by 2011Ch48, 1990En08 (also 1998En04 update) and 1978En02.

Sun, Lijie [Michigan State University, East Lansin

Machine Learning for Predicting Multipactor Susceptibility in Planar RF Structures

Multipactor discharge is a persistent challenge in high-power microwave (HPM) and accelerator systems, where secondary electron avalanches can cause heating, vacuum degradation, and failure. This work presents the first supervised machine learning (ML) framework for multipactor prediction, trained on high-fidelity 3D Particle-in-Cell (PIC) simulation data in planar geometries. The model maps operational, geometric, and material-dependent secondary electron yield (SEY) parameters to the time-averaged electron growth rate, enabling rapid reconstruction of susceptibility charts. Among the models evaluated, tree-based ensemble methods such as Random Forest and Extra Trees demonstrate superior generalization to unseen materials compared to neural networks such as multilayer perceptron (MLP). Performance metrics, including Intersection over Union (IoU), Structural Similarity Index Measure (SSIM), and Pearson correlation, show close agreement with simulation benchmarks. Principal Component Analysis attributes generalization limits to material feature-space disjointedness.

43 PARTICLE ACCELERATORS

Machine learning approach for vibronically renormalized electronic band structures

Here, we present a machine learning (ML) method for efficient computation of vibrational thermal expectation values of physical properties from first principles. Our approach is based on the nonperturbative frozen phonon formulation in which stochastic Monte Carlo algorithm is employed to sample configurations of nuclei in a supercell at finite temperatures based on a first-principles phonon model. A deep-learning neural network is trained to accurately predict physical properties associated with sampled phonon configurations, thus bypassing the time-consuming ab initio calculations. To incorporate the point-group symmetry of the electronic system into the ML model, group-theoretical methods are used to develop a symmetry-invariant descriptor for phonon configurations in the supercell. We apply our ML approach to compute the temperature dependent electronic energy gap of silicon based on density functional theory (DFT). We show that, with less than a hundred DFT calculations for training the neural network model, an order of magnitude larger number of sampling can be achieved for the computation of the vibrational thermal expectation values. Our work highlights the promising potential of ML techniques for finite temperature first-principles electronic structure methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

A First-Principles Study of the Structural and Thermo-Mechanical Properties of Tungsten-Based Plasma-Facing Materials

Tungsten (W) and tungsten alloys are being considered as leading candidates for structural and functional materials in future fusion energy devices. The most attractive properties of tungsten for the design of magnetic and inertial fusion energy reactors are its high melting point, high thermal conductivity, low sputtering yield, and low long-term disposal radioactive footprint. Despite these relevant features, there is a lack of understanding of how the structural and mechanical properties of W-based alloys are affected by the temperature in fusion power plants. In this work, we present a study on the thermo-mechanical properties of five W-based plasma-facing materials. First-principles density functional theory (DFT) calculations are combined with the quasi-harmonic approximation (QHA) theory to investigate the electronic, structural, mechanical, and thermal properties of these W-based alloys as a function of temperature. The coefficient of thermal expansion, temperature-dependent elastic constants, and several elastic parameters, including bulk and Young’s modulus, are calculated. Our work advances the understanding of the structural and thermo-mechanical behavior of W-based materials, thus providing insights into the design and selection of candidate plasma-facing materials in fusion energy devices.

42 ENGINEERING

An improved heat transfer configuration for a solid-core nuclear thermal rocket engine

Interrupted flow, impingement cooling, and axial power distribution are employed to enhance the heat-transfer configuration of a solid-core nuclear thermal rocket engine. Impingement cooling is introduced to increase the local heat-transfer coefficients between the reactor material and the coolants. Increased fuel loading is used at the inlet end of the reactor to enhance heat-transfer capability where the temperature differences are the greatest. A thermal-hydraulics computer program for an unfueled NERVA reactor core is employed to analyze the proposed configuration with attention given to uniform fuel loading, number of channels through the impingement wafers, fuel-element length, mass-flow rate, and wafer gap. The impingement wafer concept (IWC) is shown to have heat-transfer characteristics that are better than those of the NERVA-derived reactor at 2500 K. The IWC concept is argued to be an effective heat-transfer configuration for solid-core nuclear thermal rocket engines.

John S Clark

Engineering 2D Square Lattice Hubbard Models in 90° Twisted GeX/SnX (X =S, Se) Moiré Superlattices

Because of the large-period superlattices emerging in moiré two-dimensional (2D) materials, electronic states in such systems exhibit low energy flat bands that can be used to simulate strongly correlated physics in a highly tunable setup. While many investigations have thus far focused on moiré flat bands and emergent correlated electron physics in triangular, honeycomb, and quasi-one-dimensional lattices, tunable moiré realizations of square lattices subject to strong correlations remain elusive. Here, in this work, we propose a feasible scheme to construct moiré square lattice systems by twisting two or more layers of 2D materials in a rectangular lattice by 90°. We demonstrate the concept with twisted GeX/SnX (X =S, Se) moiré superlattices and calculate their electronic structures from first principles. We show that the lowest conduction flat band in these systems can be described by a square lattice Hubbard model with parameters which can be controlled by varying the choice of host materials, number of layers, and external electric fields. In particular, twisted double bilayer GeSe realizes a square lattice Hubbard model with strong frustration due to the next-nearest-neighbor hopping that could host unconventional superconductivity, in close analogy to the Hubbard model for copper-oxygen planes of cuprate high-temperature superconductors. The presented scheme uses 90° twisted 2D materials with rectangular unit cells as a promising platform for realizing the physical phenomena of square lattice Hubbard models, establishing a new route for studying its rich phase diagram of magnetism, charge order, and unconventional superconductivity in a highly tunable setting.

2-dimensional systems

The occurrence rate of galaxies with polar structures may be significantly underestimated

Polar-ring galaxies are photometrically and kinematically decoupled systems that are highly inclined to the major axis of the host. These galaxies have been explored since the 1970s, but the rarity of these systems has made such systematic studies difficult. However, over 250 good candidates have been identified. In this work, we examine a sample of over 18 000 galaxies from the Sloan Digital Sky Survey (SDSS) Stripe 82 for the presence of galaxies with polar structures. Using deep SDSS Stripe 82, DESI Legacy Imaging Surveys, and Hyper Suprime-Cam Subaru Strategic Program, we selected 53 good candidate galaxies with photometrically decoupled polar rings, 9 galaxies with polar halos, 6 galaxies with polar bulges, and 34 possibly forming polar-ring galaxies, versus 13 polar-ring candidates previously selected in Stripe 82. Our results suggest that the occurrence rate of galaxies with polar structures may be significantly underestimated, as revealed by the deep observations, and may amount to 1–3% of non-dwarf galaxies.

Astronomy & Astrophysics

Studies of Flame Structure in Microgravity

The present research endeavor is concerned with gaining fundamental understanding of the configuration, structure, and dynamics of laminar premixed and diffusion flames under conditions of negligible effects of gravity. Of particular interest is the potential to establish and hence study the properties of spherically- and cylindrically-symmetric flames and their response to external forces not related to gravity. For example, in an earlier experimental study of the burner-stabilized cylindrical premixed flames, the possibility of flame stabilization through flow divergence was established, while the resulting one-dimensional, adiabatic, stretchless flame also allowed an accurate means of determining the laminar flame speeds of combustible mixtures. We have recently extended our studies of the flame structure in microgravity along the following directions: (1) Analysis of the dynamics of spherical premixed flames; (2) Analysis of the spreading of cylindrical diffusion flames; (3) Experimental observation of an interesting dual luminous zone structure of a steady-state, microbuoyancy, spherical diffusion flame of air burning in a hydrogen/methane mixture environment, and its subsequent quantification through computational simulation with detailed chemistry and transport; (4) Experimental quantification of the unsteady growth of a spherical diffusion flame; and (5) Computational simulation of stretched, diffusionally-imbalanced premixed flames near and beyond the conventional limits of flammability, and the substantiation of the concept of extended limits of flammability. Motivation and results of these investigations are individually discussed.

C K Law

Identifying Strain Stacking Boundaries between Multiphase Domains in Atomically Thin Two-Dimensional Magnets

Stacking engineering of van der Waals materials is an important strategy to control the materials’ properties, such as electronic correlations, ferroelectricity, and layer-dependent two-dimensional magnetism. A timely testbed for the study of the latter is atomically thin chromium trihalides (CrX 3 , X = Cl, Br, I). Notably, by understanding the sliding mechanism between different stacking sequences, control of the stacking arrangement, and thus magnetic properties in CrX 3 , can be achieved. Such insight, however, is currently lacking. Here, in this study, advanced electron microscopy methods are used to identify multiple stacking sequences corresponding to different bulk phases in atomically thin CrX 3 (X = Cl and Br) down to bilayer thickness and with lateral domain sizes as small as tens of nanometers. Indications of nanometer scale transitions and interactions at the stacking boundaries are found, including a universally preferred sliding direction that is consistent with density functional theory calculations and the strain fields at lateral heterostructure boundaries. This study demonstrates the necessity to consider local stacking structures when interpreting averaged magnetic properties measured with macroscale probes. Additionally, the preferred sliding direction insight from this study provides a strategy to control stacking sequence in atomically thin CrX 3 samples during the exfoliation and sample fabrication process.

DFT calculations

Dynamic Oscillation and Motion of Oil‐in‐Water Emulsion Droplets

The interplay of interfacial tensions on droplets results in a range of self‐powered motions that mimic those of living systems and serve as a tunable model to understand their complex non‐equilibrium behavior. Spontaneous shape deformations and oscillations are crucial features observed in nature but difficult to incorporate in synthetic artificial systems. Here, we report sessile oil‐in‐water emulsions that exhibit rapid oscillating behavior. The oscillations depend on the nature and concentration of the surfactant, the chemical composition of the oil, and the wettability of the solid substrate. The rapid changes in the contact angle per oscillation are observed using side‐view optical microscopy. We propose that the changes in the interfacial tension of the oil droplets is due to the partitioning of the surfactant into the oil phase and the movement of self‐emulsified oil out of the parent droplets giving rise to the rhythmic variation in droplet contact‐line. The ability to control and understand droplet oscillation can help model similar oscillations in out‐of‐equilibrium systems in nature and reproduce biomimetic behavior in artificial systems for various applications, such as microfluidic lab‐on‐a‐chip and adaptive materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Cooperative and bifunctional Ga-Ca-Cr 2 O 3 @CaO structured monoliths as versatile platform for reactive capture of CO 2 and its subsequent conversion to ethylene

Cooperative and bifunctional materials (BFMs) that integrate adsorbents and catalysts offer a promising strategy for the reactive capture of CO 2 to produce valuable fuels and chemicals. In this study, we developed structured BFMs via 3D printing that combine CaO as an adsorbent with Ga–Ca–Cr 2 O 3 metal oxides as the catalyst for the reactive capture of CO 2 and its subsequent conversion to C 2 H 4 via the oxidative dehydrogenation of C 2 H 6 (CO 2 -ODHE). Three different Ga–Ca compositions were used to modify the catalyst surface characteristics and enhance C 2 H 4 selectivity. In these formulations, Ga ions stabilize the oxygen lattice of the BFM, while Ca ions interact strongly with Cr to form CaCrO 4 , thereby altering the oxygen species and enhancing the material’s basic properties. Under adsorption–reaction conditions at 600–650 °C, the optimal BFM achieved an excellent C 2 H 4 selectivity of 96.4 %, attributed to a balanced redox process and improved basicity that facilitate efficient C 2 H 6 conversion and rapid desorption of C 2 H 4 without excessive oxidation. Overall, this work provides new insights into the formulation of BFMs monoliths and highlights the critical role of catalytic surface modification in enhancing C 2 H 4 selectivity in the CO 2 -ODHE reactive capture process.

C2H4 production

Comprehensive structural characterization of charged polymers involved in moisture-driven direct air capture

This study provides a comprehensive structural characterization of commercially available alkaline anion-exchange polymers (Fumasep FAA-3 and IRA 900) used in moisture-driven direct air capture (DAC) of carbon dioxide. Using X-ray diffraction, SAXS/WAXS, atomic force microscopy, FIB-SEM, and transmission electron microscopy, the authors identify nanoscale clustering, porosity, swelling behavior, and humidity-dependent structural changes that influence CO₂ adsorption and release. These findings establish structure–function relationships critical for designing more durable and energy-efficient DAC polymer materials.

36 MATERIALS SCIENCE

Development of a high fidelity CFD model for solvent evaporation and transport in porous structure during battery electrode drying

An efficient battery manufacturing process is the key to the mass production of Electric Vehicles (EV), in which drying is one of the most energy-intensive steps significantly influencing the battery cell performance. An accurate 3D CFD model for drying is essential for predicting the drying mechanism and optimizing its parameters. By optimizing the drying process, it is possible to reduce energy consumption and cost during battery manufacturing, minimize binder loading and maximize active material loading to achieve superior electrochemical performances and facilitate wider and faster public adoption of EV. This project aims to optimize the drying process during electrode manufacturing by leveraging high-fidelity, porous electrode simulations for solvent evaporation. By optimizing this process, we seek to reduce energy consumption during battery manufacturing, while minimizing binder loading and maximizing active material loading, with the overall goal of enhancing electrical vehicle performance.

Horner, Jeffrey Scott [Sandia National Laboratorie