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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A plant genetic network for preventing dysbiosis in the phyllosphere

The aboveground parts of terrestrial plants, collectively called the phyllosphere, have a key role in the global balance of atmospheric carbon dioxide and oxygen. The phyllosphere represents one of the most abundant habitats for microbiota colonization. Whether and how plants control phyllosphere microbiota to ensure plant health is not well understood. Here we show that the Arabidopsis quadruple mutant (min7 fls2 efr cerk1; hereafter, mfec)1, simultaneously defective in pattern-triggered immunity and the MIN7 vesicle-trafficking pathway, or a constitutively activated cell death1 (cad1) mutant, carrying a S205F mutation in a membrane-attack-complex/perforin (MACPF)-domain protein, harbour altered endophytic phyllosphere microbiota and display leaf-tissue damage associated with dysbiosis. The Shannon diversity index and the relative abundance of Firmicutes were markedly reduced, whereas Proteobacteria were enriched in the mfec and cad1S205F mutants, bearing cross-kingdom resemblance to some aspects of the dysbiosis that occurs in human inflammatory bowel disease. Bacterial community transplantation experiments demonstrated a causal role of a properly assembled leaf bacterial community in phyllosphere health. Here, the pattern-triggered immune signalling, MIN7 and CAD1 are found in major land plant lineages and are probably key components of a genetic network through which terrestrial plants control the level and nurture the diversity of endophytic phyllosphere microbiota for survival and health in a microorganism-rich environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗
DOE OSTI2020

Multiscale formulation of frictional contact mechanics at the pore scale

Direct numerical simulation (DNS) yields the highest fidelity predictions of mechanical deformation at the pore scale, but is prohibitively expensive for analyzing large or many samples. Discrete element methods (DEM) are an efficient alternative, but are limited to granular media and incapable of estimating or controlling prediction errors. We present a pore-level multiscale method (PLMM) that approximates DNS efficiently and with controllable accuracy. We focus on the linear elastic response of a consolidated geologic porous medium with arbitrary microstructure, heterogeneous mineralogy, containing cracks or defects. PLMM decomposes the solid phase into non-overlapping subdomains, on which local basis functions are constructed. The bases are then coupled with a global interface problem that accounts for slip or stick contact conditions between the subdomains. PLMM produces an initial, but accurate, approximation to DNS that can be iteratively improved. It is amenable to parallelism and allows for different mesh, models, and physics in each subdomain. An algebraic interpretation of PLMM as a preconditioner is also presented to allow non-intrusive implementation into existing solvers. Lastly, this work extends previous developments of PLMM in fluid dynamics to solid mechanics and enables future extensions towards modeling coupled flow and mechanics problems.

42 ENGINEERING↗
DOE OSTI2023

Breaking Rayleigh’s Law with Spatially Correlated Disorder to Control Phonon Transport

Controlling thermal transport in insulators and semiconductors is crucial for many technological fields such as thermoelectrics and thermal insulation, for which a low thermal conductivity (κ) is desirable. A major obstacle for realizing low κ materials is Rayleigh’s law, which implies that acoustic phonons, which carry most of the heat, are insensitive to scattering by point defects at low energy. We demonstrate, with large scale simulations on tens of millions of atoms, that isotropic long-range spatial correlations in the defect distribution can dramatically reduce phonon lifetimes of important low-frequency heat-carrying modes, leading to a large reduction of κ—potentially an order of magnitude at room temperature. We propose a general and quantitative framework for controlling thermal transport in complex functional materials through structural spatial correlations, and we establish the optimal functional form of spatial correlations that minimize κ. Finally, we end by briefly discussing experimental realizations of various correlated structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Microdynamics of active particles in defect-rich colloidal crystals

Hypothesis. Because they are self-propulsive, active colloidal particles can interact with their environment in ways that differ from passive, Brownian particles. Here, we explore how interactions in different microstructural regions may contribute to colloidal crystal annealing. Experiments. We investigate active particles propagating in a quasi-2D colloidal crystal monolayer produced by alternating current electric fields (active-to-passive particle ratio ~ 1:720). The active particle is a platinum Janus sphere propelled by asymmetric decomposition of hydrogen peroxide. Crystals are characterized for changes in void properties. The mean-squared-displacement of Janus particles are measured to determine how active microdynamics depend on the local microstructure, which is comprised of void regions, void-adjacent regions (defined as within three particle diameters of a void), and interstitial regions. Findings. At active particle energy E A = 2.55 k B T, the average void size increases as much as three times and the average void anisotropy increases about 40% relative to the passive case. Further, the average microdynamical enhancement, <δ(t)>, of Janus particles in the crystal relative to an equivalent passive Janus particle is reduced compared to that of a free, active particle (<δ(t) > is 1.88 ± 0.04 and 2.66 ± 0.08, respectively). The concentration of active particles is enriched in void and void-adjacent regions. Active particles exhibit the greatest change in dynamics relative to the passive control in void-adjacent regions (<δ(t)> = 2.58 ± 0.06). The results support the conjecture that active particle microdynamical enhancement in crystal lattices is affected by local defect structure.

36 MATERIALS SCIENCE↗
DOE OSTI2025

2D Vacancy Confinement in Anatase TiO 2 for Enhanced Photocatalytic Activities

Abstract Light‐driven energy conversion devices call for the atomic‐level manipulation of defects associated with electronic states in solids. However, previous approaches to produce oxygen vacancy (V O ) as a source of sub‐bandgap energy levels have hampered the precise control of the distribution and concentration ofV O . Here, a new strategy to spatially confineV O at the homo‐interfaces is demonstrated by exploiting the sequential growth of anatase TiO 2 under dissimilar thermodynamic conditions. Remarkably, metallic behavior with high carrier density and electron mobility is observed after sequential growth of the TiO 2 films under low pressure and temperature (L‐TiO 2 ) on top of high‐quality anatase TiO 2 epitaxial films (H‐TiO 2 ), despite the insulating properties of L‐TiO 2 and H‐TiO 2 single layers. Multiple characterizations elucidate that theV O layer is geometrically confined within 4 unit cells at the interface, along with low‐temperature crystallization of upper L‐TiO 2 films; this 2DV O layer is responsible for the formation of in‐gap states, promoting photocarrier lifetime (≈300%) and light absorption. These results suggest a synthetic strategy to locally confine functional defects and emphasize how sub‐bandgap energy levels in the confined imperfections influence the kinetics of light‐driven catalytic reactions.

Chemistry↗
DOE OSTI2022

Photodiode-based machine learning for optimization of laser powder bed fusion parameters in complex geometries

We report the quality of parts produced through laser powder bed fusion additive manufacturing can be irregular, with complex geometries sometimes exhibiting dimensional inaccuracies and defects. For optimal part quality, laser process parameters should be selected carefully prior to printing and adjusted during the print if necessary. This is challenging since approaches to control and optimize the build parameters need to take into account the part geometry, the material, and the complex physics of laser powder bed fusion. This work describes a data-driven approach using experimental diagnostics for the optimization of laser process parameters prior to printing. A training dataset is generated by collecting high speed photodiode signal data while printing simple parts containing key geometry features with various process parameter strategies. Supervised learning approaches are employed to train both a forward model and an inverse model. The forward model takes as inputs track-wise geometry features and laser parameters and outputs the photodiode signal along the scan path. The inverse model takes as inputs the geometry features and photodiode signal and predicts the laser parameters. Given the part geometry and a desired photodiode signal, the inverse model can thus determine the required laser parameters. Two test parts which contain defect-prone features are used to assess the validity of the inverse model. The use of the model leads to improved part quality (higher dimensional accuracy, reduced dross, reduced distortion) for both test geometries.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Optical vortex manipulation for topological quantum computation

Topological quantum computation based on Majorana bound states may enable new paths to fault-tolerant quantum computing. Several recent experiments have suggested that the vortex cores of topological superconductors, such as iron-based superconductors, may host Majorana bound states at zero energy. However, quantum computation with these zero-energy vortex bound states requires precise and fast manipulation of individual vortices, which is difficult to do in a scalable manner. To address this issue, in this study we propose a control scheme based on local heating via, for example, scanning optical microscopy to braid vortex-bound Majorana zero modes in a two-dimensional topological superconductor. First, we derive the conditions required for transporting a single vortex between two defects in the superconducting material by trapping it with a hot spot generated by local optical heating. Equipped with critical conditions for the vortex motion, we then establish the ideal material properties for vortex braiding and describe how transition errors resulting from finite speed and/or temperature can be minimized. Our work paves the way toward optical or microscopic control of zero-energy vortex bound states in two-dimensional topological superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Synthesis and Properties of Bulk Mg 3 WN 4 in a Wurtzite-Derived Structure

Experimental synthesis of theoretically predicted materials with controlled elemental coordination environments can lead to the realization of useful properties, such as facile ion transport or ferroelectric switching. Among such materials are ternary nitrides in the Mg−W−N composition space, where several stable and metastable compounds have been predicted and synthesized recently in bulk and film forms. Here, we report for the first time on the bulk synthesis of Mg 3 WN 4 in a wurtzite-derived crystal structure via a solid-state metathesis reaction. In situ synchrotron powder X-ray diffraction shows how the ion exchange proceeds from Li 6 WN 4 + MgCl 2 precursors to Mg 3 WN 4 + LiCl products, with the reaction starting slowly near 380 °C and completing by 600 °C, including the presence of a competing disordered rocksalt-derived phase (Mg,W)N above 440 °C. The follow-up ex situ powder synthesis at 400 °C for 0.5 h with 10% excess MgCl 2 reveals the cation-ordered nature of the wurtzite-derived Mg 3 WN 4 structure with polar symmetry confirmed by second-harmonic generation measurements. Optical absorption spectra, chemical composition analysis, and electron microscopy imaging suggest that bulk Mg 3 WN 4 obtained via metathesis reaction is prone to defect formation. Overall, this study shows that selective ex situ synthesis of the phase-pure ternary nitrides, informed by in situ measurements, is possible by carefully controlling the thermal budget of the reaction and paves the way toward property characterization of the Mg 3 WN 4 wurtzite-derived material.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Solid-phase hetero epitaxial growth of α-phase formamidinium perovskite

Conventional epitaxy of semiconductor films requires a compatible single crystalline substrate and precisely controlled growth conditions, which limit the price competitiveness and versatility of the process. We demonstrate substrate-tolerant nano-heteroepitaxy (NHE) of high-quality formamidinium-lead-tri-iodide (FAPbI 3 ) perovskite films. The layered perovskite templates the solid-state phase conversion of FAPbI 3 from its hexagonal non-perovskite phase to the cubic perovskite polymorph, where the growth kinetics are controlled by a synergistic effect between strain and entropy. The slow heteroepitaxial crystal growth enlarged the perovskite crystals by 10-fold with a reduced defect density and strong preferred orientation. This NHE is readily applicable to various substrates used for devices. The proof-of-concept solar cell and light-emitting diode devices based on the NHE-FAPbI 3 showed efficiencies and stabilities superior to those of devices fabricated without NHE.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Using the optimal combined index weight ratio to improve the probability of anomaly detection in big area additive manufacturing

Big Area Additive Manufacturing (BAAM) of composites requires significant time, energy, and material, so it is critical to reduce production inefficiencies to make functional parts without multiple iterations. Statistical process control coupled with Principal Component Analysis (PCA) is a powerful technique that provides a quick, computationally inexpensive, and intuitive way for operators to detect defects that form in a manufacturing process without massive datasets. Recently, a combined index that is a weighted sum of the Hotelling's T 2 and squared residual error statistics has been proposed that can be monitored in one chart, improving interpretation accuracy and simplicity. However, the literature does not offer a formal method to optimise the weights. Here, we introduce two new approaches to the traditional weight selection approach using simulated and BAAM image data. Approach 1 uses a theoretically motivated optimum inspired by probabilistic principal component analysis. Approach 2 systematically varies the ratio of the weights to find the optimum. We show that approach 1 delivers optimal anomaly detection performance in select cases while approach 2 fares better in practice. Surprisingly, we also show that choosing a more complex PCA model has a minimal negative impact on anomaly detection performance compared to a more simplistic model.

3-dimensional printing↗
DOE OSTI2022

Additive manufacturing power map to mitigate overhang structure

A laser powder bed fusion additive manufacturing system for producing a part by creating a power map that is an intelligent feed forward model to control the laser powder bed fusion additive manufacturing for producing the part and using the power map to control the laser powder bed fusion additive manufacturing for producing the part. This includes an apparatus for producing a part including a powder bed, a laser that produces a laser beam, a proportional integral derivative controller that creates a power map that describes laser power requirements as the laser moves along a path, wherein the laser power requirements prevent defects in the part.

Khairallah, Saad A.↗
DOE OSTI2023

Chirality reversal of magnetic solitons in chiral Cr 1/3 TaS 2

Ferromagnetism in two-dimensional (2D) materials provides an ideal platform to study emergent electromagnetic phenomena in low dimensions for future spintronics. In magnetic-element intercalated transition metal dichalcogenides, topologically nontrivial spin textures, such as chiral helimagnetic spin states and chiral soliton lattices, are realized due to the chiral lattice distortions induced by intercalated magnetic ions. Consequently, the magnetic chirality is predictably determined by the sign of antisymmetric exchange interaction (or Dzyaloshinskii–Moriya interaction, DMI) vector that is coupled to the underlying crystal chirality. Here, using cryogenic Lorentz phase microscopy, we directly observed the chirality reversal behavior of the chiral soliton lattices in Cr 1/3 TaS 2 across the structural defects. We show that a partial 1 T stacking in 2H-TaS 2 locally reduces DMI, leading to magnetic chirality reversal with direct atomic resolution imaging. Furthermore, our experimental results show that manipulation of stacking sequence provides a viable way to control the chirality of topologically nontrivial soliton lattices in 2D magnets.

2D materials↗
DOE OSTI2024

Alternating-bias assisted annealing of amorphous oxide tunnel junctions

Superconducting quantum bits (qubits) rely on ultra-thin, amorphous oxide tunneling barriers that can have significant inhomogeneities and defects as grown. This can result in relatively large uncertainties and deleterious effects in the circuits, limiting the scalability. Finding a robust solution to the junction reproducibility problem has been a long-standing goal in the field. Here, we demonstrate a transformational technique for controllably tuning the electrical properties of aluminum-oxide tunnel junctions. This is accomplished using a low-voltage, alternating-bias applied individually to the tunnel junctions, with which resistance tuning by more than 70% can be achieved. The data indicates an improvement of coherence and reduction of two-level system defects. Transmission electron microscopy shows that the treated junctions are predominantly amorphous, albeit with a more uniform distribution of alumina coordination across the barrier. This technique is expected to be useful for other devices based on ionic amorphous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Discovery of atomic clock-like spin defects in simple oxides from first principles

Virtually noiseless due to the scarcity of spinful nuclei in the lattice, simple oxides hold promise as hosts of solid-state spin qubits. However, no suitable spin defect has yet been found in these systems. Using high-throughput first-principles calculations, we predict spin defects in calcium oxide with electronic properties remarkably similar to those of the NV center in diamond. These defects are charged complexes where a dopant atom — Sb, Bi, or I — occupies the volume vacated by adjacent cation and anion vacancies. The predicted zero phonon line shows that the Bi complex emits in the telecommunication range, and the computed many-body energy levels suggest a viable optical cycle required for qubit initialization. Notably, the high-spin nucleus of each dopant strongly couples to the electron spin, leading to many controllable quantum levels and the emergence of atomic clock-like transitions that are well protected from environmental noise. Specifically, the Hanh-echo coherence time increases beyond seconds at the clock-like transition in the defect with 209 Bi. Our results pave the way to designing quantum states with long coherence times in simple oxides, making them attractive platforms for quantum technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Modeling Framework to Predict Melting Dynamics at Microstructural Defects in TNT-HMX High Explosive Composites

Many high explosive (HE) formulations are composite materials whose microstructure is understood to impact functional characteristics. Interfaces are known to mediate the formation of hot spots that control their safety and initiation. Here, to study such processes at molecular scales, we developed all-atom force fields (FFs) for Octol, a prototypical HE formulation comprised of TNT (2,4,6-trinitrotoluene) and HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine). We extended a FF for TNT and recasted it in a form that can be readily combined with a well-established FF for HMX. The resulting FF was extensively validated against experimental results and density functional theory calculations. We applied the new combined TNT-HMX FF to predict and rank surface and interface energies, which indicate that there is an energetic driver for coarsening of microstructural grains in TNT-HMX composites. Finally, we assess the impact of several microstructural environments on the dynamic melting of TNT crystal under ultrafast thermal loading. We find that both free surfaces and planar material interfaces are effective nucleation points for TNT melting. However, MD simulations show that TNT crystal is prone to superheating by at least 50 K on subnanosecond time scales and that the degree of superheating is inversely correlated with surface and interface energy. The modeling framework presented here will enable future studies on hot spot formation processes in accident scenarios that are governed by strong coupling between microstructural interfaces, material mechanics, momentum and energy transport, phase transitions, and chemistry.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Evidence for nitrogen binding to surface defects for topological insulator Bi 2 Se 3

Using scanning tunneling spectroscopy and theoretical simulations we have studied the effects of nitrogen gas exposure on the electronic density of states of Bi 2 Se 3 , a well-studied topological insulator. In carefully controlled measurements, Bi 2 Se 3 crystals were initially cleaved in a helium gas environment and then exposed to a 22 SCFH flow of ultra-high purity N 2 gas. We observe a resulting change in the spectral curves, with the exposure effect saturating after approximately 50 min, ultimately bringing the Dirac point about 50 meV closer to the Fermi level. Furthermore, these results are compared to density functional theory calculations, which support a picture of N 2 molecules physisorbing near Se vacancies. Furthermore, ab initio molecular dynamics simulations aided by a Blue Moon ensemble method reveal the dissociative adsorption of N 2 molecules which then bind strongly to Se vacancies at the surface. In this scenario, the binding of the N atom to a Se vacancy site removes the surface defect state created by the vacancy and changes the position of the Fermi energy with respect to the Dirac point.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A universal method to fabricating porous carbon for Li-O 2 battery

The main bottleneck in the application of biomass-based carbon material in energy field is the development of an economical, nanoscale controllable and universal fabrication method. Herein, we demonstrate that a biomass-derived carbon consisting of loose carbon nanosphere clusters could serve as an ideal cathode material for high performance Li-O 2 batteries. The carbon nanomaterial can be prepared from both biomass derivatives and crude biomass by a low cost, facile and nanoscale controllable method. The open slit-shaped hierarchical pore structure endows the electrode sufficient active surface sites and mass transport channels that are not easily asphyxiated by the discharge products. The concentration of oxygenic groups and structure defects on the surface of obtained carbon materials is very low, which minimizes the side reactions associated with carbon decomposition. Finally, the unique pore structure and surface properties of the carbon electrode give rise to a superhigh specific capacity of 20,300 mA h g -1 and an extremely long cycle life which a cyclic capacity retention of 100% is maintained for 543 cycles with current density of 0.2 mA cm -2 at controlled discharge-charge depths of 500 mA h g -1 .

25 ENERGY STORAGE↗