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At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Magnetism and topological Hall effect in antiferromagnetic Ru 2 MnSn-based Heusler compounds

Heusler compounds and alloys based on them are of great recent interest because they exhibit a wide variety of spin structures, magnetic properties, and electron-transport phenomena. Their properties are tunable by alloying and we have investigated L2 1 -orderd compound Ru 2 MnSn and its alloys by varying the atomic Mn:Sn composition. While antiferromagnetic ordering with a Néel temperature of 361 K was observed in Ru 2 MnSn, the Mn-poor Ru 2 Mn 0.8 Sn 1.2 alloy exhibits properties of a diluted antiferromagnet in which there are localized regions of uncompensated Mn spins. Furthermore, a noncoplanar spin structure, evident from a topological Hall-effect contribution to the room-temperature Hall resistivity, is realized in Ru 2 Mn 0.8 Sn 1.2 . Finally, our combined experimental and theoretical analysis shows that in the Ru 2 Mn 0.8 Sn 1.2 alloy, the magnetic properties can be explained in terms of a noncoplanar antiferromagnetic scissor mode, which creates a small net magnetization in a magnetic field and subsequently yields a Berry curvature with a strong topological Hall effect.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Structural Origin of Chiroptical Properties in Perovskite Nanocrystals with Chiral Organic Ligands

Abstract The authors investigate how chiral ligands attached to perovskite nanocrystal (PNC) surfaces structurally distort the perovskite lattice. Chiral electro‐optical properties of the resulting PNCs are demonstrated through the fabrication of a circularly polarized light (CPL) detector with a discrimination of up to 14% between left‐ and right‐handed CPL. Both experimental and electronic‐structure‐based simulations are combined to provide insights into the interactions (both structural and electronic) between chiral organic ligands and PNCs. The major finding is a centro‐asymmetric distortion of the surface lattice that penetrates up to five atomic unit cells deep into the PNCs, which is the likely cause of the chiral‐optical properties. Spin‐polarized transport through chiral‐PNCs results from the chiral‐induced spin selectivity effect and amplifies the discrimination between left and right‐handed CPL as is experimentally demonstrated in the detectors.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Characterization of Novel Spacecraft Materials aboard the Materials International Space Station Experiment-Flight Facility (Preliminary Results)

This work will encompass the preflight characterization of 15 novel and heritage materials currently under observation on the Materials International Space Station Experiment-Flight Facility (MISSE-FF). MISSE-FF has been upgraded to perform active reflectance measurements of the materials. Images taken in RGB/IR colors are compared to results from an extensive ground testing campaign to obtain quantitative on-orbit material evolution data. Identical materials samples are to be flown on the ram, wake, and zenith faces of MISSE-FF, enabling deconvolution of the energetic electron, proton, atomic oxygen, and ultraviolet damage pathways. Energy deposition from the space environment leads to chemical changes in the material that in turn alter the optical properties. The same chemical damage that manifests as changes in optical reflectance and absorptance also leads to changes in myriad physical properties such as mechanical strength, electrical conductivity, and chemical reactivity. Therefore, flight materials are able to be characterized based on their unique reflectance spectra by comparing on-orbit measurements of optical reflectance with extensive terrestrial experiments, which help to correlate changes in reflectance with respect to changes in other material properties. The MISSE program has been a part of the International Space Station National Laboratory for many years and has been instrumental in understanding space weather modification of material properties. However, MISSE-FF has been limited to passive experiments with only pre/post flight material studies possible. In advance of the MISSE-16 experiment, the flight facility has received a major upgrade to provide daily spectral observations by way of a RGB/IR camera and a tunable light source. The MISSE-16 mission launched in February 2022 and carries 15 material samples for 6 months of the low Earth orbital exposure. Identical materials samples are to be flown on the ram, wake, and zenith faces of MISSE-FF, enabling deconvolution of the energetic electron, proton, atomic oxygen, and ultraviolet damage pathways. This paper discusses the MISSE-16 experiment, highlights the first use of the facility upgrades, and presents results from the extensive preflight material characterization that includes directional hemispherical reflectance, bidirectional reflectance, AFM, SEM, and electrical conductivity. Additionally, data showing the modification of these properties by ground-based exposure to space-like electron and atomic oxygen flux will be discussed. Finally, updates on deployment and initial check-out of the experiment on MISSE-FF will be presented. It is the ultimate goal of this program to provide validation for the development of ground based space weather simulation facilities and techniques.

Ryan Hoffman↗
DOE OSTI2021

Core–Shell Gold Nanoparticle-Star Copolymer Composites with Gradient Transfer and Transport Properties: Toward Electro-Optical Sensors and Catalysis

A series of hybrid core–shell nanomaterials was prepared by solvent phase transfer methods with gold (Au) nanoparticles (NPs) as a core and star copolymers (h-PEI-b-PCL-Cbz) as a shell—consisting of hyperbranched polyethyleneimine (h-PEI) with different poly(ε-caprolactone) (PCL) chain lengths and a carbazole-contained terminating agent (Cbz). By varying the PCL chain length, these core–shell nanomaterials exhibited gradient energy transfer properties, surface hydrophobicity, electropolymerizability, and ionic probe transport and diffusion properties. The systematic copolymer formation was verified with quadruple-detector size exclusion chromatography (SEC) and 1H nuclear magnetic resonance (NMR). High-resolution atomic force microscopy-infrared spectroscopy (AFM-IR) chemical mapping verified nanoparticle-substrate adhesion and film formation. The design of these hybrid NPs and elucidation of gradient properties will be useful for future applications of the core–shell systems in electro-optical sensing and catalysis.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Space environmental effects on LDEF low Earth orbit exposed graphite reinforced polymer matrix composites

The Long Duration Exposure Facility (LDEF) was deployed on April 7, 1984 in low earth orbit (LEO) at an altitude of 482 kilometers. On board experiments experienced the harsh LEO environment including atomic oxygen (AO), ultraviolet radiation (UV), and thermal cycling. During the 5.8 year mission, the LDEF orbit decayed to 340 kilometers where significantly higher AO concentrations exist. LDEF was retrieved on January 12, 1990 from this orbit. One experiment on board LDEF was M0003, Space Effects on Spacecraft Materials. As a subset of M0003 nearly 500 samples of polymer, metal, and glass matrix composites were flown as the Advanced Composites Experiment M0003-10. The Advanced Composites Experiment is a joint effort between government and industry with the Aerospace Corporation serving as the experiment integrator. A portion of the graphite reinforced polymer matrix composites were furnished by the Boeing Defense and Space Group, Seattle, Washington. Test results and discussions for the Boeing portion of M0003-10 are presented. Experiment and specimen location on the LDEF are presented along with a quantitative summary of the pertinent exposure conditions. Matrix materials selected for the test were epoxy, polysulfone, and polyimide. These composite materials were selected due to their suitability for high performance structural capability in spacecraft applications. Graphite reinforced polymer matrix composites offer higher strength to weight ratios along with excellent dimensional stability. The Boeing space exposed and corresponding ground control composite specimens were subjected to post flight mechanical, chemical, and physical testing in order to determine any changes in critical properties and performance characteristics. Among the more significant findings are the erosive effect of atomic oxygen on leading edge exposed specimens and microcracking in non-unidirectionally reinforced flight specimens.

George, Pete↗
DOE OSTI2025

Chemistry and Interfacial Structure Promoting Quasi-van der Waals Epitaxial Growth of WS 2 Nanosheets on Sapphire for Prospective Application in Field-Effect Transistors

How do chemical and structural modifications to the supporting crystal surface affect the subsequent van der Waals (vdW) or quasi(Q)-vdW epitaxial growth of 2D nanocrystals? Developing an atomic-scale picture of such an interfacial system is crucial for understanding its impact on the physical and chemical properties of the supported 2D materials. The elucidation of the interfacial structure and chemistry needed to promote the Q-vdW epitaxial growth of 2D tungsten disulfide (WS 2 ) nanocrystals contributes to the growth mechanism understanding, thus pushing forward the integration of such atomically thin semiconductors toward real field-effect transistor applications. In addition to an atomic-force microscopy top view, we showcase a combination of X-ray techniques for a top-to-bottom investigation of the complexities of the buried interface structures. Furthermore, this approach uses X-ray photoelectron spectroscopy, X-ray standing wave excited X-ray fluorescence, and crystal truncation rod scattering to produce a highly resolved chemical-state-specific 3D atomic map for the extended interface structure of WS 2 /α-Al 2 O 3 (001). Employing these detailed analysis methods, along with density functional theory to further refine the picoscale structure, we demonstrate how two different types of interface engineering during the pregrowth stage lead to significant differences in the chemical and structural modifications to the terminal surface of c-face sapphire, which in turn leads to substantial differences in the submonolayer growth of supported WS 2 2D nanocrystals in terms of lateral domain sizes, epitaxial registry, vdW gaps, and stability.

36 MATERIALS SCIENCE↗
NASA NTRS1991

Simulation studies for surfaces and materials strength

Investigations were carried out in the following three areas. First, a simulation study was conducted to investigate the early stages of a nucleation and growth mechanism taking place on diamond surfaces. The energetically most favorable binding sites were calculated along with the binding energies for up to three carbon atoms deposited on the planes of a diamond crystal. Secondly, calculations were carried out to analyze energies and structural properties for restructured patterns of the surface of a diamond. Two different model functions, developed recently for carbon, were employed in the calculations. Lastly, a crack propagation process for the graphitic basal plane, was investigated using a molecular dynamics technique. Interactions among carbon atoms in the system were calculated using the Tersoff potential energy function.

Halicioglu, Timur↗
DOE OSTI2020

Predicting the propensity for thermally activated β events in metallic glasses via interpretable machine learning

Abstract The elementary excitations in metallic glasses (MGs), i.e., β processes that involve hopping between nearby sub-basins, underlie many unusual properties of the amorphous alloys. A high-efficacy prediction of the propensity for those activated processes from solely the atomic positions, however, has remained a daunting challenge. Recently, employing well-designed site environment descriptors and machine learning (ML), notable progress has been made in predicting the propensity for stress-activated β processes (i.e., shear transformations) from the static structure. However, the complex tensorial stress field and direction-dependent activation could induce non-trivial noises in the data, limiting the accuracy of the structure-property mapping learned. Here, we focus on the thermally activated elementary excitations and generate high-quality data in several Cu-Zr MGs, allowing quantitative mapping of the potential energy landscape. After fingerprinting the atomic environment with short- and medium-range interstice distribution, ML can identify the atoms with strong resistance or high compliance to thermal activation, at a high accuracy over ML models for stress-driven activation events. Interestingly, a quantitative “between-task” transferring test reveals that our learnt model can also generalize to predict the propensity of shear transformation. Our dataset is potentially useful for benchmarking future ML models on structure-property relationships in MGs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Machine learning defect properties in Cd-based chalcogenides

Impurity energy levels in the band gap can have serious consequences for a semiconductor's performance as a photovoltaic absorber. Data-driven approaches can help accelerate the prediction of point defect properties in common semiconductors, and thus lead to the identification of potential deep lying impurity states. In this work, we use density functional theory (DFT) to compute defect formation energies and charge transition levels of hundreds of impurities in CdX chalcogenide compounds, where X = Te, Se or S. We apply machine learning techniques on the DFT data and develop on-demand predictive models for the formation energy and relevant transition levels of any impurity atom in any site. The trained ML models are general and accurate enough to predict the properties of any possible point defects in any Cd-based chalcogenide, as we prove by testing on a few selected defects in mixed chalcogen compounds CdTe 0.5 Se 0.5 and CdSe 0.5 S 0.5 . The ML framework used in this work can be extended to any class of semiconductors.

density functional theory↗
DOE OSTI2021

Probing Microstructure-induced Swelling & Thermal Property Changes in Ion-Irradiated Oxide Fuels using Laser-generated Surface Acoustic Waves

Radiation of fuel rods with neutrons during a fission reaction in a nuclear reactor is known to affect the material microstructure of the fuel as a result of fission fragment damage, and lead to the formation of atomic-level defects such as voids, dislocation loops, and lattice swelling from fission-gas release. A consequence of the radiation-induced damage in nuclear fuels is the drastic alteration of material properties, in particular, the reduction of the thermal conductivity – a key parameter that governs the transport of thermal energy released from fissile fuel atoms to the surrounding coolant. Swelling can induce high stresses and ultimate failure of the cladding. A fundamental understanding of the role of radiation-induced damage on the thermal transport and mechanical properties of nuclear fuels is therefore critical for efficient, reliable and safe operation of a nuclear power plant. As opposed to conventional post-irradiation examination techniques that are often time-consuming and require significant sample preparation, laser-based characterization methods have emerged as promising non-contact, non-destructive tools to measure the evolution of microstructure-induced material property changes. Moreover, laser methods offer the promise of in-situ characterization while the material is being irradiated. This project aims to develop an improved understanding of the impact of radiation-induced changes to material microstructure on the thermal and elastic properties of nuclear materials. A laser ultrasonic technique, known as the transient grating (TG) spectroscopy method, is used to simultaneously measure thermal diffusivity and elastic properties in unirradiated and ion-irradiated oxide nuclear fuel samples. The results will complement on-going investigations on electron- and phonon-mediated thermal transport in nuclear materials and will provide foundational work for incorporating the influence of defects in fuel performance codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Utilization of coupled eigenmodes in Akiyama atomic force microscopy probes for bimodal multifrequency sensing

Akiyama atomic force microscopy probes represent a unique means of combining several of the desirable properties of tuning fork and cantilever probe designs. As a hybridized mechanical resonator, the vibrational characteristics of Akiyama probes result from a complex coupling between the intrinsic vibrational eigenmodes of its constituent tuning fork and bridging cantilever components. Here, through a combination of finite element analysis modeling and experimental measurements of the thermal vibrations of Akiyama probes, we identify a complex series of vibrational eigenmodes and measure their frequencies, quality factors, and spring constants. We then demonstrate the viability of Akiyama probes to perform bimodal multi-frequency force sensing by performing a multimodal measurement of a surface's nanoscale photothermal response using photo-induced force microscopy imaging techniques. Further performing a parametric search over alternative Akiyama probe geometries, we propose two modified probe designs to enhance the capability of Akiyama probes to perform sensitive bimodal multifrequency force sensing measurements.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Toward Low-Thermal-Budget Hafnia-Based Ferroelectrics via Atomic Layer Deposition

Since the first report of ferroelectricity in fluorite structure oxides a decade ago, significant attention has been devoted to studying hafnia-based ferroelectric material systems due to their promising properties and opportunities. To achieve such ferroelectric fluorite structure oxides at low temperatures (below 400 °C), stabilizing the metastable noncentrosymmetric orthorhombic phase is crucial. This review provides a comprehensive overview of atomic layer deposition (ALD) techniques for obtaining the orthorhombic phase for low-temperature ferroelectric applications. We discuss optimization of the ALD process for synthesizing high-quality, low-temperature crystallizing ferroelectric films, including doping, precursor and oxygen source selection, deposition temperature, and interface engineering. In addition, the techniques for stabilizing the ferroelectric phase by regulating the thermal budget and stress with various annealing methods and stressors are discussed. In conclusion, the review focuses on different techniques to reduce the thermal budget required to acquire ferroelectricity, making hafnia-based ferroelectric materials compatible with back-end-of-line and three-dimensional integration for a variety of future applications, including flexible electronics applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Prediction of carbon nanostructure mechanical properties and the role of defects using machine learning

Graphene-based nanostructures hold immense potential as strong and lightweight materials, however, their mechanical properties such as modulus and strength are difficult to fully exploit due to challenges in atomic-scale engineering. This study presents a database of over 2,000 pristine and defective nanoscale CNT bundles and other graphitic assemblies, inspired by microscopy, with associated stress–strain curves from reactive molecular dynamics (MD) simulations using the reactive INTERFACE force field (IFF-R). These 3D structures, containing up to 80,000 atoms, enable detailed analyses of structure-stiffness-failure relationships. By leveraging the database and physics- and chemistry-informed machine learning (ML), accurate predictions of elastic moduli and tensile strength are demonstrated at speeds 1,000 to 10,000 times faster than efficient MD simulations. Hierarchical Graph Neural Networks with Spatial Information (HS-GNNs) are introduced, which integrate chemistry knowledge. HS-GNNs as well as extreme gradient boosted trees (XGBoost) achieve forecasts of mechanical properties of arbitrary carbon nanostructures with only 3 to 6% mean relative error. The reliability equals experimental accuracy and is up to 20 times higher than other ML methods. Predictions maintain 8 to 18% accuracy for large CNT bundles, CNT junctions, and carbon fiber cross-sections outside the training distribution. The physics- and chemistry-informed HS-GNN works remarkably well for data outside the training range while XGBoost works well with limited training data inside the training range. The carbon nanostructure database is designed for integration with multimodal experimental and simulation data, scalable beyond 100 nm size, and extendable to chemically similar compounds and broader property ranges. The ML approaches have potential for applications in structural materials, nanoelectronics, and carbon-based catalysts.

Winetrout, Jordan J.↗
DOE OSTI2021

Multisublattice cluster expansion study of short-range ordering in iron-substituted strontium titanate

Owing to the challenges in obtaining realistic atomic configurations in large chemical phase spaces, it is not straightforward to describe structure–property relations in materials exhibiting configurational disorder. One example is iron-substituted strontium titanate (SrTi 1–x Fe x O 3–d , STF), a promising perovskite-derivative cathode material in solid oxide fuel cells that exhibits full solid solubility 0 ≤ x ≤ 1 and a tendency to exhibit short-range order. Here we demonstrate a multisublattice cluster expansion (CE) framework and apply it to STF across the full composition range. The CE approach is distinct from more traditional CE formulations in that clusters are defined explicitly by the chemical species distributed among multiple sublattices, rather than via cluster functions of occupation variables with decoration. The modified CE approach makes it easy to distinguish meaningful chemical interactions that are harder to extract from conventional CE, since for the latter chemical identity in a cluster is expressed as a product of site occupations. The least absolute shrinkage and selection operator (LASSO) is implemented as a regression analysis tool to select key clusters and avoid overfitting. We demonstrate this formulation on STF, and show that it can accurately predict configurational energies in comparison to conventional CE. From the key clusters, we identify that short-range ordering between substitutional Fe and oxygen vacancies (V O ) results in the formation of Fe–VO strings. In addition, we consider the stability of STF through CE-based Monte Carlo (MC) simulations and confirm the presence of superstructures that were previously observed in transmission electron microscopy. In this work, analysis of atomic configurations from MC samples reveals variations in the oxidation state of Fe atoms, which can be explained by the ordering tendency of Fe and V O . The cluster description and selection formalism described here may be applied to other disordered multisublattice systems for accurate and efficient material modeling.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Atomic-Scale Tracking of Topological Defect Motion and Incommensurate Charge Order Melting

Charge order pervades the phase diagrams of quantum materials where it competes with superconducting and magnetic phases, hosts electronic phase transitions and topological defects, and couples to the lattice generating intricate structural distortions. Incommensurate charge order is readily stabilized in manganese oxides, where it is associated with anomalous electronic and magnetic properties, but its nanoscale structural inhomogeneity complicates precise characterization and understanding of its relationship with competing phases. Leveraging atomic-resolution variable-temperature cryogenic scanning transmission electron microscopy, we characterize the thermal evolution of charge order as it transforms from its ground state in a model manganite system. We find that mobile networks of discommensurations and dislocations generate phase inhomogeneity and induce global incommensurability in an otherwise lattice-locked modulation. Driving the order to melt at high temperatures, the discommensuration density grows, and regions of order locally decouple from the lattice periodicity. Published by the American Physical Society 2025

Schnitzer, Noah (ORCID:0000000210421146)↗
DOE OSTI2025

Deep potential molecular dynamics simulations of ion-enhanced etching of silicon by atomic chlorine

The continued development of plasma-assisted processing techniques requires a fundamental understanding of plasma-surface interactions. Molecular dynamics (MD) simulations have been employed to complement experimental studies and better understand the properties of such systems. Recently, machine learning (ML) methods have enabled the development of ab initio-based interatomic potentials, which can be generalized to complex combinations of multiple atom types. In this work, we use ML potentials developed using the Deep Potential Molecular Dynamics (DeepMD) framework to provide a model of ion-enhanced etching of Si by Cl atoms. We demonstrate the importance of proper selection of the training data set to the accuracy of the DeepMD model and compare our results to MD results using empirical potentials, as well as to experimental measurements. Exposure of undoped Si at 300 K to thermal Cl atoms yields a steady-state Cl coverage of 1.25 monolayers, which is slightly lower than the value obtained in previous experimental studies. Predictions of Si etch yields by simultaneous Cl atom and Ar + ion impacts as a function of ion energy, neutral to ion flux ratio, and angle of incidence of the ions are in reasonably good agreement with classical MD results and experimental measurements. Finally, etch yields and SiCl x mixed layer thicknesses during simultaneous bombardment of the Si(100) surface by Cl atoms and Cl + ions are in good agreement with experimental data. In conclusion, the present work is a necessary condition for the extension of the DeepMD procedure to more complex systems of interest in plasma-surface interactions.

Artificial neural networks↗
DOE OSTI2022

Effect of interfacial vibrational coupling on surface wettability and water transport

Here, we report that the atomic-scale vibrational coupling at the solid-fluid interface can substantially alter the interfacial properties such as wettability and fluid slip. The wettability of water droplets on substrates subjected to various vibrational frequencies is studied using molecular dynamics simulation. The contact angle increases (i.e., becomes more hydrophobic) when the oscillation frequency of the substrate matches the intermolecular bending frequency of liquid water. We investigate the underlying mechanism by examining the dynamics of water molecules at the interface and find that the temporal contact between the solid and fluid is shorter when the frequencies match, resulting in weak solid-fluid adsorption. We further report that the vibrational match at the interface reduces wall-fluid friction and enhances water transport through the nanopore. Our findings demonstrate the importance of the atomic-scale vibrational coupling at the solid-fluid interface on the physicochemical behavior of nanodevices and biological nanochannels.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Hydrocyclization/Defluorination of CF 3 ‐Substituted Acrylamides: Insights from Kinetics of Hydrogen Atom Transfer

Abstract The introduction of F‐containing groups into organic molecules can significantly alter their physical and chemical properties. Particularly, gem ‐difluoroalkenes serve as versatile precursors for a broad variety of organofluorine compounds, commonly used in agrochemicals, pharmaceuticals, and materials science. Based on the kinetics of H• transfer to acrylamide ( k H = 2.28 × 10 −4 M −1 s −1 at 300 K in toluene), the study describes a nickel‐hydride‐(or Li[BEt 3 H]) initiated hydrocyclization/defluorination of CF 3 ‐substituted acrylamides, offering alternative access to 4‐fluorovinyl‐substituted 2‐pyrrolidones (Seletracetam derivatives that are antiepileptic drug candidates). This process proceeds with high yields and remarkable chemo‐ and regioselectivity. The hydrocyclization/defluorination can be initiated by either H• or H – transfer, followed by a 5‐exo‐trig cyclization and subsequent fluorine elimination. The strategy has been applied in the late‐stage functionalization of drug molecules, providing a valuable tool in the synthesis of pharmaceutical compounds.

Wan, Yanjun [College of Pharmaceutical Sciences Zh↗