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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

High Layer Number ( n = 1–6) 2D Ruddlesden–Popper Lead Bromide Perovskites: Nanosheets, Crystal Structure, and Optoelectronic Properties

2D Ruddlesden–Popper (RP) lead halide perovskites have highly tunable structures, compositions, and properties that enable their promising optoelectronic applications. Among various 2D halide perovskites, the materials chemistry and fundamental optoelectronic properties of high layer number (n) lead-bromide RP perovskites, where n refers to the number of inorganic octahedra layers, have been less studied. Here, we report the synthesis of thin nanosheets of (PEA) 2 Cs n–1 Pb n Br 3n+1 (n = 1–6, PEA = phenylethylammonium) perovskites and study the optical properties, assigning photoluminescence emissions of 486, 496, and 505 nm to n = 4–6 phases, respectively, and reporting the photoluminescence lifetimes. Furthermore, the crystal structure of (PEA) 2 Cs 2 Pb 3 Br 10 was determined to reveal minimal octahedral structural distortions. Ultraviolet photoelectron spectroscopy measurements reveal the positioning of the valence and conduction bands for n = 1–3 phases and confirm the type-I band alignment for the (PEA) 2 Cs n–1 Pb n Br 3n+1 series, laying the foundation for rational heterostructure device design in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Chlorine Gas as a Lewis Acid–Base Probe for Molten Salts of Divalent Metal Ions

In the context of energy applications for salts and, more specifically, in the case of molten salt reactors, the solvation of corrosion species, the nature and behavior of radiation-produced excess electrons, transient radicals, and molecular gas species all depend on the Lewis acid–base behavior of the constituent salt melt. Speciation of dissolved species and their transport properties are also influenced by the ability of the melt to form networks. This article focuses on the structural properties of melts composed of alkaline earth metal ions coupled with the Cl – anion, and the quantum mechanical behavior of Cl 2 , a typical product of the reaction of radiation-produced chlorine radicals in Cl – -based molten salts. We explore the effect of M 2+ Lewis acidity on chlorobasicity, seen in this work as the availability of Cl – ions to chemically react with Cl 2 to produce Cl 3 – .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

2.2.2.405 - Verdant/NREL Research Measurement Campaign

The marine renewable energy industry primarily uses thermoset composite materials for blades and other hydrodynamic components, which can have up to 50% reduction in strength when exposed to seawater and are not recyclable. Thermoplastic composite materials have been shown at a coupon-scale to have improved seawater saturated properties but have not been validated at full scale. The primary goal of the project is to demonstrate the structural properties of thermoplastic-fiberglass composite blades compared to epoxy-fiberglass composite blades in seawater at a tidal energy site on an operational turbine. Through this work, NREL manufactured, tested and deployed thermoplastic blades and a data acquisition system on Verdant Power's turbine TriFrame in the East River, NYC. The thermoplastic blades and DAQ were retrieved after a 6-month deployment with no signs of degradation and all cable connections, structural supports and strain gages had a 100% survival rate. The blades are currently undergoing post-deployment structural validation to compare their performance to traditional epoxy blades that were deployed for the same amount of time. This will increase confidence in thermoplastic materials and move it closer to commercial adoption, as well as increase confidence in the design of a DAQ and instrumentation method for a tidal turbine. However, due to an error in the DAQ software that was introduced after the DAQ and software were validated, there was no loads data collected during the deployment.

blade testing↗
DOE OSTI2021

Computational study of the effect of core–skin structure on the mechanical properties of carbon nanofibers

The effect of the core–skin structure on the mechanical properties of carbon nanofibers is investigated in large-scale molecular dynamics simulations of tensile deformation of carbon nanofibers with the core–skin and homogeneous structures. Contrary to an established notion of the deleterious effect of the skin layer on the strength of carbon fibers, the presence of a high-quality skin layer is found to increase both the Young’s modulus and tensile strength of the nanofiber. A detailed analysis of the fracture process indicates that the nanofiber strengthening is related to the ability of skin layer to suppress crack nucleation at the core–skin interface. Furthermore, the computational predictions suggest that the design of new approaches to carbon fiber manufacturing and processing leading to the generation of a high-quality skin layer while avoiding the introduction of structural defects at the core–skin interface may yield a significant enhancement of the mechanical properties of carbon fibers.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Accelerating uncertainty quantification in incremental dynamic analysis using dimension reduction-based surrogate modeling

We propose a surrogate modeling framework based on dimension reduction to facilitate the quantification of seismic risk of structural systems in performance-based earthquake engineering. The framework adopts incremental dynamic analysis (IDA) for addressing hazard variability, and promotes significant computational efficiency improvement for propagating epistemic uncertainties associated with the structural models. It utilizes both linear and nonlinear dimension reduction approaches, equipped with inverse mappings, to learn a functional between the input parameter space (e.g., the epistemic uncertainties of the structure) to the high-dimensional output space created through the IDA implementation across different ground motions and seismic intensity levels. Polynomial chaos expansion is adopted as the surrogate model to learn this functional in the reduced space. A nine-story steel moment-resisting frame with uncertain structural properties is used as a testbed. Furthermore, we select the seismic fragility curves as a measure of the structure’s seismic performance, since it provides an estimate of the probability of entering specified damage states for given levels of ground shaking.

42 ENGINEERING↗
DOE OSTI2026

Computational Insights into the Salt-Induced Modulation of Electron Transporting Conjugated Polyelectrolytes

The morphological and electronic properties of conjugated polyelectrolytes (CPEs) are highly sensitive to their ionic environment and remain poorly understood. To elucidate structure–property relationships in CPEs, we investigate the role of salt concentration on CPE morphology and hole conductivity using a quantum mechanically informed coarse-grained (CG) model coupled with semiclassical rate theory. Under good solvent conditions, high salt concentration induces torsional disorder along the conjugated backbone, decreasing hole delocalization. In contrast, under poor solvent conditions, high salt concentration promotes CPE aggregation, leading to thicker fibers and increased hole mobilities. Collectively, this work characterizes the competing interactions governing CPE assembly and hole transport as a function of salt concentration, highlighting ion engineering as a powerful strategy for tailoring the properties of mixed-conducting polymers.

diseases↗
DOE OSTI2024

Latent Pitfalls in Microstructure-Based Modeling for Thermally Aged 9Cr-1Mo-V Steel (Grade 91)

A case study was conducted on a mechanistic model development that predicted tensile strength deterioration with thermal aging of 9Cr-1Mo-V steel in supporting the 60-year design life expected for advanced nuclear reactors. For property prediction beyond practical testing times, mechanistic modeling is highly desired, as it taps into the physics of structure–property relationships and therefore can generate reliable results for extrapolation. Meanwhile, as mechanistic models are often complicated, reflecting the intricacy of microstructure and strengthening mechanisms, pitfalls that are difficult to detect often exist. Here, this paper discusses latent pitfalls that are common in mechanistic modeling or specific in this 9Cr-1Mo-V case development through using the American Society of Mechanical Engineers verification and validation in computational solid mechanics (ASME V&V 10) standard for evaluating credibility of modeling in materials engineering. Suggestions are also made for enhancing reliability of microstructure-based modeling.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Note on the Effects of Linear Topology Preservation in Monte Carlo Simulations of Knotted Proteins

Monte Carlo simulations are a powerful technique and are widely used in different fields. When applied to complex molecular systems with long chains, such as those in synthetic polymers and proteins, they have the advantage of providing a fast and computationally efficient way to sample equilibrium ensembles and calculate thermodynamic and structural properties under desired conditions. Conformational Monte Carlo techniques employ a move set to perform the transitions in the simulation Markov chain. While accepted conformations must preserve the sequential bonding of the protein chain model and excluded volume among its units, the moves themselves may take the chain across itself. We call this a break in linear topology preservation. In this manuscript, we show, using simple protein models, that there is no difference in equilibrium properties calculated with a move set that preserves linear topology and one that does not. However, for complex structures, such as those of deeply knotted proteins, the preservation of linear topology provides correct equilibrium results but only after long relaxation. In any case, to analyze folding pathways, knotting mechanisms and folding kinetics, the preservation of linear topology may be an unavoidable requirement.

Especial, João N. C. (ORCID:0000000254765370)↗
DOE OSTI2024

Facile Tensile Testing Platform for In Situ Transmission Electron Microscopy of Nanomaterials

In situ tensile testing using transmission electron microscopy (TEM) is a powerful technique to probe structure-property relationships of materials at the atomic scale. In this work, a facile tensile testing platform for in situ characterization of materials inside a transmission electron microscope is demonstrated. The platform consists of: 1) a commercially available, flexible, electron-transparent substrate (e.g., TEM grid) integrated with a conventional tensile testing holder, and 2) a finite element simulation providing quantification of specimen-applied strain. The flexible substrate (carbon support film of the TEM grid) mitigates strain concentrations usually found in free-standing films and enables in situ straining experiments to be performed on materials that cannot undergo localized thinning or focused ion beam lift-out. The finite element simulation enables direct correlation of holder displacement with sample strain, providing upper and lower bounds of expected strain across the substrate. The tensile testing platform is validated for three disparate material systems: sputtered gold-palladium, few-layer transferred tungsten disulfide, and electrodeposited lithium, by measuring lattice strain from experimentally recorded electron diffraction data. The results show good agreement between experiment and simulation, providing confidence in the ability to transfer strain from holder to sample and relate TEM crystal structural observations with material mechanical properties.

2D materials↗
DOE OSTI2020

Magneto-structural and induction heating properties of MFe2O4 (M?=?Co, Mn, Zn) MNPs for magnetic particle hyperthermia application

The thermal decomposition approach was used for the synthesis of MFe2O4 magnetic nanoparticles (MNPs) by substituting M as Co, Mn, and Zn. The obtained MNPs were characterized for magneto-structural properties using X-Ray diffraction patterns, FTIR, Raman and Mossbauer spectroscopy techniques which confirm the formation of phase pure cubic spinel ferrite with space group Fd3m and five Raman active modes. The size, morphology, and compositional analysis was performed using HRTEM and EDX where the size of MNPs was found to be less than 10 nm that attains superparamagnetism. The magnetic hyperthermia performance of obtained MNPs was evaluated by induction heating experiments at magnetic field range 13.3 to 26.7 kAm-1. The specific absorption rate (SAR) and intrinsic loss power (ILP) values were determined at different magnetic fields within the human tolerable range and correlated with magneto-structural properties to evaluate its potential for possible magnetic particle hyperthermia therapy.

Magnetic nanoparticles, complex-decomposition, mag↗
DOE OSTI2025

Delineating the Effects of Counterions on the Structural and Vibrational Properties of U(IV) Lindqvist Polyoxometalate Complexes

Herein we conducted a full investigation into the fundamental structural and vibrational properties of uranium(IV) Peacock−Weakley-type lacunary Lindqvist (W 10 ) polyoxometalate (POM) complexes. We recently demonstrated the importance of the secondary lattice elements in tuning the distortion of the D 4d symmetry in W 10 POM complexes, and here, we synthesized eight UW 10 complexes with different alkali metal counterions and evaluated how the composition and packing of counterion species affected complex structural and vibrational properties. Single-crystal X-ray diffraction analysis on complexes 1−8 revealed changes in structural distortion parameters as a function of differences in counterion configurations, while far-infrared and Raman spectra for 1−8 also demonstrated that vibrational mode frequencies were sensitive to changes in counterion composition and packing. To more effectively compare different counterion configurations, we developed counterion effective ionic radius (eIR) as a new structural parameter, and comparisons between structural distortion parameters and eIR values strongly suggested that modulation by the secondary lattice elements can affect structural and vibrational manifolds within POM complexes. Partial least squares (PLS) analysis was used to quantitatively evaluate correlations observed within this investigation, and PLS statistical models showed a strong correlation between counterion eIR and both structural distortion parameters and vibrational mode frequencies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Investigation of 3D printed lightweight hybrid composites via theoretical modeling and machine learning

Hybrid composites combine two or more different fillers to achieve multifunctional or advanced material properties, such as lightweight and enhanced mechanical properties. The properties of the composites significantly depend on their microstructures, which can be tailored via advanced 3D printing processes. Understanding the process-structure-property relationships is critical to enable the design and engineering of novel hybrid composites for applications in aerospace, automotive, and protective coatings. Here, for this work, we develop 3D printable and lightweight hybrid composites and leverage the conventional design of experiments, a theoretical hybrid model, and an image-driven machine learning (ML) method to investigate their mechanical behaviors. The hybrid composites are formulated with elastomer matrix, microfillers, and thin-shell particles, enabling a significant degree of design freedom of microstructures with densities and mechanical properties varying up to 70% and 91%, respectively. Our statistical analysis indicates that the 3D printing path direction and the microfibers fraction are dominating process parameters with contribution percentages of 45.3% and 57.7% on the specific stiffness and strength, respectively. A hybrid mechanics model is developed based on a simple Weibull distribution function and classical single-filler models to effectively capture the variations in mechanical properties, however, it overestimates the values due to its statistical constraints and idealization of experimental uncertainty. The image-driven ML model leverages the microscale images directly without losing the structural details, shows more accurate predictions with experimental data, and has 48.6% lower root mean square error than the theoretical model.

3D printing↗
DOE OSTI2023

High-Resolution X-ray Spectromicroscopy Reveals Process-Structure Correlations in sub-5-μm Diameter Carbon Nanotube-Polymer Composite Dry-Spun Yarns

A persistent lack of detailed and quantitative structural analysis of these hierarchical carbon nanotube (CNT) ensembles precludes establishing processing-structure-property relationships that are essential to enhance macroscale performance (e.g., in mechanical, electrical, thermal applications). Here, in this work, we use scanning transmission X-ray microscopy (STXM) to analyze the hierarchical, twisted morphology of dry-spun CNT yarns and their composites, quantifying key structural characteristics such as density, porosity, alignment, and polymer loading. As the yarn twist density increases (15,000 to 150,000 turns per meter), the yarn diameter decreased (4.4–1.4 μm) and density increased (0.55–1.26 g·cm –3 ), as intuitively expected. Yarn density, ρ, ubiquitously scaled with diameter d according to ρ ~ d –2 for all parameters studied here. Spectromicroscopy probes with 30 nm resolution and elemental specificity were employed to analyze the radial and longitudinal distribution of the oxygen-containing polymer content (~30% weight fraction), demonstrating nearly perfect filling of the voids between CNTs with a vapor-phase polymer coating and cross-linking process. These quantitative correlations highlight the intimate connections between processing conditions and yarn structure with important implications for translating the nanoscale properties of CNTs to the macroscale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Synthesis, transport properties and electronic structure of p-type Cu 1+x Mn 2–x InTe 4 ( x = 0, 0.2, 0.3)

The synthesis, electronic structure and temperature dependent transport properties of polycrystalline Cu 1+x Mn 2–x InTe 4 (x = 0, 0.2, 0.3) are reported for the first time. These quaternary chalcogenides were synthesized by direct reaction of the elements, followed by solid state annealing and hot press densification. The thermal conductivity is low for all specimens and intrinsic to the material system. Furthermore, the off-stoichiometry specimens illustrate the sensitivity of the transport properties to stoichiometry, with a greater than two-orders-of magnitude increase in carrier concentration with increased Cu content. First principles calculations of the electronic structure are also reported, and are in agreement with the experimental data. Here, this fundamental investigation shows the potential towards further optimization of the electrical properties that, in addition to the intrinsically low thermal conductivity, provides a basis for further research into the viability of this material system for potential energy-related applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Tunable Solid‐State Properties and Anisotropic Charge Mobility in Hydrogen‐Bonded Diketopyrrolopyrrole Polymers via Automated Device Fabrication and Characterization

The optoelectronic properties of semiconducting polymers and device performance rely on a delicate interplay of design and processing conditions. However, screening and optimizing the relationships between these parameters for reliably fabricating organic electronics can be an arduous task requiring significant time and resources. To overcome this challenge, Polybot is developed—a robotic platform within a self‐driving lab that can efficiently produce organic field‐effect transistors (OFETs) from various semiconducting polymers via high‐throughput blade coating deposition. Polybot not only handles the fabrication process but also can conduct characterization tests on the devices and autonomously analyze the data gathered, thus facilitating the rapid acquisition of data on a large scale. This work leverages the capabilities of this platform to investigate the fabrication of OFETs using hydrogen bonding‐containing semiconducting polymers. Through high‐throughput fabrication and characterization, various data trends are analyzed, and large extents of anisotropic charge mobility are observed in devices. The materials are thoroughly characterized to understand the role of processing conditions in solid state and electronic properties of these organic semiconductors. The findings demonstrate the effectiveness of automated fabrication and characterization platforms in uncovering novel structure–property relationships, facilitating refinement of rational chemical design, and processing conditions, ultimately leading to new semiconducting materials.

automated fabrication and characterization↗
DOE OSTI2023

Linking Phase Behavior to Performance Parameters in Non-Fullerene Acceptor Solar Cells

Performance of nonfullerene-based organic solar cells is largely dependent on the donor:acceptor blend morphology, which is initially tuned by composition. However, morphological design rules are difficult to identify due to the complex relationship between composition-dependent phase behavior and performance properties. In this study, the authors are able to establish a direct link between PM6:Y6 film morphology and device properties by combining grazing-incidence wide-angle X-ray scattering with highly sensitive Fourier transform photocurrent spectroscopy. By analyzing properties across the full composition range, interfacial microstructure and the corresponding charge transfer (CT) states are identified and direct structure–property relationships are established. Here the results indicate that open-circuit voltage is controlled by the CT state at amorphous-PM6:crystalline-Y6 interfaces. Crystalline Y6 is found to increase both transport and non-radiative recombination, suggesting that morphological tradeoffs may be necessary for overall device optimization.

14 SOLAR ENERGY↗
DOE OSTI2023

Interplay Between Kondo and Magnetic Interactions in Pr 0.75 Gd 0.25 ScGeH

Combined experimental and density functional theory (DFT) study of Pr 0.75 Gd 0.25 ScGe and its hydride (Pr 0.75 Gd 0.25 ScGeH) reveals intricacies of composition-structure-property relationships in those distinctly layered compounds. Hydrogenation of the intermetallic parent, crystalizing in a tetragonal CeScSi-type structure, leads to an anisotropic volume expansion, that is, a(=b) lattice parameter decreases while the lattice expands along the c direction, yielding a net increase of cell volume. DFT calculations predict an antiparallel coupling of localized Gd and Pr magnetic moments in both materials at the ground state. While experiments corroborate this for the parent compound, there is no conclusive experimental proof for the hydride, where Pr moments do not order down to 3 K. DFT results also reveal that rare-earth – hydrogen interactions reduce spin-polarization of the Pr and Gd 5d and Sc 3d states at the Fermi energy, disrupt indirect exchange interactions mediated by conduction electrons, dramatically reduce the magnetic ordering temperature, and open a pseudo-gap in the majority-spin channel. Here, both experiments and theory show evidence of Kondo-like behavior in the hydride in the absence of an applied magnetic field, whereas increasing the field promotes magnetic ordering and suppresses Kondo-like behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction

The discovery of high-performing and stable materials for sustainable energy applications is a pressing goal in catalysis and materials science. Understanding the relationship between a material’s structure and functionality is an important step in the process, such that viable polymorphs for a given chemical composition need to be identified. Machine-learning-based surrogate models have the potential to accelerate the search for polymorphs that target specific applications. Herein, we report a readily generalizable active-learning (AL) accelerated algorithm for identification of electrochemically stable iridium oxide polymorphs of IrO 2 and IrO 3 . The search is coupled to a subsequent analysis of the electrochemical stability of the discovered structures for the acidic oxygen evolution reaction (OER). Structural candidates are generated by identifying all 956 structurally unique AB2 and AB3 prototypes in existing materials databases (more than 38000). Next, using an active learning approach, we find 196 IrO 2 polymorphs within the thermodynamic amorphous synthesizability limit and reaffirm the global stability of the rutile structure. We find 75 synthesizable IrO 3 polymorphs and report a previously unknown FeF 3 -type structure as the most stable, termed α-IrO 3 . To test the algorithms performance, we compare to a random search of the candidate space and report at least a 2-fold increase in the rate of discovery. Additionally, the AL approach can acquire the most stable polymorphs of IrO 2 and IrO 3 with fewer than 30 density functional theory optimizations. Analysis of the structural properties of the discovered polymorphs reveals that octahedral local coordination environments are preferred for nearly all low-energy structures. Subsequent Pourbaix Ir–H 2 O analysis shows that α-IrO3 is the globally stable solid phase under acidic OER conditions and supersedes the stability of rutile IrO 2 . Calculation of theoretical OER surface activities reveal ideal weaker binding of the OER intermediates on α-IrO 3 than on any other considered iridium oxide. We emphasize that the proposed AL algorithm can be easily generalized to search for any binary metal oxide structure with a defined stoichiometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗