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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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The work done to fabricate Marchuk plasma discharge tubes for measurement of the cesiated emission of lanthanum hexaboride and thoriated tungsten electrodes is described. A photon counting pyrometer was completed and is to be calibrated with a gold standard.
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In order to improve the energy production within the United States, new materials are developed with the goal of increased functionality. These materials are required to perform at extreme pressures and temperatures (up to and beyond 200MPa and 650â??) as well as be sustainable beyond 105 hours. Before developing these materials into components for power generation, mechanical testing is required to better understand the behavior of these materials at various loads and temperatures. The longest of these tests is the conventional creep test which is a real time test that can beyond 105 hours depending on service conditions. Hundreds of specimens must be tested before being approved for use in power generation, but it is extremely difficult to rapidly qualify when each material is required to exceed 105 hours making testing through conventional means unfeasible. While others have designed accelerated testing methods to help qualify materials, many of these experiments use an empirical approach that requires test data to fit already existing creep data. In this study, an accelerated creep test called the stepped isostress method (SSM) is then applied to wrought Inconel 718 (IN 718) specimens. A test matrix is designed using deformation mechanism maps, time-temperature-transformation diagrams, and time-temperature-precipitation diagrams, in order to ensure that microstructurally, the accelerated creep tests fail similarly to the conventional creep tests. The data from the stepped isostress method is then applied to the McVetty and Sin-hyperbolic (Sinh) constitutive models in order to generate a creep master curve. The results from the model fits are then compared to the conventional creep data done from experiments as well as from the NIMS database for Inconel 718. Optical microscopy and scanning electron microscopy are used to compare the evolution of the microstructure from the conventional creep and accelerated creep tests. It is found that using the Sinh model on the accelerated creep data provides reasonable creep rupture predictions when compared to the scatter band of creep tests. It was also observed that the microstructural evolution between the SSM experiments and creep tests were very similar in terms of the volume fraction of precipitates and phases.
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Natural organisms make a wide variety of exquisitely complex, nano-, micro-, and macroscale structured materials in an energy-efficient and highly reproducible manner. During these processes, the information-carrying biomolecules (e.g., proteins, peptides, and carbohydrates) enable (1) hierarchical organization to assemble scaffold materials and execute high-level functions and (2) exquisite control over inorganic materials synthesis, generating biominerals whose properties are optimized for their functions. Inspired by nature, significant efforts have been devoted to developing functional materials that can rival those natural molecules by mimicking in vivo functions using engineered proteins, peptides, DNAs, sequence-defined synthetic molecules (e.g., peptoids), and other biomimetic polymers. Among them, peptoids, a new type of synthetic mimetics of peptides and proteins, have received particular attention because they combine the merits of both synthetic polymers (e.g., high chemical stability and efficient synthesis) and biomolecules (e.g., sequence programmability and biocompatibility). The lack of both chirality and hydrogen bonds in their backbone results in a highly designable peptoid-based system with reduced structural complexity and side chain-chemistry-dominated properties. Here in this Account, we present our recent efforts in this field by programming amphiphilic peptoid sequences for (1) the controlled self-assembly into different hierarchically structured nanomaterials with favorable properties and (2) manipulating inorganic (nano)crystal nucleation, growth, and assembly into superstructures. First, we designed a series of amphiphilic peptoids with controlled side chain chemistries that self-assembled into 1D highly stiff and dynamic nanotubes, 2D membrane-mimetic nanosheets, hexagonally patterned nanoribbons, and 3D nanoflowers. These crystalline nanostructures exhibited sequence-dependent properties and showed promise for different applications. The corresponding peptoid self-assembly pathways and mechanisms were also investigated by leveraging in situ atomic force microscopy studies and molecular dynamics simulations, which showed precise sequence dependency. Second, inspired by peptide- and protein-controlled formation of hierarchical inorganic nanostructures in nature, we developed peptoid-based biomimetic approaches for controlled synthesis of inorganic materials (e.g., noble metals and calcite), in which we took advantage of the substantial side chain chemistry of peptoids and investigated the relationship between the peptoid sequences and the morphology and growth kinetics of inorganic materials. For example, to overcome the challenges (e.g., complexity of protein- and peptide-folding, poor thermal and chemical stabilities) facing the area of protein- and peptide-controlled synthesis of inorganic materials, we recently reported the design of sequence-defined peptoids for controlled synthesis of highly branched plasmonic gold particles. Moreover, we developed a rule of thumb for designing peptoids that predictively enabled the morphological evolution from spherical to coral-shaped gold nanoparticles (NPs). With this Account, we hope to stimulate the research interest of chemists and materials scientists and promote the predictive synthesis of functional and robust materials through the design of sequence-defined synthetic molecules.
Nuclear industries can benefit from materials that can perform well mechanically and thermally in high temperature and corrosion environments. Functionally graded materials (FGM) are materials manufactured with complex spatial, structural, and chemical compositions, creating components predesigned with tailored microstructural and mechanical properties. Porosity-graded FGMs are designed to introduce pores into a component’s structure as a mechanism to increase bulk or surface material performance, such as stress accommodation and negative thermal conductivity. Additive manufacturing (AM) techniques such as laser energy net shape (LENS) and wire arc additive manufacturing (WAAM), excel in high energy density, point-to-point metal deposition, and present in combination with other combinatorial approaches, exciting methods to manufacture porous FGM components. This project is also examining plasma jet printing as another means for method evaluations for smaller scale graded components. This study explores AM FGM process parameters and combinatorial fabrication methodologies for stainless steel components functionally graded in porosity levels. Preliminary characterization results are provided to attest the feasibility of the combinational fabrication techniques.
A high-performance p -type transparent conductor (TC) does not yet exist but could lead to advances in a wide range of optoelectronic applications and enable new architectures for, e.g., next-generation photovoltaic (PV) devices. High-throughput computational material screenings have been a promising approach to filter databases and identify new p -type TC candidates and some of these predictions have been experimentally validated. However, most of these predicted candidates do not have experimentally achieved properties on par with n -type TCs used in solar cells and therefore have not yet been used in commercial devices. Thus, there is still a significant divide between transforming predictions into results that are actually achievable in the laboratory and an even greater lag in scaling predicted materials into functional devices. In this perspective, we outline some of the major disconnects in this materials discovery process—from scaling computational predictions into synthesizable crystals and thin films in the laboratory to scaling laboratory-grown films into real-world solar devices—and share insights to inform future strategies for TC discovery and design. Published by the American Physical Society 2024
Constructed to satisfy 17 known exact constraints for a semilocal density functional, the strongly constrained and appropriately normed (SCAN) meta-generalized-gradient-approximation functional has shown early promise for accurately describing the electronic structure of molecules and solids. One open question is how well SCAN predicts the formation energy, a key quantity for describing the thermodynamic stability of solid-state compounds. To answer this question, we perform an extensive benchmark of SCAN by computing the formation energies for a diverse group of nearly 1000 crystalline compounds for which experimental values are known. Due to an enhanced exchange interaction in the covalent bonding regime, SCAN substantially decreases the formation energy errors for strongly bound compounds, by approximately 50% to 110 meV/atom, as compared to the generalized gradient approximation of Perdew, Burke, and Ernzerhof (PBE). However, for intermetallic compounds, SCAN performs moderately worse than PBE with an increase in formation energy error of approximately 20%, stemming from SCAN's distinct behavior in the weak bonding regime. The formation energy errors can be further reduced via elemental chemical potential fitting. We find that SCAN leads to significantly more accurate predicted crystal volumes, moderately enhanced magnetism, and mildly improved band gaps as compared to PBE. Altogether, SCAN represents a significant improvement in accurately describing the thermodynamics of strongly bound compounds.
Expanding the library of known inorganic materials with functional electronic or magnetic behavior is a long-standing goal in condensed matter physics and materials science. Recently, the transition metal chalcogenides including selenium and sulfur have been of interest because of their correlated-electron properties, as seen in the iron-based superconductors and the transition metal dichalcogenides. However, the chalcogenide chemical space is less explored than that of oxides, and there is an open question of whether there may be new materials heretofore undiscovered. We perform a systematic combined theoretical and experimental search over ternary phase diagrams that are empty in the Inorganic Crystal Structure Database containing cations, transition metals, and one of selenium or sulfur. In these 27 ternary systems, we use a probabilistic model to reduce the likelihood of false negative predictions, which results in a list of 24 candidate materials. We then conduct a variety of synthesis experiments to check the candidate materials for stability. While the prediction method did obtain previously unknown compositions that are predicted stable within density functional theory, none of the candidate materials formed in our experiments. Finally, we come to the conclusion that these phase diagrams are “empty” in the case of bulk synthesis, but it remains a possibility that alternate synthesis routes may produce some of these phases.
This report summarizes the development of a new class of recyclable multi-functional composite materials for production of lightweight smart structures and surfaces. Functional high stiffness conductive composites were processed using molding methods that integrated continuous fiber and additively manufactured features. Methods for integration of sensing functionality and controls were also developed to reduce system cost while providing a new capability for structural health monitoring. This new class of composites is applicable to a broad range of vehicle interior, exterior and battery enclosure systems. By way of demonstration, a vehicle instrument panel cross car beam was developed that provided a 38% mass savings compared to steel while maintaining a cost penalty competitive to alternate lightweight material solutions. These technologies were validated for implementation by a uniquely qualified project team comprising a US automotive OEM, Tier 1 and Tier 2 supplier, with key contributions from Oak Ridge National Lab, Purdue University and Michigan State University.
The Small Gram Quantity (SGQ) concept is based on the understanding that small amounts of hazardous materials, in this case radioactive materials (RAM), are significantly less hazardous than large amounts of the same materials. This paper describes a methodology designed to estimate an SGQ for several neutron and gamma emitting isotopes that can be shipped in a package compliant with 10 CFR Part 71 external radiation level limits regulations. These regulations require packaging for the shipment of radioactive materials, under both normal and accident conditions, to perform the essential functions of material containment, subcriticality, and maintain external radiation levels within the specified limits. By placing the contents in a helium leak-tight containment vessel, and limiting the mass to ensure subcriticality, the first two essential functions are readily met. Some isotopes emit sufficiently strong photon radiation that small amounts of material can yield a large dose rate outside the package. Quantifying the dose rate for a proposed content is a challenging issue for the SGQ approach. It is essential to quantify external radiation levels from several common gamma and neutron sources that can be safely placed in a specific packaging, to ensure compliance with federal regulations. The Packaging Certification Program (PCP) Methodology for Determining Dose Rate for Small Gram Quantities in Shipping Packagings provides bounding shielding calculations that define mass limits compliant with 10 CFR 71.47 for a set of proposed SGQ isotopes. The approach is based on energy superposition with dose response calculated for a set of spectral groups for a baseline physical packaging configuration. The methodology includes using the MCNP radiation transport code to evaluate a family of neutron and photon spectral groups using the 9977 shipping package and its associated shielded containers as the base case. This results in a set of multipliers for 'dose per particle' for each spectral group. For a given isotope, the source spectrum is folded with the response for each group. The summed contribution from all isotopes determines the total dose from the RAM in the container.
Vapor-phase infiltration (VPI) of inorganic materials in polymers is increasingly becoming popular for synthesizing various functional hybrid materials. While AlO x infiltration using trimethylaluminum (TMA) has been extensively studied, the mechanism of diethylzinc (DEZ)-based ZnO x infiltration, especially one that is initiated by AlO x priming, has not received much attention because highly reactive hydroxyl groups generated by AlO x -priming are expected to dominate the initial binding of DEZ, thus enabling the overall ZnO x VPI. Here, we interrogate the ZnO x infiltration mechanism in AlO x -primed poly(methyl methacrylate) (PMMA) in comparison to the control AlO x -only infiltration by utilizing a suite of complementary characterizations, including quartz crystal microbalance mass gain measurement, transmission electron microscopy, infrared reflection–absorption spectroscopy (IRRAS), and synchrotron X-ray absorption spectroscopy (XAS). The multivalent TMA precursor and associated hyperbranched AlO x network can quickly saturate the AlO x infiltration by clogging the polymer-free volume near the top. On the contrary, the ZnO x infiltration using divalent DEZ precursor, once activated via AlO x -priming, can lead to accelerated ZnOx infiltration. With the help of IRRAS, XAS, and density functional theory (DFT) simulations, we uncover that the AlO x -priming enhances the reactivity of neighboring carbonyl groups toward DEZ and opens up simultaneous reaction pathways, leading to accelerated high-fidelity infiltration of ZnO x .
Fast-neutron transmission imaging provides complementary information to x-ray transmission imaging. While fast neutron imaging resolution is generally below x-ray imaging, 14-MeV neutrons have an advantage over portable x-ray systems. Neutrons have higher transmission through high-Z materials due to a more uniform attenuation as a function of material atomic number Z compared to X-rays, and can therefore image low-Z materials inside high-Z materials. As a result, portable neutron transmission imaging has many applications, including inspection of concrete and welds for corrosion in vehicles, bridges, and other infrastructure, measurement of material levels in containers, and inspection of suspicious packages. Fast-neutron imaging is also more practical for field use than thermal-neutron imaging due to the size and shielding requirements typical of thermal-imaging systems compared to the availability of small 14.1 MeV D-T neutron generators. However, there are limitations in portable fast-neutron imaging systems, including limited neutron output, limited light produced by neutron scintillators, and lower resolution due to neutron source spot size and 2-3 mm scintillator thickness. In addition, digital-panel dark-noise is roughly 100x higher than neutron scintillator light, and variations in noise across the panel and in time is comparable to the imaging signal. Here we discuss recent efforts in developing a portable fast-neutron radiography system, including an improved neutron scintillator, mitigation of panel noise, and new commercial portable D-T neutron generators. We also present MCNP efforts to model neutron imaging, including scintillator resolution and the effects of neutron scattering from the object and surrounding materials.
The Orion Multi-Purpose Crew Vehicle (MPCV) will transport four crew members to and from lunar-class orbital destinations. The first orbital Exploration Flight Test (EFT-1) is scheduled for December 2014 and will provide valuable data on several systems, including the heat shield. The heat shield material is AvcoatTM, a mid-density ablator. Specifically, the heat shield contains a fiberglass-phenolic honeycomb structure filled with an ablative epoxy novolac resin. Post-flight characterization of the EFT-1 thermal protection system will be conducted in order to study the material response and measure the char front of the material. Avcoat density profiling will be conducted to study three critical material zones: char, pyrolysis, and virgin states as a function of material depth. As part of a ground test campaign, Avcoat coupons are tested at the NASA Ames Research Center Arc Jet Complex. The test campaign is set forth to study material response based on environments, perform Avcoat material density characterization, and compare the char depths from the HEAT sensor and density profiling studies. These investigations will then be compared to flight data in order to improve upon TPS material response models.
Previous methods for the evaluation of the exfoliation of two-dimensional (2D) layered materials have drawbacks in computational efficiency and are unable to describe cases with semi-infinite substrates. Based on a Green's function surface (GFS) model, here we develop an approach to efficiently determine the tendency of exfoliation of 2D materials from their bulk crystals or semi-infinite substrates. By constructing appropriate surface configurations, we may calculate the exfoliation energy more precisely and quickly than the traditional way with the slab model. Furthermore, the GFS approach can provide angle-resolved photoemission spectroscopy of surface systems for direct comparison with experimental data. In this work, our findings indicate that the GFS approach is powerful for studies of 2D materials and various surface problems.
This paper, the last in the series, continues developing the nonlinear constitutive relations for non-isothermal, compressible, solid viscoelasticity. We initially discuss a single integral approach, more suitable for the glassy state of rubber-like materials, with basic functionals involved in the thermodynamic description for this type of viscoelasticity. Then we switch our attention to analyzing stability constraints, imposed on the general formulation of the nonlinear theory of solid viscoelasticity. Finally, we discuss specific (known from the literature or new) expressions for material functions that are involved in the constitutive formulations of both the rubber-like and glassy-like, complementary parts of the theory.
Boron nitride (BN) allotropes hold great promise in many advanced applications ranging from optical and photonic devices to energy storage and battery systems to tribological components. The diverse functionalities of this material stem from BN’s highly tunable structural and electronic properties, which are governed by the versatile boron–nitrogen bonding configurations. Exploring the structural landscape of BN can unveil novel structures possessing unique properties suited for specific applications, therefore accelerating the design of next-generation advanced functional materials. In this work, we leverage boron K-edge X-ray absorption spectroscopy (XAS) as an effective probe for local structural features and chemical environments. A total of 210 BN crystal structures are generated via analogies to the extensive array of carbon allotropes, and XAS is simulated for each unique local motif within the resulting collection of structures. A mapping between structural features and spectral signatures was established by synergizing first-principle simulations with data-driven based post-analysis approaches. Specifically, we developed a neural network model that can satisfactorily predict spectra line shapes from local structural descriptors. Toward automatic spectroscopic interpretation of any new BN structures, supervised machine learning models, trained on this structure–spectrum dataset, can accurately infer local coordination environments from simulated XAS, highlighting the strength of this unique approach of combining high-fidelity first-principles simulation and machine-learning to accelerate target design of novel BN materials via rational understanding of local structure-spectrum correlations.