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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 use and supply of strategic elements in nickel base superalloys for gas turbine engines are reviewed. Substitution of strategic elements, advanced processing concepts, and the identification of alternate materials are considered. Cobalt, tantalum, columbium, and chromium, the supplies of which are 91-100% imported, are the materials of major concern.
We report the crystal growth and structural and electronic properties of superconducting, van der Waals layered PtTe. Easily cleavable crystals with a platelike morphology consistent with the layered structure were grown from a platinum-rich flux. A consistent determination of T c = 0.57 K is made from the onset of diamagnetism, the zero of resistivity, and the midpoint of the heat-capacity jump. The observed behavior is consistent with type-II superconductivity, with upper critical field at T = 0 estimated using the Werthamer-Helfand-Hohenberg theory to be 143 and 65 Oe for fields out of and in the plane, respectively. The heat-capacity discontinuity is close to the weak-coupling BCS value. Density-functional theory calculations and analysis of the electronic structure finds that PtTe is a topological semimetal with numerous surface states but suggests that the superconducting state itself may be topologically trivial. Additionally, angle-resolved photoemission spectroscopy reveals a normal-state Fermi surface in remarkable agreement with theory and confirms the overall topological nature of the material by experimental identification of the surface bands. Together, these findings identify PtTe as an interesting example of a cleavable, topological, and superconducting material.
Unidirectional fibrous composite material laminae are the construction material of a laminate. Four failure modes can occur in this material, and the identification of these modes is as important as the identification of onset of fracture. Acoustic emission (AE) pulses, generated by the change in the stress field resulting from cracking in a material, have a unique pattern of amplitude distribution that depends only on the mode of fracture and the type of material. By using a tapered double-cantilever beam as grips for the unidirectional lamina, a crack with a constant stress intensity factor was induced, thus eliminating the factor of the stress level. Placing the lamina in different directions relative to the grips imposed a different failure mode. By plotting the log of the relative number of AE pulses above some level versus the log of the relative level, a single constant coefficient can be measured for each material and mode of fracture. The AE energy is proportional to the energy released by the cracking; this proportionality depends on the medium where the AE waves have to travel, and not on the cracking mode.
The Complex Functional Materials (CFM) area of leadership focuses on the identification and development of materials comprised of multiple components or building blocks that are integrated or chemically bound together to achieve a desired function or response. Soft materials, such as polymers, as well as structural properties at the meso- and micro-scale that control materials function are particularly emphasized in this leadership area. Further, complex functional materials are generally developed to satisfy multiple materials design criteria all of which are essential to the overall application. CFM supports applications that are aligned with all three Los Alamos National Laboratory mission areas. These mission areas are: materials for nuclear deterrence, materials for energy security, and materials for global security
The NASA Orbital Debris Program Office (ODPO) has used laboratory measurements to help bring ground-based measurements together with models to ascertain Earth-orbiting target parameters of interest to support various orbital debris models. In 2005, the Optical Measurement Center (OMC) was established to simulate space-based illumination conditions using equipment and techniques that recreate telescopic observations, particularly source-target-sensor orientations. The intent was to recreate light curves using known aspect angles of known targets and phase angles (angle is defined by the vertex between illumination source-object-detector) to complement telescopic observations that could be used to update the current optical size estimation model (OSEM) – a model that converts object brightness into size for orbital debris models. To support the above goals, the laboratory has undergone several equipment upgrades to increase capabilities over almost 20 years of operation. The primary instrumentation acquires reflectance measurements and includes a solar-like light source, CCD camera with astrometric filters, and robotic arm. A rotary arm was added approximately five years after full operation to allow acquisition through a full 360° range of phase angles. Another part of the OMC instrumentation is a field spectrometer, predominately used for field operations to acquire pre- and post-flight spacecraft material spectral measurements. Additionally, reflectance spectroscopy of various materials is also of interest resulting from hypervelocity impact tests, pristine spacecraft materials, or samples of materials that are used in spacecraft design. These measurements are stored in NASA’s Spectral Material Database, a resource that is still being populated today. The study of spectral measurements also enabled the development of spectral unmixing routines to support the identification of spacecraft materials from spectral data gathered by ground based telescopes. Preliminary OMC investigations focused on feasibility studies to acquire 360° rotation light curves of simple shapes at a single-phase angle and extended to measurements of representative fragments from ground-based explosion tests. To correlate the light curves with ground-based optical measurements, a focused study on high area to mass materials was conducted in support of a newly identified population (at the time) in geosynchronous orbit (GEO) consisting of multi-layered insulation. To further characterize orbital debris, a larger selection of materials was analyzed using laboratory photometric measurements that included representative targets from pristine spacecraft materials and ground-based impact tests. Around 2012, an initiative was requested to understand the feasibility of active debris removal (ADR) of larger targets using grappling methods for spent rocket bodies. Using a priori information on selected targets, scaled-down versions of rocket bodies were generated thanks to improvements in 3D printing technology and machining. These targets were studied in the OMC to understand rotation characteristics. These were compared with telescopic data to determine if the tumble and rotation angles would allow ADR. In 2013, the OMC focused on combining spectral measurements with photometric data to characterize GEO orbital debris. Several years later, NASA acquired a Titan III Transtage test article from “The Boneyard” with a high-resemblance to on-orbit Titan III Transtage rocket bodies, allowing physical access to a representative rocket body that suffered fragmentations in GEO. This prompted the creation of 3D models using lidar technology and spectral measurements of the materials. Focused research also transitioned to specific materials (i.e., solar cells) when telescopic surveys requested characterization of specific GEO targets. In the different research products presented, the focus has been to understand the various parameters that influence optical size estimation, including albedo, phase functions, and brightness variations. Work in this area continues with newer sources of data, including DebriSat, a high-fidelity 56-kg spacecraft replica representative of a modern low Earth orbit (LEO) satellite subjected to a laboratory hypervelocity impact test to understand fragmentation events and to support updates to satellite breakup models and size estimation models. Utilizing the vast population of fragments from DebriSat and prior laboratory impact experiments, the ODPO has focused on acquiring bidirectional reflectance distribution function (BRDF) data to characterize targets in the laboratory, thus removing aspect angle dependencies. Additionally, the DebriSat project has provided improved processes for measuring size via image acquisition, such that a true fragment size can be directly compared to the derived size using the OSEM. The team continues to assess BRDFs and use spectral measurement data to investigate the parameters used in the OSEM, specifically magnitudes, albedo, and phase functions.
Recent developments highlighting the promise of two-dimensional perovskites have vastly increased the compositional search space in the perovskite family. This presents a great opportunity for the realization of highly performant devices and practical challenges associated with the identification of candidate materials. High-fidelity computational screening offers great value in this regard. In this study, we carry out a multiscale computational workflow, generating a dataset of two-dimensional perovskites in the Dion-Jacobson and Ruddlesden-Popper phases. Our dataset comprises ten B-site cations, four halogens, and over 20 organic cations across over 2000 materials. We compute electronic properties, thermoelectric performance, and numerous geometric characteristics. Furthermore, we introduce a framework for the high-throughput computation of Rashba-Dresselhaus splitting. Finally, we use this dataset to train machine learning models for the accurate prediction of band gaps, candidate Rashba-Dresselhaus materials, and partial charges. The work presented herein can aid future investigations of two-dimensional perovskites with targeted applications in mind.
Imaging spectrometry for the remote sensing of the Earth is introduced. Reflected solar energy from the surface is dispersed in a spectrometer and used to form up to 200 registered spectral images. Each pixel has associated with it sufficient information for the reconstruction of a complete reflectance spectrum. The technique allows the diagnostic narrow band spectral features that are characteristic of many surface materials to be used to identify those materials. These spectral features are typically 20 to 40 nm wide; spectral imaging systems which acquire data in contiguous 10 nm bands therefore have sufficient resolution for direct identification of those materials with diagnostic spectral bands.
A capaciflector sensor system scanned in frequency is used to detect the permittivity of the material of an object being sensed. A capaciflector sensor element, coupled to current-measuring voltage follower circuitry, is driven by a frequency swept oscillator and generates an output which corresponds to capacity as a function of the input frequency. This swept frequency information is fed into apparatus e.g. a digital computer for comparing the shape of the capacitance vs. frequency curve against characteristic capacitor vs. frequency curves for a variety of different materials which are stored, for example, in a digital memory of the computer or a database. Using a technique of pattern matching, a determination is made as to the identification of the material. Also, when desirable, the distance between the sensor and the object can be determined.
Neutron activation analysis (NAA) is a powerful technique for identifying and quantifying trace elements in materials. However, challenges such as high dead times, spectral interferences, and high Compton continuum often arise. This study employs a Compton suppression system (CSS) to enhance NAA sensitivity by reducing the Compton continuum, thereby improving the peak-to-Compton ratio. National Institute of Standards and Technology certified reference materials 1632d, 1633c, and Canadian National Research Council TORT-1 were irradiated in a thermal and epithermal neutron flux under various irradiation, decay and counting times and analyzed using high-resolution gamma-ray spectroscopy with and without Compton suppression. The reduction factor was calculated to evaluate the effectiveness of the CSS, demonstrating significant background reduction and improved detection limits for trace elements. Additional experiments with a 137Cs point source demonstrated the impact of detector-source geometry on system performance, showing a decrease in the reduction factor as the source was moved further from the NaI detector. An optimum distance between the source and HPGe detector was observed, yielding the highest peak-to-Compton ratio. The results highlight the CSS's ability to minimize spectral interference and enhance elemental identification.
The following topics are discussed: (1) Assignment of population to microclimatic zones; (2) specifications of the mix of buildings in the SCE territory; (3) specification of four typical buildings for thermal analysis and market penetration studies; (4) identification of the materials and energy conserving characteristics of these typical buildings; (5) specifications of the HVAC functions used in each typical building, and determination of the HVAC systems used in each building; and (6) identification of the type of fuel used in each building.
This library includes in-progress code for the optimization of materials and molecules using reinforcement learning. This project seeks to develop a generalized machine learning approach for optimizing targeted, and often complex, functional properties over the space of possible material structures, allowing faster identification of promising candidates. Electronic and transport properties of materials are determined by their molecular structure (for molecules) or their crystal structure (for in-organic crystalline materials). The atomic composition, bonding, and 3-D-spatial arrangement in these systems therefore represent a vast, discontinuous search space for optimal candidates. This library implements AlphaZero style reinforcement learning applied to two worked examples: the optimization of stable organic radicals for redox flow batteries, and the determination of stable electrolyte species for solid state batteries. The current code contains proof-of-concept results run on the Eagle HPC system, while the completed package will be a flexible tool for material optimization across of number of energy-relevant fields, which leverages cloud compute resources for the majority of the computational heavy lifting.
Radiative recombination processes can occur in solid-state systems through the pairing of donor and acceptor defects of the lattice. Recently, donor-acceptor pairs (DAP) have been proposed as promising candidates for quantum applications, and their signature has been observed in emerging low-dimensional materials. Therefore, the identification of such processes is gaining interest and requires methods to efficiently and reliably characterize them. Here, we introduce a general algorithm to identify DAP processes starting from the experimental photoluminescence (PL) emission spectrum and basic material parameters, including the lattice structure and dielectric constant. The algorithm recognizes possible DAP transitions from the emission pattern in the spectrum and returns the characteristic energy of the DAP transition and the separation between the donor and acceptor sites. By testing the algorithm on the photoluminescence spectrum of hexagonal boron nitride (hBN), we show that our method is robust against experimental errors and adds new capabilities to the investigation toolbox of semiconductors and their optical properties.
Large volumes of data from material characterizations call for rapid and automatic data analysis to accelerate materials discovery. Herein, we report a convolutional neural network (CNN) that was trained based on theoretical data and very limited experimental data for fast identification of experimental X-ray diffraction (XRD) patterns of metal–organic frameworks (MOFs). To augment the data for training the model, noise was extracted from experimental data and shuffled; then it was merged with the main peaks that were extracted from theoretical spectra to synthesize new spectra. For the first time, one-to-one material identification was achieved. Theoretical MOFs patterns (1012) were augmented to a whole data set of 72 864 samples. It was then randomly shuffled and split into training (58 292 samples) and validation (14 572 samples) data sets at a ratio of 4:1. For the task of discriminating, the optimized model showed the highest identification accuracy of 96.7% for the top 5 ranking on a test data set of 30 hold-out samples. Neighborhood component analysis (NCA) on the experimental XRD samples shows that the samples from the same material are clustered in groups in the NCA map. Analysis on the class activation maps of the last CNN layer further discloses the mechanism by which the CNN model successfully identifies individual MOFs from the XRD patterns. Furthermore, this CNN model trained by the data augmentation technique would not only open numerous potential applications for identifying XRD patterns for different materials, but also pave avenues to autonomously analyze data by other characterization tools such as FTIR, Raman, and NMR spectroscopies.
Volatile contaminants of space cabin materials
Screening tests on candidate construction materials for spacecraft cabins to determine gas-off and oxidation products
A newly discovered absorption feature in Io's spectrum at 2.1253 microns promises to reveal significant insights in the nature of the interaction among Io's surface, atmosphere, and volcanoes. The most likely candidate for this feature appears to be clusters of CO2 molecules. Observations are underway on a current series of occultations and eclipses of Io by other Galilean satellites in order to locate the source of this newly discovered material on Io, which should provide further clues to its origin.
Process analysis can identify opportunities for efficiency improvement including cost reduction, increased safety, improved quality, and decreased environmental impact. A thorough, systematic approach to materials and process selection is valuable in any analysis. New operations and facilities design offer the best opportunities for proactive cost reduction and environmental improvement, but existing operations and facilities can also benefit greatly. Materials and processes that have been used for many years may be sources of excessive resource use, waste generation, pollution, and cost burden that should be replaced. Operational and purchasing personnel may not recognize some materials and processes as problems. Reasons for materials or process replacement may include quality and efficiency improvements, excessive resource use and waste generation, materials and operational costs, safety (flammability or toxicity), pollution prevention, compatibility with new processes or materials, and new or anticipated regulations.
The study of nuclear forensics harkens back to the Manhattan Project-era, when scientists first started to analyze the debris from the 1945 Trinity test. Political turmoil stemming from the Cold War and the rehabilitation of Germany following WWII has led to new challenges in international security involving nuclear proliferation. Nuclear materials have, on occasion, been lost, misplaced, or stolen from former Soviet countries, and illicit materials have been interdicted all over the world. The National Technical Nuclear Forensics Center (NTNFC) was established in 2006, and has been at the forefront of drive to advance nuclear forensic capabilities in the United States. The ultimate goal of nuclear forensics is to examine nuclear and other radioactive materials using analytical techniques to determine origin and history of the material, particularly in the context of law enforcement investigations. Nuclear forensics can be divided into two parts: predetonation and post-detonation. Pre-detonation forensics, as the name implies, is the investigation of a nuclear material or weapon that has not been detonated or involved in an explosion, whereas postdetonation forensics is the study of activation or fission products in debris or the environment following the use of a nuclear or radiological dispersal device (RDD). Both parts require a number of analytical chemical and radiochemical techniques to determine identification of the material. Many advancements in analytical techniques, including rapidity, sample size, and forensic signatures have been made in recent years. The analytical methods that can be used in a nuclear forensic investigation, such as mass spectrometry and gamma spectroscopy, have been described in detail in previous reviews, including Straub et.al, and will not be explained here. This review will discuss recent publications (from 2016 to present) describing advancements of techniques such as radiochronometry, morphology, development of novel reference materials, and inter-laboratory collaborations for both pre- and post-detonation nuclear forensics.