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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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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Synthesis of La 2–x Sr x CuO 4 films via atomic layer-by-layer molecular beam epitaxy

Atomic layer-by-layer molecular beam epitaxy (ALL-MBE) is a sophisticated technique to synthesize high-temperature superconductor (HTS) materials. ALL-MBE produces single-crystal HTS films with atomically smooth surfaces and interfaces, as well as precise multilayer heterostructures engineered down to a single atomic layer level. This enables the fabrication of tunnel junctions, nanowires, nanorings, and other HTS devices of interest. Our group has focused on ALL-MBE synthesis and materials science of La 2–x Sr x CuO 4 (LSCO), a representative HTS cuprate. In the past two decades, we have synthesized over three thousand LSCO thin films and characterized them by a range of analytical techniques. Here, we present in full detail a systematic process for the synthesis and engineering of atomically perfect LSCO films. The procedure includes the preparation of substrates, calibration of the elemental sources, the recipe for ALL growth of LSCO films without any secondary-phase precipitates, post-growth annealing of the films, and ex situ film characterization. This report should aid replication and dissemination of this technique of synthesizing single-crystal LSCO films for basic research as well as for HTS electronic applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS2006

Sensor Management for Applied Research Technologies (SMART)-On Demand Modeling (ODM) Project

NASA requires timely on-demand data and analysis capabilities to enable practical benefits of Earth science observations. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep learning curve associated with each sensor and data type. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output. A three year project, entitled Sensor Management for Applied Research Technologies (SMART) - On Demand Modeling (ODM), will develop and demonstrate the readiness of Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities that integrate both Earth observations and forecast model output into new data acquisition and assimilation strategies. The advancement of SWE-enabled systems (i.e., use of SensorML, sensor planning services - SPS, sensor observation services - SOS, sensor alert services - SAS and common observation model protocols) will have practical and efficient uses in the Earth science community for enhanced data set generation, real-time data assimilation with operational applications, and for autonomous sensor tasking for unique data collection.

Goodman, M.↗

NASA NTRS2007

The Sensor Management for Applied Research Technologies (SMART) Project

NASA seeks on-demand data processing and analysis of Earth science observations to facilitate timely decision-making that can lead to the realization of the practical benefits of satellite instruments, airborne and surface remote sensing systems. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep "learning curve" associated with each sensor, data type, and associated products. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output.

Goodman, Michael↗

DOE OSTI2020

Cooperative formation of porous silica and peptides on the prebiotic Earth

Significance Although catalysis by mineral surfaces has been considered to be important in prebiotic chemistry, the role of porous silica phases, with reactions taking place within specific confined environments, has not been explored. This paper proposes that structure direction through interaction of dissolved silica with organic species in aqueous solution produces porous silica catalysts for prebiotic organic reactions to form larger polymerized molecules, with possible control of chirality. This process may involve feedback and amplification if the organics produced by catalysis can also act as structure-directing agents for enhanced synthesis of the catalytic silica structures. To our knowledge, such structure direction and catalysis, though well known in materials science, have not been considered previously in the context of prebiotic chemistry.

58 GEOSCIENCES↗

DOE OSTI2025

Seeing is Believing: Autonomous Microscopy and the Data Revolution in Materials Science [Slides]

Machine intelligence has the potential to revolutionize materials science, enabling autonomous synthesis, self-driving characterization, and accelerated modeling. However, despite the promise, successful implementation of these methods in day-to-day research remains a challenge. This talk will delve into the reasons behind this, exploring how truly intelligent experiments are hindered by opaque experiment control, a lack of domain-specific models, and human-centric design. Through a focus on the characterization of next-generation microelectronics and energy storage materials, I will share insights from both successful and failed attempts to implement machine intelligence. We will then explore the next steps necessary to unlock the full potential of machine intelligence in materials science, creating a future where intelligent systems work seamlessly alongside researchers to drive innovation and discovery.

36 MATERIALS SCIENCE↗

DOE OSTI2024

The Rise of Intelligent Materials Science: Unleashing the Power of Machine Intelligence in Characterization

autonomous↗

DOE OSTI2024

Beyond Human Vision: Exploring Materials with Machine Intelligence

artificial intelligence↗

DOE OSTI2022

Machine learned synthesizability predictions aided by density functional theory

Abstract A grand challenge of materials science is predicting synthesis pathways for novel compounds. Data-driven approaches have made significant progress in predicting a compound’s synthesizability; however, some recent attempts ignore phase stability information. Here, we combine thermodynamic stability calculated using density functional theory with composition-based features to train a machine learning model that predicts a material’s synthesizability. Our model predicts the synthesizability of ternary 1:1:1 compositions in the half-Heusler structure, achieving a cross-validated precision of 0.82 and recall of 0.82. Our model shows improvement in predicting non-half-Heuslers compared to a previous study’s model, and identifies 121 synthesizable candidates out of 4141 unreported ternary compositions. More notably, 39 stable compositions are predicted unsynthesizable while 62 unstable compositions are predicted synthesizable; these findings otherwise cannot be made using density functional theory stability alone. This study presents a new approach for accurately predicting synthesizability, and identifies new half-Heuslers for experimental synthesis.

Lee, Andrew (ORCID:0000000153014295)↗

DOE OSTI2024

Emerging magnetic materials for electric vehicle drive motors

Abstract Increasing demand for electric vehicles (EVs) is increasing demand for the permanent magnets that drive their motors, as approximately 80% of modern EV drivetrains rely on high-performance permanent magnets to convert electricity into torque. In turn, these high-performance permanent magnets rely on rare earth elements for their magnetic properties. These elements are “critical” (i.e., at risk of limiting the growth of renewable energy technologies such as EVs), which motivates an exploration for alternative materials. In this article, we overview the relevant fundamentals of permanent magnets, describe commercialized and emerging materials, and add perspective on future areas of research. Currently, the leading magnetic material for EV motors is Nd 2 Fe 14 B, with samarium-cobalt compounds (SmCo 5 and Sm 2 Co 17 ) providing the only high-performing commercialized alternative. Emerging materials that address criticality concerns include Sm 2 Fe 17 N 3 , Fe 16 N 2 , and the L1 0 structure of FeNi, which use lower cost elements that produce similar magnetic properties. However, these temperature-sensitive materials are incompatible with current metallurgical processing techniques. We provide perspective on how advances in low-temperature synthesis and processing science could unlock new classes of high-performing magnetic materials for a paradigm shift beyond rare earth-based magnets. In doing so, we explore the question: What magnetic materials will drive future EVs? Graphical abstract

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Probing the solidification of quasicrystals via joint experiment and simulation (Final Report)

Quasicrystals (QCs) possess long-range positional order but non-crystallographic orientational order. Their classically ‘forbidden’ symmetry has long attracted the interest of scientists worldwide. Despite their frequent observation in both metal alloys and soft matter structures in the 35 years since their discovery, little is known about how QCs evolve from a liquid, amorphous, or crystalline precursor. In this project, we sought to resolve the enigma of QC self-assembly through a combined experimental and computational program. The Shahani group employed in situ electron and synchrotron X ray imaging to peer into the growth dynamics of QCs in a liquid, covering a broad range of length scales and solidification pathways. Glotzer's team developed new simulation models incorporating phasonic defects — which are unique to quasicrystals — and used this model to investigate two grains growing together, closely mimicking the experimental conditions. While QCs remain exceptional structures, most compounds in the realm of intermetallics adopt non-trivial geometries. In fact, only around 6% of phases are comprised of the simplest sphere packings that researchers so readily associate with metals. State-of-the-art knowledge of phase transformations at the outset of this collaborative project did not encompass the remaining 94% of intermetallic compounds that possess complex and aperiodic structure types. Therefore, we expect that outcomes from this project will have immediate and profound impact on synthesis and processing science: our efforts will be used to not only explain the growth dynamics of QCs but also complex intermetallics more broadly.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Emerging magnetic materials for electric vehicle drive motors [Slides]

Increasing demand for electric vehicles (EVs) is increasing demand for the permanent magnets that drive their motors, as approximately 80% of modern EV drivetrains rely on high-performance permanent magnets to convert electricity into torque. In turn, these high-performance permanent magnets rely on rare earth elements for their magnetic properties. These elements are "critical" (i.e., at risk of limiting the growth of renewable energy technologies such as EVs), which motivates an exploration for alternative materials. In this article, we overview the relevant fundamentals of permanent magnets, describe commercialized and emerging materials, and add perspective on future areas of research. Currently, the leading magnetic material for EV motors is Nd 2 Fe 14 B, with samarium-cobalt compounds (SmCo 5 and Sm 2 Co 17 ) providing the only high-performing commercialized alternative. Emerging materials that address criticality concerns include Sm 2 Fe 17 N 3 , Fe 16 N 2 , and the L10 structure of FeNi, which use lower cost elements that produce similar magnetic properties. However, these temperature-sensitive materials are incompatible with current metallurgical processing techniques. We provide perspective on how advances in low-temperature synthesis and processing science could unlock new classes of high-performing magnetic materials for a paradigm shift beyond rare earth-based magnets. In doing so, we explore the question: What magnetic materials will drive future EVs?

42 ENGINEERING↗

DOE OSTI2023

A highly proton conductive perfluorinated covalent triazine framework via low-temperature synthesis

Proton-conducting materials are essential to the emerging hydrogen economy. Covalent triazine frameworks (CTFs) are promising proton-conducting materials at high temperatures but need more effective sites to strengthen interaction for proton carriers. However, their construction and design in a concise condition are still challenges. Herein, we show a low temperature approach to synthesize CTFs via a direct cyclotrimerization of aromatic aldehyde using ammonium iodide as facile nitrogen source. Among the CTFs, the perfluorinated CTF (CTF-TF) was successfully synthesized with much lower temperature ( ≤ 160 °C) and open-air atmosphere. Due to the additional hydrogen-bonding interaction between fluorine atoms and proton carriers (H 3 PO 4 ), the CTF-TF achieves a proton conductivity of 1.82 × 10 -1 S cm -1 at 150 °C after H 3 PO 4 loading. Moreover, the CTF-TF can be readily integrated into mixed matrix membranes, displaying high proton conduction abilities and good mechanical strength. This work provides an alternative strategy for rational design of proton conducting media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

In crystallo observation of three metal ion promoted DNA polymerase misincorporation

Error-free replication of DNA is essential for life. Despite the proofreading capability of several polymerases, intrinsic polymerase fidelity is in general much higher than what base-pairing energies can provide. Although researchers have investigated this long-standing question with kinetics, structural determination, and computational simulations, the structural factors that dictate polymerase fidelity are not fully resolved. Time-resolved crystallography has elucidated correct nucleotide incorporation and established a three-metal-ion-dependent catalytic mechanism for polymerases. Using X-ray time-resolved crystallography, we visualize the complete DNA misincorporation process catalyzed by DNA polymerase η. The resulting molecular snapshots suggest primer 3´-OH alignment mediated by A-site metal ion binding is the key step in substrate discrimination. Moreover, we observe that C-site metal ion binding preceded the nucleotidyl transfer reaction and demonstrate that the C-site metal ion is strictly required for misincorporation. Our results highlight the essential but separate roles of the three metal ions in DNA synthesis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

High-throughput chemical imaging for optimizing biofuel synthesis using synthetic biology (Final Technical Report)

Fatty acids can be produced biosynthetically in microbes and these compounds can serve as precursors to biodiesels and other high value oleochemicals. However, progress on engineering fatty acid biosynthesis, and biofuel synthesis more generally, has been hindered by current quantification methods that are either indirect or not amenable to high-throughput or single-cell resolution screening. In this project, we assembled an interdisciplinary team with complimentary expertise in synthetic biology and microscopy, metabolic engineering, and chemical imaging to address these challenges. We used chemical imaging to directly measure lipid biosynthesis in Escherichia coli engineered to produce fatty acids, obtaining detailed single-cell resolution measurements. We deployed stimulated Raman scattering (SRS) microscopy in concert with multiplexed genome engineering and gene circuit design strategies from synthetic biology to optimize production of fatty acids. These results provided novel insight into cell-to-cell heterogeneity present in biofuel production strains. In addition, we introduced new chemical imaging methods which are label-free and do not require fluorescent reporters. These efforts were complemented by other studied developing foundational tools for regulation and control, which offer excellent potential for advancing researchers’ ability to rapidly design, build, and test strains for enhanced biofuel synthesis.

09 BIOMASS FUELS↗

DOE OSTI2021

Low barrier height in a ZnO nanorods/NbSe 2 heterostructure prepared by van der Waals epitaxy

Two-dimensional (2D) materials as contacts for semiconductor devices have attracted much attention due to minimizing Fermi level pinning. Schottky–Mott physics has been widely employed to design 2D material-based electrodes and to elucidate their contact behavior. In this study, we revealed that charge transfer across a 2D/semiconductor heterointerface and materials characteristics besides work function should be accounted for in fabrication of electrodes based on 2D materials. Our density functional theory (DFT) calculations predicted that charge transfer between ZnO and NbSe 2 lowers the barrier height at the heterojunction and that conductive surface states of ZnO provide an additional conduction channel in the ZnO/NbSe 2 heterostructures. Crystalline ZnO/NbSe 2 heterostructures were prepared by the hydrothermal method. Electrical characterizations of the ZnO/NbSe 2 heterostructures showed Ohmic-like behavior as predicted by the DFT calculations, opposed to the prediction based on the Schottky–Mott model.

2D materials↗

DOE OSTI2023

Low temperature tetragonal polymorph of CaZrF 6

A new tetragonal polymorph of CaZrF 6 can be prepared by high energy ball milling of a CaF 2 /ZrF 4 mixture, followed by heat treatment at 325 °C. This polymorph is thermodynamically stable with respect to the well-known cubic form at low temperatures. However, it readily transforms to the cubic form on heating above ~400 °C. The tetragonal (β) CaZrF 6 is not isostructural with any previously known alkaline earth AZrF 6 phase. Unlike the cubic form, which shows strong negative thermal expansion over a wide temperature range, the tetragonal form displays positive thermal expansion in all directions (100–400 K: α l ~ +17 × 10 –6 K –1 and +13 × 10 –6 K –1 along the a- and c-axes, respectively).

36 MATERIALS SCIENCE↗

DOE OSTI2024

Discovering type I cis-AT polyketides through computational mass spectrometry and genome mining with Seq2PKS

Type 1 polyketides are a major class of natural products used as antiviral, antibiotic, antifungal, antiparasitic, immunosuppressive, and antitumor drugs. Analysis of public microbial genomes leads to the discovery of over sixty thousand type 1 polyketide gene clusters. However, the molecular products of only about a hundred of these clusters are characterized, leaving most metabolites unknown. Characterizing polyketides relies on bioactivity-guided purification, which is expensive and time-consuming. To address this, we present Seq2PKS, a machine learning algorithm that predicts chemical structures derived from Type 1 polyketide synthases. Seq2PKS predicts numerous putative structures for each gene cluster to enhance accuracy. The correct structure is identified using a variable mass spectral database search. Benchmarks show that Seq2PKS outperforms existing methods. Applying Seq2PKS to Actinobacteria datasets, we discover biosynthetic gene clusters for monazomycin, oasomycin A, and 2-aminobenzamide-actiphenol.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

The influence of cooling rate on condensation of iron, aluminum, and uranium oxide nanoparticles

Fundamental observations of particle size distributions are needed to develop models that predict the fate and transport of radioactive materials in the atmosphere following a nuclear incident. The extent of material transport is influenced by the time scales of particle formation processes (e.g., condensation, coagulation). In this study, we investigated the influence of cooling time scales on size distributions of uranium, aluminum, and iron oxide particles that are synthesized separately under identical run conditions inside the controlled environment of an argon plasma flow reactor. Two distinct temperature distributions are imposed along the flow reactor by varying the argon flow rate downstream of the plasma torch. The vaporized reactants of uranium, aluminum, and iron are cooled from about 5000K to 1000K before they are collected on silicon wafers for ex situ scanning electron microscope analysis. The microscope images show that the sizes of the largest aluminum and iron oxide particles heavily depend on the cooling time scales, whereas significant size variation with cooling rate is not observed for uranium oxide particles. In addition, the size distribution of aluminum oxide particles exhibits the broadest range among all three metal oxides studied. We performed simulations of particle size distributions using a kinetic model that couples gas phase oxidation chemistry with particle formation processes, including nucleation, condensation, and coagulation. The model results demonstrate the strong sensitivity of particle size distribution to different cooling histories (i.e., temperature vs residence time) along the flow reactor. In conclusion, the kinetic model also helps identify directions for future research to improve the predictions.

36 MATERIALS SCIENCE↗