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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

TiO x -supported Na-Mn-W oxides for the oxidative coupling of methane

Supported Na-Mn-W oxides are among the most studied catalysts for the oxidative coupling of methane (OCM) because of their superior thermal stability and relatively high C 2+ product yields. However, because of the structural complexity, the roles of each component in these catalysts have been controversial. In this work, WO x and MnO x sites were supported on titanate nanowires and employed in OCM studies. Compared to the commonly studied silica support, which is subject to severe restructuring due to the Na-induced crystallization, titanate support not only serves as a reservoir for alkali metals (e.g., Na), but also stabilizes isolated MnO x species. The catalytic performance of the titanate-based catalyst is similar to that of reference catalyst, MnO x /Na 2 WO 4 /SiO 2 , with a synergistic effect between MnO x and WO x sites. Further, advanced electron microscopy, X-ray diffraction, infrared spectroscopy, and X-ray absorption near edge structure spectroscopy suggest that the basic NaO x and MnO x species have strong interactions with the acidic WO x and TiO x species, which might contribute to the high selectivity toward C 2+ products and suppressed CO x formation.

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

Tunable Nanostructures from Inverse Surfactants

Hierarchical materials in the natural world are often made through the self-assembly of amphiphilic molecules. Achieving similar structural complexity in synthetic materials requires understanding how various molecular parameters affect assembly behavior. In recent years, inverse surfactants─molecules with hydrophobic head groups and hydrophilic macromolecular tails─have been shown to self-assemble into supramolecular assemblies in aqueous solutions that show promise for a number of applications, including drug delivery. Here, we build an understanding of the morphological phase diagram of inverse surfactants using insights from scattering experiments, computer simulations, and statistical mechanics. The scattering and simulation results reveal that changing the headgroup size is an important molecular knob in controlling morphological transitions. The molecular size ratio of the hydrophobic group to the hydrophilic group emerges as a crucial dimensionless quantity in our theory and plays a determining role in setting the micelle structure and the transition from mesoscale to macroscale aggregates. Our minimal theory is able to qualitatively explain the key features of the morphological phase diagram, including the prevalence of fiber-like structures in comparison to spherical and planar micelles. Together, these findings provide a more complete picture of the molecular dependencies of assemblies of inverse surfactants, which we hope may aid in the de novo design of supramolecular structures.

Christakopoulos, Panagiotis [ORNL] (ORCID:00090004↗
NASA NTRS1986

High dynamic range VLBI observations of NGC 6251

The large radio galaxy NGC 6251 has been observed with an 11-telescope VLBI array, including the full VLA, at 18 cm. High-dynamic-range maps of both the VLBI-scale and VLA-scale radio structure from these observations, as well as hybrid maps from earlier VLBI experiments at 6 and 13 cm, are presented. The 18-cm VLBI hybrid map has an unusually high dynamic range of about 300 to 1 (ratio of the peak brightness to five times the rms noise level) and is limited by thermal noise rather than calibration errors. A lower limit of 80 to 1 for the ratio of jet/counterjet brightness at parsec scales can be set. This is the strongest such limit produced by VLBI observations of any source to date. If the absence of a detectable counterjet is caused by relativistic beaming, then the jet must be aligned within 45 deg of the line of sight. The VLA map shows a complex structure along the previously detected kiloparsec-scale counterjet. The physical conditions in the inner few parsecs of the NGC 6251 jet and their relation to the conditions in the extraordinarily long and well collimated kiloparsec-scale jets are discussed, and it is shown that both small-scale and large-scale morphology can be explained in terms of a simple model and relativistic beaming.

Jones, D. L.↗
DOE OSTI2024

Frequency-domain computing using nonlinear acoustic-wave device on lithium niobate

Abstract Multiply-accumulation are crucial computing operations in signal processing, numerical simulations, and machine learning. In recent years, optical analog approaches have demonstrated higher computing performance and better power efficiency than their digital counterparts. However, analog computing chips usually need large areas and complex structures for parallel computing, as a single device element only executes one computing operation at a single time. Here, we demonstrate frequency-domain computing using the nonlinear acoustic-wave devices on lithium niobate, featuring a normalized external second-harmonic generation conversion efficiency of ~ 5.7 × 10-4 W-1. The second-order sum-frequency nonlinear process of lithium niobate enables multiplication of inputs encoded in the frequency domain. Compared to the analog schemes, our device features a notably simpler design, and nanofabrication requires only one lift-off. Using a single acoustic-wave device within an area of 0.03 mm2, we can simultaneously conduct over 130,000 multiply-accumulation operations. Our acoustic-wave device shows applications in real and complex vector convolutions and image processing. This demonstration sets the stage for experimental realizations into frequency-domain integrated nonlinear acoustic computing systems, potentially shaping future developments in acoustic neural networks and quantum computing.

chai, mingzhao (ORCID:0009000466226341)↗
DOE OSTI2024

Leveraging Artificial Intelligence to Expedite Antibody Design and Enhance Antibody–Antigen Interactions

This perspective sheds light on the transformative impact of recent computational advancements in the field of protein therapeutics, with a particular focus on the design and development of antibodies. Cutting-edge computational methods have revolutionized our understanding of protein–protein interactions (PPIs), enhancing the efficacy of protein therapeutics in preclinical and clinical settings. Central to these advancements is the application of machine learning and deep learning, which offers unprecedented insights into the intricate mechanisms of PPIs and facilitates precise control over protein functions. Despite these advancements, the complex structural nuances of antibodies pose ongoing challenges in their design and optimization. Our review provides a comprehensive exploration of the latest deep learning approaches, including language models and diffusion techniques, and their role in surmounting these challenges. We also present a critical analysis of these methods, offering insights to drive further progress in this rapidly evolving field. The paper includes practical recommendations for the application of these computational techniques, supplemented with independent benchmark studies. These studies focus on key performance metrics such as accuracy and the ease of program execution, providing a valuable resource for researchers engaged in antibody design and development. Through this detailed perspective, we aim to contribute to the advancement of antibody design, equipping researchers with the tools and knowledge to navigate the complexities of this field.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

New Trick for an Old Dog: From Prediction to Properties of “Hidden Clathrates” Ba 2 Zn 5 As 6 and Ba 2 Zn 5 Sb 6

The zinc–antimony phase space has been heavily investigated due to the structural complexity and abundance of high-performing thermoelectric materials. Consequentially, the desire to use zinc and antimony as framework elements to encage rattling cations and achieve phonon-glass-electron-crystal-type properties has remained an enticing goal with only two alkali metal clathrates to date, Cs 8 Zn 18 Sb 28 and K 58 Zn 122 Sb 207 . Guided by Zintl electron-counting predictions, here we explored the Ba–Zn–Pn (Pn = As, Sb) phase space proximal to the expected composition of the type-I clathrate. In situ powder X-ray diffraction studies revealed two “hidden” compounds which can only be synthesized in a narrow temperature range. The ex situ synthesis and crystal growth unveiled that instead of type-I clathrates, compositionally close but structurally different new clathrate-like compounds formed, Ba 2 Zn 5 As 6 and Ba 2 Zn 5 Sb 6 . These materials crystallize in a unique structure, in the orthorhombic space group Pmna with the Wyckoff sequence i 2 h 6 gfe. Single-phase synthesis enabled the exploration of their transport properties. Rattling of the Ba cations in oversized cages manifested low thermal conductivity, which, coupled with the high Seebeck coefficients observed, are prerequisites for a promising thermoelectric material. Potential for further optimization of the thermoelectric performance by aliovalent doping was computationally analyzed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1980

Structural attachments for large space structures

The feasibility of fabricating beams in space and using them as components of a large, crew assembled structure, was investigated. Two projects were undertaken: (1) design and development of a ground version of an automated beam builder capable of producing triangular cross section aluminum beams; and (2) design and fabrication of lap joints to connect the beams orthogonally and centroidal end caps to connect beams end to end at any desired angle. The first project produced a beam building machine which fabricates aluminum beams suitable for neutral buoyancy evaluation. The second project produced concepts for the lap joint and end cap. However, neither of these joint concepts was suitable for use by a pressure suited crew member in a zero gravity environment. It is concluded that before the beams can be evaluated the joint designs need to be completed and sufficient joints produced to allow assembly of a complex structure.

Pruett, E. C.↗
DOE OSTI2020

Three-Dimensional Imaging and Quantification of Gas Storativity in Nanoporous Media via X-rays Computed Tomography

This study provides the engineering science underpinnings for improved characterization and quantification of the interplay of gases with kerogen and minerals in shale. Natural nanoporous media such as shale (i.e., mudstone) often present with low permeability and dual porosity, making them difficult to characterize given the complex structural and chemical features across multiple scales. These structures give nanoporous solids a large surface area for gas to sorb. In oil and gas applications, full understanding of these media and their sorption characteristics are critical for evaluating gas reserves, flow, and storage for enhanced recovery and CO 2 sequestration potential. Other applications include CO 2 capture from industrial plants, hydrogen storage on sorbent surfaces, and heterogeneous catalysis in ammonia synthesis. Therefore, high-resolution experimental procedures are demanded to better understand the gas–solid behavior. In this study, CT imaging was applied on the sub-millimeter scale to shale samples (Eagle Ford and Wolfcamp) to improve quantitative agreement between CT-derived and pulse decay (mass balance) derived results. Improved CT imaging formulations are presented that better match mass balance results, highlighting the significance of gas sorption in complex nanoporous media. The proposed CT routine implemented on the Eagle Ford sample demonstrated a 17% error reduction (22% to 5%) when compared to the conventional CT procedure. These observations are consistent in the Wolfcamp sample, emphasizing the reliability of this technique for broader implementation of digital adsorption studies in nanoporous geomaterials.

42 ENGINEERING↗
DOE OSTI2021

Performance of Embedded Sensors in 3D Printed SiC

This report summarizes recent advances in embedding sensors in 3D printed silicon carbide (SiC) ceramic components under the Transformational Challenge Reactor (TCR) program. The additive manufacturing technologies developed under this program will enable fabrication of complex structures with embedded fuels and sensors. The sensors will be capable of characterizing fuel performance using spatially distributed measurements at the most strategic locations that would be otherwise inaccessible using conventional manufacturing techniques. While previous programmatic updates describe initial concepts for embedding sensors, materials selection, and initial characterization of the embedded sensors, the technology requires further demonstration, and quality-significant procedures must be established before the embedding technology is ready for adoption by industry. To this end, this report describes the most effective techniques that have been used to embed functional sensors in 3D printed components using a combination of binder-jet additive manufacturing and chemical vapor infiltration (CVI). A detailed procedure describes each step in the process and is available upon request. Molybdenum (Mo)-sheathed thermocouples have been successfully embedded in complex SiC components, and temperatures were monitored in situ during the embedding process. Post-embedding measurements showed no significant hysteresis, and characterization of the interface revealed qualitatively strong bonding around the entire perimeter of the sensor sheath. Distributed fiber-optic temperature sensors were able to briefly measure temperature profiles during CVI, but they ultimately failed prior to completion of the CVI run. The failure appears to be related to the fiber coating at temperatures close to 1,000°C. Future work will focus on irradiation testing of embedded thermocouples and other sheathed electrical sensors, as well as the identification of fiber-optic sensor coatings that can survive CVI.

42 ENGINEERING↗
DOE OSTI2023

Prediction and Validation of Flow Properties in Porous Lattice Structures

High-porosity metal foams have been extensively studied as an attractive candidate for efficient and compact heat exchanger design. With the advancements in additive manufacturing, such foams can be manufactured with controlled topology to yield highly tailorable mechanical and transport properties. In this study, a lattice Boltzmann method (LBM)-based pore-scale model is implemented to simulate the fluid flow in additively manufactured (AM) metal foams with unit cell topologies of Cube, Face Diagonal (FD)-Cube, Tetrakaidecahedron (TKD), and Octet lattices. The pressure gradient versus average velocity profiles predicted by the LBM model were validated against in-house measurements on the AM lattice samples with the same unit cell topologies. Based on the simulation results, a novel hybrid model is proposed to accurately predict the volume averaged flow properties (permeability and inertial coefficients) of the four structures. Specifically, the linear LBM (neglecting inertial forces) is first implemented to obtain the intrinsic permeability, and then the standard LBM is applied to obtain the inertial coefficient. Convenient correlations for those flow properties as a function of porosity and fiber diameter are constructed. The effects of the AM print qualities on the flow properties are also discussed. The advantages of the hybrid model compared to the polynomial fitting approach for determining flow properties are discussed and compared quantitatively. The hybrid model and presented results are valuable for flow and thermal transport evaluation when designing new metal foams for specific applications and with different materials and topologies. Finally, the presented correlations based on pore-scale simulations can also be conveniently used in volume-averaged models to predict the macroscale flow behavior in such complex structures.

42 ENGINEERING↗
DOE OSTI2022

Effect of iron redox ratio on the structures of boroaluminosilicate glasses

Iron oxide is commonly found in natural or industrial glass compositions and can exist as ferrous (Fe 2+ ) or ferric (Fe 3+ ) species, with their ratios depending on glass composition, temperature, pressure and the redox reactions during the glass forming process. The iron redox ratio plays an important role on silicate glass structures and consequently various properties. This work aims to study the effect of iron oxide, and particularly the iron redox ratio, on the structures of borosilicate and boroaluminosilicate glasses using molecular dynamics simulations with newly developed iron potential parameters that are compatible with the borosilicate potentials. The results provide detailed cation coordination states of both iron species and the effect of redox ratio on boron coordination and other structural features. Particularly, competition for charge compensating modifier cations (such as Na + ) among the fourfold-coordinated cations such as B 3+ , Al 3+ , and Fe 3+ is investigated by calculating the cation–cation pair distribution functions and coordination preferential ratios. The results show that the trivalent ferric ions, with a shorter Fe–O bond distance and better defined first coordiation shell with mainly four-fold coordination, act as a glass former whereas the divalent ferrous ions mainly play the role of glass modifier. The ferrous/ferric ratio (Fe 2+ /Fe 3+ ) was found to affect the glass chemistry and hence glass properties by regulating the amount of four-coordinated boron, the fraction of non-briding oxygen and other features. Finally, the results are compared with available experimental data to gain insights of the complex structures and charge compensation schemes of the glass system.

36 MATERIALS SCIENCE↗
DOE OSTI2020

On Simulating the Formation of Structured, Crystalline Systems via Non-classical Pathways

Observations in crystal growth and assembly from recent in situ methods suggest alternative, non-classical crystallization pathways play an important role in the determination of the micro- and meso- structures in crystalline systems. These processes display parallels that cross-cut multiple disciplines investigating crystallization across four orders of magnitude in size scales and widely differing environments, hinting that alternative crystal growth pathways may be a fundamental scheme in natural crystal formation. Using a system of short-range attractive microbeads, we demonstrate that the addition of a small concentration of sub-species incommensurate with the lattice spacing of the dominant species results in a stark change in crystal size and morphology. These changes are attributed to the presence of fleeting, amorphous-like configurations of beads that ultimately change the melting and growth dynamics in preferred directions. From these real-time observations, we hypothesize the amorphous mineral precursors present in biological mineralized tissues undergo similar non-classical crystallization processes resulting in the complex structures found in biomineralization.

36 MATERIALS SCIENCE↗
NASA NTRS2003

Combined Radiometer-Radar Microphysical Profile Estimations with Emphasis on High Frequency Brightness Temperature Observations

Information about the vertical microphysical cloud structure is useful in many modeling and predictive practices. Radiometers and radars are used to observe hydrometeor properties. This paper describes an iterative retrieval algorithm that combines the use of airborne active and wideband (10 to 340 GHz) passive observations to estimate the vertical content and particle size distributions of liquid and frozen hydrometeors. The physically-based retrieval algorithm relies on the high frequencies (greater than 89 GHz) to provide details on the frozen hydrometeors. Neglecting the high frequencies yielded acceptable estimates of the liquid profiles, but the ice profiles were poorly retrieved. Airborne radar and radiometer observations from the third Convection and Moisture EXperiment (CAMEX-3) were used in the retrieval algorithm as constraints. Nadir profiles were estimated for a minute each of flight time (approximately 12.5 km along track) from an anvil, convection, and quasi- stratiform rain. The complex structure of the frozen hydrometeors required the most iterations for convergence for the anvil cloud type. The wideband observations were found to more than double the estimated frozen hydrometeor content as compared to retrievals using only 90-GHz and below. The convective and quasi-stratiform quickly reached convergence (minimized difference between observations and calculations using the estimated profiles). A qualitative validation using coincident in situ CAMEX-3 observations shows that the retrieved particle size distributions are well corroborated with independent measurements.

Gail Skofronick-Jackson↗
DOE OSTI2021

Davis Computational Spectroscopy Workflow—From Structure to Spectra

Here, we describe an automated workflow that connects a series of atomic simulation tools to investigate the relationship between atomic structure, lattice dynamics, materials properties, and inelastic neutron scattering (INS) spectra. Starting from the atomic simulation environment (ASE) as an interface, we demonstrate the use of a selection of calculators, including density functional theory (DFT) and density functional tight binding (DFTB), to optimize the structures and calculate interatomic force constants. We present the use of our workflow to compute the phonon frequencies and eigenvectors, which are required to accurately simulate the INS spectra in crystalline solids like diamond and graphite as well as molecular solids like rubrene. We have also implemented a machine-learning force field based on Chebyshev polynomials called the Chebyshev interaction model for efficient simulation (ChIMES) to improve the accuracy of the DFTB simulations. We then explore the transferability of our DFTB/ChIMES models by comparing simulations derived from different training sets. We show that DFTB/ChIMES demonstrates ~100× reduction in computational expense while retaining most of the accuracy of DFT as well as yielding high accuracy for different materials outside of our training sets. The DFTB/ChIMES method within the workflow expands the possibilities to use simulations to accurately predict materials properties of increasingly complex structures that would be unfeasible with ab initio methods.

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

Mechanistic Insights into Copper(I) and Copper(II) Cation Exchange Reactions in CdSe Nanoplatelets

In this study, we investigated the synthesis of copper selenide nanoplatelets (NPLs) through a cation exchange reaction (CER) in 5-monolayer-thick CdSe NPLs using Cu(I) and Cu(II) precursors. We discovered that the exposure of CdSe NPLs to a Cu(I) precursor led to the transformation of NPLs into Cu 2-x Se while maintaining their nanoplatelet morphology. The replacement of Cd(II) with Cu(I) prevailed over the formation of doped structures. In the case of the Cu(II) precursor, we observed that Cu(II) was first reduced to Cu(I) before being intercalated into the host lattice, resulting in the synthesis of Cu 2-x Se, similar to CER with Cu(I) precursors but without preservation of the initial morphology of NPLs. Interestingly, the presence of oxygen was found to facilitate the cation exchange processes in CdSe NPLs, whereas a nitrogen atmosphere suppressed the CER. Further, despite the similar ionic sizes of Cu(I) and Cu(II), the substitution of Cd(II) with Cu(II) was found to be challenging, possibly due to the involvement of redox processes resulting in the significant deterioration of initial CdSe NPLs. We demonstrate that CER can achieve near-complete substitution of cadmium atoms with monovalent copper at room temperature. Understanding the processes involved in CERs is crucial for engineering more complex structures, such as high-entropy nanoparticles involving cation exchange with different oxidation states and development of material synthesis using machine learning and artificial intelligence approaches.

2D nanoplatelets↗
DOE OSTI2024

Dynamic Evolution of Copper Nanowires during CO 2 Reduction Probed by Operando Electrochemical 4D-STEM and X-ray Spectroscopy

Nanowires have emerged as an important family of one-dimensional (1D) nanomaterials owing to their exceptional optical, electrical, and chemical properties. In particular, Cu nanowires (NWs) show promising applications in catalyzing the challenging electrochemical CO 2 reduction reaction (CO 2 RR) to valuable chemical fuels. Despite early reports showing morphological changes of Cu NWs after CO 2 RR processes, their structural evolution and the resulting exact nature of active Cu sites remain largely elusive, which calls for the development of multimodal operando time-resolved nm-scale methods. Here, in this study, we report that well-defined 1D copper nanowires, with a diameter of around 30 nm, have a metallic 5-fold twinned Cu core and around 4 nm Cu 2 O shell. Operando electrochemical liquid-cell scanning transmission electron microscopy (EC-STEM) showed that as-synthesized Cu@Cu 2 O NWs experienced electroreduction of surface Cu 2 O to disordered (spongy) metallic Cu shell (Cu@Cu S NWs) under CO 2 RR relevant conditions. Cu@Cu S NWs further underwent a CO-driven Cu migration leading to a complete evolution to polycrystalline metallic Cu nanograins. Operando electrochemical four-dimensional (4D) STEM in liquid, assisted by machine learning, interrogates the complex structures of Cu nanograin boundaries. Correlative operando synchrotron-based high-energy-resolution X-ray absorption spectroscopy unambiguously probes the electroreduction of Cu@Cu 2 O to fully metallic Cu nanograins followed by partial reoxidation of surface Cu during postelectrolysis air exposure. This study shows that Cu nanowires evolve into completely different metallic Cu nanograin structures supporting the operando (operating) active sites for the CO 2 RR.

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

Isothermal Microcalorimetry Analysis of Li/ β -MnO 2 Discharge

Despite widespread use over several decades, the lithium/manganese dioxide (Li/MnO 2 ) discharge mechanism is not completely understood owing to the structural complexity of the material. However, an improved understanding could lead to broader adoption as a primary and even secondary cathode material. Here, we examine the discharge of single-phaseβ-MnO 2 using isothermal microcalorimetry for the first time. Equilibrium voltage and entropy changes are characterized over the entire discharge range and used to rationalize the results. These measurements are supplemented by electrochemical impedance and X-ray diffraction data that give the clearest picture of theβ-MnO 2 lithiation process to date. We find that the first half of discharge is dominated by a two-phase reaction to form Li 0.5 MnO 2 followed by single-phase insertion to a composition of Li 1.0 MnO 2 , which confirms prior first-principles calculations. The tetragonalβ-MnO 2 lattice undergoes asymmetric expansion from Jahn-Teller distorted Mn 3+ to form an orthorhombic LiMnO 2 phase which retains the 1 × 1 tunnel structure. Microcalorimetry results suggest the presence of parasitic reactions occurring during the second half of discharge, which could arise from decomposition of electrolyte or release and reaction of residual water retained in the structure.

Electrochemistry↗
DOE OSTI2022

Dual Atomic Coherence in the Self-Assembly of Patchy Heterostructural Nanocrystals

Advances in the synthesis and self-assembly of nanocrystals have enabled researchers to create a plethora of different nanoparticle superlattices. But while many super lattices with complex types of translational order have been realized, rotational order of nanoparticle building blocks within the lattice is more difficult to achieve. Self-assembled superstructures with atomically coherent nanocrystal lattices, which are desirable due to their exceptional electronic and optical properties, have been fabricated only for a few selected systems. Here, we combine experiments with molecular dynamics (MD) simulations to study the self-assembly of heterostructural nanocrystals (HNCs), consisting of a near-spherical quantum dot (QD) host decorated with a small number of epitaxially grown gold nanocrystal (Au NC) "patches ". Self-assembly of these HNCs results in face-centered-cubic (fcc) superlattices with well-defined orientational relationships between the atomic lattices of both QD hosts and Au patches. MD simulations indicate that the observed dual atomic coherence is linked to the number, size, and relative positions of gold patches. Here this study provides a strategy for the design and fabrication of NC superlattices with large structural complexity and delicate orientational order.

77 NANOSCIENCE AND NANOTECHNOLOGY↗