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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 775 records · Page 43

Predicting Catalyst Surface Stability Under Reaction Conditions Using Deep Reinforcement Learning and Machine Learning Potentials

Catalysts are critical for most large-scale energy intensive chemical transformation processes, such as energy storage, liquid fuel production, and the formation of chemical building blocks. The catalyst composition, structure, and morphology impact the performance under reaction conditions and influences properties like activity and selectivity. Many industrial catalysts offer imperfect activity/selectivity, or contain expensive metals. Further, catalysts can deactivate over time as the morphology changes or harsh reactive environments alter the surface structure. Methods to automatically model and predict the kinetics of how catalyst surfaces will restructure would enable engineers to design around these challenges, improve performance, increase longevity. This project investigated a specific type of machine learning model, deep reinforcement learning, machine learning models to act as surrogates for the physical system, and compared the results of these approaches with a specialized high-throughput experimental synthesis and measurement platform.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advances in relaxation and memory effects of magnetic nanoparticles for biomedical applications

Functionalized magnetic nanoparticles are pivotal in magnetic resonance imaging, computed tomography, controlled drug delivery, and hyperthermia treatments due to their exceptional magnetic relaxation and functional properties. The magnetic core composition and structure significantly affects the complex magnetic properties of these nanoparticles necessitating a thorough examination of magnetism fundamentals related to these systems. One important aspect is the ability of magnetic nanoparticles to retain previous magnetic state configurations known as memory effect, primarily governed by domain structure and magnetic anisotropy. Despite its relevance to advanced applications, comprehensive studies on magnetic relaxation and memory effects remain limited. Here, the present review aims to bridge this gap by investigating relaxation mechanisms, synthesis strategies, and applications, fostering further innovation. It investigates the memory effects and their dependence on particle composition and morphology along with key synthesis techniques for large-scale production in industrial adoption. Structured into focused sections on magnetic properties and their influence on biomedical and technological applications, this review provides essential insights into memory effects, magneto-relaxation mechanisms, influencing factors, and both experimental and theoretical methodologies. It also delves into computational modelling and AI-driven design, which are revolutionizing the prediction, discovery, and optimization of materials with tailored properties.

36 MATERIALS SCIENCE↗

Probabilistic Deep Learning Approach to Automate the Interpretation of Multi-phase Diffraction Spectra

Autonomous synthesis and characterization of inorganic materials requires the automatic and accurate analysis of X-ray diffraction spectra. For this task, we designed a probabilistic deep learning algorithm to identify complex multi-phase mixtures. At the core of this algorithm lies an ensemble convolutional neural network trained on simulated diffraction spectra, which are systematically augmented with physics-informed perturbations to account for artifacts that can arise during experimental sample preparation and synthesis. In this work, larger perturbations associated with off-stoichiometry are also captured by supplementing the training set with hypothetical solid solutions. Spectra containing mixtures of materials are analyzed with a newly developed branching algorithm that utilizes the probabilistic nature of the neural network to explore suspected mixtures and identify the set of phases that maximize confidence in the prediction. Our model is benchmarked on simulated and experimentally measured diffraction spectra, showing exceptional performance with accuracies exceeding those given by previously reported methods based on profile matching and deep learning. We envision that the algorithm presented here may be integrated in experimental workflows to facilitate the high-throughput and autonomous discovery of inorganic materials.

36 MATERIALS SCIENCE↗

NEXTorch: A Design and Bayesian Optimization Toolkit for Chemical Sciences and Engineering

Automation and optimization of chemical systems require well-informed decisions on what experiments to run to reduce time, materials, and/or computations. Data-driven active learning algorithms have emerged as valuable tools to solve such tasks. Bayesian optimization, a sequential global optimization approach, is a popular active-learning framework. Past studies have demonstrated its efficiency in solving chemistry and engineering problems. Here we introduce NEXTorch, a library in Python/PyTorch, to facilitate laboratory or computational design using Bayesian optimization. NEXTorch offers fast predictive modeling, flexible optimization loops, visualization capabilities, easy interfacing with legacy software, and multiple types of parameters and data type conversions. It provides GPU acceleration, parallelization, and state-of-the-art Bayesian optimization algorithms and supports both automated an d human-in-the-loop optimization. The comprehensive online documentation introduces Bayesian optimization theory and several examples from catalyst synthesis, reaction condition optimization, parameter estimation, and reactor geometry optimization. NEXTorch is open-source and available on GitHub

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computer-oriented synthesis of wide-band non-uniform negative resistance amplifiers

This paper presents a synthesis procedure which provides design values for broad-band amplifiers using non-uniform negative resistance devices. Employing a weighted least squares optimization scheme, the technique, based on an extension of procedures for uniform negative resistance devices, is capable of providing designs for a variety of matching network topologies. It also provides, for the first time, quantitative results for predicting the effects of parameter element variations on overall amplifier performance. The technique is also unique in that it employs exact partial derivatives for optimization and sensitivity computation. In comparison with conventional procedures, significantly improved broad-band designs are shown to result.

Branner, G. R.↗

Performance and Reliability Optimization for Aerospace Systems subject to Uncertainty and Degradation

This report summarizes work performed by the Space Systems Laboratory (SSL) for NASA Langley Research Center in the field of performance optimization for systems subject to uncertainty. The objective of the research is to develop design methods and tools to the aerospace vehicle design process which take into account lifecycle uncertainties. It recognizes that uncertainty between the predictions of integrated models and data collected from the system in its operational environment is unavoidable. Given the presence of uncertainty, the goal of this work is to develop means of identifying critical sources of uncertainty, and to combine these with the analytical tools used with integrated modeling. In this manner, system uncertainty analysis becomes part of the design process, and can motivate redesign. The specific program objectives were: 1. To incorporate uncertainty modeling, propagation and analysis into the integrated (controls, structures, payloads, disturbances, etc.) design process to derive the error bars associated with performance predictions. 2. To apply modern optimization tools to guide in the expenditure of funds in a way that most cost-effectively improves the lifecycle productivity of the system by enhancing the subsystem reliability and redundancy. The results from the second program objective are described. This report describes the work and results for the first objective: uncertainty modeling, propagation, and synthesis with integrated modeling.

Miller, David W.↗

Precision Synthesis of Conjugated Polymer Films by Surface-Confined Stepwise Sonogashira Cross-Coupling

Thin films of poly(arylene ethynylene)-conjugated polymers, including low-energy-gap donor–acceptor polymers, can be prepared via stepwise polymerization utilizing surface-confined Sonogashira cross-coupling. This robust and efficient polymerization protocol yields conjugated polymers with a precise molecular structure and with nanometer-level control of the organization and the uniform alignment of the macromolecular chains in the densely packed film. In addition to high stability and predictable and well-defined molecular organization and morphology, the surface-confined conjugated polymer chains experience significant interchain electronic interactions, resulting in dominating intermolecular π-electron delocalization which is primarily responsible for the electronic and spectroscopic properties of polymer films. The fluorescent films demonstrate remarkable performance in chemosensing applications, showing a turn-off fluorescent response on the sub-ppt (part per trillion) level of nitroaromatic explosives in water. This unique sensitivity is likely related to the enhanced exciton mobility in the uniformly aligned and structurally monodisperse polymer films.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Towards the Synthesis and Identification of Tetrahedral N4

Tetrahedral (Td)-N4 has attracted attention as a high energy density material candidate. Although computational studies have shown Td-N4 to be a stable structure on the ground-state potential energy surface, it has yet to be experimentally observed. This study investigates possible synthetic pathways via excited state surfaces. Preliminary results include a comparison of vertical excitation energies from Td-N4 using CIS, CIS(D), CIS(3), LRCCSD, CASSCF, CASPT2, and MRCI ab initio methods. Previous studies have predicted weak IR vibrational intensities. Therefore, alternative detection schemes of Td-N4 are also investigated, such as UV and vibrational Raman spectroscopy.

Dateo, Christopher E.↗

High Energy Density Physics of Inertial Confinement Fusion Ablator Materials

The historic December 5, 2022 experiment at Lawrence Livermore National Lab’s (LLNL) National Ignition Facility (NIF) reached fusion energy ignition for the first time. This is the most important scientific breakthrough of the 21st century paves the way to future clean inertial fusion energy (IFE). The diamond (high density carbon (HDC)) ablator material used in this experiment displays detrimental effects due to the development of hydrodynamic instabilities at the diamond/fuel interface under shock compression. New alternatives to diamond ablators are required to step up the energy yield in ICF experiments. The unique combination of mechanical strength (approaching that of diamond), the ability to accommodate high-Z dopants (in contrast to diamond), and the tunability of the properties (through synthesis material with varying sp 3 content) make amorphous carbon (a-C) a promising material for next-generation IFE ablative capsules. However, despite its critical importance to the IFE program, the behavior of a-C carbon at extreme temperatures and pressures remains largely unexplored. The primary goals of this project were to perform groundbreaking dynamic compression experiments and predictive simulations to uncover the fundamental high-energy-density physics of amorphous carbon. Our goals were (1) to uncover the metastability range of amorphous carbon and probe phase transitions to diamond or metastable supercooled liquid carbon; (2) to acquire high-quality equation of state (EOS) data and develop an experimentally validated EOS from machine-learning MD simulations of the complex states of carbon; and (3) to uncover the complex behavior of carbon liquid in both thermodynamically stable and metastable supercooled states by accessing large areas of carbon phase diagram with amorphous samples with variable sp 3 content. Our proposed experimental program included measurements of equation of state and diffraction measurements using the Omega EP laser at the Laboratory of Laser Energetics at the University of Rochester. The theoretical/simulation program involved the development of machine-learning models of the complex response of amorphous carbon under dynamic compression by performing molecular dynamics simulations at experimental time and length scales using leadership class DOE supercomputers. Simulations guided experiments to observe predicted phenomena and acquire critical experimental data in specific pressure-temperature domains to validate theoretical models. This research delivered fundamental properties of novel amorphous carbon IFE ablator material, including phase diagram and EOS. These results will aid in IFE target design and implosion experiments. A unique combination of predictive simulations and dynamic and static experiments provided a highly inspirational intellectual environment for graduate students and postdocs involved in this project.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Open-loop nanosecond-synchronization for wideband satellite communications

A synchronization technique for use with an onboard processing satellite communication system is discussed. The satellite oscillator is used both as the system time reference and as the frequency source for all downlink carriers and data clocks. Downlink timing is established at each system earth terminal through a combination of carrier and data-clock tracking and a downlink timing epoch signal consisting of one bit per TDMA data burst. Uplink timing is established by an open-loop range prediction process using precision ephemerides calculated and distributed by the central control station. Overall timing accuracy of the uplink signal at the satellite receiver of + or - 7 nanoseconds permits unambiguous identification of each data bit position in a 128 Mbps TDMA burst. This is accomplished by means of simple, inexpensive terminal hardware using available crystal oscillators for time/frequency references and digital synthesis techniques that may be implemented in digital LSI chips.

Holmes, W. M., Jr.↗

Full spectrum (350-2500 nm) leaf and canopy spectral reflectance, Seward Peninsula, Alaska, 2019

Full-range (350 - 2500 nm) leaf and canopy reflectance spectra of various Arctic tundra ecosystem endmembers, including species-level leaf reflectance, canopy-scale species endmember spectra, plot-scale spectra, and transect spectra. These data were collected in support of ongoing NASA ABoVE AVIRIS data synthesis work. The datasets were collected at the NGEE-Arctic watershed sites, Kougarok MM64 and MM80, and Teller MM27 on the Seward Peninsula, Alaska. The data were collected in July 2019 using a full-range Spectra Vista Corporation (SVC) HR-1024i spectroradiometer. Leaf-level spectra were collected with the original SVC leaf clip/plant probe connected to the spectrometer through a 1.15 meter long fiber optic cable, while canopy-scale reflectance was collected with an 8-degree field-of-view (FOV) foreoptic lens. All spectral measurements were collected as calibrated surface radiance and converted to surface reflectance using a 99.99% reflective Spectralon white reference standard. For those canopy spectra collected with associated functional trait data, the FOV of the instrument was positioned to include the same leaves harvested for functional trait measurements, including leaf mass per area (LMA) and foliar carbon and nitrogen content (see leaf trait data package for these data). Canopy spectra were obtained for 23 different species, and leaf spectra for 8 species. This data package includes processed canopy and leaf spectra (*.csv), processed dGPS locations (*.csv and *.kmz), digital photographs of spectral targets (*.jpg) and raw data from spectroradiometer and dGPS instruments (compressed as tar.gz). Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA212_flmd.csv.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Stellar Characterization and Radius Inflation of Hyades M-dwarf Stars from the APOGEE Survey

We present a spectroscopic analysis of a sample of 48 M-dwarf stars (0.2 M ⊙ < M < 0.6 M ⊙ ) from the Hyades open cluster using high-resolution H-band spectra from the Sloan Digital Sky Survey/Apache Point Observatory Galactic Evolution Experiment (APOGEE) survey. Our methodology adopts spectrum synthesis with LTE MARCS model atmospheres, along with the APOGEE Data Release 17 line list, to determine effective temperatures, surface gravities, metallicities, and projected rotational velocities. The median metallicity obtained for the Hyades M dwarfs is [M/H] = 0.09 ± 0.03 dex, indicating a small internal uncertainty and good agreement with optical results for Hyades red giants. Overall, the median radii are larger than predicted by stellar models by 1.6% ± 2.3% and 2.4% ± 2.3%, relative to a MIST and DARTMOUTH isochrone, respectively. We emphasize, however, that these isochrones are different, and the fractional radius inflation for the fully and partially convective regimes have distinct behaviors depending on the isochrone. Using a MIST isochrone there is no evidence of radius inflation for the fully convective stars, while for the partially convective M dwarfs the radii are inflated by 2.7% ± 2.1%, which is in agreement with predictions from models that include magnetic fields. For the partially convective stars, rapid rotators present on average higher inflation levels than slow rotators. The comparison with SPOTS isochrone models indicates that the derived M-dwarf radii can be explained by accounting for stellar spots in the photosphere of the stars, with 76% of the studied M dwarfs having up to 20% spot coverage, and the most inflated stars with ~20%–40% spot coverage.

79 ASTRONOMY AND ASTROPHYSICS↗

Computer study of a jet flap ASTVOL 'Harrier'

A study of the costs/benefits trade-off was conducted for an Advanced Supersonic Short Takeoff and Vertical Landing (ASTOVL) aircraft incorporating a jet flap. The data used were the theory of jet flaps and high aspect ratio nozzles, experience with a V/STOL aircraft study performed for NASA Ames Research Center in February 1982, and a high performance aircraft-synthesis program (ACSYNT). The methodology was to accurately model the supersonic Harrier V/STOL aircraft design on ACSYNT, and then modify the design by both adding high aspect-ratio nozzles in place of the rear (core-flow) nozzles on the Pegasus-type turbofan engine, and integrating these nozzles on each wing's trailing edge, thus creating a jet flap. The predicted performance advantages (increase in maximum lift coefficient with flap deflection and horizontal thrust recovery) were traded off against the disadvantages (additional weight and thrust loss due to ducting) on two representative missions.

Wilson, S. B., III↗

Low Temperature CO 2 Hydrogenation on Unsupported Mo 2 C Catalysts

CO 2 hydrogenation to methanol, a key reaction for decarbonizing the fuel and chemical industries, requires catalyst formulations that hydrogenate CO 2 selectively to methanol at temperatures where methanol conversion is not significantly equilibrium limited (<423 K). Herein we report continuous CO 2 hydrogenation at low temperatures (348-408 K, H 2 /CO 2 = 0.1-50, 5-35 bar) with high selectivity to methanol (up to ca. 80%) over unsupported β-Mo 2 C catalysts. Active site density quantification via titration with trifluoroacetic acid at reaction temperatures enables an assessment of site-specific rates. Methanation and reverse water gas shift (RWGS) occur concurrently with methanol synthesis during CO 2 hydrogenation over Mo 2 C. Reaction pathway analysis, product cofeeds, and reversibility formalisms show that all products form through primary reaction pathways from CO 2 , but secondary reactions of CO contribute significantly to rates of methanation. Dependences of forward rates on reactant and product concentration determined by independently varying the CO 2 , H 2 , CO, H 2 O, CH 3 OH, and CH 4 pressure in conjunction with reversibility formalisms reveal that all products form through H-assisted CO 2 activation and involve partially hydrogenated CO 2 -derived intermediates. Here, these inferences were verified by quantitative agreement between measured site-time yields and site-time yields predicted by closed form kinetic rate expressions in an integral reactor model over widely varying conditions (85-2000 kPa H 2 , 80-1500 kPa CO 2 , 0-45 kPa H 2 O, 0-21 kPa CO, 0-25 kPa CH 3 OH, 0-75 kPa CH 4 , 5-87 mol Mo s s mol CO 2 -1 ). Coverages calculated based on the kinetic model reveal that the Mo 2 C surface is covered with bidentate CO- and CO 2 -derived intermediates of the stoichiometry H 2 CO 2 and H 2 CO, indicating that H 2 and CO x do not compete for surface occupancy but instead adsorb cooperatively to form partially hydrogenated intermediates. Hydrogenation of the CO-derived H 2 CO** intermediate favors methanation, while hydrogenation of CO 2 -derived H 2 CO 2 ** favors methanol synthesis. Together, these findings demonstrate the ability of unsupported Mo 2 C to catalyze the hydrogenation of CO 2 to methanol at low temperatures and provide insight into the reaction network and mechanisms involved in its formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Intrinsic Defects in MoS 2 Grown by Pulsed Laser Deposition: From Monolayers to Bilayers

Pulsed laser deposition (PLD) can be considered a powerful method for the growth of two-dimensional (2D) transition-metal dichalcogenides (TMDs) into van der Waals heterostructures. However, despite significant progress, the defects in 2D TMDs grown by PLD remain largely unknown and yet to be explored. In this work, we combine atomic resolution images and first-principles calculations to reveal the atomic structure of defects, grains, and grain boundaries in mono- and bilayer MoS 2 grown by PLD. We find that sulfur vacancies and MoS antisites are the predominant point defects in 2D MoS 2 . We predict that the aforementioned point defects are thermodynamically favorable under a Mo-rich/S-poor environment. The MoS 2 monolayers are polycrystalline and feature nanometer size grains connected by a high density of grain boundaries. In particular, the coalescence of nanometer grains results in the formation of 180° mirror twin boundaries consisting of distinct 4- and 8-membered rings. We show that PLD synthesis of bilayer MoS 2 results in various structural symmetries, including AA' and AB, but also turbostratic with characteristic moiré patterns. Moreover, we report on the experimental demonstration of an electron beam-driven transition between the AB and AA' stacking orientations in bilayer MoS 2 . These results provide a detailed insight into the atomic structure of monolayer MoS 2 and the role of the grain boundaries on the growth of bilayer MoS 2 , which has importance for future applications in optoelectronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spontaneous dynamical disordering of borophenes in MgB2 and related metal borides

Abstract Layered boron compounds have attracted significant interest in applications from energy storage to electronic materials to device applications, owing in part to a diversity of surface properties tied to specific arrangements of boron atoms. Here we report the energy landscape for surface atomic configurations of MgB 2 by combining first-principles calculations, global optimization, material synthesis and characterization. We demonstrate that contrary to previous assumptions, multiple disordered reconstructions are thermodynamically preferred and kinetically accessible within exposed B surfaces in MgB 2 and other layered metal diborides at low boron chemical potentials. Such a dynamic environment and intrinsic disordering of the B surface atoms present new opportunities to realize a diverse set of 2D boron structures. We validated the predicted surface disorder by characterizing exfoliated boron-terminated MgB 2 nanosheets. We further discuss application-relevant implications, with a particular view towards understanding the impact of boron surface heterogeneity on hydrogen storage performance.

36 MATERIALS SCIENCE↗

Solid-state synthesis of UV-plasmonic Cr2N nanoparticles

Materials that exhibit plasmonic response in the UV region can be advantageous for many applications, such as biological photodegradation, photocatalysis, disinfection, and bioimaging. Transition metal nitrides have recently emerged as chemically and thermally stable alternatives to metal-based plasmonic materials. However, most free-standing nitride nanostructures explored so far have plasmonic responses in the visible and near-IR regions. Herein, we report the synthesis of UV-plasmonic Cr2N nanoparticles using a solid-state nitridation reaction. The nanoparticles had an average diameter of 9 ± 5 nm and a positively charged surface that yields stable colloidal suspension. The particles were composed of a crystalline nitride core and an amorphous oxide/oxynitride shell whose thickness varied between 1 and 7 nm. Calculations performed using the finite element method predicted the localized surface plasmon resonance (LSPR) for these nanoparticles to be in the UV-C region (100–280 nm). While a distinctive LSPR peak could not be observed using absorbance measurements, low-loss electron energy loss spectroscopy showed the presence of surface plasmons between 80 and 250 nm (or ∼5 to 15 eV) and bulk plasmons centered around 50–62 nm (or ∼20 to 25 eV). Plasmonic coupling was also observed between the nanoparticles, resulting in resonances between 250 and 400 nm (or ∼2.5 to 5 eV).

Chemistry↗

Computer program to perform cost and weight analysis of transport aircraft. Volume 1: Summary

A digital computer program for evaluating the weight and costs of advanced transport designs was developed. The resultant program, intended for use at the preliminary design level, incorporates both batch mode and interactive graphics run capability. The basis of the weight and cost estimation method developed is a unique way of predicting the physical design of each detail part of a vehicle structure at a time when only configuration concept drawings are available. In addition, the technique relies on methods to predict the precise manufacturing processes and the associated material required to produce each detail part. Weight data are generated in four areas of the program. Overall vehicle system weights are derived on a statistical basis as part of the vehicle sizing process. Theoretical weights, actual weights, and the weight of the raw material to be purchased are derived as part of the structural synthesis and part definition processes based on the computed part geometry.

Source record↗