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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Nano Scale Poly(vinylidene chloride-co-acrylonitrile) Protection for Reversible and Stable Mg Anode Interface

This study investigates the efficacy of a polymer coating, PVdC-co-AN, in enhancing the stability and reversibility of the electrochemical Mg anode interface. Coated electrodes, immersed in a 0.25 M Mg(TFSI) 2 −0.50 M MgCl 2 /dimethoxyethane (DME) electrolyte, exhibit notable improvements. Cyclic voltammetry demonstrates consistent behavior with the coated electrode, while the uncoated electrode changes dramatically. During extended open circuit potential conditions, the coated electrode maintains much higher coulombic efficiency (93%) compared to the uncoated electrode (62%). Galvanostatic cycling test over 200 cycles further show the benefits of the PVdC-co-AN coating, decreasing the overpotential of Mg plating and improving long-term stability. The coated electrodes also demonstrate improved rate capability at higher current densities. Surface analysis reveals differences in the formation of byproducts between the coated and uncoated electrodes, indicating a more stable and uniform interface in the former. Nuclear magnetic resonance (NMR) spectroscopy suggests that the polymer influences ion mobility through tuning the solvation environments which results in better kinetics and fewer byproducts. In summary, the study affirms that the PVdC-co-AN coating significantly improves the stability and performance of Mg electrochemistry, offering a promising advancement for practical battery applications.

25 ENERGY STORAGE↗
DOE OSTI2025

Post-DTL Beam Delivery

Ensuring that the beam delivered from the upgraded Front-End (FE) meets the Key Performance Parameters (KPPs) at each user facility is critical to the success of the LANSCE Accelerator Modernization Project (LAMP). For a high-intensity, multi-user facility like LANSCE, compliance with beam loss and radiation thresholds is as important as the charge delivered to each target. While early LAMPF/LANSCE operations relied on iterative tuning to minimize losses from beam halo and tail particles, the new FE may introduce different beam distributions and loss modes—making predictive modeling essential. To manage this, the F2E (Front-End to End) effort is developing detailed particle-tracking models that reflect realistic beamline conditions, including halo formation and expected diagnostic readings. These "snapshot" simulations aim to benchmark live machine performance at a given moment. This will help quantify how beam quality from the new FE will propagate downstream through the facility. Only by validating these models can we confidently assess and mitigate the potential impacts of the LAMP FE on beam delivery. Post-DTL, the beam splits to serve five major user facilities. Historically, low-energy beam transport has been modeled using TRACE, and higher-energy sections with TRANSPORT. These have now been unified into MAD-X format and validated with codes such as Elegant, pyOrbit, XSuite, Impact-Z, and HPSim. The primary focus now is on accurate modeling of full particle distributions (including beam halo) as they traverse the accelerator and beamlines to each experimental station. All models are at various stages of validation with empirical data.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

History Matching and Performance Prediction of a Polymer Flood Pilot in Heavy Oil Reservoir on Alaska North Slope

The first-ever polymer flood pilot to enhance heavy oil recovery on Alaska North Slope (ANS) is ongoing. After more than 2.5 years of polymer injection, significant benefit has been observed from the decrease in water cut from 65% to less than 15% in the project producers. The primary objective of this study is to develop a robust history-matched reservoir simulation model capable of predicting future polymer flood performance. In this work, the reservoir simulation model has been developed based on the geological model and available reservoir and fluid data. In particular, four high transmissibility strips were introduced to connect the injector-producer well pairs, simulating short-circuiting flow behavior that can be explained by viscous fingering and reproducing the water cut history. The strip transmissibilities were manually tuned to improve the history matching results during the waterflooding and polymer flooding periods, respectively. It has been found that higher strip transmissibilities match the sharp water cut increase very well in the waterflooding period. Then the strip transmissibilities need to be reduced with time to match the significant water cut reduction. The viscous fingering effect in the reservoir during waterflooding and the restoration of injection conformance during polymer flooding have been effectively represented. Based on the validated simulation model, numerical simulation tests have been conducted to investigate the oil recovery performance under different development strategies, with consideration for sensitivity to polymer parameter uncertainties. The oil recovery factor with polymer flooding can reach about 39% in 30 years, twice as much as forecasted with continued waterflooding. Besides, the updated reservoir model has been successfully employed to forecast polymer utilization, a valuable parameter to evaluate the pilot test’s economic efficiency. All the investigated development strategies indicate polymer utilization lower than 3.5 lbs/bbl in 30 years, which is economically attractive.

Wang, Xindan↗
DOE OSTI2023

Enhanced thermoelectric performance of SnSe by controlled vacancy population

Abstract The thermoelectric performance of SnSe strongly depends on its low-energy electron band structure that provides high density of states in a narrow energy window due to the multi-valley valence band maximum (VBM). Angle-resolved photoemission spectroscopy measurements, in conjunction with first-principles calculations, reveal that the binding energy of the VBM of SnSe is tuned by the population of Sn vacancy, which is determined by the cooling rate during the sample growth. The VBM shift follows precisely the behavior of the thermoelectric power factor, while the effective mass is barely modified upon changing the population of Sn vacancies. These findings indicate that the low-energy electron band structure is closely correlated with the high thermoelectric performance of hole-doped SnSe, providing a viable route toward engineering the intrinsic defect-induced thermoelectric performance via the sample growth condition without an additional ex-situ process. Graphical Abstract

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Controlling Exsolution Dynamics in High‐Entropy Oxides for Highly Active and Selective Acetylene Semi‐Hydrogenation

Exsolution-derived catalysts feature robust metal–support interactions that enhance catalytic performance; yet achieving precise control over exsolution dynamics in multicomponent oxides remains challenging. In this study, we demonstrate that exsolution behavior in high-entropy oxides (HEOs) can be rationally tuned through coupled lattice- and valence-engineering to create a highly active and selective catalyst for acetylene semi-hydrogenation. Incorporation of Li + into a rock salt-structured HEO (LiNiMgCuZnCoO x and LiHEO) induces local lattice distortion, generates oxygen vacancies, and partially oxidizes Co sites from Co 2+ to Co 3+ , collectively modulating local charge redistribution. This strategy enables facilitated Cu nanoparticle exsolution and alters the exsolution sequence from Cu 0 > Ni 0 > Co 0 in pristine HEO to Cu 0 > Co 0 > Ni 0 in the LiHEO. The resulting catalyst via controlled exsolution exhibits superior activity and ethylene selectivity, outperforming state-of-the-art transition metal systems. This work establishes entropy-enabled lattice and valence engineering as a facile route to programmable exsolution for enhanced catalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Validation of a Tapered Impact Damper for Traffic Signal Structure Vibrations Using the Method of Harmonic Balance

Significant vibration amplitudes and cycles can be produced when traffic signal structures with low inherent damping are excited near one of their natural frequencies. For the mitigation of wind-induced vibrations, dynamic vibration absorbers coupled to the structure are often used. Here, this research investigates the performance of a tapered impact damper, consisting of a hanging spring-mass oscillator inside a housing capable of reducing vibration amplitude over a broader frequency range than the conventional tuned mass damper. A nonlinear, two degree-of-freedom model is developed with coordinates representing the traffic structure and the tapered impact damper. This research focuses on the application of the harmonic balance method to approximate the periodic solutions of the nonlinear equations to compute the nonlinear dynamics of the damped traffic signal structure. After designing and manufacturing a tapered impact damper, the traffic signal structure is tested with and without the damper using free vibration snapback tests. The experimental frequency and damping backbone curves are used to validate the analytical model, and the effectiveness of the damper is discussed.

42 ENGINEERING↗
DOE OSTI2022

Material processing, microstructure, and composite properties of low carbon Engineered Cementitious Composites (ECC)

Traditional PVA fiber-reinforced Engineered Cementitious Composites (ECC) show high tensile ductility and superior durability with tight crack width, but the high cost and embodied carbon can hinder its wider application in infrastructures. The objective of this study is to develop a better understanding of the fresh and hardened properties of an ECC that employs a lower embodied-carbon binder, Limestone Calcined Clay Cement (LC3), and lower-cost PP fiber that is widely available. Specifically, the interrelations between material processing, microstructure, and composite properties were studied experimentally. The results showed that ECC with high tensile ductility up to 9% tensile strain and tight crack width with 50 μm at 2% tensile strain can be achieved. It was found that a matrix paste with higher viscosity generally enhanced fiber dispersion uniformity and robustness in tensile strain-hardening. The paste viscosity is increased when OPC is replaced by LC3 and can be tuned with superplasticizer content. Larger maximum flaw size leads to lower first crack strength, beneficial for microcrack initiation and multiple cracking. This study generates fundamental knowledge linking processing-microstructure-performance of PP-LC3-ECC. This class of low embodied carbon ECC with tight crack width is expected to contribute to reducing the carbon footprint of the built environment.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Fluorination Enables Simultaneous Improvements of a Dialkoxybenzene-Based Redoxmer for Nonaqueous Redox Flow Batteries

Redoxmers or redox-active organic materials, arc one critical component for nonaqueous redox flow batteries (RFBs), which hold high promise in enabling the time domain of the grid. While tuning redox potentials of redoxmers is a very effective way to enhance energy densities of NRFBs, those improvements often accompany accelerated kinetics of the charged species, undermining stability and cycling performance. In this paper, a strategy for designing redoxmers with simultaneous improvements in redox potential and stability is proposed. Specifically, the redoxmer 1,4-di-tert-butyl-2,5-bis(2,2,2-trifluoroethoxy)benzene (ANL-C46) is developed by incorporating fluorinated substitutions into the dialkoxybenzene-based platform. Compared to the non-fluorinated analogue, ANL-C46 demonstrates not only an increased (similar to 0.41 V) redox potential but also much enhanced stability (1.6 times) and cyclability (4 times) evidenced by electron paramagnetic resonance kinetic study, H-cell and flow cell cycling. In fact, the cycling performance of ANL-C46 is among the best of high potential (>1.0 V vs Ag/Ag + ) redoxmers ever reported. Density functional theory calculations suggest that while the introduced fluorine substitutions elevate the redox potentials, they also help to depress the decomposition reactions of the charged redoxmers, affording excellent stability. The findings represent an interesting strategy for simultaneously improving energy density and stability, which could further prompt the development of high-performance redoxmers.

25 ENERGY STORAGE↗
DOE OSTI2022

Impact of Molecular Design on Degradation Lifetimes of Degradable Imine-Based Semiconducting Polymers

Transient electronics are a rapidly emerging field due to their potential applications in the environment and human health. Recently, a few studies have incorporated acid-labile imine bonds into polymer semiconductors to impart transience; however, understanding of the structure–degradation property relationships of these polymers is limited. In this work, we systematically design and characterize a series of fully degradable diketopyrrolopyrrole-based polymers with engineered sidechains to investigate the impact of several molecular design parameters on the degradation lifetimes of these polymers. By monitoring degradation kinetics via ultraviolet–visible spectroscopy, we reveal that polymer degradation in solution is aggregation-dependent based on the branching point and M n , with accelerated degradation rates facilitated by decreasing aggregation. Additionally, increasing the hydrophilicity of the polymers promotes water diffusion and therefore acid hydrolysis of the imine bonds along the polymer backbone. The aggregation properties and degradation lifetimes of these polymers rely heavily on solvent, with polymers in chlorobenzene taking six times as long to degrade as in chloroform. We develop a new method for quantifying the degradation of polymers in the thin film and observe that similar factors and considerations (e.g., interchain order, crystallite size, and hydrophilicity) used for designing high-performance semiconductors impact the degradation of imine-based polymer semiconductors. We found that terpolymerization serves as an attractive approach for achieving degradable semiconductors with both good charge transport and tuned degradation properties. This study provides crucial principles for the molecular design of degradable semiconducting polymers, and we anticipate that these findings will expedite progress toward transient electronics with controlled lifetimes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Entropy Stabilization Effects and Ion Migration in 3D “Hollow” Halide Perovskites

A recently discovered new family of 3D halide perovskites with the general formula (A) 1–x (en) x (Pb) 1–0.7x (X) 3–0.4x (A = MA, FA; X = Br, I; MA = methylammonium, FA = formamidinium, en = ethylenediammonium) is referred to as “hollow” perovskites owing to extensive Pb and X vacancies created on incorporation of en cations in the 3D network. The “hollow” motif allows fine tuning of optical, electronic, and transport properties and bestowing good environmental stability proportional to en loading. To shed light on the origin of the apparent stability of these materials, we performed detailed thermochemical studies, using room temperature solution calorimetry combined with density functional theory simulations on three different families of “hollow” perovskites namely en/FAPbI 3 , en/MAPbI 3 , and en/FAPbBr 3 . We found that the bromide perovskites are more energetically stable compared to iodide perovskites in the FA-based hollow compounds, as shown by the measured enthalpies of formation and the calculated formation energies. The least stable FAPbI 3 gains stability on incorporation of the en cation, whereas FAPbBr 3 becomes less stable with en loading. This behavior is attributed to the difference in the 3D cage size in the bromide and iodide perovskites. Configurational entropy, which arises from randomly distributed cation and anion vacancies, plays a significant role in stabilizing these “hollow” perovskite structures despite small differences in their formation enthalpies. With the increased vacancy defect population, we have also examined halide ion migration in the FA-based “hollow” perovskites and found that the migration energy barriers become smaller with the increasing en content.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Atomic Layers of B2 CuPd on Cu Nanocubes as Catalysts for Selective Hydrogenation

The search for highly active and selective catalysts with high precious metal atom utilization efficiency has attracted increasing interest in both the fundamental synthesis of materials and important industrial reactions. Here, in this work, we report the synthesis of Pd–Cu nanocubes with a Cu core and an ordered B2 intermetallic CuPd shell with controllable atomic layers on the surface (denoted as Cu/B2 CuPd), which can efficiently and robustly catalyze the selective hydrogenation of acetylene (C 2 H 2 ) to ethylene (C 2 H 4 ) under mild conditions. The optimized Cu/B2 CuPd with a Pd loading of 9.5 at. % exhibited outstanding performance in the C 2 H 2 semi-hydrogenation with 100% C 2 H 2 conversion and 95.2% C 2 H 4 selectivity at 90 °C. We attributed this outstanding performance to the core/shell structure with a high surface density of active Pd sites isolated by Cu in the B2 intermetallic matrix, representing a structural motif of single-atom alloys (SAAs) on the surface. The combined experimental and computational studies further revealed that the electronic states of Pd and Cu are modulated by SAAs from the synergistic effect between Pd and Cu, leading to enhanced performance compared with pristine Pd and Cu catalysts. This study provides a new synthetic methodology for making single-atom catalysts with high precious metal atom utilization efficiency, enabling simultaneous tuning of both geometric and electronic structures of Pd active sites for enhanced catalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Cation-doped ZnS catalysts for polysulfide conversion in lithium–sulfur batteries

Catalytic conversion of polysulfides is regarded as a crucial approach to enhancing kinetics and suppressing the shuttle effect in lithium-sulfur (Li-S) batteries. However, the activity prediction of Li-S catalysts remains elusive owing to the lack of mechanistic understanding of activity descriptors. Here, we report a volcano-shaped relationship between polysulfide adsorption ability and catalytic activity. In conjunction with theoretical analysis, we distinguish catalytic and anchoring effects to delineate the role of adsorption and emphasize the passivation of catalysts. These findings enable us to develop a composite catalyst, Co0.125Zn0.875S, which shows higher performance than simple binary compounds. Such a fundamental understanding of the intrinsic link between polysulfide adsorption and catalytic activity offers a rational viewpoint for designing Li-S catalysts and tuning their activities.

Shen, Zihan↗
DOE OSTI2025

GIScience in the era of Artificial Intelligence: a research agenda towards Autonomous GIS

The advent of generative AI exemplified by large language models (LLMs) opens new ways to represent and compute geographic information and transcends the process of geographic knowledge production, driving geographic information systems (GIS) towards autonomous GIS. Leveraging LLMs as the decision core, autonomous GIS can independently generate and execute geoprocessing workflows to perform spatial analysis. In this vision paper, we further elaborate on the concept of autonomous GIS and present a conceptual framework that defines its five autonomous goals, five levels of autonomy, five core functions, and three operational scales. We demonstrate how autonomous GIS could perform geospatial data retrieval, spatial analysis, and map making with four proof-of-concept GIS agents. We conclude by identifying critical challenges and future research directions, including fine-tuning and self-growing decision-cores, autonomous modelling, and examining the societal and practical implications of autonomous GIS. By establishing the groundwork for a paradigm shift in GIScience, this paper envisions a future where GIS moves beyond traditional workflows to autonomously reason, derive, innovate, and advance geospatial solutions to pressing global challenges. Meanwhile, we emphasize that as we design and deploy increasingly intelligent geospatial systems, we carry a responsibility to ensure they are developed in socially responsible ways, serve the public good, and support the continued value of human geographic insight in an AI-augmented future.

Autonomous GI↗
DOE OSTI2021

Optimization and supervised machine learning methods for fitting numerical physics models without derivatives

Here, we address the calibration of a computationally expensive nuclear physics model for which derivative information with respect to the fit parameters is not readily available. Of particular interest is the performance of optimization-based training algorithms when dozens, rather than millions or more, of training data are available and when the expense of the model places limitations on the number of concurrent model evaluations that can be performed. As a case study, we consider the Fayans energy density functional model, which has characteristics similar to many model fitting and calibration problems in nuclear physics. We analyze hyperparameter tuning considerations and variability associated with stochastic optimization algorithms and illustrate considerations for tuning in different computational settings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Optimization of Backscatter and Symmetry for Laser Fusion Experiments Using Multiple Tunable Wavelengths

A new additional wavelength-tuning capability has been implemented on the National Ignition Facility (NIF) laser allowing for unprecedented control of crossed-beam energy transfer (CBET) between all groups of beams for better performance of indirect-drive inertial confinement fusion (ICF) ignition experiments. In particular, this advance allows for negation and reversal of flow-induced CBET and the rebalancing of the intensity of different groups of beams within an indirect-drive (ICF) hohlraum. The experiments conducted at the NIF using a 1.1 MJ laser pulse with peak power of 390 TW demonstrate this high level of control through measurements of the precise changes to stimulated Brillouin scattering, typically driven by flow-induced CBET at the end of the pulse. Additionally, this new capability is shown to be able to predictably control gold-wall plasma expansion in the target driven by early-time flow-induced CBET. Estimates of early-time CBET from the wall expansion are shown to be consistent with simulation expectations. This new additional capability to control symmetry and backscatter expands the design space of current experiments and provides extra margin for increased laser energy in near-future experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

De novo design of drug-binding proteins with predictable binding energy and specificity

The de novo design of small molecule–binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase–1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from <5 nM to low micromolar. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free energy calculations performed directly on the designed models were in excellent agreement with the experimentally measured affinities. We conclude that de novo design of high-affinity small molecule–binding proteins with tuned interaction energies is feasible entirely from computation.

Science & Technology - Other Topics↗
DOE OSTI2022

A Wrapper to Use a Machine-Learning-Based Algorithm for Earthquake Monitoring

Seismology is one of the main sciences used to monitor volcanic activity worldwide. Fast, efficient, and accurate seismicity detectors are crucial to assess the activity level of a volcano in near–real time and to issue timely warnings. Traditional real–time seismic processing software uses phase onset pickers followed by a phase association algorithm to declare an event and estimate its location. The pickers typically do not identify whether the detected phase is a P or S arrival, which can have a negative impact on hypocentral location quality and complicates phase association. We implemented the deep–neural–network–based method PhaseNet to identify in real time P and S seismic waves on data from one– and three–component seismometers. We tuned the Earthworm binder_ew associator module to use the phase identification from PhaseNet to detect and locate the events, which we archive in a SeisComP3 database. We assessed the performance of the algorithm by comparing the results with existing catalogs built to monitor seismic and volcanic activity in Mayotte and the Lesser Antilles region. Our algorithm, which we refer to as PhaseWorm, showed promising results in both contexts and clearly outperformed the previous automatic method implemented in Mayotte. As a result, this innovative real–time processing system is now operational for seismicity monitoring in Mayotte and Martinique.

58 GEOSCIENCES↗
DOE OSTI2020

PIPER: Performance Insight for Programmers and Exascale Runtimes (Final Technical Report)

This project concentrated on the development of novel performance tools and analysis techniques for large scale parallel systems and applications, eventually targeting exascale platforms. Activities conducted included work to novel root cause detection approaches and an auto-tuning framework for parallel systems. The work has led to several software solutions, which are available as open source.

97 MATHEMATICS AND COMPUTING↗