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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Energy Migration Processes in Re(I) MLCT Complexes Featuring a Chromophoric Ancillary Ligand

We present herein the synthesis, structural characterization, electronic structure calculations, and ultrafast and supra-nanosecond photophysical properties of a series of five Re(I) bichromophores exhibiting metal to ligand charge transfer (MLCT) excited states based on the general formula fac -[Re(N ^ N)(CO) 3 (PNI-py)]PF 6, where PNI-py is 4-piperidinyl-1,8-naphthalimidepyridine and N ^ N is a diimine ligand ( Re1 – 5 ), along with their corresponding model chromophores where 4-ethylpyridine was substituted for PNI-py ( Mod1 – 5 ). The diimine ligands used include 1,10-phenanthroline (phen, 1 ), 2,9-dimethyl-4,7-diphenyl-1,10-phenanthroline (bcp, 2 ), 4,4'-di- tert -butyl-2,2'-bipyridine (dtbb, 3 ), 4,4'-diethyl ester-2,2'-bipyridine (deeb, 4 ), and 2,2'-biquinoline (biq, 5 ). In these metal–organic bichromophores, structural modification of the diimine ligand resulted in substantial changes to the observed energy transfer efficiencies between the two chromophores as a result of the variation in 3 MLCT excited-state energies. The photophysical properties and energetic pathways of the model chromophores were explored in parallel to accurately track the changes that arose from introduction of the organic chromophore pendant on the ancillary ligand. All relevant photophysical and energy transfer processes were probed and characterized using time-resolved photoluminescence spectroscopy, ultrafast and nanosecond transient absorption spectroscopy, and time-dependent density functional theory calculations. Of the five bichromophores in this study, four ( Re1 – 4 ) exhibited a thermal equilibrium between the 3 PNI-py and the 3 MLCT excited state, drastically extending the lifetimes of the parent model chromophores.

14 SOLAR ENERGY↗
DOE OSTI2021

Synthesis and thermodynamics of uranium-incorporated α-Fe 2 O 3 nanoparticles

Hematite nanoparticles were synthesized with U(VI) in circumneutral water through a coprecipitation and hydrothermal treatment process. XRD, TEM, and EXAFS analyses reveal that uranium may aggregate along grain boundaries and occupy Fe sites within hematite. The described synthesis method produces crystalline, single-phase iron oxide nanoparticles absent of surface-bound uranyl complexes. EXAFS data were comparable to spectra from existing studies whose syntheses were more representative of naturally occurring, extended aging processes. Herein this work provides and validates an accelerated method of synthesizing uranium-immobilized iron oxide nanoparticles for further mechanistic studies. High temperature oxide melt solution calorimetry measurements were performed to calculate the thermodynamic stability of uranium-incorporated iron oxide nanoparticles. Increasing uranium content within hematite resulted in more positive formation enthalpies. Standard formation enthalpies of U x Fe 2–2x O 3 were as high as 76.88 ± 2.83 kJ/mol relative to their binary oxides, or -764.04 ± 3.74 kJ/mol relative to their constituent elements, at x = 0.037. Data on the thermodynamic stability of uranium retention pathways may assist in predicting waste uranyl remobilization, as well as in developing more effective methods to retain uranium captured from aqueous environments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Characterization of the thermophilic xylanase Fsa02490Xyn from the hyperthermophile Fervidibacter sacchari belonging to glycoside hydrolase family 10

Fervidibacter sacchari is an aerobic hyperthermophile belonging to the phylum Armatimonadota that degrades a variety of polysaccharides. Its genome encodes 117 enzymes with one or more annotated glycoside hydrolase (GH) domain, but the roles of these putative GHs in polysaccharide catabolism are poorly defined. Here, we describe one F. sacchari enzyme encoding a GH10 domain, Fsa02490Xyn, that was previously shown to be active on Miscanthus, oat β-glucan, and beech-wood xylan, with optimal activity at 90-100 °C. We show that Fsa02490Xyn is also active on birch-wood xylan and gellan gum. The pH range on beech-wood xylan was 4.5 to 9.5 (pHopt 7.0-8.0). Fsa024940Xyn had a Km of 2.375 mm, Vmax of 1250 μm·min-1, and kcat/Km of 1.259 × 104 s-1·m-1 when using a para-nitrophenyl-?-xylobioside assay. A phylogenetic analysis of GH10 family enzymes revealed a large clade of enzymes from diverse members of the class Fervidibacteria, including Fsa02490Xyn and a second enzyme from F. sacchari, with apparent horizontal gene transfer within Fervidibacteria and between Fervidibacteria and thermophilic Bacillota. This study establishes Fsa02490Xyn as a hyperthermophilic GH10 enzyme with endo-β-1,4-xylanase activity and identifies a large clade of homologous GH10 enzymes within the class Fervidibacteria. Impact statement The depolymerization of xylan at high temperatures is important because this process limits the degradation of polysaccharides in nature and the synthesis of biofuels from plant wastes. Our study is also important because F. sacchari is one of only a few cultivated members of the Armatimonadota, which are polysaccharide-degradation specialists.

Armatimonadota↗
DOE OSTI2023

High-Throughput Automated Exploration of Phase Growth Behaviors in Quasi-2D Formamidinium Metal Halide Perovskites

Quasi-2D metal halide perovskites (MHPs) are an emerging material platform for sustainable functional optoelectronics, but the uncontrollable, broad phase distribution remains a critical challenge for applications. Nevertheless, the basic principles for controlling phases in quasi-2D MHPs remain poorly understood, due to the rapid crystallization kinetics during the conventional thin-film fabrication process. In this work, a high-throughput automated synthesis-characterization-analysis workflow is implemented to accelerate material exploration in formamidinium (FA)-based quasi-2D MHP compositional space, revealing the early-stage phase growth behaviors fundamentally determining the phase distributions. Upon comprehensive exploration with varying synthesis conditions including 2D:3D composition ratios, antisolvent injection rates, and temperatures in an automated synthesis-characterization platform, it is observed that the prominent n = 2 2D phase restricts the growth kinetics of 3D-like phases—α-FAPbI 3 MHPs with spacer-coordinated surface—across the MHP compositions. Thermal annealing is a critical step for proper phase growth, although it can lead to the emergence of unwanted local PbI 2 crystallites. Additionally, fundamental insights into the precursor chemistry associated with spacer-solvent interaction determining the quasi-2D MHP morphologies and microstructures are demonstrated. The high-throughput study provides comprehensive insights into the fundamental principles in quasi-2D MHP phase control, enabling new control of the functionalities in complex materials systems for sustainable device applications.

2D perovskites↗
DOE OSTI2024

Light–Material Interactions Using Laser and Flash Sources for Energy Conversion and Storage Applications

Abstract This review provides a comprehensive overview of the progress in light–material interactions (LMIs), focusing on lasers and flash lights for energy conversion and storage applications. We discuss intricate LMI parameters such as light sources, interaction time, and fluence to elucidate their importance in material processing. In addition, this study covers various light-induced photothermal and photochemical processes ranging from melting, crystallization, and ablation to doping and synthesis, which are essential for developing energy materials and devices. Finally, we present extensive energy conversion and storage applications demonstrated by LMI technologies, including energy harvesters, sensors, capacitors, and batteries. Despite the several challenges associated with LMIs, such as complex mechanisms, and high-degrees of freedom, we believe that substantial contributions and potential for the commercialization of future energy systems can be achieved by advancing optical technologies through comprehensive academic research and multidisciplinary collaborations.

Materials Science↗
DOE OSTI2020

Multifunctional transition metal doped titanium dioxide reduced graphene oxide composites as highly efficient adsorbents and photocatalysts

A series of novel, mesoporous transition metal doped titanium dioxide-reduced graphene oxide composites are synthesized where the dopants were Mn, Co, Ni, Mo, and W. An in-situ synthesis method was used which involves a green, economic, hydrothermal process which can be scaled up easily. The composites show high surface areas (165–245 m 2 /g) and monomodal pore size distributions with average pore diameters in the range of 3–5 nm. The homogeneous distributions of the dopants are seen in SEM-EDX mapping data. The indirect band gaps of the composite materials are in the range of 2.20–2.48 eV. The composites show excellent dye adsorption activities where 100% adsorption of Rhodamine B occurs within 5 min when Mo–TiO 2 /rGO composite is used. Furthermore, the adsorbed dye can either be desorbed or photocatalytically degraded and the composite is reusable up to 10 cycles without losing significant activity. Mo–TiO 2 /rGO composite showed excellent adsorption of both cationic and anionic dyes at neutral pH.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Design, Synthesis, and Characterization of Polymer Precursors to Li x PON and Li x SiPON Glasses: Materials That Enable All-Solid-State Batteries (ASBs)

LiPON-like glasses that form lithium dendrite impenetrable interfaces between lithium battery components are enabling materials that may replace liquid electrolytes permitting production of all-solid-state batteries (ASBs). Unfortunately, to date, such materials are introduced only via gas-phase deposition. Furthermore, we demonstrate the design and synthesis of easily scaled, lowtemperature, low-cost, solution-processable inorganic polymers containing LiPON/LiSiPON elements. OPCl 3 and hexachlorophosphazene [Cl 2 P=N] 3 provide starting points for elaboration using MNH 2 (M = Li/Na) or (Me 3 Si)NH followed by reaction with controlled amounts of LiNH 2 to produce oligomers/polymers with molecular weights (MWs) ≈1–2 kDa characterized by multinuclear NMR, gel permeation chromatography (GPC), thermogravimetric analysis (TGA), Fourier-transform infrared (FTIR), X-ray powder diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and matrix-assisted laser desorption/ ionization (MALDI)-time-of-flight (ToF) offering stabilities to 150–200 °C and ceramic yields (800 °C) of 50–60%. 7 Li NMR suggests that precursor-bound Li + dissociates easily, beneficial for electrochemical applications. XPS shows higher N/P ratios (1–3) than via gas-phase methods (<1) correlating N/P ratios, 7 Li shifts, and Li + conductivities. Li 2 SiPHN offers the highest ambient conductivity of 3 × 10 –1 mS cm –1 at 400 °C/2 h/N 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2020

Engineering unsymmetrically coordinated Cu-S 1 N 3 single atom sites with enhanced oxygen reduction activity

Atomic interface regulation is thought to be an efficient method to adjust the performance of single atom catalysts. Herein, a practical strategy was reported to rationally design single copper atoms coordinated with both sulfur and nitrogen atoms in metal-organic framework derived hierarchically porous carbon (S-Cu-ISA/SNC). The atomic interface configuration of the copper site in S-Cu-ISA/SNC is detected to be an unsymmetrically arranged Cu-S 1 N 3 moiety. The catalyst exhibits excellent oxygen reduction reaction activity with a half-wave potential of 0.918 V vs. RHE. Additionally, through in situ X-ray absorption fine structure tests, we discover that the low-valent Cuprous-S 1 N 3 moiety acts as an active center during the oxygen reduction process. Our discovery provides a universal scheme for the controllable synthesis and performance regulation of single metal atom catalysts toward energy applications.

25 ENERGY STORAGE↗
DOE OSTI2021

Wavy graphene sheets from electrochemical sewing of corannulene

A bottom-up synthesis of wavy graphene structures obtained through an anodic polymerization process, combined with an electrochemically triggered oxidative cyclodehydrogenation, of the bowl-shaped polyaromatic hydrocarbon corannulene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Utilization of machine learning to accelerate colloidal synthesis and discovery

Machine learning techniques are seeing increased usage for predicting new materials with targeted properties. However, widespread adoption of these techniques is hindered by the relatively greater experimental efforts required to test the predictions. Furthermore, because failed synthesis pathways are rarely communicated, it is difficult to find prior datasets that are sufficient for modeling. This work presents a closed-loop machine learning-based strategy for colloidal synthesis of nanoparticles, assuming no prior knowledge of the synthetic process, in order to show that synthetic discovery can be accelerated despite limited data availability.

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

Measurement of the Ne 18 ( α , p ) Na 21 reaction with the ANASEN active-target detector system at E c . m . = 2.5 – 4 MeV

The 18 Ne(α,p) 21 Na reaction plays a significant role in Type-I X-ray bursts. It is a major path in the breakout from the hot-CNO cycles to the synthesis of heavier elements in the αp- and rp-processes. An experiment to determine the cross section of this reaction was performed with the ANASEN active-target detector system, determining the cross section at energies between 2.5 and 4 MeV in the center-of-mass frame. The measured cross sections for reactions populating the ground state in 21 Na are consistent with results obtained from the time-inverse reaction, but significantly lower than the previously published experimental data of direct measurements. The total cross sections are also compared with those derived from indirect methods and statistical-model calculations. Furthermore, this experiment establishes a new experimental data set on the excitation function of the 18 Ne(α,p) 21 Na reaction, revealing the significance of the excited states' contributions to the total reaction cross section and allowing us to separate the contribution of the (α,2p) reaction. The impact of the measured cross section on thermal reaction rates is discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

α -cluster microscopic study of C 12 + C 12 fusion toward the zero energy limit

The carbon burning process is a fundamental step of stellar evolution and governs the synthesis of chemical elements important for the formation of life. In this work, we utilize the microscopic hybrid α cluster (HαC) model and an analytical approach, both in the framework of the Imaginary Time Method (ITM), to study the carbon fusion reaction towards zero energy. We obtain the values of the cross sections, astrophysical factors and correlate our results to collective motion. We also include a calculation for the 2 + carbon fusion and discuss a possible experimental investigation. Our results confirm direct experimental and theoretical results close to the barrier, while suggest possible 2 + mixtures in the indirect experimental data. Furthermore, our study offers an accurate view of the burning process in the somewhat unexplored low energy region.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Uncertainty quantification of mass models using ensemble Bayesian model averaging

Developments in the description of the masses of atomic nuclei have led to various nuclear mass models that provide predictions for masses across the whole chart of nuclides. These mass models play an important role in understanding the synthesis of heavy elements in the rapid neutron capture ( r ) process. However, it is still a challenging task to estimate the size of uncertainty associated with the predictions of each mass model. In this work, a method called ensemble Bayesian model averaging (EBMA) is introduced to quantify the uncertainty of one-neutron separation energies (S 1 n ) which are directly relevant in the calculations of r -process observables. Here, this Bayesian method provides a natural way to perform model averaging, selection, and uncertainty quantification, by combining the mass models as a mixture of normal distributions whose parameters are optimized against the experimental data, employing the Markov chain Monte Carlo method using the no-u-turn sampler. The EBMA model optimized with all the experimental S 1 n from the AME2003 nuclides are shown to provide reliable uncertainty estimates when tested with the new data in the AME2020.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

wa-hls4ml: A Benchmark and Surrogate Models for hls4ml Resource and Latency Estimation

As machine learning (ML) is increasingly implemented in hardware to address real-time challenges in scientific applications, the development of advanced toolchains has significantly reduced the time required to iterate on various designs. These advancements have solved major obstacles, but also exposed new challenges. For example, processes that were not previously considered bottlenecks, such as hardware synthesis, are becoming limiting factors in the rapid iteration of designs. To mitigate these emerging constraints, multiple efforts have been undertaken to develop an ML-based surrogate model that estimates resource usage of ML accelerator architectures. We introduce wa-hls4ml, a benchmark for ML accelerator resource and latency estimation, and its corresponding initial dataset of over 680,000 fully connected and convolutional neural networks, all synthesized using hls4ml and targeting Xilinx FPGAs. The benchmark evaluates the performance of resource and latency predictors against several common ML model architectures, primarily originating from scientific domains, as exemplar models, and the average performance across a subset of the dataset. Additionally, we introduce GNN- and transformer-based surrogate models that predict latency and resources for ML accelerators. We present the architecture and performance of the models and find that the models generally predict latency and resources for the 75% percentile within several percent of the synthesized resources on the synthetic test dataset.

Hawks, Benjamin [Fermilab] (ORCID:0000000157000288↗
DOE OSTI2020

Advancing the Physics of Magnetized Dusty Plasmas (Collaborative Research Final Report)

Dusty (or complex) plasmas are four-component systems consisting of the usual plasma constituents of electrons, ions, and neutral atoms with the addition of a third charged component - nanometer to micrometer sized solid particulates; i.e., "dust". The study of magnetized dusty plasmas is grounded in important questions that are relevant to space, astrophysical, and also technological plasmas and therefore have the potential to make a societal impact. The formation and control of nanometer-sized particles in industrial plasma processes is currently being exploited as a technique to induce the formation of nanocrystals on material surfaces. For example, when combined with magnetron sources, these are important processes that could lead to improved techniques for customizing material synthesis. The interaction between the edge plasma and walls of magnetic confinement fusion devices is a source of particulate material that can be transported throughout the plasma with potentially detrimental effects on plasma performance. Understanding the formation, transport, and destruction of these "dust" particles is of critical importance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Low Cost High Efficiency Photovoltaics Using Semiconductor Nanocrystals: Cooperative Research and Development CRADA Number CRD-15-00598 (Final Report)

Collaboration will occur between NREL and KIMM in the area of semiconductor nanocrystals for use in advanced solar photon energy conversion strategies. The project takes advantage of the unique capabilities and expertise regarding the incorporation of quantum dots (QD) into solar energy technologies that are available at NREL within the BES-funded programs. KIMM has unique expertise in the synthesis of new types of nanocrystals as well as advanced processes for solution processing.

14 SOLAR ENERGY↗
DOE OSTI2023

Additive Manufacturing of Ultrahigh Temperature Refractory Metal Alloys

The project advances the manufacture of RMA for ultrahigh-temperature service with three main innovations: a thermodynamically derived high-throughput AM synthesis and characterization using reactive synthesis of elemental powders, a new dimensional number to predict processing parameters, and a novel processing scheme for the fabrication of components with functional grading microstructures. With these advances, the project demonstrates in Phase I the manufacture of RMAs exhibiting room temperature compression ductility above 20%, room temperature fracture toughness above 10 MPam 0.5 , and the fabrication of tensile test samples that have a transformative impact on the manufacturing of RMAs by enabling cost-efficient and large-scale fabrication of components.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

wa-hls4ml and lui-gnn: A benchmark and GNN-based surrogate model for hls4ml resource and latency estimation

As machine learning (ML) increasingly serves as a tool for addressing real-time challenges in scientific applications, the development of advanced tooling has significantly reduced the time required to iterate on various designs. These advancements have solved major obstacles, but also exposed new challenges. For example, processes that were not previously considered bottlenecks, such as model synthesis, are now becoming limiting factors in the rapid iteration of designs. To reduce these emerging constraints, multiple efforts are being launched toward designing an ML-based surrogate model that estimates resource usage of synthesized accelerator architectures. This model would reduce the design iteration time, especially when designing within a set of given hardware constraints. This approach shows considerable potential, but as it stands, the effort is early and would benefit from coordination and standardization to assist future work as it emerges. We introduce wa-hls4ml, a benchmark for ML accelerator resource and latency estimation, and its corresponding initial dataset of more than 100,000 fully connected neural networks, all synthesized using hls4ml and targeting Xilinx FPGAs. In addition to the resource utilization and latency data provided, the dataset includes generated artifacts and log files for many of the synthesized neural networks, in order to support future research in ML-based code generation. The benchmark evaluates the performance of resource and latency predictors against several common ML model architectures, primarily originating from scientific domains, as exemplar models, as well as the average performance across a subset of the dataset. We measure the performance of a given predictor model through multiple metrics, including $R^2$ score and SMAPE on regression tasks, as well as inference time to further characterize the estimator under test. Additionally, we introduce the latency/utilization inference graph neural network (lui-gnn), a surrogate model that uses a graph neural network to represent input architectures in the form of a directed graph. This graph representation allows for a diverse set of model architectures to all be effectively handled by a surrogate model. We present the architecture and performance of the model, as evaluated by the new proposed benchmark, including SMAPE, $R^2$ score, and inference times, and find that lui-gnn generally predicts latency and utilization for the 75\% quantile within several percent of the synthesized resources on the synthetic test dataset, indicating that this approach of estimating resource and latency via a surrogate models has promise and warrants further research.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗