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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Plasmon-induced excitation energy transfer in silver nanoparticle dimers: A real-time TDDFTB investigation

Here, using real-time quantum dynamics calculations, we perform theoretical investigations of light-induced interactions and electronic excitation transfer in a silver nanoparticle dimer. Real-time time-dependent density functional tight-binding (RT-TDDFTB) calculations provide details of the quantum dynamical processes at an electronic/atomistic level with attosecond resolution. The computational efficiency of RT-TDDFTB allows us to examine electronic dynamics up to picosecond time scales. With time scales varying over six orders of magnitude, we provide insight into interactions between the nanoparticle and laser and between nanoparticles. Our results show that the coupling between nanoparticle monomers is dependent on the separation distance between the nanoparticles in the dimer. As the interparticle distance is varied, the dipole–dipole interactions and electronic excitation transfer mechanisms are markedly different. At large distances (from 50 to 20 Å), the energy transfer from NP1 to NP2 becomes more efficient as the interparticle distance decreases. The total dipole moment of the Ag 14 nanoparticle dimer increases linearly at an interparticle distance of 20 Å and reaches its maximum after 1.2 ps. The electronic excitation transfer is also the most efficient at 20 Å. At short distances, back-transfer effects reduce the ability of the dimer and NP1 to accept energy from the incident electric field. We attribute the distance-dependent features of the nanoparticle dimer to the beating between the laser acting on NP1 and the back transfer from NP2 to NP1.

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

Cryo-EM structures of Uba7 reveal the molecular basis for ISG15 activation and E1-E2 thioester transfer

ISG15 plays a crucial role in the innate immune response and has been well-studied due to its antiviral activity and regulation of signal transduction, apoptosis, and autophagy. ISG15 is a ubiquitin-like protein that is activated by an E1 enzyme (Uba7) and transferred to a cognate E2 enzyme (UBE2L6) to form a UBE2L6-ISG15 intermediate that functions with E3 ligases that catalyze conjugation of ISG15 to target proteins. Despite its biological importance, the molecular basis by which Uba7 catalyzes ISG15 activation and transfer to UBE2L6 is unknown as there is no available structure of Uba7. Here, we present cryo-EM structures of human Uba7 in complex with UBE2L6, ISG15 adenylate, and ISG15 thioester intermediate that are poised for catalysis of Uba7-UBE2L6-ISG15 thioester transfer. Our structures reveal a unique overall architecture of the complex compared to structures from the ubiquitin conjugation pathway, particularly with respect to the location of ISG15 thioester intermediate. Our structures also illuminate the molecular basis for Uba7 activities and for its exquisite specificity for ISG15 and UBE2L6. Altogether, our structural, biochemical, and human cell-based data provide significant insights into the functions of Uba7, UBE2L6, and ISG15 in cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Patient mutations in human ATP:cob(I)alamin adenosyltransferase differentially affect its catalytic versus chaperone functions

Human ATP:cob(I)alamin adenosyltransferase (ATR) is a mitochondrial enzyme that catalyzes an adenosyl transfer to cob(I)alamin, synthesizing 5'-deoxyadenosylcobalamin (AdoCbl) or coenzyme B 12 . ATR is also a chaperone that escorts AdoCbl, transferring it to methylmalonyl-CoA mutase, which is important in propionate metabolism. Mutations in ATR lead to methylmalonic aciduria type B, an inborn error of B12 metabolism. Our previous studies have furnished insights into how ATR protein dynamics influence redox-linked cobalt coordination chemistry, controlling its catalytic versus chaperone functions. In this study, we have characterized three patient mutations at two conserved active site residues in human ATR, R190C/H, and E193K and obtained crystal structures of R190C and E193K variants, which display only subtle structural changes. All three mutations were found to weaken affinities for the cob(II)alamin substrate and the AdoCbl product and increase K M(ATP) . 31 P NMR studies show that binding of the triphosphate product, formed during the adenosylation reaction, is also weakened. However, although the k cat of this reaction is significantly diminished for the R190C/H mutants, it is comparable with the WT enzyme for the E193K variant, revealing the catalytic importance of Arg-190. Furthermore, although the E193K mutation selectively impairs the chaperone function by promoting product release into solution, its catalytic function might be unaffected at physiological ATP concentrations. In contrast, the R190C/H mutations affect both the catalytic and chaperoning activities of ATR. Because the E193K mutation spares the catalytic activity of ATR, our data suggest that the patients carrying this mutation are more likely to be responsive to cobalamin therapy.

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

Revised Nitrogen Reduction Scaling Relations from Potential-Dependent Modeling of Chemical and Electrochemical Steps

The electrochemical nitrogen reduction reaction (NRR) is a promising route to enable carbon-free ammonia production. However, this reaction is limited by the poor activity and selectivity of current catalysts. The rational design of superior NRR electrocatalysts requires a detailed mechanistic understanding of current material limitations to inform how these might be overcome. The current understanding of how scaling limits NRR on metal catalysts is predicated on a simplified reaction pathway that considers only proton-coupled electron transfer (PCET) steps. Here, we apply grand-canonical density functional theory to investigate a more comprehensive NRR mechanism that includes both electrochemical and chemical steps on 30 metal surfaces in solvent under an applied potential. We applied ..phi..max, a grand-canonical adaptation of the Gmax thermodynamic descriptor, to evaluate trends in catalyst activity. This approach produces a ..phi..max "volcano" diagram for NRR activity scaling on metals that qualitatively differs from the scaling relations identified when only PCET steps are considered. NH3* desorption was found to limit the NRR activity for materials at the top of the volcano and truncate the volcano's peak at increasingly reducing potentials. These revised scaling relations may inform the rational design of superior NRR electrocatalysts. This approach is transferable to study other materials and reaction chemistries where both electrochemical and chemical steps are modeled under an applied potential.

electrocatalysis↗
DOE OSTI2026

Supervised Learning-Based Spatial Position Estimation with Vertical Displacement for Hovering UAV Wireless Power Transfer

This study presents a supervised learning-based spatial position estimation approach for wireless power transfer (WPT) systems supporting hovering unmanned aerial vehicle (UAV) charging. Unlike stationary charging scenarios, hovering UAVs introduce continuous lateral misalignment and vertical displacement, leading to variations in magnetic coupling and reduced power transfer efficiency. To address this challenge, the proposed method estimates the relative spatial position of the receiver coil using only electrical measurements obtained at the secondary side. A supervised learning model is trained to map output voltage and current features to spatial coordinates, enabling position awareness without requiring external sensors, vision systems, or communication links. The sensing functionality is inherently integrated into the WPT system, allowing simultaneous power transfer and localization through the same magnetic interface. Experimental validation is conducted on a laboratory-scale prototype under varying lateral offsets and air-gap conditions. In addition, spline-based interpolation is employed to increase spatial data density for training. The results demonstrate that the proposed framework can capture spatial variations associated with both lateral and vertical displacement, providing reliable position estimation under hovering conditions. This work establishes a hardware-efficient, sensorless solution for UAV wireless charging and serves as a baseline for advanced data-driven position estimation methods in dynamic WPT systems.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
DOE OSTI2022

Covalent Organic Frameworks with Irreversible Linkages via Reductive Cyclization of Imines

Covalent organic frameworks (COFs) show great potential for many advanced applications on account of their structural uniqueness. To address the synthetic challenges, facile chemical routes to engineer the porosity, crystallinity, and functionality of COFs are highly sought after. Herein, we report a synthetic approach that employs the Cadogan reaction to introduce nitrogen-containing heterocycles as the linkages in the framework. Irreversible indazole and benzimidazolylidene (BIY) linkages are introduced into COFs for the first time via phosphine-induced reductive cyclization of the common imine linkages following either stepwise or one-pot reaction protocols. Further, the successful linkage transformation introduces new functionalities, as demonstrated in the case of BIY-COF, which displays excellent intrinsic proton conductivity without the need of impregnation with external proton transfer reagents. Such a general strategy will open the window to a broader class of functional porous crystalline materials.

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

Ultrafast infrared transient absorption spectroscopy of gas-phase Ni(CO) 4 photodissociation at 261 nm

Here, we employ ultrafast mid-infrared transient absorption spectroscopy to probe the rapid loss of carbonyl ligands from gas-phase nickel tetracarbonyl following ultraviolet photoexcitation at 261 nm. Here, nickel tetracarbonyl undergoes prompt dissociation to produce nickel tricarbonyl in a singlet excited state; this electronically excited tricarbonyl loses another CO group over tens of picoseconds. Our results also suggest the presence of a parallel, concerted dissociation mechanism to produce nickel dicarbonyl in a triplet excited state, which likely dissociates to nickel monocarbonyl. Mechanisms for the formation of these photoproducts in multiple electronic excited states are theoretically predicted with one-dimensional cuts through the potential energy surfaces and computation of spin–orbit coupling constants using equation of motion coupled cluster methods (EOM-CC) and coupled cluster theory with single and double excitations (CCSD). Bond dissociation energies are calculated with CCSD, and anharmonic frequencies of ground and excited state species are computed using density functional theory (DFT) and time-dependent density functional theory (TD-DFT).

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

Ultrafast hole transfer from monolayer ReS 2 to thin-film F 8 ZnPc

We report a combined experimental and computational study on the charge transfer properties of heterostructures formed by monolayer 1T’-ReS 2 and fluorinated zinc phthalocyanine, F 8 ZnPc. Two-dimensional (2D) ReS 2 monolayer flakes were exfoliated from bulk crystals, and a F 8 ZnPc film with a thickness of 4 nm was thermally deposited on ReS 2 . Density functional theory shows that the two materials form a type-II band alignment. In transient absorption measurements, photocarriers are selectively excited in ReS 2 and monitored in F 8 ZnPc. Here, we found that holes in ReS 2 can transfer to F 8 ZnPc on a time scale shorter than 0.35 ps. The transferred holes have a long lifetime in F 8 ZnPc on the order of 1 ns, confirming the lack of electron transfer. The efficient charge transfer from a 1T’ transition metal dichalcogenide monolayer to an organic semiconductor illustrates the feasibility of developing 2D/organic heterostructures with in-plane anisotropic electronic and optoelectronic properties.

2D materials↗
DOE OSTI2026

Assessing Structural, Thermal, and Functional Characteristics of Marigold Flower Protein as a Sustainable Food Ingredient

The demand for sustainable and alternative protein sources has been on the rise, driving interest in the valorization of underutilized plants. This study evaluated Calendula officinalis (marigold), a common floral waste, as a sustainable alternative protein source for the food industry. The primary objective of this study was to investigate the physicochemical properties of protein fractions from Calendula officinalis flower to evaluate their potential as a novel protein ingredient. Extraction of the Calendula officinalis flower yielded 92.17% of the crude protein. A sequential extraction of albumin, globulin, glutelin, and prolamin from marigold flower revealed albumin as the dominant fraction (65.47%) and exhibited the highest protein functionality, including water-holding capacity (2.37 g/g), oil-holding capacity (2.49 g/g), and emulsifying capacity (65.22 mL/g). Compared with other protein fractions, glutelin showed a relatively high emulsifying and foaming capacity (EC: 59.13 mL/g; FC: 16.23%). Differential scanning calorimetry revealed high thermal stability for albumin (T p = 105.28 °C) and glutelin (T p = 97.6 °C). Sodium Dodecyl Sulfate–Polyacrylamide Gel Electrophoresis (SDS-PAGE) and Liquid Chromatography–Mass Spectrometry (LC-MS) confirmed the presence of abundant low-molecular-weight polypeptides (<37 kDa), which enhanced emulsification, while scanning electron microscopy revealed porous structures aligned with hydration properties. Antioxidant activity was higher in albumin and glutelin, linked to surface hydrophobicity. LC-MS/MS identified 33 short-chain proteins, including oxidoreductase proteins and lipid-transfer proteins. Findings highlight marigold flower proteins as a sustainable, functional ingredient for a diverse range of food applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Leveraging transfer learning and leaf spectroscopy for leaf trait prediction with broad spatial, species, and temporal applicability

Accurate and reliable prediction of leaf traits is crucial for understanding plant adaptations to environmental variation, monitoring terrestrial ecosystems, and enhancing comprehension of functional diversity and ecosystem functioning. Currently, various approaches (e.g., statistical, physical models) have been developed to estimate leaf traits through hyperspectral remote sensing and leaf spectroscopy. However, the absence of high-performing, transferable, and stable models across various domains of space, plant functional types (PFTs) and seasons hinder our ability to quantify and comprehend spatiotemporal variations in leaf traits. This study proposes robust and highly transferable models for better predicting leaf traits with hyperspectral reflectance. Initially, three datasets were assembled, pairing common leaf traits — chlorophyll (Chla+b), carotenoids (Ccar), leaf mass per area (LAM), equivalent water thickness (EWT) — with leaf spectra measurements collected across diverse geographic locations in the U.S. and Europe, PFTs, and seasons. Measurements were acquired using spectroradiometers (e.g., ASD FieldSpec 3/4/Pro and SVC HR-1024i) with integrating spheres, leaf clips, and contact probes. Here, we then developed transfer learning-based hybrid models that incorporated the domain knowledge of radiative transfer models (RTMs) through pretraining processes and were well-constrained by fine-tuning with field measurements. Through comparison with other state-of-the-art statistical models, including partial-least squares regression (PLSR) and Gaussian Process Regression (GPR), as well as pure physical models, we found that the proposed transfer learning models achieved better predictive performance and higher transferability. Specifically, compared to other statistical models and pure RTMs, the transfer learning model exhibited higher coefficient of determination (R 2 ) values with range of 0.01 to 0.79, lower normalized root mean square error (NRMSE) with range of 0.06 % to 33.25 % in model performance. Additionally, the models exhibited improved transferability, with higher R 2 values range from 0.04 to 0.32, lower NRMSE range from 0.08 % to 30.81 %. The findings underscore that transfer learning models through integrating domain knowledge from RTMs and limited observations, can harness the advantages of both RTMs and statistical models and serve as a promising approach for effectively predicting leaf traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Designing Physicochemically‐Ordered Interphases for High‐Performance Composites

To enhance the mechanical properties of carbon fiber‐reinforced polymer composites, a physicochemical scaffold is designed incorporating microscopically architected chemically reactive nanofibers that act as a multiscale bridge between the carbon fibers and the matrix. Thermally activated nanofibers leverage their morphologically driven mechanochemical properties to form covalent bonds with adjacent polymer molecules, creating a co‐continuous network that dramatically enhances fiber‐matrix load transfer. By meticulously controlling the nanofiber architecture through variable surface area, functional group availability, and polymer chain alignment effects, the extent of covalent bonding between nanofibers and the matrix is manipulated ultimately resulting in improved carbon fiber‐matrix adhesion. Further, the concept was validated using polyacrylonitrile nanofibers within an acrylonitrile butadiene styrene matrix in a discontinuous carbon fiber‐reinforced composite system. Nanomechanical studies using atomic force microscopy and low‐field nuclear magnetic resonance spectroscopy confirmed immobilized, chemically transferred, and ordered nanostructures at the interphase. The resulting composites demonstrated ≈56% and ≈175% improvements in tensile strength and toughness, respectively, compared to composites without nanofiber. Comprehensive thermal, rheological, and X‐ray scattering analyses, along side all‐atomic molecular dynamics simulations, revealed the fundamental mechanisms behind these improvements in mechanical behavior. The versatility and efficacy of the approach have the potential to address longstanding interphase challenges in the composite industry.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Electrochemical Hydrogenation of CO on Cu(100): Insights from Accurate Multiconfigurational Wavefunction Methods

Copper (Cu) remains the most efficacious electrocatalyst for electrochemical CO 2 reduction (CO 2 R). Its activity and selectivity are highly facet-dependent. We recently examined the commonly proposed rate-limiting CO hydrogenation step on Cu(111) via embedded correlated wavefunction (ECW) theory and demonstrated that only this higher-level theory yields predictions consistent with potential-dependent experimental kinetics. Here, to understand the differing activities of Cu(111) and Cu(100) in catalyzing CO 2 R, we explore CO hydrogenation on Cu(100) using ECW theory. We predict that the preferred pathway involves the reduction of adsorbed CO (*CO) to *COH via proton-coupled electron transfer (PCET) at working potentials, although *CHO also may form with a kinetically accessible but higher barrier. In contrast, our earlier work on Cu(111) concluded that *COH and *CHO formation via PCET are equally feasible. Furthermore, this work illustrates one possible origin of the facet dependence of CO 2 R mechanisms and products on Cu electrodes and sheds light on how the selectivity of CO 2 R electrocatalysts can be controlled by the surface morphology.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Machine-learning-enabled on-the-fly analysis of RHEED patterns during thin film deposition by molecular beam epitaxy

Thin film deposition is a fundamental technology for the discovery, optimization, and manufacturing of functional materials. Deposition by molecular beam epitaxy (MBE) typically employs reflection high-energy electron diffraction (RHEED) as a real-time in situ probe of the growing film. However, the state-of-the-art for RHEED analysis during deposition requires human observation. Here, we present an approach using machine learning (ML) methods to monitor, analyze, and interpret RHEED images on-the-fly during thin film deposition. In the analysis workflow, RHEED pattern images are collected at one frame per second and featurized using a pretrained deep convolutional neural network. The feature vectors are then statistically analyzed to identify changepoints; these changepoints can be related to changes in the deposition mode from initial film nucleation to a transition regime, smooth film deposition, and in some cases, an additional transition to a rough, islanded deposition regime. The feature vectors are additionally analyzed via graph analysis and community classification. The graph is quantified as a stabilization plot, and we show that inflection points in the stabilization plot correspond to changes in the growth regime. The full RHEED analysis workflow is termed RHAAPsody and includes data transfer and output to a visual dashboard. We demonstrate the functionality of RHAAPsody by analyzing the precaptured RHEED images from epitaxial depositions of anatase TiO2 on SrTiO3(001) and show that the analysis workflow can be executed in less than 1 s. Our approach shows promise as one component of ML-enabled real-time feedback control of the MBE deposition process.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Chirality transfer from chiral perovskite to molecular dopants via charge transfer states

Chiral perovskites are semiconductors with broken mirror symmetries. Their photo responses are often constrained in the UV range. In this work, we demonstrate that doping 2,3,5,6-Tetrafluoro-7,7,8,8-tetracyanoquinodimethane in the chiral perovskite matrix introduces a visible light absorption feature through the emerging charge-transfer electronic states. These charge-transfer states exhibits circular dichroism inherited from the chiral host, indicating effective chirality transfer from host to guest component via electronic coupling. Quantum-chemical modeling identifies a strong wave function overlap between an electron and a hole of the guest-host in a closely packed crystal configuration promoting the charge transfer state’s optical activity. We further integrate the doped chiral perovskite film into photodetectors and demonstrate a selective detection of circularly polarized light in both UV and visible regions. Our results suggest a universal approach of introducing visible photo absorption states to the chiral matrix to broaden the optical active range while enhancing the electrical conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effects of Proton Irradiation on the Performance of Skipper CCDs

Skipper CCDs are a mature detector technology that has been suggested for future space telescope instruments requiring sub-electron readout noise in the near-ultraviolet to the near-infrared. While modern skipper CCDs inherit from the radiation-tolerant p-channel detectors developed by LBNL, the effects of high doses of ionizing radiation on skipper CCDs (such as those expected in space) remains largely unmeasured. We report preliminary results on the performance of p-channel skipper CCDs following irradiation with 217-MeV protons at the Northwestern Medicine Proton Center. The total nonionizing energy loss (NIEL) experienced by the detectors exceeds 6 years at the Sun-Earth Lagrange Point 2 (L2). We demonstrate that the skipper amplifier continues to function as expected following this irradiation. Owing to the low readout noise of these detectors, controlled irradiation tests can be used to sensitively characterize the charge transfer inefficiency, dark current, and the density and time constants of charge traps as a function of proton fluence. We conclude with a brief outlook toward future tests of these detectors at other proton and gamma-ray facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Optimization of the Reax force field for the lithium–oxygen system using a high fidelity charge model

Studies using molecular dynamics (MD) have long struggled to simulate the failure modes of materials, predicting unrealistically high ductility and failing to capture brittle fracture. The primary cause of this shortcoming is an inadequate description of bond breaking. While reactive force fields such as ReaxFF show improvements compared to traditional force fields, the charge models used yield unphysical partial charges, especially during dissociation of ionic bonds. This flaw may be remedied by using the atom-condensed Kohn–Sham density functional theory (DFT) approximated to a second order (ACKS2) charge model for determining partial charges. In this work, we present a new ACKS2-enabled Reax force field for fracture simulations of lithium oxide systems, which was obtained by training against an extensive set of DFT, multireference configuration interaction (MRCI), and MRCI+Q reference data using genetic optimization techniques. This new force field significantly improves the bond breaking behavior, but still cannot fully capture the brittle fracture in MD simulations, suggesting more research is needed to improve simulation of brittle fracture.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Free Energy Dependencies for Interfacial Electron Transfer from Tin-Doped Indium Oxide (ITO) to Molecular Photoredox Catalysts

John B. Goodenough proposed that interfacial electron transfer kinetics from main group metal oxides should be fundamentally different from that of transition metal oxides, an expectation that has not been widely tested. Herein, the kinetics for interfacial electron transfer from mesoporous transparent conductive oxide Tin-doped Indium Oxide (ITO) to four photoredox catalysts (PCs) were characterized in acetonitrile electrolytes. The photocatalysts had the form: [Ru(4,4ʹ-R 2 -2,2′-bipyridine) 2 (4,4ʹ-(PO 3 H 2 ) 2 -2,2′-bipyridine)] 2+ , where R was H, methoxy, tert -butyl, and Br. The impact of the surface binding group was characterized with [Ru(2,2′-bipyridine) 2 (4,4ʹ-(CO 2 H) 2 -bpy)] 2+ . The interfacial electron transfer reaction ITO(e − )∣PC + → ITO∣PC was quantified by nanosecond absorption spectroscopy as a function of the applied potential (and hence ‒Δ G °). Specific conditions of applied potential were identified where the kinetics were sensitive to the incident irradiance. A layer-by-layer method was used to insert ionic methylene bridge(s) between the PC and the oxide surface. Marcus-Gerischer analysis of the kinetic data indicates non-adiabatic interfacial electron transfer with total reorganization energies that increase when bridges were placed between the photocatalyst and the ITO surface.

Bangle, Rachel E.↗