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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Ethylene polymerization with a crystallographically well-defined metal–organic framework supported catalyst

The inherent crystallinity of metal–organic framework (MOF) catalysts offers the possibility to understand the structure of the active site at the molecular level. This property is often lacking in traditional amorphous supports. Cr-SIM-NU-1000, a MOF-supported Cr 3+ heterogeneous catalyst, is shown to be competent for ethylene polymerization after activation with AlEt 2 Cl (DEAC), producing crystalline linear polyethylene (PE). The polymer produced has a low polydispersity (D = 2.0), in marked contrast to the Phillips supported chromium catalyst, Cr@SiO 2 (D ~ 8–65). Cr-SIM-NU-1000 achieves a turnover frequency of 2.6 × 10 3 h –1 under 40 bar ethylene pressure at room temperature, with corresponding PE productivity of 1.3 × 10 5 g PE mol –1 Cr per h. Single crystal X-ray diffraction (SC-XRD) of the pre-catalyst was conducted by collecting a structure of alkyl aluminum (DEAC) co-catalyst treated Cr-SIM-NU-1000. This crystal structure provides insight into the interactions between DEAC co-catalyst and Cr active site, revealing a Cr–C bond after treatment with DEAC. Furthermore, DEAC is crystallographically resolved at the terminal oxy-ligands of the node and likely also exists within the window pores of the framework between nodes, based on electron density mapping. Cr-SIM-NU-1000 offers the opportunity to study a structurally well-defined olefin polymerization system, with atomically precise characterization of the pre-catalyst structure. Furthermore, this allows the proposal of a mechanism and feeds into future development of next-generation heterogeneous catalyst systems.

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

First-Principles-Based Study of the Decomposition of Phenol and Hydroquinone on Pt(111) Combined with Quantitative Information from XPS Spectra to Address the Impact of Coverage and Number of Hydroxyl Functional Groups

A combined first-principles-based and experimental X-ray photoelectron spectroscopy approach was used to investigate the thermal decomposition of two model biofuel compounds, phenol and hydroquinone, on Pt(111) at both low and high coverages. The DFT-based approach yields adsorption geometries and energies, activation barriers and core-level binding energy shifts for C 1s and O 1s. Increasing the coverage in the theoretical model leads to slight shifts in core-level binding energies─toward higher values for C 1s and lower values for O 1s. It also alters the energy profiles of the decomposition reaction pathway, resulting in weaker adsorption energies and changes in both reaction and activation barriers. At low temperatures, we observe a multilayer for phenol and hydroquinone upon adsorption, with desorption occurring at 200 and 270 K, respectively. Following desorption of the multilayer, decomposition proceeds via initial O–H bond scission, followed by two parallel pathways involving either C–H or C–C bond scission, whereby in the case of phenol C–H bond scission occurs first. Here, we further provide characteristic core level binding energies by theoretical calculations that are subsequently used in experimental analyses, establishing a reference database for key spectra of phenolic functionalities applicable to a range of catalytic reactions.

09 BIOMASS FUELS↗
DOE OSTI2022

On Single-Cell Enzyme Assays in Marine Microbial Ecology and Biogeochemistry

Extracellular enzyme activity is a well-established parameter for evaluating microbial biogeochemical roles in marine ecosystems. The presence and activity of extracellular enzymes in seawater provide insights into the quality and quantity of organic matter being processed by the present microorganisms. A key challenge in our understanding of these processes is to decode the extracellular enzyme repertoire and activities of natural communities at the single-cell level. Current measurements are carried out on bulk or size-fractionated samples capturing activities of mixed populations. This approach – even with size-fractionation – cannot be used to trace enzymes back to their producers, nor distinguish the active microbial members, leading to a disconnect between measured activities and the producer cells. By targeting extracellular enzymes and resolving their activities at the single-cell level, we can investigate underlying phenotypic heterogeneity among clonal or closely related organisms, characterize enzyme kinetics under varying environmental conditions, and resolve spatio-temporal distribution of individual enzyme producers within natural communities. In this perspective piece, we discuss state-of-the-art technologies in the fields of microfluidic droplets and functional screening of prokaryotic cells for measuring enzyme activity in marine seawater samples, one cell at a time. We further elaborate on how this single-cell approach can be used to address research questions that cannot be answered with current methods, as pertinent to the enzymatic degradation of organic matter by marine microorganisms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

International Collaboration Activities in Geologic Disposal R&D: Spent Fuel and High-Level Waste Disposition (FY25 Progress Report)

This report describes the FY25 status of international collaboration on geologic disposal research and development (R&D) in the Office of Spent Fuel and High-Level Waste Disposition (SFHLWD) in the U.S. Department of Energy’s (DOE) Office of Nuclear Energy (NE). The mission of this office is to provide confidence in the safe long-term management of the nation’s spent nuclear fuel and high-level radioactive waste by reducing uncertainty and advancing technology for extended storage, transportation, and geologic disposal. R&D in geologic disposal is administered in SFHLWD’s Disposal R&D Campaign.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Activation of H 2 O by ThO 2 – Experimental and Computational Studies

Here, a synergetic study that utilized anion photoelectron spectroscopy and high-level abinitio calculations has explored the activation of H 2 O molecules by ThO 2 – molecular anions. Both experiment and theory found conclusive evidence for said activation. In the experiments, this appeared as a tell-tale directional shift in the spectral profile of the anionic complex that ruled out physisorption,i.e., ThO 2 – (H 2 O), and implied chemisorption. In the computations, good agreement was found between the calculated and measured vertical detachment energies, and the atomic connectivity (the structure) of the resulting anionic complex was found to be [OTh(OH) 2 ] – .

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

CholecTriplet2021: A benchmark challenge for surgical action triplet recognition

Context-aware decision support in the operating room can foster surgical safety and efficiency by leveraging real-time feedback from surgical workflow analysis. Most existing works recognize surgical activities at a coarse-grained level, such as phases, steps or events, leaving out fine-grained interaction details about the surgical activity; yet those are needed for more helpful AI assistance in the operating room. Recognizing surgical actions as triplets of ‹ instrument, verb, target › combination delivers more comprehensive details about the activities taking place in surgical videos. This paper presents CholecTriplet2021: an endoscopic vision challenge organized at MICCAI 2021 for the recognition of surgical action triplets in laparoscopic videos. Here, the challenge granted private access to the large-scale CholecT50 dataset, which is annotated with action triplet information. In this paper, we present the challenge setup and the assessment of the state-of-the-art deep learning methods proposed by the participants during the challenge. Here, a total of 4 baseline methods from the challenge organizers and 19 new deep learning algorithms from the competing teams are presented to recognize surgical action triplets directly from surgical videos, achieving mean average precision (mAP) ranging from 4.2% to 38.1%. This study also analyzes the significance of the results obtained by the presented approaches, performs a thorough methodological comparison between them, in-depth result analysis, and proposes a novel ensemble method for enhanced recognition. Our analysis shows that surgical workflow analysis is not yet solved, and also highlights interesting directions for future research on fine-grained surgical activity recognition which is of utmost importance for the development of AI in surgery.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A simple model of COVID-19 explains disease severity and the effect of treatments

Abstract Considerable effort has been made to better understand why some people suffer from severe COVID-19 while others remain asymptomatic. This has led to important clinical findings; people with severe COVID-19 generally experience persistently high levels of inflammation, slower viral load decay, display a dysregulated type-I interferon response, have less active natural killer cells and increased levels of neutrophil extracellular traps. How these findings are connected to the pathogenesis of COVID-19 remains unclear. We propose a mathematical model that sheds light on this issue by focusing on cells that trigger inflammation through molecular patterns: infected cells carrying pathogen-associated molecular patterns (PAMPs) and damaged cells producing damage-associated molecular patterns (DAMPs). The former signals the presence of pathogens while the latter signals danger such as hypoxia or lack of nutrients. Analyses show that SARS-CoV-2 infections can lead to a self-perpetuating feedback loop between DAMP expressing cells and inflammation, identifying the inability to quickly clear PAMPs and DAMPs as the main contributor to hyperinflammation. The model explains clinical findings and reveal conditions that can increase the likelihood of desired clinical outcome from treatment administration. In particular, the analysis suggest that antivirals need to be administered early during infection to have an impact on disease severity. The simplicity of the model and its high level of consistency with clinical findings motivate its use for the formulation of new treatment strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Interaction of Soil pH and Mineralogy Controls Soil Organic Matter Persistence through Changes in the Composition and Amount of Microbial Necromass

Microbial necromass–mineral associations are key to long-term soil organic matter (SOM) persistence. However, how soil pH and mineralogy interact to regulate SOM stability remains poorly understood. Here, we used artificial soils to test how three clay minerals (bentonite, kaolinite, and goethite), adjusted to four pH levels (5–8), affect microbial activity (respiration), microbial physiology (carbon use efficiency, CUE), microbial-derived residue material (necromass), and the formation and stability of mineral-associated organic matter (MAOM). Artificial soils were inoculated with a rhizosphere-derived microbial community cultured under the same pH conditions and on two representative simulated exudate types (organic acids and carbohydrates) and incubated for 6 weeks. In two complementary experiments, we added necromass from known microbial taxa to the same minerals across pH levels to isolate the role of necromass chemistry and loading. We found that soil pH shaped MAOM chemistry by altering microbial activity and necromass composition. In interaction with mineral type, pH also controlled MAOM thermal stability. Higher necromass loading weakened mineral-organic bonding, reducing MAOM stability, consistent with zonal mineral–organic interaction models. Our results demonstrate that microbial activity, rather than carbon use efficiency, better predicts MAOM formation and that pH-dependent necromass composition and loading govern MAOM persistence. These findings advance mechanistic understanding of SOM stabilization and have implications for predicting soil carbon dynamics under shifting environmental conditions.

carbon use efficiency↗
DOE OSTI2023

Effects from Time Dependence of Ice Nucleus Activity for Contrasting Cloud Types

Abstract The role of time-dependent freezing of ice nucleating particles (INPs) is evaluated with the “Aerosol–Cloud” (AC) model in 1) deep convection observed over Oklahoma during the Midlatitude Continental Convective Cloud Experiment (MC3E), 2) orographic clouds observed over North California during the Atmospheric Radiation Measurement (ARM) Cloud Aerosol Precipitation Experiment (ACAPEX), and 3) supercooled, stratiform clouds over the United Kingdom, observed during the Aerosol Properties, Processes And Influences on the Earth’s climate (APPRAISE) campaign. AC uses the dynamical core of the WRF Model and has hybrid bin–bulk microphysics and a 3D mesoscale domain. AC is validated against coincident aircraft, ground-based, and satellite observations for all three cases. Filtered concentrations of ice (>0.1–0.2 mm) agree with those observed at all sampled levels. AC predicts the INP activity of various types of aerosol particles with an empirical parameterization (EP), which follows a singular approach (no time dependence). Here, the EP is modified to represent time-dependent INP activity by a purely empirical approach, using our published laboratory observations of time-dependent INP activity. In all simulated clouds, the inclusion of time dependence increases the predicted INP activity of mineral dust particles by 0.5–1 order of magnitude. However, there is little impact on the cloud glaciation because the total ice is mostly (80%–90%) from secondary ice production (SIP) at levels warmer than about −36°C. The Hallett–Mossop process and fragmentation in ice–ice collisions together initiate about 70% of the total ice, whereas fragmentation during both raindrop freezing and sublimation contributes <10%. Overall, total ice concentrations and SIP are unaffected by time-dependent INP activity. In the simulated APPRAISE case, the main causes of persistence of long-lived clouds and precipitation are predicted to be SIP in weak embedded convection and reactivation following recirculation of dust particles in supercooled layer cloud.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Metabolic flux and resource balance in the oleaginous yeast Rhodotorula toruloides

The yeast Rhodotorula toruloides is a promising bioproduction organism due to its high lipid yields and ability to grow on cheap and abundant substrates. Quantitative, systems-level assessment of its metabolic activity is accordingly merited. Resource-balance analysis (RBA) models capture not only reaction stoichiometry but also enzyme requirements for catalysis, providing valuable tools for understanding metabolic trade-offs and optimizing metabolic engineering strategies. Here, in this work, we present systems-level measurements of R. toruloides metabolic flux based on isotope tracing and metabolic flux analysis. In combination with new proteomic measurements, these flux data are used to parameterize a genome-scale resource balance model rtRBA. We find that S. cerevisiae and R. toruloides grow at nearly indistinguishable rates using similar biosynthetic but dramatically different central metabolic programs. R. toruloides consumes one-fifth as much glucose, which it metabolizes primarily via the pentose phosphate pathway and TCA cycle unlike primarily glycolysis in S. cerevisiae . Overall, across these two divergent yeasts, protein abundances aligned more closely than metabolic flux. Resource balance modeling of these metabolic programs predicts superior theoretical yields but lower productivities in R. toruloides than S. cerevisiae for industrial chemicals, highlighting the value of rapid glucose uptake for productivity but respiratory metabolism for yields.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Characterizing Defect Dynamics in Silicon Carbide Using Symmetry-Adapted Collective Variables and Machine Learning Interatomic Potentials

Silicon carbide (SiC) divacancies are attractive candidates for spin-defect qubits possessing long coherence times and optical addressability. The high activation barriers associated with SiC defect formation and motion pose challenges for their study by first-principles molecular dynamics. In this work, we develop and deploy machine learning interatomic potentials (MLIPs) to accelerate defect dynamics simulations while retaining ab initio accuracy. We employ an active learning strategy comprising symmetry-adapted collective variable discovery and enhanced sampling to compile configurationally diverse training data, calculation of energies and forces using density functional theory (DFT), and training of an E(3)-equivariant MLIP based on the Allegro model. Here, the trained MLIP reproduces DFT-level accuracy in defect transition activation free energy barriers, enables the efficient and stable simulation of multidefect 216-atom supercells, and permits an analysis of the temperature dependence of defect thermodynamic stability and formation/annihilation kinetics to propose an optimal annealing temperature to maximally stabilize VV divacancies.

Computer simulations↗
DOE OSTI2021

Single-layered organic photovoltaics with double cascading charge transport pathways: 18% efficiencies

The chemical structure of donors and acceptors limit the power conversion efficiencies achievable with active layers of binary donor-acceptor mixtures. Here, using quaternary blends, double cascading energy level alignment in bulk heterojunction organic photovoltaic active layers are realized, enabling efficient carrier splitting and transport. Numerous avenues to optimize light absorption, carrier transport, and charge-transfer state energy levels are opened by the chemical constitution of the components. Record-breaking PCEs of 18.07% are achieved where, by electronic structure and morphology optimization, simultaneous improvements of the open-circuit voltage, short-circuit current and fill factor occur. The donor and acceptor chemical structures afford control over electronic structure and charge-transfer state energy levels, enabling manipulation of hole-transfer rates, carrier transport, and non-radiative recombination losses.

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

Nature of the Reactive Biferric Peroxy Intermediate P′ in the Arylamine Oxygenases and Related Binuclear Fe Enzymes

Binuclear nonheme iron enzymes activate O 2 to perform a wide range of chemical transformations. The process of O 2 activation typically involves a biferric peroxy-level intermediate P. It has been previously found that this intermediate undergoes further activation, either protonation or rearrangement to form P′ or further oxidation to form high-valent intermediates Q or X. Here, this study defines the structure of the P′ intermediate in the N-oxygenases CmlI (and AurF based on previous data) using nuclear resonance vibrational spectroscopy (NRVS) in conjugation with density functional theory (DFT) calculations. These results, combined with variable temperature variable field (VTVH) magnetic circular dichroism (MCD) spectroscopy on the 1-electron cryoreduced P′, define the structure of the P′ intermediate as a μ-1,2-hydroxoperoxo biferric site with a second hydroxide bridge. Reaction coordinate calculations demonstrate that single electron transfer (SET) is facilitated by protonation of the peroxo, activating its reductive cleavage, and that the additional hydroxide bridge does not impact this reaction. VTVH MCD studies further reveal that the hydroxide bridge is absent in the biferrous site, suggesting that during the O 2 reaction with the biferrous site, a water molecule forms the hydroxide bridge in providing the proton that activates the peroxide in P′ for reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Performance Assessment for the Disposal of Low Level Waste in the 200 West Area Burial Grounds (FY2019 Annual Statius Report)

This annual review provides the projected dose estimates of radionuclide inventories disposed in the active 200 West Area Low-Level Waste Burial Grounds (LLBGs) since September 26, 1988. These estimates are calculated using the original dose methodology developed in the performance assessment (PA) analysis (WHC-EP-0645) and are compared with performance objectives defined in U.S. Department of Energy requirements (DOE O 435.1 and its companion documents DOE M 435.1-1 and DOE-STD-5002-2017). All performance objectives are currently satisfied, and operational waste acceptance criteria (HNF-EP-0063) and waste acceptance practices continue to be sufficient to maintain compliance with performance objectives. Inventory estimates and associated dose estimates from future waste disposal actions are unchanged from previous years’ evaluations, indicating that potential impacts are well below performance objectives; therefore, future compliance with DOE O 435.1 is expected.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Panel Session 98B: Treatment of Low-Activity Tank Waste at Hanford: Considering the Alternatives

This panel focused on alternative treatment of the Hanford Low-Activity Tank Waste. Currently, Tank Waste at the Hanford Site is to be separated into low-activity (LAW) and high-level waste (HLW) fractions, and then vitrified to produce immobilized LAW glass for onsite disposal, and HLW glass for ultimate geologic disposal. This panel discussed several commissioned studies by the National Laboratories, National Academies, and General Accountability Office to evaluate the risks, costs, and benefits associated with considering options for immobilizing portions of the Hanford LAW waste forms. Panelists with presentations: Analysis of Supplemental Treatment Approaches for Low-Activity Waste at the Hanford Nuclear Reservation Overview and Conclusions (Michael Stone); Analysis of Supplemental Treatment Approaches for Low-Activity Waste at the Hanford Nuclear Reservation: Disposal Performance Evaluation (Tom Brouns); National Academies Review of the Study on Supplemental Treatment Approaches of Low-Activity Waste at the Hanford Nuclear Reservation (Charles Ferguson); GAO Observations on Immobilizing Low-Activity Waste at DoE's Hanford Site (David Trimble)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗