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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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Employing gadolinium micro-disks as temperature probes for magnetic resonance imaging
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Employing methylotrophs for a green economy: one-carbon to fuel them all and through metabolism redesign them
Microbial platforms are currently being optimized to revolutionize industrial energy production while mitigating shortages of global resources and food supplies. Here, in this work, we address recent advances to develop bacterial methylotrophic platforms as promising platforms enabling the reuse of products and materials (at their highest value) while reducing waste and pollution.
Angular-spectral filtering of recoil protons for optimization of fast neutron imaging employing proton converters
Fast neutron imaging is an important capability for diverse applications such as inertial confinement fusion diagnostics, cargo security, nuclear nonproliferation and arms control, and industrial inspection. Traditional phosphor image plates can be enhanced for fast neutron imaging using hydrogenous plastic converters which allow fast neutrons to scatter off hydrogen nuclei to produce energetic protons that can be recorded by the image plate. However, protons emitted by image plates are not constrained in their emission angle, which contributes to the blur of the resulting image. Here, we investigate two methods that can alter the spatial extent of converted protons that deposit energy in the image plate: reducing the converter thickness, and introducing a proton filter between the plastic converter and image plate to reduce the contribution of lower-energy, off-axis protons to the image. Here we determine the optimal plastic converter thickness for maximizing the signal intensity to be 2–3 mm through Monte Carlo simulations, and we benchmark this result against experimental measurements with a deuterium-tritium (DT) neutron generator. Next, we evaluate the image smearing and signal loss for various converters to show that solely reducing the converter thickness has the expected effect of reducing the blur from proton image smearing of the sharpness of an edge recorded on the image plate at the cost of reducing the signal intensity. The use of a proton filter is shown to achieve a similar improvement of edge sharpness as reducing the converter thickness while also sacrificing the signal intensity. We conclude that the use of proton energy filtering can improve the sharpness of fast neutron images in situations where the converter thickness cannot be reduced below some practical minimum. For more intense neutron sources, the signal intensity is of less concern, and optimizing the resolution of the image plate and therefore of the imaging system could have greater value. In these applications, proton filters may allow for improved fast neutron imaging measurements.
Finite element analysis of the impact of beam heating mode in molten salt corrosion experiments employing simultaneous ion irradiation
Finite element analysis was used to investigate the temperature and stress profiles that develop in 316L stainless steel membranes being irradiated using different proton beam conditions in contact with a molten salt environment. It was shown that in addition to a nonuniform irradiation profile, a focused 2 MeV proton beam leads to very strong temperature and stress gradients in the membrane, introducing highly localized driving forces that complicate and even compromise the integrity and reliability of the experimental results of corrosion studies. Here, the use of a focused beam in corrosion studies can create experimental artifacts that may misrepresent the true corrosion behavior. In contrast, the use of a rastered beam is shown to distribute the protons and resulting radiation damage uniformly across the membrane face, and more importantly, results in temperature and stress profiles that are not only very uniform but are of much lower magnitude. The use of a rastered beam during molten salt corrosion experiments is therefore recommended to achieve uniform damage rates, thereby reducing both gradients and magnitudes of the temperature and stress distributions.
Employing Long-Range Inductive Effects to Modulate Metal-to-Ligand Charge Transfer Photoluminescence in Homoleptic Cu(I) Complexes
Four Cu(I) bis(phenanthroline) photosensitizers formulated from a new ligand structural motif (Cu1-Cu4) coded according to their 2,9-substituents, were synthesized, structurally characterized, and fully evaluated using steady-state and time-resolved absorption and photoluminescence (PL) measurements as well as electrochemistry. The 2,9-disubstituted-3,4,7,8-tetramethyl-1,10-phenanthroline ligands feature the following six-membered ring systems prepared through photochemical synthesis: 4,4-dimethylcyclohexyl (1), tetrahydro-2H-pyran-4-yl (2), tetrahydro-2H-thiopyran-4-yl (3), and 4,4-difluorocyclohexyl (4). Universally, these Cu(I) metal-to-ligand charge transfer (MLCT) chromophores display excited state lifetimes on the microseconds time scale at room temperature, including the three longest-lived homoleptic cuprous phenanthroline excited states measured to date in deaerated CH 2 Cl 2 , τ = 2.5 to 4.3 μs. This series of molecules also feature high PL quantum efficiencies (ΦPL = 5.3 to 12% in CH 2 Cl 2 ). Temperature-dependent PL lifetime experiments confirmed that all these molecules exhibit reverse intersystem crossing and display thermally activated delayed PL from a 1 MLCT excited state lying slightly above the 3 MLCT state, 1050 – 1490 cm -1 . Ultrafast and conventional transient absorption measurements confirmed that the PL originates from the MLCT excited state, which remains sterically arrested, preventing an excessive flattening distortion even when dissolved in Lewis basic CH 3 CN. Combined PL and electrochemical data provided evidence that Cu1-Cu4 are highly potent photoreductants (E ox * = -1.73 to -1.62 V vs. Fc +/o in CH 3 CN), whose potentials are altered solely based on which heteroatoms or substituents are resident on the 2,9-appended ring derivatives. It is proposed that long-range electronic inductive effects are responsible for the systematic modulation observed in the PL spectra, excited state lifetimes, as well as the ground state absorption spectra and redox potentials. Cu1-Cu4 quantitatively follow the energy gap law, correlating well with structurally related cuprous phenanthrolines and are also shown to triplet photosensitize the excited states of 9,10-diphenylanthracene with bimolecular rate constants ranging from 1.61 to 2.82 × 10 8 M –1 s –1 . Furthermore, the ability to tailor both photophysical and electrochemical properties using long-range inductive effects imposed by the 2,9-ring platforms advocates new directions for future MLCT chromophore discovery.
Hole Transfer to Carbazole Derivatives: Untold Story of “Self-Assembled Monolayers” Employed in “Halide Perovskite Solar Cells”
Carbazole derivatives, such as MeO-2PACz and 2PACz are known to improve the performance of halide perovskite solar cells by facilitating hole transfer. To assess their interaction with halide perovskites, this work probes the hole transfer from excited CsPbBr3 quantum dots to MeO-2PACz and 2PACz using emission spectroscopic and transient absorption techniques. The different oxidation potentials of these two carbazoles result in divergent interactions with CsPbBr 3 QDs. Whereas MeO-2PACz quenches the emission of CsPbBr 3 QDs, 2PACz enhances the emission by remediating the surface traps. Transient absorption studies confirm the formation of MeO-2PACz +• cation radical with characteristic absorption in the near IR region. No such oxidation process was observed with 2PACz. The mechanistic insights into the interaction of the two carbazole derivatives with excited perovskite nanocrystals will add another piece to the untold story behind the improved performance of perovskite photovoltaic devices.
Advancing the Performance of Anion Exchange Membrane Electrolysis by Employing a Powder-Based Ionomer during Anode Catalyst Layer Fabrication
The performance of anion exchange membrane water electrolysis (AEMWE) can be significantly improved by utilizing powdered ionomers during the fabrication of the anode catalyst layer (CL) to modify the CL properties. When comparing powdered ionomers to dispersed ionomers across various catalysts including cobalt oxide (Co 3 O 4 ), nickel−iron oxide (NiFe 2 O 4 ), and iridium oxide (IrO 2 ) the anode fabricated with powdered ionomers demonstrates improved performance in polarization curves, enhanced charge transfer kinetics, and reduced ohmic and transport losses, as evidenced by voltage breakdown and electrochemical impedance spectroscopy analyses. Optimal performance is achieved using a Co 3 O 4 catalyst with a 10 wt % powdered ionomer via the catalystcoated substrate method. Microscopy analyses reveal that electrodes formed with powdered ionomers during fabrication exhibit a more uniform catalyst and ionomer distribution, increased porosity with smaller pore areas, improved electronic conduction with less catalyst agglomeration isolated by a nonconductive ionomer, and enhanced interfacial contact with the membrane and transport layer. These findings highlight that ionomers in a powdered form can promote beneficial properties and are a promising approach to improving AEMWE efficiency.
Hydrogen Bonding Analysis of Structural Transition-Induced Symmetry Breaking and Spin Splitting in a Hybrid Perovskite Employing a Synergistic Diffraction-DFT Approach
Two-dimensional (2D) hybrid organic–inorganic perovskites (HOIPs) offer an outstanding opportunity for spin-related technologies owing in part to their tunable structural symmetry breaking and distortions driven by organic–inorganic hydrogen (H) bonds. However, understanding how H-bonds tailor inorganic symmetry and distortions and therefore enhance spin splitting for more effective spin manipulation remains imprecise due to challenges in measuring H atom positions using X-ray diffraction. Here, we report a thermally induced structural transition (at ~209 K) for a 2D HOIP, (2-BrPEA) 2 PbI 4 [2-BrPEA = 2-(2-bromophenyl)ethylammonium], which induces inversion asymmetry and a strong spin splitting (ΔE > 30 meV). While X-ray diffraction generally establishes heavy atom coordinates, we utilize neutron diffraction for accurate H atom position determination, demonstrating that the structural transition-induced rearrangement of H-bonds with distinct bond strengths asymmetrically shifts associated iodine atom positions. Further, consequences of this shift include an increased structural asymmetry, an enhanced difference between adjacent interoctahedra distortions (i.e., Pb–I–Pb bond angles), and therefore significant spin splitting. We further show that H-only density-functional theory (DFT) relaxation of the X-ray structure shifts H atoms to positions that are consistent with the neutron experimental data, validating a convenient pathway to more generally improve upon HOIP H-bonding analyses derived from quicker/less-expensive X-ray data.
Employing Machine Learning for New Particle Formation Identification and Mechanistic Analysis: Insights From a Six‐Year Observational Study in the Southern Great Plains
We present a supervised machine learning (ML) framework to automatically identify new particle formation (NPF) events and analyze key atmospheric factors associated with their occurrence and growth. We applied ML to detect NPF events using start time and particle concentrations across size ranges, while identifying atmospheric variables including ambient temperature, relative humidity, solar radiation intensity (SRI), wind speed, wind direction, boundary layer height, total organics, sulfate, nitrate, total surface area concentration, sulfur dioxide, and turbulent kinetic energy (TKE). We analyzed a 6-year data set from the Atmospheric Radiation Measurement at the Southern Great Plains (SGP) site in Oklahoma, USA. Using long-term ground-based measurements, we identified NPF events and applied Random Forest Classifiers, which achieved 90%–95% prediction accuracy. Feature importance analysis highlighted SRI, relative humidity, and ambient temperature as the most influential variables, contributing normalized importances of 28%, 17%, and 10%. Partial Dependence Plots (PDPs) indicated that higher SRI and lower relative humidity were critical in promoting NPF formation at SGP. Seasonally, NPF events were more frequent in winter (42.1%) and spring (35.5%), and least in summer (4.0%). Particle growth rates also exhibited a seasonal variation, with the lowest in winter (below 2 nm hr −1 ) and highest in late spring and early summer (exceeding 5 nm hr −1 ). Temperature, turbulent kinetic energy, and aerosol properties were the primary factors of growth rate variability. This study advances predictive modeling of NPF, offers insights for future campaign deployments, and demonstrates the effectiveness of ML in understanding the formation and growth of atmospheric aerosols.
Employing Technology to Enable Remote Research Charrettes as a Method for Engaging Industry and Uncovering Best Practices: A Novel Approach for a Post-COVID-19 World
Methods to collect data in construction engineering and management (CEM) research are evolving, informed by recent technological advancements. One such method is research charrettes that allow effective interactions and knowledge sharing between expert industry practitioners and academic researchers, all colocated in a single venue, enabling rich data collection and live communication. A pivot point in technological evolution occurred with the COVID-19 pandemic, forcing a global shift to remote work. Hence, planned in-person research charrettes had to shift to remote sessions, relying on virtual conferencing platforms and online data collection mechanisms. Technology-enabled charrettes have allowed the authors to collect significantly richer data sets and ensure a more diverse representation of participants, while saving tremendous amounts of time. With the continuing emergence of technological applications, the world might not go back to functioning fully in person. The authors believe remote research charrettes (RRCs) will still be used in a post-COVID-19 world because of their superior performance. This paper builds on a previous publication that described traditional research charrettes as a method to enhance CEM research a decade ago; it offers a significantly updated and improved RRC method based on the knowledge gained from transitioning a dozen in-person charrettes into RRCs. It also presents performance comparisons between RRCs and traditional charrettes by quantifying metrics indicating how RRCs are more time-efficient and cost-saving, harness more participants from more diverse locations, and enable the collection of richer data sets and four times more industry comments and expert feedback. This paper also provides guidance on the integration of technology with traditional research charrettes, hence contributing to the CEM body of knowledge.
Assessment of DFT functionals for a minimal nitrogenase [Fe(SH) 4 H]- model employing state-of-the-art ab initio methods
We have designed a [Fe(SH)4H]- model with the fifth proton binding either to Fe or S. We show that the energy difference between these two isomers (ΔE) is hard to estimate with quantum-mechanical (QM) methods. For example, different density functional theory (DFT) methods give ΔE estimates that vary by almost 140 kJ/mol, mainly depending on the amount of exact Hartree–Fock included (0%–54%). The model is so small that it can be treated by many high-level QM methods, including coupled-cluster (CC) and multiconfigurational perturbation theory approaches. With extrapolated CC series (up to fully connected coupled-cluster calculations with singles, doubles, and triples) and semistochastic heat-bath configuration interaction methods, we obtain results that seem to be converged to full configuration interaction results within 5 kJ/mol. Our best result for ΔE is 101 kJ/mol. With this reference, we show that M06 and B3LYP-D3 give the best results among 35 DFT methods tested for this system. Brueckner doubles coupled cluster with perturbaitve triples seems to be the most accurate coupled-cluster approach with approximate triples. CCSD(T) with Kohn–Sham orbitals gives results within 4–11 kJ/mol of the extrapolated CC results, depending on the DFT method. Single-reference CC calculations seem to be reasonably accurate (giving an error of ~5 kJ/mol compared to multireference methods), even if the D1 diagnostic is quite high (0.25) for one of the two isomers.
Inverted organic tandem solar cells with a charge recombination stack employing spatially confined p-type electrical doping
We report on the application of solution-based p-type electrical doping using 12-molybdophosphoric acid hydrate (PMA) to the fabrication of organic tandem solar cells. Such a doping approach leads to a spatially confined vertical doping profile down to a limited depth from the surface of polymer films, thus allowing the hole-collecting component of the charge recombination stack to be embedded in the photoactive layer of the bottom sub-cell. This simplifies the device architecture by removing the need for an extra dedicated hole-collecting layer. It is shown that this novel charge recombination stack comprising a PMA-doped bottom photoactive layer and a trilayer of Ag/AZO/PEIE is compatible with a solution-processed top photoactive layer. Here, the fabricated inverted organic tandem solar cells exhibit an open-circuit voltage that is close to the sum of the open-circuit voltages of the individual sub-cells, and a fill factor that is close to the better fill factor of the two sub-cells.
Low-mode nonuniformity in direct-drive ICF implosions due to laser smoothing techniques employed on OMEGA
For successful laser-direct-drive inertial confinement fusion implosions, the laser irradiation must be highly uniform over the target surface. On OMEGA, multiple laser beams are used to illuminate targets quasi-uniformly. High-mode-number nonuniformities due to laser speckle on each individual beam are reduced by splitting each beam into two orthogonal polarizations (i.e., polarization smoothing, or PS) and a range of wavelengths (i.e., smoothing by spectral dispersion) that are dispersed at the target plane. However, cross-beam energy transfer (CBET) is sensitive to both the polarizations and wavelengths of the interacting beams, so the interplay between CBET and the laser-smoothing schemes results in unique intensity variation across each beam profile, which is a systematic source of low-mode drive nonuniformity on OMEGA. Here, we model these effects and find that the predicted ℓ = 1 mode in the laser-absorption distribution is consistent with the systematic core-flow direction that has been determined from the OMEGA implosion database. We also observe good agreement with the measured core-flow directions for two specific sets of implosions (one with PS, the other without PS) when we also account for the measured beam mispointing and the beam power imbalance.
Metal cofactor stabilization by a partner protein is a widespread strategy employed for amidase acti
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A Case for Nuclear Chemical Engineering in the Era of Fission and Fusion Reactors that Employ Molten Salts
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Evaluation of antifouling surfaces using a method that employs mussel larvae settlement quantified by machine learning
Antifouling coating development requires extensive performance testing. Coatings that prevent aquatic larval settlement are of interest because many forms of macrofouling begin at the larval stage. However, field testing can be time consuming and poorly controlled. Herein is reported a screening tool, Settlement of Larvae Assay using Mussels (SLAM), for down-selecting materials prior to field testing. The method entails using a dense concentration of mussel larvae that are allowed to settle on submerged test surfaces. Settled larvae are then quantified to provide a measure of antifouling performance. The SLAM test differentiated coatings with only slight differences in formulation. To enable efficient quantification of dense larvae settlement, an automated counting method was developed that combines two analyses: a color thresholding identifies larvae clumps, and a machine learning algorithm identifies non-clumped larvae. Finally, this automated ‘hybrid’ approach rapidly quantifies settled larvae as effectively as manual counting but in a fraction of the time.
Reconstructed lung doses for the million person study cohort of 26,650 Tennessee Eastman corporation workers employed between 1942 and 1947
Abstract Tennessee Eastman Corporation workers were exposed to uranium dust resulting in high-linear energy transfer (LET) irradiation to lung tissue. In this work, radiation lung doses were reconstructed for 26 650 men and women working at the plant between 1942 and 1947. Site air monitoring data of uranium concentrations and payroll records were used to determine the daily inhaled activities and annualized lung doses. Variations in the activity median aerodynamic diameter of the uranium dust, the solubility of particulate matter in the lungs and the sex-specific breathing rate were investigated as part of a sensitivity analysis. Male and female mean lung doses of 18.9 and 32.7 mGy, respectively, from high-LET alpha irradiation, and there was general agreement with evaluations from previously published epidemiological studies. Annual lung dose estimates and sensitivity analysis for the 26 650 workers in the TEC cohort have been archived on the United States Department of Energy Comprehensive Epidemiologic Data Resource.