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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 1,045 records · Page 58

Operational Implementation of a Pc Uncertainty Construct for Conjunction Assessment Risk Analysis

Earlier this year the NASA Conjunction Assessment and Risk Analysis (CARA) project presented the theoretical and algorithmic aspects of a method to include the uncertainties in the calculation inputs when computing the probability of collision (Pc) between two space objects, principally uncertainties in the covariances and the hard-body radius. The output of this calculation approach is to produce rather than a single Pc value an entire probability density function that will represent the range of possible Pc values given the uncertainties in the inputs and bring CA risk analysis methodologies more in line with modern risk management theory. The present study provides results from the exercise of this method against an extended dataset of satellite conjunctions in order to determine the effect of its use on the evaluation of conjunction assessment (CA) event risk posture. The effects are found to be considerable: a good number of events are downgraded from or upgraded to a serious risk designation on the basis of consideration of the Pc uncertainty. The findings counsel the integration of the developed methods into NASA CA operations.

assessment↗

Mechanisms of water oxidation on heterogeneous catalyst surfaces

Water oxidation, an essential step in photosynthesis, has attracted intense research attention. Understanding the reaction pathways at the electrocatalyst/water interface is of great importance for the development of water oxidation catalysts. How the water is oxidized on the electrocatalyst surface by the positive charges is still an open question. This review summarizes current advances in studies on surface chemistry within the context of water oxidation, including the intermediates, reaction mechanisms, and their influences on the reaction kinetics. The Tafel analyses of some electrocatalysts and the rate-laws relative to charge consumption rates are also presented. Moreover, how the multiple charge transfer relies on the intermediate coverage and the accumulated charge numbers is outlined. Finally, the intermediates and rate-determining steps on some water oxidation catalysts are discussed based on density functional theories.

14 SOLAR ENERGY↗

Spin–Orbit Matrix Elements for a Combined Spin-Flip and IP/EA approach

We introduce a practical approach for computing the Breit–Pauli spin–orbit matrix elements of multiconfigurational systems with both spin and spatial degeneracies based on our recently developed RAS-nSF-IP/EA method (Houck, S. E.; et al. J. Chem. Theory Comput. 2019, 15, 2278). The spin–orbit matrix elements over all the multiplet components are computed using a single one-particle reduced density matrix as a result of the Wigner–Eckart theorem. A mean field spin–orbit approximation was used to account for the two-electron contributions. Basis set dependence as well as the effect of including additional excitations is presented. The effect of correlating the core and semicore orbitals is also examined. Surprisingly accurate results are obtained for spin–orbit coupling constants, despite the fact that the efficient wave function approximations we research neglect the bulk of dynamical correlation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ligand Coverage and Exciton Delocalization Control Chiral Imprinting in Perovskite Nanoplatelets

Chiral perovskites have generated significant recent interest, yet little is known about how their chiro-optical properties arise. In this study, chiral methylammonium lead halide perovskite nanoplatelets (NPLs) with varied halide and ligand compositions are prepared using direct synthetic methods. Circular dichroism (CD) and 1 H NMR studies find a non-linear relationship between the chiroptical properties and the ratio of chiral phenylethylammonium (PEA) to achiral octylamine (OA) ligands on the NPL surface. We use density functional theory (DFT) computations and a chiral imprinted particle-in-a-box model to rationalize the experimentally observed CD spectra and find that the saturation point of the induced chirality depends on the size of the perovskite exciton relative to the size of the ligands. Temperature-dependent CD and 1 H NMR studies, combined with DFT analysis, show that both the CD intensity and sign depend strongly on the structure and orientation of the ligands. Furthermore, this work reveals the complex nature of chiral imprinting in perovskite nanostructures and establishes a simple physical model for ligand-induced chiral imprinting to guide the further development of chiral materials.

36 MATERIALS SCIENCE↗

Giant spontaneous polarization for enhanced ferroelectric properties of biaxially oriented poly(vinylidene fluoride) by mobile oriented amorphous fractions

Poly(vinylidene fluoride) (PVDF) and its random copolymers exhibit the most distinctive ferroelectric properties; however, their spontaneous polarization (60–105 mC m -2 ) is still inferior to those (>200 mC m -2 ) of the ceramic counterparts. In this work, we report an unprecedented spontaneous polarization ( P s = 140 mC m -2 ) for a highly poled biaxially oriented PVDF (BOPVDF) film, which contains a pure β crystalline phase. Given the crystallinity of ~0.52, the P s for the β phase ( P s,β ) is calculated to be 279 mC m -2 , if a simple two-phase model of semicrystalline polymers is assumed. This high P s,β is invalid, because the theoretical limit of P s,β is 185 mC m -2 , as calculated by density functional theory. To explain such a high P s for the poled BOPVDF, a third component in the amorphous phase must participate in the ferroelectric switching to contribute to the P s . Namely, an oriented amorphous fraction (OAF) links the lamellar crystal and the mobile amorphous fraction. From the hysteresis loop study, the OAF content was determined to be ~0.28, more than 50% of the amorphous phase. Because of the high polarizability of the OAFs, the dielectric constant of the poled BOPVDF reached nearly twice the value of conventional PVDF. Overall, the fundamental knowledge obtained from this study will provide a solid foundation for the future development of PVDF-based high performance electroactive polymers for wearable electronics and soft robotic applications.

36 MATERIALS SCIENCE↗

Machine learning reveals factors that control ion mobility in anti-perovskite solid electrolytes

Solid-state batteries are projected to exhibit improved energy densities and safety compared to liquid-electrolyte-based systems. Consequently, the development of solid electrolytes that can conduct cations at rates comparable to that of liquid electrolytes is an active area of research. To facilitate this search it is desirable to understand the chemical and structural features that control ion transport through a crystalline lattice. Here, machine learning (ML) is used to identify features that influence ion mobility in solids, quantify the relative importance of those features, and demonstrate how the variation of individual features alters ion mobility. Adopting the anti-perovskite lattice as a model system, ML algorithms were trained to predict migration barriers from a data set containing hundreds of barriers calculated using density functional theory. In this study, more than 10 6 feature sets of non-redundant descriptors were evaluated for their ability to predict migration barriers. The present analysis correctly reiterates the importance of several features that are known to influence mobility – for example, anion polarizability – but also identifies others whose importance is not widely recognized. Lattice properties such as hopping distance and channel width exhibit the greatest influence on cation mobility. Individual conditional expectation analyses performed on these features shows that barriers decrease as hopping distance decreases and as channel width increases. The defect formation energy – which is commonly associated with the concentration of defects, but not with their mobility – is identified as an important feature for interstitial migration. In sum, this analysis aids in the design of optimal solid electrolytes by simplifying the multi-dimensional design space to a sub-set of properties that are the most important.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Novel Catalysts and Processing Technologies for Production of Aerospace Fuels from Non-Petroleum Raw Materials

Transportation fuels production (including aerospace propellants) from non-traditional sources (gases, waste materials, and biomass) has been an active area of research and development for decades. Reducing terrestrial waste streams simultaneous with energy conversion, plentiful biomass, new low-cost methane sources, and/or extra-terrestrial resource harvesting and utilization present significant technological and business opportunities being realized by a new generation of visionary entrepreneurs. We examine several new approaches to catalyst fabrication and new processing technologies to enable utilization of these nontraditional raw materials. Two basic processing architectures are considered: a single-stage pyrolysis approach that seeks to basically re-cycle hydrocarbons with minimal net chemistry or a two-step paradigm that involves production of supply or synthesis gas (mainly carbon oxides and H2) followed by production of fuel(s) via Sabatier or methanation reactions and/or Fischer-Tröpsch synthesis. Optimizing the fraction of product stream relevant to targeted aerospace (and other transportation) fuels via modeling, catalyst fabrication and novel reactor design are described. Energy utilization is a concern for production of fuels for either terrestrial or space operations; renewable sources based on solar energy and/or energy efficient processes may be mission enabling. Another important issue is minimizing impurities in the product stream(s), especially those potentially posing risks to personnel or operations through (catalyst) poisoning or (equipment) damage. Technologies being developed to remove (and/or recycle) heteroatom impurities are briefly discussed as well as the development of chemically robust catalysts whose activities are not diminished during operation. The potential impacts on future missions by such new approaches as well as balance of system issues are addressed.

space processing↗

Multireference Methods for Chemistry and Materials Science: Automated Active Spaces, Efficient Dynamic Correlation, and Extended Systems

While multiconfigurational approaches have long been relegated to expert practitioners working on a case-by-case basis, recent developments have increasingly made these methods more routine and applicable to broader sets of systems. This article outlines the state-of-the-art in multiconfigurational approaches, with an emphasis on moving from delicate hand-selected pathways through configuration space toward more robust and efficient approaches to treating a host of challenging chemical systems accurately. First, we overview recent work in automated active-space selection, which has enabled increasingly large-scale applications of multireference methods to modeling vertical excitations and reactivity. Second, we highlight the increasingly efficient methods for recovering correlation energy beyond the active space, as headlined by extensions of pair-density functional theory and its role in accurate and efficient treatment of excited-state dynamics and its utilization to train machine-learned potentials. Finally, we highlight recent efforts to treat extended systems that until recently have lied beyond the traditional limits of active-space methods, giving center stage to product-form wave functions of the localized active space family of methods that allow for the computation of multiconfigurational band structures. These recent advancements point to a broader use of multireference approaches for high-impact chemical and materials science applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Vibrationally resolved optical excitations of the nitrogen-vacancy center in diamond

A comprehensive description of the optical cycle of spin defects in solids requires the understanding of the electronic and atomistic structure of states with different spin multiplicity, including singlet states which are particularly challenging from a theoretical standpoint. We present a general framework, based on spin-flip time-dependent density function theory, to determine the excited state potential energy surfaces of the many-body singlet states of spin defects; we then predict the vibrationally resolved absorption spectrum between singlet shelving states of a prototypical defect, the nitrogen-vacancy center in diamond. Our results, which are in very good agreement with experiments, provide an interpretation of the measured spectra and reveal the key role of specific phonons in determining absorption processes, and the notable influence of non-adiabatic interactions. The insights gained from our calculations may be useful in defining strategies to improve infrared-absorption-based magnetometry and optical pumping schemes. The theoretical framework developed here is general and applicable to a variety of other spin defects and materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Multicolor polymeric carbon dots: synthesis, separation and polyamide-supported molecular fluorescence

Multicolor carbon dots (CDs) have been developed recently and demonstrate great potential in bio-imaging, sensing, and LEDs. However, the fluorescence mechanism of their tunable colors is still under debate, and efficient separation methods are still challenging. Herein, we synthesized multicolor polymeric CDs through solvothermal treatment of citric acid and urea in formamide. Automated reversed-phase column separation was used to achieve fractions with distinct colors, including blue, cyan, green, yellow, orange and red. This work explores the physicochemical properties and fluorescence origins of the red, green, and blue fractions in depth with combined experimental and computational methods. Three dominant fluorescence mechanism hypotheses were evaluated by comparing time-dependent density functional theory and molecular dynamics calculation results to measured characteristics. We find that blue fluorescence likely comes from embedded small molecules trapped in carbonaceous cages, while pyrene analogs are the most likely origin for emission at other wavelengths, especially in the red. Also important, upon interaction with live cells, different CD color fractions are trafficked to different sub-cellular locations. Super-resolution imaging shows that the blue CDs were found in a variety of organelles, such as mitochondria and lysosomes, while the red CDs were primarily localized in lysosomes. These findings significantly advance our understanding of the photoluminescence mechanism of multicolor CDs and help to guide future design and applications of these promising nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Learning Vacancy Formation Energy in Nickel-Based Superalloys

Thermal vacancies play a critical role in high-temperature Ni-based superalloys and influence various properties such as creep resistance, oxidation, etc. This study systematically investigates the impact of commonly used transition metals (Cr, Co, Fe), refractory metals (Nb, Ta, Mo, W) and other elements (Al, Cu, Ti, Mn) on the thermodynamic stability of 36 binary, 20 ternary, 11 quaternary, 9 quinary, and 3 senary FCC Ni-based alloys covering various elemental combinations. Density functional theory-based studies on Ni-X binary alloys show that higher concentrations of Cr, Nb, Ta, Al, and Ti introduce significant lattice distortions and broaden the distribution of vacancy formation energies (standard deviation up to 0.15 eV). These elements partially donate electrons, reducing their self-consistent chemical potentials relative to single-element reference values and lowering vacancy formation energies, while Co, Fe, Mo, and W show lower charge localization. These trends extend from 3-6 element alloys, where Cr, Nb, and Ta-rich compositions have low-energy states (~0.5 eV) that increase vacancy concentrations. Finally, graph neural network models are developed to screen over 5000 virtual alloys. Eleven leading compositions are identified with mean vacancy formation energy higher than 1.75 eV and vacancy concentration ~2 orders of magnitude lower than pure Ni at 1000 K. These results provide valuable guidelines to achieve controlled defect engineering in structural alloys.

DFT↗

Cobalt‐Doped Bismuth Nanosheet Catalyst for Enhanced Electrochemical CO 2 Reduction to Electrolyte‐Free Formic Acid

Electrochemical carbon dioxide (CO 2 ) reduction reaction (CO 2 RR) to valuable liquid fuels, such as formic acid/formate (HCOOH/HCOO − ) is a promising strategy for carbon neutrality. Enhancing CO 2 RR activity while retaining high selectivity is critical for commercialization. To address this, we developed metal-doped bismuth (Bi) nanosheets via a facile hydrolysis method. These doped nanosheets efficiently generated high-purity HCOOH using a porous solid electrolyte (PSE) layer. Among the evaluated metal-doped Bi catalysts, Co-doped Bi demonstrated improved CO 2 RR performance compared to pristine Bi, achieving ~90 % HCOO − selectivity and boosted activity with a low overpotential of ~1.0 V at a current density of 200 mA cm −2 . In a solid electrolyte reactor, Co-doped Bi maintained HCOOH Faradaic efficiency of ~72 % after a 100-hour operation under a current density of 100 mA cm −2 , generating 0.1 M HCOOH at 3.2 V. Density functional theory (DFT) results revealed that Co-doped Bi required a lower applied potential for HCOOH generation from CO 2 , due to stronger binding energy to the key intermediates OCHO* compared to pure Bi. In conclusion, this study shows that metal doping in Bi nanosheets modifies the chemical composition, element distribution, and morphology, improving CO 2 RR catalytic activity performance by tuning surface adsorption affinity and reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pursuing Heteroleptic Ligand Design Principles for Photoactive Fe Complexes with Ultrafast X-ray Emission and Variable-Temperature Optical Spectroscopies

Understanding the key parameters that govern the photophysical and photochemical properties of transition metal complexes is essential for the development of efficient photosensitizers for photocatalytic applications. Achieving this objective necessitates clear and detailed investigations of their electronic excited states, for which time-resolved metal Kβ X-ray emission spectroscopy (XES) has proven highly effective. Here, we present a time-resolved Fe Kβ XES study of a heteroleptic Fe(II) polypyridyl carbene complex, [Fe(phen) 2 (C 4 H 10 N 4 )] 2+ (1; phen = 1,10-phenanthroline), utilizing both the valence-to-core and Kβ mainline spectral regions, complemented by variable-temperature transient optical absorption (VT-TA) spectroscopy. Detailed analysis of the time-resolved Kβ XES data, supported by density functional theory (DFT) calculations and an Eyring analysis of the VT-TA data, reveals parallel excited state relaxation dynamics that support an assignment of the long-lived excited state to a triplet metal-centered state. Placing these results in the context of prior studies of heteroleptic Fe(II) polypyridyl cyanide complexes motivated a series of DFT calculations to investigate the effects of ligand structural flexibility and arrangement. These calculations reinforce the experimentally derived conclusion that constraining structural flexibility with multidentate ligands significantly impacts the excited state relaxation dynamics. Furthermore, our study emphasizes that the arrangement of strong field ligands in heteroleptic complexes substantially affects the energy of Jahn–Teller active triplet metal-centered states in low-spin d 6 metal complexes. Together, these findings provide synthetic design principles for extending metal-to-ligand charge transfer excited state lifetimes of heteroleptic Fe complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Critical role of acceptor dopants in designing highly stable and compatible proton-conducting electrolytes for reversible solid oxide cells

Proton-conducting electrolytes are receiving increasing attention due to their high ionic conductivity at intermediate temperatures, enabling the operation of solid oxide cells with high energy efficiency at low cost. However, the effect of B-site dopants on the properties of doped barium hafnate-cerate electrolyte materials, especially in single cells under operating conditions, has not been systematically studied. Here we report our findings in the development of a series of proton-conducting electrolytes with a general formula of BaHf 0.1 Ce 0.7 R 0.2 O 3–δ (BHCR172, R = Yb, Er, Y, Gd, Sm). Here, the results reveal that electrical conductivity, ionic transference number, chemical stability against steam and CO 2 , and compatibility with NiO during sintering are all closely correlated with the dopant size. In particular, the reaction with NiO is found to strongly affect the properties of the electrolytes and hence cell performance. Among all tested compositions, BaHf 0.1 Ce 0.7 Yb 0.2 O 3–δ (BHCYb172) shows excellent chemical stability and minimal reactivity towards NiO, as predicted from density functional theory (DFT)-based calculations and confirmed by experimental results. In addition, proton-conducting reversible solid oxide cells (P-ReSOCs) based on the optimized electrolyte composition, BHCYb172, demonstrate exceptional performance and stability, achieving a remarkable peak power density of 1.74 W cm –2 (O 2 as the oxidant) at 600 °C in the fuel cell mode and a high current density of 2.0 A cm –2 at 1.3 V and 600 °C in the steam electrolysis mode while maintaining excellent durability for over 1000 h.

25 ENERGY STORAGE↗

Role of electron correlation on the adenine dimer interaction for non-equilibrium geometries: a benchmark Quantum Monte Carlo study

The accurate description of non-covalent interactions is critical for understanding the structure, dynamics, and eventual function of biomolecules. The adenine dimer serves as a benchmark system for computational methods due to its role in nucleic acid structures and its rich conformational landscape. In this study, we employ benchmark diffusion quantum Monte Carlo (DMC) methods to investigate the relative energies and role of electron correlation on a set of adenine dimer conformations generated via a search of the potential energy landscape using the global optimizer algorithm. Relative DMC energies are compared against a wide range of density functional theory (DFT) approximation results. We find that although most of the DFT functionals perform well for low-energy structures, their accuracy varies significantly for higher-energy conformations, including stacked and T-shaped structures. A large fraction of the variation is due to the treatment of the van der Waals interaction. BLYP, B3LYP, and PBE0 significantly improve with added D4 dispersion, while the recent r2SCAN-D4 and ωB97M-V functionals show the least scatter and closest agreement with the DMC. These findings highlight the delicate nature of these interactions in biomolecular systems and provide guidance for simulations of their structure and dynamics and for the development of machine learned interatomic potentials.

Washburn, Laurel [ORNL] (ORCID:0000000324179335)↗

Surrogate models for linear response

Linear response theory is a well-established method in physics and chemistry for exploring excitations of many-body systems. In particular, the quasiparticle random-phase approximation (QRPA) provides a powerful microscopic framework by building excitations on top of the mean-field vacuum; however, its high computational cost limits model calibration and uncertainty quantification studies. Here, we present two complementary QRPA surrogate models and apply them to study response functions of finite nuclei. One is a reduced-order model that exploits the underlying QRPA structure, while the other utilizes the recently developed parametric matrix model algorithm to construct a map between the system’s Hamiltonian and observables. Our benchmark applications, the calculation of the electric dipole polarizability of 180 Yb and the 𝛽-decay half-life of 80 Ni, show that both emulators can achieve 0.1%–1% accuracy while offering a 6–7 orders of magnitude speedup compared to state-of-the-art QRPA solvers. These results demonstrate that the developed QRPA emulators are well positioned to enable Bayesian calibration and large-scale studies of computationally expensive physics models describing the properties of many-body systems.

Beta decay↗

Heterostructure engineering for wurtzite LaN

Wurtzite LaN (wz-LaN) is a semiconducting nitride with favorable piezoelectric and ferroelectric properties, making it promising for applications in electronics. Here, we use first-principles density functional theory with a hybrid functional to investigate several features that are key for its use in heterostructures. First, for the purposes of growing wz-LaN on a substrate or designing a heterostructure, we show that it can be lattice-matched with a number of cubic materials along their [111] axes. We also evaluate the bound charge at such interfaces, taking into account both the polarization discontinuity and the piezoelectric polarization due to pseudomorphic strain. Second, we investigate band alignments and assess the results for interfaces with zincblende-, rocksalt-, and perovskite-structure compounds, along with chemically similar wurtzite and rocksalt nitrides. Our results provide guidance for the development of electronic devices based on wz-LaN.

36 MATERIALS SCIENCE↗

Computational design of high entropy alloy coating for hydrogen turbine applications

This project aims to develop novel high entropy alloy (HEA)-based coatings to protect critical components in hydrogen-fueled turbine power system. The HEA-coatings will demonstrate superior performance in hydrogen combustion environment to commercial NiCoCrAlY coating in current natural gas turbine system. The HEA coating facilitates the formation of a protective scale of alpha-alumina to slow down the inward diffusion of oxidizing species and the outward diffusion of metal elements, and possesses ultrahigh corrosion and spallation resistance to prolong the service lifetime of critical components in hydrogen turbine power system. Aimed to accelerate the discovery of novel HEA coating compositions, high throughput computational modeling including CALPHAD and density functional theory and machine learning are performed to predict phase stability, oxygen permeability, oxidation rate constant, coefficient of thermal expansion, and mechanical properties. Based on the modeling and machine learning prediction, experimental validation is performed. Preliminary results will be presented and approaches to minimize oxidation will be discussed.

alloy design↗