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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 523 records · Page 29

Simultaneous structural and control optimization via linear quadratic regulator eigenstructure assignment

A method for simultaneous structural and control design of large flexible space structures (LFSS) to reduce vibration generated by disturbances is presented. Desired natural frequencies and damping ratios for the closed loop system are achieved by using a combination of linear quadratic regulator (LQR) synthesis and numerical optimization techniques. The state and control weighing matrices (Q and R) are expressed in terms of structural parameters such as mass and stiffness. The design parameters are selected by numerical optimization so as to minimize the weight of the structure and to achieve the desired closed-loop eigenvalues. An illustrative example of the design of a two bar truss is presented.

Becus, G. A.↗

Acoustic design considerations: Review of rotor acoustic sources

It is not sufficient to optimize a rotor design in terms of a single noise level calculated for a single flight condition and a single measurement location. The various noise sources, their frequency content, amplitude, and directivity as a function of operating condition must be considered. A summary of the frequency ranges, directivity patterns and the most important operational and design parameters for major rotor noise sources is presented. It is difficult to generalize design requirements for rotor noise because the acoustic output varies so widely depending on the noise source, flight condition, measurement location, and frequency range. However, assuming the rotor must lift a fixed nominal payload and operate over a wide range of flight conditions, three general design guidelines can be stated: (1) minimize tip Mach number; (2) minimize blade thickness in the tip region; and (3) minimize gradients in the spanwise lift distribution in the tip region. Constraints on blade thickness, maximum values for hover tip Mach number, advancing tip Mach number and spanwise lift coefficient gradient will be specified during the aerodynamic, dynamic and structural optimization process. The rotor noise sources to be considered include the low frequency loading and thickness noise, and the higher frequency noise due to blade-vortex interactions (BVI). The analyses to be employed will include the comprehensive rotor analysis and design program CAMRAD and the rotor noise prediction program WOPWOP.

Martin, Ruth M.↗

Density functional modeling of the binding energies between aluminosilicate oligomers and different metal cations

Interactions between negatively charged aluminosilicate species and positively charged metal cations are critical to many important engineering processes and applications, including sustainable cements and aluminosilicate glasses. In an effort to probe these interactions, here we have calculated the pair-wise interaction energies (i.e., binding energies) between aluminosilicate dimer/trimer and 17 different metal cations M n+ (M n+ = Li + , Na + , K + , Cu + , Cu 2+ , Co 2+ , Zn 2+ , Ni 2+ , Mg 2+ , Ca 2+ , Ti 2+ , Fe 2+ , Fe 3+ , Co 3+ , Cr 3+ , Ti 4+ and Cr 6+ ) using a density functional theory (DFT) approach. Analysis of the DFT-optimized structural representations for the clusters (dimer/trimer + M n+ ) shows that their structural attributes (e.g., interatomic distances) are generally consistent with literature observations on aluminosilicate glasses. The DFT-derived binding energies are seen to vary considerably depending on the type of cations (i.e., charge and ionic radii) and aluminosilicate species (i.e., dimer or trimer). A survey of the literature reveals that the difference in the calculated binding energies between different M n+ can be used to explain many literature observations associated with the impact of metal cations on materials properties (e.g., glass corrosion, mineral dissolution, and ionic transport). Analysis of all the DFT-derived binding energies reveals that the correlation between these energy values and the ionic potential and field strength of the metal cations are well captured by 2nd order polynomial functions ( R 2 values of 0.99–1.00 are achieved for regressions). Given that the ionic potential and field strength of a given metal cation can be readily estimated using well-tabulated ionic radii available in the literature, these simple polynomial functions would enable rapid estimation of the binding energies of a much wider range of cations with the aluminosilicate dimer/trimer, providing guidance on the design and optimization of sustainable cements and aluminosilicate glasses and their associated applications. Finally, the limitations associated with using these simple model systems to model complex interactions are also discussed.

Gong, Kai↗

Spectroscopic evidence of highly correlated electrons in $\mathrm{VSe_2}$

We present detailed high-resolution angle-resolved photoemission experiments on $\mathrm{VSe_2}$ grown under various conditions. The surface electronic structure optimally grown samples can host high-temperature spectral kink, quasiparticle peak, and the Fermi gap. Collective observation of these electronic features refers to the strong electronic correlation and is usually attributed to the characteristics of superconductors. Temperature evolution of the quasiparticle peak and the Fermi gap also follow the trend observed in high-$T_c$ superconductors as progressive quenching of the quasiparticle peak at a lower temperature than the complete Fermi gap closing. As a result, the quasiparticle peak can be observed up to 100 ± 5 K while the Fermi gap persists up to ~ 150 K. Importantly, these realizations can guide future studies to induce high-temperature superconductivity in transition metal dichalcogenides as well as understand the physics behind high-$T_c$ superconductors.

36 MATERIALS SCIENCE↗

Concurrent Enhancement of Acetylene Uptake Capacity and Selectivity by Progressive Core Expansion and Extra–Framework Anions in Pore–Space–Partitioned Metal–Organic Frameworks

A multi-stage core-expansion method is proposed here as one component of the integrative binding-site/extender/core-expansion (BEC) strategy. The conceptual deconstruction of the partitioning ligand into three editable parts draws our focus onto progressive core expansion and allows the optimization of both acetylene uptake and selectivity. Herein the effectiveness of this strategy is shown through a family of eight cationic pore-partitioned materials containing three different partitioning ligands and various counter anions. The optimized structure, Co 3 -cpt-tph-Cl (Hcpt=4-(p-carboxyphenyl)-1,2,4-triazole, H-tph=(2,5,8-tri-(4-pyridyl)-1,3,4,6,7,9-hexaazaphenalene) with the largest surface area and highest C 2 H 2 uptake capacity (200 cm 3 /g at 298 K), also exhibits (desirably) the lowest CO 2 uptake and hence the highest C 2 H 2 /CO 2 selectivity. The successful boost in both C 2 H 2 capacity and IAST selectivity allows Co 3 -cpt-tph-Cl to rank among the best crystalline porous materials, ionic MOFs in particular, for C 2 H 2 uptake and C 2 H 2 /CO 2 experimental breakthrough separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Construction of the Bioconjugate Py‐Macrodipa‐PSMA and Its In Vivo Investigations with Large 132/135 La 3+ and Small 47 Sc 3+ Radiometal Ions

To harness radiometals in clinical settings, a chelator forming a stable complex with the metal of interest and targets the desired pathological site is needed. Toward this goal, we previously reported a unique set of chelators that can stably bind to both large and small metal ions, via a conformational switch. Within this chelator class, py-macrodipa is particularly promising based on its ability to stably bind several medicinally valuable radiometals including large 132/135 La 3+ , 213 Bi 3+ , and small 44 Sc 3+ . Here, in this study, we report a 10-step organic synthesis of its bifunctional analogue py-macrodipa-NCS, which contains an amine-reactive −NCS group that is amenable for bioconjugation reactions to targeting vectors. The hydrolytic stability of py-macordipa-NCS was assessed, revealing a half-life of 6.0 d in pH 9.0 aqueous buffer. This bifunctional chelator was then conjugated to a prostate-specific membrane antigen (PSMA)-binding moiety, yielding the bioconjugate py-macrodipa-PSMA, which was subsequently radiolabeled with large 132/135 La 3+ and small 47 Sc 3+ , revealing efficient and quantitative complex formation. The resulting radiocomplexes were injected into mice bearing both PSMA-expressing and PSMA-non-expressing tumor xenografts to determine their biodistribution patterns, revealing delivery of both 132/135 La 3+ and 47 Sc 3+ to PSMA+ tumor sites. However, partial radiometal dissociation was observed, suggesting that py-macrodipa-PSMA needs further structural optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material properties in solid mechanics

Material identification is critical for understanding the relationship between mechanical properties and the associated mechanical functions. However, material identification is a challenging task, especially when the characteristic of the material is highly nonlinear in nature, as is common in biological tissue. In this work, we identify unknown material properties in continuum solid mechanics via physics-informed neural networks (PINNs). To improve the accuracy and efficiency of PINNs, we develop efficient strategies to nonuniformly sample observational data. We also investigate different approaches to enforce Dirichlet-type boundary conditions (BCs) as soft or hard constraints. Finally, we apply the proposed methods to a diverse set of time-dependent and time-independent solid mechanic examples that span linear elastic and hyperelastic material space. The estimated material parameters achieve relative errors of less than 1%. As such, this work is relevant to diverse applications, including optimizing structural integrity and developing novel materials.

97 MATHEMATICS AND COMPUTING↗

Matrimid substrates with bicontinuous surface and macrovoids in the bulk: A nearly ideal substrate for composite membranes in CO 2 capture

Scalable fabrication of thin-film composite (TFC) membrane for post-combustion carbon capture is often limited by the availability of high-performance nanoporous substrate. Ideally, the substrate should allow for fast gas transport at the selective layer/substrate interface as well as in the bulk of the substrate. In this study, highly permeable Matrimid substrates were prepared via vapor- and nonsolvent-induced phase separations. The phase separation mechanism of the Matrimid®/N-methyl-2-pyrrolidone casting solution was modulated by the addition of LiCl to control the solution thermodynamic stability, and nanoporous Matrimid substrates were formed with a bicontinuous surface and macrovoids in the bulk. This hierarchically optimized structure resulted in a CO 2 permeance of 2.60 × 10 5 GPU (1 GPU = 1 × 10 –6 cm 3 (STP) cm –2 s –1 cmHg –1 = 3.349 × 10 –10 mol m –2 s –1 Pa –1 ), which was ca. 11 times more permeable than a benchmark polyethersulfone substrate with cellular pores. The benefit of using this new substrate was demonstrated by coating a 170-nm amine-containing polymer to form a TFC facilitated transport membrane. The membrane exhibited a CO 2 permeance of 932 GPU at 57°C, which was 72 GPU higher than the counterpart coated on the benchmark substrate. Meanwhile, the CO 2 /N 2 selectivity was remained at 158. This permeance improvement could be well explained by the resistance-in-series model, where the improved permeance was attributed to the reductions in substrate and lateral diffusion mass transfer resistances. The upper bound (UB) analysis indicates that the Matrimid substrate is nearly ideal for the state-of-the-art polymers for CO 2 /N 2 separation. Here, the substrate improvement could also reduce the parasitic energy associated with the membrane process due to the reduced membrane cost and flue gas compression requirement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enhancing durability and activity toward oxygen evolution reaction using single-site Re-doped NiFeO x catalysts at ampere-level

NiFeO x materials are known as among the most active catalysts toward oxygen evolution reaction (OER) for hydrogen generation in alkaline media. Nevertheless, the long-term durability of NiFeO x catalysts for OER is still too far to the industrial application. Herein, we prepared a NiFeReO x catalyst with single-site Re dopants and observed that the single-site Re dopants could significantly enhance the durability without compromising the activity. A cell voltage of 1.82 V without iR correction is noted at the current density of 3000 mA cm –2 in anion-exchange membrane water electrolyzer (AEMWE) with NiFeReO x catalyst, and a very small degradation is observed under 2000 and 1000 mA cm –2 , which remarkably outperforms the pristine NiFeO x . Additionally, the overpotential of 305 mV at 10 mA cm –2 is achieved with the NiFeReO x catalyst, which is lower than 50 mV compared with the pristine NiFeO x catalyst, together with a smaller Tafel slope of 54.3 mV dec -1 . The boosted OER durability and activity of the NiFeReO x catalyst could be attributed to the strong electron-withdrawing property of Re 7+ single atoms leading to the electronic structure optimization and stabilization of Ni/Fe active sites. Our insights propose a new path for designing NiFeO x catalysts with high durability and activity toward OER.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

express: Extensible, high-level workflows for swifter ab initio materials modeling

In this work, we introduce an open-source Julia project, express, an extensible, lightweight, high-throughput, high-level workflow framework that aims to automate ab initio calculations for the materials science community. express is shipped with well-tested workflow templates, including structure optimization, equation of state (EOS) fitting, phonon spectrum (lattice dynamics) calculation, and thermodynamic property calculation in the framework of the quasi-harmonic approximation (QHA). It is designed to be highly modularized so that its components can be reused across various occasions, and customized workflows can be built on top of that. Users can also track the status of workflows in real-time, and rerun failed jobs thanks to the data lineage feature express provides. Finally, two working examples, i.e., all workflows applied to lime and akimotoite, are also presented in the code and this paper.

36 MATERIALS SCIENCE↗

Magnetism and finite-temperature effects in UZr 2 : A density functional theory analysis

The structure and the thermophysical properties of d-UZr 2 are investigated using 0 K density functional theory and ab initio molecular dynamics (AIMD). Modeling the true paramagnetic state of this intermetallic compound has been challenging using first-principles calculations. For the first time, we find that the generalized gradient approximation method without applying an on-site Coulomb interaction term (Hubbard U) can result in a ground state that is antiferromagnetic (AFM). We believe that this weak AFM ground state is the closest to the real paramagnetic state. We found that structure optimization at finite temperatures using AIMD is necessary to achieve this ground state instead of the non-magnetic and ferromagnetic states previously reported in the literature. Our findings indicate that applying the Hubbard U on uranium f-orbitals in this metallic system is unnecessary and not recommended, as it leads to a large overestimation of the volume and introduces an unphysical strong spin polarization. Finally, our approach results in atomic volume, thermal expansion, and heat capacities that have strong agreement with experiments.

36 MATERIALS SCIENCE↗

Effect of 3D-printed surface textures on wear mechanism in 3-body abrasion of soil

This study systematically investigates the enhancement of wear resistance in 3D printed surface textures through both experimental and theoretical approaches. Three distinct surface morphologies (Smooth Surface, Surface with uniformly distributed Pits, and Surface with uniformly distributed Bumps) were fabricated using High-Impact Polystyrene, where the meso-scale textures were precisely controlled through the 3D printing process. Wear behavior was evaluated using a 3-body wear tester in an abrasive particle environment, analyzing the influence of surface textures under various operating conditions. Systematic wear tests revealed that optimally designed surface textures achieved a remarkable 77 % reduction in wear compared to the worst-performing sample. The wear mechanisms were comprehensively characterized through weight loss measurements, Scanning Electron Microscopy (SEM), and Energy Dispersive Spectroscopy (EDS) analyses, elucidating the surface morphology changes and their interaction with wear particles. Notably, the study identified how the geometric characteristics of surface textures influence the movement of wear particles and the distribution of contact stresses. Discrete element method simulations corroborated the experimental findings, providing theoretical validation for the enhanced wear resistance of the optimal structure. The high correlation between simulated wear patterns and experimental results validates the reliability of the proposed design methodology. In conclusion, these results demonstrate that 3D printed surface texturing offers a cost-effective and scalable approach to significantly improve wear resistance in engineering applications, presenting a practical alternative to conventional, high-cost surface engineering methods.

3-body abrasion↗

Next-Generation Reverse Logistics Networks of Photovoltaic Recycling: Perspectives and Challenges

With the growing adoption of solar energy as a key component of the global energy transition and its new industrial policy (the Inflation Reduction Act and others), the United States is witnessing a significant increase in solar investments. This surge in installations and domestic and reshored manufacturing of solar photovoltaic (PV) panels brings with it a pressing issue: the proper management of end-of-life (EoL) PV panels. As these panels are decommissioned, either due to reaching the end of their lifespans or due to breakage across the various stages of the forward supply chain, it becomes crucial to establish efficient reverse supply chain logistics systems to address the challenges associated with their disposal, while also unlocking the value of the inherent materials that are of critical value for other forward supply chains. This perspective article examines the challenges regarding EoL PV panels and relevant reverse supply chain and logistics networks, and proposes future research directions based on the gaps observed among academic research, industry, and policy-making challenges. We identify the main bottlenecks and hurdles including, among others, the lack of supportive regulations and absence of structured, optimized recycling infrastructure. To this end, it is proposed that the key to achieving a sustainable reverse supply chain network for solar PV panels lies in relentless end-to-end supply chain cost optimization efforts supported by enabling policies. Moreover, it is proposed that designing systematic decision-making modeling frameworks is vital for examining different possibilities and scenarios for state, region or nation-wide optimization of solar PV reverse supply chain networks. Indicative to this effect, we discuss the development of a Resource-Task-Network (RTN)-based model and demonstrate its application and benefits through a case study. We wrap up with conclusions and future research directions.

circular economy↗

Computationally Guided Investigation of the Optical Spectra of Pure β-UO 3

Single-phase β-UO 3 is synthesized by flash heating UO 2 (NO 3 )·6H 2 O in air to 450 °C and annealing for 60 h under the same conditions. For the first time, we report the Raman spectra of pure β-UO 3 . To facilitate the assignment of Raman and infrared vibrational modes, we use density functional theory with density functional perturbation theory. By employing a novel analysis scheme that includes the mode frequencies as well as a quantitative analysis of the mode eigenvectors, we assign the observed spectral features to individual chemical modes. In particular, the density functional theory optimized structure, observed Raman spectrum, and eigenvector analysis suggest the presence of four crystallographically distinct uranyl ions, one more than has previously been suggested.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interplay between London Dispersion, Hubbard U , and Metastable States for Uranium Compounds

High-throughput computational studies of lanthanide and actinide chemistry with density-functional theory are complicated by the need for Hubbard U corrections, which ensure localization of the f-electrons, but can lead to metastable states. This work presents a systematic investigation of the effects of both Hubbard U value and metastable states on the predicted structural and thermodynamic properties of four uranium compounds central to the field of nuclear fuels: UC, UN, UO 2 , and UCl 3 . We also assess the impact of the exchange-hole dipole moment (XDM) dispersion correction on the computed properties. Overall, the choice of Hubbard U value and inclusion of a dispersion correction cause larger variations in the computed geometric properties than result from metastable states. Further, the weak dependence of structure optimization on metastable states should simplify future high-throughput calculations on actinides. Conversely, addition of the dispersion correction is found to offset the repulsion introduced by the Hubbard U term and provides greatly improved agreement with experiment for both cell volumes and heats of formation. The XDM dispersion correction is largely invariant to the chosen U value, making it a robust dispersion correction for actinide systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

More Than 30 000-fold Field Enhancement of Terahertz Nanoresonators Enabled by Rapid Inverse Design

The rapid development of 6G communications using terahertz (THz) electromagnetic waves has created a demand for highly sensitive THz nanoresonators capable of detecting these waves. Among the potential candidates, THz nanogap loop arrays show promising characteristics but require significant computational resources for accurate simulation. This requirement arises because their unit cells are 10 times smaller than millimeter wavelengths, with nanogap regions that are 1 000 000 times smaller. To address this challenge, we propose a rapid inverse design method using physics-informed machine learning, employing double deep Q-learning with an analytical model of the THz nanogap loop array. In ~39 h on a middle-level personal computer, our approach identifies the optimal structure through 200 000 iterations, achieving an experimental electric field enhancement of 32 000 at 0.2 THz, 300% stronger than prior results. In conclusion, our analytical model-based approach significantly reduces the amount of computational resources required, offering a practical alternative to numerical simulation-based inverse design for THz nanodevices.

21 terahertz time-domain spectroscopy↗