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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Systematic Design and Experimental Demonstration of Transmission-Type Multiplexed Acoustic Metaholograms

Acoustic holograms have promising applications in sound-field reconstruction, particle manipulation, ultrasonic haptics, and therapy. This study reports on the theoretical, numerical, and experimental investigation of multiplexed acoustic holograms at both audio and ultrasonic frequencies via a rationally designed transmission-type acoustic metamaterial. The proposed metahologram is composed of two Fabry–Pérot resonant channels per unit cell, which enables the simultaneous modulation of the transmitted amplitude and phase at two desired frequencies. In contrast to conventional acoustic metamaterial-based holograms, the design strategy proposed here provides a new degree of freedom (frequency) that can actively tailor holograms that are otherwise completely passive and significantly enhances the information encoded in acoustic metamaterials. To demonstrate the multiplexed acoustic metamaterial, the projection of two different high-quality metaholograms is first shown at 14 and 17 kHz, with the patterns of the letters N and S. Then, two-channel ultrasound focusing and annular beams generation for the incident ultrasonic frequencies of 35 and 42.5 kHz are demonstrated. Furthermore, these multiplexed acoustic metaholograms offer a technical advance to tackle the rising challenges in the fields of acoustic metamaterials, architectural acoustics, and medical ultrasound.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Layered Transition Metal Oxides as Ca Intercalation Cathodes: A Systematic First-Principles Evaluation

Finding high-voltage Ca cathode materials is a critical step to unleashing the full potential of high-energy-density Ca-ion batteries. Therefore, first-principles calculations are used to demonstrate that P-type layered calcium transition metal (TM) oxide materials (CaTM 2 O 4 ) with a range of TM substitutions (TM = Ti, V, Cr, Mn, Fe, Co, and Ni) have excellent battery-related properties including thermodynamic stability, average voltage, energy density, synthesizability, ionic mobility, and electronic structure. However, the thermodynamic stability of the charged phase and TM redox activity are shown to be sensitive to TM selection, with CaCo 2 O 4 having the best balance of all considered properties. The utility of combining multiple TMs to expand the chemical search space for TM substitutions is demonstrated by mixing Co and Ni in layered CaTM 2 O 4 .

25 ENERGY STORAGE↗
DOE OSTI2023

US FDA Postmarketing Requirements and Commitments: A Systematic Assessment of Clinical Pharmacology Studies and Their Impact on US FDA Prescribing Information

Abstract Many of the conditions for the safe and effective use of new molecular entities (NMEs) are understood at the time of initial drug approval. However, some remaining knowledge gaps can be addressed after drug approval through postmarketing requirements (PMRs) or commitments (PMCs) established by the US Food and Drug Administration (FDA). Our objective was to conduct an assessment of clinical pharmacology–related PMRs and PMCs established at the time of approval and evaluate the impact of fulfilled PMRs and PMCs on prescription information (PI). This analysis included clinical pharmacology–related PMRs and PMCs established for NMEs approved between 2009 and 2020. Of the 1171 PMRs and PMCs, over one‐third were clinical pharmacology–related. Of these, 46% were to evaluate drug interactions, 16% were to evaluate drug dosing in patients with hepatic impairment, and 10% were related to dose. The majority (57%) of PMRs and PMCs were fulfilled at the time of analysis, with a median time to fulfillment of approximately 2.3 years. The majority (94%) of the fulfilled PMRs and PMCs, either with or without a PI revision, resulted in new or modified instructions for use or supported existing instructions for use. This is the first time that clinical pharmacology–related PMRs and PMCs have been catalogued and analyzed to understand their impact on PI. An understanding of the knowledge gaps that exist at the time of drug approval could inform the most effective and efficient methods for evidence generation prior to and after new drug approval.

Pharmacology & Pharmacy↗
DOE OSTI2022

Systematically testing singlet models for $(g - 2)_{μ}$

We comprehensively study all viable new-physics scenarios that resolve the muon $(g - 2)_{μ}$ anomaly with only Standard Model singlet particles coupled to muons via renormalizable interactions. Since such models are only viable in the MeV–TeV mass range and require sizable muon couplings, they predict abundant accelerator production through the same interaction that resolves the anomaly. We find that a combination of fixed-target $(\text {NA64}μ, M^{3})$, B-factory (BABAR, Belle II), and collider (LHC, muon collider) searches can cover nearly all viable singlets scenarios, independently of their decay modes. In particular, future muon collider searches offer the only certain test of singlets above the GeV scale, covering all higher masses up to the TeV-scale unitarity limit for these models. Intriguingly, we find that $ \mathcal{O}\left(100\ \mathrm{GeV}\right) $ muon colliders may yield better coverage for GeV-scale singlets compared to TeV-scale concepts, which has important implications for the starting center-of-mass energy of a staged muon collider program.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

A systematic study of hidden sector dark matter: application to the gamma-ray and antiproton excesses

In hidden sector models, dark matter does not directly couple to the particle content of the Standard Model, strongly suppressing rates at direct detection experiments, while still allowing for large signals from annihilation. In this paper, we conduct an extensive study of hidden sector dark matter, covering a wide range of dark matter spins, mediator spins, interaction diagrams, and annihilation final states, in each case determining whether the annihilations are s-wave (thus enabling efficient annihilation in the universe today). We then go on to consider a variety of portal interactions that allow the hidden sector annihilation products to decay into the Standard Model. We broadly classify constraints from relic density requirements and dwarf spheroidal galaxy observations. In the scenario that the hidden sector was in equilibrium with the Standard Model in the early universe, we place a lower bound on the portal coupling, as well as on the dark matter’s elastic scattering cross section with nuclei. We apply our hidden sector results to the observed Galactic Center gamma-ray excess and the cosmic-ray antiproton excess. We find that both of these excesses can be simultaneously explained by a variety of hidden sector models, without any tension with constraints from observations of dwarf spheroidal galaxies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

A systematic comparison of machine learning methods for modeling of dynamic processes applied to combustion emission rate modeling

Ten established, data-driven dynamic algorithms are surveyed and a practical guide for understanding these methods generated. Existing Python programming packages for implementing each algorithm are acknowledged, and the model equations necessary for prediction are presented. A case study on a coal-fired power plant’s NO x emission rates is performed, directly comparing each modeling method’s performance on a mutual system. Each model is evaluated by its root mean squared error (RMSE) on out-of-sample future horizon predictions. Optimal hyperparameters are identified using either an exhaustive search or genetic algorithm. The top five model structures of each method are used to recursively predict future NO x emission rates over a 60-step time horizon. The RMSE at each future timestep is determined, and the recursive output prediction trends compared against measurements in time. The GRU neural network is identified as the best candidate for representing the system, demonstrating accurate and stable predictions across the future horizon by all considered models, while satisfactory performance was observed in several of the ARX/NARX formulations. Finally, these efforts have contributed 1) a concise resource of multiple proven dynamic machine learning methods, 2) a practical guide explaining the use of these methods, effectively lowering the “barrier-to-entry” of deploying such models in control systems, 3) a comparison study evaluating each method’s performance on a mutual system, 4) demonstration of accurate multi-timestep emissions modeling suitable for systems-level control, and 5) generalizable results demonstrating the suitability of each method for prediction over a multi-step future horizon to other complex dynamic systems.

42 ENGINEERING↗