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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Process-Specific Effects of Sulfate on CaCO 3 Formation in Environmentally Relevant Systems

Additives, such as ions, small molecules, and macromolecules, have been found to regulate the formation of CaCO 3 and control its morphologies and properties. However, a single additive usually affects dominantly one process in CaCO 3 's formation and is seldom found to significantly affect multiple CaCO 3 formation processes. In this work, we used in situ grazing incidence X-ray techniques to observe the heterogeneous formation of CaCO 3 and found that a series of formation processes (i.e., nucleation, growth, and Ostwald ripening) were modulated by sulfate. In the nucleation process, increased interfacial free energy and bulk free energy cooperatively increased the nucleation barrier and decreased nucleation rates. In the growth process, sulfate reduced the electrostatic repulsion between CaCO 3 precursors and nuclei, promoting CaCO 3 growth. This influence on the growth counteracted the inhibition effect in the nucleation process, causing a nearly 100% increase in the volume of heterogeneously formed CaCO 3 . Meanwhile, adsorbed sulfate on CaCO 3 nuclei may poison the surface of smaller CaCO 3 nuclei, inhibiting Ostwald ripening. These revealed sulfate's active roles in controlling CaCO 3 formation advance our understanding of sulfate-incorporated biomineralization and scaling phenomena in natural and engineered aquatic environments.

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

Rapid Quantification of 237 U Specific Activity for Nuclear Forensics

In the event of an unattributed nuclear explosion, rapid assessment of the short-lived uranium isotope activity and mass can provide valuable information for subsequent forensic analysis. Rapid analysis in the field is enabled by using microfluidic chemistry and deployable instrumentation. Here, this work presents a flow chemistry system, controlled in LabVIEW, that integrates three functionalities: (1) selective extraction of uranium from the sample matrix via a 3D-printed supported liquid membrane module; (2) UV–visible absorbance spectrophotometry to measure the total uranium concentration in the strip flow; and (3) a portable CdTe γ-ray spectrometer coupled to a 3D-printed flow cell to measure 237 U activity concentration in the strip solution. The system was calibrated using standard solutions, and its functionality was demonstrated using a solution of depleted uranium spiked with 237 U. Uranium concentrations of 40–5000 μg/mL were directly quantified online using a 100 mm optical flow cell, while concentrations of 0.5–10 μg/mL were quantified online using a colorimetric reagent. The mass concentration measurement takes approximately 60 min while the activity concentration via γ-ray spectrometry varies depending on the activity of 237 U, with 1 kBq/mL requiring about 30 min of acquisition time to obtain <10% uncertainty at 1σ. This platform provides a fieldable approach for quantifying uranium mass and radioactivity relevant to postdetonation nuclear debris.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Surfactant-Specific AI-Driven Molecular Design: Integrating Generative Models, Predictive Modeling, and Reinforcement Learning for Tailored Surfactant Synthesis

Molecular design is a critical aspect of various scientific and industrial fields, where the properties of molecules hold significant importance. In this study, a 3-fold methodology design is presented that leverages the power of generative artificial intelligence (AI), predictive modeling, and reinforcement learning to create tailored molecules with desired properties. This model synergistically combines deep learning techniques with Self-Referencing Embedded Strings (SELFIES) molecular representation to build a generative model that generates valid molecules and a graphical neural network model that accurately forecasts molecular properties. The Variational Autoencoder (VAE) coupled with reinforcement learning helps refine molecule generation based on targeted attributes. Data from an experimental study involving surfactants were used to test the framework. A validation of the structural integrity of the molecules generated was conducted, and Tanimoto similarities were used to quantify the similarity and diversity between the original and generated molecular structures. Also, saliency maps for the generated surfactants were produced to identify the features explaining the property values. Lastly, molecular dynamics simulations were used to validate the stability of the generated molecules. The results showed that the proposed framework can effectively produce valid molecules within the set property threshold value.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Element-Specific Study of Magnetic Anisotropy and Hardening in SmCo 5– x Cu x Thin Films

This work investigates the effect of copper substitution on the magnetic properties of SmCo 5 thin films synthesized by molecular beam epitaxy. A series of thin films with varying concentrations of Cu were grown under otherwise identical conditions to disentangle structural and compositional effects on the magnetic behavior. The combined experimental and theoretical studies show that Cu substitution at the Co 3g sites not only stabilizes the formation of the SmCo 5 structure but also enhances magnetic anisotropy and coercivity. Density functional theory calculations indicate that Sm(Co 4 Cu 3g ) 5 possesses a higher single-ion anisotropy as compared to pure SmCo 5 . In addition, X-ray magnetic circular dichroism reveals that Cu substitution causes an increasing decoupling of the Sm 4f and Co 3d moments. Scanning transmission electron microscopy confirms predominantly SmCo 5 phase formation and reveals nanoscale inhomogeneities in the Cu and Co distribution. Our study based on thin film model systems and advanced characterization as well as modeling reveals novel aspects of the complex interplay of intrinsic and extrinsic contributions to magnetic hysteresis in rare-earth-based magnets, i.e., the combination of increased intrinsic anisotropy due to Cu substitution and the extrinsic effect of inhomogeneous elemental distribution of Cu and Co.

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

N 5 -Scaling Excited-State-Specific Perturbation Theory

In this paper, we show that by working in a basis similar to that of the natural transition orbitals and using a modified zeroth-order Hamiltonian, the cost of a recently introduced perturbative correction to excited-state mean field theory can be reduced from seventh to fifth order in the system size. The (occupied) 2 (virtual) 3 asymptotic scaling matches that of ground-state second-order Møller-Plesset theory but with a significantly higher prefactor because the bottleneck is iterative: it appears in the Krylov-subspace-based solution of the linear equation that yields the first-order wave function. Here, we discuss the details of the modified zeroth-order Hamiltonian we use to reduce the cost and the automatic code generation process we used to derive and verify the cost scaling of the different terms. Overall, we find that our modifications have little impact on the method's accuracy, which remains competitive with singles and doubles equation-of-motion coupled cluster.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗