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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 1,657 records · Page 92

Comparison of Experimental Measurements of Thermal Conductivity of Fe{sub 2}O{sub 3} Nanofluids Against Standard Theoretical Models and Artificial Neural Network Approach

In the present work, the practicability of Fe{sub 2}O{sub 3} nanofluids for heat transfer applications has been examined. Nanofluids performance, in terms of modulation of thermal conductivity, has been investigated with increasing concentration of Fe{sub 2}O{sub 3} nanoparticles in water and ethylene glycol base fluids at 10, 20, 30, 40, 50, 60 and 70 °C. Fe{sub 2}O{sub 3} nanoparticles have been synthesized using the wet chemical method and characterized using TEM, SEM, XRD and UV–Vis. The characterization results revealed a face-centered cubic structure having alpha phase and particle size in the range of 40-55 nm for the synthesized Fe{sub 2}O{sub 3} nanoparticles. Thermal conductivity measurement results show increases in thermal conductivity with the increase in concentration and temperature of nanofluids. 16.45 and 19.76% enhancement in thermal conductivity have been observed for Fe{sub 2}O{sub 3}–water and Fe{sub 2}O{sub 3}–ethylene glycol nanofluids of 2 vol.% at 70 °C compared to water and ethylene glycol base fluids at 10 °C, respectively. Results of the ANN approach are in good agreement with experimental results, and H–C model gives better predictions compared to other standard models. The study gives clear insights into improved heat transfer performance by material engineering.

36 MATERIALS SCIENCE↗

Artificial neural network algorithms for pulse shape discrimination and recovery of piled-up pulses in organic scintillators

We developed two neural-network (NN)-based algorithms (fully-connected neural network (Fc-NN) and recurrent neural network (RNN)) to perform pulse shape discrimination (PSD) and identification of piled-up pulses produced by organic scintillators, upon interaction with neutrons and gamma rays. We tested the algorithms on measured and verification sets of data and compared their classification performances to standard approaches. At a high acquisition count rate (100,000 counts per second, cps), in the presence of a gamma-to-neutron ratio of approximately 400–1, the proposed NN-based algorithm achieves a fraction of misclassified neutron, gamma, and piled-up pulses of approximately 1%, 1.8%, and 0.6%, respectively. Compared to the traditional approach, it exhibits 3×, 14×, and 11× improved (lower) miscalculation rates for neutron, gamma, and piled-up pulses, respectively. Here, we also demonstrate the capability of NN-based algorithms of successfully recovering and identifying neutron and gamma ray compositions from piled-up pulses in challenging, high pulse count rate conditions.

42 ENGINEERING↗

Molecular simulation and artificial intelligence for the circular economy of bioenergy and bioproducts

The concept of the circular bioeconomy is a carbon neutral, sustainable system with zero waste. One vision for such an economy is based upon lignocellulosic biomass. This lignocellulosic circular bioeconomy requires CO 2 absorption from biomass growth and the efficient deconstruction of recalcitrant biomass into solubilized and fractionated biopolymers, which are then used as precursors for the sustainable production of high-quality liquid fuels, chemical bioproducts, and bio-based materials. Here, in this study, we summarize the roles that molecular dynamics (MD) simulations and machine learning (ML) are playing in overcoming several fundamental challenges hindering the adoption of a circular bioeconomy. Specifically, we discuss the role of MD and ML/AI in overcoming lignocellulose recalcitrance by designing biomass pretreatment methods to efficiently produce solubilized cellulose/lignin/hemicellulose and of that in improving energy-intensive manufacturing of biomass-based materials and their structural and mechanical properties. Quantum mechanical methods and MD simulations, in addition to offering a mechanistic understanding of biomass deconstruction and biomaterials design, can provide meaningful structural, energetics, and physiochemical properties as inputs to train AI/ML models. The ML models can guide the experimental prioritization of materials/solvents and process parameters that significantly accelerate the development of biofuel and biomaterial components of the circular bioeconomy.

Smith, Jeremy C. [Oak Ridge National Laboratory (O↗

Artificial Transmembrane Channel Constructed from Shape-Persistent Covalent Organic Molecular Cages Capable of Ion and Small Molecule Transport

Shape-persistent arylene ethynylene molecular cages have been investigated as transmembrane channels for ions and small molecules. The molecular cages were obtained starting from tetrayne monomers through alkyne metathesis cyclooligomerization. We found these porphyrin-based rigid molecular cages can insert into the lipid bilayer and efficiently transport ions and small molecules (e.g., calcein). Our study reveals longer hydrophobic alkyl chains on the cage molecule promote the channeling efficiency, while shorter and/or more polar side chains impair such activity. Kinetic analysis shows linear correlation between the rate of proton transport and the concentration of the cage, suggesting the active species is likely a monomeric cage. We found that C70-encapsulated cages are nearly inactive for transmembrane ion transportation, indicating that ions are likely transported through the internal cavity of the cage. Discrete shape-persistent organic cages represent highly stable synthetic ion channels or pores, which could have interesting applications in biomimetic signaling and drug delivery.

alkyne metathesis↗

Quantifying the effects of artificial aging on the ignition and self-propagating reactions of Ni(V)/Al multilayers

Bimetallic, reactive multilayers are uniformly structured materials composed of alternating nanoscale layers that may be ignited to produce self-propagating intermetallic-formation reactions. When reactive multilayers age, there is a change in local composition and loss of stored chemical energy due to mass transport and rearrangement at the interfaces. Here, to quantify the long-term reliability of commercial Ni(V)/Al multilayers, the effects of accelerated aging on both ignition sensitivity and self-propagating reactions have been examined. Thermally aged samples were characterized using transmission electron microscopy, differential scanning calorimetry, and laser ignition combined with high-speed videography. The analytically quantifiable nature of both continuous wave laser ignition and reactive wave propagation enabled calculations of Arrhenius rate constants for as-received and various heat-treated multilayers. With heat treatment, there is a change in the intermixed thickness and interfacial chemistry that decreases the activation energy for point ignition but increases it for self-propagating reactions. This finding implies that with increased thermal aging, the reaction becomes easier to facilitate in the solid state but harder in the liquid phase.

Energetic material↗

Electrochemical stability, physical, and electronic properties of thermally pre-formed oxide compared to artificially sputtered oxide on Fe thin films in aqueous chloride

Here the electrochemical stability and corrosion behavior of the thermally pre-oxidized and sputter deposited variant of an oxide single-crystalline Fe thin film were compared. Thermal oxides formed Fe 2 O 3 over an inner layer of Fe 3 O 4 while the sputtered oxides were found to have grown Fe 3 O 4 instead of the target stoichiometry of Fe 2 O 3 . Oxide films of both types were stable in pH=9.3 borate buffer solution, however, were altered in pH=9.3, 0.1 M NaCl solution in the case of thermally pre-oxidized Fe thin film. The stability of the oxide differed in pH=4, 0.1 M NaCl where sputtered Fe films were more stable against acidic chemical dissolution than the thermally formed Fe oxide film. These differences were traced by AC/DC electrochemical analysis including electronic defect densities, and molecular identity characterized by ex-situ X-ray photoelectron spectroscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Influence of artificial aging on corrosion of abraded Al-Zn-Mg-Cu alloys

Surface abrasion has been shown to create altered surface layers (ASLs) that are hundreds of nm thick on all types of Al alloys. Such ASLs have lower corrosion resistance than the underlying substrate of Al-Zn-Mg-Cu alloys. Here, we demonstrate how heat treatments affect the ASL microstructure on abraded Al-Zn-Mg-Cu alloys using transmission electron microscopy and atom probe tomography, and also how the corrosion properties change using electrochemical polarization. Additionally, high temperature treatments on the abraded bulk samples enhance η phase precipitation in the ASL, leading to a decreased Zn content in the ASL solid solution, which ennobles the ASL breakdown potential.

36 MATERIALS SCIENCE↗