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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Photoactive Blend Morphology Engineering through Systematically Tuning Aggregation in All-Polymer Solar Cells

Polymer aggregation plays a critical role in the miscibility of materials and the performance of all-polymer solar cells (APSCs). However, many aspects of how polymer texturing and aggregation affect photoactive blend film microstructure and photovoltaic performance are poorly understood. Here the effects of aggregation in donor–acceptor blends are studied, in which the number-average molecular weights (Mns) of both an amorphous donor polymer, poly[4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b;4,5-b]dithiophene-2,6-diyl-alt-(4-(2-ethylhexyl)-3-fluorothieno[3,4-b]thiophene-)-2-carboxylate-2-6-diyl)] (PBDTT-FTTE) and a semicrystalline acceptor polymer, poly{[N,N'-bis(2-octyldodecyl)naphthalene-1,4,5,8-bis(dicarboximide)-2,6-diyl]-alt-5,5'-(2,2'-bithiophene)} (P(NDI2OD-T2)) are systematically varied. The photovoltaic performance is correlated with active layer microstructural and optoelectronic data acquired by in-depth transmission electron microscopy, grazing incidence wide-angle X-ray scattering, thermal analysis, and optical spectroscopic measurements. Coarse-grained modeling provides insight into the effects of polymer aggregation on the blend morphology. Notably, the computed average distance between the donor and the acceptor polymers correlates well with solar cell photovoltaic metrics such as short-circuit current density (Jsc) and represents a useful index for understanding/predicting active layer blend material intermixing trends. Importantly, these results demonstrate that for polymers with different texturing tendencies (amorphous/semicrystalline), the key for optimal APSC performance, photovoltaic blend morphology can be controlled via both donor and acceptor polymer aggregation.

bio-inspired↗
DOE OSTI2019

Amphoteric Indium Enables Carrier Engineering to Enhance the Power Factor and Thermoelectric Performance in n -Type Ag n Pb 100 In n Te 100+2 n (LIST)

The Ag and In co-doped PbTe, Ag n Pb 100 In n Te 100+2n (LIST), exhibits n-type behavior and features unique inherent electronic levels that induce self-tuning carrier density. Results show that In is amphoteric in the LIST, forming both In 3+ and In 1+ centers. Through unique interplay of valence fluctuations in the In centers and conduction band filling, the electron carrier density can be increased from ≈3.1 × 10 18 cm -3 at 323 K to ≈2.4 × 10 19 cm -3 at 820 K, leading to large power factors peaking at ≈16.0 μWcm -1 K -2 at 873 K. The lone pair of electrons from In + can be thermally continuously promoted into the conduction band forming In 3+ , consistent with the amphoteric character of In. Moreover, with rising temperature, the Fermi level shifts into the conduction band, which enlarges the optical band gap based on the Moss–Burstein effect, and reduces bipolar diffusion and thermal conductivity. Adding extra Ag in LIST improves the electrical transport properties and meanwhile lowers the lattice thermal conductivity to ≈0.40 Wm -1 K -1 . Here, the addition of Ag creates spindle-shaped Ag 2 Te nanoprecipitates and atomic-scale interstitials that scatter a broader set of phonons. As a result, a maximum ZT value ≈1.5 at 873 K is achieved in Ag 6 Pb 100 InTe 102 (LIST).

36 MATERIALS SCIENCE↗
DOE OSTI2019

Systems Metabolic Engineering of Escherichia coli Improves Coconversion of Lignocellulose-Derived Sugars

Currently, microbial conversion of lignocellulose-derived glucose and xylose to biofuels is hindered by the fact that most microbes (including Escherichia coli [E. coli], Saccharomyces cerevisiae, and Zymomonas mobilis) preferentially consume glucose first and consume xylose slowly after glucose is depleted in lignocellulosic hydrolysates. In this study, E. coli strains are developed that simultaneously utilize glucose and xylose in lignocellulosic biomass hydrolysate using genome-scale models and adaptive laboratory evolution. E. coli strains are designed and constructed that coutilize glucose and xylose and adaptively evolve them to improve glucose and xylose utilization. Whole-genome resequencing of the evolved strains find relevant mutations in metabolic and regulatory genes and the mutations’ involvement in sugar coutilization is investigated. The developed strains show significantly improved coconversion of sugars in lignocellulosic biomass hydrolysates and provide a promising platform for producing next-generation biofuels.

Kim, Joonhoon↗
DOE OSTI2018

Grain boundary engineering to control the discontinuous precipitation in multicomponent U10Mo alloy

Grain boundaries in metallic alloys often play a crucial role, not only in determining the mechanical properties or thermal stability of alloys, but also in dictating the phase transformation kinetics during thermomechanical processing. We demonstrate that locally stabilized structure and compositional segregation at grain boundaries—“grain boundary complexions”—in a complex multicomponent alloy can be modified to influence the kinetics of cellular transformation during subsequent thermomechanical processing. Using aberration-corrected scanning transmission electron microscopy and atom probe tomography analysis of a metallic nuclear fuel highly relevant to worldwide nuclear non-proliferation efforts —uranium-10 wt% molybdenum (U-10Mo) alloy, new evidence for the existence of grain boundary complexion is provided. We then modified the concentration of impurities dissolved in Υ-UMo grain interiors and/or segregated to Υ-UMo grain boundaries by changing the homogenization treatment, and these effects were used used to retard the kinetics of cellular transformation during subsequent sub-eutectoid annealing in this U-10-Mo alloy during sub-eutectoid annealing. Thus, this work provided insights on tailoring the final microstructure of the U-10Mo alloy, which can potentially improve the irradiation performance of this important class of alloy fuels.

Devaraj, Arun (ORCID:0000000313146212)↗
DOE OSTI2020

A Probabilistic Model-Based Diagnostic Framework for Nuclear Engineering Systems

A fault diagnostic framework was investigated in this study for applications in thermal–hydraulic systems of nuclear power plants. The proposed framework consists of quantitative model-based diagnosis, statistical change detection and probabilistic reasoning. The use of physics-based diagnostic models provides high detection sensitivity and allows noise and measurement uncertainty to be incorporated robustly. Performance-related parametric models for each component are constructed based on first principles. Numerical model residuals are generated using the concept of analytical redundancy. Statistical change detection methods are employed to detect non-zero residuals in the presence of uncertainty. The diagnosis task is performed using Bayesian inference to detect and localize possible faults. Application to a single-phase heat exchanger for demonstration showed that the proposed probabilistic framework can provide improved results in comparison with traditional approaches while remaining less sensitive to false alarms in the presence of measurement and modeling uncertainty.

Bayesian network↗