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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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Light-driven hydrogen production from Photosystem I-catalyst hybrids
Solar energy conversion of water into environmentally clean fuels, such as hydrogen, offers one of the best long-term solutions for meeting future global energy needs. In photosynthesis, high quantum yield charge separation is achieved by a series of rapid, photoinitiated electron transfer steps that take place in proteins called reaction centers (RCs). Of current interest are new strategies that couple RC photochemistry to the direct synthesis of energy-rich molecules, offering opportunities to more directly tune the products of photosynthesis and potentially to increase solar energy conversion capacity. Innovative designs link RC photochemistry with synthetic molecular catalysts to create earth abundant biohybrid complexes that use light to rapidly produce hydrogen from water.
Hydrothermal catalytic deoxygenation of palmitic acid over nickel catalyst
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Exploiting basic principles to control the selectivity of the vapor phase catalytic oxidative cross-coupling of primary alcohols over npAu catalysts
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Comparative Study on the Machine Learning-Based Prediction of Adsorption Energies for Ring and Chain Species on Metal Catalyst Surfaces
Computation of adsorption and transition state energies for a large number of surface intermediates for numerous active site models pose significant computational overhead in computational screening of catalysts. Machine learning (ML) techniques can be used to predict part of these energies. To predict the energies, ML models need to be fed appropriate metal and species descriptors. For complex surface chemistries, the structures of the intermediate species can vary greatly. In this paper, working with the hydrodeoxygenation of succinic acid on six different metal surfaces, we have studied the effect of linear and non-linear ML models used along with pen-and-paper based species descriptors and two categories of metal descriptors on two different categories of intermediate species: chain and ring. More specifically, our computations include the prediction of chain species when trained on only chain species and also when trained on both chain and ring species. Similar computations were performed for predictions of ring species. In each case, results of linear ML models were compared with kernel based non-linear models. Our results indicate that ring species data does not improve the prediction of chain species. Similarly, chain species data does not improve the prediction of ring species. The use of non-linear ML models, however, did help to minimize the prediction errors compared to the linear models. Furthermore, the study also shows that electronic or adsorption energy based metal descriptors along with bond count based species fingerprints can achieve a mean absolute error (MAE) of less than 0.2 eV for complex chain molecules when used with an appropriate machine learning model.
Validation of Methods for Computational Catalyst Design: Geometries, Structures, and Energies of Neutral and Charged Silver Clusters
We report a systematic study of small silver clusters, Agn, Agn+, and Agn–, n = 1–7. We studied all possible isomers of clusters with n = 5–7. We tested 42 exchange–correlation functionals, and we assess these functionals for their accuracy in three respects: geometries (quantitative prediction of internuclear distances), structures (the nature of the lowest-energy structure, for example, whether it is planar or nonplanar), and energies. We find that the ingredients of exchange–correlation functionals are indicators of their success in predicting geometries and structures: local exchange–correlation functionals are generally better than hybrid functionals for geometries; functionals depending on kinetic energy density are the best for predicting the lowest-energy isomer correctly, especially for predicting two-dimensional to three-dimenstional transitions correctly. The accuracy for energies is less sensitive to the ingredient list. Our findings could be useful for guiding the selection of methods for computational catalyst design.
Preferred Orientation of a Physisorbed Molecular Catalyst and Implications for Selectivity
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Characterizing substrate–surface interactions on alumina-supported metal catalysts by dynamic nuclear polarization-enhanced double-resonance NMR spectroscopy [Characterizing substrate-surface interactions on alumina supported metal catalysts by DNP-enhanced double-resonance NMR spectroscopy]
The characterization of nanometer-scale interactions between carbon-containing substrates and alumina surfaces is of paramount importance to industrial and academic catalysis applications, but it is also very challenging. Here, we demonstrate that dynamic nuclear polarization surface-enhanced NMR spectroscopy (DNP SENS) allows the unambiguous description of the coordination geometries and conformations of the substrates at the alumina surface through high-resolution measurements of 13 C– 27 Al distances. We apply this new technique to elucidate the molecular-level geometry of 13 C-enriched methionine and natural abundance poly(vinyl alcohol) adsorbed on γ-Al 2 O 3 -supported Pd catalysts, and we support these results with element-specific X-ray absorption near-edge measurements. Furthermore, this work clearly demonstrates a surprising bimodal coordination of methionine at the Pd–Al 2 O 3 interface.
Composite Ni/NiO-Cr2O3 Catalyst for Alkaline Hydrogen Evolution Reaction
We report a Ni-Cr/C electrocatalyst with unpreeedented massactivity for the hydrogen evolution reaction (HER). in alkaline electrolyte. The HER Oietics of numerous binary and ternary Ni-alloys and composite Ni/metal-euride/C samples were evaluated in aquebus 0.1 M KOH electrolyte. The highest HER mass-activity was observed for Ni-Cr materials which exhibit metallic Ni as well as NiOx and Cr2O3 phases as determined by X-ray diffraction (XRD) and X-ray absorption spectroscopy (XAS) analysis. The onset of the HER is significantly improved compared to munerous binary dor ternary Ni-alloys, inCluding Ni Mg materials. It is likely that at adjacent Ni/NiOx sites, the oxide acts as a sink for OHads, while the metallic Ni acts as a, sink for the H-ads, intermediate of the HER, thus minimizing the high activation energy of hydrogen evolution via water reduction. This is confirmed by in situ XAS studies that show that the synergistic HER enhancement is due to NiO content and that the Cr2O3 appears to stabilize the composite NiO component-under HER conditions (where NiOx would typically be reduced to metallic Ni-0). Furthermore, in contrast to Pt, the Ni(O-x)/Cr2O3 catalyst appears resistant to poisoning by the anion.exchange ionomer (AEI), a serloua consideration when applied to an anionic polymer electrolyte interface. Furthermore, we report a: detailed model of the double layer interface which helps explain the observed ensemble effect in the presence of AEI.
Balancing activity, stability and conductivity of nanoporous core-shell iridium/iridium oxide oxygen evolution catalysts [Balancing activity, stability and conductivity of nanoporous core-shell Ir/IrO 2 oxygen evolution catalysts]
The selection of oxide materials for catalyzing the Oxygen Evolution Reaction in acid-based electrolyzers must be guided by the proper balance between activity, stability and conductivity – a challenging mission of great importance for delivering affordable and environmentally friendly hydrogen. Here we report that the highly conductive nanoporous architecture of an iridium oxide shell on a metallic iridium core, formed through the fast dealloying of osmium from an Ir 25 Os 75 alloy, exhibits an exceptional balance between oxygen evolution activity and stability as quantified by the Activity-Stability FactorASF. Based on this metric, the nanoporous Ir/IrO 2 morphology of dealloyed Ir 25 Os 75 shows a factor of ~30 improvement ASFrelative to conventional Ir-based oxide materials and a ~8 times improvement over dealloyed Ir 25 Os 75 nanoparticles due to optimized stability and conductivity, respectively. Here, we propose that the Activity-Stability FactorASF is the key “metric” for determining the technological relevance of oxide-based anodic water electrolyzer catalysts.
Lignin depolymerization over Ni/C catalyst in methanol, a continuation: effect of substrate and catalyst loading
In conversion of lignin the product spectrum and yield vary significantly across catalyst loading and biomass type and origin.
Highly active Au/δ-MoC and Au/β-Mo 2 C catalysts for the low-temperature water gas shift reaction: effects of the carbide metal/carbon ratio on the catalyst performance
In this paper, the water gas shift (WGS) reaction catalyzed by orthorhombic β-Mo 2 C and cubic δ-MoC surfaces with and without Au clusters supported thereon has been studied by means of a combination of sophisticated experiments and state-of-the-art computational modeling. Experiments evidence the importance of the metal/carbon ratio on the performance of these systems, where Au/δ-MoC is presented as a suitable catalyst for WGS at low temperatures owing to its high activity, selectivity (only CO 2 and H 2 are detected), and stability (oxycarbides are not observed). Periodic density functional theory-based calculations show that the supported Au clusters and the Au/δ-MoC interface do not take part directly in water dissociation but their presence is crucial to switch the reaction mechanism, drastically decreasing the effect of the reverse WGS reaction and favoring the WGS products desorption, thus leading to an increase in CO 2 and H 2 production. Finally, the present results clearly display the importance of the Mo/C ratio and the synergy with the admetal clusters in tuning the activity and selectivity of the carbide substrate.
Mesoporous cobalt/manganese oxide: a highly selective bifunctional catalyst for amine–imine transformations
Here, we discuss a heterogeneous catalytic protocol using cobalt doped mesoporous manganese oxide for amine–alcohol cross-coupling to selectively produce symmetric or asymmetric imines. Thorough investigations on the surface chemistry and physical properties of the material revealed its outstanding oxidation–reduction properties and reaction mechanism which was supported by quantum mechanical calculations done by using density functional theory (DFT).
Selective hydroxylation of aryl iodides to produce phenols under mild conditions using a supported copper catalyst
Atomically dispersed Cu catalyst was designed for highly efficient hydroxylation of aryl iodides under mild conditions.
Catalyst-layer ionomer imaging of fuel cells
Investigation of membrane/electrode assembly (MEA) microstructure has become an essential step to optimize the MEA components and manufacturing processes or to study the MEA degradation. For these investigations, transmission electron microscopy (TEM) is a tool of choice as it provides direct imaging of the different components. TEM is then widely used for analyzing the catalyst nanoparticles and their carbon support. However, the ionomer inside the electrode is more difficult to be imaged. The difficulties come from the fact that the ionomer forms an ultrathin layer surrounding the carbon particles and in addition, these two components, having similar density, present no difference in contrast. In this paper, we show how the recent progresses in TEM techniques as spherical aberration (Cs) corrected HRTEM, electron tomography and X-EDS elemental mapping provide new possibilities for imaging this ionomer network and consequently to study its degradation.