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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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Single unit process fabrication of a responsive Ag nanoparticle (NP) chemical hydrogel composite is achieved through digital visible light processing (DLP) 3D printing of a self-assembled nanostructured (multilamellar) resin doped with Ag( i ).
The impact of a single yttria (Y 2 O 3 ) nanoparticle onto a yttria substrate was studied as a function of particle velocity (300–1200 m/s) and diameter (5–12 nm) for three particle orientations and two substrate orientations using molecular dynamics simulations. Impacts resulted in minimal dislocation motion but extensive disordering of the crystal lattice without approaching the melting temperature. The resulting amorphous microstructure was both precisely coincident with plastic strain and retained until the end of the simulation, suggesting a deformation mechanism of amorphization-facilitated viscous flow. Further analysis revealed that the degree of amorphization depended primarily on the impact velocity and secondarily on the orientations of the particle and substrate, with significant second-order effects from variable interactions.
Heterojunctions are an important strategy for designing high performance electrical sensor materials and related devices. Herein, a new type of metal-semiconductor hybrid nanoparticle has been successfully used to remarkably sensitize the surface of ZnO nanowires for detecting NO 2 with high responses over a broad temperature window ranging from room temperature to 600 °C. These hybrid nanoparticles are comprised of iron oxide nanowires with well dispersed single crystalline Au nanoparticles. The hybrid nanoparticle decorated ZnO nanowires have achieved a giant response, as high as 74 500 toward NO 2 gas, about 42 times that of Au decorated ZnO nanowire sensors. This dramatic enhancement may be attributed to the efficient charge transfer across the Au–Fe 2 O 3 Schottky and Fe 2 O 3 –ZnO semiconductor heterojunction interfaces. Due to the incorporation of thermally-stable Fe 2 O 3 nanoparticles as the support of Au nanoparticles, the working temperature of nanowire sensors was successfully extended to higher temperatures, with an increase of 200 °C, from 400 °C to 600 °C. Such a combination of semiconductor heterojunction and semiconductor-metal Schottky contact presents a new strategy for designing high performance electrical sensors with high sensitivity, stability, selectivity, and wide operation temperature window, which are potentially suitable for advanced energy systems such as automotive engines and power plants.
A novel employment of single particle-inductively coupled plasma-mass spectrometry (SP-ICP-MS) was developed, where a microextraction (ME) probe is used to sample nanoparticles from a surface and analyze them in a single analytical step. The effects of several parameters on the performance of ME-SP-ICP-MS were investigated, including the flow rate, choice of carrier solution, particle size, and the design of the microextraction probe head itself. The optimized ME-SP-ICP-MS technique was used to compare the extraction efficiency (EE, defined as the ratio of particles measured to particles deposited on the surface) of the commercial probe head to a newly designed SP polyether ether ketone (PEEK) probe head. The SP PEEK probe head was found to have increased EE compared to the commercial probe head (8.5 ± 3% vs 3.9 ± 3%, respectively). Increasing the carrier solution flow rate was found to decrease the total analysis time at the cost of decreasing EE. Extraction efficiencies for ME-SP-ICP-MS were typically 4–10%, which is similar to transport efficiencies (1–10%) for conventional SP-ICP-MS. Lastly, ME-SP-ICP-MS was employed for the analysis of nano- and microparticles. The sizes of gold nanoparticles, 30 ± 3 and 51 ± 1.9 nm (certified sizes), and iron-based microparticles, 1000 ± 50 nm (certified size), were accurately determined to be 32.2 ± 2.5, 50.8 ± 3.4, and 1030 ± 57 nm, respectively, by ME-SP-ICP-MS. Further, this work demonstrates the potential of ME-SP-ICP-MS for the direct analysis of particles on common collection surfaces (GSR tabs, carbon planchettes, etc.) while retaining spatial information on particle distribution across the surface.
CO oxidation on Pt group metals is affected by the metal size and reducibility of the oxide support. In this study, we report that Ir supported on MgAl 2 O 4 , traditionally considered non-reducible, exhibits properties similar to reducible oxides when the Ir size is in the subnanometer regime. To show this effect, we synthesized subnanometer Ir clusters and compared their properties to single atoms and nanoparticles (1–1.5 nm). The CO oxidation activity is highest on Ir 0.6–0.8nm while showing distinctly different reaction orders in CO and O 2 (0, +0.4), than single atoms (1, 0) and nanoparticles (–1, +1). Microcalorimetry, in situ X-ray absorption, and infrared spectroscopies show that the CO-saturated Ir 0.6–0.8nm clusters could adsorb and activate O 2 despite binding CO more strongly than nanoparticles. Density functional theory calculations on CO saturated Ir 4 clusters suggest that the increased activity is due to the ability to activate O 2 on oxygen vacancies at the Ir–MgAl 2 O 4 interface. The findings show the important effect of the metal nuclearity on the support and catalyst properties and can guide future design of CO oxidation catalysts.
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Ebola virus (EBOV) glycoprotein (GP) can be recognized by neutralizing antibodies (NAbs) and is the main target for vaccine design. Here, we first investigate the contribution of the stalk and heptad repeat 1-C (HR1 C ) regions to GP metastability. Specific stalk and HR1 C modifications in a mucin-deleted form (GPΔmuc) increase trimer yield, whereas alterations of HR1 C exert a more complex effect on thermostability. Crystal structures are determined to validate two rationally designed GPΔmuc trimers in their unliganded state. We then display a modified GPΔmuc trimer on reengineered protein nanoparticles that encapsulate a layer of locking domains (LD) and a cluster of helper T-cell epitopes. In mice and rabbits, GP trimers and nanoparticles elicit cross-ebolavirus NAbs, as well as non-NAbs that enhance pseudovirus infection. Repertoire sequencing reveals quantitative profiles of vaccine-induced B-cell responses. This study demonstrates a promising vaccine strategy for filoviruses, such as EBOV, based on GP stabilization and nanoparticle display.
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Achieving fine control over the dispersion of supported platinum nanoparticles (Pt) is a promising avenue to enhancing their catalytic activity and selectivity. Experimental observations suggest that exposing ceria-supported Pt nanoparticles to O 2 at 500 °C promotes their dispersion into smaller particles and eventually single atoms. The exact role of oxygen in this process is not yet well understood. Past density functional theory studies of ceria-supported Pt have typically narrowed their scope to single atoms and clusters of a few atoms. Herein, we combine several approaches and types of models in a consistent atomistic framework to evaluate the relative stability of ceria-supported Pt as a function of the degree of oxidation of Pt and of the particle size, ranging from single atoms to nanoparticles 1.5 nm of diameter. Finally, we find that the largest nanoparticles remain the thermodynamically most stable species on the lowest energy facet of ceria even under oxidizing conditions, suggesting that stronger adsorption sites are required to stabilize smaller clusters and single atoms and promote oxidative dispersion.
A computationally efficient and transferable approach for modeling reactions at metal/water interfaces could significantly accelerate our understanding and ultimately the development of new catalytic transformations, particularly in the context of the emerging field of biomass conversion. Here, we present a parametrization of Pt–X (X = H, O, C) density-functional tight-binding (DFTB) for addressing this need. We first constructed Pt–H, Pt–O, and Pt–C repulsive potential splines. These pairwise parameters were then augmented to include many-body interactions using the Chebyshev Interaction Model for Efficient Simulation (ChIMES). We compare the geometrical and energetic performances of both DFTB and DFTB/ChIMES methods with DFT reference data across a variety of organic molecules at the platinum surface from nanoparticles to single-crystal surfaces. DFTB shows limited transferability between extended crystal surfaces and small nanoparticles. This transferability is significantly improved through the introduction of three-body interactions with Pt in DFTB/ChIMES, which provides consistent results across various systems, with reductions in the RMSD from around 30 kcal/mol in DFTB to around 10 kcal/mol. We demonstrate the stability and reliability of the obtained parameters by performing metadynamic simulations for the adsorption of phenol on Pt(111). We observe that DFTB itself is undersolvating the surface, leading to only one or two chemisorbed water molecules in a c(4 × 6) unit cell. In contrast, DFTB/ChIMES leads to a coverage of about 0.5 ML and successfully captures the chemisorbed mode of phenol at both the solid/liquid and the solid/gas interfaces. Furthermore, in agreement with experimental measurements, the adsorption at the solid/liquid interface is significantly weaker than that at the solid/gas interface. As a result, we highlight that even with DFTB, where we can accumulate dynamics for more than 1 ns for a given system, the simulations are not fully converged.
Inspired by structural colors in avian species, various synthetic strategies have been developed to produce noniridescent, saturated colors using nanoparticle assemblies. Nanoparticle mixtures varying in particle chemistry and size have additional emergent properties that affect the color produced. For complex multicomponent systems, understanding the assembled structure and a robust optical modeling tool can empower scientists to identify structure-color relationships and fabricate designer materials with tailored color. Here, we demonstrate how we can reconstruct the assembled structure from small-angle scattering measurements using the computational reverse-engineering analysis for scattering experiments method and use the reconstructed structure in finite-difference time-domain calculations to predict color. We successfully, quantitatively predict experimentally observed color in mixtures containing strongly absorbing nanoparticles and demonstrate the influence of a single layer of segregated nanoparticles on color produced. The versatile computational approach that we present is useful for engineering synthetic materials with desired colors without laborious trial-and-error experiments.
Due to their exceptional catalytic properties for the oxygen reduction reaction (ORR) and other crucial electrochemical reactions, PtCo intermetallic nanoparticle (NP) and single atomic (SA) Pt metal site catalysts have received considerable attention. However, their formation mechanisms at the atomic level during high-temperature annealing processes remain elusive. Furthermore, the thermally driven structure evolution of Pt–Co binary catalyst systems is investigated using advanced in situ electron microscopy, including PtCo intermetallic alloys and single Pt/Co metal sites. The pre-doping of CoN 4 sites in carbon supports and the initial Pt NP sizes play essential roles in forming either Pt 3 Co intermetallics or single Pt/Co metal sites. Importantly, the initial Pt NP loadings against the carbon support are critical to whether alloying to L1 2 -ordered Pt 3 Co NPs or atomizing to SA Pt sites at high temperatures. High Pt NP loadings (e.g., 20%) tend to lead to the formation of highly ordered Pt 3 Co intermetallic NPs with excellent activity and enhanced stability toward the ORR. In contrast, at a relatively low Pt loading (<6 wt%), the formation of single Pt sites in the form of PtC 3 N is thermodynamically favorable, in which a synergy between the PtC 3 N and the CoN 4 sites could enhance the catalytic activity for the ORR, but showing insufficient stability.
Grafting polymer chains on the surfaces of nanoparticles is a well-known route to control their self-assembly and distribution in a polymer matrix. A wide variety of self-assembled structures are achieved by changing the grafting patterns on the surface of an individual nanoparticle. However, an accurate estimation of the effective potential of mean force between a pair of grafted nanoparticles that determines their assembly and distribution in a polymer matrix is an outstanding challenge in nanoscience. We address this problem via deep learning. As a proof of concept, here we report a deep learning framework that learns the interaction between a pair of single-chain grafted spherical nanoparticles from their molecular dynamics trajectory. Subsequently, we carry out the deep learning potential of mean force-based molecular simulation that predicts the self-assembly of a large number of single-chain grafted nanoparticles into various anisotropic superstructures, including percolating networks and bilayers depending on the nanoparticle concentration in three-dimensions. The deep learning potential of mean force-predicted self-assembled superstructures are consistent with the actual superstructures of single-chain polymer grafted spherical nanoparticles. This deep learning framework is very generic and extensible to more complex systems including multiple-chain grafted nanoparticles. Finally, we expect that this deep learning approach will accelerate the characterization and prediction of the self-assembly and phase behaviour of polymer-grafted and unfunctionalized nanoparticles in free space or a polymer matrix.
Great efforts have been devoted to the development of bifunctional electrocatalysts to accelerate the sluggish kinetics of cathodic oxygen reduction/evolution reactions (ORR/OER) in zinc–air batteries (ZABs). Here we report a thermal evaporation–trapping synergistic strategy to fabricate a bifunctional electrocatalyst of flexible N-doped carbon fiber cloth loaded with both CoFe-oxide nanoparticles and single-atom Co/Fe–Nx sites, in which the thermal evaporation process functions in both downsizing CoFe-oxide nanoparticles and trapping the evaporated Co/Fe species to generate Co/Fe–Nx sites. The obtained flexible electrocatalyst, directly serving as an oxygen electrode, displays a small potential gap of 0.542 V for the OER/ORR, large peak power densities (liquid-state ZAB: 237.4 mW cm2 ; solid-state ZAB: 141.1 mW cm2 ), and excellent charge–discharge cycling stability without decay after working more than 770 hours. Furthermore, in situ Raman spectroscopy characterization and theoretical calculations reveal that CoFe2O4 species is responsible for the OER while atomic Fe/Co sites play a key role in the ORR
Facet-dependent surface charging of metal oxides in water dominates the ion transport behavior across the interface, in turn impacting many natural and industrial processes such as adsorption, the formation and stabilization of nanoparticle suspensions, corrosion, and heterogeneous catalysis. Here we investigated the pH-dependent surface chemistry of two low-index MgO single crystal surfaces, namely MgO(100) and MgO(111), using vibrational sum frequency generation (vSFG) spectroscopy. This allowed us to evaluate facet-dependent pH effects on the hydration and hydroxylation at the solid/aqueous interface and point-of-zero charge (PZC) values. The MgO system is complicated by its thermodynamic instability with respect to Mg(OH) 2 in water at ambient conditions. Here, for both hydroxylated MgO(100) and MgO(111) surfaces, the PZC is found to be around pH ∼ 12, which compares well with reported values for MgO single crystal and nanoparticle surfaces. However, structure specific differences in the molecular water hydrogen bonding network near the surface are evident at mildly acidic pH. To our knowledge, this is the first account of the PZC values for the MgO(111) single-crystal surface, an electrostatically unstable MgO termination that is prone to reconstruction.
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