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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 361 records · Page 20

Mechanism of structural colors in binary mixtures of nanoparticle-based supraballs

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.

36 MATERIALS SCIENCE↗

Robust measurement of microbial reduction of graphene oxide nanoparticles using image analysis

ABSTRACT Shewanella oneidensis ( S. oneidensis ) has the capacity to reduce electron acceptors within a medium and is thus used frequently in microbial fuel generation, pollutant breakdown, and nanoparticle fabrication. Microbial fuel setups, however, often require costly or labor-intensive components, thus making optimization of their performance onerous. For rapid optimization of setup conditions, a model reduction assay can be employed to allow simultaneous, large-scale experiments at lower cost and effort. Since S. oneidensis uses different extracellular electron transfer pathways depending on the electron acceptor, it is essential to use a reduction assay that mirrors the pathways employed in the microbial fuel system. For microbial fuel setups that use nanoparticles to stimulate electron transfer, reduction of graphene oxide provides a more accurate model than other commonly used assays as it is a bulk material that forms flocculates in solutions with a large ionic component. However, graphene oxide flocculates can interfere with traditional absorbance-based measurement techniques. This study introduces a novel image analysis method for quantifying graphene oxide reduction, showing improved performance and statistical accuracy over traditional methods. A comparative analysis shows that the image analysis method produces smaller errors between replicates and reveals more statistically significant differences between samples than traditional plate reader measurements under conditions causing graphene oxide flocculation. Image analysis can also detect reduction activity at earlier time points due to its use of larger solution volumes, enhancing color detection. These improvements in accuracy make image analysis a promising method for optimizing microbial fuel cells that use nanoparticles or bulk substrates. IMPORTANCE Shewanella oneidensis ( S. oneidensis ) is widely used in reduction processes such as microbial fuel generation due to its capacity to reduce electron acceptors. Often, these setups are labor-intensive to operate and require days to produce results, so use of a model assay would reduce the time and expenses needed for optimization. Our research developed a novel digital analysis method for analysis of graphene oxide flocculates that may be utilized as a model assay for reduction platforms featuring nanoparticles. Use of this model reduction assay will enable rapid optimization and drive improvements in the microbial fuel generation sector.

Bennett, Danielle T. (ORCID:0009000188748827)↗

Oxygen Evolution on Iron Oxide Nanoparticles: The Impact of Crystallinity and Size on the Overpotential

The oxygen evolution reaction (OER) is a critical reaction in electrolysis and photoelectrolysis of water to generate and store clean energy. Therefore, the development of low-cost and efficient electrocatalysts for the OER is of great scientific and technological importance. Although promising iron oxide-based electrocatalysts have been recently developed for the OER, an in-depth experimental and theoretical analysis of the OER mechanism on iron oxide-based electrocatalysts is still needed to provide guidelines to optimize the performance of iron oxide-based electrocatalysts further. To address this need, we synthesized a series of monodisperse iron oxide nanoparticles to analyze their intrinsic OER activities. Using nanoparticles of the same size but different crystallinity, we show that amorphous iron oxide nanoparticles have better OER activity than crystalline ones. The size effect studies further revealed that the edge/defect sites are the active sites for the OER. Density functional theory calculations demonstrated that the edge/defect sites provide bridge sites to adsorb OER intermediates, resulting in low OER overpotential. These calculations confirm that the high OER activity of amorphous nanoparticles results from a high concentration of defect sites on their surface. These results provide novel strategies to increase the performance of iron oxide-based and likely other oxide-based OER electrocatalysts.

Electrochemistry↗

Science Driven Discovery of Nanoparticle Photocatalysts

Photocatalytic water splitting using suspensions of nanoparticle photocatalysts is a promising route to economically sustainable production of green hydrogen. The principal challenge is to develop photocatalysts with overall solar-to-hydrogen conversion efficiency that exceeds 10 percent. In this project we have developed a new platform for investigating candidate materials for photocatalytic water splitting. Our platform consists of patterned Au electrodes and a Ag/AgCl reference electrode on an insulating substrate onto which we disperse nanoparticle photocatalysts. We then cover the substrate with a thin layer of ionogel containing a protic ionic liquid that dissolves water from the ambient. Using this platform we have demonstrated photoelectrochemical activity mapping for single and small clusters of BiVO 4 nanoparticle photocatalysts and correlated these results to their Raman and photoluminescence spectra. The preliminary results suggest a strong correlation for low efficiency nanoparticles, followed by saturation for those with higher activities, indicating that interface reaction or electrolyte transport become the limiting factor. We anticipate that further application of this platform to investigation of candidate photocatalyst materials will provide useful insights into the mechanisms that limit their performance.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Multi‐Scale Model‐Informed Deep Learning for Plasma‐Nanoparticle Interaction

The Overarching Goal of this proposed research is to understand and quantitively determine the interactions between non-thermal plasma (hot electrons, reactive radicals, vibrationally excited species) and surface reactions on influencing the activity and selectivity of the desired reactions via developing multi-scale model informed deep learning algorithm. Investigating non-thermal plasma-surface interaction is feasible due to the low bulk temperature in the discharge region. To investigate the role of plasma-nanoparticle interaction on enhancing the reaction kinetics, we will focus on ammonia cracking to generate clean hydrogen over earth-abundant, non-critical metallic nanoparticles, which is of great significance for decarbonization. We hypothesize that (1) reactive radicals interacting with surface reaction species via Eley–Rideal mechanism will significantly lower the energetics of the potential rate-limiting step of nitrogen formation; (2) the surface will be charged heterogeneously under non-thermal plasma conditions and the charged site will lower the energetics of ammonia cracking through Langmuir– Hinshelwood mechanism; (3) vibrationally excited ammonia will further promote the initial N-H bond cleavage. To access the hypothesis, we will (1) reveal the surface charge effects on tunning the reaction energetics via interpretable, physics-informed deep learning accelerated density functional theory (DFT) calculations; (2) determine the reactive radicals interacting with surface reaction species on tuning the reaction energetics via DFT; (3) reveal the surface charge effects on tunning the reaction energetics via DFT and deep learning models, (4) quantify how vibrationally excited species, reactive radicals, and surface charging effects on enhancing the catalysis via developing DFT-based microkinetic modeling (MKM) and active learning. Deep and active learning of plasma-nanoparticle interactions effects on enhancing ammonia cracking to generate hydrogen represents a new paradigm for designing high performance plasma materials. The fundamental science of how plasma-nanoparticle interactions will change the plasma kinetics and will improve the energy efficiency for decarbonization and sustainability. The interpretable and physics-informed machine learning model will accelerate low temperature plasma chemistry and material discovery with physics rules and model interpretation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Multiscale Modeling of Nanoparticle Precipitation in Oxide Dispersion-Strengthened Steels Produced by Laser Powder Bed Fusion

Laser Powder Bed Fusion (LPBF) enables the efficient production of near-net-shape oxide dispersion-strengthened (ODS) alloys, which possess superior mechanical properties due to oxide nanoparticles (e.g., yttrium oxide, Y-O, and yttrium-titanium oxide, Y-Ti-O) embedded in the alloy matrix. To better understand the precipitation mechanisms of the oxide nanoparticles and predict their size distribution under LPBF conditions, we developed an innovative physics-based multiscale modeling strategy that incorporates multiple computational approaches. These include a finite volume method model (Flow3D) to analyze the temperature field and cooling rate of the melt pool during the LPBF process, a density functional theory model to calculate the binding energy of Y-O particles and the temperature-dependent diffusivities of Y and O in molten 316L stainless steel (SS), and a cluster dynamics model to evaluate the kinetic evolution and size distribution of Y-O nanoparticles in as-fabricated 316L SS ODS alloys. The model-predicted particle sizes exhibit good agreement with experimental measurements across various LPBF process parameters, i.e., laser power (110–220 W) and scanning speed (150–900 mm/s), demonstrating the reliability and predictive power of the modeling approach. The multiscale approach can be used to guide the future design of experimental process parameters to control oxide nanoparticle characteristics in LPBF-manufactured ODS alloys. Additionally, our approach introduces a novel strategy for understanding and modeling the thermodynamics and kinetics of precipitation in high-temperature systems, particularly molten alloys.

Wang, Zhengming (ORCID:0000000241627112)↗

Magnetic and Impedance Analysis of Fe 2 O 3 Nanoparticles for Chemical Warfare Agent Sensing Applications

A dire need for real-time detection of toxic chemical compounds exists in both civilian and military spheres. In this paper, we demonstrate that inexpensive, commercially available Fe 2 O 3 nanoparticles are capable of selective sensing of chemical warfare agents (CWAs) using frequency-dependent impedance spectroscopy, with additional potential as an orthogonal magnetic sensor. X-ray magnetic circular dichroism analysis shows that Fe 2 O 3 nanoparticles possess moderately lowered moment upon exposure to 2-chloroethyl ethyl sulfide (2-CEES) and diisopropyl methylphosphonate (DIMP) and significantly lowered moment upon exposure to dimethyl methylphosphonate (DMMP) and dimethyl chlorophosphate (DMCP). Associated X-ray absorption spectra confirm a redox reaction in the Fe 2 O 3 nanoparticles due to CWA structural analog exposure, with differentiable energy-dependent features that suggest selective sensing is possible, given the correct method. Impedance spectroscopy performed on samples dosed with DMMP, DMCP, and tabun (GA, chemical warfare nerve agent) showed strong, differentiable, frequency-dependent responses. The frequency profiles provide unique “shift fingerprints” with which high specificity can be determined, even amongst similar analytes. The results suggest that frequency-dependent impedance fingerprinting using commercially available Fe 2 O 3 nanoparticles as a sensor material is a feasible route to selective detection.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tailored design of protein nanoparticle scaffolds for multivalent presentation of viral glycoprotein antigens

Multivalent presentation of viral glycoproteins can substantially increase the elicitation of antigen-specific antibodies. To enable a new generation of anti-viral vaccines, we designed self-assembling protein nanoparticles with geometries tailored to present the ectodomains of influenza, HIV, and RSV viral glycoprotein trimers. We first de novo designed trimers tailored for antigen fusion, featuring N-terminal helices positioned to match the C termini of the viral glycoproteins. Trimers that experimentally adopted their designed configurations were incorporated as components of tetrahedral, octahedral, and icosahedral nanoparticles, which were characterized by cryo-electron microscopy and assessed for their ability to present viral glycoproteins. Electron microscopy and antibody binding experiments demonstrated that the designed nanoparticles presented antigenically intact prefusion HIV-1 Env, influenza hemagglutinin, and RSV F trimers in the predicted geometries. This work demonstrates that antigen-displaying protein nanoparticles can be designed from scratch, and provides a systematic way to investigate the influence of antigen presentation geometry on the immune response to vaccination.

59 BASIC BIOLOGICAL SCIENCES↗

Core-shell structured nanoparticles for lithium-sulfur cells

Described is a core-shell nanoparticle comprising a lithium sulfide nanoparticle core and a shell covering the lithium sulfide nanoparticle core. The core-shell nanoparticle may be used for a positive electrode in a lithium/sulfur battery cell.

Cairns, Elton J.↗

Liquid bicontinuous stabilized assemblies by interfacial jamming of nanoparticles

A method for preparing a stabilized assembly includes combining a first liquid phase including nanoparticles and a second, immiscible liquid phase, dissolving in the second phase a first end-functionalized polymer having a first molecular weight, and a second end-functionalized polymer having a second molecular weight, wherein the second molecular weight is greater than the first molecular weight, applying a shearing external deformation field to increase the surface area of the first phase to create a new interface, wherein the nanoparticle surfactants form a disordered, jammed assembly at the new interface, and releasing the shearing external deformation field. The polymer and the nanoparticles can interact at an interface through ligand interactions to form nanoparticle surfactants and upon releasing the external deformation field the jammed assembly at the new interface traps the first phase in a deformed state having the first liquid phase and the second liquid phase as interpenetrating domains.

Huang, Caili↗

Nanofibers decorated with nanoparticles and methods of their manufacture

Nanostructured materials, and methods and apparatus for their production are provided. Nanostructured materials comprise nanofibers having nanoparticles deposited along the outer surface thereof. The size of the nanofibers and nanoparticles, and the spacing of such nanoparticles along the nanofibers may be controlled over a wide range. Nanostructured materials may comprise a plurality of such nanofibers interwoven together to form fiber cloth-like materials. Many materials may be used to form the nanofibers including polymer nanofiber materials (e.g., polyvinyl alcohol (PVA) polyvinylpyrrolidone (PVP), etc.) along with compatible nanoparticle materials (e.g., salts or other crystallizable materials).

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Methods of producing cobalt nanoparticles and hollow gold nanospheres and kits for practicing same

Provided are methods of producing cobalt nanoparticles (Co NPs). The methods include combining a cobalt salt, a capping agent, and a reducing agent, under Co NP synthesis conditions including a temperature selected to produce cobalt nanoparticles of a pre-selected diameter, where the temperature and pre-selected diameter are inversely related. In certain aspects, the methods further include producing hollow gold nano spheres (HGNs) using the cobalt nanoparticles as scaffolds. Also provided are cobalt nanoparticles and hollow gold nano spheres (HGNs) produced according to the present methods. Kits that find use in practicing the methods of the present disclosure are also provided.

Pu, Ying-Chih↗

Aqueous based nanoparticle ink

Water-based nanoparticle inks may be formulated to be compatible with printed electronic direct-write methods. The water-based nanoparticle inks may include a functional material (nanoparticle) in combination with an appropriate solvent system. A method may include dispersing nanoparticles in a solvent and printing a circuit in an aerosol jet process or plasma jet process.

Fujimoto, Kiyo↗

Dendritic gold nanoparticles and methods of synthesis

A method of producing dendritic gold nanoparticles by combining a gold precursor solution, a reducing agent, and a bifunctional peptide having an amine-rich amino acid sequence into a buffered aqueous solution in a single container, and agitating the mixture causing the formation of the dendritic gold nanoparticles having a surface with a positive charge and a second end portion of the bifunctional peptide exposed on the surface of the dendritic gold nanoparticles. The dendritic gold nanoparticles may be used to deliver therapeutic, diagnostic, and/or immunogenic amino acid sequences as portions of the bifunctional peptide.

Mao, Chuanbin↗

Solvothermal synthesis of metal alkanoate and metal oxide nanoparticles

A facile solvothermal method can be used to synthesize metal alkanoate nanoparticles using a metal nitrate precursor, alcohol/water, and alkanoic acid. The method can produce lanthanide (e.g., La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, or Yb) and transition metal (e.g., Ag, Co, Cu, or Pb) alkanoate nanoparticles (<100 nm) with spherical morphology. These hybrid nanomaterials adopt a lamellar structure consisting of inorganic metal cation layers separated by an alkanoate anion bilayer and exhibit liquid crystalline phases during melting. The metal alkanoate nanoparticles can be calcined to produce metal oxide nanoparticles.

Treadwell, LaRico Juan↗

Carbon fiber-nanoparticle composites with electromechanical properties

A carbon fiber composite material comprising: (i) a carbon fiber having an outer surface, a thickness of at least 1 micron, and an aspect ratio of at least 1000; (ii) a sizing agent coated on the outer surface of the carbon fiber, wherein the sizing agent has a thickness of up to 200 nm; and (iii) nanoparticles having a size in at least one dimension of up to 100 nm embedded within the sizing agent, wherein the nanoparticles have a metal carbide, metal oxide, metal nitride, and/or metal boride composition. A method for producing the fiber composite material comprises: (a) continuously feeding and coating a continuous carbon fiber with a liquid containing a solvent, sizing agent, and nanoparticles in a continuous feed-through process to result in said sizing agent and nanoparticles coating the surface of the continuous carbon fiber; and (b) removing the solvent from the coated fiber.

Bowland, Christopher C.↗

Tuning Point Defects by Elastic Strain Modulates Nanoparticle Exsolution on Perovskite Oxides

Exsolution generates stable and catalytically active metal nanoparticles via phase precipitation out of a host oxide. An ability to control the size and dispersion of the exsolution particles is desirable for design of nanostructured (electro)catalysts. In this work, we demonstrate that tuning point defects by lattice strain affects both the thermodynamics and the kinetics of iron (Fe 0 ) exsolution on La 0.6 Sr 0.4 FeO 3 (LSF) thin film model. By combining in situ surface characterization and ab initio defect modeling, we show oxygen vacancy and Schottky defects to be the primary point defects formed upon Fe0 exsolution. Lattice strain tunes the formation energy, and thus the abundance of these defects, and alters the amount and size of the resulting exsolution particles. In addition, we find that the density of exsolved nanoparticles matches the concentration of oxygen vacancy pairs, thus pointing to the surface oxygen vacancy pairs as preferential nucleation sites for exsolution. The tensile-strained LSF with a facile formation of these critical point defects results in a higher Fe 0 metal concentration, a larger density of nanoparticles, and a reduced particle size at its surfaces. These results provide important mechanistic insights and highlight the role of point-defect engineering in designing nanostructured catalysts in energy and fuel conversion technologies.

36 MATERIALS SCIENCE↗

Synthesis of Solid-Solution Mn x Zn 1– x O Nanoparticles and their Electrochemical Oxidation of Furfural

Electrochemical valorization of biomass-derived substrates has become a prominent area of research due to its potential to produce value-added products from renewable feedstocks in a more sustainable way. First-row transition metal electrodes are compelling candidates for these conversions due to their stability, abundance, and cost-effectiveness. Herein, we report on the colloidal synthesis of Mn x Zn 1– x O (x = 0.3-0.7) nanoparticles and their electrocatalytic activity towards furfural oxidation. We find that the hindrance of a MnO impurity can be achieved by leveraging the oxidation state of the Mn precursor. The Mn x Zn 1– x O composition closely follows the ratio of precursors, with all the nanoparticles having a wurtzite structure as determined by ICP-MS and PXRD, respectively. XANES and XPS revealed the presence of Mn in different oxidation states with the ratio of these varying based on the composition. When comparing the electrocatalytic activity of the monometallic and bimetallic oxides for furfural oxidation, a decrease in current density was observed with increasing Zn content. We find the Mn x Zn 1– x O nanoparticles favor the formation of the 6 e - oxidation product 5-hydroxy-2(5H)-furanone, while both monometallic oxides primarily yield CO 2 and other deeply oxidized products as the majority pathway. Furthermore, these findings can contribute towards the design and synthesis of more active and selective electrocatalyst.

Aldehydes↗