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Results for “nanoparticles catalysts”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Preparation of a membrane-sealed cell for studying catalyst nanoparticles in flowing gas with high vacuum x-ray photoelectron spectrometer

Here a sealing-style x-ray photoelectron spectroscopy study of the surface of a 1.0 wt. %Ni/TiO2 nanoparticle catalyst in a flowing mixture of CO and O2 at 1 bar was performed with a graphene membrane-sealed Si3N4 window-based miniature cell. We report the details on how a commercial Si3N4 window is modified before assembling a graphene membrane, how single-layer graphene membranes are transferred from their metal supports to the modified Si3N4 window, how a modified Si3N4 window covered with a double-layer graphene membrane is assembled onto a blank cell cap, how a nanoparticle catalyst is introduced to the cell cap and then the cell cap is installed onto a cell body to form a complete reaction cell, and how a complete cell is interfaced with a high vacuum chamber of an XPS system before an XPS study of 1.0 wt. %Ni/TiO2 catalyst surface in a flowing mixture for 0.2 bar CO and 0.8 bar O2 is performed. How the characterization of a catalyst using this type of graphene membrane-sealed Si3N4 window-based miniature cell is relevant to the finding of the actual surface chemistry of a catalyst during catalysis is discussed.

Instruments & Instrumentation↗
DOE OSTI2021

Design and Characterization of ALD-Based Overcoats for Supported Metal Nanoparticle Catalysts

Supported metal nanoparticle (SMN) catalysts are enormously crucial for many catalytic applications. However, catalyst deactivation, caused by sintering and coke formation, is a ubiquitous problem that significantly undermines catalytic processing economics. The application of material overcoating onto supported metal nanoparticles by atomic layer deposition (ALD) offers the solution to inhibit catalyst deactivation. Herein, we discuss examples in which ALD has been used to stabilize SMN catalysts in gaseous and aqueous-phase reactions. We highlight the ALD tools and methods in coating high-surface-area catalysts. Besides, various techniques are introduced to understand better how to characterize the overcoating layer and the catalyst itself. Finally, the outlook for new techniques to characterize the ALD overcoated catalytic materials is discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Systems and methods for scale-up synthesis multi-layered Pt-skin nanoparticle catalysts

A method for scaled-up synthesis of PtNi nanoparticles. Synthesizing a Pt nanoparticle catalyst comprises the steps of: synthesizing PtNi nanoparticles, isolating PtNi/substrate nanoparticles, acid leaching the PtNi/substrate, and annealing the leached PtNi/substrate nanoparticles, and forming a Pt-skin on the PtNi/substrate nanoparticles.

Stamenkovic, Vojislav↗
DOE OSTI2022

Organo-Nanocups Assist the Formation of Ultra-Small Palladium Nanoparticle Catalysts for Hydrogen Evolution Reaction

Ultra-small palladium nanoparticles were synthesized and applied as catalysts for a hydrogen evolution reaction. The palladium metal precursor was produced via beta-cyclodextrin as organo-nanocup (ONC) capping agent to produce ultra-small nanoparticles used in this study. The produced ~3 nm nanoparticle catalyst was then characterized via X-ray diffraction (XRD), transmission electron microscopy (TEM), ultraviolet-visible spectroscopy (UV-Vis), and Fourier transform infrared spectroscopy (FTIR) to confirm the successful synthesis of ~3 nm palladium nanoparticles. The nanoparticles’ catalytic ability was explored via the hydrolysis reaction of sodium borohydride. The palladium nanoparticle catalyst performed best at 303 K at a pH of 7 with 925 μmol of sodium borohydride having an H 2 generation rate of 1.431 mL min -1 mL cat -1 . The activation energy of the palladium catalyst was calculated to be 58.9 kJ/mol.

36 MATERIALS SCIENCE↗
NASA NTRS2003

Metal Nanoparticle Catalysts for Carbon Nanotube Growth

Work this summer involved and new and unique process for producing the metal nanoparticle catalysts needed for carbon nanotube (CNT) growth. There are many applications attributed to CNT's, and their properties have deemed them to be a hot spot in research today. Many groups have demonstrated the versatility in CNT's by exploring a wide spectrum of roles that these nanotubes are able to fill. A short list of such promising applications are: nanoscaled electronic circuitry, storage media, chemical sensors, microscope enhancement, and coating reinforcement. Different methods have been used to grow these CNT's. Some examples are laser ablation, flame synthesis, or furnace synthesis. Every single approach requires the presence of a metal catalyst (Fe, Co, and Ni are among the best) that is small enough to produce a CNT. Herein lies the uniqueness of this work. Microemulsions (containing inverse micelles) were used to generate these metal particles for subsequent CNT growth. The goal of this summer work was basically to accomplish as much preliminary work as possible. I strived to pinpoint which variable (experimental process, metal product, substrate, method of application, CVD conditions, etc.) was the determining factor in the results. The resulting SEM images were sufficient for the appropriate comparisons to be made. The future work of this project consists of the optimization of the more promising experimental procedures and further exploration onto what exactly dictated the results.

Pierce, Benjamin F.↗
DOE OSTI2019

Room-temperature Synthesis of High-entropy Perovskite Oxide Nanoparticle Catalysts via Ultrasonication-based Method

Currently, a sonochemical-based technique for one-pot synthesis of entropy-stabilized perovskite oxide nanoparticle catalysts with high surface area is reported. The high-entropy perovskite oxides were synthesized as monodispersed, spherical nanoparticles with average crystallite size of ~5.9 nm. Taking advantage of the acoustic cavitation phenomenon in ultrasonication process, the nanoparticles of BaSr(ZrHfTi)O 3 , BaSrBi(ZrHfTiFe)O 3 and Ru/BaSrBi(ZrHfTiFe)O 3 were crystallized as single-phase perovskite structures through ultrasonication exposure without calcination. Of utmost importance, the entropically-driven stability of Ru/BaSrBi(ZrHfTiFe)O 3 with excellent dispersion of Ru in the perovskite phase, bestowed the nanoparticles of Ru/BaSrBi(ZrHfTiFe)O 3 with good catalytic activity for CO oxidation.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Ripening of Rh Nanoparticle Catalysts in Reverse Water–Gas Shift via a Data-Driven Model Combining Physics, Theory, and Experiment

Degradation via sintering is an ongoing challenge that impedes the broad commercial success of supported metallic nanoparticle catalysts. To mitigate degradation via informed catalyst design and process operations, here we aim to disambiguate the underlying mechanisms of sintering by combining theory and experiment in a quantitative framework. While mechanistic sintering models exist, they only model a single sintering pathway, even though multiple sintering mechanisms can occur simultaneously or dominate at different stages of the process. Data-driven machine learning models have emerged as a means to represent complex processes through data regression. However, machine learning models have very large data needs and lack mechanistic insights due to their black-box encoding. To develop an interpretive model of catalyst degradation via sintering, we constructed a hybrid model combining mechanistic “physics-based” models and data-driven methods to obtain both reliable predictions and mechanistic insights regarding experimentally observed sintering phenomena. Focusing on nanoparticle sintering in the Rh–TiO 2 catalyst for the reverse water–gas shift (RWGS) reaction, the hybrid model couples a mechanistic term for Ostwald ripening with energy values calculated via density functional theory (DFT) with a parametric, data-driven discrepancy function term for unmodeled mechanisms. The hybrid model is trained using Bayesian inference with data collected from small-angle X-ray scattering (SAXS) in situ experiments wherein average nanoparticle diameter versus time was measured at three relevant operating temperatures. The calibrated hybrid model results show that an Ostwald ripening-only model parameterized with fixed DFT energies does not fully capture the time and temperature dependence of the SAXS-observed sintering kinetics, and that an additional functional contribution, or DFT energy calibration, is required to reconcile simulation and experiment. Analysis of the hybrid-model error confirms that the hybrid model outperforms both the purely mechanistic and purely data-driven alternatives in terms of expected predictive accuracy for time-evolving average particle sizes. Furthermore, the results support the hypothesis that the Ostwald ripening mechanism is less important for explaining the sintering phenomena as operating temperature increases under an assumed fixed DFT parameterization. This could be explained in one of two ways: either latent, unmodeled sintering mechanisms dominate at higher temperatures, or the DFT uncertainty increases with temperature. The proposed modeling approach directly links theory to experiments and simulations via a statistical hybrid modeling framework and can be extended to other catalytic systems to improve predictive models and mechanistic understanding.

Bayesian hybrid modeling↗
DOE OSTI2021

Entropic Control of HD Exchange Rates over Dilute Pd-in-Au Alloy Nanoparticle Catalysts

Dilute Pd-in-Au alloy catalysts are promising materials for selective hydrogenation catalysis. Extensive surface science studies have contributed mechanistic insight on the energetic aspect of hydrogen dissociation, migration and recombination on dilute alloy systems. Yet, translating these fundamental concepts to the kinetics and free energy of hydrogen dissociation on nanoparticle catalysts operating at ambient pressures and temperatures remains challenging. Here, the effect of the Pd concentration and Pd ensemble size on the catalytic activity, apparent activation energy and rate limiting process is addressed by combining experiment and theory. Experiments in a flow reactor show that a compositional change from 4 to 8 atm% Pd of the Pd-in-Au alloy catalyst leads to strong increase in activity, even exceeding the activity per Pd atom of monometallic Pd under the same conditions, albeit with an increase in apparent activation energy. First-principles calculations show that the rate and apparent activation enthalpy for HD exchange increase when increasing the Pd ensemble size from single Pd atoms to Pd trimers in a Au surface, suggesting that the ensemble size distribution shifts from mainly single Pd atoms on the 4 atm% Pd alloy to larger Pd ensembles of at least three atoms for the 8 atm% Pd/Au catalyst. The DFT studies also indicated that the rate-controlling process is different: H 2 (D 2 ) dissociation determines the rate for single atoms whereas recombination of adsorbed H and D determines the rate on Pd trimers. Both experiment and theory suggest that the increased reaction rate with increasing Pd content and ensemble size stems from an entropic driving force. Lastly, our results support hydrogen migration between Pd sites via Au and indicate that the dilute alloy design prevents the formation of subsurface hydrogen, which is crucial in achieving high selectivity in hydrogenation catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Data-Driven Discovery of Bimetallic Nanoparticles Catalysts for the Hydrogenolysis of Polyethylene

Supported platinum nanoparticles are known to convert polyolefins to high-quality liquid hydrocarbons with hydrogen under relatively mild conditions. However, no systematic study has been undertaken using bimetallic catalysts for polyethylene upcycling. Specifically, a total of 98 monometallic and bimetallic combinations (Ag, Cr, Co, Cu, Fe, Ga, In, Mn, Ni, Pd, Pt, Rh, Ru, Zr) on alumina were synthesized utilizing surface organometallic chemistry (SOMC) technique via robotic platform. These were investigated at a small scale (10 mg of catalyst and 50 mg of polyethylene) for their activity for the hydrogenolysis of polyethylene in a high-throughput batch reactor. Combinations of Ni and Co were selected as candidates with high activity toward conversion into paraffin oils. Reaction conditions were optimized with Ni/Co/Al 2 O 3 catalyst at a larger scale (300 mg catalyst and 3 g polyethylene) to obtain a high yield (93.1%) of paraffin wax with desired properties (M n = 380 Da) and low polydispersity (Đ = 1.2). Ni/Co/Al 2 O 3 was compared against Co/Ni/Al 2 O 3 to understand the role of the deposition sequence. When Co is deposited before Ni, a layer of cobalt aluminate is formed upon reduction, stabilizing the deposition of 5 nm metallic Ni particles. When nickel is deposited before Co, particles are larger (average >20 nm) and more oxidized (Ni δ+ in NiAl 2 O 4 ), decreasing the availability of the catalytically active metallic Ni. In conclusion, the difference in electronic environments was also described by DFT calculations, which revealed that smaller 3D clusters of Ni are preferred on CoAl2O4 over the 3D clusters on NiAl 2 O 4 and that these smaller clusters are more reducible, as confirmed experimentally.

Polymer↗
DOE OSTI2019

Achieving High Selectivity for Alkyne Hydrogenation at High Conversions with Compositionally Optimized PdAu Nanoparticle Catalysts in Raspberry Colloid-Templated SiO 2

Improving the selectivity for catalytic hydrogenation of alkynes is a key step in upgrading feedstocks for olefin polymerization. Herein, dilute Pd x Au 1-x alloy nanoparticles embedded in raspberry colloidtemplated silica (x = 0.02, 0.04, and 0.09) are demonstrated to be highly active and selective for the gas-phase hydrogenation of 1-hexyne, exhibiting higher selectivity than pure Pd at high conversion. The conversion of 1-hexyne remains high even for the very low amounts of Pd in Pd 0.02 Au 0.98 . These catalysts are highly resistant to sintering—addressing a long-standing challenge in the use of Au-based catalysts. Clear evidence is presented that the addition of the second hydrogen to the halfhydrogenated intermediate is the rate-limiting step, and that the stability of the half-hydrogenated intermediate of the alkyne is higher than the half-hydrogenated alkene which explains the high selectivity even at high conversions. Moreover, of the three compositions investigated, optimum selectivity and activity is observed for the nanoparticles containing 4% Pd. The apparent activation energy for production of 1-hexene from 1-hexyne is measured to be 38 kJ mol -1 for the Pd 0.04 Au 0.96 catalysts, which is ~14 kJ mol -1 lower than for pure Pd. The hydrogenation is completely, but reversibly, suppressed by adding CO to the reactant mixture, indicating that the Pd centers are the active sites for reaction. The method of templating used in preparation of the catalysts is highly customizable and versatile. As a result, this study demonstrates that the composition of the nanoparticles as defined by the dilution ratio of Pd in Au and by the method used to make the supported catalyst are important tunable parameters that can be used to optimize activity and selectivity of bimetallic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Computational Design of Graphene–Nanoparticle Catalysts

Nanoclusters possess electronic properties that are inherently different from their bulk counterparts due to quantum effects that are strongly manifested at the nanoscale. Therefore, the catalytic properties of nanoclusters cannot be understood by a simple extrapolation of our understanding of catalysis on bulk metal surfaces. The presence of supports further modifies the electronic properties, morphology, and catalytic activity of a nanoparticle due to interplay between the electronic properties of the support and the nanoparticle. The objective of this research was to develop a systematic computational approach for designing and evaluating the activity and selectivity of supported catalyst nanoclusters, in the specific context of graphenesupported Pt and Pt-Ru nanoparticles for methanol decomposition. While the enhanced activity of nanoclusters has long been exploited in Pt–carbon black catalysts, recent experiments have shown that Pt–graphene catalysts can far outperform their predecessors, in particular, for methanol oxidation—a reaction of crucial importance for methanol fuel cells. However, the fundamental mechanisms by which graphene enhances the activity of nanoparticles for methanol oxidation as yet remain to be understood.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Throughput Optimization of Molybdenum Carbide Nanoparticle Catalysts in a Continuous Flow Reactor Using Design of Experiments

Transition metal carbides (TMCs) have attracted significant attention because of their applications toward a wide range of catalytic transformations. However, the practicality of their synthesis is still limited because of the harsh conditions in which most TMCs are prepared. Recently, a solution-phase synthesis of phase-pure a-MoC1-x nanoparticles was presented. While this synthetic route yielded nanoparticles with exceptional catalytic performance, the reaction parameter space was not explored, and catalyst throughput was not optimized for scale-up. Continuous flow platforms coupled with statistical design of experiments (DoE) can provide a powerful method for understanding the reaction parameter space for optimizations. Here, we demonstrate the use of statistical DoE in tandem with response surface methodology for a parametric screening analysis to optimize the throughput of a MoC1-x nanoparticle synthesis utilizing a millifluidic flow reactor. A full factorial design was implemented to evaluate four input variables (reaction temperature, flow rate, solvent fraction of oleylamine, and precursor concentration) that carry statistically significant effects on three responses (throughput, residence time, and isolated yield). A Doehlert matrix was implemented to investigate each significant variable at a higher number of levels to optimize throughput. Our results give a nonintuitive set of experimental conditions that resulted in an optimized throughput of 2.2 g h-1. This translates to a 50-fold increase in throughput compared to the previously reported batch method. The catalytic performance of the MoC1-x nanoparticles produced under optimized throughput was demonstrated in the CO2 hydrogenation reaction. This DoE screening analysis and throughput optimization of MoC1-x synthesis open the door to an increased feasibility for scale-up.

design of experiments↗