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Results for “Heterogenous catalysis”

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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Ternary aromatic and anti-aromatic clusters derived from the hypho species [Sn 2 Sb 5 ] 3-

Heterometallic clusters have attracted broad interests in the synthetic chemistry due to their various coordination modes and potential applications in heterogeneous catalysis. Here we report the synthesis, experimental, and theoretical characterizations of four ternary clusters ([M 2 (CO) 6 Sn 2 Sb 5 ] 3- (M = Cr, Mo), and [(MSn 2 Sb 5 ) 2 ] 4- , (M = Cu, Ag)) in the process of capturing the hypho - [Sn 2 Sb 5 ] 3- in ethylenediamine (en) solution. We show that the coordination of the binary anion to transition-metal ions or fragments provides additional stabilization due to the formation of locally σ-aromatic units, producing a spherical aromatic shielding region in the cages. While in the case of [Mo 2 (CO) 6 Sn 2 Sb 5 ] 3- stabilization arises from locally σ-aromatic three-centre and five-centre two-electron bonds, aromatic islands in [(AgSn 2 Sb 5 ) 2 ] 4- and [(CuSn 2 Sb 5 ) 2 ] 4- render them globally antiaromatic. This work describes the coordination chemistry of the versatile building block [Sn 2 Sb 5 ] 3- , thus providing conceptual advances in the field of metal-metal bonding in clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Reversing sintering effect of Ni particles on γ-Mo 2 N via strong metal support interaction

Reversing the thermal induced sintering phenomenon and forming high temperature stable fine dispersed metallic centers with unique structural and electronic properties is one of the ever-lasting targets of heterogeneous catalysis. Here we report that the dispersion of metallic Ni particles into under-coordinated two-dimensional Ni clusters over γ-Mo 2 N is a thermodynamically favorable process based on the AIMD simulation. A Ni-4nm/γ-Mo 2 N model catalyst is synthesized and used to further study the reverse sintering effect by the combination of multiple in-situ characterization methods, including in-situ quick XANES and EXAFS, ambient pressure XPS and environmental SE/STEM etc. The under-coordinated two-dimensional layered Ni clusters on molybdenum nitride support generated from the Ni-4nm/γ-Mo 2 N has been demonstrated to be a thermally stable catalyst in 50 h stability test in CO 2 hydrogenation, and exhibits a remarkable catalytic selectivity reverse compared with traditional Ni particles-based catalyst, leading to a chemo-specific CO 2 hydrogenation to CO.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Zeolite-promoted platinum catalyst for efficient reduction of nitrogen oxides with hydrogen

Internal combustion engine fueled by carbon-free hydrogen (H 2 -ICE) offers a promising alternative for sustainable transportation. Herein, we report a facile and universal strategy through the physical mixing of Pt catalyst with zeolites to significantly improve the catalytic performance in the selective catalytic reduction of nitrogen oxides (NO x ) with H 2 (H 2 -SCR), a process aiming at NO x removal from H 2 -ICE. Via the physical mixing of Pt/TiO 2 with Y zeolite (Pt/TiO 2 + Y), a remarkable enhancement of NO x reduction activity and N 2 selectivity was simultaneously achieved. The incorporation of Y zeolite effectively captured the in-situ generated water, fostering a water-rich environment surrounding the Pt active sites. This environment weakened the NO adsorption while concurrently promoting the H 2 activation, leading to the strikingly elevated H 2 -SCR activity and N 2 selectivity on Pt/TiO 2 + Y catalyst. This study provides a unique, easy and sustainable physical mixing approach to achieve proficient heterogeneous catalysis for environmental applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Bayesian framework for adsorption energy prediction on bimetallic alloy catalysts

Abstract For high-throughput screening of materials for heterogeneous catalysis, scaling relations provides an efficient scheme to estimate the chemisorption energies of hydrogenated species. However, conditioning on a single descriptor ignores the model uncertainty and leads to suboptimal prediction of the chemisorption energy. In this article, we extend the single descriptor linear scaling relation to a multi-descriptor linear regression models to leverage the correlation between adsorption energy of any two pair of adsorbates. With a large dataset, we use Bayesian Information Criteria (BIC) as the model evidence to select the best linear regression model. Furthermore, Gaussian Process Regression (GPR) based on the meaningful convolution of physical properties of the metal-adsorbate complex can be used to predict the baseline residual of the selected model. This integrated Bayesian model selection and Gaussian process regression, dubbed as residual learning, can achieve performance comparable to standard DFT error (0.1 eV) for most adsorbate system. For sparse and small datasets, we propose an ad hoc Bayesian Model Averaging (BMA) approach to make a robust prediction. With this Bayesian framework, we significantly reduce the model uncertainty and improve the prediction accuracy. The possibilities of the framework for high-throughput catalytic materials exploration in a realistic setting is illustrated using large and small sets of both dense and sparse simulated dataset generated from a public database of bimetallic alloys available in Catalysis-Hub.org.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Benchmarking graph neural networks for materials chemistry

Graph neural networks (GNNs) have received intense interest as a rapidly expanding class of machine learning models remarkably well-suited for materials applications. To date, a number of successful GNNs have been proposed and demonstrated for systems ranging from crystal stability to electronic property prediction and to surface chemistry and heterogeneous catalysis. However, a consistent benchmark of these models remains lacking, hindering the development and consistent evaluation of new models in the materials field. Here, we present a workflow and testing platform, MatDeepLearn, for quickly and reproducibly assessing and comparing GNNs and other machine learning models. We use this platform to optimize and evaluate a selection of top performing GNNs on several representative datasets in computational materials chemistry. From our investigations we note the importance of hyperparameter selection and find roughly similar performances for the top models once optimized. We identify several strengths in GNNs over conventional models in cases with compositionally diverse datasets and in its overall flexibility with respect to inputs, due to learned rather than defined representations. Meanwhile several weaknesses of GNNs are also observed including high data requirements, and suggestions for further improvement for applications in materials chemistry are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Super-resolution imaging of non-fluorescent reactions via competition

Super-resolved fluorescence microscopy techniques have enabled substantial advances in the chemical and biological sciences. However, they can only interrogate entities that fluoresce, and most chemical or biological processes do not involve fluorescent species. Here we report a competition-enabled imaging technique with super-resolution (COMPEITS) (a COMPetition-Enabled Imaging Technique with Super-resolution) that enables quantitative super-resolution imaging of non-fluorescent processes. It is based on the incorporation of competition into a single-molecule fluorescence-detection scheme. We demonstrate COMPEITS by investigating a photoelectrocatalytic reaction; we map, with nanometre precision, a non-fluorescent surface reaction that is important for water decontamination on single photocatalyst particles. The subparticle-level quantitative information of reactant adsorption affinities unambiguously decouples size- and shape-scaling laws on specific particle facets and uncovers a surprising biphasic shape dependence, leading to catalyst design principles for optimal reactant adsorption efficacy. With its ability to provide spatially resolved information on the behaviours of unlabelled, non-fluorescent entities under operando conditions, COMPEITS could interrogate a variety of surface processes in fields ranging from heterogeneous catalysis and materials engineering to nanotechnology and energy sciences.

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

Deciphering electrocatalysts with multimodal operando approaches

Here, the electrocatalytic processes of a copper catalyst during nitrate electroreduction are unveiled by correlated operando microscopy and spectroscopy. Catalysts are vital to the modern chemical industry, yet their development has largely relied on trial-and-error approaches. Optimizing catalysts requires a fundamental understanding of their structure–chemical property behaviour under operational conditions. However, operando characterization remains challenging, especially for reactions occurring in the complex and dynamic liquid environments of electrochemical systems. Over the past decade, the rapid development of in situ and operando environmental transmission electron microscopy (ETEM) and microelectromechanical system (MEMS)-based closed-cell holders, enabling environmental studies within the vacuum environment of transmission electron microscopy (TEM), has substantively advanced understanding of heterogeneous catalysis, notably for gas-phase reactions. In situ ETEM enables the direct observation of the catalyst evolution in terms of structure, morphology and chemical state at the nano-to-atomic scale, providing insights into their correlation with catalytic performance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Dataset of theoretical multinary perovskite oxides

Perovskite oxides (ternary chemical formula ABO 3 ) are a diverse class of materials with applications including heterogeneous catalysis, solid-oxide fuel cells, thermochemical conversion, and oxygen transport membranes. However, their multicomponent (chemical formula $A_xA^{'}_{1-x}B_yB^{'}_{1-y}O_3$) chemical space is underexplored due to the immense number of possible compositions. To expand the number of computed $A_xA^{'}_{1-x}B_yB^{'}_{1-y}O_3$ compounds we report a dataset of 66,516 theoretical multinary oxides, 59,708 of which are perovskites. First, 69,407 $A_{0.5}A^{'}_{0.5}B_{0.5}B^{'}_{0.5}O_3$ compositions were generated in the a - b + a - Glazer tilting mode using the computationally-inexpensive Structure Prediction and Diagnostic Software (SPuDS) program. Next, we optimized these structures with density functional theory (DFT) using parameters compatible with the Materials Project (MP) database. Our dataset contains these optimized structures and their formation (ΔH f ) and decomposition enthalpies (ΔH d ) computed relative to MP tabulated elemental references and competing phases, respectively. This dataset can be mined, used to train machine learning models, and rapidly and systematically expanded by optimizing more SPuDS-generated $A_{0.5}A^{'}_{0.5}B_{0.5}B^{'}_{0.5}O_3$ perovskite structures using MP-compatible DFT calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Continuity of reaction kinetics across the pressure and materials gaps in CO oxidation on FeO–Pt interfaces

Translating atomic-scale insights from surface science studies of model catalysts to practical powder catalysts remains a persistent challenge in heterogeneous catalysis. Here, in this study, we demonstrate mechanistic continuity across the pressure and materials gaps during CO oxidation at the FeO-Pt interface using in situ microscopy, spectroscopy and computational modelling. Under reaction conditions, coordinatively unsaturated Fe (Fe cus ) sites at the interface enable selective O 2 activation on CO-saturated surfaces, circumventing the CO-poisoning limitation of platinum-group metals. We identify parallel reaction pathways involving the *O 2 -*CO intermediate. Remarkably, activation energies remain consistent at 12-15 kJ mol −1 (0.12-0.16 eV) from ultrahigh vacuum to atmospheric pressures and from FeO/Pt(111) model catalysts to FeO/Pt powder catalysts, validating mechanistic insights derived from surface science studies. Our findings show an example of bridging the long-standing divide between model and practical catalyst systems, establishing an effective approach to capture catalytic behaviours under operational conditions and advancing mechanism-driven catalyst design.

03 NATURAL GAS↗
DOE OSTI2019

Glucose isomerization in dioxane/water with Sn-β catalyst: improved catalyst stability and use for HMF production

The stability of zeolite Sn-beta (Sn-β) was greatly improved for glucose isomerization to fructose and fructose yield of 41.5% has been obtained when dioxane/water was used as solvent. The effect of dioxane/water solvent mixtures for fructose dehydration on Amberlyst-131 was also studied and it was found that small amounts of water in dioxane increase the yield of HMF (up to 74%) by limiting the formation of oligomers like difructose anhydride (III). 56% yield of HMF from glucose, maltose, trehalose or cellobiose and 60% from sucrose were produced when hydrolysis of disaccharides, glucose isomerization and fructose dehydration were coupled in a mixture of dioxane/water (5 wt%).

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

Aluminum hydroxide-mediated synthesis of mesoporous metal oxides by a mechanochemical nanocasting strategy

Mesoporous metal oxides (MOs) have attracted significant interest in heterogeneous catalysis due to their wide pore size distribution and high pore volume. In this work, we present a facile mechanochemical nanocasting strategy using aluminum hydroxide as the mesoporous structure-directing agent, which overcomes the drawbacks associated with wet template-assisted methods. In this procedure, by simply grinding a mixture of commercial aluminum hydroxide and MO precursors, a series of mesoporous MOs with high specific surface areas and narrow pore size distributions have been constructed in a short time (e.g., Fe 2 O 3 , 280 m 2 g –1 ; Co 3 O 4 , 155 m 2 g –1 ; CeO 2 , 192 m 2 g –1 ; ZrO 2 , 170 m 2 g –1 ; CuO x –CeO y , 177 m 2 g –1 ; FeO x –CeO y , 170 m 2 g –1 ; CoO x –CuO y –CeO z , 154 m 2 g –1 ; CoO x –FeO y –CeO z , 133 m 2 g –1 ). It is expected that this strategy may open up new opportunities for fabricating a number of advanced porous materials with abundant porosity in the near future.

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

Unraveling the structural stability and the electronic structure of ThO 2 clusters

Unraveling the correlations between the geometry, the relative energy and the electronic structure of metal oxide nanostructures is crucial for a better control of their size, shape and properties. Here, we investigated these correlations for stoichiometric thorium dioxide clusters ranging from ThO 2 to Th 8 O 16 using a chemically-driven geometry search algorithm in combination with state-of-the-art first principles calculations. This strategy allows us to homogeneously screen the potential energy surface of actinide oxide clusters for the first time. It is found that the presence of peroxo and superoxo groups tends to increase the total energy of the system by at least 3.5 eV and 7 eV, respectively. For the larger clusters, the presence of terminal oxygen atoms increases the energy by about 0.5 eV. Regarding the electronic structure, it is found that the HOMO–LUMO gap is larger in systems containing only bridging oxygen atoms (~2–3.5 eV) than for systems containing oxo groups (~1–3 eV), peroxo groups (~0–2 eV), and superoxo groups (~0–1 eV). Furthermore, while the LUMO is always dominated by thorium orbitals, the composition of the HOMO changes in the presence or the absence of oxo, peroxo and/or superoxo groups: in the presence of peroxo groups, it is dominated by thorium orbitals, in all other cases, it is dominated by oxygen orbitals, and is rather localized in the presence of terminal oxo or superoxo groups. These correlations are of great interest for synthesizing clusters with tailored properties, especially for applications in the field of nuclear energy and heterogeneous catalysis.

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

Unexpected trends in the enhanced Ce 3+ surface concentration in ceria–zirconia catalyst materials

Despite the immense importance of ceria–zirconia solid solutions in heterogeneous catalysis, and the growing consensus that catalytic activity correlates with the concentration of reduced Ce 3+ species and accompanying oxygen vacancies, the extent of reduction at the surfaces of these materials, where catalysis occurs, is unknown. Using angle-resolved X-ray Absorption Near Edge Spectroscopy (XANES), we quantify under technologically relevant conditions the Ce 3+ concentration in the surface (2–3 nm) and bulk regions of ceria–zirconia films grown on single crystal yttria-stabilized zirconia, YSZ (001). In all circumstances, we observe substantial Ce 3+ enrichment at the surface relative to the bulk. Surprisingly, the degree of enhancement is highest in the absence of Zr. This behavior stands in direct contrast to that of the bulk in which the Ce 3+ concentration monotonically increases with increasing Zr content. Overall, these results suggest that while Zr enhances the oxygen storage capacity in ceria, undoped ceria may have higher surface catalytic activity. They further urge caution in the use of bulk properties as surrogate descriptors for surface characteristics and hence catalytic activity.

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

Expeditious synthesis of covalent organic frameworks: a review

Covalent organic frameworks (COFs), a burgeoning class of crystalline porous materials constructed by covalently connecting organic building blocks, have garnered tremendous attention. The predominant solvothermal synthesis of COFs usually requires high temperature and long reaction times (three days or longer), which creates substantial obstacles for their accelerated discovery and exploration in practical applications. Hence, the expeditious synthesis of COFs without compromising their inherent properties is exceedingly appealing from the viewpoint of cost, time, and energy footprint. To overcome the sluggishness of the synthesis, considerable efforts have been invested in the rapid synthesis of high-quality COFs through innovations in energy source, catalyst, solvent, monomer, nucleation, and workup activation, leading to a drastic reduction of reaction time from multiple days to a few hours, and even to seconds in some cases. In this contribution, we provide a comprehensive overview of the advances in expediting the synthesis science of COFs. Though a nascent effort, six prevalent strategies have been identified for the rapid synthesis of COFs, which have led to intriguing applications in a diverse range of areas including gas adsorption, separation, heterogeneous catalysis, environmental remediation, and photodynamic therapy. We also outline the major challenges and perspectives on the future directions empowered by expeditious COF synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗