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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Nonclassical Strong Metal–Support Interactions for Enhanced Catalysis

Strong metal–support interaction (SMSI), which encompasses reversible encapsulation and de-encapsulation and modulation of surface adsorption properties, imposes great impacts on the performance of heterogeneous catalysts. Recent development of SMSI has surpassed the prototypical encapsulated Pt-TiO 2 catalyst, affording a series of conceptually novel and practically advantageous catalytic systems. Here, in this work, we provide our perspective on recent progress in nonclassical SMSIs for enhanced catalysis. Unravelling the structural complexity of SMSI necessitates the combination of multiple characterization techniques at different scales. Synthesis strategies leveraging chemical, photonic, and mechanochemical driving forces further expand the definition and application scope of SMSI. Exquisite structure engineering permits elucidation of the interface, entropy, and size effect on the geometric and electronic characteristics. Materials innovation places the atomically thin two-dimensional materials at the forefront of interfacial active site control. A broader space is awaiting exploration, where exploitation of metal–support interactions brings compelling catalytic activity, selectivity, and stability.

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

Computing Reaction Kinetics with MC-PDFT–OPESf: Combining Multireference Electronic Structure Theory and Enhanced Sampling

Accurate rate constants are crucial for understanding and optimizing catalytic reactions mediated by enzymes, metalloproteins, and heterogeneous catalysts. These systems frequently present a dual computational challenge. Multiconfigurational reaction sites require multireference techniques for the accurate treatment of the electronic structure, and high activation barriers prevent efficient sampling of unbiased reactive transitions. In this work, we combine multiconfiguration pair-density functional theory (MC-PDFT) as an accurate and efficient multireference electronic structure method with on-the-fly probability-enhanced sampling flooding (OPESf) as an enhanced sampling method capable of accelerating reactive transitions. We demonstrate the approach on the Diels–Alder [4+2] cycloaddition between cis-butadiene and ethene as a reaction characterized by a large activation barrier and multireference character. MC-PDFT–OPESf provides reaction rates in agreement with experiments at a fraction of the computational cost required by conventional unbiased ab initio calculations. Here, we propose MC-PDFT–OPESf as an efficient approach for computing kinetics in strongly correlated molecular systems.

Chemical calculations↗
DOE OSTI2024

The Overlooked Potential of Sulfated Zirconia: Reexamining Solid Superacidity Toward the Controlled Depolymerization of Polyolefins

Closed-loop recycling via an efficient chemical process can help alleviate the global plastic waste crisis. However, conventional depolymerization methods for polyolefins, which compose more than 50% of plastics, demand high temperatures and pressures, employ precious noble metals, and yield complex mixtures of products limited to single-use fuels or oils. Superacidic sulfated zirconia (SZrO) with Hammet Acidity Functions (H 0 ) = -12 (i.e., stronger than 100% H 2 SO 4 ) is an industrially deployed heterogeneous catalyst capable of activating hydrocarbons under mild conditions and is shown to decompose polyolefins at ambient pressure and temperatures near 200 °C. Additionally, confinement of active sites in porous supports is known to radically increase selectivity, coking and sintering resistance, and acid site activity, presenting a possible approach to low-energy polyolefin depolymerization. However, a critical examination of the literature on SZrO led us to a surprising conclusion: despite 40 years of catalytic study, engineering, and industrial use, the surface chemistry of SZrO is poorly understood. Ostensibly spurred by SZrO's impressive catalytic activity, the application-driven study of SZrO has resulted in deleterious ambiguity in requisite synthetic conditions and insufficient characterization of acidity, porosity, and active site structure. Here, this ambiguity has produced significant knowledge gaps surrounding the synthesis, structure, and mechanisms of hydrocarbon activation for optimized SZrO, stunting the potential of this catalyst in olefin cracking and other industrially relevant reactions, such as isomerization, esterification, and alkylation. Toward mitigating these long extant issues, we herein identify and highlight these current shortcomings and knowledge gaps, propose explicit guidelines for characterization of and reporting on characterization of solid acidity, and discuss the potential of pore-confined superacids in the efficient and selective depolymerization of polyolefins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Modulating the Contact Angle between Nonpolar Polymers and SiO 2 Nanoparticles

Polymer–nanoparticle interactions play an important role in determining the morphology and properties of polymer nanocomposites and controlling the polymeric reactions involving heterogeneous catalysts. Here, in this study, we modulate the interactions between nonpolar polymers and nanoparticles by modifying the nanoparticle surface chemistry and quantify the interaction strength through direct contact angle measurements. We investigate the interactions of three nonpolar polymers, polystyrene, polyethylene, and polycyclooctene, with silica nanoparticles whose surface chemistry has been modified by atomic layer deposition of titania and calcium carbonate and by alkyl silanization. Significant differences in polymer–nanoparticle interactions are observed, which can be attributed to differences in the polarizability of the polymers and oxide surface composition. Compared to fully hydrogenated polycyclooctene, polycyclooctene is shown to have stronger interactions with most metal oxides; however, this trend is reversed following alkyl silanization of the silica nanoparticles, which makes the surface of the particles less polar. These differences in interactions can be leveraged to make polymer nanocomposites with unique properties and enable the selective conversion of polymers without the need for separations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Exploring Plasmonic Photocatalysis via Single-Molecule Reaction Imaging

Plasmonic photocatalysis has emerged as a new frontier in heterogeneous catalysis due to its promise in harvesting light to drive reactions. Yet many mechanistic aspects remain to be unambiguously defined. Using single-molecule fluorescence imaging, Li et al. studied a fluorogenic and plasmon-enhanced reaction, amplex red oxidation, on single Au nanorods at subturnover resolution and under operando conditions. Both the rate-determining step and its activation energy were identified from the multiple elemental reactions. Here, the results provide insights into the mechanism of plasmonic photocatalysis that may help the rational design of heterogeneous catalysts.

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

Stabilization of Ultrasmall Platinum Nanoparticles by Nitrogen-Doped Carbon: Implications for Catalysis and Electrocatalysis

Heterogeneous materials comprising platinum nanoparticles on carbon supports have numerous applications including fuel cell electrodes and heterogeneous catalysts. The effective application of these materials for fuel cells and catalysis will be greatly advanced by the ability to control the oxidation and sintering of the nanoparticles by modifications of the carbon support. One attempt of such control has been doping carbon supports with nitrogen. Here, in this work, a cutting-edge, high-sensitivity, in situ XRD instrument, which allows observation of ultrasmall Pt nanoparticles, has been combined with in situ XPS to provide unprecedented clarity in the characterization of supported Pt nanoparticles in oxidizing and high-temperature environments. On a nitrogen-doped carbon support derived from poly-phenylporphyrin, Pt nanoparticles show increased stability to oxidation and thermal sintering. The enhanced Pt–support interaction arising from the N dopant versus the N-free carbon is manifested by (1) decreased initial Pt particle sizes, (2) small particle size at higher surface densities, (3) increased resistance of Pt nanoparticles to oxidation, (4) increased electron binding energy of Pt0, and (5) increased resistance of Pt nanoparticles to sintering. It is expected that the higher stability of Pt on NC will be manifested in higher activity in fuel cells and high-temperature catalytic reactions.

catalytic reactions↗
DOE OSTI2024

Monodisperse Cu Nanoparticles Supported on a Versatile Metal–Organic Framework for Electrocatalytic Reduction of CO 2

Rare-earth metal–organic frameworks (REMOFs) based on polynuclear metal clusters are an emerging class of materials that have shown promise for CO 2 capture and conversion. Here, in this work, copper nanoparticles (CuNPs) were successfully installed on a cluster-based Y(III) MOF to yield a composite material, CuNP-Y-TBAP. The abundance of Cu binding sites on the Y(III) clusters allowed a remarkably high Cu loading to be achieved, and electron microscopy demonstrated that the MOF-supported CuNPs are exceptionally small and monodisperse. CuNP-Y-TBAP was found to be an active heterogeneous catalyst for electrochemical reduction of CO 2 , yielding CO and CH 4 as the primary CO 2 reduction products.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Classification of Adsorbed Hydrocarbons Based on Bonding Configurations of the Adsorbates and Surface Site Stabilities

The design of heterogeneous catalysts can be accelerated by identifying relevant descriptors that accurately and effectively link the binding and activation energies to reactivity. Herein, we investigated scaling relations between binding energies of various hydrocarbon-based adsorbates on three different Pt surfaces and metal binding energies estimated via the recently developed α-scheme model. In this study, we find that the scaling slopes are similar for certain groups of adsorbates, which then can be classified based on their spatial and electronic structure enabling fast description of binding strengths for each member of the class. Hence, our findings show that the binding energies of simple hydrocarbons CH x , x = {0,1,2,3,4}, and CHCH 2 can be used to identify the binding energies of more complex hydrocarbon-based adsorbates. We introduce this classification to establish a generalizable scheme in which complex hydrogenation/dehydrogenation processes of higher hydrocarbons can be predicted via the binding energies of simpler hydrocarbon-based species and ultimately through surface site stabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Intercalative Redox Tuning for Cu/Li x Mn 2 O 4 -Catalyzed Oxidative Alkyne Coupling

Modulation of heterogeneous catalyst structure is ubiquitous within efforts to improve catalytic activity and selectivity at the molecular level. Herein, manganese oxide (MnO 2 ) is employed as a continuously tunable catalyst support through increasing extent of lithium intercalation and reduced surface potential. Oxidative grafting of an organocopper complex onto various lithium manganese oxides (Li x Mn 2 O 4 , x = 0-2.1) produced divalent and monovalent copper species on the partially reduced (0 ≤ x ≤ 1.2) and fully reduced (x = 2.1) surfaces, respectively, as determined by X-ray absorption fine structure (XAFS) analysis. In this study, the resultant materials are catalytically active for the oxidative coupling of terminal alkynes, with steady-state reaction rate data of oxidative propyne dimerization (200 °C, 0.6-2.4 kPa propyne, 2.4-9.9 kPa O 2 ) indicating that complete support lithiation (Li 2.1 Mn 2 O 4 ) provides increased catalytic performance and renders reoxidation steps less kinetically demanding compared to the unreduced parent material. Enacting a dual site (Cu and MnO x ) kinetic model can account for dimerization rates measured over Cu/Li 2.1 Mn 2 O 4 under various reactant concentrations, copper loadings, and surface coverages, providing supporting evidence for the synergistic role of the metal and support in facilitating the coupling reaction. Overall, results presented here provide an extension for general strategies of systematically controlling catalytic structure and function through lithium reduction of bulk oxides and subsequent electronic modulation of the metals supported thereon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Flexible and Extensive Platinum Ion Gel Condensers for Programmable Catalysis

Catalytic condensers composed of ion gels separating a metal electrode from a platinum-on-carbon active layer were fabricated and characterized to achieve more powerful, high surface area dynamic heterogeneous catalyst surfaces. Ion gels comprised of poly(vinylidene difluoride)/1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide were spin coated as a 3.8 μm film on a Au surface, after which carbon sputtering of a 1.8 nm carbon film and electron-beam evaporation of 2 nm Pt clusters created an active surface exposed to reactant gases. Electronic characterization indicated that most charge condensed within the Pt nanoclusters upon application of a potential bias, with the condenser device achieving a capacitance of ∼20 μF/cm 2 at applied frequencies of up to 120 Hz. The maximum charge of ∼10 14 |e – | cm –2 was condensed under stable device conditions at 200 °C on catalytic films with ∼10 15 sites cm –2 . Grazing incidence infrared spectroscopy measured carbon monoxide adsorption isobars, indicating a change in the CO* binding energy of ∼19 kJ mol –1 over an applied potential bias of only 1.25 V. Condensers were also fabricated on flexible, large area Kapton substrates allowing stacked or tubular form factors that facilitate high volumetric active site densities, ultimately enabling a fast and powerful catalytic condenser that can be fabricated for programmable catalysis applications.

Catalysis↗
DOE OSTI2020

Metal–Ligand Cooperativity via Exchange Coupling Promotes Iron- Catalyzed Electrochemical CO 2 Reduction at Low Overpotentials

Biological and heterogeneous catalysts for the electrochemical CO 2 reduction reaction (CO 2 RR) often exhibit a high degree of electronic delocalization that serves to minimize overpotential and maximize selectivity over the hydrogen evolution reaction (HER). Here, we report a molecular iron(II) system that captures this design concept in a homogeneous setting through the use of a redox non-innocent terpyridine-based pentapyridine ligand (tpyPY2Me). As a result of strong metal-ligand exchange coupling between the Fe(II) center and ligand, [Fe(tpyPY2Me)] 2+ exhibits redox behavior at potentials 640 mV more positive than the isostructural [Zn(tpyPY2Me)] 2+ analog containing the redox-inactive Zn(II) ion. This shift in redox potential is attributed to the requirement for both an open-shell metal ion and a redox non-innocent ligand. The metal-ligand cooperativity in [Fe(tpyPY2Me)] 2+ drives the electrochemical reduction of CO 2 to CO at low overpotentials with high selectivity for CO 2 RR (>90%) and turnover frequencies of 100,000 s -1 with no degradation over 20 h. The decrease in the thermodynamic barrier engendered by this coupling also enables homogeneous CO 2 reduction catalysis in water without compromising selectivity or rates. Synthesis of the two-electron reduction product, [Fe(tpyPY2Me)] o , and characterization by X-ray crystallography, Mössbauer spectroscopy, X-ray absorption spectroscopy (XAS), variable temperature NMR, and density functional theory (DFT) calculations, support assignment of an open-shell singlet electronic structure that maintains a formal Fe(II) oxidation state with a doubly reduced ligand system. Furthermore, this work provides a starting point for the design of systems that exploit metal-ligand cooperativity for electrocatalysis where the electrochemical potential of redox non-innocent ligands can be tuned through secondary metal-dependent interactions.

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

Electron Inversion and Tunneling at Silicon Thermal Oxide Interfaces for Solar-Driven Molecular Catalysis to Syngas

Semiconductor photoelectrodes are regularly coupled to solid-state heterogeneous catalysts to perform solar-driven reduction of CO 2 . Less frequently, molecular catalysts are employed to better control the reactivity toward desired products, yet the development of robust semiconductor/molecule interfaces has proven challenging. Here, we demonstrate that a 2–3 nm thermal oxide layer on Si exhibits stability in aqueous solution, high photovoltage, and a photocurrent density of ∼10 mA/cm 2 for the solar-driven photoelectrochemical reduction of a homogeneous molecular catalyst, producing syngas with an ∼2:1 H 2 to CO ratio. Because of a low defect density, the oxide interface forms an electron inversion layer with metal-like electron density at cathodic potentials. This inversion layer facilitates electron transfer to redox-active molecules via tunneling even if the molecule’s reduction potential is beyond the semiconductor’s conduction band edge. Using an electrolyte solution composed of a homogeneous cobalt bis(terpyridine) catalyst in a water/organic solvent mixture, stable photoelectrochemistry was observed under 1-sun illumination, exhibiting an ∼30% Faradaic efficiency for CO that was similar to a glassy carbon electrode under comparable conditions. Furthermore, the results demonstrate that an ultrathin thermal oxide interface is a robust platform for development of aqueous-stable, molecule-driven photoelectrocatalysis.

Catalysts↗
DOE OSTI2025

Controlling Reaction Pathways of Ethylene Hydroformylation Using Isolated Bimetallic Rhodium–Cobalt Sites

Designing efficient ligand-free heterogeneous catalysts for ethylene hydroformylation to produce C 3 oxygenates is of importance for both fundamental research and practical applications, but it is often hindered by insufficient catalytic activity and selectivity. Here, this work designs isolated rhodium–cobalt (Rh–Co) sites confined within a ZSM-5 zeolite to enhance ethylene hydroformylation rates and selectivity while maintaining catalyst stability. By adjusting the Co/Al ratio in Co-ZSM-5, different sizes of Co are formed; subsequent Rh introduction produces isolated Rh 1 Co x clusters with different Rh–Co coordination numbers (CNs). In-situ characterizations and density functional theory calculations reveal that a Rh–Co CN of 3, corresponding to an isolated Rh 1 Co 3 site, provides optimal bindings to reaction intermediates and thus achieves the highest hydroformylation rates among supported Rh-based catalysts. This study demonstrates the role of coordination-tuning via a secondary metal in effectively controlling the reaction pathway over single Rh atom catalysts.

03 NATURAL GAS↗
DOE OSTI2025

CO Adsorbates Induced Framework-Associated Low-Valence Co δ+ Sites in Co-ZSM-5 for Ethane Dehydrogenation

The dynamic structural evolution of heterogeneous catalysts is a ubiquitous phenomenon that has attracted a lot of interest. Catalyst reconstruction can occur after appropriate pretreatment, resulting in more efficient active catalysts, which is an attractive but challenging issue. Here, we reveal a CO activation strategy that controls the microenvironment of the Co sites in the high-silica Co-ZSM-5 catalyst (denoted as 0.50Co-Z5(340)), resulting in three times higher initial conversion and superior regeneration durability in the ethane dehydrogenation reaction compared to the same catalyst without CO pretreatment. In situ spectroscopy and metadynamics simulations reveal that the Co 2+ sites in 0.50Co-Z5(340) dislodge from the framework and move toward the nearby Brønsted acid sites, forming framework-associated low-valence Co δ+ species. Mechanistic studies indicate that the Co δ+ species catalyze ethane C–H bond cleavage via an oxidative addition mechanism, and ethylene is produced simultaneously with H* coupling (direct pathway). The promoted C–H bond activation and facile ethylene desorption explain the superior ethane dehydrogenation performance of the herein CO preactivated 0.50Co-Z5(340) catalyst.

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

Hydrogen migration at restructuring palladium–silver oxide boundaries dramatically enhances reduction rate of silver oxide

Heterogeneous catalysts are complex materials with multiple interfaces. A critical proposition in exploiting bifunctionality in alloy catalysts is to achieve surface migration across interfaces separating functionally dissimilar regions. Herein, we demonstrate the enhancement of more than 10 4 in the rate of molecular hydrogen reduction of a silver surface oxide in the presence of palladium oxide compared to pure silver oxide resulting from the transfer of atomic hydrogen from palladium oxide islands onto the surrounding surface formed from oxidation of a palladium-silver alloy. The palladium-silver interface also dynamically restructures during reduction, resulting in silver-palladium intermixing. This study clearly demonstrates the migration of reaction intermediates and catalyst material across surface interfacial boundaries in alloys with a significant effect on surface reactivity, having broad implications for the catalytic function of bimetallic materials.

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

Machine learned features from density of states for accurate adsorption energy prediction

Materials databases generated by high-throughput computational screening, typically using density functional theory (DFT), have become valuable resources for discovering new heterogeneous catalysts, though the computational cost associated with generating them presents a crucial roadblock. Hence there is a significant demand for developing descriptors or features, in lieu of DFT, to accurately predict catalytic properties, such as adsorption energies. Here, we demonstrate an approach to predict energies using a convolutional neural network-based machine learning model to automatically obtain key features from the electronic density of states (DOS). The model, DOSnet, is evaluated for a diverse set of adsorbates and surfaces, yielding a mean absolute error on the order of 0.1 eV. In addition, DOSnet can provide physically meaningful predictions and insights by predicting responses to external perturbations to the electronic structure without additional DFT calculations, paving the way for the accelerated discovery of materials and catalysts by exploration of the electronic space.

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

Graph theory approach to determine configurations of multidentate and high coverage adsorbates for heterogeneous catalysis

Abstract Heterogeneous catalysts constitute a crucial component of many industrial processes, and to gain an understanding of the atomic-scale features of such catalysts, ab initio density functional theory is widely employed. Recently, growing computational power has permitted the extension of such studies to complex reaction networks involving either high adsorbate coverages or multidentate adsorbates, which bind to the surface through multiple atoms. Describing all possible adsorbate configurations for such systems, however, is often not possible based on chemical intuition alone. To systematically treat such complexities, we present a generalized Python-based graph theory approach to convert atomic scale models into undirected graph representations. These representations, when combined with workflows such as evolutionary algorithms, can systematically generate high coverage adsorbate models and classify unique minimum energy multidentate adsorbate configurations for surfaces of low symmetry, including multi-elemental alloy surfaces, steps, and kinks. Two case studies are presented which demonstrate these capabilities; first, an analysis of a coverage-dependent phase diagram of absorbate NO on the Pt 3 Sn(111) terrace surface, and second, an investigation of adsorption energies, together with identifying unique minimum energy configurations, for the reaction intermediate propyne (CHCCH 3 *) adsorbed on a PdIn(021) step surface. The evolutionary algorithm approach reproduces high coverage configurations of NO on Pt 3 Sn(111) using only 15% of the number of simulations required for a brute force approach. Furthermore, the screening of potentially hundreds of multidentate adsorbates is shown to be possible without human intervention. The strategy presented is quite general and can be applied to a spectrum of complex atomic systems.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Regularized machine learning on molecular graph model explains systematic error in DFT enthalpies

Abstract A major goal of materials research is the discovery of novel and efficient heterogeneous catalysts for various chemical processes. In such studies, the candidate catalyst material is modeled using tens to thousands of chemical species and elementary reactions. Density Functional Theory (DFT) is widely used to calculate the thermochemistry of these species which might be surface species or gas-phase molecules. The use of an approximate exchange correlation functional in the DFT framework introduces an important source of error in such models. This is especially true in the calculation of gas phase molecules whose thermochemistry is calculated using the same planewave basis set as the rest of the surface mechanism. Unfortunately, the nature and magnitude of these errors is unknown for most practical molecules. Here, we investigate the error in the enthalpy of formation for 1676 gaseous species using two different DFT levels of theory and the ‘ground truth values’ obtained from the NIST database. We featurize molecules using graph theory. We use a regularized algorithm to discover a sparse model of the error and identify important molecular fragments that drive this error. The model is robust to rigorous statistical tests and is used to correct DFT thermochemistry, achieving more than an order of magnitude improvement.

36 MATERIALS SCIENCE↗