Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “heterogeneous catalyst”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Controlling Hydrocarbon (De)Hydrogenation Pathways with Bifunctional PtCu Single-Atom Alloys

The conversions of surface-bound alkyl groups to alkanes and alkenes are important steps in many heterogeneously catalyzed reactions. On the one hand, while Pt is ubiquitous in industry because of its high activity toward C–H activation, many Pt-based catalysts tend to overbind reactive intermediates, which leads to deactivation by carbon deposition and coke formation. On the other hand, Cu binds intermediates more weakly than Pt, but activation barriers tend to be higher on Cu. We examine the reactivity of ethyl, the simplest alkyl group that can undergo hydrogenation and dehydrogenation via β-elimination, and show that isolated Pt atoms in Cu enable low-temperature hydrogenation of ethyl, unseen on Cu, while avoiding the decomposition pathways on pure Pt that lead to coking. Lastly, we confirm the predictions of our theoretical model and experimentally demonstrate that the selectivity of ethyl (de)hydrogenation can be controlled by changing the surface coverage of hydrogen.

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

Mesoflow: An Open-Source Reacting Flow Solver for Catalysis at Mesoscale

We present the capabilities and software performance metrics of our open-source continuum solver for catalysis, Mesoflow, developed specifically for modeling transport and chemistry at the mesoscale. Our solver utilizes Cartesian block-structured adaptive mesh refinement to resolve complex catalyst surface morphologies directly obtained from X-ray tomography data. An immersed boundary based formulation enables rapid representation of complex geometries prevalent in most mesoporous catalyst interfaces. The solver is developed on top of open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Our flexible software framework enables integration of complex chemical mechanisms at heterogenous interfaces and time-split algorithms for circumventing highly disparate reaction and flow time-scales. Our current studies indicate a ten-fold performance gain by using graphics-processing-units (GPUs) compared to a single processor for representative problem sizes (2 million cell mesh). We will also present a brief introduction on how to build and use this software for application problems pertaining to catalytic upgrading and gas transport within porous catalyst particles.

adaptive meshing↗
DOE OSTI2021

2D Covalent Organic Frameworks with an Incorporated Manganese Complex for Light Driven Carbon Dioxide Reduction

Covalent organic frameworks (COFs) have emerged as a novel class of crystalline porous photocatalytic materials due to their unique properties such as large surface area, tunable porosity, and rigid structure. Here in this work, we report the direct incorporation of a manganese CO 2 molecular catalyst (MC) into COFs (Mn-TTA-COF) and the evaluation of its capability as photocatalyst for visible light driven CO 2 reduction to form CO. We found that the photocatalytic activity of Mn-TTA-COF is quite low, which mainly results from the elimination of the CO ligand in the Mn MC upon light illumination, rendering its short duration in the catalytic reaction. While this is a central concern for the further use Mn-TTA-COF as a CO 2 reduction catalyst, here we found that the stability and efficiency of Mn MC is largely enhanced after being incorporated into COFs with respect to its homogeneous version, suggesting the capability of COFs as heterogeneous platform to incorporate MC and improve the catalytic performance of MC. Moreover, transient absorption spectroscopic studies show that the intramolecular charge transfer lifetime of the Mn-incorporated COF is longer than that in the parent COF, which suggests that charge separation (CS) may occur from the parent COF to the Mn moiety. These results together suggest that COFs may show promise as a platform for creating next-generation photocatalysts with a built-in photosensitizer and MC, which can facilitate CS and enhance the stability and efficiency of the incorporated MC.

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

Numerical modeling of chemical looping oxidative dehydrogenation of ethane in parallel packed beds

Chemical looping oxidative dehydrogenation (CL-ODH) of ethane has the potential to be a highly efficient alternative to steam cracking for ethylene production. Accurate reactor modeling is of critical importance to efficiently scale up and optimize this new technology. This study reports a one-dimensional, heterogeneous packed bed model to simulate the CL-ODH of ethane to ethylene with a Na 2 MoO 4 -promoted CaTi 0.1 Mn 0.9 O 3 redox catalyst. Here, the overall reaction kinetics was well-described by coupling the gas-phase steam cracking of ethane with the reduction kinetics of the redox catalyst by H 2 and C 2 H 4 . The impact of H 2 on the formation rate of CO 2 byproduct from C 2 H 4 conversion was also thoroughly investigated to validate the applicability of the kinetic model under operational environments. The temperature variation within the different CL-ODH steps and the temperature distribution along the bed were also carefully considered. The accuracy of the model was validated by experiments conducted in a large lab-scale packed bed reactor (200 g catalyst loading), with an average deviation of 2.8% in terms of ethane conversion and ethylene yield. The model was subsequently used to optimize the operating parameters of the CL-ODH reactor, indicating that up to 63.7% single-pass C 2 +olefin yield can be achieved with the current redox catalyst bed whereas further optimization of the redox catalyst to inhibit C 2 H 4 activation can result in 69.4% single-pass C 2 +yield while maintaining low CO 2 selectivity.

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

On the use of NMR distance measurements for assessing surface site homogeneity

The past few decades have seen tremendous growth in the area of single-site heterogeneous catalysis, which aims to combine the best aspects of homogeneous and heterogeneous catalysis, namely molecular-level site control and ease of separation/recycling. Despite this, we still do not have a means of assessing site homogeneity and whether the produced catalyst is indeed a “single-site”. Recent developments have enabled the use of NMR-based distance measurements to determine the conformations and configurations of surface sites, leading to the question whether such measurements can be used to distinguish materials containing either single or multiple surface sites with otherwise indistinguishable NMR properties. Here, we describe a Monte Carlo-based multi-structure search algorithm and its application to the determination of multi-site structures from supported metal complexes. The sensitivity of REDOR data to the existence of multiple sites is assessed using synthetic data and prior literature examples are revisited to determine whether the single-site approximation was indeed appropriate. We lastly apply this new methodology to differentiate the configurations of zirconocene complexes grafted onto alumina supports that were thermally treated at different temperatures.

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

Prediction of hydration energies of adsorbates at Pt(111) and liquid water interfaces using machine learning

Aqueous phase heterogeneous catalysis is important to various industrial processes, including biomass conversion, Fischer–Tropsch synthesis, and electrocatalysis. Accurate calculation of solvation thermodynamic properties is essential for modeling the performance of catalysts for these processes. Explicit solvation methods employing multiscale modeling, e.g., involving density functional theory and molecular dynamics have emerged for this purpose. Although accurate, these methods are computationally intensive. This study introduces machine learning (ML) models to predict solvation thermodynamics for adsorbates on a Pt(111) surface, aiming to enhance computational efficiency without compromising accuracy. In particular, ML models are developed using a combination of molecular descriptors and fingerprints and trained on previously published water–adsorbate interaction energies, energies of solvation, and free energies of solvation of adsorbates bound to Pt(111). These models achieve root mean square error values of 0.09 eV for interaction energies, 0.04 eV for energies of solvation, and 0.06 eV for free energies of solvation, demonstrating accuracy within the standard error of multiscale modeling. Feature importance analysis reveals that hydrogen bonding, van der Waals interactions, and solvent density, together with the properties of the adsorbate, are critical factors influencing solvation thermodynamics. Furthermore, these findings suggest that ML models can provide rapid and reliable predictions of solvation properties. This approach not only reduces computational costs but also offers insights into the solvation characteristics of adsorbates at Pt(111)–water interfaces.

Adsorption↗
DOE OSTI2020

A Review of Microwave-Assisted Synthesis-Based Approaches to Reduce Pd-Content in Catalysts

This review article focuses on the latest advances in the synthesis of inorganic nano-catalysts using microwave heating, which has progressed significantly since its initial implementation in the mid-1980s. Over the years, nanoparticles (NPs), which inherently offer better surface accessibility for heterogeneous catalysis, have been synthesized using a wide array of heating methods. Microwave heating is one such method and employs a unique heating mechanism that can have several benefits for catalysis. When compared to conventional form of heating which relies on inter-layer mixing via convection, microwave heating operates through the chemical polarity in the target chemicals leading to an “inside-out” mode of heating. This heating mechanism is more targeted and therefore results in rapid synthesis of catalytically active NPs. Platinum group metals (PGM) have classically been the focus of nano-catalysis; however, recent efforts have also applied non-PGM group metals with the goals of lower costs, and ideally, improved catalytic reactivity and durability. This is especially of interest with respect to Pd because of its current historically high cost. Investigations into these new materials have primarily focused on new/improved synthetic methods and catalytic compositions, but it is important to note that these approaches must also be economic and scalable to attain practical relevance. With this overarching goal in mind, this review summarizes notable recent findings with a focus on Pd-dilution and microwave heating in a chronological fashion.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Detecting Cage Crossing and Filling Clusters of Magnesium and Carbon Atoms in Zeolite SSZ-13 with Atom Probe Tomography

The conversion of methanol to valuable hydrocarbon molecules is of great commercial interest, as the process serves as a sustainable alternative for the production of, for instance, the base chemicals for plastics. The reaction is catalyzed by zeolite materials. By the introduction of magnesium as a cationic metal, the properties of the zeolite, and thereby the catalytic performance, are changed. With atom probe tomography (APT), nanoscale relations within zeolite materials can be revealed: i.e., crucial information for a fundamental mechanistic understanding. We show that magnesium forms clusters within the cages of zeolite SSZ-13, while the framework elements are homogeneously distributed. These clusters of just a few nanometers were analyzed and visualized in 3-D. Magnesium atoms seem to initially be directed to the aluminum sites, after which they aggregate and fill one or two cages in the zeolite SSZ-13 structure. The presence of magnesium in zeolite SSZ-13 increases the lifetime as well as the propylene selectivity. By using operando UV–vis spectroscopy and X-ray diffraction techniques, we are able to show that these findings are related to the suppression of aromatic intermediate products, while maintaining the formation of polyaromatic compounds. Further nanoscale analysis of the spent catalysts showed indications of magnesium redistribution after catalysis. Unlike zeolite H-SSZ-13, for which only a homogeneous distribution of carbon was found, carbon can be either homogeneously or heterogeneously distributed within zeolite Mg-SSZ-13 crystals as the magnesium decreases the coking rate. Carbon clusters were isolated, visualized, and analyzed and were assumed to be polyaromatic compounds. Small one-cage-filling polyaromatic compounds were identified; furthermore, large-cage-crossing aromatic molecules were found by isolating large coke clusters, demonstrating the unique coking mechanism in zeolite SSZ-13. Short-length-scale evidence for the formation of polyaromatic compounds at acid sites is discovered, as clear nanoscale relations between aluminum and carbon atoms exist.

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

Recent Advancements in Catalytic Fast Pyrolysis for the Production of Fuels and Chemicals from Biomass

Catalytic fast pyrolysis (CFP) is a promising biorefinery technology platform for generating both fuel blendstocks and chemical co-products. The versatility of this platform is afforded by (1) the coupling of a thermochemical deconstruction step to a catalytic step that enables tuning of the product slate and (2) the diversity of accessible products across gaseous, liquid, and solid streams. However, there are a number of challenges impeding commercial viability for this CFP platform, including high process costs caused by low carbon efficiency to bio-oil due to coking and light gas formation, the quality and properties of the bio-oil dictate processability for downstream operations, and the heterogeneity of the bio-oil limits quality of resulting fuel blendstocks. This presentation will discuss our efforts to address these challenges through a combined experimental-computational approach to catalyst design and process development, with a specific focus on (1) modifying product composition through catalyst design and (2) generating olefinic and oxygenated chemical co-products.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Investigation of Ethane Dehydrogenation and Hydrogenolysis on Pt(111), Pt(211), and Pt(100): Bayesian Quantification and Correction of DFT-Based Enthalpic and Entropic Uncertainties

Computational investigations of heterogeneously catalyzed reactions using density functional theory (DFT) are often inaccurate, largely due to uncertainties in the choice of DFT functional (enthalpic uncertainty) and approximations for modeling adsorbate movement along the catalyst surface (entropic uncertainty). This work illustrates that both uncertainties are significant in the investigation of ethane dehydrogenation (EDH) and hydrogenolysis on Pt catalysts by considering the complete deconstruction of ethane on Pt(111), Pt(211), and Pt(100) using microkinetic modeling (MKM). Hence, this work uses both noncalibrated and Bayesian-calibrated MKMs to quantify and correct inaccuracies in macroscopic properties due to both uncertainties. A Bayesian approach to the correction of entropic errors was introduced using a “Modified Fermi Function (MFF)” to calibrate between the two bounds of entropy represented by the harmonic oscillator (HO) and free translator (FT) approximations. Regardless of enthalpic and entropic uncertainties, all three surfaces are capable of ethane activation; however, Pt(211) was found to be the most active and is largely responsible for methane production. Next, Pt(111) is largely responsible for acetylene production, and Pt(100) has the highest ethylene selectivity but is most susceptible to coking. By comparison of different calibrated models, the FT entropy approximation was found to better describe EDH under typical experimental conditions. Statistical evidence was found to support Pt(111) as the active site for EDH, assuming that one single site is responsible for the chemistry. On the three surfaces, competing second dehydrogenations to CH 2 CH 2 and CH 3 CH were observed as well as isomerization of CH 3 CH back to CH 2 CH 2 and deeper dehydrogenation of CH 3 CH. In conclusion, C–C cleavage was found to largely proceed via the CH 3 C intermediate on Pt(100) and Pt(111), while on Pt(211), it was via both CHC and CH 3 C.

Bayesian model selection↗
DOE OSTI2021

Cesium-Induced Active Sites for C–C Coupling and Ethanol Synthesis from CO 2 Hydrogenation on Cu/ZnO(000$\bar{1}$) Surfaces

The efficient conversion of carbon dioxide, a major air pollutant, into ethanol or higher alcohols is a big challenge in heterogeneous catalysis, generating great interest in both basic scientific research and commercial applications. Here, we report the facilitated methanol synthesis and the enabled ethanol synthesis from carbon dioxide hydrogenation on a catalyst generated by codepositing Cs and Cu on a ZnO(000$\bar{1}$) substrate. A combination of catalytic testing, X-ray photoelectron spectroscopy (XPS) measurements, and calculations based on density functional theory (DFT) and kinetic Monte Carlo (KMC) simulation was used. The results of XPS showed a clear change in the reaction mechanism when going from Cs/Cu(111) to a Cs/Cu/ZnO(000$\bar{1}$) catalyst. The Cs-promoting effect on C–C coupling is a result of a synergy among Cs, Cu, and ZnO components that leads to the presence of CH x and CH y O species on the surface. Furthermore, according to the DFT-based KMC simulations, the deposition of Cs introduces multifunctional sites with a unique structure at the Cu–Cs–ZnO interface, particularly being able to promote the interaction with CO 2 and thus the methanol synthesis predominantly via the formate pathway. More importantly, it tunes the CHO binding strongly enough to facilitate the HCOOH decomposition to CHO via the formate pathway, but weakly enough to allow further hydrogenation to methanol. The fine-tuning of CHO binding also enables a close alignment of a CHO pair to facilitate the C–C coupling and eventually ethanol synthesis. Our study opens new possibilities to allow the highly active and selective conversion of carbon dioxide to higher alcohols on widely used and low-cost Cu-based catalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Adsorbate-induced adatom formation on Au-Cu bimetallic alloys and its possible consequences for CO 2 electroreduction

The adsorbate-induced formation of sub-nanometer clusters on transition-metal single crystals observed in previous high-pressure microscopic studies hinted at the in-situ formation of unique active sites even on large nanoparticle catalysts. We propose that the adatom formation energy can be used as an energetic descriptor for the initial step toward the adsorbate-induced metal-cluster formation process. This descriptor can be efficiently computed using density functional theory (DFT) calculations and applied for screening and identification of metal catalysts where this phenomenon may play an important role in generating active sites in-situ. As a proof of concept, here, we construct an adatom formation energy database for three Au x Cu y alloys (x:y = 3:1, 1:1, or 1:3) and eighteen adsorbates (H, C, N, O, F, S, Cl, Br, I, CH x , NH x (x = 1 – 3), CO, NO, and OH) commonly involved in catalytic reactions. The energetics of adatom formation were examined in all cases where the (111) terrace, (211) step-edge, and (874) kink were the sources of the adatom. We demonstrate that the presence of an adsorbate could alter not only the energetics for adatom formation but also the elemental nature of the preferred adatom being formed. Using our database, we identified promising systems which favor adsorbate-induced adatom formation under near-ambient conditions. Specifically, CO-induced adatom formation on all three Au-Cu alloy surfaces could occur under CO 2 electroreduction (CO 2 RR) conditions. This phenomenon offers a qualitative explanation for the experimentally observed CO 2 RR activity on Au-Cu alloy catalysts. As a result, our methodology offers an easily expandable and efficient approach for large-scale catalyst screening with regards to adatom/cluster formation under reaction conditions and provides insight into the possible nature of active sites on alloy catalysts from a novel perspective.

Active site↗
DOE OSTI2024

Mechanocatalytic Hydrogenolysis of the Lignin Model Dimer Benzyl Phenyl Ether over Supported Palladium Catalysts

This work demonstrates the mechanocatalytic hydrogenolysis of the ether bond in the lignin model compound benzyl phenyl ether (BPE) and hardwood lignin isolated by hydrolysis with supercritical water. Pd catalysts with 4 wt % loading on Al 2 O 3 and SiO 2 supports achieve 100% conversion of BPE with a toluene production rate of (2.6–2.9) × 10 –5 mol·min –1 . The formation of palladium hydrides under H 2 gas flow contributes to an increase in the turnover frequency by a factor of up to 300 compared to Ni on silica–alumina. While a near-quantitative toluene yield is obtained, some of the phenolic products remain adsorbed on the catalyst.

36 MATERIALS SCIENCE↗
DOE OSTI2024

CatTestHub: A benchmarking database of experimental heterogeneous catalysis for evaluating advanced materials

The ability to quantitatively compare newly evolving catalytic materials and technologies is hindered by the widespread availability of catalytic data collected in a consistent manner. While certain catalytic chemistries have been widely studied across decades of scientific research, quantitative comparisons based on literature information is hindered by variability in reaction conditions, types of reported data, and reporting procedures. Here, we present CatTestHub, an open-access database dedicated to benchmarking experimental heterogeneous catalysis data. Combining systematically reported catalytic activity data for selected probe chemistries, with relevant material characterization and reactor configuration information, the database provides a collection of catalytic benchmarks for distinct classes of active site functionality. Through key choices in data access, availability, and traceability, CatTestHub seeks to balance the fundamental information needs of chemical catalysis and the FAIR data design principles. Details of the database architecture and the means through which to navigate it are presented, highlighting examples of catalytic insights readily drawn from the available benchmarking data. In its current iteration, CatTestHub spans over 250 unique experimental data points, collected over 24 solid catalysts, that facilitated the turnover of 3 distinct catalytic chemistries. Here, a roadmap is presented through which to expand the open-access platform that serves as a community wide benchmark, primarily through continuous addition of kinetic information on select catalytic systems by members of the heterogeneous catalysis community at large.

Benchmark↗
DOE OSTI2020

In-situ and In-operando Cobalt Oxidation Studied by Atom Probe Tomography

Heterogeneous catalysis is one of the pillars of the chemical industry and the “green chemistry” concept. However, the sparse understanding of surface mechanisms at molecular scale impedes development of high-performance catalysts and requires development of new tools and methodologies. Cobalt is notably able to dissociate CO 2 into CO(g) and O 2 (g), allowing further conversion to higher value compounds such as long-chain hydrocarbons. Such application leads inevitably to Co surface oxidation. Finally, from its pure form (Co(0)) to oxidized ones (CoO and Co 3 O 4 ) the formation mechanism remains unclear as well as the surface structure evolution and its influence on the chemical reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗