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At least 775 records · Page 43

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Dissecting Critical Factors for Electrochemical CO 2 Reduction on Atomically Precise Au Nanoclusters

Here, this work investigates the critical factors impacting electrochemical CO 2 reduction reaction (CO 2 RR) using atomically precise Au nanoclusters (NCs) as electrocatalysts. First, the influence of size on CO 2 RR is studied by precisely controlling NC size in the 1–2.5 nm regime. We find that the electrocatalytic CO partial current density increases for smaller NCs, but the CO Faradaic efficiency (FE) is not directly associated with the NC size. This indicates that the surface-to-volume ratio, i.e. the population of active sites, is the dominant factor for determining the catalytic activity, but the selectivity is not directly impacted by size. Second, we compare the CO 2 RR performance of Au 38 isomers (Au 38 Q and Au 38 T) to reveal that structural rearrangement of identical size NCs can lead to significant changes in both CO 2 RR activity and selectivity. Au 38 Q shows higher activity and selectivity towards CO than Au 38 T, and density functional theory (DFT) calculations reveal that the average formation energy of the key *COOH intermediate on the proposed active sites is significantly lower on Au 38 Q than Au 38 T. These results demonstrate how the structural isomerism can impact stabilization of reaction intermediates as well as the overall CO 2 RR performance of identical size Au NCs. Overall, this work provides important structure–property relationships for tailoring the NCs for CO 2 RR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Catalytic resonance theory for parametric uncertainty of programmable catalysis

Microkinetic models are useful tools for screening catalytic materials; however, errors in their input parameters can lead to significant uncertainty in model predictions of catalyst performance. Here, in this work, we investigate the impact of linear scaling and Brønsted-Evans-Polanyi relation parametric uncertainty on microkinetic predictions of programmable-catalyst performance. Two case studies are considered: a generic A-to-B prototype reaction and the oxygen evolution reaction (OER). The results show that error-unaware models can accurately predict trends and, for the prototype reaction, values of optimal waveform parameters. The specific model parameters driving output uncertainty are identified via variance-based global sensitivity analysis. However, predictions of dynamic rate enhancement can decrease when uncertainty is propagated into the models. In both cases, we identify operating conditions where the programmable catalyst achieves a rate enhancement of at least one order of magnitude despite parametric uncertainty in the model, supporting programmable catalysis as a viable strategy for exceeding the Sabatier limit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Acceleration of Pd-V intermetallic diffusion by hydrogen

Vanadium-based membranes have great potential for hydrogen purification due to their perfect selectivity, high permeability, and relatively low cost. With appropriate surface cleaning, V efficiently permeates hydrogen at elevated temperature, but performance declines due to its affinity to absorb impurities. Here, the application of palladium thin films maintains a clean surface that catalyzes hydrogen dissociation and recombination. Hydrogen permeation in Pd-V-Pd membranes initially reach theoretical permeability, but declines due to Pd-V interdiffusion. The objective of this work was to quantify the intermetallic diffusion process as a function of temperature and ambient. Pd-V composites were subjected to various annealing treatments and characterized using Auger electron spectroscopy, X-ray diffraction, and energy dispersive X-ray spectroscopy, as well as correlated to measurements of membrane permeability. In an inert environment Pd-V interdiffusion was observable as low as 300 °C, and the diffusion coefficient had an activation energy of 44 kJ/mol. Furthermore, the presence of hydrogen at partial pressures > 10 kPa accelerated interdiffusion six-fold at T = 400 °C. Membrane performance degraded with an activation energy 75 kJ/mol, suggesting that intermetallic diffusion leads to both a loss of catalytic activity and as well as degradation of bulk permeability. These findings provide a baseline for evaluating hydrogen permeable interdiffusion barriers to overcome these challenges.

08 HYDROGEN↗

DOE OSTI2021

Machine learning reveals sequence-function relationships in family 7 glycoside hydrolases

Family 7 glycoside hydrolases (GH7) are among the principal enzymes for cellulose degradation in nature and industrially. These important enzymes are often bimodular, including a catalytic domain and carbohydrate binding module (CBM) attached via a flexible linker, and exhibit an active site that binds cello-oligomers of up to ten glucosyl moieties. GH7 cellulases consist of two major subtypes: cellobiohydrolases (CBH) and endoglucanases (EG). Despite the critical importance of GH7 enzymes, there remain gaps in our understanding of how GH7 sequence and structure relate to function. Here, we employed machine learning to gain data-driven insights into relationships between sequence, structure, and function across the GH7 family. Machine-learning models, trained only on the number of residues in the active-site loops as features, were able discriminate GH7 CBHs and EGs with up to 99% accuracy, demonstrating that the lengths of loops A4, B2, B3, and B4 strongly correlate with functional subtype across the GH7 family. Classification rules were derived such that specific residues at 42 different sequence positions each predicted the functional subtype with accuracies surpassing 87%. A random forest model trained on residues at 19 positions in the catalytic domain predicted the presence of a CBM with 89.5% accuracy. Our ML results recapitulate, as top-performing features, a substantial number of the sequence positions determined by previous experimental studies to play vital roles in GH7 activity. We surmise that the yet-to-be-explored sequence positions among the top-performing features also contribute to GH7 functional variation and may be exploited to understand and manipulate function.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Impact of Selected High-Performance Fuel Blends on Three-Way Catalyst Light Off under Synthetic Spark-Ignition Engine-Exhaust Conditions

The U.S. Department of Energy funded Co-Optimization of Fuels and Engines initiative aims to simultaneously develop advanced engines along with high-performance fuels to reduce petroleum consumption. The engine exhaust of spark-ignited light-duty vehicles contains pollutants such as nitrogen oxides, carbon monoxide (CO), and non-methane organic gases. When operated above their “light-off” temperature, three-way catalysts (TWCs) efficiently control the emissions of these pollutants from the vehicle exhaust. However, below the catalyst light-off temperature, during cold start, the TWCs are not effective. Thus, the stringent environmental regulations necessitate cold-start compliance of advanced engines operating on novel fuels for commercialization. Exhaust composition strongly impacts the effectiveness of TWCs. Hence, ensuring that the high-performance fuels under consideration do not have detrimental effects on current emissions control technology is necessary. To mitigate cold-start emissions, a low light-off temperature of the fuel on the TWC is desirable. As real-world fuels are multicomponent blends, we conducted investigations into the light-off behavior of representative fuel mixtures on a three-mode redox-aged commercial TWC under synthetic engine-exhaust conditions. The high-performance fuels in this study included 10–30% volumetric levels of ethanol, isobutanol, diisobutylene, and an aromatic mixture. Each of these high-performance fuel components was mixed into a gasoline surrogate blendstock for oxygenate blending (BOB). Our results showed that aromatics and alkenes in the surrogate BOB inhibit low-temperature reactivity of alkanes, alcohols, and CO on the TWC and dominate the blend light-off behavior. All the high-performance fuel blends had a very similar light-off behavior to the surrogate gasoline BOB, indicating that blending up to 30% (by vol.) of high-performance blendstocks in a gasoline base fuel can potentially reduce greenhouse gas emissions through improved engine efficiency and petroleum displacement without jeopardizing the ability to meet emissions regulations. While some high-performance blendstocks demonstrated lower light-off temperatures than a surrogate gasoline blend, taking advantage of the higher catalytic reactivity of these blendstocks to reduce cold-start emissions would require reducing the aromatic content in petroleum-based market fuels.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Quantifying Percolated Triple Phase Boundary Density and Its Effects on Anodic Polarization in Ni-Infiltrated Ni/YSZ SOFC Anodes

Increasing the density of percolated triple phase boundaries (TPBs) by infiltrating nanoscale electrocatalysts can improve the performance of solid oxide fuel cell (SOFC) anodes. However, the complex microstructure of these infiltrated nanocatalysts creates challenges in quantifying their role in anode performance improvements. In this research, scanning electron microscopy of fractured cross-sections of a Ni-nanocatalyst infiltrated anodic symmetric cell along with three-dimensional (3-D) reconstruction of the same anode have been used to quantify the changes in percolated TPB densities due to infiltration. This change in percolated TPB density has been compared to the improvement in anode activation polarization resistance measured by electrochemical impedance spectroscopy (EIS). It was found that increased TPB densities only partially accounted for the measured performance improvement. Distribution of relaxation times (DRT) analyses showed that a reduction in the time constants of the catalytic processes in the anode also play a role, suggesting that the added nanoscale percolated TPB boundaries are more electrochemically active as compared to the cermet TPB boundaries.

25 ENERGY STORAGE↗

DOE OSTI2020

Spatial Atomic Layer Deposition to Scale Manufacturing of Robust Catalysts for Biomass Conversion Applications: Cooperative Research and Development Final Report, CRADA Number CRD-17-715

This CRADA will facilitate technology maturation for NREL-developed ALD-coated catalyst materials that are tailored for durability during harsh biomass conversion chemistries. This project will address optimizing process parameters for scale-up of Al2O3 ALD-coated catalysts, demonstrating ALD-coated catalyst performance for muconic acid hydrogenation, and validating economic models that project significant cost benefits for ALD-enhanced catalytic processes. This work will strengthen private-public partnerships in the area of advanced catalyst manufacturing for energy-related technology. Critical information will be collected to elevate the Technology Readiness Level and increase our competitiveness for cooperative R&D agreements and licensing. Success of this work will be crosscutting as it can facilitate advanced catalyst development for both renewable and conventional processes.

09 BIOMASS FUELS↗

DOE OSTI2021

Analysis of Ion-Exchanged ZSM-5, BEA, and SSZ-13 Zeolite Trapping Materials under Realistic Exhaust Conditions

An industry-defined evaluation protocol was used to evaluate the hydrocarbon trapping (HCT) and passive NOx adsorption (PNA) potential for BEA, ZSM-5, and SSZ-13 zeolites with ion-exchanged Pd or Ag. All materials underwent 700 °C degreening prior to exposure to an industry-derived protocol gas stream, which included NOx, ethylene, toluene, and decane as measured trapping species as well as common exhaust gasses CO, H2O, O2, CO2, and H2. Evaluation showed that BEA and ZSM-5 zeolites were effective at trapping hydrocarbons (HCs), as saturation was not achieved after 30 min of exposure. SSZ-13 also stored HCs but was only able to adsorb 20–25% compared to BEA and ZSM-5. The presence of Ag or Pd did not impact the overall HC uptake, particularly in the first three minutes. Pd/zeolites had significantly lower THC release temperature, and it aided in the conversion of the released HCs; Ag only had a moderate effect in both areas. With respect to NOx adsorption, the level of uptake was much lower than HCs on all samples, and Ag or Pd was necessary with Pd being notably more effective. Additionally, only Pd/ZSM-5 and Pd/SSZ-13 continue to store a portion of the NOx above 200 °C, which is critical for downstream selective catalytic NOx reduction (SCR). Hydrothermal aging (800 °C for 50 h) of a subset of the samples were performed: BEA, Pd/BEA, ZSM-5, Pd/ZSM-5, and Pd/SSZ-13. There was a minimal effect on the HC storage, ~10% reduction in capacity with no effect on release temperature; however, only Pd/SSZ-13 showed significant NOx storage after aging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1994

Multiblock analysis for Shuttle Orbiter reentry heating from Mach 24 to Mach 12

A multiblock, laminar heating analysis for the shuttle orbiter at three trajectory points ranging from Mach 24.3 to Mach 12.86 on reentry is described. The analysis is performed using the Langley Aerothermodynamic Upwind Relaxation Algorithm with a seven species chemical nonequilibrium model. A finite-catalytic-wall model appropriate for shuttle tiles at a radiative equilibrium wall temperature is applied. Computed heating levels are generally in good agreement with the flight data, although a few rather large discrepancies remain unexplained. The multiblock relaxation strategy partitions the flowfield into manageable blocks requiring a fraction of the computational resources (time and memory) required by a full domain approach. In fact, the computational cost for a solution at even a single trajectory point would be prohibitively expensive at the given resolution without the multiblock approach. Converged blocks are reassembled to enable a fully coupled converged solution over the entire vehicle, starting from a nearly converged initial condition.

LANGLEY AEROTHERMODYNAMIC UPWI↗

DOE OSTI2021

Catalytic materials for lithium-sulfur batteries: mechanisms, design strategies and future perspective

Lithium-sulfur batteries (LSBs) are attractive candidates for post-lithium-ion battery technologies because of their ultrahigh theoretical energy density and low cost of active cathode materials. However, the commercialization of LSBs remains extremely challenging primarily due to poor cycling performance and safety concerns, which are inherently caused by low conductivity of S 8 and Li 2 S, severe polysulfide shuttling, and high polarization by solid Li 2 S 2 /Li 2 S deposition. Catalytic materials could facilitate the large-scale practical application of LSBs by overcoming all these challenges. In this review, we investigate the sulfur species evolution in LSBs and explore the roles of catalytic materials in charge/discharge processes, highlighting the catalysis of solid S 8 to liquid polysulfides and solid Li 2 S 2 to Li 2 S. Furthermore, we offer systematic strategies from atomic to macro levels, including defect engineering, morphology engineering and catalyst compositing, to enhance catalysis efficiency in terms of sulfur supercooling, fast charge transfer, thiosulfate generation, disulfide bond cleavage, tuneable Li 2 S growth and Li 2 S decomposition enhancement. Finally, the design and availability of the proposed catalytic materials will further advance LSB technology from coin cells and pouch cells to the subsequent commercialization scale.

25 ENERGY STORAGE↗

DOE OSTI2020

Multi-modal surface analysis of porous films under operando conditions

Practical catalysts with a porous framework, such as zeolites, host catalytic reactions at active sites engrained in the pores and channels of the scaffold. The mechanism of interaction at these active sites, defining catalyst performance, remains elusive, in large part, due to the lack of surface characterization methods available for thick films or powders. Here, we present thin film analogs of practical catalysts that allow for the implementation of surface characterization tools, including advanced microscopy and operando spectroscopy methodologies. Specifically, we investigated bilayer silica, MFI nanosheets, and UiO-66 thin films using a multi-modal approach addressing film growth, characterization, and gas adsorption aimed at understanding catalytic activity, reactivity, and selectivity properties, as defined by molecular-level changes in the reaction mechanism.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Mechanistic Insights into the Catalytic Condensation of Methyl Ketones on MgO Surfaces

Ketone coupling via aldol condensation is one of the promising routes to produce cyclic and value-added precursors for renewable hydrocarbon biofuels. A first-principles-based microkinetic modeling is performed to evaluate the surface-mediated reaction mechanisms and the role of water molecules in the observed activities for 2-pentanone and 3-pentanone aldol condensation on dehydroxylated MgO(111) surface and hydroxylated terminated surface[OH-MgO(111)]. Here, we have identified the enhancement of the surface OH group to MgO(111) surface catalytic activity by destabilizing the binding strength of reaction intermediates and reducing the energy barriers of rate-determining steps(proton transfer and dehydration steps). The 2-pentanone has one elementary step less in the complete reaction mechanism of aldol condensation and preferable energy barrier for proton transfer and dehydration steps, revealing 2-pentanone as terminal ketone is more reactive than 3-pentanone as central ketone. The water molecules dominated the OH-MgO( 111) surface after further addition of water, leading to the reduction of turnover frequency of the aldol condensation dimer product as the loss of aldol condensation reaction intermediates in competitive adsorption with water molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

The number of catalytic cycles in an enzyme’s lifetime and why it matters to metabolic engineering

Metabolic engineering uses enzymes as parts to build biosystems for specified tasks. Although a part’s working life and failure modes are key engineering performance indicators, this is not yet so in metabolic engineering because it is not known how long enzymes remain functional in vivo or whether cumulative deterioration (wear-out), sudden random failure, or other causes drive replacement. Consequently, enzymes cannot be engineered to extend life and cut the high energy costs of replacement. Guided by catalyst engineering, we adopted catalytic cycles until replacement (CCR) as a metric for enzyme functional life span in vivo. CCR is the number of catalytic cycles that an enzyme mediates in vivo before failure or replacement, i.e., metabolic flux rate/protein turnover rate. We used estimated fluxes and measured protein turnover rates to calculate CCRs for ~100–200 enzymes each from Lactococcus lactis, yeast, and Arabidopsis. CCRs in these organisms had similar ranges (<10 3 to >10 7 ) but different median values (3–4 × 10 4 in L. lactis and yeast versus 4 × 10 5 in Arabidopsis). In all organisms, enzymes whose substrates, products, or mechanisms can attack reactive amino acid residues had significantly lower median CCR values than other enzymes. Taken with literature on mechanism-based inactivation, the latter finding supports the proposal that 1) random active-site damage by reaction chemistry is an important cause of enzyme failure, and 2) reactive noncatalytic residues in the active-site region are likely contributors to damage susceptibility. Enzyme engineering to raise CCRs and lower replacement costs may thus be both beneficial and feasible.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Predicting the Activity and Selectivity of Bimetallic Metal Catalysts for Ethanol Reforming using Machine Learning

Machine learning is ideally suited for the pattern detection in large uniform datasets, but consistent experimental datasets on catalyst studies are often small. Here we demonstrate how a combination of machine learning and first-principles calculations can be used to extract knowledge from a relatively small set of experimental data. The approach is based on combining a complex machine-learning model trained on an extensive computational library of transition-state energies with simple linear regression models of experimental catalytic activities and selectivities from the literature. Using the combined model, we identify the key C–C bond scission reactions involved in ethanol reforming and perform a computational screening for ethanol reforming on monolayer bimetallic catalysts with architectures TM-Pt-Pt(111) and Pt-TM-Pt(111) (TM = 3d transition metals). The model also predicts four promising catalyst compositions for future experimental studies. In conclusion, the approach is not limited to ethanol reforming but is of general use for the interpretation of experimental observations as well as for the computational discovery of novel catalytic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Catalytic DNA Polymerization Can Be Expedited by Active Product Release**

Abstract The sequence‐specific hybridization of DNA facilitates its use as a building block for designer nanoscale structures and reaction networks that perform computations. However, the strong binding energy of Watson–Crick base pairing that underlies this specificity also causes the DNA dehybridization rate to depend sensitively on sequence length and temperature. This strong dependency imposes stringent constraints on the design of multi‐step DNA reactions. Here we show how an ATP‐dependent helicase, Rep‐X, can drive specific dehybridization reactions at rates independent of sequence length, removing the constraints of equilibrium on DNA hybridization and dehybridization. To illustrate how this new capacity can speed up designed DNA reaction networks, we show that Rep‐X extends the range of conditions where the primer exchange reaction, which catalytically adds a domain provided by a hairpin template to a DNA substrate, proceeds rapidly.

Moerman, Pepijn G.↗

DOE OSTI2022

Catalytic DNA Polymerization Can Be Expedited by Active Product Release**

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Synthesis of NiRu-Layered Double Hydroxide for Enhanced Oxygen Evolution Reaction

Nickel−ruthenium layered double hydroxide (NiRu-LDH) was synthesized by coprecipitation using formamide as both solvent and intercalant. The synthesis was performed at various temperatures to study the impact of temperature on electrochemical performance. Temperature plays a vital role in optimizing LDH synthesis to enhance oxygen evolution reaction (OER) efficiency. The optimal temperature yielded a well-defined morphology with balanced crystallinity, leading to more active sites and improved charge transfer. Electrochemical tests indicated that the NiRu-LDH sample prepared at 50 °C (NiRu-LDH-50) required only 280 mV overpotential versus the reversible hydrogen electrode to achieve 10 mA/cm 2 and exhibited a low Tafel slope of 52 mV/dec, demonstrating excellent catalytic kinetics. This study presents the synthesis of NiRu-LDH via coprecipitation and emphasizes how reaction temperature influences LDH structural properties and OER performance.

Catalysts↗

DOE OSTI2021

Microwave-enhanced catalytic ammonia synthesis under moderate pressure and temperature

In this study, an alternative approach based on microwave-enhanced ammonia synthesis for Haber-Bosch process was carried out under moderate pressure of 0.1–0.65 MPa and temperature range of 280–400 °C over a stable CsRu/CeO 2 catalyst. The ammonia production rate is significantly improved under microwave conditions. At 0.65 MPa and 320 °C, maximum ammonia production rate was achieved at H 2 /N 2 ratio of 1/1. Stable performance was obtained in a 6-cycles of startup-shutdown operation for cumulative on-line time of 80 h. The work demonstrates the potential of microwave catalytic technology for the distributed ammonia synthesis using renewable power having intermittent nature of energy supply.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗