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At least 487 records · Page 27

Resource-Efficient Chemistry on Quantum Computers with the Variational Quantum Eigensolver and The Double Unitary Coupled-Cluster approach

Applications of quantum simulation algorithms to obtain electronic energies of molecules on noisy intermediate-scale quantum (NISQ) devices require careful consideration of resources describing the complex electron correlation effects. In modeling second-quantized problems, the biggest challenge confronted is that the number of qubits scales linearly with the size of molecular basis. This poses a significant limitation on the size of the basis sets and the number of correlated electrons included in quantum simulations of chemical processes. To address this issue and to enable more realistic simulations on NISQ computers, we employ the double unitary coupled-cluster (DUCC) method to effectively downfold correlation effects into the reduced-size orbital space, commonly referred to as the active space. Using downfolding techniques, we demonstrate that properly constructed effective Hamiltonians can capture the effect of the whole orbital space in small-size active spaces. Combining the downfolding pre-processing technique with the Variational Quantum Eigensolver, we solve for the ground-state energy of H2 and Li2 in the cc-pVTZ basis using the DUCC-reduced active spaces. We compare these results to full configuration-interaction and high-level coupled-cluster reference calculations.

quantum computing, variational quantum solver, cou↗

The Effects of Buoyancy and Dilution on the Structure and Lift-Off of Coflow Laminar Diffusion Flames

The ability to predict the coupled effects of complex transport phenomena with detailed chemical kinetics in diffusion flames is critical in the modeling of turbulent reacting flows and in understanding the processes by which soot formation and radiative transfer take place. In addition, an understanding of those factors that affect flame extinction in diffusion flames is critical in the suppression of fires and in improving engine efficiency. A goal of this work is to bring to microgravity flame studies the detailed experimental and numerical tools that have been used to study ground-based systems. This will lead to a more detailed understanding of the interaction of convection, diffusion and chemistry in a nonbuoyant environment. To better understand these phenomena, experimental and computational studies of a coflow laminar diffusion flame have been carried out. To date, these studies have focused on a single set of flow conditions, in which a nitrogen-diluted methane fuel stream (65% methane by volume) was surrounded by an air coflow, with exit velocities matched at 35 cm/s. Of particular interest is the change in flame shape due to the absence of buoyant forces, as well as the amount of diluent in the fuel stream and the coflow velocity. As a sensitive marker of changes in the flame shape, the number densities of excited-state CH (A(exp 2 delta) denoted CH*), and excited-state OH (A(exp 2 sigma, denoted OH*) are measured. CH* and OH* number densities are deconvoluted from line-of-sight chemiluminescence measurements made on the NASA KC135 reduced-gravity aircraft. Measured signal levels are calibrated, post-flight, with Rayleigh scattering. In extending the study to microgravity conditions, improvements to the computational model have been made and new calculations performed for a range of gravity conditions. In addition, modifications to the experimental approach were required as a consequence of the constraints imposed by existing microgravity facilities. Results from the computations and experiments are presented.

Walsh, Kevin T.↗

Laboratory studies of chemical and photochemical processes relevant to stratospheric ozone

The purpose of this project is to reduce the uncertainty in several key gas-phase kinetic processes which impact our understanding of stratospheric ozone. The main emphasis of this work is on measuring rate coefficients and product channels for reactions of HO(sub x) and NO(sub x) species in the temperature range 200 K to 240 K relevant to the lower stratosphere. Other areas of study have included infrared spectroscopic studies of the HO2 radical, measurements of OH radical reactions with alternative fluorocarbons, and determination of the vapor pressures of nitric acid hydrates under stratospheric conditions. The results of these studies will improve models of stratospheric ozone chemistry and predictions of perturbations due to human influences. In this annual report, we focus on our recent accomplishments in the quantitative spectroscopy of the HO2 radical. This report details the measurements of the broadening coefficients for the v(sub 2) vibrational band. Further measurements of the vapor pressures of nitric acid hydrates relevant to the polar stratospheric cloud formation indicate the importance of metastable crystalline phases of H2SO4, HNO3, and H2O. Large particles produced from these metastable phases may provide a removal mechanism for HNO3 in the polar stratosphere.

Zahniser, Mark S.↗

Decadal Changes in Summertime Reactive Oxidized Nitrogen and Surface Ozone over the Southeast United States

Widespread efforts to abate ozone (O3) smog have significantly reduced emissions of nitrogen oxides (NOx) over the past 2 decades in the Southeast US, a place heavily influenced by both anthropogenic and biogenic emissions. How reactive nitrogen speciation responds to the reduction in NOx emissions in this region remains to be elucidated. Here we exploit aircraft measurements from ICARTT (International Consortium for Atmospheric Research on Transport and Transformation - July-August 2004), SENEX (Southeast Nexus - June-July 2013), and SEAC4RS (Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys - August-September 2013) and long-term ground measurement networks alongside a global chemistry-climate model to examine decadal changes in summertime reactive oxidized nitrogen (RON) and ozone over the Southeast US. We show that our model can reproduce the mean vertical profiles of major RON species and the total (NO (sub y)) in both 2004 and 2013. Among the major RON species, nitric acid (HNO3) is dominant (approximately 42-45 percent), followed by NOx (31 percent), total peroxy nitrates (Sigma PNs; 14 percent), and total alkyl nitrates (Sigma ANs; 9-12 percent) on a regional scale. We find that most RON species, including NOx, Sigma PNs, and HNO3, decline proportionally with decreasing NOx emissions in this region, leading to a similar decline in NO (sub y). This linear response might be in part due to the nearly constant summertime supply of biogenic VOC (Volatile Organic Compounds) emissions in this region. Our model captures the observed relative change in RON and surface ozone from 2004 to 2013. Model sensitivity tests indicate that further reductions of NOx emissions will lead to a continued decline in surface ozone and less frequent high-ozone events.

Li, Jingyi↗

Charge Movement and Structural Changes in the Gas-Phase Unfolding of Multimeric Protein Complexes Captured by Native Top-Down Mass Spectrometry

The extent to which noncovalent protein complexes retain native structure in the gas phase is highly dependent on experimental conditions. Energetic collisions with background gas can cause structural changes ranging from unfolding to subunit dissociation. Additionally, recent studies have highlighted the role of charge in such structural changes, but the mechanism is not completely understood. In this study, native top down (native TD) mass spectrometry was used to probe gas-phase structural changes of alcohol dehydrogenase (ADH, 4mer) under varying degrees of in-source activation. Changes in covalent backbone fragments produced by electron capture dissociation (ECD) or 193 nm ultraviolet photodissociation (UVPD) were correlated to structural changes of the ADH 4mer. ECD fragments indicated unfolding started at the N-terminus, and the charge states of UVPD fragments enabled monitoring of charge migration to the unfolded regions. Interestingly, UVPD fragments also indicated that the charge at the “unfolding” N-terminus of ADH decreased at high in-source activation energies after the initial increase. We proposed a possible “refolding-after-unfolding” mechanism, as further supported by monitoring hydrogen elimination from radical a-ions produced by UVPD at the N-terminus of ADH. However, “refolding-after-unfolding” with increasing in-source activation was not observed for charge-reduced ADH, which likely adopted compact structures that are resistant to both charge migration and unfolding. Combined, these results support a charge-directed unfolding mechanism for protein complexes. Overall, an experimental framework was outlined for utilizing native TD to generate structure-informative mass spectral signatures for protein complexes that complement other structure characterization techniques, such as ion mobility spectrometry and computational modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Heat transport in liquid water from first-principles and deep neural network simulations

In this work, we compute the thermal conductivity of water within linear response theory from equilibrium molecular dynamics simulations, by adopting two different approaches. In one, the potential energy surface (PES) is derived on the fly from the electronic ground state of density functional theory (DFT) and the corresponding analytical expression is used for the energy flux. In the other, the PES is represented by a deep neural network (DNN) trained on DFT data, whereby the PES has an explicit local decomposition and the energy flux takes a particularly simple expression. By virtue of a gauge invariance principle, established by Marcolongo, Umari, and Baroni, the two approaches should be equivalent if the PES were reproduced accurately by the DNN model. We test this hypothesis by calculating the thermal conductivity, at the GGA (PBE) level of theory, using the direct formulation and its DNN proxy, finding that both approaches yield the same conductivity, in excess of the experimental value by approximately 60%. Besides being numerically much more efficient than its direct DFT counterpart, the DNN scheme has the advantage of being easily applicable to more sophisticated DFT approximations, such as meta-GGA and hybrid functionals, for which it would be hard to derive analytically the expression of the energy flux. We find in this way that a DNN model, trained on meta-GGA (SCAN) data, reduces the deviation from experiment of the predicted thermal conductivity by about 50%, leaving the question open as to whether the residual error is due to deficiencies of the functional, to a neglect of nuclear quantum effects in the atomic dynamics, or, likely, to a combination of the two.

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High-throughput screening of tribological properties of monolayer films using molecular dynamics and machine learning

Monolayer films have shown promise as a lubricating layer to reduce friction and wear of mechanical devices with separations on the nanoscale. These films have a vast design space with many tunable properties that can affect their tribological effectiveness. For example, terminal group chemistry, film composition, and backbone chemistry can all lead to films with significantly different tribological properties. This design space, however, is very difficult to explore without a combinatorial approach and an automatable, reproducible, and extensible workflow to screen for promising candidate films. Here, using the Molecular Simulation Design Framework (MoSDeF), a combinatorial screening study was performed to explore 9747 unique monolayer films (116 964 total simulations) and a machine learning (ML) model using a random forest regressor, an ensemble learning technique, to explore the role of terminal group chemistry and its effect on tribological effectiveness. The most promising films were found to contain small terminal groups such as cyano and ethylene. The ML model was subsequently applied to screen terminal group candidates identified from the ChEMBL small molecule library. Approximately 193 131 unique film candidates were screened with approximately a five order of magnitude speed-up in analysis compared to simulation alone. The ML model was thus able to be used as a predictive tool to greatly speed up the initial screening of promising candidate films for future simulation studies, suggesting that computational screening in combination with ML can greatly increase the throughput in combinatorial approaches to generate in silico data and then train ML models in a controlled, self-consistent fashion.

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Model Experiments and Model Descriptions

The Second Workshop on Stratospheric Models and Measurements Workshop (M&M II) is the continuation of the effort previously started in the first Workshop (M&M I, Prather and Remsberg [1993]) held in 1992. As originally stated, the aim of M&M is to provide a foundation for establishing the credibility of stratospheric models used in environmental assessments of the ozone response to chlorofluorocarbons, aircraft emissions, and other climate-chemistry interactions. To accomplish this, a set of measurements of the present day atmosphere was selected. The intent was that successful simulations of the set of measurements should become the prerequisite for the acceptance of these models as having a reliable prediction for future ozone behavior. This section is divided into two: model experiment and model descriptions. In the model experiment, participant were given the charge to design a number of experiments that would use observations to test whether models are using the correct mechanisms to simulate the distributions of ozone and other trace gases in the atmosphere. The purpose is closely tied to the needs to reduce the uncertainties in the model predicted responses of stratospheric ozone to perturbations. The specifications for the experiments were sent out to the modeling community in June 1997. Twenty eight modeling groups responded to the requests for input. The first part of this section discusses the different modeling group, along with the experiments performed. Part two of this section, gives brief descriptions of each model as provided by the individual modeling groups.

Jackman, Charles H.↗

Connecting Regional Aerosol Emissions Reductions to Local and Remote Precipitation Responses

The unintended climatic implications of aerosol and precursor emission reductions implemented to protect public health are poorly understood. We investigate the precipitation response to regional changes in aerosol emissions using three coupled chemistry-climate models: NOAA Geophysical Fluid Dynamics Laboratory Coupled Model 3 (GFDL-CM3), NCAR Community Earth System Model (CESM1), and NASA Goddard Institute for Space Studies ModelE2 (GISS-E2). Our approach contrasts a long present-day control simulation from each model (up to 400 years with perpetual year 2000 or 2005 emissions) with 14 individual aerosol emissions perturbation simulations (160-240 years each). We perturb emissions of sulfur dioxide and/or carbonaceous aerosol within six world regions and assess the significance of precipitation responses relative to internal variability determined by the control simulation and across the models. Global and regional precipitation mostly increases when we reduce regional aerosol emissions in the models, with the strongest responses occurring for sulfur dioxide emissions reductions from Europe and the United States. Precipitation responses to aerosol emissions reductions are largest in the tropics and project onto the El Nino Southern Oscillation (ENSO). Regressing precipitation onto an Indo-Pacific zonal sea level pressure gradient index (a proxy for ENSO) indicates that the ENSO component of the precipitation response to regional aerosol removal can be as large as 20% of the total simulated response. Precipitation increases in the Sahel in response to aerosol reductions in remote regions because an anomalous interhemispheric temperature gradient alters the position of the Intertropical Convergence Zone (ITCZ). This mechanism holds across multiple aerosol reduction simulations and models.

Westervelt, Daniel M.↗

$\mathrm{CROPSR}$: an automated platform for complex genome-wide $\mathrm{CRISPR}$ g$\mathrm{RNA}$ design and validation

CRISPR/Cas9 technology has become an important tool to generate targeted, highly specific genome mutations. The technology has great potential for crop improvement, as crop genomes are tailored to optimize specific traits over generations of breeding. Many crops have highly complex and polyploid genomes, particularly those used for bioenergy or bioproducts. The majority of tools currently available for designing and evaluating gRNAs for CRISPR experiments were developed based on mammalian genomes that do not share the characteristics or design criteria for crop genomes. We have developed an open source tool for genome-wide design and evaluation of gRNA sequences for CRISPR experiments, CROPSR. The genome-wide approach provides a significant decrease in the time required to design a CRISPR experiment, including validation through PCR, at the expense of an overhead compute time required once per genome, at the first run. To better cater to the needs of crop geneticists, restrictions imposed by other packages on design and evaluation of gRNA sequences were lifted. A new machine learning model was developed to provide scores while avoiding situations in which the currently available tools sometimes failed to provide guides for repetitive, A/T-rich genomic regions. We show that our gRNA scoring model provides a significant increase in prediction accuracy over existing tools, even in non-crop genomes. CROPSR provides the scientific community with new methods and a new workflow for performing CRISPR/Cas9 knockout experiments. CROPSR reduces the challenges of working in crops, and helps speed gRNA sequence design, evaluation and validation. We hope that the new software will accelerate discovery and reduce the number of failed experiments.

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Optimizing the Operational Parameters of an Electrochemical Purification Cell for Corrosion Mitigation in CSP Plants During Operation: Preprint

To make concentrating solar power (CSP) cost-competitive, the next generation of CSP plants will increase efficiency by operating at a higher temperature, which will require a new thermal energy storage material. One option for the thermal energy storage material is a ternary chloride salt that is stable at the temperatures required, but reacts easily with the atmosphere to form MgOHCl, a corrosive impurity. If left unchecked, this impurity will corrode the containment alloys, potentially leading to dangerous spills. We are working to design an electrochemical purification cell to remove MgOHCl from the molten chloride salt during CSP plant operation. In this paper, we use predictive modeling to assess the rate at which purification must occur. Additionally, we analyze possible process flow pathways for the molten chloride salts. Ultimately, we determine that implementation of a single reactor through which all chloride salts flow is the most efficient design to reduce impurity concentration below 0.1 mol % impurity.

concentrating solar power↗

Assessing Uncertainties and Approximations in Solar Heating of the Climate System

In calculating solar radiation, climate models make many simplifications, in part to reduce computational cost and enable climate modeling, and in part from lack of understanding of critical atmospheric information. Whether known errors or unknown errors, the community's concern is how these could impact the modeled climate. The simplifications are well known and most have published studies evaluating them, but with individual studies it is difficult to compare. Here, we collect a wide range of such simplifications in either radiative transfer modeling or atmospheric conditions and assess potential errors within a consistent framework on climate-relevant scales. We build benchmarking capability around a solar heating code (Solar-J) that doubles as a photolysis code for chemistry and can be readily adapted to consider other errors and uncertainties. The broad classes here include: use of broad wavelength bands to integrate over spectral features; scattering approximations that alter phase function and optical depths for clouds and gases; uncertainty in ice-cloud optics; treatment of fractional cloud cover including overlap; and variability of ocean surface albedo. We geographically map the errors in W m -2 using a full climate re-creation for January 2015 from a weather forecasting model. For many approximations assessed here, mean errors are ~2 W m -2 with greater latitudinal biases and are likely to affect a model’s ability to match the current climate state. Combining this work with previous studies, we make priority recommendations for fixing these simplifications based on both the magnitude of error and the ease or computational cost of the fix.

58 GEOSCIENCES↗

El Chichon volcanic aerosols - Impact of radiative, thermal, and chemical perturbations

The impact of the March-April, 1982 eruption of El Chichon volcano on the earth's stratospheric chemistry is examined. Calculations, performed using a one-dimensional radiative transfer model, predict that total radiation increased by 8 percent within the aerosol layer longward of 3000 A. Consequently, changes in the photolysis rates were obtained with a photochemical model, which can in part explain the observed ozone changes; the results agree qualitatively with observations on other species, but fail to quantitatively account for the observed significant decreases in NO and NO2 and increases in HCl. A heterogeneous reaction, catalyzed by aerosol surfaces, which transforms ClNO3 into HCl is proposed, which would provide a pathway for sequestering NO(x) and at the same time reducing ClNO3 in favor of HCl.

Michelangeli, Diane V.↗

Catalytic Ignition and Upstream Reaction Propagation in Monolith Reactors

Using numerical simulations, this work demonstrates a concept called back-end ignition for lighting-off and pre-heating a catalytic monolith in a power generation system. In this concept, a downstream heat source (e.g. a flame) or resistive heating in the downstream portion of the monolith initiates a localized catalytic reaction which subsequently propagates upstream and heats the entire monolith. The simulations used a transient numerical model of a single catalytic channel which characterizes the behavior of the entire monolith. The model treats both the gas and solid phases and includes detailed homogeneous and heterogeneous reactions. An important parameter in the model for back-end ignition is upstream heat conduction along the solid. The simulations used both dry and wet CO chemistry as a model fuel for the proof-of-concept calculations; the presence of water vapor can trigger homogenous reactions, provided that gas-phase temperatures are adequately high and there is sufficient fuel remaining after surface reactions. With sufficiently high inlet equivalence ratio, back-end ignition occurs using the thermophysical properties of both a ceramic and metal monolith (coated with platinum in both cases), with the heat-up times significantly faster for the metal monolith. For lower equivalence ratios, back-end ignition occurs without upstream propagation. Once light-off and propagation occur, the inlet equivalence ratio could be reduced significantly while still maintaining an ignited monolith as demonstrated by calculations using complete monolith heating.

Struk, Peter M.↗

Preferential Direction of Electron Transfers at a Dye–Metal Oxide Interface with an Insulating Fluorinated Self-Assembled Monolayer and MgO

Slowing non-desirable electron transfer reactions at metal oxide-dye interfaces is important for many technologies. Specifically, after an interfacial photoinduced charge separation event at a metal oxide-dye interface, it is critically important to limit the rate of electron transfer reactions back to sensitizers and to limit electron transfer reactions between the electrolyte and the metal oxide. Ruthenium-based dyes at metal oxide interfaces are widely used in many fields; however, these dyes often have poor surface insulation resulting in fast recombination kinetics with transition metal-based redox shuttles in an electrolyte. This work explores two semiconductor surface modification strategies designed to minimize recombination events of electrons in TiO 2 with oxidized redox shuttles using a fluorinated siloxane insulator (PFTS) and a metal oxide insulator (MgO) with a well-known Ru dye, B11. Additionally, the influence of these treatments on the rate and duration of photoinduced interfacial charge separation at the TiO 2 -dye interface was examined. The TiO 2 -dye-redox shuttle systems were studied via dye-sensitized solar cell current-voltage curve, incident photon-to-current conversion efficiency, small-modulated photovoltage transient, time-correlated single photon counting, and transient absorption spectroscopy measurements. MgO was found to decrease the rate of the electron transfer reaction from the metal oxide to the electrolyte, decrease the rate of the electron transfer reaction to the oxidized dye from TiO 2 , increase the electron transfer reaction rate from a reduced redox shuttle to an oxidized dye, and decrease the electron injection rate from the photoexcited dye to TiO2. Interestingly, PFTS was found to desirably improve on these rates relative to MgO or untreated TiO 2 . Here, a model based on electrostatic interactions is presented to explain the exceptional behavior of PFTS with DFT computational analysis of PFTS supporting this model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A System for Standardizing and Combining U.S. Environmental Protection Agency Emissions and Waste Inventory Data

The U.S. Environmental Protection Agency (USEPA) provides databases that agglomerate data provided by companies or states reporting emissions, releases, wastes generated, and other activities to meet statutory requirements. These databases, often referred to as inventories, can be used for a wide variety of environmental reporting and modeling purposes to characterize conditions in the United States. Yet, users are often challenged to find, retrieve, and interpret these data due to the unique schemes employed for data management, which could result in erroneous estimations or double-counting of emissions. To address these challenges, a system called Standardized Emission and Waste Inventories (StEWI) has been created. The system consists of four python modules that provide rapid access to USEPA inventory data in standard formats and permit filtering and combination of these inventory data. When accessed through StEWI, reported emissions of carbon dioxide to air and ammonia to water are reduced approximately two- and four-fold, respectively, to avoid duplicate reporting. StEWI will greatly facilitate the use of USEPA inventory data in chemical release and exposure modeling and life cycle assessment tools, among other things. To date, StEWI has been used to build the recent USEEIO model and the baseline electricity life cycle inventory database for the Federal LCA Commons.

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Robust highly durable solid oxide fuel cell cathodes – Improved materials compatibility & self-regulating surface chemistry

Solid oxide fuel cells (SOFCs) are electrochemical conversion devices that directly transform hydrogen or hydrocarbon fuels to electricity, with energy efficiencies as high as 90%, coupled with reduced emissions. Several factors, however, remain to be addressed when considering scale-up of SOFC technology, including the need to overcome decreased performance due to sluggish rates of the oxygen reduction reaction (ORR) at the cathode under reduced temperatures and susceptibility to degradation in performance from surface poisoning e.g. from chromia, while limiting the use of critical raw materials (lanthanides and transition metals) present in high performing mixed ionic electronic conducting electrodes like (La,Sr)CoO 3 (LSC). In this project we explored the key descriptors for determining ORR activity in SOFC electrodes and tried to recover performance degradation by applying them to SOFC electrodes. In order to do this, we first selected a model mixed ionic electronic conducting (MIEC) oxide, Pr-doped CeO 2 (Pr 0.1 Ce 0.9 O 2-δ , PCO), which is a chemically stable fluorite and free of inherent poison sources (e.g. Sr segregation in LSC) that potentially react with external impurities such as Cr-species vaporized from the interconnect. The three approaches originally planned in this project are as follows: 1) evaluation of scavenger exsolution characteristics, 2) study of scavengers gettering efficacy following Cr and Si poisoning and 3) integration of new compositions into porous electrodes. Among them, exceptional progress has been made in 2) and 3), especially understanding the role of surface infiltrants in impacting electrode performance and degradation of PCO materials. We found that the Smith acidity scale for binary oxides serves as a powerful descriptor for tuning and predicting the oxygen exchange kinetics on MIEC PCO surfaces. As a result, with infiltration with binary oxides, ranging from strongly basic (Li 2 O) to strongly acidic (SiO 2 ) onto the surface of porous PCO, it was possible to systematically vary the chemical surface exchange coefficient (k chem ) by 6 orders of magnitude! L i2 O increased k chem by nearly 1,000 times over that of pristine PCO, while SiO 2 decreased k chem by nearly the same factor. Strikingly, although the pre-exponential of k chem scales linearly with the acidity of the infiltrated binary oxide, there is nearly no change in the activation energy. With this insight, we attributed the origin of these dramatic changes in k chem values to the systematic increase and decrease in the surface electron density induced by infiltrated binary oxides. More interestingly, although both Cr 2 O 3 and SiO 2 were determined to be acidic by Smith, suggesting that this feature could likely be the primary reason that these compounds serve to poison the ORR on SOFC cathodes, the effect of poisoning could be subsequently tuned by adding multiple infiltrants and controlling their relative surface acidities. We also systematically examined the effect of serial infiltration of basic and acidic oxides. It turned out that serial infiltration of Li not only recovers approximately 20-fold degraded k chem of PCO by acidic Cr 2 O 3 but its k chem is enhanced even beyond that of the non-infiltrated PCO by more than three orders of magnitude. This was further verified with a screen-printing PCO symmetric cell in terms of the electrode performance (area-specific resistance, ASR) related to approach 3). These observations point to acidity as a key descriptor not only in tuning and predicting the ORR activity of SOFC cathodes that largely determines the overall performance of SOFC, but in mitigating and reactivating poisoned electrode performance. This work provides novel guidelines for making the electrode performance much more active and robust in SOFCs, which can further be applied to all applications requiring oxygen exchange reaction, such as electrolyzers, permeation membranes and gas sensors.

30 DIRECT ENERGY CONVERSION↗

Structural and Kinetic Characterization of Hyperthermophilic NADH-Dependent Persulfide Reductase from Archaeoglobus fulgidus

NADH-dependent persulfide reductase (Npsr) has been proposed to facilitate dissimilatory sulfur respiration by reducing persulfide or sulfane sulfur-containing substrates to H2S. The presence of this gene in the sulfate and thiosulfate-reducing Archaeoglobus fulgidus DSM 4304 and other hyperthermophilic Archaeoglobales appears anomalous, as A. fulgidus is unable to respire S0 and grow in the presence of elemental sulfur. To assess the role of Npsr in the sulfur metabolism of A. fulgidus DSM 4304, the Npsr from A. fulgidus was characterized. AfNpsr is specific for persulfide and polysulfide as substrates in the oxidative half-reaction, exhibiting k cat / K m on the order of 104 M-1 s-1, which is similar to the kinetic parameters observed for hyperthermophilic CoA persulfide reductases. In contrast to the bacterial Npsr, AfNpsr exhibits low disulfide reductase activity with DTNB; however, similar to the bacterial enzymes, it does not show detectable activity with CoA-disulfide, oxidized glutathione, or cystine. The 3.1 Å X-ray structure of AfNpsr reveals access to the tightly bound catalytic CoA, and the active site Cys 42 is restricted by a flexible loop (residues 60-66) that is not seen in the bacterial homologs from Shewanella loihica PV-4 and Bacillus anthracis. Unlike the bacterial enzymes, AfNpsr exhibits NADH oxidase activity and also shows no detectable activity with NADPH. Models suggest steric and electrostatic repulsions of the NADPH 2 ′ -phosphate account for the strong preference for NADH. The presence of Npsr in the nonsulfur-reducing A. fulgidus suggests that the enzyme may offer some protection against S0 or serve in another metabolic role that has yet to be identified.

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