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At least 901 records · Page 50

Anomalous Role of Carbon in Pd‐Catalyzed Selective Hydrogenation

Carbonaceous species, including subsurface carbidic carbon and surface carbon, play crucial roles in heterogeneous catalysis. Many reports suggested the importance of subsurface carbon in the selective hydrogenation of alkynes over Pd‐based catalysts. However, the role of surface carbon has been largely overlooked. Here, we demonstrate that subsurface carbon in Pd is not responsible for the selectivity in acetylene hydrogenation. In contrast, the structure of surface carbonaceous species plays a decisive role in hydrogenation selectivity. Electron microscopy and spectroscopy evidence, along with theoretical modelling, reveal that partial graphitization of surface carbonaceous species results in unique spatial confinement of surface reaction intermediates, thus altering the reaction energy landscape in favour of ethylene desorption as opposed to over‐hydrogenation. This mechanism for selectivity control is analogous to enzyme catalysis, where the active centers selectively attract reactants and release products. Similar mechanism may be present in CO/CO 2 hydrogenation and alkane dehydrogenation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Climate, food and humans predict communities of mammals in the United States

Abstract Aim The assembly of species into communities and ecoregions is the result of interacting factors that affect plant and animal distribution and abundance at biogeographic scales. Here, we empirically derive ecoregions for mammals to test whether human disturbance has become more important than climate and habitat resources in structuring communities. Location Conterminous United States. Time Period 2010–2021. Major Taxa Studied Twenty‐five species of mammals. Methods We analysed data from 25 mammal species recorded by camera traps at 6645 locations across the conterminous United States in a joint modelling framework to estimate relative abundance of each species. We then used a clustering analysis to describe 8 broad and 16 narrow mammal communities. Results Climate was the most important predictor of mammal abundance overall, while human population density and agriculture were less important, with mixed effects across species. Seed production by forests also predicted mammal abundance, especially hard‐mast tree species. The mammal community maps are similar to those of plants, with an east–west split driven by different dominant species of deer and squirrels. Communities vary along gradients of temperature in the east and precipitation in the west. Most fine‐scale mammal community boundaries aligned with established plant ecoregions and were distinguished by the presence of regional specialists or shifts in relative abundance of widespread species. Maps of potential ecosystem services provided by these communities suggest high herbivory in the Rocky Mountains and eastern forests, high invertebrate predation in the subtropical south and greater predation pressure on large vertebrates in the west. Main Conclusions Our results highlight the importance of climate to modern mammals and suggest that climate change will have strong impacts on these communities. Our new empirical approach to recognizing ecoregions has potential to be applied to expanded communities of mammals or other taxa.

Kays, Roland↗

Experimental investigation on the origin of the genetic code.

A simple model of interacting complex systems of species is tested to assess the binding behavior of monomeric nucleic acid and protein components during evolution. Nine representative amino acids are immobilized by the formation of an amide linkage on a prepared chromatographic support. Selective binding of ribonucleoside 5-phosphates in these amino acids is achieved under standardized conditions, and a site-binding model is derived to characterize the binding. It is shown that the binding behavior of the reactants during nucleic acid-protein interactions depends on the nature of the base and the amino acid. The results of the study are assessed as useful for the interpretation of more complex nucleic acid-protein systems and of their role in the evolution of the cell.

Saxinger, C.↗

ab initio Sub-Mechanism Development for Cyclopentene Oxidation

To accurately predict low-temperature oxidation behavior, chemical kinetics mechanisms must contain complete reaction networks that include detailed consumption reactions of intermediates produced directly from hydroperoxyalkyl radicals, Q̇OOH, which undergo competing unimolecular reactions and bimolecular reactions with O2. Rates of chain-branching are governed by the flux between the two competing pathways, and inherently depend on temperature, pressure, and oxygen concentration. Neglect of consumption pathways for major oxidation intermediates leads to mechanism truncation error that is ameliorated by expanding the level of detail included in sub-mechanisms and employing ab initio methods for computing rates of elementary reactions and thermochemical properties of species involved. In the present work, an ab initio-derived sub-mechanism is developed using AutoMech to model the chemical kinetics of cyclopentene, a major product of cyclopentane oxidation. The ab initio sub-mechanism builds on a detailed mechanism developed using Reaction Mechanism Generator (RMG) for the specific purpose of determining the extent to which replacing cyclopentene-specific reactions and species with quantum chemical computations reduces model inaccuracies resulting from mechanism truncation error. In an effort to minimize interference from other reactions present during the formation of cyclopentene from cyclopentyl + O2, providing a narrower experimental scope, the model is compared against speciation measurements from jet-stirred reactor (JSR) experiments on cyclopentene oxidation. The experiments utilize vacuum ultraviolet-absorption spectroscopy and mass spectrometry for isomer-resolved speciation of intermediates at 835 Torr from 700 – 950 K. [O2]-dependent experiments were also conducted from 0.057 – 2.01 · 1018 molecules cm–3 at 825 K to examine the influence of oxygen on species profiles. Model predictions using the ab initio-revised mechanism yielded significant improvements in species profiles for both the temperature- and [O2]-dependent measurements, owing in part to increased rates of HOȮ and H2O2 production, which underscores the influence of theoretical calculations of reaction rates involving species produced from Ṙ + O2 such as cyclopentene.

AutoMech↗

Wave-modified mean exothermic heating in the mesopause region

We employ a model of wave-driven OH nightglow fluctuations to calculate the effects of gravity waves on the chemical exothermic heating due to reactions involving odd hydrogen and odd oxygen species in the mesopause region. Using a model based on time means and deviations from those means, it is demonstrated that gravity waves contribute to the time-average exothermic heating. The effect can be significant because the fractional fluctuations in minor species density can be substantially greater than the fractional fluctuation of the major gas density. Our calculations reveal that the waves mitigate the exothermic heating, demonstrating their potential importance in the heat budget of the mesopause region.

Hickey, Michael P.↗

Seed classification with random forest models

Premise: To improve forest conservation monitoring, we developed a protocol to automatically count and identify the seeds of plant species with minimal resource requirements, making the process more efficient and less dependent on human operators. Methods and Results: Seeds from six North American conifer tree species were separated from leaf litter and imaged on a flatbed scanner. In the most successful species-classification approach, an ImageJ macro automatically extracted measurements for random forest classification in the software R. The method allows for good classification accuracy, and the same process can be used to train the model on other species. Conclusions: This protocol is an adaptable tool for efficient and consistent identification of seed species or potentially other objects. Automated seed classification is efficient and inexpensive, making it a practical solution that enhances the feasibility of large-scale monitoring projects in conservation biology.

59 BASIC BIOLOGICAL SCIENCES↗

Developing mass spectrometric techniques for boundary layer measurement in hypersonic high enthalpy test facilities

Thermodynamic flow properties of gases in the boundary layer or the flowfield have been mainly deduced from pressures and temperatures measured on a model. However, further progress with respect to an understanding of these properties requires a more complete characterization of the layer including determination of the gas composition and chemistry. Most attempts to measure boundary layer chemistry involve the employment of a mass spectrometer and an associated gas sampling system. The three major limiting factors which must be addressed for species measurement in aerothermodynamic investigations on models at reentry stream velocities, are gas sampling effects, instrument limitations, and problems with data acquisition. The present investigation is concerned with a concentrated effort to quantitatively identify and correct for instrument and sampling system effects, and to develop a miniaturized high performance mass spectrometer for on-model real-time analysis of the boundary layer and its associated atmosphere.

Wood, G. M., Jr.↗

Single Droplet Combustion of Decane in Microgravity: Experiments and Numerical Modeling

This paper presents experimental data on single droplet combustion of decane in microgravity and compares the results to a numerical model. The primary independent experiment variables are the ambient pressure and oxygen mole fraction, pressure, droplet size (over a relatively small range) and ignition energy. The droplet history (D(sup 2) history) is non-linear with the burning rate constant increasing throughout the test. The average burning rate constant, consistent with classical theory, increased with increasing ambient oxygen mole fraction and was nearly independent of pressure, initial droplet size and ignition energy. The flame typically increased in size initially, and then decreased in size, in response to the shrinking droplet. The flame standoff increased linearly for the majority of the droplet lifetime. The flame surrounding the droplet extinguished at a finite droplet size at lower ambient pressures and an oxygen mole fraction of 0.15. The extinction droplet size increased with decreasing pressure. The model is transient and assumes spherical symmetry, constant thermo-physical properties (specific heat, thermal conductivity and species Lewis number) and single step chemistry. The model includes gas-phase radiative loss and a spherically symmetric, transient liquid phase. The model accurately predicts the droplet and flame histories of the experiments. Good agreement requires that the ignition in the experiment be reasonably approximated in the model and that the model accurately predict the pre-ignition vaporization of the droplet. The model does not accurately predict the dependence of extinction droplet diameter on pressure, a result of the simplified chemistry in the model. The transient flame behavior suggests the potential importance of fuel vapor accumulation. The model results, however, show that the fractional mass consumption rate of fuel in the flame relative to fuel vaporized is close to 1.0 for all but the lowest ambient oxygen mole fractions.

Dietrich, D. L.↗

A Model of Silicate Grain Nucleation and Growth in Circumstellar Outflows

Based on its abundance, high bond energy, and recent measurements of its vapor pressure SiO is a natural candidate for dust nucleation in circumstellar outflows around asymptotic giant branch stars. In this paper, we describe a model of the nucleation and growth of silicate dust in such outflows. The sensitivity of the model to varying choices of poorly constrained chemical parameters is explored, and the merits of using scaled rather than classical nucleation theory are briefly considered, An elaboration of the model that includes magnesium and iron as growth species is then presented and discussed. The composition of the bulk of the grains derived from the model is consistent with olivines and pyroxenes, but somewhat metal-rich grains and very small, nearly pure SiO grains are also produced,

Paquette, John A.↗

Photochemical processes in the inner coma

Models for the inner-coma chemistry of comets are reviewed. The physics relevant to the coma's chemistry is summarized, and the interaction of solar radiation with the coma is described, along with photolytic and chemical processes. The formation and destruction of several observed species are traced through a chemical reaction network, and model results are compared with observations. The species considered include CN, C2, C3, NH2, CH, CO, CO(+), OH, H2O, HCO, C2H4, and C2H3. The models most consistent with observations are shown to indicate that only trace amounts (2% in all) of molecules bearing CN, C2, C3, and NH2 can be present in the nucleus of a comet.

Huebner, W. F.↗

Allometric, Growth, and Biomass Estimation Models for Acacia dealbata Link.: A Case Study in Serra da Estrela Natural Park (Portugal)

Allometric, growth, and biomass estimation models for the quantification of missing parameters in trees are widely used to estimate the productivity of a stand. However, regarding species with lower economic interest, or exotic invasive species, the creation of these tools did not occur in the same way as for other species, lacking the development of relationships to allow a deeper study of these species. Thus, data were collected in a settlement of Acacia dealbata Link. in Portugal, in an area known for the current infestation of this species. After a bibliographic review, some of the identified models were tested to select those who best fit the characteristics of this stand, which were used to develop relationships that, based on the data collected, would be able to estimate parameters, such as height, volume, or mass. It was found that the models established, at least for the initial 20 years of the life of the trees, followed close to a linear model. However, the model still presents some weaknesses. For being considered an invasive species in Portugal, A. dealbata is frequently controlled, and for this reason it is very difficult to find trees older than 20 years.

Nunes, Leonel J. R. (ORCID:0000000154048163)↗

Production and Catalytic Upgrading of 2,3-Butanediol Fermentation Broth into Sustainable Aviation Fuel Blendstock and Fuel Properties Measurement

With the increasing demand for sustainable supplies of aviation fuel and need to address climate change, new conversion technologies are needed to efficiently process biomass, produce high quality jet fuel blendstock, and meet carbon emission targets. This study demonstrates the synthesis, conditioning, and catalytic upgrading of 2,3-butanediol (BDO) fermentation broth into a jet fuel blendstock candidate. A high-titer 2,3-BDO fermentation broth (i.e., ~90 g/L) was produced at a 100-L scale and pretreated via nanofiltration to decrease the impurities level in the broth from 4.6 to 0.6 wt%. A novel process for catalytic upgrading of aqueous 2,3-BDO into a jet fuel blendstock candidate was developed, and each step was efficiently demonstrated. The catalytic steps include 1) 2,3-BDO dehydration into methyl ethyl ketone (MEK) over AlPO4, 2) MEK conversion into olefins over Zn1Zr10Ox, 3) oligomerization of olefins over a zeolite beta, and 4) hydrogenation over platinum/carbon. Both the model feed and real 2,3-BDO fermentation broth were tested for upgrading 2,3-BDO to MEK. With the real feed, a continuous loss of conversion (i.e., >50% loss over ~140 h time-on-stream [TOS]) was partly attributed to reversible deactivation from coking species. However, the conversion remained stable with the model feed, which demonstrates the efficiency of the first step for converting aqueous 2,3-BDO (10 wt% in water). For upgrading MEK to olefins, high selectivity to olefins (i.e., 82.5%) was obtained at high conversion levels (i.e., 93-98%) with stable conditions being achieved for > 70-hours TOS. Oligomerization of light olefins, which was demonstrated for > 270 h TOS, mainly led to the formation of dimers (C8-10) and trimers (C13-14). The oligomerized product was hydrogenated and distilled to recover the jet fraction (35 mass% or 40.9% carbon based yield), which consists mostly of desired isoalkanes (31.7 wt%), n-alkanes (24.5 wt%), and cycloalkanes (29.6 wt%). While some improvement is still needed to meet ASTM D7566 specifications for viscosity and final boiling point temperature, freezing point, density, aromatics content, and sulfur content of the jet blendstock candidate were within acceptable ranges, thus highlighting the potential of this process for production of jet fuel blendstock.

ADVANCED PROPULSION SYSTEMS,BIOMASS FUELS↗

Modeling of the SiC chemical vapor deposition process and comparison with experimental results

A model of the NASA Lewis SiC CVD process is described, and the results presented. A key feature of the model is the direct coupling of gas-phase chemical kinetics with diffusion. A deposition chemistry model using reactive sticking coefficients for each gas-phase species provides the diffusion boundary conditions. SiC deposition rates predicted by the model agree reasonably well with experimentally observed rates.

Annen, K. D.↗

Simulation Studies of the Effect of Forest Spatial Structure on InSAR Signature

The height of scattering phase retrieved from InSAR data is considered being correlated with the tree height and the spatial structure of the forest stand. Though some researchers have used simple backscattering models to estimate tree height from the height of scattering center, the effect of forest spatial structure on InSAR data is not well understood yet. A three-dimensional coherent radar backscattering model for forest canopies based on realistic three-dimensional scene was used to investigate the effect in this paper. The realistic spatial structure of forest canopies was established either by field measurements (stem map) or through use of forest growth model. Field measurements or a forest growth model parameterized using local environmental parameters provides information of forest species composition and tree sizes in certain growth phases. A fractal tree model (L-system) was used to simulate individual 3- D tree structure of different ages or heights. Trees were positioned in a stand in certain patterns resulting in a 3-D medium of discrete scatterers. The radar coherent backscatter model took the 3-D forest scene as input and simulates the coherent radar backscattering signature. Interferometric SAR images of 3D scenes were simulated and heights of scattering phase centers were estimated from the simulated InSAR data. The effects of tree height, crown cover, crown depth, and the spatial distribution patterns of trees on the scattering phase center were analyzed. The results will be presented in the paper.

Sun, Guoqing↗

AMORE-Isoprene v1.0: a new reduced mechanism for gas-phase isoprene oxidation

Abstract. Gas-phase oxidation of isoprene by ozone (O3) and the hydroxyl (OH) and nitrate (NO3) radicals significantly impacts tropospheric oxidant levels and secondary organic aerosol formation. The most comprehensive and up-to-date chemical mechanism for isoprene oxidation consists of several hundred species and over 800 reactions. Therefore, the computational expense of including the entire mechanism in large-scale atmospheric chemical transport models is usually prohibitive, and most models employ reduced isoprene mechanisms ranging in size from ∼ 10 to ∼ 200 species. We have developed a new reduced isoprene oxidation mechanism using a directed-graph path-based automated model reduction approach, with minimal manual adjustment of the output mechanism. The approach takes as inputs a full isoprene oxidation mechanism, the environmental parameter space, and a list of priority species which are protected from elimination during the reduction process. Our reduced mechanism, AMORE-Isoprene (where AMORE stands for Automated Model Reduction), consists of 12 species which are unique to the isoprene mechanism as well as 22 reactions. We demonstrate its performance in a box model in comparison with experimental data from the literature and other current isoprene oxidation mechanisms. AMORE-Isoprene's performance with respect to predicting the time evolution of isoprene oxidation products, including isoprene epoxydiols (IEPOX) and formaldehyde, is favorable compared with other similarly sized mechanisms. When AMORE-Isoprene is included in the Community Regional Atmospheric Chemistry Multiphase Mechanism 1.0 (CRACMM1AMORE) in the Community Multiscale Air Quality Model (CMAQ, v5.3.3), O3 and formaldehyde agreement with Environmental Protection Agency (EPA) Air Quality System observations is improved. O3 bias is reduced by 3.4 ppb under daytime conditions for O3 concentrations over 50 ppb. Formaldehyde bias is reduced by 0.26 ppb on average for all formaldehyde measurements compared with the base CRACMM1. There was no significant change in computation time between CRACMM1AMORE and the base CRACMM. AMORE-Isoprene shows a 35 % improvement in agreement between simulated IEPOX concentrations and chamber data over the base CRACMM1 mechanism when compared in the Framework for 0-D Atmospheric Modeling (F0AM) box model framework. This work demonstrates a new highly reduced isoprene mechanism and shows the potential value of automated model reduction for complex reaction systems.

58 GEOSCIENCES↗

AMORE-Isoprene v1.0: A New Reduced Mechanism for Gas-Phase Isoprene Oxidation

Gas-phase oxidation of isoprene by ozone (O 3 ) and the hydroxyl (OH) and nitrate (NO 3 ) radicals significantly impacts tropospheric oxidant levels and secondary organic aerosol formation. The most comprehensive and up-to-date chemical mechanism for isoprene oxidation consists of several hundred species and over 800 reactions. Therefore, the computational expense of including the entire mechanism in large-scale atmospheric chemical transport models is usually prohibitive, and most models employ reduced isoprene mechanisms ranging in size from ∼ 10 to ∼ 200 species. We have developed a new reduced isoprene oxidation mechanism using a directed-graph path-based automated model reduction approach, with minimal manual adjustment of the output mechanism. The approach takes as inputs a full isoprene oxidation mechanism, the environmental parameter space, and a list of priority species which are protected from elimination during the reduction process. Our reduced mechanism, AMORE-Isoprene (where AMORE stands for Automated Model Reduction), consists of 12 species which are unique to the isoprene mechanism as well as 22 reactions. We demonstrate its performance in a box model in comparison with experimental data from the literature and other current isoprene oxidation mechanisms. AMORE-Isoprene's performance with respect to predicting the time evolution of isoprene oxidation products, including isoprene epoxydiols (IEPOX) and formaldehyde, is favorable compared with other similarly sized mechanisms. When AMORE-Isoprene is included in the Community Regional Atmospheric Chemistry Multiphase Mechanism 1.0 (CRACMM1AMORE) in the Community Multiscale Air Quality Model (CMAQ, v5.3.3), O 3 and formaldehyde agreement with Environmental Protection Agency (EPA) Air Quality System observations is improved. O 3 bias is reduced by 3.4 ppb under daytime conditions for O 3 concentrations over 50 ppb. Formaldehyde bias is reduced by 0.26 ppb on average for all formaldehyde measurements compared with the base CRACMM1. There was no significant change in computation time between CRACMM1AMORE and the base CRACMM. AMORE-Isoprene shows a 35 % improvement in agreement between simulated IEPOX concentrations and chamber data over the base CRACMM1 mechanism when compared in the Framework for 0-D Atmospheric Modeling (F0AM) box model framework. This work demonstrates a new highly reduced isoprene mechanism and shows the potential value of automated model reduction for complex reaction systems.

Automated Model Reduction↗

Deep learning-based model for progress variable dissipation rate in turbulent premixed flames

A deep neural network (DNN) based large eddy simulation (LES) model for progress variable dissipation rate in turbulent premixed flames is presented. The DNN model is trained using filtered data from direct numerical simulations (DNS) of statistically planar turbulent premixed flames with n-heptane as fuel. Training data was comprised of flames with varying turbulence levels leading to a range of Karlovitz numbers. Through a-priori tests the DNN model is shown to predict the subfilter contribution to progress variable dissipation rate accurately over a range of filter widths and for all Karlovitz numbers examined in this study. Superior performance of the DNN model relative to an established physics-based model is also demonstrated. Additionally, transferability of the DNN model is highlighted by a-priori evaluation of the model using filtered DNS data from multiple cases with different Karlovitz numbers and fuel species than those that were used for training the model.

33 ADVANCED PROPULSION SYSTEMS↗