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At least 1,297 records · Page 72

Assessing the Role of the Support in Acetic Acid Hydrodeoxygenation Selectivity on Pt/TiO2

To produce drop-in quality biofuels following the thermochemical conversion of biomass via catalytic fast pyrolysis (CFP), hydrodeoxygenation (HDO) reactions can be performed to remove excess oxygen and create a more stable bio-oil product. HDO reactions involve co-feeding the CFP vapor-phase product and H2 gas over bi-functional catalysts, such as noble-metal catalysts supported on reducible metal oxides (e.g., Pt/TiO2). Recent model-compound studies, focusing on important classes of species in the CFP vapor mixture, have sought to determine the role of the various Pt/TiO2 actives sites (i.e., Pt-metal, TiO2-support, Pt-TiO2-interfacial sites) in producing the observed desired deoxygenation and undesired decarboxylation/decarbonylation products. One important class of compounds in the CFP vapor-phase product is carboxylic acids (e.g., acetic acid). Prior experimental work on acetic acid HDO (AA-HDO) found that Pt/C and Pt/TiO2 catalysts favored the formation of undesired C-C and desired C-O bond-dissociation products; however, the fundamental surface chemistry driving this shift in selectivity has not been established. This presentation employs atomic-scale modeling to determine, through comparisons of adsorption and reaction energetics, how Pt-metal, Pt-TiO2-interface, and interfacial-vacancy sites catalyze the competing reaction pathways for AA-HDO. Our analysis indicates that hydroxyl vacancies at the Pt-TiO2 interface are critical for lowering barriers for C-O bond-cleavage steps, such that they become favorable/competitive with respect to C-C bond-dissociation steps.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗

Observations of the Minor Species Al and Fe in Mercury's Exosphere

We report here on the first observational evidence of Al and Fe in the exosphere of Mercury, based on measurements of resolved emission lines of these metals with Keck-1/HIRES. Al emission was observed on two separate runs, in 2008 and 2013, with tangent column densities of 3.1 +/- 1.0 and 4.0 +/-1.5 x 10(exp 7) Al atoms cm(exp - 2) at altitudes of 1185 and 1870 km (1.5 and 1.75 R(sub M). The Al radiative intensity was seen to increase where the slit crossed the planetary penumbral shadow, and then decrease monotonically with altitude. Fe emission has been observed once, in 2009, indicating an extended source. We also present observed 3- Sigma Ca(+) upper limits near Mercury's equatorial anti-solar limb, from which an abundance limit of 4.0 x 10(exp 6) cm(exp -2) at 1650 km altitude is derived for the Ca ion. A simple model for zenith column abundances of the neutral species yields 1.9 -5.2 x 10(exp 7) Al cm(exp -2) , and 8.2 x 10(exp 8) Fe cm(exp -2) . The observations appear to be consistent with production of these species by impact vaporization, with a large fraction of the Al ejecta in molecular form, and that for Fe in mixed atomic and molecular forms. The scale height of the Al gas is consistent with a kinetic temperature of 6100-8000 K. The apparent high temperature and low density of the Al gas would suggest that it may be produced by dissociation of molecules.

Mercury↗

SWIPE: Spectral Water Inversion Processor and Emulator

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will be discussing the progress made developing SWIPE: Spectral Water Inversion Processor and Emulator. SWIPE is a platform for advanced modeling of coastal and inland aquatic habitats. The goal is create a comprehensive and cohesive system to leverage recent advancements in computation and machine learning to develop a synthetic training ground for sensitivity studies and algorithm development. The four principal facets of SWIPE include: 1. Advanced two-layer coated sphere bio-optical modeling and GPU radiative transfer modeling, 2. Big Data involving massive synthetic spectral libraries of optical properties of various global aquatic particles, surface reflectance, and top-of-atmosphere reflectance, all at hyperspectral resolution leveraging high-end computing systems at NASA Ames Research Center, 3. Deep Learning for algorithm development for water quality inversion of concentrations of common biogeophysical variables as well as optics, full uncertainty characterization by water type, and forward emulation, and lastly, 4. Image Processing for application of developed retrieval algorithms for both hyperspectral and multispectral sensors with experimental corrections for global adjacency, noise, sunglint, and benthic reflectance. This presentation will demonstrate the Equivalent Algal Populations (EAP) two-layer coated sphere scattering model which has been used develop spectral libraries of hyperspectral inherent optical properties of roughly 80 species of phytoplankton, covering 15 different classes and nine taxonomic functional types. The EAP model was also used to derive spectral properties of 10 different non-algal particle functional types. Examples of how the SMART-G (Speed-up Monte-carlo Advanced Radiative Transfer using GPU) radiative transfer code is used to model optically complex aquatic signals will be presented and discussed in the context of creating a massive synthetic database which can leverage the full power of next generation machine learning techniques and high end computing for water quality inversion. We will discuss our active investigation in things like appropriate model architectures, dimensionality reduction techniques such as PCA and autoencoders, uncertainty quantification and abstaining, and which variables actually benefit most from hyperspectral information versus multispectral resolution. We are also curious about questions relating to cost/benefit analysis in terms of computation resources, neural network complexity, and data volumes. Answers to these questions will hopefully elaborate on cost efficiency for potential future sensor design considerations.

SWIPE↗

Multi‐Scale Model‐Informed Deep Learning for Plasma‐Nanoparticle Interaction

The Overarching Goal of this proposed research is to understand and quantitively determine the interactions between non-thermal plasma (hot electrons, reactive radicals, vibrationally excited species) and surface reactions on influencing the activity and selectivity of the desired reactions via developing multi-scale model informed deep learning algorithm. Investigating non-thermal plasma-surface interaction is feasible due to the low bulk temperature in the discharge region. To investigate the role of plasma-nanoparticle interaction on enhancing the reaction kinetics, we will focus on ammonia cracking to generate clean hydrogen over earth-abundant, non-critical metallic nanoparticles, which is of great significance for decarbonization. We hypothesize that (1) reactive radicals interacting with surface reaction species via Eley–Rideal mechanism will significantly lower the energetics of the potential rate-limiting step of nitrogen formation; (2) the surface will be charged heterogeneously under non-thermal plasma conditions and the charged site will lower the energetics of ammonia cracking through Langmuir– Hinshelwood mechanism; (3) vibrationally excited ammonia will further promote the initial N-H bond cleavage. To access the hypothesis, we will (1) reveal the surface charge effects on tunning the reaction energetics via interpretable, physics-informed deep learning accelerated density functional theory (DFT) calculations; (2) determine the reactive radicals interacting with surface reaction species on tuning the reaction energetics via DFT; (3) reveal the surface charge effects on tunning the reaction energetics via DFT and deep learning models, (4) quantify how vibrationally excited species, reactive radicals, and surface charging effects on enhancing the catalysis via developing DFT-based microkinetic modeling (MKM) and active learning. Deep and active learning of plasma-nanoparticle interactions effects on enhancing ammonia cracking to generate hydrogen represents a new paradigm for designing high performance plasma materials. The fundamental science of how plasma-nanoparticle interactions will change the plasma kinetics and will improve the energy efficiency for decarbonization and sustainability. The interpretable and physics-informed machine learning model will accelerate low temperature plasma chemistry and material discovery with physics rules and model interpretation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Biophysical analysis of the plant-specific GIPC sphingolipids reveals multiple modes of membrane regulation

The plant plasma membrane (PM) is an essential barrier between the cell and the external environment, controlling signal perception and transmission. It consists of an asymmetrical lipid bilayer made up of three different lipid classes: sphingolipids, sterols, and phospholipids. The glycosyl inositol phosphoryl ceramides (GIPCs), representing up to 40% of total sphingolipids, are assumed to be almost exclusively in the outer leaflet of the PM. However, their biological role and properties are poorly defined. In this study, we investigated the role of GIPCs in membrane organization. Because GIPCs are not commercially available, we developed a protocol to extract and isolate GIPC-enriched fractions from eudicots (cauliflower and tobacco) and monocots (leek and rice). Lipidomic analysis confirmed the presence of trihydroxylated long chain bases and 2-hydroxylated very long-chain fatty acids up to 26 carbon atoms. The glycan head groups of the GIPCs from monocots and dicots were analyzed by gas chromatograph-mass spectrometry, revealing different sugar moieties. Multiple biophysics tools, namely Langmuir monolayer, ζ-Potential, light scattering, neutron reflectivity, solid state 2H-NMR, and molecular modeling, were used to investigate the physical properties of the GIPCs, as well as their interaction with free and conjugated phytosterols. We showed that GIPCs increase the thickness and electronegativity of model membranes, interact differentially with the different phytosterols species, and regulate the gel-to-fluid phase transition during temperature variations. These results unveil the multiple roles played by GIPCs in the plant PM.

59 BASIC BIOLOGICAL SCIENCES↗

Elevated nocturnal respiratory rates in the mitochondria of CAM plants: current knowledge and unanswered questions

Abstract Crassulacean acid metabolism (CAM) is a metabolic adaptation that has evolved convergently in 38 plant families to aid survival in water-limited niches. Whilst primarily considered a photosynthetic adaptation, CAM also has substantial consequences for nocturnal respiratory metabolism. Here, we outline the history, current state and future of nocturnal respiration research in CAM plants, with a particular focus on the energetics of nocturnal respiratory oxygen consumption. Throughout the 20th century, research interest in nocturnal respiration occurred alongside initial discoveries of CAM, although the energetic and mechanistic implications of nocturnal oxygen consumption and links to the operation of the CAM cycle were not fully understood. Recent flux balance analysis (FBA) models have provided new insights into the role that mitochondria play in the CAM cycle. Several FBA models have predicted that CAM requires elevated nocturnal respiratory rates, compared to C3 species, to power vacuolar malic acid accumulation. We provide physiological data, from the genus Clusia, to corroborate these modelling predictions, thereby reinforcing the importance of elevated nocturnal respiratory rates for CAM. Finally, we outline five unanswered questions pertaining to nocturnal respiration which must be addressed if we are to fully understand and utilize CAM plants in a hotter, drier world.

59 BASIC BIOLOGICAL SCIENCES↗

Mechanistic Understanding of Methane Combustion over Ni/CeO 2 : A Combined Experimental and Theoretical Approach

Catalytic oxidation of methane (CH 4 ) over nonprecious Ni/CeO 2 catalysts has received a lot of attention due to the large natural gas reserves found in North America and the prohibitive cost of palladium-based catalysts, commonly used for CH 4 oxidation. However, the catalytic mechanism of CH 4 oxidation over Ni/CeO 2 still remains unclear. Moreover, the parameters affecting the reaction rates, the interaction between nickel and CeO 2 , and the reaction intermediates are still not well understood. In this study, kinetic model fitting, CH 4 temperature-programmed reduction-mass spectroscopy (CH 4 TPR-MS), in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and density functional theory (DFT) calculations were combined to elucidate the mechanism of complete oxidation of CH 4 over Ni/CeO 2 . CH 4 TPR-MS showed that the complete oxidation of CH 4 over Ni/CeO 2 requires 55–120 °C lower compared to bare CeO 2 or Ni/quartz sand; complete oxidation of CH 4 took place when the surface oxygen species were abundant, while partial oxidation products (CO, H 2 ) were formed when the oxygen species were depleted. In situ DRIFTS showed that CH 3 , CH 2 , CO, and CO 2 were formed after CH 4 activation over Ni/CeO 2 , while CH 3 O species were not observed. Combining those findings with kinetic model fitting, a redox Mars–van Krevelen (MvK) mechanism showed the best description of the experimental observations. The MvK mechanism involves the reaction of dissociated oxygen species with gas-phase CH 4 while water inhibits the reaction rate by adsorbing on the oxidized sites. Moreover, CH 4 activation leads to the reduction of the active sites and oxygen vacancy formation followed by reoxidation of the active sites by gas-phase O 2 . A CH 4 oxidation reaction pathway over Ni/CeO 2 is proposed by DFT calculations. In summary, the findings shown here suggest that CH 4 oxidation over Ni/CeO 2 follows a redox MvK mechanism and provides guidance for the rational design of non-precious-metal catalysts for CH 4 oxidation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Numerical investigation of equivalence ratio effects on Flex-Fuel mixing controlled combustion enabled by prechamber ignition

There is interest in adapting renewable and low-carbon intensity fuels to heavy-duty engines to help displace criteria and greenhouse gas emissions associated with diesel combustion. Low-carbon fuels have inherently low cetane numbers and thus pose a significant challenge when considering direct substitution in diesel combustion systems. Use of an actively fueled prechamber as an ignition source to initiate mixing-controlled combustion (PC-MCC) of low-cetane fuels is becoming an attractive combustion mode to alleviate the identified reactivity deficit. This work focuses on the utilization of an active prechamber to facilitate diesel-like combustion of bioethanol-gasoline fuel blends in a heavy-duty engine. Recent results in this emerging technology suggest that ignition quality is uniquely coupled to prechamber equivalence ratio. In this numerical study, the fundamental implications of prechamber equivalence ratio on the ignition performance of direct injected fuels ranging from E10 to E100 are investigated using CONVERGE. Parametric studies of the prechamber operating strategy were assessed at diesel-like conditions to characterize the performance trends relative to a diesel baseline at the same boundary conditions. Simulation results indicate that PC-MCC is flex-fuel capable and achieves diesel-like ignition qualities and combustion processes for all fuels considered under stoichiometric and rich prechamber conditions. To characterize the equivalence ratio trends observed, a novel inflow boundary modeling technique was utilized to prescribe turbulent jets in place of the prechamber where selective speciation of the jet composition was conducted to isolate the ignition contributions of radical and reacting species in lean, stoichiometric, and rich jets. The inflow boundary modeling suggests that excess fuel and combustion intermediates present in jets produced from stratified and fuel-rich prechamber operation promotes higher jet temperatures and as such are superior ignition sources. Relative to a lean prechamber jet, the peak temperature of a reacting jet from a rich prechamber was up to 600 K hotter at fixed distances from the orifice exit. Furthermore, radicals also demonstrated an influence on the ignition process, but the combustion mode was identified to be thermally dominant.

33 ADVANCED PROPULSION SYSTEMS↗

Determination of Chemical Kinetic Rate Constants of a Model for Carbothermal Processing of Lunar Regolith Simulant Using Methane

We have previously developed a chemical conversion model of the carbothermal processing of lunar regolith using methane to predict the rate of production of carbon monoxide. In this carbothermal process, gaseous methane is pyrolyzed as it flows over the hot surface of a molten zone of lunar regolith and is converted to carbon and hydrogen. Hydrogen is carried away by the exiting stream of gases and carbon is deposited on the melt surface. The deposited carbon mixes with the melt and reacts with the metal oxides in it to produce carbon monoxide that bubbles out of the melt. In our model, we assume that the flux of carbon deposited is equal to the product of the surface reaction rate constant gamma and the concentration of methane adjacent to the melt surface. Similarly, the rate of consumption of carbon per unit volume in the melt is equal to the product of the melt reaction rate constant k and the concentrations of carbon and metal oxide in the melt. In this paper, we describe our effort to determine gamma and k by comparison of the predictions from our model with test data obtained by ORBITEC (Orbital Technologies Corporation). The concentration of methane adjacent to the melt surface is a necessary input to the model. It is inferred from the test data by a mass balance of methane, adopting the usual assumptions of the continuously-stirred-tank-reactor model, whereby the average concentration of a given gaseous species equals its exit concentration. The reaction rates gamma and k have been determined by a non-linear least-squares fit to the test data for the production of carbon monoxide and the fraction of the incoming methane that is converted. The comparison of test data with our model predictions using the determined chemical kinetic rate constants provides a consistent interpretation of the process over the full range of temperatures, pressures, and methane flow rates used in the tests, thereby increasing our confidence to use the model for scale-up purposes.

Balasubramaniam, R↗

CN and C2H in IRC +10216

The effects of the production of the radicals CN and C2H from the dissociation of HCN and C2H2 by ambient UV photons in the outer envelope of IRC +10216 are investigated. The spatial distribution of the radicals and their observable millimeter emission-line characteristics are calculated from the inferred abundances of the progenitor species in the envelope of IRC +10216 using photochemical and radiative transfer models. These are compared with available observations to examine whether photoproduction is a possible explanation of the observed emission from these species. The results suggest that the variable abundances induced by photodestruction of their progenitors do affect the observed emission from the radicals.

Huggins, P. J.↗

Flow Characteristics of UHV Nitrogen Arcjet

Flow characteristics in the nozzle of a nitrogen arcjet have been simulated by a model. Electrons, ions, and neutral atoms and molecules are represented as separate species. Dissociation, ionization, and recombination are treated as separate reactions. Thermal non-equilibrium is represented by a two-temperature model. Energy input to plasma from the arc is modeled as a source determined by local current and electrical conductivity. Momentum and energy losses and recombinations at the nozzle wall are included as source/sink determined by fluxes to the wall. The results show essentially frozen gas-phase reactions and thermal nonequilibrium due to Joule heating of electrons and in the expansion part of the nozzle. Wall interactions have strong effects on the results, indicating that they play important roles in the flow due to very high surface area relative to the volume of the plasma. For example, plasma velocity decreases from 6000 m per s without wall interactions to 3000 m per s with modest amount of wall interactions. These results also show reasonable agreement with optical emission measurements, which confirms that the arcjet plasma is far from LTE. The spectra suggest nitrogen dissociation levels of 0.3% - 9%, depending on nitrogen flow rate and arc plasma current, which also determine the relative amounts of excited atomic and molecular nitrogen. Langmuir probe studies of the source show that electron and ion fluxes increase with increasing power, and that the ion energy distribution shifts to lower energies. Typical ion fluxes were on the order of 4E-9 A/cm**2 with a maximum ion kinetic energy of 3.5eV. The median electron energy was 1eV, with a maximum of less than 4eV.

Chang, C. H.↗

Reduced-order condensed-phase kinetic models for polyethylene, polypropylene and polystyrene thermochemical recycling

Thermochemical recycling of plastic waste (PW) into chemicals and energy vectors requires coupling particle and reactor-scale simulations to accurate condensed phase pyrolysis mechanisms for each constituent. This work proposes a methodology to derive reduced-order condensed-phase kinetic models from validated semi-detailed kinetic mechanisms. Two types of kinetic models are obtained for polyethylene (PE), polypropylene (PP) and polystyrene (PS): reduced semi-detailed models and multi-step fully lumped ones. These families offer different compromises between accuracy and computational cost. The former employ 50–100 gas + liquid species and describe both the radical degradation and the detailed carbon distribution of the products. Conversely, the latter involves 5–10 species per polymer tracking only the main petroleum cuts. The kinetic mechanisms are complemented by the definition of thermochemical properties of gas, liquid, and solid-phase species, accounting for phase-transitions through pseudo-chemical reactions. Model validations are performed by comparison with experimental data and the original semi-detailed mechanisms in terms of mass loss, heat fluxes and product distribution profiles. The resulting CHEMKIN-like condensed-phase models are attached as Supplementary Material and as a GitHub repository. Extending the proposed approach to other polymers and coupling it with existing subsets in the CRECK kinetic framework (e.g., biomass, PVC, PET) offers a powerful tool to model thermochemical recycling of PW and biomass/PW mixtures.

kinetics↗

The P( 4 S) + NH( 3 Σ – ) and N( 4 S) + PH( 3 Σ – )reactions as sources of interstellar phosphorus nitride

Phosphorus nitride (PN) is believed to be one of the major reservoirs of phosphorus in the interstellar medium (ISM). For this reason, understanding which reactions produce PN in space and predicting their rate coefficients is important for modelling the relative abundances of P-bearing species and clarifying the role of phosphorus in astrochemistry. Here, in this work, we explore the potential energy surfaces of the $\textrm{P}(^4\textrm{S}) + \textrm{NH}(^3\Sigma^-)$ and $\textrm{N}(^4\textrm{S}) + \textrm{PH}(^3\Sigma^-)$ reactions and the formation of $\textrm{H}(^2\textrm{S}) + \textrm{PN}(^1\Sigma^+)$ through high accuracy ab initio calculations and the variable reaction coordinate transition state theory (VRC-TST). We found that both reactions proceed without an activation barrier and with similar rate coefficients that can be described by a modified Arrhenius equation ( $k(T)=\alpha\!\left( T/300 \right)^{\beta} \exp\!{(\!-\!\gamma/T)})$ with $\alpha=0.93\times 10^{-10}\rm cm^3\,s^{-1}$ , $\beta=-0.18$ and $\gamma=0.24\, \rm K$ for the $\textrm{P} + \textrm{NH} \longrightarrow \textrm{H} + \textrm{PN}$ reaction and $\alpha=0.88\times 10^{-10}\rm cm^3\,s^{-1}$ , $\beta=-0.18$ and $\gamma=1.01\, \rm K$ for the $\textrm{N} + \textrm{PH} \longrightarrow \textrm{H} + \textrm{PN}$ one. Both reactions are expected to be relevant for modelling PN abundances even in the cold environments of the ISM. Given the abundance of hydrogen in space, we have also predicted rate coefficients for the destruction of PN via H + PN collisions.

79 ASTRONOMY AND ASTROPHYSICS↗

A comparative study of machine learning models for predicting the state of reactive mixing

Mixing phenomena are important mechanisms controlling flow, species transport, and reaction processes in fluids and porous media. Accurate predictions of reactive mixing are critical for many Earth and environmental science problems such as contaminant fate and remediation, macroalgae growth, and plankton biomass evolution. Here, to investigate the evolution of mixing dynamics under different scenarios (e.g., anisotropy, fluctuating velocity fields), a finite-element-based numerical model was built to solve the fast, irreversible bimolecular reaction-diffusion equations to simulate a range of reactive-mixing scenarios. A total of 2,315 simulations were performed using different sets of model input parameters comprising various spatial scales of vortex structures in the velocity field, time-scales associated with velocity oscillations, the perturbation parameter for the vortex-based velocity, anisotropic dispersion contrast (i.e., ratio of longitudinal-to-transverse dispersion), and molecular diffusion. The outputs comprised concentration profiles of reactants and products. The inputs to and outputs from these simulations were concatenated into feature and label matrices, respectively, to train 20 different machine learning (ML) models intended to emulate system behavior. These 20 ML emulators, based on linear methods, Bayesian methods, ensemble learning methods, and multilayer perceptrons (MLPs), were trained to classify the state of mixing and predict three quantities of interest (QoIs) characterizing species production, decay (i.e., average concentration, square of average concentration), and degree of mixing (i.e., variances of species concentration). Unsurprisingly, linear classifiers and regressors failed to reproduce the QoIs; however, ensemble methods (classifiers and regressors) and the MLP model accurately classified the state of reactive mixing and the QoIs. Among ensemble methods, random forest and decision-tree-based AdaBoost faithfully predicted the QoIs. At run time, trained ML emulators produced results times faster than the finite-element simulations. Due to their low computational expense and high accuracy, ensemble and MLP models are excellent emulators for these numerical simulations and great utilities in uncertainty quantification exercises, which can require 1,000s of forward model runs.

97 MATHEMATICS AND COMPUTING↗

Mass spectrometry imaging of natural carbonyl products directly from agar-based microbial interactions using 4-APEBA derivatization

Aliphatic carboxylic acids, aldehydes, and ketones play diverse roles in microbial adaptation to their microenvironment, from excretion as toxins to adaptive metabolites for membrane fluidity. However, the spatial distribution of these molecules throughout biofilms and how microbes in these environments exchange these molecules remain elusive for many of these bioactive species due to inefficient molecular imaging strategies. Herein, we apply on-tissue chemical derivatization (OTCD) using 4-(2-((4-bromophenethyl)dimethylammonio)ethoxy)benzenaminium dibromide (4-APEBA) on a co-culture of a soil bacterium (Bacillus subtilis NCIB 3610) and fungus (Fusarium sp. DS 682) grown on agar as our model system. Using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), we spatially resolved more than 300 different metabolites containing carbonyl groups within this model system. Various spatial patterns are observable in these species, which indicate possible extracellular or intercellular processes of the metabolites and their up- or downregulation during microbial interaction. The unique chemistry of our approach allowed us to bring additional confidence in accurate carbonyl identification, especially when multiple isomeric candidates were possible, and this provided the ability to generate hypotheses about the potential role of some aliphatic carbonyls in this B. subtilis/Fusarium sp. interaction. The results shown here demonstrate the utility of 4-ABEBA-based OTCD MALDI-MSI in probing interkingdom interactions directly from microbial co-cultures, and these methods will enable future microbial interaction studies with expanded metabolic coverage.

4-APEBA↗

Dynamics and Structure of Dusty Reacting Flows: Inert Particles in Strained, Laminar, Premixed Flames

A detailed numerical study was conducted on the dynamics and thermal response of inert, spherical particles in strained, laminar, premixed hydrogen/air flames. The modeling included the solution of the steady conservation equations for both the gas and particle phases along and around the stagnation streamline of an opposed-jet configuration, and the use of detailed descriptions of chemical kinetics and molecular transport, For the gas phase, the equations of mass, momentum, energy, and species are considered, while for the particle phase, the model is based on conservation equations of the particle momentum balance in the axial and radial direction, the particle number density, and the particle thermal energy equation. The particle momentum equation includes the forces as induced by drag, thermophoresis, and gravity. The particle thermal energy equation includes the convective/conductive heat exchange between the two phases, as well as radiation emission and absorption by the particle. A one-point continuation method is also included in the code that allows for the description of turning points, typical of ignition and extinction behavior. As expected, results showed that the particle velocity can be substantially different than the gas phase velocity, especially in the presence of large temperature gradients and large strain rates. Large particles were also found to cross the gas stagnation plane, stagnate, and eventually reverse as a result of the opposing gas phase velocity. It was also shown that the particle number density varies substantially throughout the flowfield, as a result of the straining of the flow and the thermal expansion. Finally, for increased values of the particle number density, substantial flame cooling to extinction states and modification of the gas phase fluid mechanics were observed. As also expected, the effect of gravity was shown to be important for low convective velocities and heavy particles. Under such conditions, simulations indicate that the magnitude and direction of the gravitational force can substantially affect the profiles of the particle velocity, number density, mass flux, and temperature.

Egolfopoulos, Fokion N.↗

Dynamics and Structure of Dusty Reacting Flows: Inert Particles in Strained, Laminar, Premixed Flames

A detailed numerical study was conducted on the dynamics and thermal response of inert spherical particles in strained, laminar, premixed hydrogen/air flames. The modeling included the solution of the steady conservation equations for both the gas and particle phases along and around the stagnation streamline of an opposed-jet configuration, and the use of detailed descriptions of chemical kinetics and molecular transport. For the gas phase, the equations of mass, momentum, energy, and species are considered, while for the particle phase, the model is based on conservation equations of the particle momentum balance in the axial and radial direction, the particle number density, and the particle thermal energy equation. The particle momentum equation includes the forces as induced by drag, thermophoresis, and gravity. The particle thermal energy equation includes the convective/conductive heat exchange between the two phases, as well as radiation emission and absorption by the particle. A one-point continuation method is also included in the code that allows for the description of turning points, typical of ignition and extinction behavior. As expected, results showed that the particle velocity can be substantially different than the gas phase velocity, especially in the presence of large temperature gradients and large strain rates. Large particles were also found to cross the gas stagnation plane, stagnate, and eventually reverse as a result of the opposing gas phase velocity. It was also shown that the particle number density varies substantially throughout the flowfield, as a result of the straining of the flow and the thermal expansion. Finally, for increased values of the particle number density, substantial flame cooling to extinction states and modification of the gas phase fluid mechanics were observed. As also expected, the effect of gravity was shown to be important for low convective velocities and heavy particles. Under such conditions, simulations indicate that the magnitude and direction of the gravitational force can substantially affect the profiles of the particle velocity, number density, mass flux, and temperature.

Egolfopoulos, Fokion N.↗

Dependence of Aerosol Light Absorption and Single-Scattering Albedo On Ambient Relative Humidity for Sulfate Aerosols with Black Carbon Cores

Atmospheric aerosols frequently contain hygroscopic sulfate species and black carbon (soot) inclusions. In this paper we report results of a modeling study to determine the change in aerosol absorption due to increases in ambient relative humidity (RH), for three common sulfate species, assuming that the soot mass fraction is present as a single concentric core within each particle. Because of the lack of detailed knowledge about various input parameters to models describing internally mixed aerosol particle optics, we focus on results that were aimed at determining the maximum effect that particle humidification may have on aerosol light absorption. In the wavelength range from 450 to 750 nm, maximum absorption humidification factors (ratio of wet to 'dry=30% RH' absorption) for single aerosol particles are found to be as large as 1.75 when the RH changes from 30 to 99.5%. Upon lesser humidification from 30 to 80% RH, absorption humidification for single particles is only as much as 1.2, even for the most favorable combination of initial ('dry') soot mass fraction and particle size. Integrated over monomodal lognormal particle size distributions, maximum absorption humidification factors range between 1.07 and 1.15 for humidification from 30 to 80% and between 1.1 and 1.35 for humidification from 30 to 95% RH for all species considered. The largest humidification factors at a wavelength of 450 nm are obtained for 'dry' particle size distributions that peak at a radius of 0.05 microns, while the absorption humidification factors at 700 nm are largest for 'dry' size distributions that are dominated by particles in the radius range of 0.06 to 0.08 microns. Single-scattering albedo estimates at ambient conditions are often based on absorption measurements at low RH (approx. 30%) and the assumption that aerosol absorption does not change upon humidification (i.e., absorption humidification equal to unity). Our modeling study suggests that this assumption alone can introduce absolute errors in estimates of the midvisible single-scattering albedo of up to 0.05 for realistic dry particle size distributions. Our study also indicates that this error increases with increasing wavelength. The potential errors in aerosol single-scattering albedo derived here are comparable in magnitude and in addition to uncertainties in single-scattering albedo estimates that are based on measurements of aerosol light absorption and scattering.

Redemann, Jens↗