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At least 1,711 records · Page 95

Emissions Relationships Among Western Forest Fire Plumes: II. Plume Typing for Sources of Ozone and Aerosol Absorption

Previous studies of emission factors from biomass burning are prone to largeerrors since they ignore the interplay of mixing and varying pre-fire backgroundCO2 levels. Such complications severely affected our studies of 446 forest fireplume samples measured in the Western US by the science teams of NASAs SEAC4RS and ARCTAS airborne missions. Consequently we propose a MixedEffects Regression Emission Technique (MERET) to check techniques like theNormalized Emission Ratio Method (NERM), where use of sequentialobservations cannot disentangle emissions and mixing. We also evaluate asimpler consensus technique. All techniques relate emissions to fuel burnedusing Cburn Ctot added to the fire plume, where Ctot (CO2 + CO). Mixed-effectsregression can estimate pre-fire background values of Ctot (indexed byobservation j) simultaneously with emissions factors indexed by individualspecies i, xi (Cburn )i,j., MERET and consensus require more than twoemissions indicators. Our studies excluded samples where exogenous CO orCH4 might have been fed into a fire plume, mimicking emission.We sought to let the data on 13 gases and particulate properties suggest clustersof variables and plume types, using non-negative matrix factorization (NMF).While samples were mixtures, the NMF unmixing suggested purer burn types.Particulate properties (bscat, babs, SSA, AE) and gas-phase emissions were interrelated.Finally, we sought a simple categorization useful for modeling ozone productionin plumes. Two kinds of fires produced high ozone: those with large fuel nitrogenas evidenced by remnant CH3CN in the plumes, and also those from veryintense large burns. Fire types with optimal ratios of delta-NOydelta-HCHO associate with the highest additional ozone per unit Cburn, Perhaps theseplumes exhibit limited NOx binding to reactive organics. Perhaps these plumesexhibit limited NOx binding to reactive organics.

ozone↗

Novel Parameterization of Ice Cloud Effective Diameter from Collocated CALIOP-IIR and CloudSat Retrievals

Satellite-based measurements of global ice cloud microphysical properties are sampled to develop a novel set of physical parameterizations, relating to cloud layer temperature and effective diameter D(e), that can be implemented for two separate applications: in numerical weather prediction models and lidar-based cloud radiative forcing studies. Ice cloud optical properties (i.e., spectral scattering and absorption) are estimated based on the effective size and habit mixture of the cloud particles. Historically, the ice cloud D(e) has been parameterized from aircraft in situ measurements. However, aircraft-based parameterizations are opportunistic in that they only represent specific types of clouds (e.g., convective anvil, tropopause-topped cirrus) in the regions in which they were sampled and, in some cases, are limited in fully resolving the entire vertical cloud layer. Breaking away from the aircraft-based parameterization paradigm, this study is the first of its kind to attempt a parameterization of D(e) as a function of temperature, ice water content (IWC), and lidar-derived extinction from satellite-based global oceanic measurements of ice clouds. Data from both active and passive remote sensing sensors from two of NASA’s A-Train satellites, CloudSat and CALIPSO, are collected to guide development of globally robust parameterizations of all ice cloud types and one exclusively for cirrus clouds.

Ice Cloud↗

Coal-derived conductive pavement for winter de-icing: prototype, modeling, and simulation

Existing pavement de-icing methods result in high installation and maintenance costs, traffic delays, excessive weariness and corrosion, and negative environmental and safety impacts. To overcome these challenges, this paper presents an innovative pathway to designing and constructing smart self-heating pavements using a low-cost coal-char bearing asphalt material. The conductive asphalt incorporates coal char, i.e., a key byproduct of the coal pyrolysis process, into the Stone Mastic Asphalt (SMA) mixture. This asphalt containing coal-derived solid carbon exhibits highly tailorable electrical conductivity, satisfactory mechanical and thermophysical properties, and superior cost-efficiency as compared to other conductive pavement materials. The de-icing performance was also demonstrated by laboratory experiments on a bench-scale prototype. Furthermore, an efficient thermal network model was developed and validated by experiments to investigate the transient thermal behavior and energy performance of the Ohmic heating pavement system. Furthermore, the whole-year energy simulation case studies were conducted on a bridge pavement with an annual energy use of 24.6–1444.8 kWh/m 2 , showcasing its potential in field applications across cool humid, cold humid, and subarctic/arctic climate zones.

42 ENGINEERING↗

Recommended Direct Simulation Monte Carlo Collision Model Parameters for Reacting Methane Flows

While hydrocarbon combustion and gas-surface interactions have been simulated for a variety of applications in continuum solvers, such processes have been rarely investigated in Direct Simulation Monte Carlo (DSMC). Thus Variable Hard/Soft Sphere (VHS/VSS)collision parameters are not available for most molecules of interest in the decomposition of methane, a significant pyrolysis gas product and potential atmospheric species for Titan re-entries. As these properties are essential for accurate modeling of gas transport and thermochemical effects, a method must be devised to compute them for use in DSMC. In this study, the methodology outlined in Stephani et al is utilized to compute the VHS/VSS parameters by fitting the Ω(1,1)and Ω(2,2) collision integrals [1]. These collision integrals are typically computed from intermolecular potentials and are used in CFD simulations to calculate transport properties such as viscosity, thermal conductivity, and diffusion. This approach ensures consistency between micro-scale collisions and macro-scale transport properties. To produce the necessary collision integrals needed for the fitting routine, we utilize the method described by Laricchiuta et al, where collision integrals are computed based on the constituent particles’ polarizability and effective electron number [2].Preliminary computations of pure-species Ω(1,1)and Ω(2,2)collision integrals produced from the coupled approach of Stephani et al and Laricchiuta et al for methane show good agreement with those computed via available ab-initio Potential Energy Surface Computations, as seen in Figure 1. Above 300K, no more than 12% deviation is observed between the two results over the temperature range of the fitted PES data [3].Current results of this study include full collision-specificVSS transport properties for a complex-species mixture involving major byproducts of pure methane decomposition. Targeted final results will include a comprehensive list of VSS parameters relevant toDSMC simulations of Titan atmospheric entry, based on the reduced kinetic model of Savajano et al [4].

M R Gosma↗

Technology Assessment for Producing Propellant From Lunar Water

Introduction: The presence of water ice in permanently shadowed regions (PSRs) on the lunar surface may enable a sustained human presence on the Moon with minimal need for consumables. One of the most valuable uses of lunar water is to produce rocket propellant. A sustained human presence on the Moon will re-quire frequent launches from the lunar surface, and each launch will require tons of propellant. However, many other volatiles are likely to be present in the areas where lunar water is stable1. Producing propellant from lunar water in-situ will require the separation and purification of water before it can be electrolyzed into oxygen and hydrogen gas. The Resource Exploration and Science of OUR Cosmic Environment (RESOURCE) project, funded by the Solar System Exploration Research Virtual Institute (SSERVI) program, includes a task to demonstrate the end-to-end process of water extraction, capture, purification and electrolysis to produce pure/dry oxygen gas sourced from an icy regolith mixture. Water Purification: The requirements for water purity are driven by the type of water electrolyzer used. For example, the water electrolyzer currently used on the International Space Station is based on proton ex-change membrane (PEM) technology. PEM-based electrolyzers require water to be ultrapure and deionized (>10 MegaOhm-cm) so that electrical conductivity is limited to the membranes themselves, where electrical current is used to convert H2O into H2 and O2.. A practical first step toward purifying water that is sourced from a lunar PSR is to use freeze distillation to separate water from other volatiles2. A sub-micronic filter can also be used to ensure that a minimal amount of dust is present in any lunar water that is captured. The combination of freeze distillation and sub-micronic filtration will result in relatively pure water but would require a deionization step if being fed into a PEM electrolyzer. Water Electrolysis: An alternative to PEM electrolysis is to use a Solid Oxide Electrolyzer (SOE). This technology operates at a much higher operating temperature (~800oC) and has a limited pressure range but does not require water to be ultrapure and deionized. Another advantage of SOE technology is that it produces pure dry oxygen gas without the need of an additional drying step. PEM electrolyzers produce humid oxygen gas and the humidity must be removed prior to liquefaction. Assessment: In order to compare PEM and SOE technologies side-by-side, they must be compared at a system level that includes water purification and gas drying steps. Engineers at the Johnson Space Center up-dated and utilized a detailed In-Situ Resource Utilization (ISRU) system model to compare and select the best option for the RESOURCE project which will conclude with a laboratory demonstration of the process of producing pure/dry oxygen from an icy regolith mixture in 2025.

A.J. Paz↗

Technology Assessment for Producing Propellant From Lunar Water

Introduction: The presence of water ice in permanently shadowed regions (PSRs) on the lunar surface may enable a sustained human presence on the Moon with minimal need for consumables. One of the most valuable uses of lunar water is to produce rocket propellant. A sustained human presence on the Moon will re-quire frequent launches from the lunar surface, and each launch will require tons of propellant. However, many other volatiles are likely to be present in the areas where lunar water is stable1. Producing propellant from lunar water in-situ will require the separation and purification of water before it can be electrolyzed into oxygen and hydrogen gas. The Resource Exploration and Science of OUR Cosmic Environment (RESOURCE) project, funded by the Solar System Exploration Research Virtual Institute (SSERVI) program, includes a task to demonstrate the end-to-end process of water extraction, capture, purification and electrolysis to produce pure/dry oxygen gas sourced from an icy regolith mixture. Water Purification: The requirements for water purity are driven by the type of water electrolyzer used. For example, the water electrolyzer currently used on the International Space Station is based on proton ex-change membrane (PEM) technology. PEM-based electrolyzers require water to be ultrapure and deionized (>10 MegaOhm-cm) so that electrical conductivity is limited to the membranes themselves, where electrical current is used to convert H2O into H2 and O2.. A practical first step toward purifying water that is sourced from a lunar PSR is to use freeze distillation to separate water from other volatiles2. A sub-micronic filter can also be used to ensure that a minimal amount of dust is present in any lunar water that is captured. The combination of freeze distillation and sub-micronic filtration will result in relatively pure water but would require a deionization step if being fed into a PEM electrolyzer. Water Electrolysis: An alternative to PEM electrolysis is to use a Solid Oxide Electrolyzer (SOE). This technology operates at a much higher operating temperature (~800oC) and has a limited pressure range but does not require water to be ultrapure and deionized. Another advantage of SOE technology is that it produces pure dry oxygen gas without the need of an additional drying step. PEM electrolyzers produce humid oxygen gas and the humidity must be removed prior to liquefaction. Assessment: In order to compare PEM and SOE technologies side-by-side, they must be compared at a system level that includes water purification and gas drying steps. Engineers at the Johnson Space Center up-dated and utilized a detailed In-Situ Resource Utilization (ISRU) system model to compare and select the best option for the RESOURCE project which will conclude with a laboratory demonstration of the process of producing pure/dry oxygen from an icy regolith mixture in 2025.

ISRU↗

Modeling Plutonium Decorporation in a Female Nuclear Worker Treated with Ca-DTPA after Inhalation Intake

The present work models plutonium (Pu) biokinetics in a female former nuclear worker. Her bioassay measurements are available at the US Transuranium and Uranium Registries. The worker was internally exposed to a plutonium-americium mixture via acute inhalation at a nuclear weapons facility. She was medically treated with injections of 1 g Ca-DTPA on days 0, 5, and 14 after the intake. Between days 0 and 20, fecal and urine samples were collected and analyzed for 239 Pu and 241 Am. Subsequently, she was followed up for bioassay monitoring over 14 y, with additional post-treatment urine samples collected and analyzed for 239 Pu. The uniqueness of this dataset is due to the availability of: (1) both early and long-term bioassay data from a female with plutonium intake; (2) data on chelation therapy for a female; and (3) fecal measurement results. Chelation therapy with Ca- and/or Zn-salts of DTPA is known to aid in reducing the internal radiation dose by enhancing the excretion of plutonium and americium from the body. Such enhancement affects plutonium biokinetics in the human body, posing a challenge to the internal dose assessment. The current radiation dose assessment practice is to exclude the data affected by Ca-DTPA from the analysis. The present analysis is the first to explicitly model the chelation-affected bioassay data in a female by using a newly developed chelation model. Thus, the bioassay data collected during and after the Ca-DTPA administrations were used for biokinetic modeling and dose assessment. The Markov Chain Monte Carlo method was used to investigate model parameter uncertainty, based on the bioassay data and assumed prior probability distributions. A χ 2 /nData (number of data points) ≈ 1 was observed in this study, which indicates self-consistency of the data with the model. Results of this study show that the worker’s 239 Pu intake was 12 Bq, with a committed effective dose to the whole-body of 1.2 mSv and a committed equivalent dose to the bone surfaces, liver, and lungs of 37.8, 9.1, and 0.8 mSv, respectively. This study also discusses the worker’s dose reduction due to chelation treatment.

61 RADIATION PROTECTION AND DOSIMETRY↗

Enceladus and Europa: How Does Hydrothermal Activity Begin at the Surface?

The question of how the surface hydrothermal activity (e.g., eruptive plumes and heat flow) is initiated can be addressed within the frame-work of our "Perrier Ocean" model. This model delivers the necessary heat and chemicals to support the heat flow and plumes observed by Cassini in Enceladus' South Polar Region. The model employs closed-loop circulation of water from a sub-surface ocean. The ocean is the main reservoir of heat and chemicals, including dissolved gases. As ocean water moves up toward the surface, pressure is re-duced and gases exsolve forming bubbles. This bub-bly mixture is less dense than the icy crust and the buoyant ocean-water mixture rises toward the surface. Near the surface, heat and chemicals, including some volatiles, are delivered to the chambers in which plumes form and also to shallow reservoirs that keep the surface ice "warm". (Plume operations, per se, are as described by Schmidt et al. and Postberg et al. and are adopted by us.) After transferring heat, the water cools, bubbles contract and dissolve, and the mixture is now relatively dense. It descends through cracks in the crust and returns to the ocean. Once the closed-loop circulation has started it is self-sustaining. Loss of water via the erupting plumes is relatively negligible compared to the amount needed to maintain the heat flow.We note that the activity described herein for the the "Perrier-Ocean" model could, a priori, apply to all small icy bodies that sheltered an interior ocean at some point in their history.

Enceladus↗

Initial Verification of GEOS-4 Aerosols Using CALIPSO and MODIS: Scene Classification

A-train sensors such as MODIS and MISR provide column aerosol properties, and in the process a means of estimating aerosol type (e.g. smoke vs. dust). Correct classification of aerosol type is important because retrievals are often dependent upon selection of the right aerosol model. In addition, aerosol scene classification helps place the retrieved products in context for comparisons and analysis with aerosol transport models. The recent addition of CALIPSO to the A-train now provides a means of classifying aerosol distribution with altitude. CALIPSO level 1 products include profiles of attenuated backscatter at 532 and 1064 nm, and depolarization at 532 nm. Backscatter intensity, wavelength ratio, and depolarization provide information on the vertical profile of aerosol concentration, size, and shape. Thus similar estimates of aerosol type using MODIS or MISR are possible with CALIPSO, and the combination of data from all sensors provides a means of 3D aerosol scene classification. The NASA Goddard Earth Observing System general circulation model and data assimilation system (GEOS-4) provides global 3D aerosol mass for sulfate, sea salt, dust, and black and organic carbon. A GEOS-4 aerosol scene classification algorithm has been developed to provide estimates of aerosol mixtures along the flight track for NASA's Geoscience Laser Altimeter System (GLAS) satellite lidar. GLAS launched in 2003 and did not have the benefit of depolarization measurements or other sensors from the A-train. Aerosol typing from GLAS data alone was not possible, and the GEOS-4 aerosol classifier has been used to identify aerosol type and improve the retrieval of GLAS products. Here we compare 3D aerosol scene classification using CALIPSO and MODIS with the GEOS-4 aerosol classifier. Dust, smoke, and pollution examples will be discussed in the context of providing an initial verification of the 3D GEOS-4 aerosol products. Prior model verification has only been attempted with surface mass comparisons and column optical depth from AERONET and MODIS.

Welton, Ellsworth J.↗

Comets, impacts, and atmospheres

We are proposing a model for the delivery of volatiles to the inner planets by icy planetesimals (comets). Laboratory studies of the trapping of gases in ice forming at low temperatures simulate the formation of comet nuclei at various distances from the Sun in the solar nebula. The total gas content as well as the relative proportions of gases trapped in the ice are strong functions of temperature. As they trap N2 inefficiently, all planetesimals formed interior to Neptune are deficient in nitrogen, acquiring values of C/N resembling those found in the inner planet volatile inventories. A mixture of three basic types of comets appears capable of accounting for the observed volatile inventories on Venus, Earth, and Mars, with the caveat that impact erosion is necessary to explain the present condition of the martian atmosphere. The model includes the possibility of several epochs of clement conditions on early Mars. Some tests of these ideas are suggested, including measurements in Jupiter's atmosphere by the Galileo probe.

Non-NASA Center↗

The effect of dense cores on the structure and evolution of Jupiter and Saturn

The evolutionary and static models of Jupiter and Saturn were calculated with homogeneous solar composition mantles and dense cores of material consisting of solar abundances of SiO2, MgO, Fe, and Ni. Evolutionary sequences for Jupiter were calculated with cores of mass ranging from 2 to 8% of the Jovian mass; the Saturn sequences ranged from cores of mass of 16 to 22% of total mass. Two envelope mixtures representative of the solar abundances were used: they contained mass fraction of 0.74 and 0.77 of hydrogen, respectively, and 0.24 and 0.21 mass fractions of helium. For Jupiter, the observations of the temperature at 1 bar pressure, of radius and of internal luminosity were best fit by evolutionary models with a core mass of about 6.5% and chemical composition of 0.77 mass fraction of hydrogen and 0.21 mass fraction of helium. The cooling time calculated for Saturn was 2.6 x 10 to the 9th yr, almost a factor of 2 less than the percentage of the solar system.

Grossman, A. S.↗

Simplified Analysis of Pulse Detonation Rocket Engine B1owdown Gasdynamics and Performance

Pulsed detonation rocket engines (PDREs) have generated considerable research interest in recent years as a chemical propulsion system potentially offering improved performance and reduced complexity compared to conventional rocket engines. The detonative mode of combustion employed by these devices offers a thermodynamic advantage over the constant-pressure deflagrative combustion mode used in conventional rocket engines and gas turbines. However, while this theoretical advantage has spurred a great deal of interest in building PDRE devices, the unsteady blowdown process intrinsic to the PDRE has made realistic estimates of the actual propulsive performance problematic. The recent review article by Kailasanath highlights some of the difficulties in comparing the available experimental measurements with numerical models. The goal of this paper is to improve understanding of PDRE blowdown gasdynamics and performance issues through use of a simplified model that captures the essential features of the unsteady blowdown process, and yet remains computationally inexpensive. The PDRE system studied here is highly idealized, consisting of a constant-area detonation tube with one end closed and the other end open to the environment. The tube is prefilled with a gaseous propellant mixture with no initial velocity or outflow to the environment. The detonation is initiated instantaneously at the closed end of the device. Chapman-Jouguet (C-J) post-detonation gas conditions are calculated using the CET89 version of the NASA thermochemical code. The I-D, unsteady method of characteristics is used to calculate the flowfield following the detonation front. See the compressible flow texts by Thompson and Zucrow and Hoffman for details of this method. Parametric studies of the effect of mixture stoichiometry, fill temperature, and blowdown pressure ratio on performance are reported. A comparison of the performance of an idealized straight-tube PDRE with a conventional steady-state rocket engine is provided. The effect of constant-gamma and equilibrium chemistry assumptions is also examined. Additionally, in order to form an assessment of the accuracy of the model, the flowfield time history is compared to experimental data from Stanford University.

Morris, Christopher I.↗

Spherically expanding flame in silane–hydrogen–nitrous oxide–argon mixtures

The effect of silane addition on the laminar flame speed ($S^0_u$) of flames propagating in hydrogen–nitrous oxide–argon mixtures has been investigated experimentally for the first time using the spherically expanding flame technique in a constant volume combustion chamber. Replacing hydrogen by silane and maintaining the equivalence ratio constant, much higher flame speeds, explosion peak pressures, and pressure rise coefficients were measured. A previously developed detailed reaction model has been updated based on ab initio thermodynamic properties calculations and collision limit violation analysis. The improved reaction model demonstrates encouraging performance in predicting the flame speed, with a mean absolute error below 11%. To explain the effect of silane addition on the flame dynamics, a number of parameters have been calculated including OH and H rate of production, heat release rate per reaction, and sensitivity coefficient on . The dynamics of freely propagating flames in SiH 4 –H 2 –N 2 O–Ar mixtures is essentially controlled by reactions of the H–O–N chemical system: N 2 O+H=N 2 +OH, OH+H 2 =H 2 O+H, and N 2 O(+M)=N 2 +O(+M). Whereas silane addition does not influence much the rate of production of OH, it significantly modifies that of H with a number of pyrolytic chemical pathways of silicon hydrides, such as SiH+H 2 =SiH 2 +H and Si+H 2 =SiH+H, which act as sink of H atom as they proceed in the backward direction. The reactions forming SiO(s) and SiO 2 (s), such as SiO+OH=SiO 2 (s)+H and 2SiO=2SiO(s), are exothermic and significantly contribute to the temperature increase. The adiabatic, constant pressure flame temperature for mixture containing silane is significantly higher, up to several 100’s K. The increase of induced by silane addition seems to be mostly related to the large increase of the flame temperature which leads to higher energy release rate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Simplified Approach Based on Cellular Automata for Describing Direct Reduced Iron Production in Different Reducing Conditions

A quick computation approach based on cellular automata is developed and implemented to describe the reduction of iron ore pellets by a mixture of reducing agents featured by different H 2 /CO ratios. The evolution of oxygen concentration inside the pellet is followed from the beginning to the end of contact between reducing agent and pellet. The variation of thermal state of pellets and gas mixture is computed based on their initial temperature, considering the heat involved and the convective heat exchange between pellet and gas mixture. The use of cellular automata and finite‐difference method to solve the diffusion equation point out the absence of any diffusion coefficient value, allowing to make the model fit the experimental trial, because the problem is that it is not ruled just by diffusion but also by the concentration variation of reducing agent inside the pellet due to porosity increasing during reduction. The updating of the reducing agents concentration implies a sharp decrease of oxygen concentration that the cellular automata model considers. The developed model is able to provide the in‐line control of reduction process and could be used to adjust the chemical concentration and temperature of injected reducing agents.

Metallurgy & Metallurgical Engineering↗

Effects of non-thermal termolecular reactions on wedge-induced oblique detonation waves

The shock-induced combustion ramjet (Shcramjet) based on oblique detonation waves (ODWs) is among the promising choices for hypersonic propulsion systems. An understanding of the ignition, propagation, and stability of ODWs is critical to harnessing their propulsive potential. In such high speed reacting flows, there is a high probability of occurrence of non-thermal reactions due to the presence of non-trivial amounts of highly reactive radicals including H, O and OH apart from O 2 as demonstrated recently [M. P. Burke, S. J. Klippenstein, Nat. Chem. 9 (2017) 1078–1082, Y. Tao, A. W. Jasper, Y. Georgievskii, S. J. Klippenstein, R. Sivaramakrishnan, Proc. Combust. Inst. 38 (2021) 515–522]. The present work focuses on examining the initiation, propagation and structure of oblique detonation waves in stoichiometric H 2 -air mixtures through numerical simulations with and without non-thermal reactivity on a two-dimensional adaptive grid. Non-thermal reactions were included in the macroscopic kinetic model as chemically termolecular reactions facilitated by the H + OH radical-radical recombination and the H + O 2 radical-molecule association reactions. Since, the non-thermal reactions result in a corresponding decrease in the reaction fluxes of the incipient recombination/association reactions, an additional simulation was performed by applying corrections to the respective incipient recombination/association rate constants using the methodology demonstrated by Tao et al. [Y. Tao, A. W. Jasper, Y. Georgievskii, S. J. Klippenstein, R. Sivaramakrishnan, Proc. Combust. Inst. 38 (2021) 515–522]. Results show that, under ODWE relevant conditions, non-thermal reactivity fundamentally alters the induction length, intensity as well as the structure of the ODW. Specifically, it is found that non-thermal reactivity leads to a noticeable reduction in initiation length and a simultaneous increase in instantaneous peak heat release rate and the degree of unsteadiness of the ODW. Finally, statistical analysis of key thermo-chemical variables is performed to elucidate the important species as well as reactions responsible for the observed variations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Kinetic model-based group contribution method for derived cetane number prediction of oxygenated fuel components and blends

A four-step autoignition model was used to derive an expression for the ignition delay (ID) measured in ignition quality testers (IQT) with the derived cetane number (DCN) determined from this ID using the ASTM D6890 standard correlation. The model predicts DCN for individual compounds and blends as a function of each compound's global initiation and net chain branching rate constants. Expressions for these values were determined assuming they could be related to the functional groups present in each compound. Measurement data for 125 compounds and 94 binary and ternary blends (including oxygenates: alcohols, aldehydes, esters, ethers, and ketones), from literature and from measurements performed in our lab, were used to obtain the dependence of the measured ignition delay on each functional group. The new kinetic model-based group contribution method was able to predict the ignition delay of both pure compounds and blends, with an average DCN error of 4.4 (19%) and 2.8 (11%), respectively. Here, the blend model was also used to develop an ID mixing rule by incorporating existing IQT ignition delay data for each compound. Use of the mixing rule gave an average DCN error of 3.6 (16%) for blends. Both the blend model and mixing rule were found to be superior compared to standard linear by volume fraction or mole fraction mixing rules commonly used to estimate the DCN of mixtures.

42 ENGINEERING↗

Dilute Pd-in-Au alloy RCT-SiO 2 catalysts for enhanced oxidative methanol coupling

Dilute alloy catalysts have the potential to enhance selectivity and activity for large-scale reactions. Highly dilute Pd-in-Au nanoparticle alloys partially embedded in porous silica (“raspberry colloid templated” (RCT)-SiO 2 ) prove to be robust and selective catalysts for oxidative coupling of methanol. Palladium concentrations in the bimetallic nanoparticles as low as ~3.4 at.% catalyze the production of methyl formate with a selectivity of ~95% at conversions of ~55%, whereas conversions are low (<10%) for ~1.7 at.% Pd-in-Au nanoparticle and pure Au nanoparticle catalysts. Fractional reaction orders for both CH 3 OH and O 2 measured for ~3.4 at.% Pd-in-Au nanoparticles supported on RCT-SiO 2 indicated a complex mechanism in which the sites for O 2 dissociation are not saturated. Optimal methyl formate production was found for an equimolar mixture. There is no conversion of methanol in the absence of O 2 between 360 and 450 K. Finally, all observations are consistent with a mechanism derived from model studies, requiring that clusters of Pd be available on the catalyst for O 2 dissociation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Learning and IAST-Aided High-Throughput Screening of Cationic and Silica Zeolites for Alkane Capture, Storage, and Separations

We present an approach for quantitatively predicting the temperature-dependent single-component adsorption behavior of linear alkanes in silica and Na-exchanged cationic zeolites using machine learning (ML) models trained from extensive molecular simulations based on force fields with coupled cluster accuracy. A high-performing classification model was developed to distinguish between instances with negligible and non-negligible adsorption. Subsequently, two ML models were trained to predict the single-component adsorption loading and the heat of adsorption at any pressure at 300 K for any zeolite topology and silicon-to-aluminum ratio. The ML models were trained on International Zeolite Association (IZA) zeolites, and their transferability to hypothetical zeolites was successfully validated. We then expand the power of these predictions to adsorbed mixtures at arbitrary temperatures by integrating them with the Clausius–Clapeyron equation and ideal adsorbed solution theory (IAST). This approach was validated and then applied to a temperature swing adsorption separation process to demonstrate its practical utility. We demonstrate how predictions from this ML-enabled approach can allow the selection of high-performing materials that are then validated using detailed molecular simulations based on quantitatively accurate force fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗