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At least 289 records · Page 16

Coupled cluster benchmarks of large noncovalent complexes: The L7 dataset as well as DNA–ellipticine and buckycatcher–fullerene

In this work, benchmark binding energies for dispersion-bound complexes in the L7 dataset, the DNA–ellipticine intercalation complex, and the buckycatcher–C60 complex with 120 heavy atoms using a focal-point method based on the canonical form of second-order Møller−Plesset theory (MP2) and the domain based local pair natural orbital scheme for the coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] extrapolated to the complete basis set (CBS) limit are reported. This work allows for increased confidence given the agreement with respect to values recently obtained using the local natural orbital CCSD(T) for L7 and the canonical CCSD(T)/CBS result for the coronene dimer (C2C2PD). Therefore, these results can be considered pushing the CCSD(T)/CBS binding benchmark to the hundred-atom scale. The disagreements between the two state-of-the-art methods, CCSD(T) and fixed-node diffusion Monte Carlo, are substantial with at least 2.0 (∼10%), 1.9 (∼5%), and 10.3 kcal/mol (∼25%) differences for C2C2PD in L7, DNA–ellipticine, and buckycatcher–C60, respectively. Such sizable discrepancy above “chemical accuracy” for large noncovalent complexes indicates how challenging it is to obtain benchmark binding interactions for systems beyond small molecules, although the three up-to-date density functionals, PBE0+D4, ωB97M-V, and B97M-V, agree better with CCSD(T) for these large systems. In addition to reporting these values, different basis sets and various CBS extrapolation parameters for Hartree–Fock and MP2 correlation energies were tested for the first time in large noncovalent complexes with the goal of providing some indications toward optimal cost effective routes to approach the CBS limit without substantial loss in quality.

Ballesteros, Francisco (ORCID:0000000325732307)↗

Physical discovery in representation learning via conditioning on prior knowledge

Recent advances in electron, scanning probe, optical, and chemical imaging and spectroscopy yield bespoke data sets containing the information of structure and functionality of complex systems. In many cases, the resulting data sets are underpinned by low-dimensional simple representations encoding the factors of variability within the data. The representation learning methods seek to discover these factors of variability, ideally further connecting them with relevant physical mechanisms. However, generally, the task of identifying the latent variables corresponding to actual physical mechanisms is extremely complex. Here, we present an empirical study of an approach based on conditioning the data on the known (continuous) physical parameters and systematically compare it with the previously introduced approach based on the invariant variational autoencoders. The conditional variational autoencoder (cVAE) approach does not rely on the existence of the invariant transforms and hence allows for much greater flexibility and applicability. Interestingly, cVAE allows for limited extrapolation outside of the original domain of the conditional variable. However, this extrapolation is limited compared to the cases when true physical mechanisms are known, and the physical factor of variability can be disentangled in full. We further show that introducing the known conditioning results in the simplification of the latent distribution if the conditioning vector is correlated with the factor of variability in the data, thus allowing us to separate relevant physical factors. We initially demonstrate this approach using 1D and 2D examples on a synthetic data set and then extend it to the analysis of experimental data on ferroelectric domain dynamics visualized via piezoresponse force microscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Reactant conversion in homogeneous turbulence: Mathematical modeling, computational validations and practical applications

Closed form analytical expressions are obtained for predicting the limited rate of reactant conversion in a binary reaction of the type F + rO yields (1 + r) Product in unpremixed homogeneous turbulence. These relations are obtained by means of a single point Probability Density Function (PDF) method based on the Amplitude Mapping Closure. It is demonstrated that with this model, the maximum rate of the reactants' decay can be conveniently expressed in terms of definite integrals of the Parabolic Cylinder Functions. For the cases with complete initial segregation, it is shown that the results agree very closely with those predicted by employing a Beta density of the first kind for an appropriately defined Shvab-Zeldovich scalar variable. With this assumption, the final results can also be expressed in terms of closed form analytical expressions which are based on the Incomplete Beta Functions. With both models, the dependence of the results on the stoichiometric coefficient and the equivalence ratio can be expressed in an explicit manner. For a stoichiometric mixture, the analytical results simplify significantly. In the mapping closure, these results are expressed in terms of simple trigonometric functions. For the Beta density model, they are in the form of Gamma Functions. In all the cases considered, the results are shown to agree well with data generated by Direct Numerical Simulations (DNS). Due to the simplicity of these expressions and because of nice mathematical features of the Parabolic Cylinder and the Incomplete Beta Functions, these models are recommended for estimating the limiting rate of reactant conversion in homogeneous reacting flows. These results also provide useful insights in assessing the extent of validity of turbulence closures in the modeling of unpremixed reacting flows. Some discussions are provided on the extension of the model for treating more complicated reacting systems including realistic kinetics schemes and multi-scalar mixing with finite rate chemical reactions in more complex configurations.

Madnia, C. K.↗

Gas Chromatographic Detectors for Exobiology Flight Experiments

Exobiology flight experiments require highly sensitive instrumentation for in situ chemical analysis of the volatile chemical species that occur in the atmospheres and surfaces of various bodies within the solar system. The complex mixtures encountered place a heavy burden on the analytical instrumentation to detect and identify all species present. Future missions to Mars', comets, or planetary moons such as Europa, will perform experiments with complex analyses. In addition, instrumentation for such missions must perform under severely restricted conditions with limited resources. To meet these analytical requirements, improved methods and highly sensitive yet smaller instruments must continually be developed with increasingly greater capabilities. We describe here efforts to achieve this objective, for past and future missions, through the development of new or the improvement of existing sensitive, miniaturized gas chromatographic detectors.

Kojiro, Daniel R.↗

Flame Synthesis Of Single-Walled Carbon Nanotubes And Nanofibers

Carbon nanotubes are widely sought for a variety of applications including gas storage, intercalation media, catalyst support and composite reinforcing material [1]. Each of these applications will require large scale quantities of CNTs. A second consideration is that some of these applications may require redispersal of the collected CNTs and attachment to a support structure. If the CNTs could be synthesized directly upon the support to be used in the end application, a tremendous savings in post-synthesis processing could be realized. Therein we have pursued both aerosol and supported catalyst synthesis of CNTs. Given space limitations, only the aerosol portion of the work is outlined here though results from both thrusts will be presented during the talk. Aerosol methods of SWNT, MWNT or nanofiber synthesis hold promise of large-scale production to supply the tonnage quantities these applications will require. Aerosol methods may potentially permit control of the catalyst particle size, offer continuous processing, provide highest product purity and most importantly, are scaleable. Only via economy of scale will the cost of CNTs be sufficient to realize the large-scale structural and power applications on both earth and in space. Present aerosol methods for SWNT synthesis include laser ablation of composite metalgraphite targets or thermal decomposition/pyrolysis of a sublimed or vaporized organometallic [2]. Both approaches, conducted within a high temperature furnace, have produced single-walled nanotubes (SWNTs). The former method requires sophisticated hardware and is inherently limited by the energy deposition that can be realized using pulsed laser light. The latter method, using expensive organometallics is difficult to control for SWNT synthesis given a range of gasparticle mixing conditions along variable temperature gradients; multi-walled nanotubes (MWNTs) are a far more likely end products. Both approaches require large energy expenditures and produce CNTs at prohibitive costs, around $500 per gram. Moreover these approaches do not possess demonstrated scalability. In contrast to these approaches, flame synthesis can be a very energy efficient, low-cost process [3]; a portion of the fuel serves as the heating source while the remainder serves as reactant. Moreover, flame systems are geometrically versatile as illustrated by innumerable boiler and furnace designs. Addressing scalability, flame systems are commercially used for producing megatonnage quantities of carbon black [4]. Although it presents a complex chemically reacting flow, a flame also offers many variables for control, e.g. temperature, chemical environment and residence times [5]. Despite these advantages, there are challenges to scaling flame synthesis as well.

Wal, Randy L. Vander↗

Implementation of an Experimental Setup Based on the Three-Omega Method for Thermal Conductivity Measurements of Molten Salts

Molten salt reactors (MSRs) are one of the most promising next-generation nuclear reactor designs which use molten salts as the fuel and coolant. To design, model, predict, license, and operate MSRs, the behavior of the fuel and coolant must be understood as a function of temperature and irradiation, i.e., burnup. Of particular importance and complexity is the reliable and reproducible measurement of thermal conductivity of molten salts at high temperatures (> 500 °C). Thermal conductivity provides information on the rate at which heat passes through a specified material and is dependent on chemical composition. Currently, in the national laboratory complex, several methods for measuring thermal conductivity on molten salt systems are under development, however, to date, consistent data have not been produced. Typically, thermal conductivity measurements of high-temperature melts have been conducted by using the Transient Hot Wire (THW) method where thermal conductivity is determined by the change in temperature over time at a certain distance from a heating wire. Another time-dependent technique is the laser flash method, commonly used for solid samples. Laser flash requires prior measurements of density and heat capacity to calculate the thermal conductivity of the sample, introducing additional measurement errors. Steady state and time-dependent measurements such as THW and laser flash have errors from convection and ambient temperature fluctuations (heat radiation). In order to produce high fidelity thermal conductivity data, a measurement technique needs to be developed that will reduce the effect of convection at high temperatures by measuring in a very fast time window. In addition, to measure on actinide and irradiated salts the sample size should be small. Therefore, this project aims to develop a frequency-domain technique based on the three-omega (3?) method, previously proven to work on solids, nanofluids and low temperature solar salts (25 to 250 °C). If the 3?-device can be designed with materials that can withstand high temperatures (>500 °C) and can be configured to reduce errors due to convection, then it would prove to be a valuable technique for ensuring thermal conductivity on molten salt systems needed for MSR development. For this proposal, the 3? instrument will be designed, assembled, and tested on non-radioactive salts before being used on actinide bearing salts. In addition, a thermal model will be developed to determine the thermal conductivity of the sample from the measured thermal oscillation of the sensor. Because 3? is a direct method that requires a small volume of sample and works in a very fast time window, it will aid in suppressing the interference due to convection which is ideal when working with high temperature liquid samples.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Experimental Studies on the Effect of Impact Processes on the Formation and Evolution of Amino Acids

Introduction: A critical step in the emergence of life on Earth was the synthesis of larger organic molecules from simple building blocks such as NH3, CO2, H2O, and CH3OH. The presence of amino acids and other complex organics in comets and meteorites demonstrates that widespread organic synthesis likely occurred across the early solar system. Building on previous work [e.g., 1-3], we systematically explore impact-driven chemical evolution of exogenous organics and their precursors. Collisional processes may also have provided a source of energy for the formation of more complex organics from endogenous building blocks. The high flux of impactors to Earth immediately prior to and during the origins of life suggests that impacts could have played a critical role. Key Questions: 1. How are the formation and evolution of amino acids affected by the presence of a mineral matrix during cometary and asteroidal impacts onto the early Earth? 2. Do some minerals (e.g., phyllosilicates) provide a more robust protective framework or reactive surface site for amino-acid formation and/or polymerization? 3. Does the abundance of ices and/or amino acids relative to that of the mineral matrix affect the formation and evolution of amino acids? 4. Are there impact velocities/shock pressures at which formation or polymerization of amino acids is favored or precluded? Experimental Approach: This study systematically examines the conditions under which amino acids and other organic molecules can form, be polymerized, and/or be destroyed during impact events into particulate regolith simulants. Variable parameters include the modal composition of this regolith (silicate matrices, ratios of ices, silicates, and amino acids) and impact velocities/shock pressures. Impacts experiments were performed using the two-stage light-gas gun (LGG), vertical gun (VG), and flat-plate accelerator (FPA) in the Experimental Impact Lab at JSC. FPA experiments were performed over a range of shock pressures (11.3-31.5 GPa) using CM chondrite simulant mixed with amino acids at ratios of 0:10, 1:10, 1:103, and 1:106 (amino acid:host). Techniques for mixing cometary ices have been optimized and test runs have been performed using the LGG (see figure below). Analysis: Post-impact, samples are heated in water to extract amino acids and peptides. Extracts are characterized via liquid chromatography-mass spectrometry (LC-MS) and the mineralogies of solid residues are characterized using X-ray diffraction, scanning electron microscopy and transmission electron microscopy. Additional LC-MS and mineralogical analyses are underway.

Eve L Berger↗

Characterizing Olefin Selectivity and Stability of Silver Salts in Ionic Liquids Using Inverse Gas Chromatography

Separation systems utilizing silver(I) ion-olefin complexation have limitations since silver(I) ions can be poisoned or reduced to metallic silver. Ionic liquids (ILs) are used as solvents for silver(I) ions to facilitate separations since their physico-chemical properties can be easily tuned. To develop separation systems with sustainable olefin selectivity, factors that affect silver(I) ion stability need to be understood. In this study, a total of 13 silver salt/IL mixtures were examined by inverse gas chromatography to identify the effects of silver salt anion and IL cation/anion combination on silver(I) ion stability. The effects of temperature and three different exposure gases on silver(I) ion stability were systematically studied. Exposing silver salt/IL mixtures to hydrogen at high temperatures had a greater effect on decreasing silver(I) ion-olefin complexation. Silver(I) ions from the silver bis[(trifluoromethyl)sulfonyl]imide ([NTf 2 – ]) salt were more stable in [NTf 2 – ]-containing ILs than in [BF 4 – ]-containing ILs. Optimum mixtures exhibited high olefin selectivity and were stable beyond 90 h when exposed to hydrogen gas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrochemical Imaging of Interfaces in Energy Storage via Scanning Probe Methods: Techniques, Applications, and Prospects

Developing a deeper understanding of dynamic chemical, electronic, and morphological changes at interfaces is key to solving practical issues in electrochemical energy storage systems (EESSs). To unravel this complexity, an assortment of tools with distinct capabilities and spatiotemporal resolutions have been used to creatively visualize interfacial processes as they occur. This review highlights how electrochemical scanning probe techniques (ESPTs) such as electrochemical atomic force microscopy, scanning electrochemical microscopy, scanning ion conductance microscopy, and scanning electrochemical cell microscopy are uniquely positioned to address these challenges in EESSs. We describe the operating principles of ESPTs, focusing on the inspection of interfacial structure and chemical processes involved in Li-ion batteries and beyond. We discuss current examples, performance limitations, and complementary ESPTs. Finally, we discuss prospects for imaging improvements and deep learning for automation. We foresee that ESPTs will play an enabling role in advancing EESSs as we transition to renewable energies.

25 ENERGY STORAGE↗

Quantification of complex protective surface oxide layer formed during plasma jet exposure of multicomponent ultra-high temperature carbides

Multicomponent ultra-high temperature ceramics (MC-UHTCs) has garnered attention due to their improved thermo-mechanical and oxidation properties. MC-UHTC was progressively formed by adding a UHTC component at each step, producing binary, ternary and quaternary UHTC systems, processed by spark plasma sintering (SPS). Here, we investigate the role of multi-elements and thermochemical stability of the surface oxide layer formed during plasma arc jet exposure (T > 2500 °C) of MC-UHTCs using core-level X-ray photoelectron spectroscopy (XPS) correlated with the structural investigation. The results indicate that adding a UHTC component improves oxidation resistance due to the assemblage of refractory phases forming complex mixed oxides via preferential oxidation. XPS spectra of Ta4f, Nb3d, Ti1p, and Hf4f showed that the nature of the chemical bonds switched from metal carbides to metal oxides (metal oxy-carbides) in the binary system with retained metal carbides in ternary and quaternary UHTCs. The absence of a metal carbide peak in the high-resolution C1s scan of the binary system also supports this finding. The principal complex mixed oxide phases emanate in the exiguous oxidation of MC-UHTCs are quantified using Rietveld analysis. Overall, this study suggests that MC-UHTC is a promising material for possible application in thermal protection systems (TPS).

36 MATERIALS SCIENCE↗

Numerical assessment of triply periodic minimal surfaces for direct air capture of carbon dioxide

Direct air capture (DAC) systems often consist of packing material wetted by a capture fluid that reacts with CO 2 in the airstream. The efficiency of the contactor is determined by a complex relationship of fluid dynamics, heat and mass transfer, contactor geometry, and chemical properties. The efficiency of the contactor must be balanced with other factors, primarily pressure drop through the system. Triply periodic minimal surfaces (TPMS) are a class of differential surfaces that have been explored in multiple engineering applications and have been shown to exhibit excellent performance when used in heat exchangers. Their tortuous path provides a high surface-to-volume ratio and favorable trade-off between contact area and pressure drop. In this work, a gyroid-type TPMS contactor was evaluated using computational fluid dynamics for a variety of geometric parameters to explore the potential benefit of TPMS shapes for DAC applications. A thin-film model was employed to model the flow and distribution of the capture solvent, allowing efficient simulations of TPMS structures at scale by eliminating the need for a computationally intensive interface capturing method. A liquid-gas mass transfer model was implemented in the commercial software STAR-CCM+ and used to predict the CO 2 capture efficiency and study the trade-off between capture performance and pressure drop through analysis of capture rates, mass transfer coefficients, and other relevant variables. TPMS contactors with a variety of geometric parameters and two capture solvent options were investigated to determine the effect of design choices on the operational performance of DAC systems. In conclusion, results showed that while contactor geometry is the dominant factor in efficiency and pressure drop, the physiochemical properties of the solvent are an important secondary influence on the contactor performance.

CFD↗

Organic Analysis of Catalytic Fischer-Tropsch Type Synthesis Products: Are they Similar to Organics in Chondritic Meteorites?

Fischer-Tropsch Type (FTT) synthesis of organic compounds has been hypothesized to occur in the early solar nebula that formed our Solar System. FTT is a collection of abiotic chemical reactions that convert a mixture of carbon monoxide and hydrogen over nano-catalysts into hydrocarbons and other more complex aromatic compounds. We hypothesized that FTT can generate similar organic compounds as those seen in chondritic meteorites; fragments of asteroids that are characteristic of the early solar system. Specific goals for this project included: 1) determining the effects of different FTT catalyst, reaction temperature, and cycles on organic compounds produced, 2) imaging of organic coatings found on the catalyst, and 3) comparison of organic compounds produced experimentally by FTT synthesis and those found in the ordinary chondrite LL5 Chelyabinsk meteorite. We used Pyrolysis Gas Chromatography Mass Spectrometry (PY-GCMS) to release organic compounds present in experimental FTT and meteorite samples, and Scanning Electron Microscopy (SEM) to take images of organic films on catalyst grains.

Yazzie, Cyriah A.↗

Generalized quantum master equations can improve the accuracy of semiclassical predictions of multitime correlation functions

Multitime quantum correlation functions are central objects in physical science, offering a direct link between the experimental observables and the dynamics of an underlying model. While experiments such as 2D spectroscopy and quantum control can now measure such quantities, the accurate simulation of such responses remains computationally expensive and sometimes impossible, depending on the system’s complexity. A natural tool to employ is the generalized quantum master equation (GQME), which can offer computational savings by extending reference dynamics at a comparatively trivial cost. However, dynamical methods that can tackle chemical systems with atomistic resolution, such as those in the semiclassical hierarchy, often suffer from poor accuracy, limiting the credence one might lend to their results. By combining work on the accuracy-boosting formulation of semiclassical memory kernels with recent work on the multitime GQME, here we show for the first time that one can exploit a multitime semiclassical GQME to dramatically improve both the accuracy of coarse mean-field Ehrenfest dynamics and obtain orders of magnitude efficiency gains.

Chemistry↗

Facilitating better and faster simulations of aerosol-cloud interactions in Earth system models

Focal Area(s): 1. Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising a hierarchy of models. 2. Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI. Science Challenge: One major challenge that Earth system models (ESMs) face in providing credible prediction of the Earth system and its water cycle characteristics (e.g., mean state, variability, and extreme events) is to accurately simulate aerosol-cloud interactions (ACI). The physical, chemical, and dynamical processes affecting ACI are extremely complex and they range from nanoscale to planetary scale. In each model development cycle, scientists spend significant efforts investigating model deficiencies and uncertainties associated with aerosols (e.g., emissions, chemical processes, aerosol microphysics, and transport) and clouds (e.g., macrophysics, microphysics, turbulence, and large-scale circulation) in order to develop improved treatments. However, despite decades of active research, ACI is still a major source of uncertainty in climate projections, even though great progress has been made. Specific scientific challenges include: (i) Parameterizations are developed based on limited data; (ii) The complexity of a parameterization required for accurate predictions is not understood; (iii) Incomplete and unknown physics leads to errors in the fully coupled Earth system; and (iv) Complex physics is computationally too expensive to employ in ESMs.

54 ENVIRONMENTAL SCIENCES↗

Building confidence in models for complex barrier systems for radionuclides

The modeling and simulation of the Cement-clay Interaction-Diffusion field (CI-D) experiment at the Mont Terri site in Switzerland presented here demonstrates that it is possible to capture the multiscale physical and chemical features of natural and engineered barrier systems for radionuclides. The simulations are successfully carried out with the newly developed CrunchODiTi high-performance computing software that accounts for multiple continua, including a continuum representing the electrical double layer (EDL) developed along negatively charged clay particles in clay rock. The simulation also accounts for both the complex three-dimensional (3D) geometry, expected as the norm in a geological waste repository, and the anisotropy of the geological formation. In addition, the high resolution of the model makes it possible to include "skin effects" developed at the interface between highly reactive materials, in this case between the high pH cement and the circumneutral but electrostatic Opalinus Clay. The successful history matching with the field experiment demonstrates that the distinct geochemical and physical properties of the cement and the Opalinus Clay in the CI-D experiment can be accounted for. Such analyses are essential for developing a defensible safety case for the underground storage of radioactive waste.

Sarsenbayev, Dauren↗

Photochemical micromotor of eccentric core in isotropic hollow shell exhibiting multimodal motion behavior

Adaptive motion behavior in response to different environmental stimuli is ubiquitous in biology and enables creatures to achieve a diversity of complex tasks, but not typically observed in synthetic systems. In this report we propose a design of chemically-powered micromotors actively performing multimodal motion behaviors with the external stimulus changing. They have isotropic outer surfaces but inherent inner mass asymmetry, such as eccentric core-in-hollow shell TiO 2 (E-TiO 2 ) microspheres. Their motion behavior can be spontaneously transformed among random Brownian propulsion (stochastic walk), negative phototaxis (moving against incident light), and negative photogravitaxis (moving against gravity) when the light intensity, illumination direction, or fuel concentration change. At a low light intensity and/or low H 2 O 2 fuel concentration, the E-TiO 2 micromotors perform directional movement away from light based on the dominated diffusiophoresis by the photocatalytic reaction over the isotropic shell. With the increase of light intensity or fuel concentration, there are more and more photons or fuels to reach the eccentric core and the contribution of the photocatalytic reaction over it to the diffusiophoresis gradually becomes dominant. In this case, the E-TiO 2 micromotors perform stochastic walks near the substrate due to their Brownian random rotational reorientations. The micromotors are single component, have low density, and can be synthesized in a large scale and at a low cost. This work will facilitate the development of multifunctional micro/nanomotors with varying behaviors and functions depending on environmental cues, e.g., enabling efficient search and delivery operations.

36 MATERIALS SCIENCE↗

Data-driven prediction of the output composition of an atmospheric pressure plasma jet

Cold atmospheric plasma (CAP) in open air hosts numerous chemical species engaged in thousands of chemical reactions. Comprehensive diagnosis of its chemical composition is important across various fields from medicine, where reactive oxygen and nitrogen play key roles, to surface modification. In applications, a centimeter-scale helium–air jet operates for minutes, featuring micrometer-sized streamers and an atmospheric pressure-induced collision frequency in the hundreds of GHz range. To address this intricate multi-scale issue, we introduce a machine learning approach: using a physics-informed neural network (PINN) to tackle the multi-scale complexities inherent in predicting the complete list of species concentrations, gas temperature, and electron temperature of a CAP jet supplied with a mixture of helium and air. Experimental measurements of O 3 , N 2 O, and NO 2 concentrations downstream of the plasma jet, combined with fundamental physics laws, the conservation of mass and charge, constrain the PINN, enabling it to predict the concentrations of all species that are not available from the experiment, along with gas and electron temperatures. The results, therefore, obey all the physical laws we provided and can have a chemical balance with the measured concentrations. In conclusion, this methodology holds promise for describing and potentially regulating complex systems with limited experimental datasets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Combustion research for gas turbine engines

Research on combustion is being conducted at Lewis Research Center to provide improved analytical models of the complex flow and chemical reaction processes which occur in the combustor of gas turbine engines and other aeropropulsion systems. The objective of the research is to obtain a better understanding of the various physical processes that occur in the gas turbine combustor in order to develop models and numerical codes which can accurately describe these processes. Activities include in-house research projects, university grants, and industry contracts and are classified under the subject areas of advanced numerics, fuel sprays, fluid mixing, and radiation-chemistry. Results are high-lighted from several projects.

Mularz, E. J.↗