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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Energy dissipation efficiency in the CP43 assembly intermediate complex of photosystem II

Photosystem II in oxygenic organisms is a large membrane bound rapidly turning over pigment protein complex. During its biogenesis, multiple assembly intermediates are formed, including the CP43-preassembly complex (pCP43). Here, to understand the energy transfer dynamics in pCP43, we first engineered a His-tagged version of the CP43 in a CP47-less strain of the cyanobacterium Synechocystis 6803. Isolated pCP43 from this engineered strain was subjected to advanced spectroscopic analysis to evaluate its excitation energy dissipation characteristics. These included measurements of steady-state absorption and fluorescence emission spectra for which correlation was tested with Stepanov relation. Comparison of fluorescence excitation and absorptance spectra determined that efficiency of energy transfer from β-carotene to chlorophyll a is 39 %. Time-resolved fluorescence images of pCP43-bound Chl a were recorded on streak camera, and fluorescence decay dynamics were evaluated with global fitting. These demonstrated that the decay kinetics strongly depends on temperature and buffer used to disperse the protein sample and fluorescence decay lifetime was estimated in 3.2–5.7 ns time range, depending on conditions. The pCP43 complex was also investigated with femtosecond and nanosecond time-resolved absorption spectroscopy upon excitation of Chl a and β-carotene to reveal pathways of singlet excitation relaxation/decay, Chl a triplet dynamics and Chl a → β-carotene triplet state sensitization process. The latter demonstrated that Chl a triplet in the pCP43 complex is not efficiently quenched by carotenoids. Finally, detailed kinetic analysis of the rise of the population of β-carotene triplets determined that the time constant of the carotenoid triplet sensitization is 40 ns.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Revealing the mechanism of surfactant-promoted enzymatic hydrolysis of dilute acid pretreated bamboo

Here, to improve the enzymatic digestibility of dilute acid pretreated bamboo residue (DABR), surfactants including PEG 4000 and Tween 80 were added to prevent the non-productive adsorption between residual lignin and enzyme. At the optimal loadings (e.g., 0.2 and 0.3 g surfactant/g lignin), the enzymatic digestibility of DABR improved from 29.4% to 64.6% and 61.6% for PEG 4000 and Tween 80, respectively. Furthermore, the promoting mechanism of these surfactants on enzymatic hydrolysis was investigated by real-time surface plasmon resonance (SPR) and fluorescence spectroscopy. Results from SPR analysis showed that Tween 80 outperformed PEG 4000 in terms of dissociating the irreversible cellulase adsorption onto lignin. Fluorescence quenching mechanism revealed that PEG 4000 and Tween 80 intervened the interaction between lignin and cellulase by hydrogen bonds/Van der Waals and hydrophobic action, respectively. This work provided an in-depth understanding of the mechanisms of PEG 4000 and Tween 80 on enhancing the enzymatic hydrolysis efficiency.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Molecular simulation using transfer-learned potentials for the disordered nanoscale structure of nitrogen-doped nanoporous carbons

Machine learning (ML)-based molecular dynamics (MD) simulations of the formation of a class of N-doped nanoporous carbons are performed to assess their disordered partially graphitized nanoscale structure. The study is motivated by the effectiveness of so-called nitrogen assembly carbons (NACs) for catalysis applications. Benchmark simulations for pure-C disordered graphitic systems reveal the importance of reliably capturing the vdW component of the potentials in order to accurately describe the tendency for layering of disordered graphene-like sheets. In our modeling, this is achieved by a transfer learning strategy incorporating features of the energetics from the optB88-vdW DFT functional into potentials initially trained with a less expensive functional, thereby providing a superior description of the pure-C systems. Generation from MD simulations of realistic partially graphitized structures is significantly more challenging for N-doped versus for pure C systems. However, such structures are achieved by a tailored MD simulation protocol mimicking the experimental synthesis process and in particular incorporating an annealing and subsequent quenching stages. Simulated PXRD patterns effectively reproduce the features of experimental observations for NACs, including the appearance of a prominent but broad (002) peak at around 25, and the development of another weaker feature associated with in-layer ordering of mixed C-N graphene-like sheets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A Graph Dynamical neural network approach for decoding dynamical states in ferroelectrics.

Ferroelectric materials such as BaTiO 3 show tremendous potential for emerging advances in memory devices, particular neuromorphic type devices. High density of memory can be obtained by stabilising polar domain walls at the nanoscale, regions of discontinuity between the well-defined polarization order parameter, but little is known about what controls their structure and dynamics in real nanoscale materials. Indeed, chiral polar domain walls have been observed in heterogeneous ferroelectrics, such as oxygen-deficient BaTiO 3 , but very little is known about how such polar-domains walls interact with defects. Indeed, a critical understanding of how dynamics of domain-walls depend on point-defects is crucial to create engineered ferroelectric memory devices. For this work, we perform large-scale simulations of nansocale domain-wall dynamics in pristine and defective BaTiO 3 using reactive force-field developed by us earlier (Phys. Chem. Chem. Phys., 2019, 21, 18240–18249), and capture their dynamical dependence on point defects using a graph dynamical neural-network approach, which we adapted to interrogate solids with well-defined order-parameters, and implemented using Pytorch based libraries. Our machine learning (ML) approach goes beyond the traditional post-processing methods to capture both spatial and temporal heterogeneities of large-scale molecular dynamics simulations of complex defective ferroelectric oxide materials. We crucially find that isolated oxygen vacancies introduce very localized spatial regions (~1–2 unit-cell in length) that show slow dipole relaxation due to formation of defect-dipoles, and that these defect-dipoles in turn slow the intrinsic dynamics of domain walls. Further, the roughness of domain walls, also influenced by vacancies, introduce dynamic heterogeneity along the domain-wall. As such we find a novel mechanism by which quenched disorder due to defects introduce dynamic heterogeneity thereby influencing response to external fields (particularly time varying fields) in a ferroelectric. Our study also emphasizes the need for creating digital twins of dynamical quantities to achieve autonomous in operando control of nanoscale switching.

42 ENGINEERING↗
DOE OSTI2021

Formation, structure, and thermal stability evolution of ternesite based on a single-stage sintering process

Highlights: • The synthesis of high-purity ternesite based on a single-stage sintering process was firstly studied. • The formation mechanism and crystallization behaviour of ternesite during sintering were investigated. • The structure perfection and symmetry of ternesite crystals were increased with its growth. • The growth and structural development of ternesite crystals during sintering resulted in a higher thermal stability of itself. Ternesite was prepared via a single-stage solid-state reaction from stoichiometric quantities of the CaCO{sub 3}, SiO{sub 2} and CaSO{sub 4}·2H{sub 2}O precursors. In this paper, the formation, structure, and thermal stability evolution of ternesite during sintering were investigated ex situ after quenching. The optimal sintering temperature for the formation of high-purity ternesite was approximately 1200 °C for 12 h, of which the purity level can reach as high as 96.3%. The results from scanning electron microscopy analysis suggest that the formation of ternesite benefited from the preformation of the intermediate silicate phase. Increasing the sintering temperature from 1100 °C to approximately 1250 °C was favourable for the growth of ternesite crystals, and a prolonged duration can also promote this behaviour. The structural perfection and symmetry of ternesite crystals increased with its growth, which was demonstrated by a multimethod approach. By means of thermal analysis, the growth and structural development of ternesite crystals during sintering eventually resulted in a higher thermal stability.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Through a glass darkly: In-situ x-ray computed tomography imaging of feed melting in continuously fed laboratory-scale glass melter

his study describes the first direct in-situ 3-D observation of a steady-state melting process by imaging a laboratory-scale slurry-fed glass melter in operation by x-ray computed tomography. Features of the reacting glass-feed, the foam layer underneath, and cavities in the glass melt pool are reconstructed in three-dimensional images. A slurry pool formed in a deep central caldera of dense dried feed, which penetrated into the glass melt. Slurry overflow from the caldera led to fast-dried and highly porous feed structure. A thin layer of foam separated the caldera from the melt. Bubbles ?5-15 mm in diameter were seen to grow beneath the reacting feed and move through the melt to escape at the edge. Pore morphology is benchmarked against computed tomography scans of a pellet of reacting simulated waste glass feed, and evolved gas analysis describes the gases generated as a function of temperature. Cooling artifacts are imaged and compared to previous studies of quenched cold caps. Detailed understanding of processes occurring during the conversion process in and below the reacting feed layer is necessary for the development of representative models of the melting process.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Influence of QD photosensitizers in the photocatalytic production of hydrogen with biomimetic [FeFe]-hydrogenase. Comparative performance of CdSe and CdTe

Photocatalytic systems comprising a hydrogenase-type catalyst and CdX (X = S, Se, Te) chalcogenide quantum dot (QD) photosensitizers show extraordinary hydrogen production rates under visible light excitation. What remains unknown is the mechanism of energy conversion in these systems. In this work, we have explored this question by comparing the performance of two QD sensitizers, CdSe and CdTe, in photocatalytic systems featuring aqueous suspensions of a [Fe 2 (μ-1,2-benzenedithiolate) CO 6 ] catalyst and an ascorbic acid sacrificial agent. Overall, the hydrogen production yield for CdSe-sensitized reactions QDs was found to be 13 times greater than that of CdTe counterparts. According to emission quenching experiments, an enhanced performance of CdSe sensitizers reflected a greater rate of electron transfer from the ascorbic acid (k Asc ). The observed difference in the QD-ascorbic acid charge transfer rates between the two QD materials was consistent with respective driving forces for these systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Visible-Light-Initiated Free-Radical Polymerization by Homomolecular Triplet-Triplet Annihilation

Polymerization reactions initiated by ultraviolet light are ubiquitous in scores of industrial applications but would markedly benefit from visible-light activation to overcome stability, energy consumption, light penetration, and sample geometry limitations. The current work leverages visible-light-driven homomolecular triplet-triplet annihilation (TTA) in zinc(II) meso-tetraphenylporphyrin (ZnTPP) to initiate facile free-radical polymerization in trimethylolpropane triacrylate (TMPTA) and methyl acrylate (MA) monomers through ultrafast electron transfer quenching. Selective Q-band (S 1 ) excitation of ZnTPP in the green or yellow sensitizes TTA occurring between two 3 ZnTPP* energized chromophores, ultimately generating the highly reducing S 2 excited state on one ZnTPP molecule (E red = –2.13 V versus saturated calomel electrode, SCE). Subsequently, this S 2 state engages in electron transfer with TMPTA or MA, thereby initiating the radical polymerization process. Bimolecular electron transfer was confirmed through optically gated fluorescence upconversion. In conclusion, FT-IR and EPR spin-trapping experiments verified visible-light-initiated polymerization leading to the formation of well-defined macro- and microscopic objects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Considering computational speed vs. accuracy: Choosing appropriate mesoscale RVE boundary conditions

Modeling a material’s microstructure using continuum theories allows for inspection of the relationship between coarse scale and fine scale behaviors. Computational limits generally require selection of a sub-volume from a bulk sample in order to directly model the microstructure. Boundary conditions are applied to the sub-volume to mimic the excluded bulk material. Appropriate selection of boundary conditions helps effectively determine the appropriate spatial scale required of the sub-volume. Applicable boundary conditions include direct displacement, periodic, and uniform traction. While direct displacement and periodic boundary conditions are commonly used, uniform traction boundary conditions have seen limited use due to rigid body stability issues in simulations of compression or shear deformation. A new application of uniform traction boundary conditions was developed through linear constraint equations, similar to approaches employed by direct displacement and periodic boundary conditions, to quench rigid body motions with minimal interference of the relative deformation of the model. These boundary conditions were tested by compressing several synthetically generated periodic microstructures using the finite element method. Evaluating the effective stiffness along the compression axis, the direct displacement boundary condition produced the stiffest response, whereas the uniform traction boundary condition produced the most compliant. Periodic boundary conditions produced the same response for all volumes analyzed and both the direct displacement and uniform traction boundary conditions trended toward the periodic response as the domain volume increased. Computational performance was also evaluated for each boundary condition using implicit and explicit solvers. Direct displacement boundary conditions presented the lowest computational cost of all of the boundary conditions followed by periodic then uniform traction. The computational expense of periodic and uniform traction boundary conditions limited the viable spatial scale and mesh resolutions able to be simulated. Selection of appropriate boundary conditions for specific uses need to be a balance between allowable computational expense and accuracy of the method. Techniques for evaluating which boundary conditions to use are discussed.

42 ENGINEERING↗
DOE OSTI2025

Differentiable lagrangian shock hydrodynamics with application to stable shock acceleration of density interfaces

We develop a gradient based optimization approach for the equations of compressible, Lagrangian hydrodynamics and demonstrate how it can be employed to automatically uncover strategies to control hydrodynamic instabilities arising from shock acceleration of density interfaces. Strategies for controlling the Richtmyer-Meshkov instability (RMI) are of great benefit for inertial confinement fusion (ICF) where shock interactions with many small imperfections in the density interface lead to instabilities which rapidly grow over time. These instabilities lead to mixing which, in the case of laser driven ICF, quenches the runaway fusion process ruining the potential for positive energy return. Here, we demonstrate that control of these instabilities can be achieved by optimization of initial conditions with ( > 100) parameters. Optimizing over a large parameter space like this is not possible with gradient-free optimization strategies. This requires computation of the gradient of the outputs of a numerical solution to the equations of Lagrangian hydrodynamics with respect to the inputs. We show that the efficient computation of these gradients is made possible via a judicious application of (i) adjoint methods, the exact formal representation of sensitivities involving partial differential equations, and (ii) automatic differentiation (AD), the algorithmic calculation of derivatives of functions. Careful regularization of multiple operators including artificial viscosity and timestep control is required. We perform design optimization of > 100 parameter energy field driving the Richtmyer Meshkov instability showing significant suppression while simultaneously enhancing the acceleration of the interface relative to a nominal baseline case.

Hydrophysics↗
DOE OSTI2021

Combustion in the ZrF 4 -Mg-Si and ZrF 4 -Al-Si systems for preparation of zirconium silicides

The exothermic reactions in the ZrF 4 –Mg-Si and ZrF 4 -Al-Si systems are investigated by a fast temperature recording (thermocouple) technique, differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). A quenching method is used to arrest the combustion process and conduct a layer-by-layer analysis of the products by x-ray diffraction (XRD) and electron microscopy. Two seemingly similar reactive systems exhibited considerably different combustion characteristics, composition, and morphology. Based on these investigations, we propose and discuss phase formation mechanisms at the early stages for each system. Three different pathways involving the reaction of ZrF 4 with other reagents and the Mg 2 Si intermediate are identified to occur in the ZrF 4 –Mg-Si system. Contrary to the complex mechanism in the ZrF 4 –Mg-Si system, the early stage of the combustion process for the ZrF 4 -Al-Si system involves the interaction of ZrF 4 with Al-Si eutectic melt. The exothermic reaction between reduced solid Zr and Si melt is the primary heat-generating step for both systems in spite of substantial differences in the early stages of the reactions. The silicon content in the reactive mixtures governs the phase composition of products. The ZrSi 2 phase, with a high growth rate, forms first on the Zr particle surfaces and then grows by a reactive diffusion mechanism. The ZrSi 2+ Zr reaction produces silicon-lean phases (e.g., ZrSi) when the silicon supply is limited. The combustion temperature also has a considerable influence on the phase compositions of the products. High combustion temperature in the ZrF 4 +2Mg+Si mixture enables the formation of multiphase products (α-ZrSi and β-ZrSi), whereas the relatively lower temperatures in the 3ZrF 4 +4Al+3Si mixture yields a single-phase α-ZrSi. As a result, lower combustion temperatures also make the ZrF 4 -Al-Si system more advantageous for the preparation of zirconium silicides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

On the hot surface ignition of a wall-stagnating spray flame

The ignition of fuel sprays due to interaction with hot surfaces is an important phenomenon in the safety analysis of many engineering systems. We perform a parametric study of the hot surface ignition (HSI) of a fuel spray approaching a heated surface caused by the accidental leakage of a fuel line. Here, to this end, we employ a one-dimensional Eulerian-Eulerian formulation with a non-equilibrium evaporation model and a realistic chemical mechanism to describe $n$-dodecane fuel chemistry. We first describe and analyze the phenomenology of the unsteady processes leading to ignition using non-dimensionalized quantities. Through consideration of the temporal development of the most reactive mixture, we demonstrate that ignition occurs at a fuel-lean composition in a premixed region near the hot surface. Using non-dimensional parameters identified from the governing equations, we perform a parametric study of the time, location and local mixture composition at ignition and determine the ignition limits. We then identify the most important parametric sensitivities for physical analysis using a data-driven classification method. Our analysis demonstrates a contraction of the ignition limits with increased Stokes number and a regime of parametric insensitivity of igniting mixture composition. We also show that at high Damköhler numbers, the ignition location conforms to the parametric behavior of the thermal boundary layer, whereas at low Damköhler numbers approaching the ignition limit it reaches a near-unity value of the quenching Peclet number. We then compare the demonstrated parametric dependencies to the results of the quasi-steady asymptotic ignition literature, showing that our results are consistent with those obtained analytically within the limitations imposed by the simplified formulation of the latter.

42 ENGINEERING↗
DOE OSTI2023

Cost-constrained adaptive simulations of transient spray combustion in a gas turbine combustor

Predictive high-fidelity simulations of turbulent spray combustion must capture the combined effects of complex chemistry, multiphase evaporating flow and spray-flame interactions to achieve physical accuracy. Finite-rate chemistry (FRC) combined with a realistic chemical mechanism is a combustion model well-suited for this purpose, but has a high computational cost due to the large number and stiffness of transported chemical species. In contrast, flamelet-based models achieve lower cost by transporting a small number of quantities of reduced stiffness, but assumptions regarding local flame topology, boundary conditions and inter-phase coupling limit their physical accuracy. Recently, the Pareto-efficient combustion (PEC) framework was developed to dynamically assign combustion models based on local cost and accuracy metrics in gas-phase reacting flows. In this work, we extend this PEC framework to spray combustion through the rigorous analysis of the multiphase coupling terms in the governing equations. The derivation shows that spray evaporation causes errors in the prediction of species mass fractions for flamelet-based models due to the sensitivity of the local thermo-chemical state to changes in composition caused by fuel vaporization across combustion regimes present in practical spray combustion devices. Sub-model assignment is formulated as a multiple-choice knapsack problem, where computational cost is directly controlled through the fraction of the domain assigned to the FRC sub-model. The extended PEC formulation is applied to the simulation of a realistic rich-quench-lean gas turbine combustor at steady-state conditions, as well as transient operation resulting in lean blow-out (LBO). Analysis of transient simulations during LBO demonstrates the extended PEC formulation’s capacity to dynamically adapt to changing conditions within the combustor. Transient combustor dynamics are shown to approach convergence with limited increases in computational cost, while retaining substantial computational cost reduction compared to monolithic FRC simulations. Through PEC simulations with increasing fractions of the domain assigned to FRC, monolithic flamelet simulations are shown to over-predict flame stability during LBO. Finally, the extended PEC formulation is thus shown to overcome deficiencies of monolithic models by controlling modeling error for multiphase combustion modeling.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Non-equilibrium low-temperature plasma-assisted combustion of iso-octane: Perturbing pyrolysis and oxidation kinetics

Here, in this study, a plasma-coupled flow reactor facility is used to examine the effects of non-equilibrium low-temperature plasmas on perturbing the pyrolysis and oxidation kinetics of iso-octane. Experiments were performed in highly dilute reactive mixtures of nitrogen, at near isothermal conditions for temperatures ranging from 523 K to 1203 K. Experiments cumulatively demonstrated enhanced chemical reactivity with the plasma for temperatures below 900 K, and a lowering of the hot-ignition temperature. Detailed kinetic insight was derived from a 0D plasma-coupled kinetic model, utilizing a constructed mechanism that combined both plasma-specific chemistry and the neutral combustion chemistry. For pyrolysis conditions, the model displayed relatively good agreement with fuel consumption and the formation of most intermediates compared to the experimental data, demonstrating the model is able to accurately predict primary radical formation from the plasma directly interacting with the fuel. Enhanced reactivity was attributed to collisional quenching of excited-states of N 2 with fuel, which led to efficient fuel fragmentation and enhancement of the H-radical flux. For oxidation conditions, the model displayed satisfactory agreement with the experiments. Model predictions were able to accurately predict fuel consumption and most intermediate speciation data for T > 800 K, but most discrepancies were towards T < 800 K in particular with oxygenated intermediates. In the presence of oxygen, plasma effects were predominantly spent on efficient enhancement of O- and H-radical fluxes, leading to further fuel fragmentation and initiation of both the OH- and HO 2 -radical pools. Subsequent reactivity of iso-octane was then dictated by the response of the temperature-dependent neutral chemistry. At low-temperatures (T = 643 K), enhanced fuel radicals and O 2 -additon chemistry lead to the formation of oxygenated species, while at intermediate temperatures (T = 843 K) net decrease in OH-radical reactivity led to an increase in hydrocarbon speciation. Near the self-ignition threshold (T = 1163 K), radicals generated by high-temperature branching reactions dominate the oxidation process and effectively ignition. This study ultimately demonstrated that the enhancement of radicals afforded by the plasma causes a deviation in known understanding of iso-octane kinetics in some regards and warrants future studies to reconcile these discrepancies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Analysis of direct and indirect noise in a next-generation aviation gas turbine combustor

A large-eddy simulation (LES) of a next-generation combustor is performed to examine effects of this combustor concepts on direct and indirect combustion noise characteristics. Direct noise is computed considering the unsteady heat release predictions while entropy fluctuations in the downstream part of the combustor are used to estimate indirect noise through the transfer function of the outlet nozzle. A low-order acoustic reconstruction technique, which utilizes the Green’s function of the configuration, is developed to compute the acoustics inside the combustor. Comparisons to experimental results are reported, showing the reasonable accuracy of the LES and combustion noise computations. The direct noise spectrum peaks at frequencies around 3 kHz because of the fast timescales associated with the chemical reactions inside the combustor. In addition, the indirect noise is dominant at low frequencies, i.e., less than 400 Hz, because of the characteristics of the entropy spectrum at the outlet nozzle. Further, compared to a conventional rich-quench-lean (RQL) combustor configuration, significant differences in the acoustics are observed, and are explained by two specific technological novelties. Firstly, the direct noise spectrum peaks at significantly higher frequencies due to the combustor’s compactness. Secondly, the entropy inhomogeneties downstream of the combustion region are an order of magnitude smaller in amplitude due to the lack of dilution with cold air. This leads to a significant reduction in the indirect noise amplitude at low frequencies, where it is the dominant source of noise. These results suggest opportunities for advanced combustion technologies to achieve substantial reductions in combustion-related noise.

42 ENGINEERING↗
DOE OSTI2025

Experimental and theoretical investigation into the high pressure deflagration products of 2,6-diamino-3,5-dinitropyrazine-1-oxide (LLM-105)

Diamond anvil cell (DAC) laser ignition experiments and reactive ab initio molecular dynamics (AIMD) simulations were performed on the high explosive (HE) LLM-105 to investigate its high pressure (HP) deflagration chemistry. Raman and optical spectroscopy measurements reveal LLM-105 reacts into an opaque carbonaceous product at 4–25 GPa. At pressures >~ 27 GPa, the reaction product consists of an amorphous optically transparent solid and nitrogen (N 2 ) in the solid phase. While not a one-to-one comparison due to the small time and length scales, the HP AIMD simulations show that some of the product is molecular N 2 , in qualitative agreement with experiment, while above 20 GPa most of the product consists of large amorphous C x H y N z O k clusters. Clustering is enhanced with pressure and reduces with temperature. In the experiments with initial sample pressure >~ 25 GPa, the pressure within the DAC decreases with minimal change in DAC cavity area. At initial sample pressures of 43.9 GPa, when quenched to 0 K, simulations predict a product experiencing a lower pressure consistent with the experimental measurement at lower load pressures. In conclusion, the results are important for understanding the HP deflagration chemistry of LLM-105.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Impact of gasoline composition on the effects of nitric oxide on autoignition and knock in a DISI engine

Modern spark-ignition engines use exhaust gas recirculation (EGR) to dilute the charge and suppress knock, enabling the use of higher compression ratios and/or more optimum combustion phasing for higher efficiency. The effectiveness of EGR is affected by the composition of the fuel and its chemical-kinetic interactions with combustion products. Among those, nitric oxide (NO) has been shown to strongly affect autoignition reactivity. However, the impact of fuel composition of the effect of NO on reactivity is not well-understood. Here, in this study, engine experiments were conducted to assess the impact of NO seeded to the intake on knock-limited operation of two gasoline fuels (high cycloalkane content, or HCA, and high olefin content, or HO). Results showed that compositionally-different fuels responded differently to NO. HCA, which was less knock-limited than HO for NO < 200 ppm, became more knock-limited for NO > 200 ppm. Moreover, it was found that differences in knock between fuels were caused by differences in autoignition chemistry and not in the sequential autoignition process of the end gas that occurs due to thermal stratification. Chemical kinetic simulations were performed to better understand the experimental results. For HCA, intermediate-temperature heat release had a greater impact on autoignition reactivity than low-temperature heat release, while the opposite was observed for HO. For both fuels, NO enhances the magnitude of low-temperature heat release via NO + HO 2 → NO 2 + OH. The effect of NO on reactivity was stronger for HCA because OH produced from NO helped to overcome the OH quenching effect of cyclopentane, a main species in HCA. In contrast, HO had relatively strong inherent low-temperature chemistry arising from iso-octane, which reduced the impact of NO on reactivity. For the range of NO mole fractions tested in this study, in-cylinder NO increased fuel’s knock propensity, especially for fuels with mild low-temperature chemistry.

Autoignition↗
DOE OSTI2024

Harnessing graph convolutional neural networks for identification of glassy states in metallic glasses

Graph Convolutional Neural Networks (GCNNs) have emerged as powerful tools for analyzing materials. In this study, we employ GCNNs to examine structural characteristics of CuZr metallic glasses (MGs) and identify their states. We use molecular dynamics to simulate the quenching process of CuZr, using cooling rates ranging from 10 9 to 10 15 K/s, to produce six unique glassy states. For each state, we create a dataset comprising 1,800 distinct samples. We evaluate the effectiveness of various GCNNs, including Graph Attention Neural Network (GANN), Graph Sample and AggreGatE (GraphSAGE), Graph Isomorphism Network (GIN), and Relational Graph Convolutional Neural Network (RGCN). GANN and GraphSAGE demonstrate comparable performance, achieving an overall accuracy of 81% in classifying the MG states. Furthermore, these results underscore the potential of GCNNs to detect subtle structural variances in disordered materials and point to broader application of deep learning in the analysis of MGs and other amorphous substances.

36 MATERIALS SCIENCE↗