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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Probing the antagonistic effect of toluene as a component in surrogate fuel models at low temperatures and high pressures. A case study of toluene/dimethyl ether mixtures

There is a dearth of experimental data which examine the fundamental low-temperature ignition (T < 900 K) behavior of toluene resulting in a lack of data for the construction, validation, and interpretation of chemical kinetic models for commercial fuels. In order to gain a better understanding of its combustion chemistry, dimethyl ether (DME) has been used as a radical initiator to induce ignition in this highly knock resistant aromatic, and its influence on the combustion of toluene ignition was studied in both shock tube and rapid compression machines as a function of temperature (624–1459 K), pressure (20–40 atm), equivalence ratio (0.5–2.0), and blending ratio (100% toluene, 76% toluene (76T/24D), 58% toluene (58T/42D), 26% toluene (26T/74D) and 100% DME). We use several literature chemical kinetic models to interpret our experimental results. For mixtures containing high concentrations of toluene at low-temperatures none of these are capable of reproducing experiment. This then implies an incomplete understanding of the low-temperature oxidation pathways which control its ignition in our experimental reactors, and by extension, in spark- (SI) and compression-ignition (CI) engines, and an updated detailed chemical kinetic model is presented for engineering applications. Model analyses indicate that although the initial fate of the fuel is dominated by single-step H-atom abstraction reactions from both the benzylic and phenylic sites, the subsequent fate of the allylic and vinylic radicals formed is much more complex. Further experimental and theoretical endeavors are required to gain a holistic qualitative and quantitative chemical kinetics based understanding of the combustion of pure toluene, toluene blends, and commercial fuels containing other aromatic components, at temperatures of relevance to SI and CI engines.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Data augmentation for disruption prediction via robust surrogate models

The goal of this work is to generate large statistically representative data sets to train machine learning models for disruption prediction provided by data from few existing discharges. Such a comprehensive training database is important to achieve satisfying and reliable prediction results in artificial neural network classifiers. Here, we aim for a robust augmentation of the training database for multivariate time series data using Student t process regression. We apply Student t process regression in a state space formulation via Bayesian filtering to tackle challenges imposed by outliers and noise in the training data set and to reduce the computational complexity. Thus, the method can also be used if the time resolution is high. We use an uncorrelated model for each dimension and impose correlations afterwards via colouring transformations. We demonstrate the efficacy of our approach on plasma diagnostics data of three different disruption classes from the DIII-D tokamak. To evaluate if the distribution of the generated data is similar to the training data, we additionally perform statistical analyses using methods from time series analysis, descriptive statistics and classic machine learning clustering algorithms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Structure and Bonding Investigation of Plutonium Peroxocarbonate Complexes Using Cerium Surrogates and Electronic Structure Modeling

Herein, we report the synthesis and structural characterization of K8[(CO3)3Pu]2(µ-η2-η2-O2)2•12H2O. This is the second plutonium-containing addition to the previously studied alkali metal peroxo-carbonate series M8[(CO3)3A]2(µ-η2-η2-O2)2•xH2O (M = alkali metal; A = Ce or Pu; x = 8, 10, 12 or 18), for which only the M = Na analog has been previously reported when A = Pu. The previously reported crystal structure for Na8[(CO3)3Pu]2(µ-η2-η2-O2)2•12H2O is not isomorphous with its known Ce analogue. However, a new synthetic route to these M8[(CO3)3A]2(µ-η2-η2-O2)2•12H2O complexes, described below, has produced crystals of Na8[(CO3)3Ce]2(µ-η2-η2-O2)2•12H2O that are isomorphous with the previously reported Pu analogue. Via this synthetic method, the M = Na, K, Rb, and Cs salts of M8[(CO3)3Ce]2(µ-η2-η2-O2)2•xH2O have also been synthesized for systematic structural comparison with each other and the available Pu analogues using single-crystal X-ray diffraction, Raman spectroscopy and density functional theory (DFT) calculations. The cerium salts in particular demonstrate subtle differences in the peroxide bond lengths which correlate to Raman shifts for the peroxide Op–Op stretch (Op = the oxygen atoms of the peroxide bridges) with each of the cations studied: Na+ (1.492(3) Å /847 cm-1), Rb+ (1.471(1) Å /854 cm-1), Cs+ (1.474(1) Å /859 cm-1), and K+ (1.468(6) Å, 870 cm-1). The trends observed in the M–Op and Op–Op bond distances appear to relate to supermolecular interactions between the neighboring cations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

“Teamwork Makes the Dream Work”: Tribal Competition Evolutionary Search as a Surrogate for Free-Energy-Based Structural Predictions

Crystal structure prediction has been a grand challenge in material science owing to the large configurational space that one must explore. Evolutionary (genetic) algorithms coupled with first principles calculations are commonly used in crystal structure prediction to sample the ground and metastable states of materials based on configurational energies. However, crystal structure predictions at finite temperature (T), pressure (P), and composition (X) require a free-energy-based search that is often computationally expensive and tedious. Here in this paper, we introduce a new machine-learning workflow for structure prediction that is based on a concept inspired by the evolution of human tribes in primitive society. Our tribal genetic algorithm (GA) combines configurational sampling with evolutionary optimization to accurately predict entropically stabilized phases at finite (T, P, X), at a computational cost that is an order of magnitude smaller than that required for a free-energy-based search. In a departure from standard GA techniques, the populations of individuals are divided into multiple tribes based on a bond-order fingerprint, and genetic operations are modified to ensure that cluster configurations are sampled adequately to capture entropic contributions. Team competition introduced into the evolutionary process allows winning teams (representing a better set of individuals) to expand their sizes; this translates into a more expanded search of the phase space allowing us to explore solutions near possible global minimum. Each team explores a specific section of the structural phase space and avoids bias on solutions arising from the use of individual populations in a purely energy-based search. We demonstrate the efficacy of our approach by performing the structural prediction of a representative two-dimensional two-body system as well as Lennard-Jones clusters over a range of temperatures up to its melting point. Our approach outperforms the standard GA approaches and enables structural search under “real nonambient conditions” on both bulk systems and finite-sized clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Direct Deoxygenation of Phenol over Fe-Based Bimetallic Surfaces Using On-the-Fly Surrogate Models

We present an accelerated nudged elastic band (NEB) study of phenol direct deoxygenation (DDO) on Fe-based bimetallic surfaces using a recently developed Gaussian process regression (GPR) calculator. Our test calculations demonstrate that the GPR calculator achieves up to 3 times speedup compared to conventional density functional theory calculations while maintaining high accuracy, with energy barrier errors below 0.015 eV. Using GPR-NEB, we systematically examine the DDO mechanism on pure Fe(110) and surfaces modified with Co and Ni in both top and subsurface layers. Our results show that subsurface Co and Ni substitutions preserve favorable thermodynamics and kinetics for both C–O bond cleavage and C–H bond formation, comparable to those on the pure Fe(110) surface. In contrast, top-layer substitutions generally increase the C–O bond cleavage barrier, render the step endothermic, and result in significantly higher reverse reaction rates, making DDO unfavorable on these surfaces. This work demonstrates the effectiveness of GRR-accelerated transition state searches for complex surface reactions and provides insights into rational design of bimetallic catalysts for selective deoxygenation.

Aromatic compounds↗
DOE OSTI2024

Porous Iron Electrodes Reduce Energy Consumption During Electrocoagulation of a Virus Surrogate: Insights into Performance Enhancements Using Three-Dimensional Neutron Computed Tomography

Electrocoagulation has attracted significant attention as an alternative to conventional chemical coagulation because it is capable of removing a wide range of contaminants and has several potential advantages. In contrast to most electrocoagulation research that has been performed with nonporous electrodes, in this study, we demonstrate energy-efficient iron electrocoagulation using porous electrodes. In batch operation, investigation of the external pore structures through optical microscopy suggested that a low porosity electrode with sparse connection between pores may lead to mechanical failure of the pore network during electrolysis, whereas a high porosity electrode is vulnerable to pore clogging. Electrodes with intermediate porosity, instead, only suffered a moderate surface deposition, leading to electrical energy savings of 21% and 36% in terms of electrocoagulant delivery and unit log virus reduction, respectively. Neutron computed tomography revealed the critical role of electrode porosity in utilizing the electrode’s internal surface for electrodissolution and effective delivery of electrocoagulant to the bulk. Energy savings of up to 88% in short-term operation were obtained with porous electrodes in a continuous flow-through system. Further investigation on the impact of current density and porosity in long-term operation is desired as well as the capital cost of porous electrodes.

42 ENGINEERING↗
DOE OSTI2020

Absolute Templating of M(111) Cluster Surrogates by Galvanic Exchange

The precise preparation of monodisperse nanomaterials is among the most fundamental tasks in inorganic synthesis and materials science. Achieving this goal by galvanic exchange is hardly predictable, and often results in major structural changes and polydisperse mixtures. Here, taking advantage of the enhanced stability imparted by ambiphilic carbenes, we report and rationalize the absolute templating — the complete exchange of metals in a template — of group 11 clusters across the entire coinage metal family by means of galvanic exchange. We further delineate that these species provide a molecular model for better understanding the reduction of CO 2 at M(111) coinage metal surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗