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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Developing a Descriptor-Based Approach for CO and NO Adsorption Strength to Transition Metal Sites in Zeolites

The discovery of new materials tailored for a given application typically requires the screening of a large number of compounds, and this process can be significantly accelerated by computational analysis. In such an approach the performance of a compound is correlated to a materials property, a so-called descriptor. Here we develop a descriptor-based approach for the adsorption of CO and NO to Cu, Ni, Co, and Fe sites in zeolites. Here we start out by discussing a possible design strategy for zeolite catalysts, define the studied test set of sites in the zeolites SSZ-13 and mordenite, and define a set of appropriate descriptors. In a subsequent step we use these descriptors in single-parameter, two-parameter, and multiparameter regression analysis and finally use a machine-learning genetic algorithm to reduce the number of variables. We find that one or two descriptors are not sufficient to accurately capture the interactions between molecules and metal centers in zeolites, and indeed a multiparameter approach is necessary. Even though many of the descriptors are directly correlated, we identify the position of the s orbital and the number of valence electrons of the active site as well as the HOMO–LUMO gap of the adsorbate as most important descriptors. Furthermore, the reconstruction of the active sites upon adsorption plays a crucial role, and when it is explicitly included in the analysis, correlations improve significantly. In the future we expect that the fundamental methodology developed here will be adapted and transferred to selected problems in adsorption and catalysis and will assist the rational design of materials for the given application.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Nature of the Active Sites for CO Reduction on Copper Nanoparticles; Suggestions for Optimizing Performance

Recent experiments show that the grain boundaries (GBs) of copper nanoparticles (NPs) lead to an outstanding performance in reducing CO 2 and CO to alcohol products. We report here multiscale simulations that simulate experimental synthesis conditions to predict the structure of a 10 nm Cu NP (158 555 atoms). To identify active sites, we first predict the CO binding at a large number of sites and select four exhibiting CO binding stronger than the (211) step surface. Then, we predict the formation energy of the *OCCOH intermediate as a descriptor for C–C coupling, identifying two active sites, both of which have an under-coordinated surface square site adjacent to a subsurface stacking fault. As a result, we then propose a periodic Cu surface (4 by 4 supercell) with a similar site that substantially decreases the formation energy of *OCCOH, by 0.14 eV.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Numerical classification of coding sequences

DNA sequences coding for protein may be represented by counts of nucleotides or codons. A complete reading frame may be abbreviated by its base count, e.g. A76C158G121T74, or with the corresponding codon table, e.g. (AAA)0(AAC)1(AAG)9 ... (TTT)0. We propose that these numerical designations be used to augment current methods of sequence annotation. Because base counts and codon tables do not require revision as knowledge of function evolves, they are well-suited to act as cross-references, for example to identify redundant GenBank entries. These descriptors may be compared, in place of DNA sequences, to extract homologous genes from large databases. This approach permits rapid searching with good selectivity.

Non-NASA Center↗
NASA NTRS2023

Progress in Predicting Ionic Cocrystal Formation: The Case of Ammonium Nitrate

In contrast to the mature predictive frameworks applied to neutral cocrystals, ionic cocrystals, those including an ion pair, are difficult to design. Furthermore, they are generally excluded categorically from studies which correlate specific molecular properties to cocrystal formation, leaving the prospective ionic cocrystal engineer with few clear avenues to success. Herein ammonium nitrate, an energetic oxidizing salt, is targeted for cocrystallization in a potential coformer group selected based on likely interactions with the nitrate ion as revealed in the Cambridge Structural Database; six novel ionic cocrystals were discovered. Molecular descriptors previously identified as being related to neutral cocrystal formation were examined across the screening group but showed no relationship with ionic cocrystal formation. High packing coefficient is shown to be a constant among the successful coformers in the set and is utilized to directly target two more successful coformers, bypassing the need for a large screening group.

Andrew J. Bennett↗
NASA NTRS1973

A semi-automated system for plotting and computer cataloging of remote sensing imagery

Description of a computer-assisted system for plotting and descriptor-cataloging of aerial imagery - an ingredient of the aerial image data handling system of the NASA Earth Resources Aircraft Project (ERAP). The system under consideration uses two graphic tablets linked interactively with a digital computer as input devices for deriving frame coordinates by correlating image points to map points. The various software programs and operating modes facilitate a semiautomatic plotting of an image by selecting two or more points within the image for matching with map details. The computer performs the scaling and orientation transformations for the calculation of the center and corner coordinates of the frame. Twenty five other descriptors for each frame are fed into a computerized data base requiring a minimum operator's time for verification and correction.

Gnauck, G. E.↗
DOE OSTI2018

Matrix Optical Absorption in UV-MALDI MS

In ultraviolet matrix-assisted laser desorption/ionization mass spectrometry (UV-MALDI MS) matrix compound optical absorption governs the uptake of laser energy, which in turn has a strong influence on experimental results. Despite this, quantitative absorption measurements are lacking for most matrix compounds. Furthermore, despite the use of UV-MALDI MS to detect a vast range of compounds, investigations into the effects of laser energy have been primarily restricted to single classes of analytes. We report the absolute solid state absorption spectra of the matrix compounds α-cyano-4-hydroxycinnamic acid (CHCA), para-nitroaniline (PNA), 2-mercaptobenzothiazole (MBT), 2,5-dihydroxybenzoic acid (2,5-DHB), and 2,4,6-trihydroxyacetophenone (THAP). The desorption/ionization characteristics of these matrix compounds with respect to laser fluence was investigated using mixed systems of matrix with either angiotensin II, PC(34:1) lipid standard, or haloperidol, acting as representatives for typical classes of analyte encountered in UV-MALDI MS. The first absolute solid phase spectra for PNA, MBT, and THAP are reported; additionally, inconsistencies between previously published spectra for CHCA are resolved. In light of these findings, suggestions are made for experimental optimization with regards to matrix and laser wavelength selection. The relationship between matrix optical cross-section and wavelength-dependant threshold fluence, fluence of maximum ion yield, and R, a new descriptor for the change in ion intensity with fluence, are described. A matrix cross-section of 1.3 × 10{sup –17} cm{sup –2} was identified as a potential minimum for desorption/ionization of analytes. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Understanding structure-processing relationships in metal additive manufacturing via featurization of microstructural images

Understanding and predicting accurate property-structure-processing relationships for additively manufactured components is important for both forward and inverse design of robust, reliable parts and assemblies. While direct mapping of process parameters to properties is sometimes plausible, it is often rendered difficult due to poor microstructural control. Exploring the direct relationship between processing conditions and microstructural features can thus provide significant physical insights and aid the overall design process. Here, in this study, we develop an automated high-throughput framework to simulate an uncertainty-aware additive manufacturing (AM) process, characterize microstructural images, and extract meaningful features/descriptors. A kinetic Monte Carlo (KMC) based model of the AM process is used to simulate microstructural evolution for a diverse set of experimentally relevant processing conditions. We perform a parametric study to explore the relationship between microstructural features and processing conditions. Our results indicate that a many-to-one mapping can exist between processing conditions and typical descriptors; therefore, multiple descriptors are thus necessary to unambiguously represent microstructural images. Our work provides crucial quantitative and qualitative in-formation that would aid in the selection of features for microstructural images. Featurized microstructures could then be utilized to build data-driven models for predictive control of microstructures and thereby properties of additively manufactured components.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Dehydrogenation Selectivity of Ethanol on Close-Packed Transition Metal Surfaces: A Computational Study of Monometallic, Pd/Au, and Rh/Au Catalysts

Ethanol (EtOH) decomposition has been widely studied in recent years. However, the initial dehydrogenation selectivity on catalytic surfaces, which plays a crucial role in EtOH partial oxidation and steam reforming, is not well understood. Here, density functional theory (DFT) was used to calculate the initial dehydrogenation selectivities of EtOH on monometallic and X/Au (X = Pd and Rh) close-packed surfaces. The energy for the initial bond scissions of O–H and α- and β-C–H were calculated on each surface. The binding energy of EtOH is found to be a good reactivity descriptor for the scission of O–H and β-C–H bonds, while the binding energy of CH 3 CHOH is a good reaction descriptor for α-C–H bond scission. The scaling relationships between the activation energy barriers and binding energies on Pd/Au and Rh/Au surface alloys are significantly different from those of monometallic surfaces. Additionally, the specific atomic ensembles on the Pd/Au and Rh/Au surfaces have different initial dehydrogenation selectivities of EtOH. Our calculated scaling relationships were used to construct contour plots that provide predictive trends for the selectivity of the initial EtOH dehydrogenation. We conclude that the presence of specific atomic ensembles on the surface of alloy catalysts can efficiently control the reaction products of EtOH dehydrogenation.

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

Mapping XANES spectra on structural descriptors of copper oxide clusters using supervised machine learning

Understanding the origins of enhanced reactivity of supported, subnanometer in size, metal oxide clusters is challenging due to the scarcity of methods capable to extract atomic-level information from the experimental data. Due to both the sensitivity of X-ray absorption near edge structure (XANES) spectroscopy to the local geometry around metal ions and reliability of theoretical spectroscopy codes for modeling XANES spectra, supervised machine learning approach has become a powerful tool for extracting structural information from the experimental spectra. Here, we present the application of this method to grazing incidence XANES spectra of size-selective Cu oxide clusters on flat support, measured in operando conditions of the methanation reaction. We demonstrate that the convolution neural network can be trained on theoretical spectra and utilized to “invert” experimental XANES data to obtain structural descriptors—the Cu–Cu coordination numbers. As a result, we were able to distinguish between different structural motifs (Cu 2 O-like and CuO-like) of Cu oxide clusters, transforming in reaction conditions, and reliably evaluate average cluster sizes, with important implications for the understanding of structure, composition, and function relationships in catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Decoupling plasma, catalyst, and gaseous mechanisms for non-oxidative methane conversion

Direct non-oxidative methane (CH 4 ) conversion to value-added hydrogen (H 2 ) and C 2 products remains hindered by fundamental catalytic scaling constraints and rapid surface deactivation at elevated temperatures. Plasma-enabled catalysis offers a promising route to overcome the thermodynamic and kinetic barriers of direct non-oxidative methane upgrading at mild conditions, yet control over C–C product selectivity and catalyst stability remains elusive. Here, we establish a unified mechanistic framework including Langmuir–Hinshelwood (L–H) and Langmuir–Rideal (L–R) mechanisms that disentangles the roles of plasma excitation (including vibrationally activated species and radicals), surface temperature (T sur ), and catalyst binding energy in steering CH 4 conversion to H 2 and C 2 hydrocarbons. Through a combination of density functional theory (DFT) informed microkinetic modeling, in situ and ex situ surface characterization, and product quantification under dielectric barrier discharge conditions, we show that vibrationally excited CH 4 lowers activation barriers selectively for dissociative chemisorption, enabling surface activation across a wide range of transition metal catalysts at low thermal energy input. We find that once CH 4 is dissociatively chemisorbed, the branching between C 2 H 2 , C 2 H 4 , and C 2 H 6 is governed by surface properties (carbon binding energy, T sur , etc), regardless of plasma excitation. The DFT informed microkinetic model decouples the effects of molecular activation from surface properties and indentifies operating windows that maximize target yields while suppressing carbon accumulation and subsequent catalytic inactivation. Experiments on polycrystalline Cu/Al 2 O 3 , Ni/Al 2 O 3 , and Pt/Al 2 O 3 validate these predictions, revealing catalyst-dependent branching toward ethane or ethylene and distinct deactivation profiles. We unify these trends into a generalized three-dimensional plasma-thermal-catalytic design space, from which reduced descriptors such as T vib /T sur in the limit of vibrationally excited L–H pathways emerge as predictive metrics. These results enable rational tuning of methane conversion pathways and unlock selective C 2 formation using earth-abundant metals under mild plasma conditions.

catalyst inactivation↗
DOE OSTI2021

Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks

Machine learning has emerged as a powerful approach in materials discovery. Its major challenge is selecting features that create interpretable representations of materials, useful across multiple prediction tasks. We introduce an end-to-end machine learning model that automatically generates descriptors that capture a complex representation of a material’s structure and chemistry. This approach builds on computational topology techniques (namely, persistent homology) and word embeddings from natural language processing. It automatically encapsulates geometric and chemical information directly from the material system. We demonstrate our approach on multiple nanoporous metal–organic framework datasets by predicting methane and carbon dioxide adsorption across different conditions. Our results show considerable improvement in both accuracy and transferability across targets compared to models constructed from the commonly-used, manually-curated features, consistently achieving an average 25–30% decrease in root-mean-squared-deviation and an average increase of 40–50% in R 2 scores. A key advantage of our approach is interpretability: Our model identifies the pores that correlate best to adsorption at different pressures, which contributes to understanding atomic-level structure–property relationships for materials design.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Elucidating Interfacial Phenomena between Solid-State Electrolytes and the Sulfur-Cathode of Lithium–Sulfur Batteries

Sulfide solid-state electrolytes are promising materials to be used in Li–S batteries because they have the potential to mitigate some of the challenges currently faced by this technology such as the dissolution of polysulfide species and the flammability of conventional organic-based electrolytes. Nevertheless, the electrode/electrolyte interfaces are not well-understood yet. In this study, we use density functional theory and ab initio molecular dynamics simulations to investigate the formation of the cathode–electrolyte interface at two limiting states of charge: S 8 and Li 2 S. β-Li 3 PS 4 and two lithium halide-doped sulfides (Li 6 PS 5 Cl and Li 7 P 2 S8I) were selected because of their Li-ion superionic conductivity and compatibility with sulfur electrodes. The work of adhesion and interfacial energy of the interfaces were calculated as descriptors of the interfacial properties, and then the mechanisms of the interfacial reactions taking place were characterized. Lastly, a charge transfer analysis is presented, suggesting that, overall, the S 8 electrode will oxidize the electrolyte, whereas the fully discharged Li 2 S cathode will reduce it at different extents depending on the reactivity of the exposed facet.

25 ENERGY STORAGE↗
DOE OSTI2018

One-pot catalytic conversion of biomass and alkanes: Kinetically coupling deoxygenation and dehydrogenation pathways

The stoichiometric hydrogen deficiency of carbohydrate feedstock implies that all conversion processes must remove oxygen and concurrently increase hydrogen content to form liquid hydrocarbon products. With support from the DOE Early Career program (DE-SC0008418) we have investigated the use of transition metal carbides for hydrodeoxygenation (HDO) chemistries using CH 4 and H 2 as co-reactants. We report that concurrently processing CH 4 and C 1 -C 3 oxygenates (oxygenate/CH 4 = 0.01-0.1) at 950 K on molybdenum carbide clusters encapsulated in zeolite micropores results in a staged bed with upstream CH 4 reforming and downstream CH 4 dehydroaromatization. Forward rates of CH 4 pyrolysis limited by CH 4 activation are unperturbed by the introduction of oxygenates with a (C/H) eff <0.25 after rigorously accounting for the thermodynamic reversibility caused by the H 2 produced in oxygenate reforming reactions and the fraction of the active catalyst bed deemed unavailable for CH 4 dehydroaromatization. A binomial distribution of 12 C/ 13 C isotopologues of CO is observed upon introduction of CH 3 13 COOH/CH 4 reactants suggesting that the introduction of oxygenates with a (C/H) eff <0.25 results in complete fragmentation of the oxygenate at these temperatures which in turn results in the invariance of forward rates of CH 4 pyrolysis when using CO 2 , HCOOH, or CH 3 COOH co-feeds. The stoichiometric loss of oxygen as CO when co-processing C 1 -C 3 oxygenates and CH 4 at these temperatures demonstrates that (C/H) eff =(C-O)/H is a single valued descriptor for oxygen removal on Mo/HZSM-5 catalysts. Separately, we have demonstrated the utility of transition metal carbides for vapor phase catalytic hydrodeoxygenation using molecular hydrogen with high selectivity for C-O cleavage and near absence of sequential hydrogenation reactions at atmospheric hydrogen pressure and illustrated that the faculty of transition metal carbides for selective hydrodeoxygenation arises due to oxygen-modification of the catalyst in situ. The oxophilic characteristics of these materials engender both the observed acid-metal catalytic bifunctionality and selectivity for hydrodeoxygenation. The evolution of catalyst surface composition and catalytic function under oxidative reaction environments proffers unique challenges in structural characterization of these materials and in this context, we developed and demonstrated the use of chemical titration and chemical transient studies to assess catalytic site identity and densities.

09 BIOMASS FUELS↗
DOE OSTI2022

High-throughput screening to predict highly active dual-atom catalysts for electrocatalytic reduction of nitrate to ammonia

Ammonia is an essential chemical owing to its importance in fertilizer production and other industrial applications. Electrocatalytic nitrate reduction to ammonia (NO 3 RR) holds great promise for low-temperature ammonia production while simultaneously addressing nitrate-based environmental concerns. To provide the mechanistic understanding needed to design an effective electrocatalyst, we systematically investigated the catalytic performance of metal-based dual-atom catalysts (DACs) anchored on two-dimensional (2D) expanded phthalocyanine (Pc) for NO 3 RR. We found that NO 3 RR can efficiently produce ammonia on Cr 2 -Pc, V 2 -Pc, Ti 2 -Pc, and Mn 2 -Pc surfaces with low limiting potentials of – 0.02, – 0.25, – 0.34, and – 0.41 V RHE , respectively. Moreover, using the free energy difference of *NO 3 - and *H as a descriptor, we found that the hydrogen evolution reaction is significantly suppressed on the DAC surface due to an ensemble effect in which the two metal atoms cooperate to selectively form ammonia. We performed high-throughput screening to develop an efficient metal-based DAC for NO 3 - reduction, followed by a mechanistic study to elucidate the NO3RR pathway on the DAC. Finally, this work provides design information for advancing sustainable ammonia synthesis under ambient conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A Unified Scaling Framework for Comparative Analysis of Major Electrical Machine Topologies

This paper presents a unified framework for comparing major electrical machine topologies under identical output and thermal constraints, with emphasis on supply-chain-aware selection among rare-earth-intensive, reduced-rare-earth, and rare-earth-free solutions. Using power factor and air-gap flux density as the principal descriptors, the framework links topology choice to relative size, copper demand, magnet dependence, cost sensitivity, and inertia. To support robust early-stage screening, the deterministic scaling model is combined with uncertainty representation, Monte Carlo scenario propagation, and hesitationaware ranking. The results show that rare-earth-rich machines remain compact and dense, whereas reduced-rare-earth and rare-earth-free alternatives become more attractive under specific material-risk and cost scenarios.

Kumar, Praveen [ORNL] (ORCID:0000000291877857)↗
NASA NTRS1979

Effect of noise spectra and a listening task upon passenger annoyance in a helicopter interior noise environment

The effects of helicopter interior noise on passenger annoyance were studied. Both reverie and listening situations were studied as well as the relative effectiveness of several descriptors (i.e., overall sound pressure level, A-weighted sound pressure level, and speech interference level) for quantifying annoyance response for these situations. The noise stimuli were based upon recordings of the interior noise of a civil helicopter research aircraft. These noises were presented at levels ranging from approximately 68 to 86 dB(A) with various gear clash tones selectively attenuated to give a range of spectra. Results indicated that annoyance during a listening condition is generally higher than annoyance during a reverie condition for corresponding interior noise environments. Attenuation of the planetary gear clash tone results in increases in listening performance but has negligible effect upon annoyance for a given noise level. The noise descriptor most effective for estimating annoyance response under conditions of reverie and listening situations is shown to be the A-weighted sound pressure level.

Clevenson, S. A.↗
DOE OSTI2026

Direct Observation of Hydroxyls Formed from Water and Oxygen on Ag(100)

The interaction of oxygen with silver is a key descriptor of the catalytic reactivity of silver nanoparticles which are ubiquitous in large-scale partial oxidation reactions like ethylene epoxidation. Despite Ag(100) being proposed as the most selective facet, it is less studied than (111) and (110) surfaces. Using scanning tunneling microscopy and synchrotron X-ray photoelectron spectroscopy, we report that, in addition to the well-known O adatoms formed from O 2 dissociation on Ag(100), hydroxyl groups (OH), at a binding energy of ∼ 531 eV, are also present. The O/OH ratio depends on exposure to water and surface temperature. These assignments are consistent with our density functional theory calculations, which indicate that the formation of two OH groups from an O atom and H 2 O molecule is exothermic. These results indicate that, in addition to O, OH is present even under ultrahigh vacuum conditions and therefore should be considered in proposed catalytic pathways.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Proton transfer kinetics of transition metal hydride complexes and implications for fuel-forming reactions

Proton transfer reactions involving transition metal hydride complexes are prevalent in a number of catalytic fuel-forming reactions, where the proton transfer kinetics to or from the metal center can have significant impacts on the efficiency, selectivity, and stability associated with the catalytic cycle. Here, this review correlates the often slow proton transfer rate constants of transition metal hydride complexes to their electronic and structural descriptors and provides perspective on how to exploit these parameters to control proton transfer kinetics to and from the metal center. A toolbox of techniques for experimental determination of proton transfer rate constants is discussed, and case studies where proton transfer rate constant determination informs fuel-forming reactions are highlighted. Opportunities for extending proton transfer kinetic measurements to additional systems are presented, and the importance of synergizing the thermodynamics and kinetics of proton transfer involving transition metal hydride complexes is emphasized.

08 HYDROGEN↗