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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Identification of $^{3}$He–$^{3}$H clusters in the $^{6}$Li+$^{89}$Y experiment using particle-$\gamma$ coincidence measurement

The 6 Li+ 89 Y experiment was performed to explore the reaction mechanism induced by a weakly bound nucleus 6 Li and its cluster configuration. Here, the particle-$\gamma$ coincidence method was used to identify the different reaction channels. The $\gamma$-rays coincident with 3 He/ 3 H indicate that the 3 H/ 3 He stripping reaction plays a significant role in the formation of Zr/Nb isotopes. The obtained results support the existence of a 3 He- 3 H cluster in 6 Li. Direct and sequential transfer reactions are adequately discussed, and the FRESCO code is used to perform precise finite-range cyclic redundancy check calculations. In the microscopic calculation, direct cluster transfer is more predominant than sequential transfer in 3 H transfer. However, the direct cluster transfer is of comparable magnitude to the sequential transfer in the 3 He transfer.

CRC calculations↗
DOE OSTI2021

A systematic analysis of phase stability in refractory high entropy alloys utilizing linear and non-linear cluster expansion models

We report that obtaining surrogate models for various types of materials has long been a goal of computational material scientists and physicists, as they allow the calculation of thermodynamic quantities and properties of interest far more efficiently than DFT. Many surrogate models, including interatomic potentials generated by machine learning algorthims and cluster expansions, rely on incorporating many-body interactions such as three-body or four-body interactions. When utilizing machine learning algorithms for interatomic potentials, it is common to start with two-body interactions and systematically include three- and four-body clusters to improve the fit, stopping when including the additional clusters does not measurably change the predictive power of the model. In cluster expansions for FCC and related lattices, it is often enough to include mostly two-body interactions and a handful of three-body interactions. However, it remains to be seen whether those will be enough in the case of lattices with a lower packing fraction, such as BCC.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Network of networks: Time series clustering of AmeriFlux sites

Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15–70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under-sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A generalized and adaptable tensor-contraction-based cluster expansion formalism for multicomponent solids

Density functional theory (DFT)-based simulations of materials have first-principles accuracy, but are very computationally expensive. For simulating various properties of multi-component alloys, the cluster expansion (CE) technique has served as the standard workaround to improve computational efficiency. However, the standard CE technique is difficult to extend to exotic and/or low-symmetry lattices, often implemented via iteration over particular cluster types, which must be enumerated per lattice structure. In this work, we introduce the tensor cluster expansion (TCE), implemented in the open-source code tce-lib, which maps correlation functions to mixed tensor contractions, eliminating the need to iterate over cluster types and additionally making the calculation of correlation functions well-suited for massively parallel architectures like GPUs. We show that local interaction energies are an immediate consequence of the TCE formalism, yielding nearly $\mathcal{O}$(1) energy difference calculations. We then use this formalism to fit CE models for the TaW and CoNiCrFeMn systems, and use these models to respectively compute the enthalpy of mixing curve and Cowley short-range order parameters, showing excellent agreement with ground truth data.

Cluster expansion↗
DOE OSTI2021

Cluster analysis of occupancy schedules in residential buildings in the United States

The energy performance of residential buildings significantly depends on the building occupants’ behavior, which can be highly variable. When the heating, ventilation and air conditioning (HVAC) system is controlled based on the presence or absence of occupants in a building, occupant behavior is of even further importance to its energy performance. In current practice, building energy simulation tools generally use a single occupancy profile to represent the building’s occupancy schedule, the schedule of which is considered to be the same, regardless of the type of household being modeled. Thus, there is significant potential for improvement to allow for more flexibility and accuracy in calculation of occupancy. The objective of this study is to assess the variations in the typical types of occupancy schedules followed by the U.S. population using cluster analysis. American Time Use Survey data, which statically represents the overall U.S. population’s activities, across 12 years (2006–2017), is used. The ATUS data is segregated into smaller groups based on age and weekday/weekend, then divided into activities that are considered “at home” and “away from home”, which are mapped to the presence or non-presence of occupants in the home. Cluster analysis is then used to identify common types of occupancy schedule patterns for each age group. Three main types of patterns are obtained from cluster analysis for each age group, which together represent approximately 88% of people in the United States. The output of the cluster analysis is further analyzed to evaluate the variation in characteristics, including the number of times leaving home, time of day when leaving the home, and the timespan of absence from the home. The results of this study provide detailed insights on how typical occupants in the United States spend their time in residential spaces which can be used to create occupancy profiles for residential buildings. Finally, these occupancy profiles could be utilized inform an assessment of the energy use impact of occupancy-based controls of energy consuming systems and technologies.

42 ENGINEERING↗
DOE OSTI2025

Differential Ligation Alters Electronic State and Coupling Signals of Iron-Sulfur Clusters in Flavin-Based Electron Bifurcation

Flavin-based electron bifurcation (FBEB) is employed by microorganisms for controlling pools of redox equivalents by reversibly splitting electron pairs into high- and low-energy levels from an initial midpoint potential. Our ability to harness this phenomenon is crucial for biocatalytic design which is limited by our understanding of energy coupling in the bifurcation system. In Pyrococcus furiosus, FBEB is carried out by the NADH-dependent ferredoxin:NADP+-oxidoreductase (NfnSL), coupling the uphill reduction of ferredoxin in NfnL to the downhill reduction of NAD+ in NfnS from oxidation of NADPH. Flanking the bifurcating flavin are two site-differentiated iron-sulfur clusters; the nearest is a glutamate-ligated [4Fe-4S] cluster in NfnL. Recent biochemical experiments substituting the native glutamate with cysteine led to loss of coupling between the uphill and downhill pathways, in contrast to the tight thermodynamic coupling in the native system. To understand how this decoupling is biochemically manifested by the cysteine-substituted [4Fe-4S] in NfnL, we employed electron paramagnetic resonance (EPR) spectroscopy to identify changes in electronic architecture and square wave voltammetry (SWV) to probe thermodynamic shifts produced by the substitution. We observed notable g-value shifts in the EPR for the cysteine-substituted iron-sulfur cluster in addition to significant downward shifts in the redox potential, as well as the disappearance of several low-field signals observed in the native NfnSL complex. These results suggest the site-differentiated glutamate residue facilitates higher spin states in the [4Fesingle bond4S] cluster to bridge energetic gaps in electron transfer to the bifurcating flavin in the native complex, preventing unwanted short-circuiting seen in the cysteine-substituted complex.

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

Interpreting experimental measurements of helium bubbles using stochastic cluster dynamics models of heterogeneous nucleation and growth in irradiated ferritic alloys

Among a number of other advantageous features, ferritic/martensitic steels are being considered as fusion reactor structural materials due to their low intrinsic swelling under irradiation. However, under high-energy neutron irradiation, He produced through (n, α) reactions stabilizes vacancy clusters, which then act as seeds for bubble formation and growth, negating the intrinsic swelling resistance of these alloys. Standard models of irradiation damage accumulation and microstructural evolution consider homogeneous nucleation as the basis for bubble formation and growth. However, this generally does not explain the large bubble densities and sizes observed experimentally under a number of different conditions. Here, we propose a more realistic physical model of bubble nucleation, formation, and growth designed to capture recent experimental measurements of He-bubble formation and evolution during co-implantation of He and Fe ions in model ferritic alloys. We find that experimental results are explained only when the following three features are considered simultaneously: (i) heterogeneous nucleation of He-vacancy bubbles at defect sinks (e.g., dislocations, grain boundaries, and second-phase precipitates), (ii) nucleation and growth of bubbles via the ‘trap mutation’ mechanism (i.e., spontaneous production of Frenkel pairs due to absorption of He atoms), and (iii) transition from a growth-limited, He-stabilized bubble regime to a ‘runaway’ void-type growth scenario. The model is implemented into a stochastic cluster dynamics framework that takes advantage of cluster size grouping methods to accelerate the simulations, allowing us to reach 10 dpa of simulated irradiated dose, and to capture cluster sizes in excess of 20 nm. Further, a careful extrapolation exercise conducted assuming classical nucleation theory leads to excellent agreement with the experimental measurements at 50 dpa of irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Gaussian mixture model clustering algorithms for the analysis of high-precision mass measurements

The development of the phase-imaging ion-cyclotron resonance (PI-ICR) technique for use in Penning trap mass spectrometry (PTMS) increased the speed and precision with which PTMS experiments can be carried out. In PI-ICR, data sets of the locations of individual ion hits on a detector are created showing how ions cluster together into spots according to their cyclotron frequency. Ideal data sets would consist of a single, 2D-spherical spot with no other noise, but in practice data sets typically contain multiple spots, non-spherical spots, or significant noise, all of which can make determining the locations of spot centers non-trivial. A method for assigning groups of ions to their respective spots and determining the spot centers is therefore essential for further improving precision and confidence in PI-ICR experiments. Here, we present the class of Gaussian mixture model (GMM) clustering algorithms as an optimal solution. We show that on simulated PI-ICR data, several types of GMM clustering algorithms perform better than other clustering algorithms over a variety of typical scenarios encountered in PI-ICR. The mass spectra of 163Gd, 163 mGd, 162 Tb, and 162 mTb measured using PI-ICR at the Canadian Penning trap mass spectrometer were checked using GMMs, producing results that were in close agreement with the previously published values.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Study of cluster ions produced from ToF-SIMS analysis of a U-6%Nb target

Cluster ions have been previously observed during time-of-flight secondary ion mass spectrometry (ToF-SIMS) analysis of metals and metal oxides. Furthermore, we have used ToF-SIMS to investigate cluster ions formed from the hydrocarbon-containing overlayer, the mixed U and Nb surface oxide, and underlying metal of a U-6 %Nb (U6Nb) target. In the overlayer, we observe U x O y + oxides and U-species likely containing hydrocarbons. In the surface oxide, we observe UO 2 +, U 2 O 2 +, U 3 O 5 +, and U 4 O 6 + as the most intense ions for each family of oxide ions containing x U atoms. Nb oxides for NbO 1-2 - were only observed in negative polarity. In contrast to the oxide, analysis of the underlying U6Nb alloy resulted in repeating units of U n +, U n (Nb)+, and U n (Nb 2 ) + ions for n = 3–11 as the highest intensity ions for each family of ions containing n U atoms. Nb n + clusters were not observed. U n +, U n (Nb)+, and U n (Nb 2 )+ clusters containing C- and O-species were observed and were likely produced from soluble C or O species or precipitates known to be present in U6Nb.

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

Solid solutions limited by grain-boundary solute clustering in ultrafine-grained alloys

Immiscible Ag-Cu alloys exhibit complex behavior due to varying Cu solid solubilities reported under equilibrium and metastable conditions. In ultrafine-grained alloys, these limits are further complicated by a high fraction of grain boundaries, where solute atoms tend to segregate and, in some cases, form clusters. Here, this study investigates the influence of Cu solute segregation and clustering on solid-solution limits in ultrafine-grained Ag-Cu alloys synthesized by magnetron sputtering with varying Cu content. X-ray diffraction peak shifts reveal a solid-solution concentration plateau for Cu contents from 4.9 to 11.7 at %, in contrast to the peak shifts predicted by density-functional theory for Ag-Cu alloys. Scanning transmission electron microscopy further reveals limited solid solubility and the formation of numerous Cu-rich clusters at grain boundaries. Atomistic simulations demonstrate that such limited solubility does not arise from grain boundary segregation alone, but only when strong solute-solute interactions promote the formation of grain-boundary Cu solute clusters.

Density-functional theory↗
DOE OSTI2023

Small bimetallic clusters Agn-1M (M = Au, Co, Cu, Ni, Pd, Pt; n = 3, 9, 15): Density functional theory and genetic algorithm

We investigated the effect of size and composition on the properties of bimetallic nanoclusters. The geometric structures, stabilities, and electronic properties of size-selected Ag n-1 M (M = Au, Co, Cu, Ni, Pd, Pt; n = 3, 9, 15) bimetallic nanoclusters are systematically analyzed using spin-polarized density functional theory (DFT) within the generalized gradient approximation (GGA). We determine the most stable geometries for these clusters using a genetic algorithm (GA) in combination with DFT. Our results show that doping pure silver clusters with an M atom (transition metal), referred to as a “guest atom”, increases the stability as compared to pure Ag n (n = 3, 9, 15) clusters. The results for various properties including formation energy per atom, electronic structure, magnetic moments, and vibrational density of states (VDOS) are evaluated as a function of both size and composition of the system. The adsorption of selected bimetallic clusters on hydroxylated alumina substrate shows weak binding and minor changes in geometric properties except for Ag 8 Pt.

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

DONKEY: A Flexible and Accurate Algorithm for Clustering

We propose an accurate clustering algorithm suitable for the varied and multidimensional data sets that correspond to temporal snapshots from on-the-fly nonadiabatic trajectory-based simulations of photoexcited dynamics. The algorithm approximates the underlying probability density function using variable kernel density estimation, with local maxima corresponding to cluster centers. Each data point is then assigned to one of the maxima by employing a maximization procedure. Finally, clusters artificially separated by minor fluctuations in the probability density are merged. The algorithm does not require parameter tuning, which ensures flexibility and reduces the risk of bias. It is tested on several synthetic data sets, where it consistently outperforms conventional clustering algorithms. As a final example, the algorithm is applied to the excited dynamics of the norbornadiene ⇌ quadricyclane (C 7 H 8 ) molecular photoswitch, demonstrating how distinct reaction pathways can be identified.

algorithms↗
DOE OSTI2024

Competition between Water–Water Hydrogen Bonds and Water–π Bonds in Pyrene–Water Cluster Anions

We present infrared spectra and density functional theory calculations of hydrated pyrene anion clusters with up to four water molecules. The experimental spectra were acquired using infrared Ar messenger photodissociation spectroscopy. Water molecules form clusters on the surface of the pyrene, forming hydrogen bonds with the pi-system. The structures of the water clusters and their interaction with the π-system are encoded in the OH stretching vibrational modes. Here, we find that the interactions between water molecules are stronger than they are between water molecules and the π-system. While all clusters show multiple conformers, three- and four-membered rings are the lowest energy structures in the larger hydrates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Influence of Domain Size and Support Composition on the Reducibility of SiO 2 and TiO 2 Supported Tungsten Oxide Clusters

Supported tungsten oxides are widely used in a variety of catalytic reactions. Depending on the support, the cluster size, oxidation state, reducibility and speciation of the tungsten oxides can widely differ. When promoted with a platinum group metal, the resulting spillover of hydrogen may facilitate the reduction of supported tungsten oxide species, depending on the support. High resolution scanning transmission electron microscopy imaging showed nanometer scale WO x clusters were synthesized on SiO 2 whereas highly dispersed species were formed on TiO 2 . Results from H 2 -temperature-programmed reduction showed the presence of Pd lowered the initial reduction temperature of SiO 2 -supported WO x species but interestingly did not affect that of TiO 2 -supported WO x . X-ray photoelectron and absorption spectroscopies showed the W atoms in SiO 2 -supported WO x species reduce from a +6 oxidation state to primarily +5 after thermal treatment in 5% H 2 , while the fraction of W in the +5 oxidation state was relatively unaffected by reduction treatment of TiO 2 -supported WO x . The unusual behavior of TiO 2 -supported WO x was explained by quantum chemical calculations that reveal the lack of change in the oxidation state of W is attributed to charge delocalization on the surface atoms of the titania support, which does not occur on silica. Moreover, modeling results at <600 K in the presence of H 2 suggest the formation of Brønsted acid sites, and the absence of Lewis acid sites, on larger aggregates of WO x on silica and all cluster sizes on titania. These results provide experimental and theoretical insights into the nature of supported tungsten oxide clusters under conditions relevant to various catalytic reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

High-Pressure and Temperature Effects on the Clustering Ability of Monohydroxy Alcohols

This study examined the clustering behavior of monohydroxy alcohols, where hydrogen-bonded clusters of up to a hundred molecules on the nanoscale can form. By performing X-ray diffraction experiments at different temperatures and under high pressure, we investigated how these conditions affect the ability of alcohols to form clusters. The pioneering high-pressure experiment performed on liquid alcohols contributes to the emerging knowledge in this field. Implementation of molecular dynamics simulations yielded excellent agreement with the experimental results, enabling the analysis of theoretical models. Here we show that at the same global density achieved either by alteration of pressure or temperature, the local aggregation of molecules at the nanoscale may significantly differ. Surprisingly, high pressure not only promotes the formation of hydrogen-bonded clusters but also induces the serious reorganization of molecules. This research represents a milestone in understanding association under extreme thermodynamic conditions in other hydrogen bonding systems such as water.

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

CO 2 Methanation on Cu-Cluster Decorated Zirconia Supports with Different Morphology: A Combined Experimental In Situ GIXANES/GISAXS, Ex Situ XPS and Theoretical DFT Study

We report that subnanometer copper tetramer-zirconia catalysts turn out to be highly efficient for CO 2 hydrogenation and its conversion to methane. The cluster size and substrate morphology are controlled to optimize the catalytic performance. The two types of zirconia supports investigated are prepared by atomic layer deposition (~ 3 nm thick film) and supersonic cluster beam deposition (nanostructured film, ~ 100 nm thick). The substrate plays a crucial role in determining the activity of the catalyst as well as its cyclability over repeated thermal ramps. A temperature-programmed reaction combined with in situ X-ray characterization reveals the correlation between the evolution in the oxidation state and catalytic activity. Ex situ photoelectron spectroscopy indicates Cu clusters with stronger interactions with the nanostructured film, which can be the cause for the higher activity of this catalyst. Density functional theory calculations based on the Cu 4 O 2 cluster supported on a ZrOx subunit reveal low activation barriers and provide mechanism for CO 2 hydrogenation and its conversion to methane. Altogether, the results show a new way to tune the catalytic activity of CO 2 hydrogenation catalysts through controlling the morphology of the support at the nanoscale.

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

Evidence for Low-Valent Electronic Configurations in Iron–Sulfur Clusters

Although biological iron-sulfur (Fe–S) clusters perform some of the most difficult redox reactions in Nature, they are thought to be composed exclusively of Fe 2+ and Fe 3+ ions, as well as mixed-valent pairs with average oxidation states of Fe 2.5+ . We herein show that Fe–S clusters formally composed of these valences can access a wider range of electronic configurations—in particular, those featuring low-valent Fe 1+ centers. We demonstrate that CO binding to a synthetic [Fe 4 S 4 ] o cluster supported by N-heterocyclic carbene ligands induces generation of Fe 1+ centers via intracluster electron transfer, wherein a neighboring pair of Fe 2+ sites reduces the CO-bound site to a low-valent Fe 1+ state. Similarly, CO binding to an [Fe 4 S 4 ] + cluster induces electron delocalization with a neighboring Fe site to form a mixed-valent Fe 1.5+ Fe 2.5+ pair in which the CO-bound site adopts partial low-valent character. Furthermore, these low-valent configurations engender remarkable C–O bond activation without having to traverse highly negative and physiologically inaccessible [Fe 4 S 4 ] o /[Fe 4 S 4 ] – redox couples.

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

Directly imaging the cooling flow in the Phoenix cluster

In the centres of many galaxy clusters, the hot (approximately 10 7 kelvin) intracluster medium can become dense enough that it should cool on short timescales. However, the low measured star formation rates in massive central galaxies and the absence of soft X-ray lines from the cooling gas suggest that most of this gas never cools. This is known as the cooling flow problem. The latest observations suggest that black hole jets are maintaining the vast majority of gas at high temperatures. A cooling flow has yet to be fully mapped through all the gas phases in any galaxy cluster. Here we present observations of the Phoenix cluster using the James Webb Space Telescope to map the [Ne vi] λ 7.652-μm emission line, enabling us to probe the gas at 10 5.5 kelvin on large scales. These data show extended [Ne vi] emission that is cospatial with the cooling peak in the intracluster medium, the coolest gas phases and the sites of active star formation. Taken together, these imply a recent episode of rapid cooling, causing a short-lived spike in the cooling rate, which we estimate to be 5,000–23,000 solar masses per year. As a result, these data provide a large-scale map of gas at temperatures between 10 5 kelvin and 10 6 kelvin in a cluster core, and highlight the critical role that black hole feedback has in not only regulating cooling but also promoting it.

79 ASTRONOMY AND ASTROPHYSICS↗