Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cluster characterization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8

Light Exposure Promotes Degradation of Intermediates and Growth of Phosphine-Ligated Gold Clusters

Subnanometer clusters exhibit unique properties not observed at the bulk or nanometer scale. Many applications, however, require clusters to be monodisperse in size and composition.While substantial progress has been made empirically on producing specific-sized gold clusters using different ligands, the mechanisms of cluster formation remain insufficiently understood. Using high mass-resolution electrospray ionization mass spectrometry (ESI-MS), we characterized the formation of cationic triphenylphosphine-ligated gold clusters [Aux(PPh3)y z+] in solution. Our data provides evidence that small hydrogen-containing intermediate “building blocks” (i.e., Au2(PPh3)2H+, Au4(PPh3)4H+, and Au7(PPh3)7H5 2+) are responsible for the growth of larger gold clusters (i.e., Au6(PPh3)6 2+ and Au8(PPh3)7 2+) over several hours. In addition, intermediate degradation and cluster growth are shown to be dependent on irradiation of the reacting solution with light. Specifically, the rate of growth of large clusters is demonstrated to scale with the intensity of light exposure. Complementary theoretical calculations were also performed that provide molecular-level insight into the nature of the bonding between the hydrogens and gold atoms in the intermediate Au-phosphine clusters. Collectively, our joint experimental and theoretical findings advance the understanding of the factors at play in the size-selective synthesis of ligated gold clusters in solution.

Hewitt, Michael A.↗

Atom Efficiency of Pd Sites for Methane Combustion: Single Atom Catalysts Versus Nanocatalysts

Methane combustion is an important reaction for energy production and methane removal from the atmosphere. This reaction highly relies on the use of noble metal Pd-based catalysts, which therefore drives the pursuit of catalysts with high atomic dispersion and activity. In this work, Pd/ceria catalysts dominated with Pd single atoms or nanosized Pd clusters (∼1 nm) are prepared and characterized by combining high-resolution high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), in situ diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS), and Raman and X-ray absorption spectroscopy (XAS) techniques. By comparing the turnover frequencies (TOF; per every Pd atom) of Pd/ceria single atom catalysts and nanocatalysts, it is found that the atom efficiency of Pd is increased by 10 ∼30 times from single atom catalysts to nanocatalysts. For Pd single atom catalysts, although their activity can be tuned by changing the local structures, the intrinsic activity and number of active sites need to be further improved by engineering the surfaces of supports. For nanosized Pd species, despite the high TOF, the Pd atoms in the bulk structure are not directly participating in the catalytic reaction. Furthermore, this work highlights the importance of increasing the intrinsic activity of individual noble atoms, as well as the homogeneity of their local structures. For Pd/ceria systems reported in this work, our results indicate that from the application point of view, at the current stage, it is not practical to replace Pd nanocatalysts with single atom catalysts for methane combustion.

Pd↗

Tailoring Lewis/Brønsted acid properties of MOF nodes via hydrothermal and solvothermal synthesis: simple approach with exceptional catalytic implications

The Lewis/Brønsted catalytic properties of the Metal–Organic Framework (MOF) nodes can be tuned by simply controlling the solvent employed in the synthetic procedure. In this work, we demonstrate that Hf-MOF-808 can be prepared from a material with a higher amount of Brønsted acid sites, via modulated hydrothermal synthesis, to a material with a higher proportion of unsaturated Hf Lewis acid sites, via modulated solvothermal synthesis. The Lewis/Brønsted acid properties of the resultant metallic clusters have been studied by different characterization techniques, including XAS, FTIR and NMR spectroscopies, combined with a DFT study. The different nature of the Hf-MOF-808 materials allows their application as selective catalysts in different target reactions requiring Lewis, Brønsted or Lewis– Brønsted acid pairs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Distinguishing time clustering of astrophysical bursts

Many astrophysical bursts can recur, and their time series structure or pattern could be closely tied to the emission and system physics. While analysis of periodic events is well established, some sources, e.g., some fast radio bursts and soft gamma-ray emitters, are suspected of more subtle and less explored periodic windowed behavior: the bursts themselves are not periodic, but the activity only occurs during periodic windows. Here, we focus on distinguishing periodic windowed behavior from merely clustered events through time clustering analysis, using techniques analogous to spatial clustering, demonstrating methods for identifying and characterizing the behavior. An important aspect is accounting for the “curious incident of the dog in the night time”—lack of bursts carries information. As a worked example, we analyze six years of data from the soft gamma repeater SGR 1935 + 2154 , deriving a window period of 231 days and 55% duty cycle.

79 ASTRONOMY AND ASTROPHYSICS↗

Bounded-Confidence Models of Multidimensional Opinions with Topic-Weighted Discordance

People’s opinions on a wide range of topics often evolve over time through their interactions with others. Models of opinion dynamics primarily focus on one-dimensional opinions, which represent opinions on one topic. However, opinions on various topics are rarely isolated; instead, they can be interdependent and correlated. In a bounded-confidence model (BCM) of opinion dynamics, agents are receptive to each other only if their opinions are sufficiently similar. Here, we extend classical agent-based BCMs—namely, the Hegselmann–Krause BCM, which has synchronous interactions, and the Deffuant–Weisbuch BCM, which has asynchronous interactions—to a multidimensional setting, in which the opinions are multidimensional vectors representing opinions of different topics and opinions on different topics are interdependent. To measure opinion differences between agents, we introduce topic-weighted discordance functions that account for opinion differences in all topics. We define regions of receptiveness for our models, and we use them to characterize the steady-state opinion clusters and provide an analytical approach to compute these regions. In addition, we numerically simulate our models on various networks with initial opinions drawn from a variety of distributions. When initial opinions are correlated across different topics, our topic-weighted BCMs yield significantly different results in both transient and steady states compared to baseline models, where the dynamics of each opinion topic are independent.

Mathematics and Computing↗

Parallel measurement of transcriptomes and proteomes from same single cells using nanodroplet splitting

Single-cell multiomics provides comprehensive insights into gene regulatory networks, cellular diversity, and temporal dynamics. While tools for co-profiling single-cell genomes, transcriptomes, and epigenomes are available, accessing proteomes in parallel is more challenging. We developed nanoSPLITS (nanodroplet SPlitting for Linked-multimodal Investigations of Trace Samples), an integrated platform that enables global profiling of the transcriptome and proteome from same single cells using RNA sequencing and mass spectrometry-based proteomics, respectively. nanoSPLITS can precisely quantify over 5000 genes, 2000 proteins, and 140 phosphopeptides per single cell and identify candidate cell markers from these modalities. By exploring Cdk1-mediated cell cycle arrest, we demonstrate how nanoSPLITS single-cell multiomics can provide comprehensive cellular characterization with insights into covarying protein/gene clusters, unique phosphorylation events, and mitotic pathways.

59 BASIC BIOLOGICAL SCIENCES↗

Probing Active Sites in Cu x Pd y Cluster Catalysts by Machine-Learning-Assisted X-ray Absorption Spectroscopy

Size-selected clusters are important model catalysts because of their narrow size and compositional distributions, as well as enhanced activity and selectivity in many reactions. Still, their structure-activity relationships are, in general, elusive. The main reason is the difficulty in identifying and quantitatively characterizing the catalytic active site in the clusters when it is confined within subnanometric dimensions and under the continuous structural changes the clusters can undergo in reaction conditions. Using machine learning approaches for analysis of the operando X-ray absorption near-edge structure spectra, we obtained accurate speciation of the Cu x Pd y cluster types during the propane oxidation reaction and the structural information about each type. As a result, we elucidated the information about active species and relative roles of Cu and Pd in the clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Isolation and Structural Elucidation of 15–Nuclear Copper Dihydride Clusters: An Intermediate in the Formation of a Two–Electron Copper Superatom

Highly reactive copper-dihydride clusters, [Cu 15 (H) 2 (S 2 CNR 2 ) 6 (C 2 Ph) 6 ](PF 6 ) {R = n Bu (1 H ), n Pr (2 H ), i Bu (3 H )}, are isolated during the reaction of [Cu 28 H 15 {S 2 CN n Bu 2 } 12 ](PF 6 ) with ten equivalents of phenylacetylene. They are found to be intermediates in the formation of the earlier reported two-electron superatom [Cu 13 (S 2 CNR 2 ) 6 (C 2 Ph) 4 ] + . Better yields are obtained by reacting dithiocarbamate sodium salts, [Cu(CH 3 CN) 4 ](PF 6 ), BH 4 – and phenylacetylene. The presence of two hydrides in the isolated clusters is confirmed by the synthesis and characterization of its deuteride analogue [Cu 15 (D) 2 (S 2 CNR 2 ) 6 (C 2 Ph) 6 ] + , and a single-crystal neutron structure of 2 H . Structural characterization of 1 H reveals a new bicapped icosahedral copper(I) cage encapsulating a linear copper dihydride (CuH 2 ) – unit. In conclusion, reaction of 3 H with Au(I) salts yields a highly luminescent [AuCu 12 (S 2 CNiBu 2 ) 6 (C 2 Ph) 4 ] + cluster.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

The complex structural and chemical nature of monolithic U-10Mo fuel and Zr barrier layer

Nanoscale microstructural characterization by advanced transmission electron microscopy techniques on a U-10Mo/Zr barrier layer monolithic fuel plate was performed to evaluate the microstructural evaluation after high burn-up. Gas bubble superlattice evolution, grain restructuring, and evolution of the Zr interaction layer is investigated through detailed electron microscopy characterization. The use of automated crystallographic orientation mapping to irradiated U-10Mo fuel highlights that the restructured ultra-fine grains are separated by high angle grain boundaries at a burn up of 4.42 × 10 21 fissions/cm 3 . Additionally, advanced chemical analysis and multi-variable statistical analysis shows spatial clustering of solid fission product precipitates. Finally, characterization of a newly observed porous nanocrystalline Zr region in the barrier layer is studied. Finally, this work provides insights into the grain subdivision and restructuring process while using advanced microscopy techniques to analyze fission products in neutron-irradiated U-10Mo fuel.

36 MATERIALS SCIENCE↗

Formation of U(VI) peroxide nanoclusters from cascade reactions with a persulfate radical initiator

Radiolysis of water in high radiation fields generates a variety of reactive oxygen species that influence the chemical behavior and complexation of hexavalent uranium. This study investigates the behavior of interaction of a uranyl cation (UO 2 2+ (VI)) with a series of free radicals that are formed in situ via activation of the free radical initiator persulphate (S 2 O 8 2− ), which releases both SO 4 ˙ − and ˙OH species in the solution. Electron Paramagnetic Resonance (EPR) and Raman spectroscopy were used to evaluate the presence of the hydroperoxyl radical (HO 2 ˙) and superoxide radicals (O 2 ˙ − ) that are formed within the solution through radical cascade reactions. In addition, a uranyl peroxide cluster solid (NaU 24 ) was crystallized and characterized using single crystal X-ray diffraction (SCXRD), vibrational spectroscopy, and EPR spectroscopy. The presence of the hydroperoxyl radical (HO 2 ˙) and superoxide radicals (O 2 ˙ − ) was also observed in the solid-state compound, but spectroscopic evidence suggests that it was associated with the Na + network and not the cluster itself. Density functional theory (DFT) calculations were also utilized to further confirm the radical species produced and determine the potential stabilization of radicals detected within the cluster and lattice.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Deformation behavior of annealed Cu64Zr36 metallic glass via molecular dynamics simulations

In the present work, we investigate the isothermal annealing process of Cu 64 Zr 36 metallic glass (MG) by means of molecular dynamics (MD) simulations, and characterize the compression properties under different temperatures and compressive rates. The pair distribution functions, the bond-orientational order, and the cluster-type index method are modeled and analyzed to characterize changes in the structure. Results of the modeling and analysis reveal that the MgZn 2 -type Laves, MgCu 2 -type Laves and five-fold local symmetry structures can be formed during the isothermal holding at 950 K. Study on the compression properties shows that at a fixed strain rate, the yield strength and yield drop all increase with decreasing temperature. At a fixed temperature, however, the increase of the strain rate leads to a noticeable increase in the yield strength at 600 K, but has little effect on yield strength at 10 K. Moreover, the modeling and analysis of the structure at a temperature of 10 K and strain-rate of 5 × 10 7 s -1 demonstrate that the order-disorder transformation initiates the shear band.

36 MATERIALS SCIENCE↗

Gold–Thiolate Nanocluster Dynamics and Intercluster Reactions Enabled by a Machine Learned Interatomic Potential

Monolayer protected metal clusters comprise a rich class of molecular systems and are promising candidate materials for a variety of applications. While a growing number of protected nanoclusters have been synthesized and characterized in crystalline forms, their dynamical behavior in solution, including prenucleation cluster formation, is not well understood due to limitations both in characterization and first-principles modeling techniques. Recent advancements in machine-learned interatomic potentials are rapidly enabling the study of complex interactions such as dynamical behavior and reactivity on the nanoscale. Here, we develop an Au-S-C-H atomic cluster expansion (ACE) interatomic potential for efficient and accurate molecular dynamics simulations of thiolate-protected gold nanoclusters (Au n (SCH 3 ) m ). Trained on more than 30,000 density functional theory calculations of gold nanoclusters, the interatomic potential exhibits ab initio level accuracy in energies and forces and replicates nanocluster dynamics including thermal vibration and chiral inversion. Long dynamics simulations (up to 0.1 μs time scale) reveal a mechanism explaining the thermal instability of neutral Au 25 (SR) 18 clusters. Specifically, we observe multiple stages of isomerization of the Au 25 (SR) 18 cluster, including a chiral isomer. Additionally, we simulate coalescence of two Au 25 (SR) 18 clusters and observe series of clusters where the formation mechanisms are critically mediated by ligand exchange in the form of [Au-S] n rings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Architecture of Metabolism Maximizes Biosynthetic Diversity in the Largest Class of Fungi

Abstract Ecological diversity in fungi is largely defined by metabolic traits, including the ability to produce secondary or “specialized” metabolites (SMs) that mediate interactions with other organisms. Fungal SM pathways are frequently encoded in biosynthetic gene clusters (BGCs), which facilitate the identification and characterization of metabolic pathways. Variation in BGC composition reflects the diversity of their SM products. Recent studies have documented surprising diversity of BGC repertoires among isolates of the same fungal species, yet little is known about how this population-level variation is inherited across macroevolutionary timescales. Here, we applied a novel linkage-based algorithm to reveal previously unexplored dimensions of diversity in BGC composition, distribution, and repertoire across 101 species of Dothideomycetes, which are considered the most phylogenetically diverse class of fungi and known to produce many SMs. We predicted both complementary and overlapping sets of clustered genes compared with existing methods and identified novel gene pairs that associate with known secondary metabolite genes. We found that variation among sets of BGCs in individual genomes is due to nonoverlapping BGC combinations and that several BGCs have biased ecological distributions, consistent with niche-specific selection. We observed that total BGC diversity scales linearly with increasing repertoire size, suggesting that secondary metabolites have little structural redundancy in individual fungi. We project that there is substantial unsampled BGC diversity across specific families of Dothideomycetes, which will provide a roadmap for future sampling efforts. Our approach and findings lend new insight into how BGC diversity is generated and maintained across an entire fungal taxonomic class.

59 BASIC BIOLOGICAL SCIENCES↗

An atomic cluster expansion potential for twisted multilayer graphene

Twisted multilayer graphene, characterized by its moiré patterns arising from inter-layer rotational misalignment, serves as a rich platform for exploring quantum phenomena. Machine learning interatomic potentials (MLIPs) are a promising approach to model such systems. Our work develops a method to generate training and test datasets for fitting MLIPs that capture all possible misalignments but remain small-scale to facilitate efficient data generation and parameter estimation. To achieve this, we generate configurations with periodic boundary conditions suitable for density functional theory calculations, and then introduce an internal twist and shift within those supercell structures. Using this technique, supplemented with an active learning workflow, we fit an Atomic Cluster Expansion potential for simulating twisted multilayer graphene and test it for accuracy and robustness on a range of simulation tasks.

2D materials↗

A cluster of results on amplituhedron tiles

Abstract The amplituhedron is a mathematical object which was introduced to provide a geometric origin of scattering amplitudes in $$\mathcal {N}=4$$ N = 4 super Yang–Mills theory. It generalizes cyclic polytopes and the positive Grassmannian and has a very rich combinatorics with connections to cluster algebras. In this article, we provide a series of results about tiles and tilings of the $$m=4$$ m = 4 amplituhedron. Firstly, we provide a full characterization of facets of BCFW tiles in terms of cluster variables for $$\text{ Gr}_{4,n}$$ Gr 4 , n . Secondly, we exhibit a tiling of the $$m=4$$ m = 4 amplituhedron which involves a tile which does not come from the BCFW recurrence—the spurion tile, which also satisfies all cluster properties. Finally, strengthening the connection with cluster algebras, we show that each standard BCFW tile is the positive part of a cluster variety, which allows us to compute the canonical form of each such tile explicitly in terms of cluster variables for $$\text{ Gr}_{4,n}$$ Gr 4 , n . This paper is a companion to our previous paper “Cluster algebras and tilings for the $$m=4$$ m = 4 amplituhedron.”

Physics↗

Clustering Acoustic Background Noise in the Stratosphere Using Machine Learning

Infrasound, characterized by low-frequency sound inaudible to humans (<20 Hz), emanates from natural and anthropogenic sources. Its efficacy for monitoring phenomena necessitates robust sensing networks. Traditional ground-based infrasound sensors have limitations due to atmospheric dynamics and noise interference. Balloon-bore sensors have emerged as an alternative, offering reduced noise and improved capabilities. This study bridges clustering algorithms with balloon borne infrasound data, a domain yet to be explored. Employing K-Means, DBSCAN, and GMM algorithms on normalized and reshaped data and only normalized data from a New Zealand-based NASA balloon flight, insights into background noise at stratospheric altitudes were revealed. Despite challenges arising from distinguishing signals amid unique background noise, this research provides vital reference material for noise analysis and calibration. Beyond infrasound event capture, the dataset enriches comprehension of background noise characteristics in the southern hemisphere.

47 OTHER INSTRUMENTATION↗

Comprehensive Genetic Characterization of Four Novel HIV-1 Circulating Recombinant Forms (CRF129_56G, CRF130_A1B, CRF131_A1B, and CRF138_cpx): Insights from Molecular Epidemiology in Cyprus

Molecular investigations of the HIV-1 pol region (2253–5250 in the HXB2 genome) were conducted on sequences obtained from 331 individuals infected with HIV-1 in Cyprus between 2017 and 2021. This study unveiled four distinct HIV-1 putative transmission clusters, encompassing 19 previously unidentified HIV-1 recombinants. These recombinants, each comprising eight, three, four, and four sequences, respectively, did not align with previously established Circulating Recombinant Forms (CRFs). To characterize these novel HIV-1 recombinants, near-full-length genome sequences were successfully obtained for 16 of the 19 recombinants (790–8795 in the HXB2 genome) using an in-house-developed RT-PCR assay. Phylogenetic analyses, employing MEGAX and Cluster-Picker, along with confirmatory neighbor-joining tree analyses of subregions, were conducted to identify distinct clusters and determine subtypes. The uniqueness of the HIV-1 recombinants was evident in their exclusive clustering within generated maximum likelihood trees. Recombination analyses highlighted the distinct chimeric nature of these recombinants, with consistent mosaic patterns observed across all sequences within each of the four putative transmission clusters. Conclusive genetic characterization identified four novel HIV-1 CRFs: CRF129_56G, CRF130_A1B, CRF131_A1B, and CRF138_cpx. CRF129_56G exhibited two recombination breakpoints and three fragments of subtypes CRF56_cpx and G. Both CRF130_A1B and CRF131_A1B featured seven recombination breakpoints and eight fragments of subtypes A1 and B. CRF138_cpx displayed five recombination breakpoints and six fragments of subtypes CRF22_01A1 and F2, along with an unclassified fragment. Additional BLAST analyses identified a Unique Recombinant Form (URF) of CRF138_cpx with three additional recombination sites, involving subtype F2, a fragment of unknown subtype origin, and CRF138_cpx. Post-identification, all putative transmission clusters remained active, with CRF130_A1B, CRF131_A1B, and CRF138_cpx clusters exhibiting further growth. Furthermore, international connections were identified through BLAST analyses, linking one sequence from the USA to the CRF130_A1B strain, and three sequences from Belgium and Cameroon to the CRF138_cpx strain. This study contributes valuable insights into the dynamic landscape of HIV-1 diversity and transmission patterns, emphasizing the need for ongoing molecular surveillance and global collaboration in tracking emerging viral variants.

60 APPLIED LIFE SCIENCES↗

Deletion analysis of the itaconic acid biosynthesis gene cluster components in Aspergillus pseudoterreus ATCC32359

The filamentous fungus Aspergillus terreus has been successfully used for industrial production of itaconic acid (IA) for many years. The IA biosynthesis pathway has recently been characterized at a molecular genetic level as an IA gene cluster (IA cluster) by a clone-based transcriptomic approach. The cluster consists of four genes, including genes for cis-aconitic acid decarboxylase (cadA), a predicted transcription factor (tf), mitochondrial organic acid transporter (mttA), and MFS (Major Facilitator Superfamily) type transporter (mfsA). In this research, we performed EST (Expressed Sequence Tag) analysis and systematic gene deletions to investigate the role of those genes in IA biosynthesis in A. pseudoterreus ATCC32359. EST analysis showed a similar expression pattern among those four genes that was distinct from neighbouring genes and further confirmed that they belong to the same biosynthesis cluster. Systematic gene deletion analysis demonstrated that tf, cadA, mttA, and mfsA genes in the cluster are essential for IA production. Deletion of any of them will either completely abolish the IA production or dramatically decrease amount of IA produced. More importantly, a significant amount of aconitic acid was detected in the cadA deletion strain but not in the other deletion strains. Therefore, the cadA deletion strain is a novel microorganism host for production of aconitic acid and other value-added chemicals from lignocellulosic biomass.

Deng, Shuang↗