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DOE OSTI2022

Red Dragon: a redshift-evolving Gaussian mixture model for galaxies

ABSTRACT Precision-era optical cluster cosmology calls for a precise definition of the red sequence (RS), consistent across redshift. To this end, we present the Red Dragon algorithm: an error-corrected multivariate Gaussian mixture model (GMM). Simultaneous use of multiple colours and smooth evolution of GMM parameters result in a continuous RS and blue cloud (BC) characterization across redshift, avoiding the discontinuities of red fraction inherent in swapping RS selection colours. Based on a mid-redshift spectroscopic sample of SDSS galaxies, an RS defined by Red Dragon selects quiescent galaxies (low specific star formation rate) with a balanced accuracy of over $90{{\ \rm per\ cent}}$. This approach to galaxy population assignment gives more natural separations between RS and BC galaxies than hard cuts in colour–magnitude or colour–colour spaces. The Red Dragon algorithm is publicly available at bitbucket.org/wkblack/red-dragon-gamma/.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Siderophores and secondary metabolites produced by Ganoderma adspersum

Ganoderma adspersum is a white-rot wood-degrading basidiomycete of ecological, biotechnological and medicinal interest. In addition to its role in lignin degradation, it produces bioactive metabolites with reported antimicrobial and antioxidant activities. However, the mechanisms of iron acquisition, including siderophore-mediated pathways, remain poorly characterized in Ganoderma species. Improved understanding of these systems is essential to elucidate their contributions to fungal physiology, secondary metabolism and ecological adaptation. In this study, the genome of G. adspersum was sequenced for the first time and screened for genes that may be involved in the production of secondary metabolites. A gene cluster was identified as potentially involved in iron uptake. In particular, genes related to non-ribosomal peptide synthetases were detected next to a gene encoding a monooxygenase and indicated a potential hydroxamate-family siderophore. Liquid chromatography (LC)-ES-MS analysis of secondary metabolites secreted by G. adspersum into the growth medium under iron-limiting conditions revealed a group of previously undescribed siderophores. Genome and MS/MS analysis suggested that these structures might be related to the coprinoferrin family of siderophores. Aside from siderophores, the genome and LC-MS analysis revealed G. adspersum to be a prolific producer of a variety of triterpenoids and sesquiterpenoids, in agreement with previous findings. This is the first description of the genome sequence of G. adspersum and its siderophores.

Reyes, Carolina [Laboratory for Cellulose and Wood↗

DOE OSTI2025

Using Apptainer in a Pilot-based Distributed Workload

GlideinWMS is a pilot and pressure-based workload manager for distributed scientific computing. Many experiments like CMS and Fermilab’s Neutrino experiments use it to provision elastic clusters for their analysis and simulations, split into close to a million concurrent jobs. Most user jobs require containers, and the pilots use Apptainer to set up the desired platform. For the pilots that run as regular batch jobs, Apptainer is safer, lighter, and easier to use than other containerization solutions. Many images used by the pilots are expanded SIF images distributed via the CernVM-FS: this combination is very efficient. At Fermilab, for example, we store on GitHub Dockerfiles that mimic the platform in the worker nodes of local clusters. GitHub workflows build and push the images to Docker Hub, and a service periodically pulls and converts them to the expanded SIF images in the CernVM-FS, so the scientists can find a familiar environment everywhere. Apptainer has also been used to run services inside the pilot jobs, like benchmarks that characterize the worker node being used, or a Triton Inference Server that allows sharing a GPU with all the jobs that run in parallel on a node.

Mambelli, Marco [Fermilab] (ORCID:0000000294892681↗

NASA NTRS1974

The local complex of O and B stars. I - Distribution of stars and interstellar dust

The O-B5 stars, supergiants, young clusters, and associations within 1 kpc of the sun populate two flat systems inclined to each other by 19 to 22 deg. The historical background, statistical significance, composition, spatial arrangement of the contents, and interstellar extinction in the two belts are discussed. A more or less random distribution in space and in age characterizes the O-B5 stars of the 'galactic belt', which is aligned nearly along the Milky Way. The 'Gould belt' is inclined to the Milky Way (north in Sco-Oph and south in Orion), and exhibits a projected distribution of O-B5 stars in its mean plane that resembles a 'dragonfly', with five major features defining it. A crude 'diameter' of the system is 750 to 1000 pc, and the sun's position is eccentric, lying toward Ophiuchus. The nuclear age of the system, while not unique, may be characterized as 30 m.y. from the spectral type of the broad main-sequence turnup near B2-5. Most of the O-B2 stars and youngest stellar groups near the sun belong to the Gould belt, but both belts have approximately equal space densities of B3-B5 stars and similar average values of interstellar extinction.-

Stothers, R.↗

NASA NTRS2002

Identification of characteristic oligonucleotides in the bacterial 16S ribosomal RNA sequence dataset

MOTIVATION: The phylogenetic structure of the bacterial world has been intensively studied by comparing sequences of 16S ribosomal RNA (16S rRNA). This database of sequences is now widely used to design probes for the detection of specific bacteria or groups of bacteria one at a time. The success of such methods reflects the fact that there are local sequence segments that are highly characteristic of particular organisms or groups of organisms. It is not clear, however, the extent to which such signature sequences exist in the 16S rRNA dataset. A better understanding of the numbers and distribution of highly informative oligonucleotide sequences may facilitate the design of hybridization arrays that can characterize the phylogenetic position of an unknown organism or serve as the basis for the development of novel approaches for use in bacterial identification. RESULTS: A computer-based algorithm that characterizes the extent to which any individual oligonucleotide sequence in 16S rRNA is characteristic of any particular bacterial grouping was developed. A measure of signature quality, Q(s), was formulated and subsequently calculated for every individual oligonucleotide sequence in the size range of 5-11 nucleotides and for 15mers with reference to each cluster and subcluster in a 929 organism representative phylogenetic tree. Subsequently, the perfect signature sequences were compared to the full set of 7322 sequences to see how common false positives were. The work completed here establishes beyond any doubt that highly characteristic oligonucleotides exist in the bacterial 16S rRNA sequence dataset in large numbers. Over 16,000 15mers were identified that might be useful as signatures. Signature oligonucleotides are available for over 80% of the nodes in the representative tree.

NASA Discipline Life Sciences Technologies↗

NASA NTRS2019

The Future of Exoplanet Direct Detection

Diffraction fundamentally limits our ability to image and characterize exoplanets. Currant and planned coronagraphic searches for exoplanets are making incredible strides but are fundamentally limited by the inner working angle of a few λ/D. Some crucial topics, such as demographics of exoplanets within the first 50 Myr and the infrared characterization of terrestrial planets, are beyond the reach of the single aperture angular resolution for the foreseeable future. Interferometry offers some advantages in exoplanet detection and characterization and we explore in this white paper some of the potential scientific breakthroughs possible. We demonstrate here that investments in "exoplanet interferometry" could open up new possibilities for speckle suppression through spatial coherence, a giant boost in astrometric precision for determining exoplanet orbits, ability to take a census of young giant exoplanets (clusters <50 Myr age), and an unrivaled potential for infrared nulling from space to detect terrestrial planets and search for atmospheric biomarkers. All signs point to an exciting future for exoplanets and interferometers, albeit a promise that will take decades to fulfill.

John Monnier↗

DOE OSTI2020

Polyhydrido Copper Nanoclusters with a Hollow Icosahedral Core: [Cu 30 H 18 {E 2 P(OR) 2 } 12 ] (E=S or Se; R= n Pr, i Pr or i Bu)

Although atomically precise polyhydrido copper nanoclusters are of prime interest for a variety of applications, they have so far remained scarce. Here, we describe the synthesis of a dithiophosphate-protected copper(I) hydride-rich nanocluster (NC), [Cu 30 H 18 {S 2 P(O n Pr) 2 } 12 ] ( 1 H ), fully characterized by various spectroscopic methods and single-crystal X-ray diffraction. The X-ray structure of 1 H reveals an unprecedented central Cu 12 hollow icosahedron. Six faces of this icosahedron are capped by Cu 3 triangles, the whole Cu 30 core being wrapped by twelve dithiophosphate ligands and the whole cluster has ideal S 6 symmetry. The locations of the 18 hydrides in 1 H were ascertained by a single-crystal neutron diffraction study. They are composed of three types: capping μ 3 -H, interstitial μ 4 -H (seesaw) and μ 5 -H ligands (square pyramidal), in good agreement with the DFT simulations. The numbers of hydrides and ligand resonances in the 1 H NMR spectrum of 1 H are in line with their coordination environment in the solid state, retaining the S 6 symmetry in solution. Furthermore, two new Se-protected polyhydrido copper nanoclusters, [Cu 30 H 18 {Se 2 P(OR) 2 } 12 ] ( 2 H : R= i Pr 3 H : R= i Bu) were synthesized from their sulfur relative 1 H via ligand displacement reaction and their X-ray structures feature the exceptional case where both the NC shape and size are fully conserved during the course of ligand exchange. DFT and TD-DFT calculations allow understanding the bonding and optical properties of clusters 1 H – 3 H . In addition, the reaction of 1 H with [Pd(PPh 3 ) 2 Cl 2 ] in the presence of terminal alkynes led to the formation of new bimetallic Cu–Pd alloy clusters [PdCu 14 H 2 {S 2 P(O n Pr) 2 } 6 (C≡CR) 6 ] ( 4 : R=Ph; 5 : R = C 6 H 4 F).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Evaluation of genetic diversity, agronomic traits, and anthracnose resistance in the NPGS Sudan Sorghum Core collection

The United States Department of Agriculture (USDA) National Plant Germplasm System (NPGS) sorghum core collection contains 3011 accessions randomly selected from 77 countries. Genomic and phenotypic characterization of this core collection is necessary to encourage and facilitate its utilization in breeding programs and to improve conservation efforts. In this study, we examined the genome sequences of 318 accessions belonging to the NPGS Sudan sorghum core set, and characterized their agronomic traits and anthracnose resistance response. We identified 183,144 single nucleotide polymorphisms (SNPs) located within or in proximity of 25,124 annotated genes using the genotyping-by-sequencing (GBS) approach. The core collection was genetically highly diverse, with an average pairwise genetic distance of 0.76 among accessions. Population structure and cluster analysis revealed five ancestral populations within the Sudan core set, with moderate to high level of genetic differentiation. In total, 171 accessions (54%) were assigned to one of these populations, which covered 96% of the total genomic variation. Genome scan based on Tajima’s D values revealed two populations under balancing selection. Phenotypic analysis showed differences in agronomic traits among the populations, suggesting that these populations belong to different ecogeographical regions. A total of 55 accessions were resistant to anthracnose; these accessions could represent multiple resistance sources. Genome-wide association study based on fixed and random model Circulating Probability (farmCPU) identified genomic regions associated with plant height, flowering time, panicle length and diameter, and anthracnose resistance response. Integrated analysis of the Sudan core set and sorghum association panel indicated that a large portion of the genetic variation in the Sudan core set might be present in breeding programs but remains unexploited within some clusters of accessions. The NPGS Sudan core collection comprises genetically and phenotypically diverse germplasm with multiple anthracnose resistance sources. Population genomic analysis could be used to improve screening efforts and identify the most valuable germplasm for breeding programs. The new GBS data set generated in this study represents a novel genomic resource for plant breeders interested in mining the genetic diversity of the NPGS sorghum collection.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

The Kinematically Hot, Extremely Metal-poor C-19 Stellar Stream in DESI DR2

Stellar streams are the result of a host galaxy’s gravitational potential tidally disrupting satellite dwarf galaxies and globular clusters (GCs), causing them to grow leading and trailing tidal tails. The C-19 stellar stream is an extremely metal-poor stellar population, showing chemical abundance patterns characteristic of a GC. However, its large velocity dispersion is difficult to reconcile with a conventional, purely baryonic, disrupting-GC progenitor. Current techniques for stream characterization are primarily applied to Gaia DR3, relying heavily on proper-motion measurements. Using the Dark Energy Spectroscopic Instrument (DESI), which provides radial velocities and metallicities for over 10 million stars and reaches significantly fainter magnitudes than comparable surveys, we employ a mixture model approach to jointly characterize stream populations in proper motions, radial velocities, and metallicities against a Milky Way halo background. By applying this framework to the C-19 stellar stream, we identify a total of 47 spectroscopically confirmed member stars, of which 41 are newly identified and only 6 were previously reported in the literature. In this work, we measure a velocity dispersion of $7.8^{+1.5}_{-1.3}$km s −1 and a mean metallicity of [Fe/H] = $-3.36^{+0.12}_{-0.10}$. We further identify a novel “spur” feature within the stream. We conclude that our measurements are in line with previous works identifying C-19 as a “hot,” metal-poor stream. In forthcoming work, we will apply this approach to many more streams in the DESI footprint, enabling population-level comparisons with predictions from simulations.

Mohammed, Nasser [University of Toronto; Dunlap In↗

NASA NTRS1976

Survey of intensity variability of strong galactic X-ray sources from Uhuru

X-ray observations made with the Uhuru satellite have been used to study the characteristics of the intensity of 19 strong galactic sources. On a time scale of 0.1-1.0 s, all but two these sources showed variability at a significance level greater than 3 sigmas. On longer time scales - minutes to hours - all but three sources showed variations above the 3-sigma level. In addition to characterizing in a systematic way the broad range of variability of the galactic X-ray sources, the results are applied to specific models of Cygnus X-1 and Cygnus X-3. Comments are also made on the similar nature of the strong galactic-center X-ray sources and the globular-cluster sources.

Forman, W.↗

NASA NTRS1993

Mass and spatial distribution of carbonaceous component in Comet Halley

Cometary grains containing large amounts of carbon and/or organic matter were discovered by in situ measurements of cometary dust composition during VEGA and GIOTTO fly-by missions. In accordance with the classification for the data of PUMA-1 and PUMA-2 mass-spectrometers on board the VEGA spacecraft, particles with a ratio of C to any rock-forming element (Mg, Si, Fe, Ca etc.) greater than 10, were categorized as CHON. There are 464 such particles in PUMA-1 data and 51 in PUMA-2 data. Application of cluster analysis to these grains revealed several distinct compositional classes, namely: (H,C,N,O), (H,C,N), (H,C), (H,C,O), (C,N), (C,O), (C,N,O), and (C). Similar classes were identified among particles analyzed by PIA. Also, about a third of all particles fell into groups (H) and (O) characterized by abundances of these elements beyond chemically reasonable limits.

Fomenkova, M.↗

NASA NTRS2004

Photoionization in Ultraviolet Processing of Astrophysical Ice Analogs at Cryogenic Temperatures

Two recent experimental studies have demonstrated that amino acids or amino acid precursors are generated when astrophysical ice analogs are subjected to ultraviolet (UV) irradiation at cryogenic temperatures. Understanding the complete phenomenology of photoprocessing is critical to elucidating chemical reaction mechanisms that can function within an ice matrix under very cold conditions. Pushing beyond the much better characterized study of photolytic dissociation of chemical bonds through electronic excitation, this work explored the ability of UV radiation present in the interstellar medium to ionize small molecules embedded in ices. Quantum chemical calculations, including bulk solvation effects, were used to study the ionization of hydrogen (H2), water, and methanol (CH3OH) bound in small clusters of water. Ionization potentials were found to be much smaller in the condensed phase than in the gas phase; even a small cluster can account for large changes in the ionization potentials in ice, as well as the known formation of an OH--H3O+ pair in the case of H2O photoionization. To gauge the impact of photoionization on subsequent grain chemistry, the reaction between OH and CO in the presence of H3O+ was studied and compared with the potential energy surface without hydronium present, which is relevant to chemistry following photolysis. The differences indicate that the reaction is somewhat more likely to proceed to products (H + CO2) in the case of photoionization.

Woon, David E.↗

DOE OSTI2021

Cluster defects in gibbsite nanoplates grown at acidic to neutral pH

Gibbsite [α-Al(OH) 3 ] is the solubility limiting phase for aluminum across a wide pH range, and it is a common mineral phase with many industrial applications. The growth mechanism of this layered-structure material, however, remains incompletely understood. Synthesis of gibbsite at low to circumneutral pH yields nanoplates with substantial interlayer disorder. Here we examine defects in this material in detail, and the effects of recrystallization in highly alkaline sodium hydroxide solution at 80 °C. We employed a multimodal approach, including scanning electron microscopy, magic-angle spinning nuclear magnetic resonance (MAS-NMR), Raman and infrared spectroscopies, X-ray diffraction (XRD), and X-ray total scattering pair distribution function (XPDF) analysis to characterize the ageing of the nanoplates over several days. Additionally, XRD and XPDF indicate that gibbsite nanoplates precipitated at circumneutral pH contain dense, truncated sheets imparting a local difference in interlayer distance. These interlayer defects appear well described by flat Al 13 aluminum hydroxide nanoclusters nearly isostructural with gibbsite sheets present under synthesis conditions and trapped as interlayer inclusions during growth. Ageing at elevated temperature in alkaline solutions gradually improves crystallinity, showing a gradual increase in H-bonding between interlayer OH groups. Between 7 to 8 vol% of the initial gibbsite nanoparticles exhibit this defect, with the majority of differences disappearing after 2–4 hours of recrystallization in alkaline solution. The results not only identify the source of disorder in gibbsite formed under acidic/neutral conditions but also point to a possible cluster-mediated growth mechanism evident through inclusion of relict oligomers with gibbsite-like topology trapped in the interlayer spaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Neutron Identification Capabilities in MicroBooNE Through the Application of Machine Learning with Blips

Neutrinos (ν) are subatomic particles first observed in 1956 by LANL physicists Clyde Cowan and Frederick Reines but first theorized by Wolfgang Pauli in 1930. Neutrinos are the least massive known particle and are classified as leptons with 3 flavors corresponding to their leptonic counterparts (electron, muon, and tau). We know that they are abundant, 65 billion neutrinos travel through your fingertip every second, and elusive, a single neutrino could fly through a lightyear of lead without interacting at all. Though, there is much still unknown and a better characterization of these “ghostly” particles can give us clues as to the matter/anti-matter asymmetry in the early universe and possible glimpses into new physics. To measure a particle that is extremely light and rarely interacting, physicists have developed an extremely sensitive detector known as a Liquid Argon Time Projection Chamber (LArTPC). The fiducial volume (or TPC) is bombarded with neutrinos, some of which interact with argon (Ar) atoms to produce particles that in turn excite and ionize the Ar. The products of these are free electrons which then drift through the TPC’s applied magnetic field towards a multi-plane wire readout system. The electrons’ charge is collected at this anode and the light from the initial interactions is collected by photomultiplier tubes (PMTs). In conjunction, these mechanisms allow LArTPCs to achieve millimeter spatial resolution and sub-MeV energy thresholds. The detector of interest in this study is the MicroBooNE Experiment at Fermilab. MicroBooNE is an above ground LArTPC with dimensions of approximately 10m × 2.5m × 2.3m, about the size of a school bus. Its purpose is to study neutrinos, so to improve rates of measured ν interactions, the detector is squarely in the path of the Booster Neutrino Beam (BNB) at Fermilab. A major challenge in neutrino studies is energy reconstruction, much of the neutrino’s original energy is lost in interactions that the detector is not sensitive to, often due to low-energy products. The initial goal of this analysis was to better identify neutrons, the main source of poor energy reconstruction in neutrino events. Because neutrons are neutral particles, like neutrinos, we can only directly measure the products of their interactions in LArTPCs. Most of these products are low-energy signals and while each one contributes a negligible amount of energy, collectively these signals make up most of the lost energy in each neutrino event. We define these signals as blips; point-like, isolated depositions of charge in the detector. Blips have MeV-scale energies and are the size of a single hit (charge deposition) or a cluster of a few hits on at least two wire planes. Blips are the principal detector features used to study low-energy physics; thus, they are the key to unlocking information not only about neutrons but gamma photons, supernova and solar neutrinos as well as helping us better identify certain particles. Therefore, this analysis strives to use blips for improved neutron identification (ID) and characterization.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Reduced-Cost Four-Component Relativistic Double Ionization Potential Equation-of-Motion Coupled-Cluster Approaches with 4-Hole–2-Particle Excitations and Three-Body Clusters

The double ionization potential (DIP) equation-ofmotion (EOM) coupled-cluster (CC) method with 4-hole−2- particle (4h-2p) excitations on top of the CC with singles, doubles, and triples calculation, abbreviated as DIP-EOMCCSDT(4h-2p), along with its perturbative DIP-EOMCCSD(T)(a)(4h-2p) approximation, are extended to a relativistic four-component (4c) framework. In addition, we introduce and test a new computationally practical DIP-EOMCC approach, which we call DIPEOMCCSD( T)(ã)(4h-2p), that approximates the treatment of 4h- 2p correlations within the DIP-EOMCCSD(T)(a)(4h-2p) method and reduces the $\mathcal{N}$ 8 scaling characterizing DIP-EOMCCSDT(4h- 2p) and DIP-EOMCCSD(T)(a)(4h-2p) to $\mathcal{N}$ 7 with the system size $\mathcal{N}$. Further improvements in computational efficiency are obtained using the frozen natural spinor (FNS) approximation to reduce the numbers of unoccupied spinors entering the correlated steps of the DIP-EOMCC calculations according to a well-defined occupation-number-based threshold. The resulting 4c-FNS-DIPEOMCC approaches are used to compute DIPs for the series of inert gas atoms from argon to radon as well as the vertical DIPs in Cl 2 , Br 2 , HBr, and HI, which have been experimentally examined in the past. We demonstrate that, when using complete basis set extrapolations and FNS truncation threshold of 10 −4.5 , the 4c-FNS-DIP-EOMCCSD(T)(ã)(4h-2p) calculations are capable of predicting DIPs in agreement with experimental data, improving upon their nonrelativistic and spin-free scalar-relativistic counterparts, particularly when examining DIPs characterized by stronger spin−orbit coupling effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Machine learning enabled quantification of the hydrogen bonds inside the polyelectrolyte brush layer probed using all-atom molecular dynamics simulations

The configuration of densely grafted charged polyelectrolyte (PE) brushes is strongly dictated by the properties and behavior of the counterions that screen the PE brush charges and the solvent molecules (typically water) that solvate the brush molecules and these screening counterions. Only recently, efforts have been made to study the PE brushes atomistically, thereby shedding light on the properties of brush-supported ions and water molecules. However, even for such efforts, there are limitations associated with using a generic definition to estimate certain properties of water and ions inside the brush layer. For example, water–water hydrogen bonds (HBs) will behave differently for locations outside and inside the brush layer, given the fact that the densely closely grafted PE brush molecules create a soft nanoconfinement where the water connectivity becomes highly disrupted: therefore, using the same definition to quantify the HBs inside and outside the brush layer will be unwise. In this paper, we address this limitation by employing an unsupervised machine learning (ML) approach to predict the water–water hydrogen bonding inside a cationic PE brush layer modeled using all-atom molecular dynamics (MD) simulations. Here, the ML method, which relies on a clustering approach and uses the equilibrium coordinates of the water molecules (obtained from the all-atom MD simulations) as the input, is capable of identifying the structural modification of water–water HBs (revealed through appropriate clustering of the data) inside the PE brush layer induced soft nanoconfinement. Such capabilities would not have been possible by using a generic definition of the HBs. Our calculations lead to four key findings: (1) the clusters formed inside and outside the brush layer are structurally similar; (2) the margin of the cluster is shorter inside the PE brush layer confirming the possible disruption of the HBs inside the PE brush layer; (3) the average “hydrogen–acceptor-oxygen–donor-oxygen” angle that defines the HB is reduced for the HBs formed inside the brush layer; (4) the use of the generic definition (definition usable for characterizing the HBs in brush-free bulk) leads to an overprediction of the number of HBs formed inside the PE brush layer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

X-ray scattering based scanning tomography for imaging and structural characterization of cellulose in plants

X-ray and neutron scattering have long been used for structural characterization of cellulose in plants. Due to averaging over the illuminated sample volume, these measurements traditionally overlooked the compositional and morphological heterogeneity within the sample. Here, a scanning tomographic imaging method is described, using contrast derived from the X-ray scattering intensity, for virtually sectioning the sample to reveal its internal structure at a resolution of a few micrometres. This method provides a means for retrieving the local scattering signal that corresponds to any voxel within the virtual section, enabling characterization of the local structure using traditional data-analysis methods. This is accomplished through tomographic reconstruction of the spatial distribution of a handful of mathematical components identified by non-negative matrix factorization from the large dataset of X-ray scattering intensity. Joint analysis of multiple datasets, to find similarity between voxels by clustering of the decomposed data, could help elucidate systematic differences between samples, such as those expected from genetic modifications, chemical treatments or fungal decay. The spatial distribution of the microfibril angle can also be analyzed, based on the tomographically reconstructed scattering intensity as a function of the azimuthal angle.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Characterizing crystalline defects in single nanoparticles from angular correlations of single-shot diffracted X-rays

Characterizing and controlling the uniformity of nanoparticles is crucial for their application in science and technology because crystalline defects in the nanoparticles strongly affect their unique properties. Recently, ultra-short and ultra-bright X-ray pulses provided by X-ray free-electron lasers (XFELs) opened up the possibility of structure determination of nanometre-scale matter with Å spatial resolution. However, it is often difficult to reconstruct the 3D structural information from single-shot X-ray diffraction patterns owing to the random orientation of the particles. This report proposes an analysis approach for characterizing defects in nanoparticles using wide-angle X-ray scattering (WAXS) data from free-flying single nanoparticles. The analysis method is based on the concept of correlated X-ray scattering, in which correlations of scattered X-ray are used to recover detailed structural information. WAXS experiments of xenon nanoparticles, or clusters, were conducted at an XFEL facility in Japan by using the SPring-8 Ångstrom compact free-electron laser (SACLA). Bragg spots in the recorded single-shot X-ray diffraction patterns showed clear angular correlations, which offered significant structural information on the nanoparticles. The experimental angular correlations were reproduced by numerical simulation in which kinematical theory of diffraction was combined with geometric calculations. We also explain the diffuse scattering intensity as being due to the stacking faults in the xenon clusters.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗