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All sources NASA NTRS DOE OSTI

DOE OSTI2020

Low-temperature MnBi alloys: Electronic and magnetic properties, constitution, morphology and fabrication (Review article)

The article reviews the rich phenomena of physical properties of MnBi. The diverse phenomena include strong spin-orbit interaction, anomalous temperature dependence of the coercivity and the magneto-crystalline anisotropy field, unique magneto-optical properties. Issues addressed include the nature of the electronic ground states of MnBi, the electronic and magnetic structures, Fermi surface, magneto-crystalline anisotropy, x-ray magnetic dichroism. The discussion includes key experiments, such as optical and magneto-optical spectroscopic measurements, de Haas-van Alphen (dHvA) measurements, x-ray photoemission and x-ray absorption spectroscopy measurements as well as x-ray magnetic circular dichroism. The effect of the spin-orbit (SO) interaction and Coulomb repulsion U were found to be crucial for the Fermi surface, cyclotron masses, magneto-optical properties, and x-ray magnetic circular dichroism. The microscopic origin of unique magneto-crystalline anisotropy and giant Kerr effect in MnBi is analyzed in detail. The huge Kerr effect in MnBi is caused by the combination of a sizable magnetic moment on manganese, the large spin-orbit coupling of bismuth, and a strong hybridization between the manganese 3d and the bismuth 6p states. The magneto-optically active states are mainly the 6p states of Bi. We show that the observed temperature dependence of the magneto-crystalline anisotropy can be explained taking into account the spin-orbit interaction together with strong Coulomb electron-electron interaction. The SO coupling of Bi is equally responsible for the large magneto-crystalline anisotropy energy as is the exchange splitting of Mn. The fabrication, morphology, and constitution of low-temperature MnBi alloys in bulk, thin films, and nanoparticles are discussed. The nanocomposite permanent magnetic materials based on MnBi, (Co, Fe) and Nd 2 Fe 14 B are also discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Advanced nanoscale characterization of aluminum nanoparticles with modified surface morphology via atmospheric helium and carbon monoxide plasmas

Aluminum nanoparticles (nAl) have the potential as energetic additives in explosive/propellant formulations. Scalable methodologies must be pursued to mitigate the inactive amorphous alumina shell surrounding the active aluminum (Al) core with modified surface morphology and chemistry for increased combustion effects. This work explores the feasibility of making reactive core/shell nAl with thinned oxide shells and modified surface coatings via a two-step atmospheric plasma surface treatment process in a custom dielectric barrier discharge plasma reactor. The commercial nAl of nominal average size similar to 40-60nm was first treated with helium (He) followed by He/carbon monoxide (CO) plasmas for different durations. The resultant samples were characterized via high-resolution transmission electron microscopy (HRTEM) and Fourier transform IR (FTIR) spectra. HRTEM images revealed sporadic patchy gamma -alumina deposits on particle surfaces and in gaps among particles for all samples, suggesting the non-uniform plasma effects of the He/CO glow. Nanoscale chemical analyses via scanning transmission electron microscopy elemental mapping and x-ray energy dispersive spectroscopy were further performed. Although no carbon-associated structure appeared in electron energy loss spectroscopy (EELS) spectra, the presence of carbonaceous materials was confirmed as a thin dispersive layer evenly distributed on the nAl surface suggesting either its amorphous nature or is present at a level insufficient to generate satisfactory EELS spectra. The trend of intensity profiles for key elements acquired by drawing lines across a single particle on the elemental maps confirmed that carbonaceous materials only existed on the surface and they were most likely carboxylates that increased with increased He/CO treatment duration, as evident by FTIR results. Finally, this work demonstrated the success of atmospheric plasma-treated reactive nAl with comprehensively characterized surface features via advanced microscopy and spectroscopy.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Shock initiation of low density polymer bonded explosive LX-14: A study of two morphologies

A series of six shock initiation experiments have been carried out on low density LX-14 powder in order to simulate a shock insult on the heavily damage polymer bonded explosive, LX-14. Two distinct morphologies were studied (tap density molding powder and machined swarf), both at the same density of 0.942 g/cm 3 , or 50.1% theoretical maximum density. The purpose of these experiments was to provide data to help make an assessment of the effects that damage has on the material sensitivity to a planar shock. This was achieved primarily by providing shock sensitivity data in the form of a Pop plot, and also reactants equation of state data, which aids in the determination of input conditions for both the experiments performed in this work and also future experiments of this material type. The experiments were of a cut-back format, consisting of four sample heights on each shot and diagnosed with optical velocimetry. The experiments were carried out at the Technical Area 40 Chamber 9 gas gun facility at the Los Alamos National Laboratory, where the LX-14 targets were subjected to Al 6061 and Oxygen Free High Conductivity copper impactors launched to velocities up to 2.14 km/s. Time corrected reactive growth wave profiles are presented in this paper along with the derivation of the following Hugoniot parameters for this explosive, where the molding powder and machine swarf are represented by the following linear equations, respectively, U s = 1.64 (±0.64)u p + 2.25 (±0.49) and U s = 0.87 (±.0.60)u p + 4.08 (±0.49). The results show that the steady increase in shock sensitivity with increasing void fraction reaches an inflection point beyond which the shock sensitivity begins to decease. This inflection point lies between 65% and 50% of the theoretical maximum density of the LX-14. In both cases, the damaged LX-14 was not as sensitive as expected, with a relative shock sensitivity of the molding powder being less than the pressed LX-14, and the machined swarf having a shock sensitivity that is comparable to pressed LX-14.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Knock-on deuteron imaging for diagnosing the morphology of an ICF implosion at OMEGA

Knock-on deuteron imaging is a new diagnostic technique that is being implemented at the OMEGA laser facility to diagnose the morphology of an inertial confinement fusion (ICF) implosion. It utilizes the fact that some of the neutrons from deuterium–tritium (DT)-fusion reactions generated in the central hot-spot of an ICF implosion elastically scatter deuterons as they traverse the surrounding shell layer. The energy of these “knock-on” deuterons depends on the scattering angle, where the most energetic deuterons are forward-scattered and probe the shape of the central hot-spot, while lower-energy deuterons are made by side-scattering or slowing down in the fuel and carry information about the distribution of the dense DT-fuel layer surrounding the hot-spot. The first proof-of-concept tests have been conducted successfully. In these tests, three penumbral imagers with different views on an implosion recorded deuterons scattered from the dense shell of DT-gas-filled deuterated plastic shell implosions with prescribed offsets. Data from these experiments are presented here, along with novel analysis techniques that iteratively reconstruct the deuteron source from the data. Reconstructed hot-spot and shell radii agree with 1D hydro simulations and indicate a P1 asymmetry in the direction of the offset. A comparison of coaxial deuteron and x-ray images suggests the presence of a mix between the hot-spot and shell on the order of 15 μm. This new diagnostic capability will allow us to study asymmetries in unprecedented detail at OMEGA.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Role of morphology in defect formation and photo-induced carrier instabilities in amorphous indium oxide

Ab initio molecular dynamics liquid-quench simulations and hybrid density functional calculations are performed to model the effects of room-temperature atomic fluctuations and photo-illumination on the structural and electronic properties of amorphous sub-stoichiometric In 2 O 2.96 . A large configurational ensemble is employed to reliably predict the distribution of localized defects as well as their response to the thermal and light activation. The results reveal that the illumination effects on the carrier concentration are greater in amorphous configurations with shorter In–O bond length and reduced polyhedral sharing as compared to the structures with a more uniform morphology. Further, the obtained correlation between the photo-induced carrier density and the reduction in the number of fully coordinated In-atoms implies that metal oxides with a significant fraction of crystalline/amorphous interfaces would show a more pronounced response to illumination. Photo-excitation also produces In–O 2 –In defects that have not been previously found in sub-stoichiometric amorphous oxides; these defects are responsible for carrier instabilities due to overdoping.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2024

Direct mechanistic connection between acoustic signals and melt pool morphology during laser powder bed fusion

Various nondestructive diagnostic techniques have been proposed for in situ process monitoring of laser powder bed fusion (LPBF), including melt pool pyrometry, whole-layer optical imaging, acoustic emission, atomic emission spectroscopy, high speed melt pool imaging, and thermionic emission. Correlations between these in situ monitoring signals and defect formation have been demonstrated with acoustic signals having been shown to predict pore formation with especially high confidence in recent machine learning studies. Here, in this work, time-resolved acoustic data are collected in both the conduction and keyhole welding regimes of LPBF-processed Ti-6Al-4V alloy. A non-dimensionalized Strouhal number analysis, used in whistle aeroacoustics, is applied to demonstrate that the acoustic signals recorded in the keyhole regimes can be directly associated with the vapor depression morphology. This mechanistic understanding developed from whistle aeroacoustics shows that acoustic monitoring during the LPBF process can provide a direct probe into the vapor depression dynamics and defect occurrence, especially in the keyhole regimes relevant to printing and defect formation.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Ferro-ionic states and domains morphology in Hf x Zr 1–x O 2 nanoparticles

Unique polar properties of nanoscale hafnia-zirconia oxides (Hf x Zr 1–x O 2 ) are of great interest for condensed matter physics, nanophysics, and advanced applications. These properties are connected (at least partially) to the ionic–electronic and electrochemical phenomena at the surface, interfaces, and/or internal grain boundaries. Here, we calculated the phase diagrams, dielectric permittivity, spontaneous polar, and antipolar ordering, as well as the domain structure morphology in Hf x Zr 1–x O 2 nanoparticles covered by ionic–electronic charge originating from surface electrochemical adsorption. We revealed that the ferro-ionic coupling supports the polar long-range order in nanoscale Hf x Zr 1–x O 2 , induces, and/or enlarges the stability region of the labyrinthine domains toward smaller sizes and smaller environmental dielectric constant at low concentrations of the surface ions. The ferro-ionic coupling causes the transition to the single-domain ferro-ionic state at high concentrations of the surface ions. We predict that the labyrinthine domain states, being multiple-degenerated, may significantly affect the emergence of the negative differential capacitance state in the nanograined/nanocrystalline Hf x Zr 1–x O 2 films.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Morphological Characterization of Uranyl Fluoride Particles via Atomic Force Microscopy

Uranium hexafluoride (UF 6 ) undergoes a rapid hydrolysis reaction when exposed to atmospheric water. In addition to producing hazardous HF gas, the hydrolysis reaction produces uranyl fluoride (UO 2 F 2 ), a radioactive solid phase particulate material. Because of the technological utility of UF 6 in the nuclear fuel cycle, understanding the transport properties of UO 2 F 2 aerosol produced via UF 6 hydrolysis is important for accident scenarios. Moreover, the fundamental chemical and physical properties of the UF 6 hydrolysis reaction are not completely understood. Recently, several experiments on the aerosol phase properties of UO 2 F 2 produced in this way have shown that under most relevant conditions, the particle size distribution (PSD) of UO 2 F 2 can be extremely small, approximately 3 to 5 nm, which is well below the threshold that can be routinely observed via scanning electron microscopy (SEM). Although readily observable in the aerosol phase, observation of nanometer-sized particles in the condensed phase (i.e. deposited on surfaces) remains a challenge. Here, in this study, we have used atomic force microscopy (AFM) to study the PSD and morphological characteristics of UO 2 F 2 deposited at low and high concentrations under different humidity conditions, a primary variable in the hydrolysis reaction. Here, we find strong agreement between PSD measured in the aerosol phase via scanning mobility particle sizing and PSD measured via AFM, with particle sizes peaked below 4 nm for low-humidity conditions. At higher humidity, the distribution is centered around 5 to 10 nm but extends up to 20 nm. These results are in stark contrast to previous measurements using SEM that show PSD on the order of 300- to 1000-nm particle sizes; moreover, these are the first direct measurements of individual particles of UO 2 F 2 having been produced via UF 6 hydrolysis deposited on surfaces. These measurements, therefore, open a new avenue for collecting and detecting UO 2 F 2 in the condensed phase and further refine the PSD, which is critical for environmental transport determinations.

Uranium hexafluoride↗

DOE OSTI2020

SDSS-IV MaNGA: The kinematic-morphology of galaxies on the mass versus star-formation relation in different environments

ABSTRACT We study the link between the kinematic-morphology of galaxies, as inferred from integral-field stellar kinematics, and their relation between mass and star formation rate. Our sample consists of ∼3200 galaxies with integral-field spectroscopic data from the MaNGA survey (Mapping Nearby Galaxies at Apache Point Observatory) with available determinations of their effective stellar angular momentum within the half-light radius $\lambda _{R_e}$. We find that for star-forming galaxies, namely along the star formation main sequence (SFMS), the $\lambda _{R_e}$ values remain large and almost unchanged over about two orders of magnitude in stellar mass, with the exception of the lowest masses $\mathcal {M}_{\star }\lesssim 2\times 10^{9} \, \mathcal {M}_{\odot }$, where $\lambda _{R_e}$ slightly decreases. The SFMS is dominated by spiral galaxies with small bulges. Below the SFMS, but above the characteristic stellar mass $\mathcal {M}_{\rm crit}\approx 2\times 10^{11} \, \mathcal {M}_{\odot }$, there is a sharp decrease in $\lambda _{R_e}$ with decreasing star formation rate (SFR): massive galaxies well below the SFMS are mainly slow-rotator early-type galaxies, namely genuinely spheroidal galaxies without discs. Below the SFMS and below $\mathcal {M}_{\rm crit}$ the decrease of $\lambda _{R_e}$ with decreasing SFR becomes modest or nearly absent: low-mass galaxies well below the SFMS, are fast-rotator early-type galaxies, and contain fast-rotating stellar discs like their star-forming counterparts. We also find a small but clear environmental dependence for the massive galaxies: in the mass range $10^{10.9}\!-\!10^{11.5} \, \mathcal {M}_{\odot }$, galaxies in rich groups or denser regions or classified as central galaxies have lower values of $\lambda _{R_e}$. While no environmental dependence is found for galaxies of lower mass. We discuss how the above results can be understood as due to the different star formation and mass assembly histories of galaxies with varying mass.

Wang, Bitao↗

DOE OSTI2020

A novel CMB component separation method: hierarchical generalized morphological component analysis

ABSTRACT We present a novel technique for cosmic microwave background (CMB) foreground subtraction based on the framework of blind source separation. Inspired by previous work incorporating local variation to generalized morphological component analysis (GMCA), we introduce hierarchical GMCA (HGMCA), a Bayesian hierarchical graphical model for source separation. We test our method on Nside = 256 simulated sky maps that include dust, synchrotron, free–free, and anomalous microwave emission, and show that HGMCA reduces foreground contamination by $25{{\ \rm per\ cent}}$ over GMCA in both the regions included and excluded by the Planck UT78 mask, decreases the error in the measurement of the CMB temperature power spectrum to the 0.02–0.03 per cent level at ℓ > 200 (and $\lt 0.26{{\ \rm per\ cent}}$ for all ℓ), and reduces correlation to all the foregrounds. We find equivalent or improved performance when compared to state-of-the-art internal linear combination type algorithms on these simulations, suggesting that HGMCA may be a competitive alternative to foreground separation techniques previously applied to observed CMB data. Additionally, we show that our performance does not suffer when we perturb model parameters or alter the CMB realization, which suggests that our algorithm generalizes well beyond our simplified simulations. Our results open a new avenue for constructing CMB maps through Bayesian hierarchical analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Galaxy morphological classification catalogue of the Dark Energy Survey Year 3 data with convolutional neural networks

ABSTRACT We present in this paper one of the largest galaxy morphological classification catalogues to date, including over 20 million galaxies, using the Dark Energy Survey (DES) Year 3 data based on convolutional neural networks (CNNs). Monochromatic i-band DES images with linear, logarithmic, and gradient scales, matched with debiased visual classifications from the Galaxy Zoo 1 (GZ1) catalogue, are used to train our CNN models. With a training set including bright galaxies (16 ≤ i < 18) at low redshift (z < 0.25), we furthermore investigate the limit of the accuracy of our predictions applied to galaxies at fainter magnitude and at higher redshifts. Our final catalogue covers magnitudes 16 ≤ i < 21, and redshifts z < 1.0, and provides predicted probabilities to two galaxy types – ellipticals and spirals (disc galaxies). Our CNN classifications reveal an accuracy of over 99 per cent for bright galaxies when comparing with the GZ1 classifications (i < 18). For fainter galaxies, the visual classification carried out by three of the co-authors shows that the CNN classifier correctly categorizes discy galaxies with rounder and blurred features, which humans often incorrectly visually classify as ellipticals. As a part of the validation, we carry out one of the largest examinations of non-parametric methods, including ∼100 ,000 galaxies with the same coverage of magnitude and redshift as the training set from our catalogue. We find that the Gini coefficient is the best single parameter discriminator between ellipticals and spirals for this data set.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

The morphology of the X-ray afterglows and of the jetted GeV emission in long GRBs

ABSTRACT We recall evidence that long gamma-ray bursts (GRBs) have binary progenitors and give new examples. Binary-driven hypernovae (BdHNe) consist of a carbon–oxygen core (COcore) and a neutron star (NS) companion. For binary periods ∼5 min, the COcore collapse originates the subclass BdHN I characterized by (1) an outstanding supernova (SN; the ‘SN-rise’); (2) a black hole (BH), born from the NS collapse by SN matter accretion, leading to a GeV emission with luminosity $L_{\rm GeV} = A_{\rm GeV}\, t^{-\alpha _{\rm GeV}}$, observed only in some cases; and (3) a new NS (νNS), born from the SN, originating from the X-ray afterglow with $L_\mathrm{ X} = A_{\rm X}\, t^{-\alpha _{\rm X}}$, observed in all BdHN I. We record 378 sources and present for four prototype GRBs 130427A, 160509A, 180720B, and 190114C: (1) spectra, luminosities, SN-rise duration; (2) AX, αX = 1.48 ± 0.32, and (3) the νNS spin time evolution. We infer (i) AGeV, αGeV = 1.19 ± 0.04 and (ii) the BdHN I morphology from time-resolved spectral analysis, three-dimensional simulations, and the GeV emission presence/absence in 54 sources within the Fermi-Large Area Telescope boresight angle. For 25 sources, we give the integrated and time-varying GeV emission, 29 sources have no GeV emission detected and show X/gamma-ray flares previously inferred as observed along the binary plane. The 25/54 ratio implies the GeV radiation is emitted within a cone of half-opening angle ≈60° from the normal to the orbital plane. We deduce BH masses of 2.3–8.9 M⊙ and spin of 0.27–0.87 by explaining the GeV emission from the BH rotational energy extraction, while their time evolution validates the BH mass–energy formula.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Beyond the hubble sequence – exploring galaxy morphology with unsupervised machine learning

We explore unsupervised machine learning for galaxy morphology analyses using a combination of feature extraction with a vector-quantized variational autoencoder (VQ-VAE) and hierarchical clustering (HC). We propose a new methodology that includes: (1) consideration of the clustering performance simultaneously when learning features from images; (2) allowing for various distance thresholds within the HC algorithm; (3) using the galaxy orientation to determine the number of clusters. This set-up provides 27 clusters created with this unsupervised learning that we show are well separated based on galaxy shape and structure (e.g. Sérsic index, concentration, asymmetry, Gini coefficient). These resulting clusters also correlate well with physical properties such as the colour–magnitude diagram, and span the range of scaling relations such as mass versus size amongst the different machine-defined clusters. When we merge these multiple clusters into two large preliminary clusters to provide a binary classification, an accuracy of $\sim 87{{\ \rm per\ cent}}$ is reached using an imbalanced data set, matching real galaxy distributions, which includes 22.7 per cent early-type galaxies and 77.3 per cent late-type galaxies. Comparing the given clusters with classic Hubble types (ellipticals, lenticulars, early spirals, late spirals, and irregulars), we show that there is an intrinsic vagueness in visual classification systems, in particular galaxies with transitional features such as lenticulars and early spirals. Based on this, the main result in this work is not how well our unsupervised method matches visual classifications and physical properties, but that the method provides an independent classification that may be more physically meaningful than any visually based ones.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

X-ray morphology of cluster-mass haloes in self-interacting dark matter

ABSTRACT We perform cosmological zoom-in simulations of 19 relaxed cluster-mass haloes with the inclusion of adiabatic gas in the cold dark matter (CDM) and self-interacting dark matter (SIDM) models. These clusters are selected as dynamically relaxed clusters from a parent simulation with $M_{\rm 200} \simeq (1\!-\!3)\times 10^{15}{\, \rm M_\odot }$. Both the dark matter and the intracluster gas distributions in SIDM appear more spherical than their CDM counterparts. Mock X-ray images are generated based on the simulations and are compared to the real X-ray images of 84 relaxed clusters selected from the Chandra and ROSAT archives. We perform ellipse fitting for the isophotes of mock and real X-ray images and obtain the ellipticities at cluster-centric radii of $r\simeq 0.1\!-\!0.2R_{\rm 200}$. The X-ray isophotes in SIDM models with increasing cross-sections are rounder than their CDM counterparts, which manifests as a systematic shift in the distribution function of ellipticities. Unexpectedly, the X-ray morphology of the observed non-cool-core clusters agrees better with SIDM models with cross-section $(\sigma /m)= 0.5\!-\!1\, {\rm cm}^2\, {\rm g}^{-1}$ than CDM and SIDM with $(\sigma /m)=0.1\, {\rm cm}^2\, {\rm g}^{-1}$. Our statistical analysis indicates that the latter two models are disfavoured at the $68{{\ \rm per\ cent}}$ confidence level (as conservative estimates). This conclusion is not altered by shifting the radial range of measurements or applying a temperature selection criterion. However, the primary uncertainty originates from the lack of baryonic physics in the adiabatic model, such as cooling, star formation and feedback effects, which still have the potential to reconcile CDM simulations with observations.

Shen, Xuejian (ORCID:000000026196823X)↗

DOE OSTI2022

Practical galaxy morphology tools from deep supervised representation learning

Astronomers have typically set out to solve supervised machine learning problems by creating their own representations from scratch. We show that deep learning models trained to answer every Galaxy Zoo DECaLS question learn meaningful semantic representations of galaxies that are useful for new tasks on which the models were never trained. We exploit these representations to outperform several recent approaches at practical tasks crucial for investigating large galaxy samples. The first task is identifying galaxies of similar morphology to a query galaxy. Given a single galaxy assigned a free text tag by humans (e.g. ‘#diffuse’), we can find galaxies matching that tag for most tags. The second task is identifying the most interesting anomalies to a particular researcher. Our approach is 100 per cent accurate at identifying the most interesting 100 anomalies (as judged by Galaxy Zoo 2 volunteers). The third task is adapting a model to solve a new task using only a small number of newly labelled galaxies. Models fine-tuned from our representation are better able to identify ring galaxies than models fine-tuned from terrestrial images (ImageNet) or trained from scratch. We solve each task with very few new labels; either one (for the similarity search) or several hundred (for anomaly detection or fine-tuning). This challenges the longstanding view that deep supervised methods require new large labelled data sets for practical use in astronomy. To help the community benefit from our pretrained models, we release our fine-tuning code zoobot. Zoobot is accessible to researchers with no prior experience in deep learning.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Nanoscale elemental and morphological imaging of nitrogen-fixing cyanobacteria

Nitrogen-fixing cyanobacteria bind atmospheric nitrogen and carbon dioxide using sunlight. This experimental study focused on a laboratory-based model system, Anabaena sp., in nitrogen-depleted culture. When combined nitrogen is scarce, the filamentous prokaryotes reconcile photosynthesis and nitrogen fixation by cellular differentiation into heterocysts. To better understand the influence of micronutrients on cellular function, 2D and 3D synchrotron X-ray fluorescence mappings were acquired from whole biological cells in their frozen-hydrated state at the Bionanoprobe, Advanced Photon Source. To study elemental homeostasis within these chain-like organisms, biologically relevant elements were mapped using X-ray fluorescence spectroscopy and energy-dispersive X-ray microanalysis. Higher levels of cytosolic K + , Ca 2+ , and Fe 2+ were measured in the heterocyst than in adjacent vegetative cells, supporting the notion of elevated micronutrient demand. P-rich clusters, identified as polyphosphate bodies involved in nutrient storage, metal detoxification, and osmotic regulation, were consistently co-localized with K + and occasionally sequestered Mg 2+ , Ca 2+ , Fe 2+ , and Mn 2+ ions. Machine-learning-based k-mean clustering revealed that P/K clusters were associated with either Fe or Ca, with Fe and Ca clusters also occurring individually. In accordance with XRF nanotomography, distinct P/K-containing clusters close to the cellular envelope were surrounded by larger Ca-rich clusters. The transition metal Fe, which is a part of nitrogenase enzyme, was detected as irregularly shaped clusters. The elemental composition and cellular morphology of diazotrophic Anabaena sp. was visualized by multimodal imaging using atomic force microscopy, scanning electron microscopy, and fluorescence microscopy. This paper discusses the first experimental results obtained with a combined in-line optical and X-ray fluorescence microscope at the Bionanoprobe.

Anabaena sp↗

DOE OSTI2025

Inference of three-dimensional hot-spot and shell morphology in inertial confinement fusion experiments using a convolutional neural network

The performance of inertial confinement fusion (ICF) implosions is sensitive to the three-dimensional (3D) morphology of the hot-spot and shell configurations. The ability to infer shell-mass uniformity and reconstruct 3D hot spots is crucial for quantifying the degradation of ignition criteria and improving symmetry in ICF implosion experiments. In this work, we present a deep-learning convolutional neural network (CNN) for reconstructing 3D hot-spot and shell structures for ICF capsules. The 3D geometry of the hot spot is reconstructed from x-ray images measured from multiple lines of sight on OMEGA. The shell configuration is inferred indirectly through machine learning using a convolutional neural network extensively trained on a dec3d simulation database. This simulation-dependent approach yields consistent agreement between reconstructed 3D shell densities and machine-learning optimized dec3d simulation results. This work demonstrates a CNN framework that successfully reconstructs 3D capsule structures from two-dimensional images in ICF implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Influence of chemical strains on the electrocaloric response, polarization morphology, tetragonality, and negative-capacitance effect of ferroelectric core-shell nanorods and nanowires

Using Landau-Ginzburg-Devonshire (LGD) approach, we proposed the analytical description of the influence of chemical strains on spontaneous polarization and the electrocaloric response in ferroelectric core-shell nanorods. We postulate that the nanorod core presents a defect-free single-crystalline ferroelectric material, and elastic defects are accumulated in the ultrathin shell, where they can induce tensile or compressive chemical strains. Finite-element modeling (FEM) based on the LGD approach reveals transitions of domain-structure morphology induced by chemical strains in the Ba Ti O 3 nanorods. Namely, tensile chemical strains induce and support the single-domain state in the central part of the nanorod, while the curled domain structures appear near the unscreened or partially screened ends of the rod. The vortexlike domains propagate toward the central part of the rod and fill it entirely, when the rod is covered by a shell with compressive chemical strains above some critical value. The critical value depends on the nanorod sizes, aspect ratio, and screening conditions at its ends. Both analytical theory and FEM predict that the tensile chemical strains in the shell increase the nanorod polarization, lattice tetragonality, and electrocaloric response well above the values corresponding to the bulk material. The physical reason for the increase is strong electrostriction coupling between the mismatch-type elastic strains induced in the core by chemical strains in the shell. Comparison with earlier XRD data confirmed an increase of the tetragonality ratio in tensile Ba Ti O 3 nanorods compared to the bulk material. Obtained analytical expressions, which are suitable for the description of strain-induced changes in a wide range of multiaxial ferroelectric core-shell nanorods and nanowires, can be useful for strain engineering of advanced ferroelectric nanomaterials for energy storage, harvesting, electrocaloric applications, and negative capacitance elements. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗