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NASA NTRS1976

Digital processing of satellite imagery application to jungle areas of Peru

The author has identified the following significant results. The use of clustering methods permits the development of relatively fast classification algorithms that could be implemented in an inexpensive computer system with limited amount of memory. Analysis of CCTs using these techniques can provide a great deal of detail permitting the use of the maximum resolution of LANDSAT imagery. Potential cases were detected in which the use of other techniques for classification using a Gaussian approximation for the distribution functions can be used with advantage. For jungle areas, channels 5 and 7 can provide enough information to delineate drainage patterns, swamp and wet areas, and make a reasonable broad classification of forest types.

Pomalaza, J. C.↗

NASA NTRS2012

Turbulence in a Global Magnetohydrodynamic Simulation of the Earth's Magnetosphere during Northward and Southward Interplanetary Magnetic Field

We report the results of MHD simulations of Earth's magnetosphere for idealized steady solar wind plasma and interplanetary magnetic field (IMF) conditions. The simulations feature purely northward and southward magnetic fields and were designed to study turbulence in the magnetotail plasma sheet. We found that the power spectral densities (PSDs) for both northward and southward IMF had the characteristics of turbulent flow. In both cases, the PSDs showed the three scale ranges expected from theory: the energy-containing scale, the inertial range, and the dissipative range. The results were generally consistent with in-situ observations and theoretical predictions. While the two cases studied, northward and southward IMF, had some similar characteristics, there were significant differences as well. For southward IMF, localized reconnection was the main energy source for the turbulence. For northward IMF, remnant reconnection contributed to driving the turbulence. Boundary waves may also have contributed. In both cases, the PSD slopes had spatial distributions in the dissipative range that reflected the pattern of resistive dissipation. For southward IMF there was a trend toward steeper slopes in the dissipative range with distance down the tail. For northward IMF there was a marked dusk-dawn asymmetry with steeper slopes on the dusk side of the tail. The inertial scale PSDs had a dusk-dawn symmetry during the northward IMF interval with steeper slopes on the dawn side. This asymmetry was not found in the distribution of inertial range slopes for southward IMF. The inertial range PSD slopes were clustered around values close to the theoretical expectation for both northward and southward IMF. In the dissipative range, however, the slopes were broadly distributed and the median values were significantly different, consistent with a different distribution of resistivity.

magnetohydrodynamics (MHD)↗

NASA NTRS1998

EMG responses to maintain stance during multidirectional surface translations

To characterize muscle synergy organization underlying multidirectional control of stance posture, electromyographic activity was recorded from 11 lower limb and trunk muscles of 7 healthy subjects while they were subjected to horizontal surface translations in 12 different, randomly presented directions. The latency and amplitude of muscle responses were quantified for each perturbation direction. Tuning curves for each muscle were examined to relate the amplitude of the muscle response to the direction of surface translation. The latencies of responses for the shank and thigh muscles were constant, regardless of perturbation direction. In contrast, the latencies for another thigh [tensor fascia latae (TFL)] and two trunk muscles [rectus abdominis (RAB) and erector spinae (ESP)] were either early or late, depending on the perturbation direction. These three muscles with direction-specific latencies may play different roles in postural control as prime movers or as stabilizers for different translation directions, depending on the timing of recruitment. Most muscle tuning curves were within one quadrant, having one direction of maximal activity, generally in response to diagonal surface translations. Two trunk muscles (RAB and ESP) and two lower limb muscles (semimembranosus and peroneus longus) had bipolar tuning curves, with two different directions of maximal activity, suggesting that these muscle can play different roles as part of different synergies, depending on translation direction. Muscle tuning curves tended to group into one of three regions in response to 12 different directions of perturbations. Two muscles [rectus femoris (RFM) and TFL] were maximally active in response to lateral surface translations. The remaining muscles clustered into one of two diagonal regions. The diagonal regions corresponded to the two primary directions of active horizontal force vector responses. Two muscles (RFM and adductor longus) were maximally active orthogonal to their predicted direction of maximal activity based on anatomic orientation. Some of the muscles in each of the synergic regions were not anatomic synergists, suggesting a complex central organization for recruitment of muscles. The results suggest that neither a simple reflex mechanism nor a fixed muscle synergy organization is adequate to explain the muscle activation patterns observed in this postural control task. Our results are consistent with a centrally mediated pattern of muscle latencies combined with peripheral influence on muscle magnitude. We suggest that a flexible continuum of muscle synergies that are modifiable in a task-dependent manner be used for equilibrium control in stance.

NASA Discipline Neuroscience↗

NASA NTRS1998

Analysis of xylem formation in pine by cDNA sequencing

Secondary xylem (wood) formation is likely to involve some genes expressed rarely or not at all in herbaceous plants. Moreover, environmental and developmental stimuli influence secondary xylem differentiation, producing morphological and chemical changes in wood. To increase our understanding of xylem formation, and to provide material for comparative analysis of gymnosperm and angiosperm sequences, ESTs were obtained from immature xylem of loblolly pine (Pinus taeda L.). A total of 1,097 single-pass sequences were obtained from 5' ends of cDNAs made from gravistimulated tissue from bent trees. Cluster analysis detected 107 groups of similar sequences, ranging in size from 2 to 20 sequences. A total of 361 sequences fell into these groups, whereas 736 sequences were unique. About 55% of the pine EST sequences show similarity to previously described sequences in public databases. About 10% of the recognized genes encode factors involved in cell wall formation. Sequences similar to cell wall proteins, most known lignin biosynthetic enzymes, and several enzymes of carbohydrate metabolism were found. A number of putative regulatory proteins also are represented. Expression patterns of several of these genes were studied in various tissues and organs of pine. Sequencing novel genes expressed during xylem formation will provide a powerful means of identifying mechanisms controlling this important differentiation pathway.

Non-NASA Center↗

DOE OSTI2018

Kinematic Flexibility Analysis: Hydrogen Bonding Patterns Impart a Spatial Hierarchy of Protein Motion

Elastic network models (ENMs) and constraint-based, topological rigidity analysis are two distinct, coarse-grained approaches to study conformational flexibility of macromolecules. In the two decades since their introduction, both have contributed significantly to insights into protein molecular mechanisms and function. However, despite a shared purpose of these approaches, the topological nature of rigidity analysis, and thereby the absence of motion modes, has impeded a direct comparison. We present an alternative, kinematic approach to rigidity analysis, which circumvents these drawbacks. We introduce a novel protein hydrogen bond network spectral decomposition, which provides an orthonormal basis for collective motions modulated by noncovalent interactions, analogous to the eigenspectrum of normal modes. The zero modes decompose proteins into rigid clusters identical to those from topological rigidity, while nonzero modes rank protein motions by their hydrogen bond collective energy penalty. Our kinematic flexibility analysis bridges topological rigidity theory and ENM, enabling a detailed analysis of motion modes obtained from both approaches. Analysis of a large, structurally diverse data set revealed that collectivity of protein motions, reported by the Shannon entropy, is significantly reduced for rigidity theory compared to normal mode approaches. Strikingly, kinematic flexibility analysis suggests that the hydrogen bonding network encodes a protein-fold specific, spatial hierarchy of motions, which goes nearly undetected in ENM. This hierarchy reveals distinct motion regimes that rationalize experimental and simulated protein stiffness variations. Kinematic motion modes highly correlate with reported crystallographic B factors and molecular dynamics simulations of adenylate kinase. A formal expression for changes in free energy derived from the spectral decomposition indicates that motions across nearly 40% of modes obey enthalpy–entropy compensation. Taken together, our results suggest that hydrogen bond networks have evolved to modulate protein structure and dynamics, which can be efficiently probed by kinematic flexibility analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Using Knowledge-Guided Machine Learning To Assess Patterns of Areal Change in Waterbodies across the Contiguous United States

Lake and reservoir surface areas are an important proxy for freshwater availability. Advancements in machine learning (ML) techniques and increased accessibility of remote sensing data products have enabled the analysis of waterbody surface area dynamics on broad spatial scales. However, interpreting the ML results remains a challenge. While ML provides important tools for identifying patterns, the resultant models do not include mechanisms. Thus, the “black-box” nature of ML techniques often lacks ecological meaning. Using ML, we characterized temporal patterns in lake and reservoir surface area change from 1984 to 2016 for 103,930 waterbodies in the contiguous United States. We then employed knowledge-guided machine learning (KGML) to classify all waterbodies into seven ecologically interpretable groups representing distinct patterns of surface area change over time. Many waterbodies were classified as having “no change” (43%), whereas the remaining 57% of waterbodies fell into other groups representing both linear and nonlinear patterns. This analysis demonstrates the potential of KGML not only for identifying ecologically relevant patterns of change across time but also for unraveling complex processes that underpin those changes.

58 GEOSCIENCES↗

NASA NTRS2003

High Resolution, Single-Step Patterning of Silica Aerogels

Three-dimensional metallic structures are fabricated with high spatial resolution in silica aerogels. In our method, silica hydrogels are prepared with a standard base-catalyzed route, and exchanged with an aqueous solution typically containing Ag' ions (1 M) and 2-propanol (0.2 M). The metal ions are reduced photolytically with a table-top ultraviolet lamp, or radiolytically, with a focused X-ray beam. We fabricated dots and lines as small as 30 x 70 km, protruding for several mm into the bulk of the materials. The hydrogels are eventually supercritically dried to yield aerogels, without any measurable change in the shape and spatial resolution of the lithographed structures. Transmission electron microscopy shows that illuminated regions are composed of Ag clusters with a size of several pm, separated by thin layers of silica.

Bertino, M. F.↗

DOE OSTI2015

Communication: Cosolvency and cononsolvency explained in terms of a Flory-Huggins type theory

Standard Flory-Huggins (FH) theory is utilized to describe the enigmatic cosolvency and cononsolvency phenomena for systems of polymers dissolved in mixed solvents. In particular, phase boundaries (specifically upper critical solution temperature spinodals) are calculated for solutions of homopolymers B in pure solvents and in binary mixtures of small molecule liquids A and C. The miscibility (or immiscibility) patterns for the ternary systems are classified in terms of the FH binary interaction parameters (χ{sub αβ}) and the ratio r = ϕ{sub A}/ϕ{sub C} of the concentrations ϕ{sub A} and ϕ{sub C} of the two solvents. The trends in miscibility are compared to those observed for blends of random copolymers (A{sub x}C{sub 1−x}) with homopolymers (B) and to those deduced for A/B/C solutions of polymers B in liquid mixtures of small molecules A and C that associate into polymeric clusters (A{sub p}C{sub q}){sub i}, (i = 1, 2, …, ∞). Although the classic FH theory is able to explain cosolvency and cononsolvency phenomena, the theory does not include a consideration of the mutual association of the solvent molecules and the competitive association between the solvent molecules and the polymer. These interactions can be incorporated in refinements of the FH theory, and the present paper provides a foundation for such extensions for modeling the rich thermodynamics of polymers in mixed solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Detecting Rain–Snow-Transition Elevations in Mountain Basins Using Wireless Sensor Networks

Here, to provide complementary information on the hydrologically important rain–snow-transition elevation in mountain basins, this study provides two estimation methods using ground measurements from basin-scale wireless sensor networks: one based on wet-bulb temperature T wet and the other based on snow-depth measurements of accumulation and ablation. With data from 17 spatially distributed clusters (178 nodes) from two networks, in the American and Feather River basins of California’s Sierra Nevada, we analyzed transition elevation during 76 storm events in 2014–18. A T wet threshold of 0.5°C best matched the transition elevation defined by snow depth. Transition elevations using T wet in upper elevations of the basins generally agreed with atmospheric snow level from radars located at lower elevations, while radar snow level was ~100 m higher due to snow-level lowering on windward mountainsides during orographic lifting. Diurnal patterns of the difference between transition elevation and radar snow level were observed in the American basin, related to diurnal ground-temperature variations. However, these patterns were not found in the Feather basin due to complex terrain and higher uncertainties in transition-elevation estimates. The American basin tends to exhibit 100-m-higher transition elevations than does the Feather basin, consistent with the Feather basin being about 1° latitude farther north. Transition elevation averaged 155 m higher in intense atmospheric river events than in other events; meanwhile, snow-level lowering was enhanced with a 90-m-larger difference between radar snow level and transition elevation. On-the-ground continuous observations from distributed sensor networks can complement radar data and provide important ground truth and spatially resolved information on transition elevations in mountain basins.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

FORESTR: Finding, Organizing, Representing, Explaining, Summarizing, and Thinning Random forests

Random forests have become popular models used for data driven predictions. As a result, random forests are currently used or being considered for high-consequence mission applications in national security, such as the prediction of yield from optical signals and malware detection. While random forests may provide accurate predictions, the complexity of the algorithm causes a lack of interpretability. Random forests are an ensemble of regression or decision trees. Individual regression and decision trees are interpretable, but ensembles are inherently difficult to interpret due to the compilation of many models. We aim to increase the interpretability of random forests by finding patterns in the ensemble of trees that can be used to “thin” (or remove) trees. As a starting point, in this report, we develop a new distance metric for quantifying the similarity between trees based on their topologies (i.e., shapes). We base the metric on a novel distance metric for graphs that is a proper mathematical distance, is invariant to transformations, has registration between graphs, and computes topological evolutions between graphs. We use the tree distance metric to compute tree statistics such as a “mean tree” and to identify clusters of trees. We apply the developed methodology to a toy dataset and a mission relevant product inspection dataset to demonstrate how the metric can provide insight into random forests. Furthermore, we discuss the limitations of the approach and ideas for future research into how the metric could be used as a thinning tool to develop less complex models.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1999

Dark Matter in the Universe and in the Galaxy

During the past four years, Prof. Kamionkowski and collaborators have made progress in research on the nature and distribution of dark-matter in the Universe and in the Galaxy, and on related topics in astrophysics and cosmology. We have made progress on research on the cosmic microwave background, large-scale structure, issues related to particle dark matter, and the gamma-ray-burst enigma. A significant fraction of the research supported by this ATP has been on the cosmic microwave background (CMB). Prof. Kamionkowski and collaborators showed how the polarization of the CMB could be used to detect long-wavelength gravitational waves, such as those produced by inflation. With Kosowsky, Prof. Kamionkowski calculated the amplitude of a stochastic gravitational-wave background that could be detected for a satellite experiment of a given sensitivity and angular resolution. They showed that polarization should improve the sensitivity oa MAP to these gravity waves, and that the Planck Surveyor should do even better. Prof. Kamionkowski, Caldwell, and a student calculated and illustrated the CMB temperature/polarization pattern produced by a single plane-wave gravitational wave. They calculated the amplitude of such a wave that would be detectable with MAP and Planck, and compared that with the sensitivity of traditional gravitational-wave detectors like LIGO and LISA. With Lue and Wang, the PI showed how parity violation from new high-energy physics could conceivably give rise to an observable signature in the CMB polarization. With Loeb, Prof. Kamionkowski showed how measurement of the polarization of CMB photons scattered by hot gas in a cluster could be used to determine the quadrupole moment of the CMB incident on that cluster. Prof. Kamionkowski and Jaffe calculated the amplitude of secondary anisotropies produced by scattering of CMB photons from reionized regions. Research has also been carried out on probing the large-scale distribution of mass in the Universe today, and on structure-formation theories. They investigated the possibility of determining the large-scale distribution of mass in the Universe via measurement of ellipticity-ellipticity correlations in the FIRST radio survey induced by weak gravitational lensing due to mass inhomogeneities along the line of sight. Dr. Summers, Prof. Kamionkowski, and a student investigated the distribution of protogalactic masses and angular momenta in an effort to understand how the luminosity function and angular-momentum distribution of disk galaxies arises from an initial power spectrum of density perturbations. Several projects related to the distribution and possible detection of dark matter in our Galactic halo were studied. The PI was involved in several projects involving the calculation of nuclear-reaction rates needed for stellar evolution and for predictions of solar-neutrino fluxes.

Kamionkowski, Marc↗

NASA NTRS2009

System for Automated Calibration of Vector Modulators

Vector modulators are used to impose baseband modulation on RF signals, but non-ideal behavior limits the overall performance. The non-ideal behavior of the vector modulator is compensated using data collected with the use of an automated test system driven by a LabVIEW program that systematically applies thousands of control-signal values to the device under test and collects RF measurement data. The technology innovation automates several steps in the process. First, an automated test system, using computer controlled digital-to-analog converters (DACs) and a computer-controlled vector network analyzer (VNA) systematically can apply different I and Q signals (which represent the complex number by which the RF signal is multiplied) to the vector modulator under test (VMUT), while measuring the RF performance specifically, gain and phase. The automated test system uses the LabVIEW software to control the test equipment, collect the data, and write it to a file. The input to the Lab - VIEW program is either user-input for systematic variation, or is provided in a file containing specific test values that should be fed to the VMUT. The output file contains both the control signals and the measured data. The second step is to post-process the file to determine the correction functions as needed. The result of the entire process is a tabular representation, which allows translation of a desired I/Q value to the required analog control signals to produce a particular RF behavior. In some applications, corrected performance is needed only for a limited range. If the vector modulator is being used as a phase shifter, there is only a need to correct I and Q values that represent points on a circle, not the entire plane. This innovation has been used to calibrate 2-GHz MMIC (monolithic microwave integrated circuit) vector modulators in the High EIRP Cluster Array project (EIRP is high effective isotropic radiated power). These calibrations were then used to create correction tables to allow the commanding of the phase shift in each of four channels used as a phased array for beam steering of a Ka-band (32-GHz) signal. The system also was the basis of a breadboard electronic beam steering system. In this breadboard, the goal was not to make systematic measurements of the properties of a vector modulator, but to drive the breadboard with a series of test patterns varying in phase and amplitude. This is essentially the same calibration process, but with the difference that the data collection process is oriented toward collecting breadboard performance, rather than the measurement of output from a network analyzer.

Lux, James↗

DOE OSTI2026

Mapping the Perseus galaxy cluster with XRISM: Gas kinematic features and their implications for turbulence

We present extended gas kinematic maps of the Perseus cluster based on a combination of five new XRISM/Resolve pointings observed in 2025 with four performance verification datasets from 2024, totaling a net exposure of 745 ks. To date, Perseus remains the only cluster that has been extensively mapped out to ≃0.7 r 2500 by XRISM/Resolve, while simultaneously offering sufficient spatial resolution to resolve gaseous substructures driven by mergers and active galactic nucleus (AGN) feedback. Our observations cover multiple radial directions and a broad range of dynamical scales, enabling us to characterize the kinematic properties of the intracluster medium up to a scale of ∼500 kpc. In the measurements, we detected high-velocity dispersions (≃300km s −1 ) in the eastern region of the cluster that are spatially coincident with the extended X-ray surface brightness excess and correspond to a nonthermal pressure fraction of ≃7 − 13%. The velocity field outside the AGN-dominant region can be effectively described by a single, large-scale kinematic driver based on the velocity structure function, which statistically favors an energy injection scale of at least a few hundred kpc. The estimated turbulent dissipation energy is comparable to the gravitational potential energy released by a recent merger, implying a significant role of turbulent cascade in the merger energy conversion. In the bulk velocity field, we observed a dipole-like pattern along the east-west direction with an amplitude of ≃ ± 200 − 300 km s −1 , indicating rotational motions induced by the recent merger event. This feature constrains the viewing direction to ≃30° −50° relative to the normal of the merger plane. Our hydrodynamic simulations suggest that Perseus has experienced at least two energetic mergers since redshift z ∼ 1, the most recent of which is associated with the radio galaxy IC310, in agreement with recent SRG/eROSITA findings. This study showcases exciting scientific opportunities for future missions with high-resolution spectroscopic capabilities (e.g., HUBS, LEM, and NewAthena).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Structured interactions drive abrupt transitions in the spatial organization of microbial communities

Bacteria possess diverse mechanisms to regulate their motility in response to environmental and physiological signals, enabling them to navigate complex habitats and adapt their behavior. Some of these mechanisms are species specific and enable cells to modulate their movement based on the ecological identity of neighboring species. Here, we introduce a model in which bacteria interact via local signals that either enhance or suppress the motility of neighboring cells depending on species type. Through large-scale simulations and a coarse-grained stochastic model, we demonstrate the emergence of a sharp transition driven by nucleation processes: increasing the density of motility-suppressing interactions drives the system from a fully mixed, motile phase to a state characterized by large, stationary bacterial clusters. Remarkably, in systems with a large number of interacting species, this transition can be triggered solely by altering the structure of the motility-regulation interaction matrix while maintaining species and interaction densities constant. In particular, we find that heterogeneous and modular interactions promote the transition more readily than homogeneous random ones. These findings add a dimension to the theory of motility-induced phase separation and contribute to the ongoing effort to understand microbial interactions, suggesting that structured, nonrandom ones may be key to reproducing commonly observed spatial patterns in microbial communities.

bacterial communities↗

NASA NTRS2018

In Situ Measurements of Angular-Dependent Light Scattering by Aerosols over the Contiguous United States

This work provides a synopsis of aerosol phase function (F (sub 11)) and polarized phase function (F (sub 12)) measurements made by the Polarized Imaging Nephelometer (PINeph) during the Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and the Deep Convection Clouds and Chemistry (DC3) field campaigns. In order to more easily explore this extensive dataset, an aerosol classification scheme is developed that identifies the different aerosol types measured during the deployments. This scheme makes use of ancillary data that include trace gases, chemical composition, aerodynamic particle size and geographic location, all independent of PI-Neph measurements. The PI-Neph measurements are then grouped according to their ancillary data classifications and the resulting scattering patterns are examined in detail. These results represent the first published airborne measurements of F (sub 11) and minus F (sub 12) divided by F (sub 11) for many common aerosol types. We then explore whether PI-Neph light-scattering measurements alone are sufficient to reconstruct the results of this ancillary data classification algorithm. Principal component analysis (PCA) is used to reduce the dimensionality of the multi-angle PI-Neph scattering data and the individual measurements are examined as a function of ancillary data classification. Clear clustering is observed in the PCA score space, corresponding to the ancillary classification results, suggesting that, indeed, a strong link exists between the angular scattering measurements and the aerosol type or composition. Two techniques are used to quantify the degree of clustering and it is found that in most cases the results of the ancillary data classification can be predicted from PI-Neph measurements alone with better than 85 percent recall. This result both emphasizes the validity of the ancillary data classification as well as the PI-Neph's ability to distinguish common aerosol types without additional information.

Aerosol phase function↗

NASA NTRS1990

Compound-specific isotopic analyses: a novel tool for reconstruction of ancient biogeochemical processes

Patterns of isotopic fractionation in biogeochemical processes are reviewed and it is suggested that isotopic fractionations will be small when substrates are large. If so, isotopic compositions of biomarkers will reflect those of their biosynthetic precursors. This prediction is tested by consideration of results of analyses of geoporphyrins and geolipids from the Greenhorn Formation (Cretaceous, Western Interior Seaway of North America) and the Messel Shale (Eocene, lacustrine, southern Germany). It is shown (i) that isotopic compositions of porphyrins that are related to a common source, but which have been altered structurally, cluster tightly and (ii) that isotopic differences between geolipids and porphyrins related to a common source are equal to those observed in modern biosynthetic products. Both of these observations are consistent with preservation of biologically controlled isotopic compositions during diagenesis. Isotopic compositions of individual compounds can thus be interpreted in terms of biogeochemical processes in ancient depositional environments. In the Cretaceous samples, isotopic compositions of n-alkanes are covariant with those of total organic carbon, while delta values for pristane and phytane are covariant with those of porphyrins. In this unit representing an open marine environment, the preserved acyclic polyisoprenoids apparently derive mainly from primary material, while the extractable, n-alkanes derive mainly from lower levels of the food chain. In the Messel Shale, isotopic compositions of individual biomarkers range from -20.9 to -73.4% vs PDB. Isotopic compositions of specific compounds can be interpreted in terms of origin from methylotrophic, chemautotrophic, and chemolithotrophic microorganisms as well as from primary producers that lived in the water column and sediments of this ancient lake.

Non-NASA Center↗

DOE OSTI2025

Structure-dependent clustering-to-declustering solute segregation transitions near disconnections

Grain-boundary disconnections, characterized by a step and a dislocation, are pervasive interfacial line defects that play a critical role in governing the properties and performance of nanocrystalline alloys. Although segregation of alloying elements is frequently observed at GB disconnections, the underlying mechanisms remain poorly understood, particularly at elevated temperatures and non-dilute conditions. In this study, we employ atomistic simulations to study the segregation behavior of Ag at various faulted disconnections in Cu as a model material system. Our results demonstrate a pronounced size and compactness effect on the segregation behavior: more compact faulted disconnection structures promote the formation of Ag segregation clusters due to a highly localized tensile field, whereas more spread faulted disconnection structures (i.e., with wider partial dislocation spacing) exhibit much weaker clustering tendencies. Furthermore, with increasing temperature, Ag clustering in small disconnections initially intensifies and then disappears, indicating a thermally driven transition from clustering to declustering segregation behavior.

Disconnections↗

DOE OSTI2021

Imaging antiferromagnetic domain fluctuations and the effect of atomic scale disorder in a doped spin-orbit Mott insulator

Correlated oxides can exhibit complex magnetic patterns. Understanding how magnetic domains form in the presence of disorder and their robustness to temperature variations has been of particular interest, but atomic scale insight has been limited. We use spin-polarized scanning tunneling microscopy to image the evolution of spin-resolved modulations originating from antiferromagnetic (AF) ordering in a spin-orbit Mott insulator perovskite iridate Sr 3 Ir 2 O 7 as a function of chemical composition and temperature. We find that replacing only several percent of lanthanum for strontium leaves behind nanometer-scale AF puddles clustering away from lanthanum substitutions preferentially located in the middle strontium oxide layer. Thermal erasure and reentry into the low-temperature ground state leads to a spatial reorganization of the AF puddles, which nevertheless maintain scale-invariant fractal geometry in each configuration. Our experiments reveal multiple stable AF configurations at low temperature and shed light onto spatial fluctuations of the AF order around atomic scale disorder in electron-doped Sr 3 Ir 2 O 7 .

36 MATERIALS SCIENCE↗