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At least 1,549 records · Page 86

Profiling of adrenocorticotropic hormone and arginine vasopressin in human pituitary gland and tumor thin tissue sections using droplet-based liquid-microjunction surface-sampling-HPLC–ESI-MS–MS

Described here are the results from the profiling of the proteins arginine vasopressin (AVP) and adrenocorticotropic hormone (ACTH) from normal human pituitary gland and pituitary adenoma tissue sections using a fully automated droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system for spatially resolved sampling, HPLC separation, and mass spectral detection. Excellent correlation was found between the protein distribution data obtained with this droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system and those data obtained with matrix assisted laser desorption ionization (MALDI) chemical imaging analyses of serial sections of the same tissue. The protein distributions correlated with the visible anatomic pattern of the pituitary gland. AVP was most abundant in the posterior pituitary gland region (neurohypophysis) and ATCH was dominant in the anterior pituitary gland region (adenohypophysis). The relative amounts of AVP and ACTH sampled from a series of ACTH secreting and non-secreting pituitary adenomas correlated with histopathological evaluation. ACTH was readily detected at significantly higher levels in regions of ACTH secreting adenomas and in normal anterior adenohypophysis compared to non-secreting adenoma and neurohypophysis. AVP was mostly detected in normal neurohypophysis as anticipated. This work demonstrates that a fully automated droplet-based liquid microjunction surface sampling system coupled to HPLC-ESI-MS/MS can be readily used for spatially resolved sampling, separation, detection, and semi-quantitation of physiologically-relevant peptide and protein hormones, such as AVP and ACTH, directly from human tissue. In addition, the relative simplicity, rapidity and specificity of the current methodology support the potential of this basic technology with further advancement for assisting surgical decision-making.

59 BASIC BIOLOGICAL SCIENCES↗

Schottky Diode Derating for Survivability in a Heavy Ion Environment

In this paper, we irradiate a number of silicon power Schottky diodes from a variety of manufacturers. The tested diodes represent a wide assortment of reverse voltages and forward currents. Additionally, we review correlations between single-event failures in Schottky diodes and device electrical parameters. The spatial locations of failures in the diode are discussed, as well as a possible explanation for why the failures occur. Based on these correlations to date, we propose a derating scheme for Schottky diodes flown in a heavy ion environment and suggest screening procedures for decreasing the risks of such failures.

Radiation effects↗

X-ray-diffraction and electrical-transport imaging of superconducting superhydride (La,Y)H 10

Understanding how microscopic structural domains govern macroscopic electronic properties is central to advancing hydride superconductors, yet such correlations remain poorly resolved under pressure. We report the synthesis and characterization of (La 0.9 Y 0.1 )H 10 superhydrides exhibiting coexisting cubic $Fm\bar{3}m$ and $P6_3/mmc$ hexagonal clathrate phases observed over the pressure range from 168 GPa down to 136 GPa. Using synchrotron-based X-ray diffraction imaging at the upgraded Advanced Photon Source, we spatially resolved μm-scale distributions of these phases, revealing structural inhomogeneity across the sample. Four-probe resistance measurements confirmed superconductivity with two distinct transitions: an onset at 244 K associated with the cubic phase and a second near 220 K linked to the hexagonal phase. Notably, resistance profiles collected from multiple current and voltage permutations showed variations in transition width and onset temperature that correlated with the spatial phase distribution. These findings demonstrate a direct connection between local structural domains and superconducting behavior.

Materials science↗

Uranium and Nickel Partitioning in a Contaminated Riparian Wetland

Uranium (U) and nickel (Ni) released 50 years ago have been immobilized in the Tims Branch wetlands located on the Savannah River Site in the United States. Sediments were collected from seven locations to identify the factors responsible for this attenuation. Ni and U contents in the solids were significantly correlated, suggesting that depositional as opposed to chemical processes contributed to their spatial distribution. Based on sequential extractions, 63 ± 16% of the U was partitioned into the organic fraction, whereas Ni was distributed between several sediment fractions. An inverse pH-organic matter (OM) correlation and positive correlations of OM with total U and organic-bound U/Ni suggest that increased OM preservation and binding to the mineral surfaces were likely responsible for Ni- and especially U-sediment retention (Tims Branch pH = 4.84 ± 0.68). EXAFS analysis indicated the predominance of U(VI) coordinated with clay minerals (~65%), together with ~35% coordinated to either OM (in areas with elevated OM levels) or iron oxides. The desorption-Kd coefficients of U (3972 ± 1370 L/kg) and Ni (30 ± 8 L/kg) indicate that dissolved Ni poses a greater long-term risk than dissolved U for migrating downstream. This study suggests that a delicate balance of geochemical properties controls whether wetlands behave as sinks or sources of contaminants.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Multi-qubit nanoscale sensing with entanglement as a resource

Nitrogen vacancy (NV) centres in diamond are widely deployed as local magnetic sensors, using single-qubit control to measure both time-averaged fields and noise with nanoscale spatial resolution. Moving beyond single qubits to multi-qubit control enables new sensing modalities such as measuring nonlocal spatiotemporal correlators or using entangled states to enhance measurement sensitivity. Here, in this work, we describe protocols for using optically unresolved NV centre pairs and nuclear spins as multi-qubit sensors for measuring correlated noise at nanometre length scales. For noninteracting NV centres, we implement a phase-cycling protocol that disambiguates magnetic correlations from variance fluctuations, leveraging the presence of a third qubit, a 13 C nucleus, to effect coherent single-NV spin flips and enable phase cycling even for co-aligned NV centres that are spectrally unresolved. For length scales around 10 nm, we create maximally entangled Bell states through dipole–dipole coupling between two NV centres and use these entangled states to directly read out the magnetic field correlation, rather than reconstructing it from independent measurements of unentangled NV centres. Importantly, this changes the scaling of sensitivity with readout noise from quadratic to linear. For conventional off-resonant readout of the NV centre spin state (for which the readout noise is roughly 30 times the quantum projection limit), this results in more than an order of magnitude improvement in sensitivity. Finally, we demonstrate methods for detecting high spatial- and temporal-resolution correlators with pairs of strongly interacting NV centres.

condensed-matter physics↗

Computational Ghost Imaging for Remote Sensing

This work relates to the generic problem of remote active imaging; that is, a source illuminates a target of interest and a receiver collects the scattered light off the target to obtain an image. Conventional imaging systems consist of an imaging lens and a high-resolution detector array [e.g., a CCD (charge coupled device) array] to register the image. However, conventional imaging systems for remote sensing require high-quality optics and need to support large detector arrays and associated electronics. This results in suboptimal size, weight, and power consumption. Computational ghost imaging (CGI) is a computational alternative to this traditional imaging concept that has a very simple receiver structure. In CGI, the transmitter illuminates the target with a modulated light source. A single-pixel (bucket) detector collects the scattered light. Then, via computation (i.e., postprocessing), the receiver can reconstruct the image using the knowledge of the modulation that was projected onto the target by the transmitter. This way, one can construct a very simple receiver that, in principle, requires no lens to image a target. Ghost imaging is a transverse imaging modality that has been receiving much attention owing to a rich interconnection of novel physical characteristics and novel signal processing algorithms suitable for active computational imaging. The original ghost imaging experiments consisted of two correlated optical beams traversing distinct paths and impinging on two spatially-separated photodetectors: one beam interacts with the target and then illuminates on a single-pixel (bucket) detector that provides no spatial resolution, whereas the other beam traverses an independent path and impinges on a high-resolution camera without any interaction with the target. The term ghost imaging was coined soon after the initial experiments were reported, to emphasize the fact that by cross-correlating two photocurrents, one generates an image of the target. In CGI, the measurement obtained from the reference arm (with the high-resolution detector) is replaced by a computational derivation of the measurement-plane intensity profile of the reference-arm beam. The algorithms applied to computational ghost imaging have diversified beyond simple correlation measurements, and now include modern reconstruction algorithms based on compressive sensing.

Erkmen, Baris I.↗

Optical Correlation of Images With Signal-Dependent Noise Using Constrained-Modulation Filter Devices

Images with signal-dependent noise present challenges beyond those of images with additive white or colored signal-independent noise in terms of designing the optimal 4-f correlation filter that maximizes correlation-peak signal-to-noise ratio, or combinations of correlation-peak metrics. Determining the proper design becomes more difficult when the filter is to be implemented on a constrained-modulation spatial light modulator device. The design issues involved for updatable optical filters for images with signal-dependent film-grain noise and speckle noise are examined. It is shown that although design of the optimal linear filter in the Fourier domain is impossible for images with signal-dependent noise, proper nonlinear preprocessing of the images allows the application of previously developed design rules for optimal filters to be implemented on constrained-modulation devices. Thus the nonlinear preprocessing becomes necessary for correlation in optical systems with current spatial light modulator technology. These results are illustrated with computer simulations of images with signal-dependent noise correlated with binary-phase-only filters and ternary-phase-amplitude filters.

Downie, John D.↗

Spatial DIC Errors due to Pattern-Induced Bias and Grey Level Discretization

Digital image correlation (DIC) is an optical metrology method widely used in experimental mechanics for full-field shape, displacement and strain measurements. The required strain resolution for engineering applications of interest mandates DIC to have a high image displacement matching accuracy, on the order of 1/100th of a pixel, which necessitates an understanding of DIC errors. In this paper, we examine two spatial bias terms that have been almost completely overlooked. They cause a persistent offset in the matching of image intensities and thus corrupt DIC results. We name them pattern-induced bias (PIB), and intensity discretization bias (IDB). We show that the PIB error occurs in the presence of an undermatched shape function and is primarily dictated by the underlying intensity pattern for a fixed displacement field and DIC settings. The IDB error is due to the quantization of the gray level intensity values in the digital camera. In this paper we demonstrate these errors and quantify their magnitudes both experimentally and with synthetic images.

47 OTHER INSTRUMENTATION↗

Thermal evolution of quasi-one-dimensional spin correlations within the anisotropic triangular lattice of α - NaMnO 2

Magnetic order on the spatially anisotropic triangular lattice of α-NaMnO 2 is studied via neutron diffraction measurements. The transition into a commensurate, collinear antiferromagnetic ground state with k=(0.5,0.5,0) was found to occur below T N =22 K. Above this temperature, the transition is preceded by the formation of a coexisting, short-range ordered, incommensurate state below TIC=45 K whose two-dimensional propagation vector evolves toward k=(0.5,0.5) as the temperature approaches T N . At high temperatures (T>T IC ), quasielastic scattering reveals one-dimensional spin correlations along the nearest-neighbor Mn-Mn “chain direction” of the MnO 6 planes. Here, our data are consistent with the predictions of a mean-field model of Ising-like spins on an anisotropic triangular lattice, as well as the predominantly one-dimensional Heisenberg spin Hamiltonian reported for this material.

36 MATERIALS SCIENCE↗

Visual Analytics of Crosstalk in Quantum Hardware

Crosstalk remains a major obstacle to building scalable and fault-tolerant quantum computers. Conventional diagnostic techniques-often based on numerical simulation or statistical modeling-struggle to scale with hardware complexity and offer limited interpretability. In this work, we present a visual analytics framework for diagnosing qubit crosstalk using lightweight, circuit-based models integrated with an interactive user interface. Our approach quantifies correlations between active and idle qubits under parameterized single- and twoqubit operations, enabling detection of both spatial and gateinduced crosstalk. The system incorporates qubit topology and gate performance data to support sector-based exploration and correlation mapping. This tool assists users in identifying correlated error sources, informing qubit placement strategies, and guiding noise-aware circuit design.

Chae, Junghoon [ORNL] (ORCID:0000000206016746)↗

Reimagining full wave rf quasilinear theory in a tokamak

The velocity dependent resonant interaction of particles with applied radio frequency (rf) waves during heating and current drive in the presence of pitch angle scattering collisions gives rise to narrow collisional velocity space boundary layers that dramatically enhance the role of collisions as recently shown by Catto (J. Plasma Phys., vol. 86, 815860302, 2020). The behavior is a generalization of the narrow collisional boundary layer that forms during Landau damping as found by Johnston (Phys. Fluids, vol. 14, 1971, pp. 2719-2726) and Auerbach (Phys. Fluids, vol. 20, 1977, pp. 1836-1844). For a wave of parallel wave number k|| interacting with weakly collisional plasma species of collision frequency ν and thermal speed vth , the effective collision frequency becomes of order ν(k_||v_th /ν)^2/3>> ν . The narrow boundary layers that arise because of the diffusive nature of the collisions allows a physically meaningful wave-particle interaction time to be defined that is the inverse of this effective collision frequency. The collisionality implied by the narrow boundary layer results in changes in the standard quasilinear treatment of applied rf fields in tokamaks while remaining consistent with causality. These changes occur because successive poloidal interactions with the rf are correlated in tokamak geometry and because the resonant velocity space dependent interactions are controlled by the spatial and temporal behavior of the perturbed full wave fields rather than just the spatially local Landau and Doppler shifted cyclotron wave-particle resonance condition associated with unperturbed motion of the particles. The correlation of successive poloidal circuits of the tokamak leads to the appearance in the quasilinear operator of transit averaged resonance conditions localized in velocity space boundary layers that maintain negative definite entropy production.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Patterns in wetland microbial community composition and functional gene repertoire associated with methane emissions

Wetland restoration on peat islands previously drained for agriculture has potential to reverse land subsidence and sequester atmospheric carbon dioxide as peat accretes. However, the emission of methane could potentially offset the greenhouse gas benefits of captured carbon. As microbial communities play a key role in governing wetland greenhouse gas fluxes, we are interested in how microbial community composition and functions are associated with wetland hydrology, biogeochemistry, and methane emission, which is critical to modeling the microbial component in wetland methane fluxes and to managing restoration projects for maximal carbon sequestration. Here, we couple sequence-based methods with biogeochemical and greenhouse gas measurements to interrogate microbial communities from a pilot-scale restored wetland in the Sacramento-San Joaquin Delta of California, revealing considerable spatial heterogeneity even within this relatively small site. A number of microbial populations and functions showed strong correlations with electron acceptor availability and methane production; some also showed a preference for association with plant roots. Marker gene phylogenies revealed a diversity of major methane-producing and -consuming populations and suggested novel diversity within methanotrophs. Methanogenic archaea were observed in all samples, as were nitrate-, sulfate-, and metal-reducing bacteria, indicating that no single terminal electron acceptor was preferred despite differences in energetic favorability and suggesting spatial microheterogeneity and microniches. Notably, methanogens were negatively correlated with nitrate-, sulfate-, and metal-reducing bacteria and were most abundant at sampling sites with high peat accretion and low electron acceptor availability, where methane production was highest. Wetlands are the largest nonanthropogenic source of atmospheric methane but also a key global carbon reservoir. Characterizing belowground microbial communities that mediate carbon cycling in wetlands is critical to accurately predicting their responses to changes in land management and climate. Here, we studied a restored wetland and revealed substantial spatial heterogeneity in biogeochemistry, methane production, and microbial communities, largely associated with the wetland hydraulic design. We observed patterns in microbial community composition and functions correlated with biogeochemistry and methane production, including diverse microorganisms involved in methane production and consumption. We found that methanogenesis gene abundance is inversely correlated with genes from pathways exploiting other electron acceptors, yet the ubiquitous presence of genes from all these pathways suggests that diverse electron acceptors contribute to the energetic balance of the ecosystem. These investigations represent an important step toward effective management of wetlands to reduce methane flux to the atmosphere and enhance belowground carbon storage.

54 ENVIRONMENTAL SCIENCES↗

Correlative multimodal chemical imaging via machine learning

Machine learning approach can combine mass spectral imaging (MSI) techniques, one with low spatial resolution but intact molecular spectra and the other with nanometer spatial resolution but fragmented molecular signatures, to predict molecular MSI spectra with submicron spatial resolution. The machine learning approach can perform transformations on the spectral image data of the two MSI techniques to reduce dimensionality, and using a correlation technique, find relationships between the transformed spectral image data. The determined relationships can be used to generate MSI spectra of desired resolution.

Ovchinnikova, Olga S.↗

Mesoscale Magnetostructural Phase Separation in Fe‐deficient Fe 5 GeTe 2

Two-dimensional van der Waals ferromagnet Fe 5-x GeTe 2 (F5GT) is promising for spintronic applications due to its high Curie temperature, layered structure, and ability to host complex magnetic textures. However, the origin of its sample-dependent magnetic anisotropy remains unclear, hindering control of its magnetic behavior. Here, we use spatially resolved cryogenic scanning transmission electron microscopy (STEM) to correlatively map magnetism, lattice structure, and chemistry across atomic-to-micron scales. We reveal that only mesoscale, not nanoscale, inclusions of a Fe-deficient secondary phase significantly modify magnetic behavior, establishing a previously unrecognized critical length scale. This phase separation, induced by quenching, leads to in-plane magnetic anisotropy, while slow cooling confines separation to a few nanometers and preserves out-of-plane anisotropy. These findings reconcile prior inconsistencies and establish a predictive framework for tuning magnetism in F5GT through thermal processing, with broader implications for controlling anisotropy in other two-dimensional magnetic materials.

2D ferromagnets↗

Leaf 13 C data constrain the uncertainty of the carbon dynamics of temperate forest ecosystems

Stable carbon isotope discrimination occurred in plant biophysical and biogeochemical processes can help understand plant physiology and soil biogeochemistry with respect to carbon cycling. Here, we incorporated the photosynthetic carbon isotope discrimination into a process-based land surface model (iTEM) to test if stable carbon isotope composition (δ 13 C) can impose additional constraint on model parameters. Sequential data assimilation was implemented at six eddy covariance flux tower sites using carbon flux observations including gross primary productivity (GPP) and net ecosystem exchange (NEE) with and without considering foliar δ 13 C (δ 13 C f ) measurement constraints, respectively. Our model-data fusion showed that δ 13 C f can provide useful constraint on photosynthetic (V cmax25 , the maximum rate of carboxylation at 25°C) and stomatal (g1, the slope of stomatal function) parameters as well as the posterior carbon fluxes. When including δ 13 C f measurement, g1 spatially varies among the six sites and is significantly correlated with annual precipitation. We incorporated the statistical relationship between g1 and annual precipitation into iTEM, which is then used to quantify the regional carbon dynamic in temperate forest ecosystems of the Northern Hemisphere. Compared with the simulation only conditioned on carbon flux observations, regional carbon flux estimations performed slightly better against the FLUXCOM products and the uncertainties of modeled carbon fluxes were reduced by 27%. Our study demonstrated that δ 13 C f data constrains carbon flux uncertainties across space.

54 ENVIRONMENTAL SCIENCES↗

Process control-enabled mitigation of microstructural and plastic heterogeneities in additively manufactured Grade 91 steel

Synergizing wire arc-directed energy deposition (WA-DED) additive manufacturing (AM) with particle-strengthened creep strength-enhanced ferritic (CSEF) steels enables fabrication and repair of critical power-plant components. Investigations focused on fusion-welded particle-strengthened CSEF steels, such as Grade 91 steel, have linked microstructurally heterogeneous regions—forming due to heat affected zones (HAZ)—with premature failure during elevated temperature service. Fusion-based AM, including WA-DED, likewise generates microstructurally and plastically heterogeneous regions due to spatiotemporally varying thermokinetics during deposition. However, works investigating such microstructural heterogeneities, their implications for mechanical behavior, and strategies to mitigate their formation remain scarce. This work identifies microstructurally and plastically heterogeneous regions within the WA-DED-processed Grade 91 steel. Spatial microhardness variations in the as-fabricated specimen correlate with the variation in the attributes of grain, martensitic microstructure, and precipitates across the fusion zone and HAZ. Digital image correlation-enabled tensile tests performed at 500 °C revealed pronounced deformation localization and a wave-like strain distribution, with wavelength close to the melt pool depth, indicating susceptibility of the as-fabricated components to premature creep failure. Such heterogeneity in microstructural and mechanical behavior was attributed to recurring solid-state phase transformations. Subsequently, an interlayer temperature control strategy was implemented, wherein maintaining interlayer temperature above the martensitic start temperature mitigated the heterogeneous microstructural and plastic response in the as-fabricated condition. Findings open pathways to achieving deformation-localization- and creep-resistant microstructures in WA-DED fabricated particle-strengthened CSEF steel components, reducing reliance on post-welding heat treatments—conventionally required to enhance creep resistance—and enabling on-demand, short lead-time fabrication of next-generation power-plant components.

Heat affected zones↗

Considering interplay between multiple physical phenomena to elucidate single crystal-like texture, phase transformations, and mechanical behavior of directed energy deposited SS316L

A widespread implementation of large scale additive manufacturing (AM) processes, such as wire arc-directed energy deposition (WA-DED) AM can transform the current manufacturing supply chain networks. Naturally, such implementation requires control of the microstructural attributes, such as texture and phase evolution in the processed alloys. Currently, the texture evolution in fusion-based AM (F-BAM) processes is majorly rationalized by the phenomena occurring only during solidification. However, such rationalization is insufficient for understanding the evolution of primary and secondary crystallographic orientations, and consequently, fails to offer a comprehensive understanding and control of overall texture in F-BAM processed alloys. To this end, we report a single crystal (SX)-like texture in WA-DED processed SS316L for the first time. Furthermore, we assess the physical phenomena that may lead to such unique microstructural evolution during WA-DED AM. Subsequently, using microstructural characterization spanning the build height and thermomechanical simulations we investigate the effect of competitive growth and epitaxial growth occurring during solidification and thermally induced plastic deformation occurring post solidification on the overall texture of WA-DED processed SS316L. A spatial variation in solidification pathway is also established and correlated with variation in undercoolings across the build. Tensile tests revealed a strong orientation dependence of deformation mechanisms with over 110% elongation to failure of specimens deformed along <011>. Such anisotropy is rationalized using Schmid's analysis of dislocation slip and deformation twinning. Importantly, overall, the mechanisms outlined in this work will facilitate an enhanced understanding and subsequent control of texture evolution, solidification behavior and mechanical behavior of WA-DED processed steels.

36 MATERIALS SCIENCE↗

Strength statistics of single crystals and metallic glasses under small stressed volumes

It has been well documented that plastic deformation of crystalline and amorphous metals/alloys shows a general trend of “smaller is stronger”. The majority of the experimental and modeling studies along this line have been focused on finding and reasoning the scaling slope or exponent in the logarithmic plot of strength versus size. In contrast to this view, here we show that the universal picture should be the thermally activated nucleation mechanisms in small stressed volume, the stochastic behavior as to find the weakest links in intermediate sizes of the stressed volume, and the convolution of these two mechanisms with respect to variables such as indenter radius in nanoindentation pop-in, crystallographic orientation, pre-strain level, sample length as in uniaxial tests, and others. Furthermore, experiments that cover the entire spectrum of length scales and a unified model that treats both thermal activation and spatial stochasticity have discovered new perspectives in understanding and correlating the strength statistics in a vast of observations in nanoindentation, micro-pillar compression, and fiber/whisker tension tests of single crystals and metallic glasses.

36 MATERIALS SCIENCE↗