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At least 1,261 records · Page 70

A biomimetic eye with a hemispherical perovskite nanowire array retina

Human eyes possess exceptional image-sensing characteristics such as an extremely wide field of view, high resolution and sensitivity with low aberration1. Biomimetic eyes with such characteristics are highly desirable, especially in robotics and visual prostheses. However, the spherical shape and the retina of the biological eye pose an enormous fabrication challenge for biomimetic devices2,3. In this paper, we present an electrochemical eye with a hemispherical retina made of a high-density array of nanowires mimicking the photoreceptors on a human retina. The device design has a high degree of structural similarity to a human eye with the potential to achieve high imaging resolution when individual nanowires are electrically addressed. Additionally, we demonstrate the image-sensing function of our biomimetic device by reconstructing the optical patterns projected onto the device. This work may lead to biomimetic photosensing devices that could find use in a wide spectrum of technological applications.

42 ENGINEERING↗

Spectral function of the $J_1$ – $J_2$ Heisenberg model on the triangular lattice

Spectral probes, such as neutron scattering, are crucial for characterizing excitations in quantum many-body systems and the properties of quantum materials. Among the most elusive phases of matter are quantum spin liquids, which have no long-range order even at zero temperature and host exotic fractionalized excitations with nontrivial statistics. These phases can occur in frustrated quantum magnets, such as the paradigmatic Heisenberg model with nearest- and next-nearest-neighbor exchange interactions on the triangular lattice, the so-called $J_1$ – $J_2$ model. In this work, we compute the spectral function using large-scale matrix product state simulations across the three different phases of this model's phase diagram, including a quantum spin-liquid phase at intermediate $J_2$/$J_1$. Despite a plethora of theoretical and experimental studies, the exact nature of this phase is still contested, with the dominant candidates being a gapped $\mathbb{Z}_2$, a gapless U(1) Dirac, and a spinon Fermi surface quantum spin-liquid state. We find a V-shaped spectrum near the center of the Brillouin zone ($Γ$ point), a key signature of a spinon Fermi surface, observed in prior neutron scattering experiments. However, we find a small gap near the $Γ$ point, ruling out such a phase. Furthermore, we find localized gapless excitations at the corner of the Brillouin zone boundary (K point) and the middle of the edge of the Brillouin zone boundary (M point), ruling out the gapped $\mathbb{Z}_2$ spin-liquid phase. Here, our results imply that the intermediate spin-liquid phase is a gapless $U(1)$ Dirac spin liquid, and provide clear signatures to detect this phase in future neutron scattering experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

OpenCSP v.1.0

SAND2024-08987O OpenCSP analyzes and improves the performance of optical mirrors that reflect sunlight and concentrate it onto a receiver. The algorithms in this library analyze the flow of light from an original source—such as the sun—reflecting off one or more mirrors, and onto a receiver, optical screen, or camera. OpenCSP also analyzes optical systems using other techniques, such as shape or slope comparison. The software calculates aggregate properties of the optical system, such as its efficiency, manufacturing error, pointing control error, expected performance, and other useful parameters. OpenCSP also includes high-level tools, such as Open SOFAST, a program that obtains high-resolution measurement of CSP mirrors, full heliostats, and other CSP collectors. OpenCSP supports producing meaningful output data to help CSP designers and field operators improve the performance of their systems. OpenCSP also includes classes and functions that support these calculations, including input utilities, analysis output libraries, geometric constraint analysis for drone flight planning, and more. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Brost, Randolph↗

Crowdsourcing biocuration: The Community Assessment of Community Annotation with Ontologies (CACAO)

Experimental data about gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying gene function, especially within model organisms. Unprecedented expansion of the scientific literature and validation of the predicted proteins have increased both data value and the challenges of keeping pace. Capturing literature-based functional annotations is limited by the ability of biocurators to handle the massive and rapidly growing scientific literature. Within the community-oriented wiki framework for GO annotation called the Gene Ontology Normal Usage Tracking System (GONUTS), we describe an approach to expand biocuration through crowdsourcing with undergraduates. This multiplies the number of high-quality annotations in international databases, enriches our coverage of the literature on normal gene function, and pushes the field in new directions. From an intercollegiate competition judged by experienced biocurators, Community Assessment of Community Annotation with Ontologies (CACAO), we have contributed nearly 5,000 literature-based annotations. Many of those annotations are to organisms not currently well-represented within GO. Over a 10-year history, our community contributors have spurred changes to the ontology not traditionally covered by professional biocurators. The CACAO principle of relying on community members to participate in and shape the future of biocuration in GO is a powerful and scalable model used to promote the scientific enterprise. It also provides undergraduate students with a unique and enriching introduction to critical reading of primary literature and acquisition of marketable skills.

59 BASIC BIOLOGICAL SCIENCES↗

Machine learning approach to pattern recognition in nuclear dynamics from the ab initio symmetry-adapted no-core shell model

A novel machine learning approach is used to provide further insight into atomic nuclei and to detect orderly patterns amid a vast data of large-scale calculations. The method utilizes a neural network that is trained on ab initio results from the symmetry-adapted no-core shell model (SA-NCSM) for light nuclei. We show that the SA-NCSM, which expands ab initio applications up to medium-mass nuclei by using dominant symmetries of nuclear dynamics, can reach heavier nuclei when coupled with the machine learning approach. In particular, we find that a neural network trained on probability amplitudes for s- and p-shell nuclear wave functions not only predicts dominant configurations for heavier nuclei but in addition, when tested for the 20 Ne ground state, accurately reproduces the probability distribution. The non-negligible configurations predicted by the network provide an important input to the SA-NCSM for reducing ultralarge model spaces to manageable sizes that can be, in turn, utilized in SA-NCSM calculations to obtain accurate observables. The neural network is capable of describing nuclear deformation and is used to track the shape evolution along the 20-42 Mg isotopic chain, suggesting a shape coexistence that is more pronounced toward the very neutron-rich isotopes. We provide first descriptions of the structure and deformation of 24 Si and 40 Mg of interest to x-ray burst nucleosynthesis, and even of the extremely heavy nuclei such as 166,168 Er and 236 U, that build on first-principles considerations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Destabilizing a Social Network Model via Intrinsic Feedback Vulnerabilities

Social influence plays a significant role in shaping individual sentiments and actions, particularly in a world of ubiquitous digital interconnection. The rapid development of generative artificial intelligence (AI) has given rise to well-founded concerns regarding the potential implementation of radicalization techniques in social media. Motivated by these developments, we present a case study investigating the effects of small but intentional perturbations on a simple social network. We employ Taylor's classic model of social influence and tools from robust control theory (most notably the Dynamical Structure Function (DSF)), to identify perturbations that qualitatively alter the system's behavior while remaining as unobtrusive as possible. We examine two such scenarios: perturbations to an existing link and perturbations that introduce a new link to the network. In each case, we identify destabilizing perturbations of minimal norm and simulate their effects. Remarkably, we find that small but targeted alterations to network structure may lead to the radicalization of all agents, exhibiting the potential for large-scale shifts in collective behavior to be triggered by comparatively minuscule adjustments in social influence. Given that this method of identifying perturbations that are innocuous yet destabilizing applies to any suitable dynamical system, our findings emphasize a need for similar analyses to be carried out on real systems (e.g., real social networks), to identify the places where such dynamics may already exist.

Rogers, Lane [ORNL]↗

A Novel Experimental Approach to Understand the Transport of Nanodrugs

Nanoparticle-based drugs offer attractive advantages like targeted delivery to the diseased site and size and shape-controlled properties. Therefore, understanding the particulate flow of the nanodrugs is important for effective delivery, accurate prediction of required dosage, and developing efficient drug delivery platforms for nanodrugs. In this study, the transport of nanodrugs including flow velocity and deposition is investigated using three model metal oxide nanodrugs of different sizes including iron oxide, zinc oxide, and combined Cu-Zn-Fe oxide synthesized via a modified polyol approach. The hydrodynamic size, size, morphology, chemical composition, crystal phase, and surface functional groups of the water-soluble nanodrugs were characterized via dynamic light scattering, transmission electron microscopy, scanning electron microscopy-energy dispersive X-ray, X-ray diffraction, and fourier transform infrared spectroscopy, respectively. Two different biomimetic flow channels with customized surfaces are developed via 3D printing to experimentally monitor the velocity and deposition of the different nanodrugs. A diffusion dominated mechanism of flow is seen in size ranges 92 nm to 110 nm of the nanodrugs, from the experimental velocity and mass loss profiles. The flow velocity analysis also shows that the transport of nanodrugs is controlled by sedimentation processes in the larger size ranges of 110–302 nm. However, the combined overview from experimental mass loss and velocity trends indicates presence of both diffusive and sedimentation forces in the 110–302 nm size ranges. It is also discovered that the nanodrugs with higher positive surface charges are transported faster through the two test channels, which also leads to lower deposition of these nanodrugs on the walls of the flow channels. The results from this study will be valuable in realizing reliable and cost-effective in vitro experimental approaches that can support in vivo methods to predict the flow of new nanodrugs.

36 MATERIALS SCIENCE↗

Systematic analysis of melt pool dynamics in laser processing of mixed powder feedstocks

Functionally graded materials (FGMs) fabricated via additive manufacturing of blended powders offer the potential to spatially tailor properties for new technologies, such as fusion first-wall systems, turbine blades, and spacecraft. However, processing these materials is difficult due to the multiplicity of processing parameters to optimize, all of which must be changed as substrate material, powder feedstock compositions, and melt pool dynamics evolve. Here, this work systematically evaluates the qualitative and quantitative effects of these variables on the melt pool size, shape, composition, and particle distribution in an exemplar Ti-Ta system, and connects the experimental results to Marangoni flow behavior and phenomena observed in other systems. Increasing laser power linearly increases melt pool size and layer thickness, driving engineering considerations such as part/geometrical tolerances. Decreasing laser velocity changes the melt pool shape from lenticular to convex and reduces chemical homogeneity due to extreme thermal and compositional gradients between the melt pool center and boundaries. Thermophysical property differences between the powder feedstock and substrate material, as well as the directionality of the gradient, affect dilution and melt pool dynamics, which in turn affect the melt pool boundary characteristics, shape, and uniformity. Mixed powder feedstocks of intermediate compositions do not behave according to linear interpolations between single-material endpoints, instead building taller and wider melt pools. As such, it is recommended to quantify process maps for at least one intermediate composition in the FGM or multi-material system of interest to ensure optimized processing parameters, predictable melt pool sizes and shapes, and compositional and spatial precision.

Dissimilar↗

Versatile Liquid Crystal Elastomer Formulations Using Amine-Acrylate Chemistry and Processing for Advanced Manufacturing

This study aims to tune rheological properties of liquid crystal elastomers (LCEs) through a strategic approach, leveraging the differing reaction rates of thiols and primary and secondary amines with acrylate monomers or the inclusion of processing additives to enable amenability to advanced manufacturing. We found that varying the time of oligomerization at elevated temperatures of amine-functional monomers with acrylate-functional monomers enabled simple control of rheological properties. Additionally, we could also control rheological properties by introducing reinforcing fillers or organic solvents. By varying the oligomerization conditions, we achieved a broad range of viscosities, from 1.1 Pa s to 560 Pa s as measured at 60 °C. When the rheological properties were varied through the incorporation of various solid and liquid inclusions, viscosities could range from less than 1 Pa s to nearly 1000 Pa s when measured at 60 °C. The shape morphing capabilities that are intrinsic to LCEs and the mechanical properties were also characterized. Here, we find that the oligomerization conditions and the addition of fillers influence shape morphing and energy absorption, as characterized by the stress–strain characteristics, further suggesting their potential to be used in energy dissipation applications where performance can be turned. Last, we demonstrate how the range of accessible rheological properties grants formulations amenable to various advanced manufacturing techniques.

Liquid chromatography↗

Ice Supersaturation Variability in Cirrus Clouds: Role of Vertical Wind Speeds and Deposition Coefficients

Abstract Aircraft measurements reveal ice supersaturation statistics in cirrus (ISSs) with broad maxima around ice saturation and pronounced variance. In this study, processes shaping ISSs in midlatitude and tropical upper tropospheric conditions are systematically investigated. Water vapor deposition and sublimation of size‐resolved ice crystal populations are simulated in an air parcel framework. Mesoscale temperature fluctuations (MTFs) due to gravity waves force the temporal evolution of supersaturation. Various levels of background wave forcing and cirrus thickness are distinguished in stochastic ensemble simulations. Kinetic limitations to ice mass growth are brought about by supersaturation‐dependent deposition coefficients that represent efficient and inefficient growth modes as a function of ice crystal size. The simulations identify a wide range of deposition coefficients in cirrus, but most values stay above 0.01 such that kinetic limitations to water uptake remain moderate. Supersaturation quenching times are long, typically 0.5–2 hr. The wave forcing thus causes a remarkably large variability in ISSs and cirrus microphysical properties except in the thickest cirrus, producing ensemble‐mean ISSs in line with in‐situ measurements. ISS variance is controlled by MTFs and increases with decreasing cirrus integral radii. In comparison, the impact of ice crystal growth rates on ISSs is small. These results contribute to efforts directed at identifying and solving issues associated with ice‐supersaturated areas and non‐equilibrium cirrus physics in global models.

Meteorology & Atmospheric Sciences↗

Half-Life and Precision Shape Measurement of the 2⁢𝜈⁢𝛽⁢𝛽 Decay of 130 Te

Here, we present a new measurement of the 2⁢𝜈⁢𝛽⁢𝛽 half-life of 130 Te (𝑇$^{2⁢𝜈}_{1/2}$) using the first complete model of the CUORE data, based on 1038 kg yr of collected exposure. Thanks to optimized data selection, we achieve a factor of two improvement in precision, obtaining 𝑇$^{2⁢𝜈}_{1/2}$ = (9.32⁢$^{+0.05}_{−0.04}$⁢stat⁢ $^{+0.07}_{−0.07}$⁢syst)×10 20 yr. The signal-to-background ratio is increased by 70% compared to our previous results, enabling the first application of the improved 2⁢𝜈⁢𝛽⁢𝛽 formalism to 130 Te . Within this framework, we determine a credibility interval for the effective axial coupling in the nuclear medium as a function of nuclear matrix elements. We also extract values for the higher-order nuclear matrix element ratios: second-to-first and third-to-first. The second-to-first ratio agrees with nuclear model predictions, while the third-to-first ratio deviates from theoretical expectations. These findings provide essential tests of nuclear models and key inputs for future 0⁢𝜈⁢𝛽⁢𝛽 searches.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Production cross sections of light and charmed mesons in 𝑒 + ⁢𝑒 − annihilation near 10.58 GeV

We report measurements of production cross sections for 𝜌 + , 𝜌 0 , 𝜔, 𝐾* + , 𝐾* 0 , 𝜙, 𝜂, 𝐾$^0_𝑆$, 𝑓 0 ⁡(980), 𝐷 + , 𝐷 0 , 𝐷$^+_𝑠$, 𝐷* + , 𝐷* 0 , and 𝐷*$^+_𝑠$ in 𝑒 + ⁢𝑒 − collisions at a center-of-mass energy near 10.58 GeV. The data were recorded by the Belle experiment, consisting of 571 fb −1 at 10.58 GeV and 74 fb −1 at 10.52 GeV. Production cross sections are extracted as a function of the fractional hadron momentum 𝑥 𝑝 . The measurements are compared to pythia Monte Carlo generator predictions with various fragmentation settings, including those that have increased fragmentation into vector mesons over pseudoscalar mesons. The cross sections measured for light hadrons are consistent with no additional increase of vector over pseudoscalar mesons. The charmed-meson cross sections are compared to earlier measurements—when available—including older Belle results, which they supersede. They are in agreement before application of an improved initial-state radiation correction procedure that causes slight changes in their 𝑥 𝑝 shapes.

fragmentation functions↗

Effect of Anisotropic Confinement on Electronic Structure and Dynamics of Band Edge Excitons in Inorganic Perovskite Nanowires

Inorganic lead halide perovskite nanostructures show promise as the active layers in photovoltaics, light emitting diodes, and other optoelectronic devices. They are robust in the presence of oxygen and water, and the electronic structure and dynamics of these nanostructures can be tuned through quantum confinement. Here we create aligned bundles of CsPbBr3 nanowires with widths resulting in quantum confinement of the electronic wave functions and subject them to ultrafast microscopy. We directly image rapid one-dimensional exciton diffusion along the nanowires, and we measure an exciton trap density of roughly one per nanowire. Using transient absorption microscopy, we observe a polarization-dependent splitting of the band edge exciton line, and from the polarized fluorescence of nanowires in solution, we determine that the exciton transition dipole moments are anisotropic in strength. Furthermore, our observations are consistent with a model in which splitting is driven by shape anisotropy in conjunction with long-range exchange.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phase Field Modeling of Crystallographic Corrosion Pits

The modeling of corrosion to understand and predict corrosion behavior is a topical issue. Here, a 3D phase field model is developed to simulate the pit morphology, primarily focusing on crystallographic pits. A crystallographic function is employed to incorporate different corrosion rates for different crystallographic planes. The model is benchmarked and validated against an analytical solution for a simple case. 3D crystallographic pits in a single crystal are simulated and the effect of substrate orientation on the pit morphology is studied. The crystallographic pit morphology changes significantly with the substrate orientation and these morphologies have a symmetry consistent with the substrate orientation. This first 3D phase field model of crystallographic pits will help in predicting the intricate shapes of pits, thereby, pushing the frontiers of pitting corrosion modeling.

36 MATERIALS SCIENCE↗

Maskless Fourier transform holography

Fourier transform holography is a lensless imaging technique that retrieves an object's exit-wave function with high fidelity. It has been used to study nanoscale phenomena and spatio-temporal dynamics in solids, with sensitivity to the phase component of electronic and magnetic textures. However, the method requires an invasive and labor-intensive nanopatterning of a holography mask directly onto the sample, which can alter the sample properties, forces a fixed field-of-view, and leads to a low signal-to-noise ratio at high resolution. In this work, we propose using wavefront-shaping diffractive optics to create a structured probe with full control of its phase at the sample plane, circumventing the need for a mask. We demonstrate in silico that the method can image nanostructures and magnetic textures and validate our approach with a visible light-based experiment. The method enables investigation of a plethora of phenomena at the nanoscale including magnetic and electronic phase coexistence in solids, with further uses in soft and biological matter research.

Keskinbora, Kahraman↗

Thermophysical properties of high-density, sintered monoliths of yttrium dihydride in the range 373–773 K

Yttrium dihydride is a promising nuclear reactor moderator for high-temperature, thermal micro-reactors due to its ability to retain hydrogen to high temperatures while having a relatively low impact on neutron economy. However, it is difficult to fabricate yttrium dihydride in high-density, near net-shape monoliths for moderator applications due to challenges associated with the hydrogen absorption process. Here, high-density monoliths of yttrium dihydride were prepared by powder metallurgical methods. The lattice strain and thermal expansion coefficient were measured using neutron diffraction of powders of directly-hydrided yttrium, while the molar heat capacity and thermal diffusivity of sintered yttrium dihydride were measured using differential scanning calorimetry (DSC) and laser flash analysis (LFA), respectively. The molar heat capacity of yttrium dihydride was also calculated using density functional theory (DFT) for comparison. These parameters were used to then calculate the thermal conductivity and resistivity of yttrium dihydride as a function of temperature. The thermophysical properties of materials produced by both methods were observed to be consistent with the values from literature for yttrium dihydride. Due to the novelty of producing yttrium dihydride by powder metallurgical methods, this result indicated that the sintered monoliths were of high quality and that powder metallurgy is a viable method for large-scale production of yttrium dihydride monoliths for nuclear reactor moderator applications.

36 MATERIALS SCIENCE↗

Kβ X-ray Emission Spectroscopy of Cu(I)-Lytic Polysaccharide Monooxygenase: Direct Observation of the Frontier Molecular Orbital for H 2 O 2 Activation

Lytic polysaccharide monooxygenases (LPMOs) catalyze the degradation of recalcitrant carbohydrate polysaccharide substrates. These enzymes are characterized by a mononuclear Cu(I) active site with a three-coordinate T-shaped “His-brace” configuration including the N-terminal histidine and its amine group as ligands. Here, this study explicitly investigates the electronic structure of the d 10 Cu(I) active site in a LPMO using Kβ X-ray emission spectroscopy (XES). The lack of inversion symmetry in the His-brace site enables the 3d/p mixing required for intensity in the Kβ valence-to-core (VtC) XES spectrum of Cu(I)-LPMO. These Kβ XES data are correlated to density functional theory (DFT) calculations to define the bonding, and in particular, the frontier molecular orbital (FMO) of the Cu(I) site. These experimentally validated DFT calculations are used to evaluate the reaction coordinate for homolytic cleavage of the H 2 O 2 O–O bond and understand the contribution of this FMO to the low barrier of this reaction and how the geometric and electronic structure of the Cu(I)-LPMO site is activated for rapid reactivity with H 2 O 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mycorrhiza better predict soil fungal community composition and function than aboveground traits in temperate forest ecosystems

We sampled soil in the organic and mineral horizons beneath two AM-associated (Fraxinus americana, Thuja occidentalis) and two ECM-associated tree species (Betula alleghaniensis, and Tsuga canadensis), with an evergreen and deciduous species in each mycorrhizal group. To characterize fungal communities and organic matter decomposition beneath each tree species, we sequenced the ITS1 region of fungal DNA and measured the potential activity of carbon and nitrogen-targeting extracellular enzymes. Each tree species harbored distinct fungal communities, supporting the need to consider both mycorrhizal type and leaf habit. However, between tree characteristics, mycorrhizal type better predicted fungal communities. Across fungal guilds, saprotrophic fungi were the most important group in shaping fungal community differences in soils beneath all tree species. The effect of leaf habit on carbon and nitrogen-targeting hydrolytic enzymes depended on tree mycorrhizal association in the organic horizon, while oxidative enzyme activities were higher beneath EcM-associated trees across both soil horizons and leaf habits. These data include extracellular hydrolytic and oxidative enzyme activities, ITS sequencing fungal community data, soil carbon to nitrogen, and soil pH. Site level data include climate (mean annual temperature, precipitation), elevation, and soil series and order information.

54 ENVIRONMENTAL SCIENCES↗