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At least 955 records · Page 53

Thermal relaxation of strain and twist in ferroelectric hexagonal boron nitride moiré interfaces

New properties can arise at van der Waals (vdW) interfaces hosting a moiré pattern generated by interlayer twist and strain. However, achieving precise control of interlayer twist/strain remains an ongoing challenge in vdW heterostructure assembly, and even subtle variation in these structural parameters can create significant changes in the moiré period and emergent properties. Characterizing the rate of interlayer twist/strain relaxation during thermal annealing is critical to establish a thermal budget for vdW heterostructure construction and may provide a route to improve the homogeneity of the interface or to control its final state. Here, we characterize the spatial and temporal dependence of interfacial twist and strain relaxation in marginally-twisted hBN/hBN interfaces heated under conditions relevant to vdW heterostructure assembly and typical sample annealing. We find that the ferroelectric hBN/hBN moiré at very small twist angles (θ ≤ 0.1°) relaxes minimally during annealing in air at typical assembly temperatures of 170°C. However, at 400°C, twist angle relaxes significantly, accompanied by a decrease in spatial uniformity. Uniaxial heterostrain initially increases and then decreases over time, becoming increasingly non-uniform in direction. Structural irregularities such as step edges, contamination bubbles, or contact with the underlying substrate result in local inhomogeneity in the rate of relaxation.

2D materials↗

ML-Based Rock Properties and Seismic Volume Enhancement

This project aims to improve field-scale Carbon Capture and Storage (CCS) assessments by enhancing petrophysical and geophysical log predictions through machine learning and neural networks. In our work during EY23, we applied Conditional Variational Autoencoders (CVAEs) to predict compressional velocity (Vp) and assess CO2 saturation levels in geological formations at the Illinois Basin Decatur Project (IBDP). In another task, we improved full-waveform inversion (FWI) methods with machine-learning approaches using lithological constraints. Full-waveform inversion (FWI) of seismic data estimates the elastic properties of subsurface rocks with high spatial resolution.

Nathanail, Athanasios↗

High-order diamond differencing schemes for the Boltzmann Fokker-Planck equation in 3D Cartesian geometries

The Boltzmann Fokker-Planck, an approximate form of the linear Boltzmann equation is commonly used to treat efficiently the transport of charged particles in matter. This paper introduces the application of high-order diamond differencing schemes (HODD), specifically the DD1 and DD2 schemes which are 4- and 6-order accurate respectively, to handle the spatial discretization of that equation in 3D Cartesian geometries. The energy deposition solutions for the coupled transport of electrons and photons presented in this work shows that HODD, compared to classical DD scheme, provides correction to the oscillations and a reduced propensity to yield negative fluxes. They are useful tools to minimize local error, notably in regions with abrupt variations of the flux solution. They also can be used to reduced execution time by decreasing the needed number of voxels to obtain a fixed accuracy. On the tested benchmarks, the DD1 scheme is 87%- 92%-91% more accurate than the classical DD scheme for total, mean per-voxels and maximum deviation of energy deposition values respectively. For comparison, a calculation with 8 times more voxels, requiring roughly 2.5 times more time to execute, is 92%-90%-77% more accurate. (authors)

97 MATHEMATICS AND COMPUTING↗

Can upscaling ground nadir SIF to eddy covariance footprint improve the relationship between SIF and GPP in croplands?

Ground solar-induced chlorophyll fluorescence (SIF) is important for the mechanistic understanding of the dynamics of vegetation gross primary production (GPP) at fine spatiotemporal scales. However, eddy covariance (EC) observations generally cover larger footprint areas than ground SIF observations (a bare fiber with nadir), and this footprint mismatch between nadir SIF and GPP could complicate the canopy SIF-GPP relationships. Here, we upscaled nadir SIF observations to EC footprint and investigated the change in SIF-GPP relationships after the upscaling in cropland. We included 13 site-years data in our study, with seven site-years corn, four site-years soybeans, and two site-years miscanthus, all located in the US Corn Belt. All sites’ crop nadir SIF observations collected from the automated FluoSpec2 system (a hemispheric-nadir system) were upscaled to the GPP footprint-based SIF using vegetation indices (VIs) calculated from high spatiotemporal satellite reflectance data. We found that SIF-GPP relationships were not substantially changed after upscaling nadir SIF to GPP footprint at our crop sites planted with corn, soybean, and miscanthus, with R 2 change after the upscaling ranging from -0.007 to 0.051 and root mean square error (RMSE) difference from -0.658 to 0.095 umol m –2 s –1 relative to original nadir SIF-GPP relationships across all the site-years. The variation of the SIF-GPP relationship within each species across different site-years was similar between the original nadir SIF and upscaled SIF. Different VIs, EC footprint models, and satellite data led to marginal differences in the SIF-GPP relationships when upscaling nadir SIF to EC footprint. Furthermore, our study provided a methodological framework to correct this spatial mismatch between ground nadir SIF and GPP observations for croplands and potentially for other ecosystems. Our results also demonstrated that the spatial mismatch between ground nadir SIF and GPP might not significantly affect the SIF-GPP relationship in cropland that are largely homogeneous.

54 ENVIRONMENTAL SCIENCES↗

Diffused trenches for high fill-factor Low-Gain Avalanche Diodes

Low-Gain Avalanche Diodes (LGADs) are a class of silicon detectors that have been specifically designed for the fast detection of minimum ionizing particles (mips) in High-Energy Physics experiments. While they provide timing resolution on the order of a few tens of picoseconds, they cannot achieve high spatial resolution due to the intrinsic characteristics of their structures. Thus, active R&D is on-going to develop detectors based on LGADs to improve their spatial resolution while maintaining the timing performance of the LGADs. Such devices are, for example, AC-coupled LGADs and Deep-Junction LGADs. Another device option is the Trench-Isolated LGAD (TI LGAD), where trenches etched at the periphery of the pixels isolate them while providing a high fill-factor. Here, in this paper, we present a variation of this latter approach, demonstrating its feasibility by means of 2-dimensional TCAD simulations.

47 OTHER INSTRUMENTATION↗

Invited article: X-ray phase contrast imaging in inertial confinement fusion and high energy density research

X-ray phase contrast imaging (XPCI) provides enhanced image contrast beyond absorption-based x-ray imaging alone due to refraction and diffraction from gradients in the object material density. It is sensitive to small variations in density, such as internal voids, cracks, grains, defects, and material flow, as well as to stronger density variations such as from a shock wave. Beyond its initial use in biology and materials science, XPCI is now routinely used in inertial confinement fusion (ICF) and high energy density (HED) research, first to characterize ICF capsules and targets, and later applied in dynamic experiments, where coherent x-ray sources, ultrafast x-ray pulses, and high temporal and spatial resolution are required. In this Review article, XPCI image formation theory is presented, its diverse use in ICF and HED research is discussed, the unique requirements for ultrafast XPCI imaging are given, as well as current challenges and issues in its use.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie

Ecosystems at coastal terrestrial–aquatic interfaces play a significant role in global biogeochemical cycles. In this study, we aimed to characterize coastal wetlands with particular focus on the co-variability between plant dynamics, topography, soil, and other environmental factors. We proposed a functional zonation approach based on machine learning clustering to identify the spatial regions, i.e., zones that capture these co-varied properties. This approach was applied to publicly available datasets along Lake Erie, in the Great Lakes Region. We investigated the heterogeneity of coastal ecosystem structures as a function of along-shore distance and transverse distance, based on the spatial data layers, including topography, wetland vegetation cover, and the time series of Landsat’s enhanced vegetation index (EVI) between 1990 and 2020. Results showed that the topographic metrics (elevation and slope), soil texture, and plant productivity influence the spatial distribution of wetland land-covers (emergent and phragmites). These results highlight a natural organization along the transverse axis, where the elevation and the EVI increase further away from the coastline. In addition, the clustering analysis allowed us to identify regions with distinct environmental characteristics, as well as the ones that are more sensitive to interannual lake-level variations.

47 OTHER INSTRUMENTATION↗

Microstructure characterization of electric field assisted sintering (EFAS) sintered metallic and ceramic materials using local thermal diffusivity measurement

Electric Field Assisted Sintering (EFAS, also referred to as spark plasma sintering) is a powerful technology for the consolidation of powder materials. The high heating rate during the sintering process is critical for minimizing energy consumption, but it can also cause microstructure heterogeneities in sintered parts, such as spatially varied porosity. The examination of localized porosity usually requires the use of a scanning electron microscope with a carefully prepared surface. In this paper, photothermal radiometry is used to measure local thermal diffusivity and extract localized porosity of EFAS-sintered parts by using a percolation-threshold model. Applying this approach, we identified the radial position-dependent porosity variation in EFAS parts, which is likely formed due to the large temperature gradient during the sintering process. This approach has a unique advantage because it can measure samples with minimal or no surface preparation, enabling the possibility of in situ characterization in EFAS with proper system modification. Necessary modifications on the measurement approach for EFAS deployment and in situ characterization are also discussed.

36 MATERIALS SCIENCE↗

Willow Biomass Crops Are a Carbon Negative or Low-Carbon Feedstock Depending on Prior Land Use and Transportation Distances to End Users

Few life cycle assessments (LCAs) on willow biomass production have investigated the effects of key geographically specific parameters. This study uses a spatial LCA model for willow biomass production to determine spatially explicit greenhouse gas (GHG) emissions and energy return on investment (EROI), including land use conversion from pasture and cropland or grassland. There were negative GHG emissions on 92% of the land identified as suitable for willow biomass production, indicating this system’s potential for climate change mitigation. For willow planted on cropland or pasture, life cycle GHG emissions ranged from −53.2 to −176.9 kg CO2eq Mg-1. When willow was grown on grassland the projected decrease in soil organic carbon resulted in a slightly positive GHG balance. Changes in soil organic carbon (SOC) associated with land use change, transportation distance, and willow yield had the greatest impacts on GHG emissions. Results from the uncertainty analysis exhibited large variations in GHG emissions between counties arising from differences in these parameters. The average EROI across the entire region was 19.2. Willow biomass can be a carbon negative or low-carbon energy source with a high EROI in regions with similar infrastructure, transportation distances, and growing conditions such as soil characteristics, land cover types, and climate.

09 BIOMASS FUELS↗

An experimental and one-dimensional modeling analysis of turbulent gas ejection in pre-chamber engines

In this work, experimental results from a study on the evolution of gas jets ejected through the orifices of a pre-chamber in a heavy-duty optical engine are presented. The work examines conditions without fuel inside the main-chamber, which helps to describe the dynamics of the ejected gas jets without the interference of subsequent combustion in the main-chamber. Experimental diagnostics consist of high-speed visible intensified imaging and low-speed infrared imaging. Additionally a one-dimensional gas jet model is used to characterize the spatial distribution of the ejected flow, including parameters such as tip penetration, which are then validated based on experimental results. Different stages in the ejection of pre-chamber jets are identified, with chemical activity restricted to a maximum distance of 5 to 10 orifice diameters downstream of the orifice as indicated by the recorded visible radiation. Sensitivity of cycle-to-cycle variations in pre-chamber jet development to the air-to-fuel ratio in the pre-chamber observed in the experiments is in most part attributed to the variations in the timing of combustion initiation in the pre-chamber. The influence of the ejection flow on the penetration of the gas jet on a cycle-to-cycle basis is presented using the one-dimensional model. The one-dimensional model also indicates that the local flow exhibits highest sensitivity to operating conditions during the start of ejection until the timing when maximum flow is attained. Differences that exist during the decreasing mass-flow ejection time-period tend to smear out in part due to the transient slowdown of the ejection process.

1-D gas jet model↗

Spatio-temporal dynamics of Hendra virus in Australia reveal stable maintenance of diverse viral clades among Pteropus bats

Hendra virus (HeV) was discovered in 1994 in Australia. Limited genomic data have hindered comprehensive understanding of HeV’s evolutionary dynamics. Here, in this work, we recovered 48 HeV genomes from bats and 9 from horses from Australia between 2016 and 2020, revealing four distinct clades. Each clade was distributed over a large spatial area with multiple clades co-circulating within a single bat roost on the same day and over consecutive years. The diversity and temporal stability of co-circulating clades suggest that viral dynamics are driven by episodic shedding of existing lineages maintained at the population level, rather than immune-driven strain-replacement dynamics. HeV isolates of different clades displayed variation in phenotypic properties but minimal antigenic differences. We provide an overview of evolutionary dynamics, phenotypic properties and assessment of countermeasures for HeV, and provide insights into the processes that maintain virus diversity in bats and influence the potential for viral emergence.

genetic variation↗

Investigating Spatial Variability of Aerosol, Cloud Condensation Nuclei, and Ice Nucleating Particles in Mountainous Terrain Field Campaign Report

The U.S. Department of Energy Atmospheric System Research (ASR)-supported Surface Atmosphere Integrated Field Laboratory (SAIL) campaign in the East River Watershed (ERW) of the Upper Colorado River Basin in southwestern Colorado ran from fall 2021 to spring 2023. Two monitoring sites were deployed in the ERW as part of SAIL. The two sites were the Aerosol Observation System (AOS) located on Crested Butte Ski Mountain, and the second ARM Mobile Facility (AMF2), located at the Rocky Mountain Biological Laboratory in Gothic, Colorado. To gain a more comprehensive understanding of aerosols in complex, mountainous terrain, Handix Scientific deployed SAIL-Net, a distributed network of six measurement nodes spanning the domain of the SAIL research area from October 2021 to July 2023. Each node measured aerosol particles between 140 nm and 3.4 μm in diameter using a small portable optical particle spectrometer (POPS; Gao et al. 2016), cloud condensation nuclei (CNN) using a miniature CCN counter (CloudPuck), and ice nucleating particles (INP) using the time-resolved aerosol filter sampler (TRAPS; Creamean et al. 2018). Our approach was similar to other studies that aimed to better characterize and understand aerosols and gas-phase pollutants using networks of lower-cost sensors (Caubel et al. 2019, Kelly et al. 2021, Asher et al. 2022). Such studies have identified neighborhood-level variations in pollutant concentrations (Schneider et al. 2017, Popoola et al. 2018, Caubel et al. 2019). Small-scale variations such as this are poorly represented in models and poorly measured by a single monitoring system (Caubel et al. 2019). Previous work has shown the representation error (the ability of measurements to represent a larger area) increases with complex orography, leading to decreases in model accuracy (Schutgens et al. 2017). The overall goal of SAIL-Net was to improve our understanding of the variability of aerosol in the ERW, thus increasing our knowledge of aerosol-cloud interactions in this region and informing the usefulness of distributed networks of measurements for future studies. We met this goal by answering the following science questions: 1. What is the aerosol temporal variability, and how does aerosol inhomogeneity vary seasonally? Is there significant seasonal variability in sources, or are short-term meteorological conditions the most important determining factor in sources for cloud nuclei? 2. What is the aerosol spatial variability? What are the aerosol characteristics at cloud base, presumably the particles most representative of those acting as cloud nuclei? 3. How should measurement networks be designed to capture aerosol-cloud interactions, and what do they need to measure? Can a single measurement site accurately represent aerosol properties in regions of complex terrain? SAIL-Net consisted of six measurement nodes spread across the ERW near Crested Butte, Colorado. The primary objective in site placement was to select locations that captured the vertical variation in aerosol properties while also spanning the domain of the SAIL campaign. The elevation of the sites ranged from roughly 2750 m along the valley floor of the ERW to approximately 3500 m near the top of Crested Butte Mountain, which is one of the taller peaks in the ERW. The farthest distance between sites was 14 km, while the closest two sites were approximately 1 km apart. Two of the sites were collocated with the ARM SAIL sites; our instruments sat on top of one of the trailers at AOS and another one of our sites was located in a meadow just above AMF2.

54 ENVIRONMENTAL SCIENCES↗

Dislocation‐Induced Structural and Luminescence Degradation in InAs Quantum Dot Emitters on Silicon

This study probes the extent to which dislocations reduce carrier lifetimes and alter growth morphology and luminescence in InAs quantum dots (QD) grown on silicon. These heterostructures are key ingredients to achieving a highly reliable monolithically integrated light source on silicon necessary for photonic-integrated circuits. Around 20%–30% shorter carrier lifetimes are found at spatially resolved individual dislocations at room temperature using time-resolved cathodoluminescence spectroscopy, highlighting the strong nonradiative impact of dislocations even against the three-dimensional confinement of QDs. Beyond these direct effects of increased nonradiative recombination, it is found that misfit dislocations in the defect filter layers employed during III–V/Si growth alter the QD growth environment to induce a crosshatch-like variation in QD emission color and intensity when the filter layer is positioned sufficiently close to the QD emitter layer. Sessile threading dislocations generate even more egregious hillock defects that also reduce emission intensities by altering layer thicknesses, as measured by transmission electron microscopy and atom probe tomography. This work presents a more complete picture of the impacts of dislocations relevant to the development of light sources for scalable silicon photonic integrated circuits.

36 MATERIALS SCIENCE↗

Processing-dependent chemical ordering in Cu 3 Au characterized via non-destructive Bragg coherent diffraction imaging

Of current importance for alloy design is controlling chemical ordering through processing routes to optimize an alloy's mechanical properties for a desired application. However, characterization of chemical ordering remains an ongoing challenge, particularly when nondestructive characterization is needed. Here, in this study, Bragg coherent diffraction imaging is used to reconstruct morphology and lattice displacement in model Cu 3 Au nanocrystals that have undergone different heat treatments to produce variation in chemical ordering. The magnitudes and distributions of the scattering amplitudes (proportional to electron density) and lattice strains within these crystals are then analyzed to correlate them to the expected amount of chemical ordering present. Nanocrystals with increased amounts of ordering are found to generally have less extreme strains present and reduced strain distribution widths. In addition, statistical correlations are found between the spatial arrangement of scattering amplitude and lattice strains.

Warren, Nathaniel [Pennsylvania State Univ., Unive↗

Observation of a phase transition within the domain walls of ferromagnetic Co3Sn2S2

Abstract The ferromagnetic phase of Co 3 Sn 2 S 2 is widely considered to be a topological Weyl semimetal, with evidence for momentum-space monopoles of Berry curvature from transport and spectroscopic probes. As the bandstructure is highly sensitive to the magnetic order, attention has focused on anomalies in magnetization, susceptibility and transport measurements that are seen well below the Curie temperature, leading to speculation that a “hidden” phase coexists with ferromagnetism. Here we report spatially-resolved measurements by Kerr effect microscopy that identify this phase. We find that the anomalies coincide with a deep minimum in domain wall (DW) mobility, indicating a crossover between two regimes of DW propagation. We demonstrate that this crossover is a manifestation of a 2D phase transition that occurs within the DW, in which the magnetization texture changes from continuous rotation to unidirectional variation. We propose that the existence of this 2D transition deep within the ferromagnetic state of the bulk is a consequence of a giant quality factor for magnetocrystalline anisotropy unique to this compound. This work broadens the horizon of the conventional binary classification of DWs into Bloch and Néel walls, and suggests new strategies for manipulation of domain walls and their role in electron and spin transport.

36 MATERIALS SCIENCE↗

Dissecting Nearby Galaxies with piXedfit. II. Spatially Resolved Scaling Relations among Stars, Dust, and Gas

We study spatially resolved scaling relations among stars, dust, and gas in ten nearby spiral galaxies. In a preceding paper, we have derived spatially resolved properties of the stellar population and dust by a panchromatic spectral energy distribution fitting using piXedfit. Now, we investigate resolved star formation (${{\rm{\Sigma }}}_{{{\rm{H}}}_{2}}$–ΣSFR–Σ * ) and dust scaling relations. While the relations with all subgalactic regions of the galaxies are reasonably tight (σ ≲ 0.3 dex), we find that most of the scaling relations exhibit galaxy-to-galaxy variations in normalization and shape. Only two relations of Σdust–Σgas and Σdust–${{\rm{\Sigma }}}_{{{\rm{H}}}_{2}}$ do not show noticeable galaxy-to-galaxy variations among our sample galaxies. We further investigate the correlations among the scaling relations. We find significant correlations among the normalization of the ${{\rm{\Sigma }}}_{{{\rm{H}}}_{2}}$–ΣSFR–Σ * relations, which suggest that the galaxies with higher levels of resolved H 2 fraction (${f}_{{{\rm{H}}}_{2}}$) tend to have higher levels of resolved star formation efficiency (SFE) and specific star formation rate (sSFR). We also observe that the galaxies with higher levels of resolved dust-to-stellar mass ratios tend to have higher levels of resolved sSFR, SFE, and ${f}_{{{\rm{H}}}_{2}}$. Moreover, we find that the galaxies with higher global sSFR and less compact morphology tend to have higher levels of the resolved sSFR, SFE, and ${f}_{{{\rm{H}}}_{2}}$, which can explain the variations in the normalization of the ${{\rm{\Sigma }}}_{{{\rm{H}}}_{2}}$–ΣSFR–Σ * relationships. Overall, we observe indications of the contributions of both global and local factors in governing the star formation process in galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

The Blue Straggler Population of the Open Clusters Trumpler 5, Trumpler 20, and NGC 2477

We present a study based on Gaia DR2 of the population of blue straggler stars in the open clusters Trumpler 5, Trumpler 20, and NGC 2477. All candidates were selected according to their position in the color–magnitude diagram, their proper motion components, and their parallax. We also looked for yellow stragglers, i.e., possible evolved blue stragglers. We found that Trumpler 5 hosts a large blue straggler star population, which allowed us to analyze their radial distribution as a probe of the cluster’s dynamical status. The blue straggler star distribution was compared with that of red giant branch stars to evaluate mass segregation. Our results indicate that blue straggler stars are not more centrally concentrated than red giant branch stars stars in any of the clusters. The radial distribution of blue straggler stars in Trumpler 5 is flat. Additionally, using a multi-epoch radial velocity survey conducted with the high-resolution spectrograph FLAMES/GIRAFFE at the Very Large Telescope, we measured the radial velocities of a sample of stragglers to compare with the mean radial velocity and velocity dispersion of the clusters. Based on the radial velocity variations for different epochs, we roughly classified these stars as possible close or long-period binaries.

47 OTHER INSTRUMENTATION↗

STSR-INR: Spatiotemporal super-resolution for multivariate time-varying volumetric data via implicit neural representation

Implicit neural representation (INR) has surfaced as a promising direction for solving different scientific visualization tasks due to its continuous representation and flexible input and output settings. We present STSR-INR, an INR solution for generating simultaneous spatiotemporal super-resolution for multivariate time-varying volumetric data. Inheriting the benefits of the INR-based approach, STSR-INR supports unsupervised learning and permits data upscaling with arbitrary spatial and temporal scale factors. Unlike existing GAN- or INR-based super-resolution methods, STSR-INR focuses on tackling variables or ensembles and enabling joint training across datasets of various spatiotemporal resolutions. Here we achieve this capability via a variable embedding scheme that learns latent vectors for different variables. In conjunction with a modulated structure in the network design, we employ a variational auto-decoder to optimize the learnable latent vectors to enable latent-space interpolation. To combat the slow training of INR, we leverage a multi-head strategy to improve training and inference speed with significant speedup. We demonstrate the effectiveness of STSR-INR with multiple scalar field datasets and compare it with conventional tricubic+linear interpolation and state-of-the-art deep-learning-based solutions (STNet and CoordNet).

97 MATHEMATICS AND COMPUTING↗