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At least 811 records · Page 45

Airborne imaging spectroscopy surveys of Arctic and boreal Alaska and northwestern Canada 2017–2023

Since 2015, NASA’s Arctic Boreal Vulnerability Experiment (ABoVE) has investigated how climate change impacts the vulnerability and/or resilience of the permafrost-affected ecosystems of Alaska and northwestern Canada. ABoVE conducted extensive surveys with the Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) during 2017, 2018, 2019, and 2022 and with AVIRIS-3 in 2023 to characterize tundra, taiga, peatlands, and wetlands in unprecedented detail. The ABoVE AVIRIS dataset comprises ~1700 individual flight lines covering ~120,000 km 2 with nominal 5 m × 5 m spatial resolution. Data include individual transects to capture important gradients like the tundra-taiga ecotone and maps of up to 10,000 km 2 for key study areas like the Mackenzie Delta. The ABoVE AVIRIS surveys enable diverse ecosystem science, provide crucial benchmark data for validating retrievals from the PACE, PRISMA, and EnMAP satellite sensors and help prepare for the SBG and CHIME missions. This paper guides interested researchers to fully explore the ABoVE AVIRIS spectral imagery and complements our guide to the ABoVE airborne synthetic aperture radar surveys.

Miller, Charles E. [California Institute of Techno↗

Ultra-Fast High-Precision Metallic Nanoparticle Synthesis using Laser-Accelerated Protons

Laser-driven proton acceleration, as produced during the interaction of a high-intensity (I > 1 × 10 18 W/cm 2 ), short pulse (<1 ps) laser with a solid target, is a prosperous field of endeavor for manifold applications in different domains, including astrophysics, biomedicine and materials science. These emerging applications benefit from the unique features of the laser-accelerated particles such as short duration, intense flux and energy versatility, which allow obtaining unprecedented temperature and pressure conditions. In this paper, we show that laser-driven protons are perfectly suited for producing, in a single sub-ns laser pulse, metallic nanocrystals with tunable diameter ranging from tens to hundreds of nm and very high precision. Our method relies on the intense and very quick proton energy deposition, which induces in a bulk material an explosive boiling and produces nanocrystals that aggregate in a plasma plume composed by atoms detached from the proton-irradiated surface. The properties of the obtained particles depend on the deposited proton energy and on the duration of the thermodynamical process. Suitably controlling the irradiated dose allows fabricating nanocrystals of a specific size with low polydispersity that can easily be isolated in order to obtain a monodisperse nanocrystal solution. Molecular Dynamics simulations confirm our experimental results.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Femtosecond laser produced periodic plasma in a colloidal crystal probed by XFEL radiation

With the rapid development of short-pulse intense laser sources, studies of matter under extreme irradiation conditions enter further unexplored regimes. In addition, an application of X-ray Free-Electron Lasers (XFELs) delivering intense femtosecond X-ray pulses, allows to investigate sample evolution in IR pump - X-ray probe experiments with an unprecedented time resolution. Here we present a detailed study of the periodic plasma created from the colloidal crystal. Both experimental data and theory modeling show that the periodicity in the sample survives to a large extent the extreme excitation and shock wave propagation inside the colloidal crystal. This feature enables probing the excited crystal, using the powerful Bragg peak analysis, in contrast to the conventional studies of dense plasma created from bulk samples for which probing with Bragg diffraction technique is not possible. X-ray diffraction measurements of excited colloidal crystals may then lead towards a better understanding of matter phase transitions under extreme irradiation conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Toward monochromated sub-nanometer UEM and femtosecond UED

A preliminary design of a mega-electron-volt (MeV) monochromator with 10 –5 energy spread for ultrafast electron diffraction (UED) and ultrafast electron microscopy (UEM) is presented. Such a narrow energy spread is advantageous in both the single shot mode, where the momentum resolution in diffraction is improved, and the accumulation mode, where shot-to-shot energy jitter is reduced. In the single-shot mode, we numerically optimized the monochromator efficiency up to 13% achieving 1.3 million electrons per pulse. In the accumulation mode, to mitigate the efficiency degradation caused by the shot-to-shot energy jitter, an optimized gun phase yields only a mild reduction of the single-shot efficiency, therefore the number of accumulated electrons nearly proportional to the repetition rate. Inspired by the recent work of Qi et al. (Phys Rev Lett 124:134803, 2020), a novel concept of applying reverse bending magnets to adjust the energy-dependent path length difference has been successfully realized in designing a MeV monochromator to achieve the minimum energy-dependent path length difference between cathode and sample. Thanks to the achromat design, the pulse length of the electron bunches and the energy-dependent timing jitter can be greatly reduced to the 10 fs level. The introduction of such a monochromator provides a major step forward, towards constructing a UEM with sub-nm resolution and a UED with ten-femtosecond temporal resolution. The one-to-one mapping between the electron beam parameter and the diffraction peak broadening enables a real-time nondestructive diagnosis of the beam energy spread and divergence. The tunable electric–magnetic monochromator allows the scanning of the electron beam energy with a 10 –5 precision, enabling online energy matching for the UEM, on-momentum flux maximizing for the UED and real-time energy measuring for energy-loss spectroscopy. A combination of the monochromator and a downstream chicane enables “two-color” double pulses with femtosecond duration and the tunable delay in the range of 10 to 160 fs, which can potentially provide an unprecedented femtosecond time resolution for time resolved UED.

36 MATERIALS SCIENCE↗

Implementation and analysis of quantum computing application to Higgs boson reconstruction at the large Hadron Collider

With the advent of the High-Luminosity Large Hadron Collider (HL-LHC) era, high energy physics (HEP) event selection will require new approaches to rapidly and accurately analyze vast databases. The current study addresses the enormity of HEP databases in an unprecedented manner—a quantum search using Grover’s Algorithm (GA) on an unsorted database, ATLAS Open Data, from the ATLAS detector. A novel method to identify rare events at 13 TeV in CERN’s LHC using quantum computing (QC) is presented. As indicated by the Higgs boson decay channel H→ZZ*→4l , the detection of four leptons in one event may be used to reconstruct the Higgs boson and, more importantly, evince Higgs boson decay to some new phenomena, such as H→ZZ d →4l . Searching the dataset for collisions resulting in detection of four leptons using a Jupyter Notebook, a classical simulation of GA, and several quantum computers with multiple qubits, the current application was found to make the proper selection in the unsorted dataset. Quantum search efficacy was analyzed for the incoming HL-LHC by implementing the QC method on multiple classical simulators and IBM’s quantum computers with the IBM Qiskit Open Source Software. The current QC application provides a novel, high-efficiency alternative to classical database searches, demonstrating its potential utility as a rapid and increasingly accurate search method in HEP.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Efficient facemask decontamination via forced ozone convection

The COVID-19 crisis has taken a significant toll on human life and the global economy since its start in early 2020. Healthcare professionals have been particularly vulnerable because of the unprecedented shortage of Facepiece Respirators (FPRs), which act as fundamental tools to protect the medical staff treating the coronavirus patients. In addition, many FPRs are designed to be disposable single-use devices, creating an issue related to the generation of large quantities of non-biodegradable waste. In this contribution, we describe a plasma-based decontamination technique designed to circumvent the shortages of FPRs and alleviate the environmental problems posed by waste generation. The system utilizes a Dielectric Barrier Discharge (DBD) to generate ozone and feed it through the fibers of the FPRs. The flow-through configuration is different than canonical ozone-based sterilization methods, in which the equipment is placed in a sealed ozone-containing enclosure without any flow through the mask polymer fibers. We demonstrate the rapid decontamination of surgical masks using Escherichia coli ( E. coli ) and Vesicular Stomatitis Virus (VSV) as model pathogens, with the flow-through configuration providing a drastic reduction in sterilization time compared to the canonical approach. We also demonstrate that there is no deterioration in mask structure or filtration efficiency resulting from sterilization. Finally, we show that this decontamination approach can be implemented using readily available tools, such as a plastic box, a glass tube, few 3D printed components, and the high-voltage power supply from a plasma globe toy. The prototype assembled for this study is portable and affordable, with effectiveness comparable to that of larger and more expensive equipment.

36 MATERIALS SCIENCE↗

Compression-rate dependence of pressure-induced phase transitions in Bi

Abstract It is qualitatively well known that kinetics related to nucleation and growth can shift apparent phase boundaries from their equilibrium value. In this work, we have measured this effect in Bi using time-resolved X-ray diffraction with unprecedented 0.25 ms time resolution, accurately determining phase transition pressures at compression rates spanning five orders of magnitude (10 –2 –10 3 GPa/s) using the dynamic diamond anvil cell. An over-pressurization of the Bi-III/Bi-V phase boundary is observed at fast compression rates for different sample types and stress states, and the largest over-pressurization that is observed is ΔP = 2.5 GPa. The work presented here paves the way for future studies of transition kinetics at previously inaccessible compression rates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Tunable x-ray free electron laser multi-pulses with nanosecond separation

X-ray Free Electron Lasers provide femtosecond x-ray pulses with narrow bandwidth and unprecedented peak brightness. Special modes of operation have been developed to deliver double pulses for x-ray pump, x-ray probe experiments. However, the longest delay between the two pulses achieved with existing single bucket methods is less than 1 picosecond, thus preventing the exploration of longer time-scale dynamics. We present a novel two-bucket scheme covering delays from 350 picoseconds to hundreds of nanoseconds in discrete steps of 350 picoseconds. Performance for each pulse can be similar to the one in a single pulse operation. The method has been experimentally tested with the Linac Coherent Light Source (LCLS-I) and the copper linac with LCLS-II hard x-ray undulators.

47 OTHER INSTRUMENTATION↗

CubeSat constellations provide enhanced crop phenology and digital agricultural insights using daily leaf area index retrievals

Satellite remote sensing has great potential to deliver on the promise of a data-driven agricultural revolution, with emerging space-based platforms providing spatiotemporal insights into precision-level attributes such as crop water use, vegetation health and condition and crop response to management practices. Using a harmonized collection of high-resolution Planet CubeSat, Sentinel-2, Landsat-8 and additional coarser resolution imagery from MODIS and VIIRS, we exploit a multi-satellite data fusion and machine learning approach to deliver a radiometrically calibrated and gap-filled time-series of daily leaf area index (LAI) at an unprecedented spatial resolution of 3 m. The insights available from such high-resolution CubeSat-based LAI data are demonstrated through tracking the growth cycle of a maize crop and identifying observable within-field spatial and temporal variations across key phenological stages. Daily LAI retrievals peaked at the tasseling stage, demonstrating their value for fertilizer and irrigation scheduling. An evaluation of satellite-based retrievals against field-measured LAI data collected from both rain-fed and irrigated fields shows high correlation and captures the spatiotemporal development of intra- and inter-field variations. Novel agricultural insights related to individual vegetative and reproductive growth stages were obtained, showcasing the capacity for new high-resolution CubeSat platforms to deliver actionable intelligence for precision agricultural and related applications.

54 ENVIRONMENTAL SCIENCES↗

How the Great Plains Dust Bowl drought spread heat extremes around the Northern Hemisphere

Abstract Extraordinary heat extremes occurred in the 1930s in areas of the Northern Hemisphere far from the record setting heat over the US associated with the Great Plains Dust Bowl drought. A climate model sensitivity experiment is used to identify a new mechanism involving a warm season circumglobal atmospheric teleconnection pattern that spread heat extremes over far-flung areas of the Northern Hemisphere arising from the intense heating over the desiccated Great Plains themselves. It has only been in the twenty-first century that human populations in these regions of the Northern Hemisphere have experienced heat extremes comparable to the 1930s. This demonstrates that humans influenced Northern Hemisphere temperature and heat extremes through disastrous and unprecedented regional land use practices over the Great Plains, and points to the possibility that future intense regional droughts could affect heat extremes on hemispheric scales.

54 ENVIRONMENTAL SCIENCES↗

Electron tomography unravels new insights into fiber cell wall nanostructure; exploring 3D macromolecular biopolymeric nano-architecture of spruce fiber secondary walls

Lignocellulose biomass has a tremendous potential as renewable biomaterials for fostering the “bio-based society” and circular bioeconomy paradigm. It requires efficient use and breakdown of fiber cell walls containing mainly cellulose, hemicellulose and lignin biopolymers. Despite their great importance, there is an extensive debate on the true structure of fiber walls and knowledge on the macromolecular nano-organization is limited and remains elusive in 3D. We employed dual-axis electron tomography that allows visualization of previously unseen 3D macromolecular organization/biopolymeric nano-architecture of the secondary S2 layer of Norway spruce fiber wall. Unprecedented 3D nano-structural details with novel insights into cellulose microfibrils (~2 nm diameter), macrofibrils, nano-pore network and cell wall chemistry (volume %) across the S2 were explored and quantified including simulation of structure related permeability. Matrix polymer association with cellulose varied between microfibrils and macrofibrils with lignin directly associated with MFs. Simulated bio-nano-mechanical properties revealed stress distribution within the S2 and showed similar properties between the idealized 3D model and the native S2 (actual tomogram). Present work has great potential for significant advancements in lignocellulose research on nano-scale understanding of cell wall assembly/disassembly processes leading to more efficient industrial processes of functionalization, valorization and target modification technologies.

3-D reconstruction↗

Magnetic molecules lose identity when connected to different combinations of magnetic metal electrodes in MTJ-based molecular spintronics devices (MTJMSD)

Abstract Understanding the magnetic molecules’ interaction with different combinations of metal electrodes is vital to advancing the molecular spintronics field. This paper describes experimental and theoretical understanding showing how paramagnetic single-molecule magnet (SMM) catalyzes long-range effects on metal electrodes and, in that process, loses its basic magnetic properties. For the first time, our Monte Carlo simulations, verified for consistency with regards to experimental studies, discuss the properties of the whole device and a generic paramagnetic molecule analog (GPMA) connected to the combinations of ferromagnet-ferromagnet, ferromagnet-paramagnet, and ferromagnet-antiferromagnet metal electrodes. We studied the magnetic moment vs. magnetic field of GPMA exchange coupled between two metal electrodes along the exposed side edge of cross junction-shaped magnetic tunnel junction (MTJ). We also studied GPMA-metal electrode interfaces’ magnetic moment vs. magnetic field response. We have also found that the MTJ dimension impacted the molecule response. This study suggests that SMM spin at the MTJ exposed sides offers a unique and high-yield method of connecting molecules to virtually endless magnetic and nonmagnetic electrodes and observing unprecedented phenomena in the molecular spintronics field.

42 ENGINEERING↗

An efficient instance segmentation approach for studying fission gas bubbles in irradiated metallic nuclear fuel

Abstract Gaseous fission products from nuclear fission reactions tend to form fission gas bubbles of various shapes and sizes inside nuclear fuel. The behavior of fission gas bubbles dictates nuclear fuel performances, such as fission gas release, grain growth, swelling, and fuel cladding mechanical interaction. Although mechanical understanding of the overall evolution behavior of fission gas bubbles is well known, lacking the quantitative data and high-level correlation between burnup/temperature and microstructure evolution blocks the development of predictive models and reduces the possibility of accelerating the qualification for new fuel forms. Historical characterization of fission gas bubbles in irradiated nuclear fuel relied on a simple threshold method working on low-resolution optical microscopy images. Advanced characterization of fission gas bubbles using scanning electron microscopic images reveals unprecedented details and extensive morphological data, which strains the effectiveness of conventional methods. This paper proposes a hybrid framework, based on digital image processing and deep learning models, to efficiently detect and classify fission gas bubbles from scanning electron microscopic images. The developed bubble annotation tool used a multitask deep learning network that integrates U-Net and ResNet to accomplish instance-level bubble segmentation. With limited annotated data, the model achieves a recall ratio of more than 90%, a leap forward compared to the threshold method. The model has the capability to identify fission gas bubbles with and without lanthanides to better understand the movement of lanthanide fission products and fuel cladding chemical interaction. Lastly, the deep learning model is versatile and applicable to the micro-structure segmentation of similar materials.

36 MATERIALS SCIENCE↗

Comparing storm resolving models and climates via unsupervised machine learning

Global storm-resolving models (GSRMs) have gained widespread interest because of the unprecedented detail with which they resolve the global climate. However, it remains difficult to quantify objective differences in how GSRMs resolve complex atmospheric formations. This lack of comprehensive tools for comparing model similarities is a problem in many disparate fields that involve simulation tools for complex data. To address this challenge we develop methods to estimate distributional distances based on both nonlinear dimensionality reduction and vector quantization. Our approach automatically learns physically meaningful notions of similarity from low-dimensional latent data representations that the different models produce. This enables an intercomparison of nine GSRMs based on their high-dimensional simulation data (2D vertical velocity snapshots) and reveals that only six are similar in their representation of atmospheric dynamics. Furthermore, we uncover signatures of the convective response to global warming in a fully unsupervised way. Our study provides a path toward evaluating future high-resolution simulation data more objectively.

54 ENVIRONMENTAL SCIENCES↗

Thin-film lithium niobate electro-optic terahertz wave detector

Here, the design, fabrication, and validation of a thin-film lithium niobate on insulator (LNOI) electro-optic (EO) time-domain terahertz (THz) wave detector is reported. LNOI offers unprecedented properties for the EO detection of freely propagating THz wave radiation pulses and transient electric fields because of the large EO coefficient of the material, engineering of the velocity matching of the THz wave and optical wave, and much reduced detector size. The proof-of-concept device is realized using thin-film lithium niobate optical waveguides forming a Mach–Zehnder interferometer with interferometer arms electrically poled in opposite directions. THz waves are coupled effectively to the fully dielectric device from free space without using antennas or plasmonics. The detection of THz waves with frequencies up to 800 GHz is successfully demonstrated. The detector allows for the detection of THz frequency electric fields up to 4.6 MV/m. The observed frequency response of the device agrees well with theoretical predictions.

47 OTHER INSTRUMENTATION↗

Increasing extreme hourly precipitation risk for New York City after Hurricane Ida

The remnants of Hurricane Ida caused major damage and death in the United States on September 1st, 2021, and 11 people drowned in flooded basement apartments within New York City (NYC). It was catastrophic because the maximum hourly precipitation intensity, recorded as 3.47 inches (88.1 mm) per hour at Central Park, was unprecedentedly high for the NYC region. The stormwater infrastructure in NYC is built for 1.75 inches (44.5 mm) per hour, and so understanding the dynamic risk associated with Ida can inform city planning efforts for climate change’s impact on short duration extreme precipitation events. We contextualize this storm’s record-breaking hourly intensity within the historical record as well as project its risk in the near- to medium-term future using nonstationary stochastic models. These models are conditioned on average temperature (T avg ) and cooling degree day (CDD) projections from three climate models as a covariate, each with a SSP 126 and SSP 370 scenario. The likelihood of such a storm was slowly increasing even before Ida happened, but the projected aggregate reoccurrence risk of an event of Ida’s magnitude over time from the non-stationary models ranges from 4 to 52 times higher than the risk given by the stationary model. Using CDD as a covariate resulted in risks that were more than twice the magnitude than when using T avg . Presenting both covariates provides a broader envelope of uncertainty, which highlights the importance and nuances in the choice of a regionally appropriate covariate for non-stationary risk analysis.

Mossel, Carolien↗

Advances in detection for neutron reflectometry with time-resolved imaging detectors

Thermal neutron detection in neutron scattering science is a challenging endeavour due to a limited number of technologies which are sensitive to these weakly interacting particles. While many improvements to conventional detectors are underway at various facilities, there is a great opportunity to make a leap in performance by combining the spatial resolution benefits of imaging and the temporal resolution and background discrimination of event-driven radiation detectors. This idea has been realized by using a neutron sensitive scintillator read out by a single-photon sensitive camera based on a Timepix3 ASIC. We demonstrate how such data-driven imaging sensors can enable unprecedented performance in neutron reflectometry using the ASTERIX instrument at the Los Alamos Neutron Scattering Center. Several samples were measured with both the new and a conventional 3 He detector systems. The results from this work demonstrate that these imaging based systems can satisfy performance parameters for the future QIKR reflectometer to be built at the Second Target Station at Oak Ridge National Laboratory. Further improvements to the detector are already underway which will allow streamlined and expedited experiments. We demonstrate at least a two order of magnitude increase in detection rate at an acceptable dead time and introduce a new way of tuning the detector efficiency using light collecting optics to accommodate highly intense direct beams which cannot be measured with any current detectors without severe attenuation. This will allow measurements of complete reflectometry profiles and using a single sample measurement combined with fewer direct beam calibration measurements on QIKR and potentially other reflectometers.

36 MATERIALS SCIENCE↗

Characterization of volcanic tuff pores pre- and post-underground nuclear detonation using ultra-small and small angle neutron scattering

The ability to accurately model the subsurface transport of radionuclides is fundamental to the remote detection and characterization of underground nuclear explosion (UNE) events. Developing more sophisticated transport models presents a significant opportunity to enhance monitoring capabilities, particularly in the reliable prediction of signature migration. Experimentally determined characterization of geologic materials associated with transport properties is the pertinent base information for such robust model development and calibration. Here, we report results from an unprecedented study demonstrating changes to the pore and fracture network structures in geological materials in response to UNEs over nanometer to micrometer length scales. Volcanic tuffs of five different lithological formations from pre- and post-UNE environments were collected from the Nevada National Security Site. Combined ultra-small and small-angle neutron scattering techniques were used to characterize the tuff pore structure. The results demonstrate measurable differences in the specific surface area and porosity of samples pre- and post-shot from texturally similar lithological formations, indicating that pore properties can serve as a direct physical signature of a UNE. The results also provide experimentally determined transport parameters in support of advanced model development through the integration of gas migration, hydrodynamic simulations, and geologic framework models.

54 ENVIRONMENTAL SCIENCES↗