Near-adjacent heavy lanthanide separation and sensing using dimerizing lanmodulins
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Biological and medical sciences↗
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Understanding Monsoonal Water Cycle Changes in a Warmer Climate in E3SMv1 Using a Normalized Gross Moist Stability Framework
Abstract One of the grand challenges of climate science is understanding the changes of the tropical rain belts and monsoon systems owing to CO 2 ‐induced warming. A promising path forward links the fluxes of energy and moisture to tropical circulation features. To this end, we make use of the Energy Exascale Earth System Model version 1, where the divergence of moist static energy and moisture have been calculated online, and employ a normalized gross moist stability (NGMS) diagnostic framework to understand the linkages between changes in the flow of energy and moisture within the monsoons. We focus on the Asian Summer Monsoon system and utilize a series of atmosphere‐land and atmosphere‐land‐ocean simulations to understand the connection between fluxes and monsoons. Uncoupled simulations with prescribed sea surface temperatures indicate that decreases in NGMS over land are important in explaining precipitation increases in response to both sea surface temperature and CO 2 increases. In fully coupled experiments, NGMS decreases remain an important contributor to the increase in P‐E, but the coupled simulations highlight the importance of consistent ocean and land responses in interpreting the monsoon changes. This study indicates that transient eddy fluxes play an important role in NGMS decreases and that a time‐mean view of the monsoon circulations is insufficient to quantify the link between future changes in the fluxes of energy and moisture. Compensation between dynamic and thermodynamic components of vertical moist static energy advection occurs, with the thermodynamic contribution dominating. The compensation is shown to be sensitive to relative humidity, with higher relative humidity leading to a stronger thermodynamic component.
Harrop, Bryce E.↗
Validation of the Community Land Model Version 5 over the Contiguous United States (CONUS) using in situ and remote sensing data sets
The Community Land Model (CLM) is an effective tool to simulate the biophysical and biogeochemical processes and their interactions with the atmosphere. Although CLM Version 5 (CLM5) constitutes various updates in these processes, its performance in simulating energy, water and carbon cycles over the Contiguous United States (CONUS) at scales which land surface changes and hydrometeorological and hydroclimatological applications are more locally relevant is yet to be assessed. In this study, we conducted three simulations at 0.125? during 1979-2018 over the CONUS using different configurations of CLM, namely CLM5-biogeochemistry (CLM5BGC), CLM4.5BGC, and CLM5-satellite phenology (CLM5SP). We validated and compared their simulations against multiple remote-sensed and in-situ datasets. Overall, the parametric and structural updates (e.g., carbon cost for nitrogen uptake, variable soil thickness, dry surface layer) in CLM5 improve its ability in capturing terrestrial biogeochemical dynamics. The low evapotranspiration in CLM5BGC is associated with biases in simulating vegetation phenological characteristics rather than soil water limitations. The mismatch between CLM5BGC-simulated peak leaf area index and reference data can be attributed to CLM5BGC's inability in simulating phenology of trees and grasses. The differences between CLM-simulated irrigation and reference estimates can be attributed to differences between processes represented in models and in reality, and uncertainties in input and validation datasets. Evaluation against observations at small catchments suggest that hydrologic parameters needed to be calibrated to improve simulations of runoff, especially subsurface runoff. Additional efforts are needed to incorporate spatially-distributed plant phenology and physiology parameters and regional-specific agricultural management practices (e.g., planting, harvest).
Cheng, Yanyan↗
4D Proxy Imaging of Fracture Dilation and Stress Shadowing Using Electrical Resistivity Tomography During High Pressure Injections into a Dense Rock Formation
Fluid flow through fractured rock systems is governed in large part by the distribution, interconnectivity, and size of fracture apertures. In-situ stress is one of the primary factors controlling fracture aperture, and one that is altered significantly during high-pressure fluid injections or extractions. Interactions between stress, pore pressure, aperture, and fluid flow can result in complex and evolving poroelastic behavior with significant implications regarding the predictability and risk of developing and managing deep subsurface reservoirs (geothermal, fossil energy, and geologic carbon sequestration). In saturated crystalline rocks, bulk electrical conductivity is highly sensitive to porosity, and therefore to fracture aperture size and distribution. We demonstrate the use of time-lapse 3D electrical resistivity tomography for remotely monitoring stress induced changes in aperture distribution during high pressure injections into a fractured rock system at a scale of tens of meters. Results reveal a complex and continuously evolving stress field involving aperture dilations in the natural fracture system and aperture contractions in adjacent zones of shadow stress. Results provide information about the spatiotemporal changes in the system behavior and point to the potential of electrical imaging for autonomously and remotely monitoring evolving stress conditions by proxy through changes in bulk electrical conductivity.
electrical resisitivity tomography, stress, 4D Tim↗
Spectral control of nonclassical light pulses using an integrated thin-film lithium niobate modulator
Abstract Manipulating the frequency and bandwidth of nonclassical light is essential for implementing frequency-encoded/multiplexed quantum computation, communication, and networking protocols, and for bridging spectral mismatch among various quantum systems. However, quantum spectral control requires a strong nonlinearity mediated by light, microwave, or acoustics, which is challenging to realize with high efficiency, low noise, and on an integrated chip. Here, we demonstrate both frequency shifting and bandwidth compression of heralded single-photon pulses using an integrated thin-film lithium niobate (TFLN) phase modulator. We achieve record-high electro-optic frequency shearing of telecom single photons over terahertz range (±641 GHz or ±5.2 nm), enabling high visibility quantum interference between frequency-nondegenerate photon pairs. We further operate the modulator as a time lens and demonstrate over eighteen-fold (6.55 nm to 0.35 nm) bandwidth compression of single photons. Our results showcase the viability and promise of on-chip quantum spectral control for scalable photonic quantum information processing.
Optics↗
Inhibitors of BRAF dimers using an allosteric site
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Cotto-Rios, Xiomaris M.↗
Decoding substance use disorder severity from clinical notes using a large language model
Substance use disorder (SUD) poses a major concern due to its detrimental effects on health and society. SUD identification and treatment depend on a variety of factors such as severity, co-determinants (e.g., withdrawal symptoms), and social determinants of health. Existing diagnostic coding systems used by insurance providers, like the International Classification of Diseases (ICD-10), lack granularity for certain diagnoses, but American clinicians will add this granularity (as that found within the Diagnostic and Statistical Manual of Mental Disorders classification or DSM-5) as supplemental unstructured text in clinical notes. Traditional natural language processing (NLP) methods face limitations in accurately parsing such diverse clinical language. Large language models (LLMs) offer promise in overcoming these challenges by adapting to diverse language patterns. This study investigates the application of LLMs for extracting severity-related information for various SUD diagnoses from clinical notes. We propose a workflow employing zero-shot learning of LLMs with carefully crafted prompts and post-processing techniques. Through experimentation with Flan-T5, an open-source LLM, we demonstrate its superior recall compared to the rule-based approach. Focusing on 11 categories of SUD diagnoses, we show the effectiveness of LLMs in extracting severity information, contributing to improved risk assessment and treatment planning for SUD patients.
60 APPLIED LIFE SCIENCES↗
Alkaline earth ion exchange study in pure silica LTA zeolites using periodic first-principles calculations
Experiments show that Zeolites, such as Linde Type A (LTA), are promising materials for radioactive decontamination processes. In this work, the thermodynamic properties associated with alkaline earth ion (Ca2+, Sr2+ and Ba2+) exchange in pure silica LTA was studied using periodic first-principles calculations. The adsorption energies of alkaline earth ions compared with that of Na+ were investigated. The driving force for the alkaline earth exchange and related isotherms were calculated, and analyzed as a function of the electron chemical potential. The results demonstrate that Na+ in a pure silica LTA can completely be removed by Ba2+ and almost completely be removed by Sr2+ from a stream, but cannot be effectively exchanged by Ca2+. We also showed that electron-donating dopants should suppress the Sr2+ and Ba2+ ion exchange, and that there is a substantial preference for incorporating Ba2+ over Sr2+. Lastly, the substantial difference between the adsorption energies of the ions in an assumed vacuum and those computed in water suggests that a solvation model is needed for accurate representation of ion adsorption in an LTA zeolite.
Kocevski, Vancho↗
A spot test for determination of residual TBA levels in 18 F-radiotracers for human use using Dragendorff reagent
When utilizing [ 18 F]tetrabutylammonium fluoride ([ 18 F]TBAF) in the synthesis of 18 F-labeled radiotracers for clinical positron emission tomography (PET) imaging, it is necessary to confirm that residual TBA levels in formulated doses do not exceed established specifications (≤2.6 mg per patient dose). Historically this has been accomplished using HPLC, but this is time consuming for short-lived PET radiotracers and limited by the need for expensive equipment. This motivated us to introduce a TLC spot test for determining residual TBA, and we have developed a new method which employs the Dragendorff reagent. Herein we report details of the TLC method and use it to quantify residual TBA in different formulations of 6-[ 18 F]fluoro-DOPA.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Tuning the work function of nickel oxide using triethoxysilane functionalized monolayers
We have synthesized a family of styryl-based molecules that have been attached to nickel oxide films using a novel ethoxysilane chemistry to modify the work function over a range of 900 meV.
Chen, Gang↗
Resolving the organization of CO 2 molecules confined in silica nanopores using in situ small-angle neutron scattering and molecular dynamics simulations
This work quantifies the core–shell structure of nano-confined CO 2 molecules under pressure in silica pores using in operando small-angle neutron scattering (SANS) measurements and molecular dynamics simulations.
Mohammed, Sohaib↗
Neutron time-of-flight detectors (nTOF) used at Sandia’s Z-Machine
Neutron time-of-flight (nTOF) detectors have been used on Sandia National Laboratories’ Z-Machine for inertial confinement fusion and magnetized liner fusion experiments to infer physics parameters including the apparent fuel-ion temperature, neutron yield, the magnetic-radius product (BR), and the liner rho-r. Single-paddle, dual-paddle, and co-axial scintillation nTOF detectors are used in axial lines-of-sight (LOS) and LOS that are 12° from the midplane. Detector fabrication, characterization, and calibration are discussed.
Chandler, G. A. (ORCID:0000000219640927)↗
Exploring the impact of ions on oxygen K-edge X-ray absorption spectroscopy in NaCl solution using the GW-Bethe-Salpeter-equation approach
X-ray absorption spectroscopy (XAS) is a powerful experimental tool to probe the local structure in materials with the core hole excitations. Here, the oxygen K-edge XAS spectra of the NaCl solution and pure water are computed by using a recently developed GW-Bethe-Salpeter equation approach, based on configurations modeled by path-integral molecular dynamics with the deep-learning technique. The neural network is trained on ab initio data obtained with strongly constrained and appropriately normed density functional theory. The observed changes in the XAS features of the NaCl solution, compared to those of pure water, are in good agreement between experimental and theoretical results. We provided detailed explanations for these spectral changes that occur when NaCl is solvated in pure water. Specifically, the presence of solvating ion pairs leads to localization of electron-hole excitons. As a result, our theoretical XAS results support the theory that the effects of the solvating ions on the H-bond network are mainly confined within the first hydration shell of ions, however beyond the shell the arrangement of water molecules remains to be comparable to that observed in pure water.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Identifying divertor detachment using a machine learning model trained on divertor camera images from DIII-D
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Physics - Plasma physics↗
Examining astrophysical gas cloud collapse using an optical depth-scaled, x-ray-irradiated, carbon-foam sphere
When stellar radiation interacts with a molecular cloud, the cloud's fate depends on the strength of the incident radiation and the radiation's mean-free-path within the cloud [F. Bertoldi, Astrophys. J. 346, 735–755 (1989)]. Under the right conditions, the radiation compresses the cloud and a star formation may occur. Where and when the stellar formation occurs in the cloud's collapse are open questions. Direct observation of the complete star–cloud lifecycle is nearly impossible due to the immense timescales and distances over which the interaction occurs. Laboratory astrophysics offers a way to investigate such a system by scaling the important astrophysical parameters to the laboratory. This work describes laboratory experiments to study the radiation-driven implosion of clouds, using x rays from a laser-irradiated, thin, gold foil as a surrogate star and a carbon-foam sphere as a surrogate cloud. An optically thick system, theoretically corresponding to a star-forming regime, was selected by choice of the foam density. Gold foil and sphere motions were imaged by x-ray radiography. Radiographic images show the formation of an interface between rarefied gold and carbon plasmas, a shock moving into the sphere, and a blunting of the initial sphere's shape. Measurements show that the shock moved linearly around 64 μm/ns into the sphere, and the gold–carbon interface formed by 2 ns at the sphere edge remained stationary. The deformation of the sphere was driven by the incident radiation and not by mechanical pressures applied by gold plasma. The blunting of the sphere was likely due to the geometric reduction of flux near the sphere's poles. Higher x-ray flux near the sphere's equator caused high compression and a faster shock, which flattened the sphere. We will discuss the results and implications of our observations.
VanDervort, R. W. [University of Michigan 1 , Ann ↗
Radiation Source Localization Using Surrogate Models Constructed from 3-D Monte Carlo Transport Physics Simulations
Recent research has focused on the development of surrogate models for radiation source localization in a simulated urban domain. We employ the Monte Carlo N-Particle (MCNP) code to provide high- delity simulations of radiation transport within an urban domain. The model is constructed to employ a source location (x, y, z) as input and return the estimated count rate for a set of speci ed detector locations. Because MCNP simulations are computationally expensive, we develop e cient and accurate surrogate models of the detector responses. We construct surrogate models using Gaussian processes (GP) and neural networks (NN) that we train and verify using the MCNP simulations. The trained surrogate models provide an e cient framework for Bayesian inference and experimental design. We employ Delayed Rejection Adaptive Metropolis (DRAM), a Markov Chain Monte Carlo (MCMC) algorithm, to infer the location and intensity of an unknown source. The DRAM results yield a posterior probability distribution for the source's location conditioned on the observed detector count rates. The posterior distribution exhibits regions of high and low probability within the simulated environment identifying potential source locations. In this manner, we can quantify the source location to within at least one of these regions of high probability in the considered cases. Employing these methods, we are able to reduce the space of potential source locations by at least 60%.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Large-Eddy Simulations of Idealized Atmospheric Boundary Layers Using Nalu-Wind
Accurate prediction of wind-plant performance relies, in part, on properly characterizing the turbulent atmospheric boundary layer (ABL) flow in which wind turbines operate. Large-eddy simulation (LES) is a powerful tool for simulating ABLs because it resolves the largest, most energetic scales of three-dimensional turbulent motions. Yet LES predictions are well known to depend on modeling choices such as grid resolution, numerical discretization schemes, and closures for unresolved scales of turbulence. Here, we evaluate how these choices influence predictions of ABL winds using Nalu-Wind, a wind-specific fork of the open-source, generalized, unstructured, massively parallel flow solver NaluCFD/Nalu.
17 WIND ENERGY↗
To use or not to use synthetic stellar spectra in population synthesis models?
ABSTRACT Stellar population synthesis (SPS) models are invaluable to study star clusters and galaxies. They provide means to extract stellar masses, stellar ages, star formation histories, chemical enrichment, and dust content of galaxies from their integrated spectral energy distributions, colours, or spectra. As most models, they contain uncertainties that can hamper our ability to model and interpret observed spectra. This work aims at studying a specific source of model uncertainty: the choice of an empirical versus a synthetic stellar spectral library. Empirical libraries suffer from limited coverage of parameter space, while synthetic libraries suffer from modelling inaccuracies. Given our current inability to have both ideal stellar-parameter coverage with ideal stellar spectra, what should one favour: better coverage of the parameters (synthetic library) or better spectra on a star-by-star basis (empirical library)? To study this question, we build a synthetic stellar library mimicking the coverage of an empirical library, and SPS models with different choices of stellar library tailored to these investigations. Through the comparison of model predictions and the spectral fitting of a sample of nearby galaxies, we learned that predicted colours are more affected by the coverage effect than the choice of a synthetic versus empirical library; the effects on predicted spectral indices are multiple and defy simple conclusions; derived galaxy ages are virtually unaffected by the choice of the library, but are underestimated when SPS models with limited parameter coverage are used; metallicities are robust against limited HRD coverage, but are underestimated when using synthetic libraries.
Coelho, Paula R. T.↗