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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Elucidating the Role of Hydrogen Bonding in the Optical Spectroscopy of the Solvated Green Fluorescent Protein Chromophore: Using Machine Learning to Establish the Importance of High-Level Electronic Structure

Hydrogen bonding interactions with chromophores in chemical and biological environments play a key role in determining their electronic absorption and relaxation processes, which are manifested in their linear and multidimensional optical spectra. For chromophores in the condensed phase, the large number of atoms needed to simulate the environment has traditionally prohibited the use of high-level excited-state electronic structure methods. By leveraging transfer learning, we show how to construct machine-learned models to accurately predict the high-level excitation energies of a chromophore in solution from only 400 high-level calculations. Here, we show that when the electronic excitations of the green fluorescent protein chromophore in water are treated using EOM-CCSD embedded in a DFT description of the solvent the optical spectrum is correctly captured and that this improvement arises from correctly treating the coupling of the electronic transition to electric fields, which leads to a larger response upon hydrogen bonding between the chromophore and water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Pathway to Complete Energy Sector Decarbonization with Available Iridium Resources using Ultralow Loaded Water Electrolyzers

We present ultralow Ir-loaded (ULL) proton exchange membrane water electrolyzer (PEMWE) cells that can produce enough hydrogen to largely decarbonize the global natural gas, transportation, and electrical storage sectors by 2050, using only half of the annual global Ir production for PEMWE deployment. This represents a significant improvement in PEMWE's global potential, enabled by careful control of the anode catalyst layer (CL), including its mesostructure and catalyst dispersion. Using commercially relevant membranes (Nafion 117), cell materials, electrocatalysts, and fabrication techniques, we achieve at peak a 250× improvement in Ir mass activity over commercial PEMWEs. An optimal Ir loading of 0.011 mg Ir cm -2 operated at an Ir-specific power of ~100 MW kg Ir -1 at a cell potential of ~1.66 V versus RHE (85% higher heating value efficiency). Here, we further evaluate the performance limitations within the ULL regime and offer new insights and guidance in CL design relevant to the broader energy conversion field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Robust Solid/Electrolyte Interphase (SEI) formation on Si Anodes Using Glyme-based Electrolytes

Silicon (Si) is the most naturally abundant element possessing 10-fold theoretical capacity than graphitebased anodes. The practicality of implementing Si anodes is, however limited by the unstable solidelectrolyte interphase (SEI) and anode fracturing during continuous lithiation/delithiation. We demonstrate that glyme-based electrolytes (GlyEls) assure a conformal SEI on Si and keep the Si ‘fracture-free’. Benchmarking against the optimal, commonly-used carbonate electrolyte with the fluoroethylene carbonate (FEC) additive, Si anode cycled in a GlyEl exhibits reduced early parasitic current (by 62.5%) and interfacial resistance (by 72.8%), while the cell capacity retention is promoted by >7% over a course of 110 cycles. The mechanistic investigation by X-ray photoelectron spectroscopy (XPS) and energy-dispersive X-ray spectroscopy (EDX) indicates GlyEl enriches Si SEI with elastic polyether but diminishes its carbonate species. Glyme-based electrolytes prove viable in stabilizing the SEI on silicon for future high energy density lithium-ion batteries.

Yang, Guang↗
DOE OSTI2021

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↗
DOE OSTI2021

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↗
DOE OSTI2022

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↗
DOE OSTI2025

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↗
DOE OSTI2020

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↗
DOE OSTI2022

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)↗
DOE OSTI2023

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↗
DOE OSTI2025

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 ↗
DOE OSTI2020

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 ↗