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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Focused Ion Beam Preparation of Low Melting Point Metals: Lessons Learned From Indium

Indium (In) and other low melting point metals are used as interconnects in a variety of hybridized circuits and a full understanding of the metallurgy of these interconnects is important to the reliability and performance of the devices. Here, this paper shows that room temperature focused ion beam (FIB) preparation of cross-sections, using Ga + or Xe + can result in artifacts that obscure the true In microbump structure. The use of modified milling strategies to minimize the increased local sample temperature are shown to produce cross-sections that are representative of the In bump microstructure in some sample configurations. Furthermore, cooling of the sample to cryogenic temperatures is shown to reliably eliminate artifacts in FIB prepared cross-sections of In bumps allowing the true bump microstructure to be observed.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Simplifying the Chemical Design of Nonfused-Ring Electron Acceptors─Lessons Learned from Thienothiophene and Benzodithiophene Cores

Nonfused-ring electron acceptors (NFREA)s have been proposed as alternatives to fused-ring acceptors in organic photovoltaics (OPV)s. The simpler molecular design of NFREAs results in a reduced synthetic complexity, potentially lowering manufacturing costs, and easier access to desired optoelectronic properties by structural modifications. However, they have not seen the same rise in popularity as fused nonfullerene acceptors (NFA)s due to their lower performances in devices. In this work, we explore structure–property relationships of three NFREA molecules based on thieno[3,2-b]thiophene (TT) and benzo[1,2-b:4,5-b′]dithiophene (BDT) cores and malononitrile functionalized-isatin end group acceptors. We describe their synthetic routes, computational analysis, and photophysical and electronic properties. Here, we investigated the effect of changing the core from TT to BDT on electronic properties of the molecules─a result of raising/lowering of the frontier molecular orbital (FMO) levels. We also explored the effect of branched vs nonbranched alkyl groups on the morphological and blend-capabilities in bulk heterojunction (BHJ) OPV devices. These effects were then reflected in the overall device performances, primarily due to favorable FMO energy alignment between the NFREA and polymer. To investigate the behavior of the excited states of the NFREAs within the active layer of the devices, we performed time-resolved microwave conductivity and transient absorption experiments, which confirmed that the TT molecules exhibited very low conductance while the BDT molecule showed moderate photoconductance. Our combined theoretical, synthetic, device, and charge carrier dynamics studies of these materials reveal the central role that structure–property relationships play in future molecular designs of NFREAs that can perform as well as their fused counterparts.

14 SOLAR ENERGY↗
DOE OSTI2023

Response of Ecosystem Productivity to High Vapor Pressure Deficit and Low Soil Moisture: Lessons Learned From the Global Eddy-Covariance Observations

Although there is mounting concern about how high vapor pressure deficit (VPD) and low soil moisture (SM) affect ecosystem productivity, their relative importance is still under debate. Here, we comprehensively quantified the relative impacts of these two factors on ecosystem gross primary production (GPP) using observations from a global network of eddy-covariance towers and two approaches (sensitivity analysis and linear regression model). Both approaches agree that a higher percentage of sites experience GPP reduction from high VPD than from low SM over the growing season. However, the constraint of high VPD and low SM on GPP reduction is tightly linked with climates and plant functional types. Humid and mesic ecosystems including forests and grasslands are dominated by VPD, while the semi-arid and arid ecosystems including shrublands and savannas are dominated by SM. The varying dominant role of these two factors on GPP is closely related to plant stomatal behavior, as predicted by a stomatal conductance model. Additionally, we highlight the non-linear impact of SM on GPP during droughts and the possible underestimation of the SM effects for deep-rooted plants when only using surface-layer SM. Our results shed light on a better understanding of the impacts of VPD and SM on vegetation productivity, with important implications for modeling the response and feedback of ecosystem dynamics to current and future climates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The Role of Atmospheric Rivers on Groundwater: Lessons Learned From an Extreme Wet Year

Abstract In the coastal regions of the western United States, atmospheric rivers (ARs) are associated with the largest precipitation generating storms and contribute up to half of annual precipitation, but the impact of ARs on the integrated hydrologic cycle, specifically on groundwater storage and hydrodynamics, is largely unknown. To better explore the hydrologic behavior of AR versus non‐AR event precipitation, we present a novel combination of two water tracking methods (one in the atmosphere and one in the subsurface) to explicitly track the full lifecycle of water parcels generated by ARs. Simulations of northern California's Cosumnes River watershed during the record wet 2017 water year are performed via the coupling of a high‐resolution regional climate model and a land surface‐groundwater model accounting for lateral groundwater flow. Despite ARs contributing more precipitation than non‐AR storms, we find less AR water is preferentially stored in aquifers by year end. Fractionally, ARs result in 300% less snow derived groundwater‐recharged compared to non‐AR precipitation. Rain‐on‐snow (RoS) plays an important role in AR‐driven discharge, where over 50% of total discharge from ARs snow is from RoS events. Finally, despite record‐breaking annual precipitation, simulated groundwater depletion occurs by year end due to estimates of groundwater pumping activities. The results from these simulations serve as a partial analogue of future hydrologic conditions where ARs are expected to intensify and provide a greater fraction of annual precipitation due to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Lessons learned from first-principles calculations of transition metal oxides

Transition metal oxides (TMOs) are an important class of materials with diverse applications, ranging from memristors to photoelectrochemical cells. First-principles calculations are critical for understanding these complex materials at an atomic level and establishing relationships between atomic and electronic structures, particularly for probing quantities difficult or inaccessible to experiment. Here, we discuss computational strategies used to understand TMOs by focusing on two examples, a photoanode material, BiVO4, and an oxide for low-power electronics, La1−xSrxCoO3. We highlight key aspects required for the modeling of TMOs, namely, the descriptions of how oxygen vacancies, extrinsic doping, the magnetic state, and polaron formation impact their electronic and atomic structures and, consequently, many of the observed properties.

Vo, Hien (ORCID:0000000158315599)↗
DOE OSTI2025

The lessons learned from ephemeral nuclei

Recent experimental analyses of fleeting clusters of protons and neutrons put the very notion of the atomic nucleus in a new light.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

STAR Data Production Workflow on HPC: Lessons Learned & Best Practices

The Solenoidal Tracker at RHIC (STAR) is a multi-national supported experiment located at Brookhaven National Lab. The raw physics data captured from the detector is on the order of tens of PBytes per data acquisition campaign, which makes STAR fit well within the definition of a big data science experiment. The production of the data has typically run on standard nodes or on standard Grid computing environments. All embedding simulations (complex workflow mixing real and simulated events) have been run on standard Linux resources at the National Energy Research Scientific Computing Center (NERSC) aka PDSF. However, HPC resources such as Cori have become available for STAR's data production as well as embedding, and STAR has been the very first experiment to show feasibility of running a sustainable data production campaign on this computing resource. The use of Docker containers with Shifter is required to run on HPC @ NERSC - this approach encapsulates the environment in which a standard STAR workflow runs. From the deployment of a tailored Scientific Linux environment (requiring many of its own libraries and special configurations required to run) to the deployment of third-party software and the STAR specific software stack, it has become impractical to rely on a set of containers containing each specific software release. To this extent, solutions based on the CERN VM File System (CVMFS) for the deployment of software and services have been employed in HENP, but one needs to make careful scalability considerations when using a resource like Cori, such as not allowing all software to be deployed in containers or bare node. Additionally, CVMFS clients are not compatible on Cori nodes and one needs to rely on an indirect NFS/DVS mount scheme. In our contribution, we will discuss our strategies from the past and our current solution based on CVMFS. Furthermore, running on HPC is not a simple task as each aspect of the workflow must be enabled to scale, run efficiently, and the workflow needs to fit within the boundaries of the provided queue system (SLURM in this case). Lastly, we will also discuss what we have learned so far about what is the best method for grouping jobs to maximize a single 48 core HPC node within a specific time frame and maximize our workflow efficiency.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Lessons Learned Using in-situ TEM Liquid Corrosion of Al Alloys

Al and Al alloys are of interest in energy applications due to their strength and low weight [1] in addition to their electrochemical properties for aluminum-air batteries for energy storage [2]. However, Al alloys also are susceptible to corrosion in a variety of environments including liquid electrolytes and in solar panels [3], which has led to a great deal of research to understand and improve corrosion resistance in these materials. Al metal forms a native, passivating oxide layer in the presence of ambient air, which slows corrosion initiation. However, pitting still occurs as this protective layer breaks down in the presence of electrolytes. Thin metal Al films were used in these experiments to observe initiation and growth of pitting, which can be used as an approximation of corrosion initiation behavior in bulk samples.

alluminum alloys↗
DOE OSTI2020

Implications of the search for optical counterparts during the second part of the Advanced LIGO’s and Advanced Virgo’s third observing run: lessons learned for future follow-up observations

ABSTRACT Joint multimessenger observations with gravitational waves and electromagnetic (EM) data offer new insights into the astrophysical studies of compact objects. The third Advanced LIGO and Advanced Virgo observing run began on 2019 April 1; during the 11 months of observation, there have been 14 compact binary systems candidates for which at least one component is potentially a neutron star. Although intensive follow-up campaigns involving tens of ground and space-based observatories searched for counterparts, no EM counterpart has been detected. Following on a previous study of the first six months of the campaign, we present in this paper the next five months of the campaign from 2019 October to 2020 March. We highlight two neutron star–black hole candidates (S191205ah and S200105ae), two binary neutron star candidates (S191213g and S200213t), and a binary merger with a possible neutron star and a ‘MassGap’ component, S200115j. Assuming that the gravitational-wave (GW) candidates are of astrophysical origin and their location was covered by optical telescopes, we derive possible constraints on the matter ejected during the events based on the non-detection of counterparts. We find that the follow-up observations during the second half of the third observing run did not meet the necessary sensitivity to constrain the source properties of the potential GW candidate. Consequently, we suggest that different strategies have to be used to allow a better usage of the available telescope time. We examine different choices for follow-up surveys to optimize sky localization coverage versus observational depth to understand the likelihood of counterpart detection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Lessons learned from the two largest Galaxy morphological classification catalogues built by convolutional neural networks

ABSTRACT We compare the two largest galaxy morphology catalogues, which separate early- and late-type galaxies at intermediate redshift. The two catalogues were built by applying supervised deep learning (convolutional neural networks, CNNs) to the Dark Energy Survey data down to a magnitude limit of ∼21 mag. The methodologies used for the construction of the catalogues include differences such as the cutout sizes, the labels used for training, and the input to the CNN – monochromatic images versus gri-band normalized images. In addition, one catalogue is trained using bright galaxies observed with DES (i < 18), while the other is trained with bright galaxies (r < 17.5) and ‘emulated’ galaxies up to r-band magnitude 22.5. Despite the different approaches, the agreement between the two catalogues is excellent up to i < 19, demonstrating that CNN predictions are reliable for samples at least one magnitude fainter than the training sample limit. It also shows that morphological classifications based on monochromatic images are comparable to those based on gri-band images, at least in the bright regime. At fainter magnitudes, i > 19, the overall agreement is good (∼95 per cent), but is mostly driven by the large spiral fraction in the two catalogues. In contrast, the agreement within the elliptical population is not as good, especially at faint magnitudes. By studying the mismatched cases, we are able to identify lenticular galaxies (at least up to i < 19), which are difficult to distinguish using standard classification approaches. The synergy of both catalogues provides an unique opportunity to select a population of unusual galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗