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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evaluation of Autoconversion Representation in E3SMv2 Using an Ensemble of Large-Eddy Simulations of Low-Level Warm Clouds

In numerical atmospheric models that treat cloud and rain droplet populations as separate condensate categories, precipitation initiation in warm clouds is often represented by an autoconversion rate (Au), which is the rate of formation of new rain droplets through the collisions of cloud droplets. Being a function of the cloud droplet size distribution (DSD), the local Au is commonly parameterized as a function of DSD moments: cloud droplet number (n c ) and mass (q c ) concentrations. When applied in a large-scale model, the grid-mean Au must also include a correction, or enhancement factor, to account for the horizontal variability of the cloud properties across the model grid. In this study, we evaluate the Au representation in the Energy Exascale Earth System Model version 2 (E3SMv2) climate model using large-eddy simulations (LES), which explicitly resolve cloud droplet spectra, and therefore the local Au, as well as its spatial variability. The analysis of an ensemble of warm low-level cloud cases shows that the E3SMv2 formulation represents the Au reasonably well compared to the horizontally averaged explicitly computed rate from LES. The agreement, however, comes from a combination of an underestimated E3SM-tuned local Au rate and an overestimated subgrid cloud variability enhancement factor. The latter bias is traced to neglecting the horizontal variability of n c and its co-variability with q c in parameterizing the grid-mean Au.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

PNV J00444033+4113068: Early superhumps with 0.7 mag amplitude and non-red color

Abstract In the first days of WZ Sge-type dwarf nova (DN) outbursts, the 2 : 1 resonance induces a spiral arm structure in the accretion disk, which is observed as early superhumps in optical light curves. We reports on our optical observations of an eclipsing WZ Sge-type DN PNV J00444033+4113068 during its 2021 superoutburst using the 3.8 m Seimei telescope and through the Variable Star Network collaboration. The eclipse analysis showed that its orbital period was 0.055425534(1) d. Our observations confirmed early superhumps with an amplitude of 0.7 mag, the largest amplitude among known WZ Sge-type DNe. More interestingly, its early superhumps became the reddest around their secondary minimum, whereas other WZ Sge-type DNe show the reddest color around the early superhump maximum. The spectrum around the peak of the outburst showed two double-peaked emission lines of He ii 4686 Å and Hα with a peak separation of ≥700 km s−1, supporting a very high-inclination system. With the early superhump mapping, the unique profile and color of the early superhump are successfully reproduced by an accretion disk with a vertically extended double arm structure. Therefore, a large amplitude and a unique color behavior of the early superhumps in PNV J00444033+4113068 can be explained by the 2 : 1 resonance model along with other WZ Sge-type DNe.

Tampo, Yusuke (ORCID:0000000301963936)↗
DOE OSTI2020

Analysis of Air-Purifying Respirator (APR) Cartridge Performance Testing on Hanford Tanks SX-101 and SX-104 (Vol.1)

Washington River Protection Solutions (WRPS) conducted tests on two types of chemical cartridges for use in air-purifying respirators to determine the period of time that the cartridges would provide adequate performance1 to protect workers when exposed to a mixture of Chemicals of Potential Concern (COPC) from vapors exiting the headspaces of Hanford tanks SX-101 and SX-104. The Occupational Safety and Health Administration (OSHA) considers cartridge testing a valid approach for establishing cartridge change schedules.2 Testing is commonly applied in situations where mixtures of COPCs exist and where other approaches such as manufacturer recommendations and modeling are less reliable. The tests were designed and conducted to ensure measurement and/or control of the key variables OSHA identified as important to estimate the cartridge service life, including temperature, humidity, COPC concentration, breathing rate, and cartridge adsorption capacity. Testing was conducted from June 16-17, 2017, and June 23-24, 2017, using headspace vapors from Hanford tank SX-104 and Hanford tank SX-101, respectively. Headspace vapors under static conditions were fed to a respirator cartridge test stand developed by WRPS in collaboration with HiLine Engineering (Richland, Washington). Multipurpose respirator cartridges, SCOTT 7422-SD1 and SCOTT 7422-SC1 (SCOTT Safety, Monroe, North Carolina), were assessed on separate days. Sample media (sorbent tubes) were used to collect samples of the vapor stream entering and exiting the respirator cartridges, and subsequently were analyzed for COPC concentrations. Pacific Northwest National Laboratory was tasked with conducting an independent analysis of the analytical results and making recommendations based on the results for respiratory cartridge performance and service life.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Injury severity analysis of truck-involved crashes under different weather conditions

This paper investigates truck-involved crashes to determine the statistically significant factors that contribute to injury severity under different weather conditions. The analysis uses crash data from the state of Ohio between 2011 and 2015 available from the Highway Safety Information System. To determine if weather conditions should be considered separately for truck safety analyses, parameter transferability tests are conducted; the results suggest that weather conditions should be modeled separately with a high level of statistical confidence. To this end, three separate mixed logit models are estimated for three different weather conditions: normal, rain and snow. The estimated models identify a variety of statistically significant factors influencing the injury severity. Different weather conditions are found to have different contributing effects on injury severity in truck-involved crashes. Rural, rear-end and sideswipe crash parameters were found to have significantly different levels of impact on injury severity. Based on the findings of this study, several countermeasures are suggested: 1) safety and enforcement programs should focus on female truck drivers, 2) a variable speed limit sign should be used to lower speeds of trucks during rainy condition, and 3) trucks should be restricted or prohibited on non-interstates during rainy and snowy conditions. These countermeasures could reduce the number and severity of truck-involved crashes under different weather conditions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Mixed-strategy approach to band-edge analysis and modeling in semiconductors

In semiconductor physics, the Urbach rule describes an exponential dependence of the UV-Vis absorption coefficient on photon energy at the band edge. The rule is so ubiquitously applied that a single common mechanism, variability in the local potential, is generally considered to be the cause of exponential band edges. Variability in the local potential may be caused by alloy inhomogeneity, structural defects, impurities, thermal excitation, or any other mechanism that interrupts ideal crystallinity and creates disorder. A crucial point of the Urbach rule is its development for band edges which approach linearity when plotted on a logarithmic scale. The rule was not developed in the context of nonlinear band edges with complex fine structure. Even so, this model has been applied extensively to band edges with such features. Using differential analysis and deconvolution, we develop an analytical technique capable of separating the components responsible for the fine structure observed. This approach reduces challenging signal-artifact convolution problems to a simple linear combination. Furthermore, we develop a model that can be applied to the nonlinear band-edge signals extracted. In this work, we show that in the limiting case of linearity, our model is consistent with and produces the same results as the linear Urbach model. Our model is capable of bypassing “tailing” as an indirect measure of the spread in the local potential and gives a direct measure of this quantity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Organic Matter Composition in June 2023 and September 2023 Across the McKenzie Sub-Basin Impacted by the 2020 Holiday Farm Fire

This dataset represents results from a field study aiming to understand the variability in post-fire responses of dissolved organic matter and determine drivers of post-fire responses. Samples were collected at 58 sites within the McKenzie River Watershed (Oregon, USA) that were upstream, within, and downstream of the Holiday Farm Fire burn perimeter. The samples were collected in June 2023 and September 2023 during storm events, approximately 3 years post-fire. Samples were characterized for benezenepolycarboxylic acids (BPCA) and ultra-high resolution mass spectrometry. Dissolved organic carbon and optics (absorbance and fluorescence) data can be found in a separate data packages (https://ir.library.oregonstate.edu/concern/datasets/zc77sz60m, https://ir.library.oregonstate.edu/concern/datasets/mc87q034m). Related data from a subset of sites from 2020-2022 can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1869708 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2478546. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset contains (1) file-level metadata; (2) data dictionary; (3) data package readme; (4) metadata; (5) methods information; (6) benzene polycarboxylic acid (BPCA) concentration data; (7) Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) methods; (8) folder of high resolution characterization of organic matter via 12 Tesla FTICR-MS data generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). This package contains the following file types: csv, xml, pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

WIND Toolkit Long-Term Ensemble Dataset

WIND Toolkit Long-term Ensemble Dataset (WTK-LED), an updated version of the meteorological WIND Toolkit, is a meteorological dataset providing high-resolution time series, including interannual variability and model uncertainty of wind speed at every modeling grid point to indicate ranges of possible wind speeds. The data were produced using the Weather Research and Forecasting Model (WRF). The vertical grid used in WTK-LED includes many vertical layers in the atmospheric boundary layer to provide information of atmospheric quantities across the rotor layer of utility scale and distributed wind turbines. The WTK-LED includes: (1) Numerical simulations of wind speed and other meteorological variables covering the contiguous United States (CONUS) and Alaska, with high-resolution (5-minute [min], 2-kilometer [km]) data for 3 years (2018-2020): WTK-LED CONUS, WTK-LED Alaska. (2) Climate simulations from Argonne National Laboratory covering North America, including Alaska, Canada, and most of Mexico and the Caribbean islands. These simulations complement the new WTK-LED to offer a 4-km, hourly dataset covering 20 years (2001-2020): WTK-LED Climate. (3) Specific long-term, high-resolution offshore simulations have been conducted separately for the U.S. coasts, Hawaii, and the Great Lakes, leading to the 2023 National Offshore Wind dataset: NOW-23. The data for Hawaii include land-based data and are part of WTK-LED Hawaii. Because the accuracy of simulations from a mesoscale model, such as WRF, varies depending on the location and weather situation, and can reach up to several m/s for wind speed, we provide simulated wind speed uncertainty estimates to the community to be used in conjunction with the deterministic model simulations. This dataset was developed to satisfy a wide group of stakeholders across various wind energy disciplines, including but not limited to stakeholders in the distributed and utility scale wind industry, the new emerging airborne wind energy field, grid integration, power systems modeling, environmental modeling, and researchers in academia, and to close some of the gaps that current public datasets have. Based on our validation results to date, we suggest use cases and applications for each dataset of the WTK-LED as shown in "WTK-LED Use Cases" resource below.

Array↗
DOE OSTI2020

Optimization-based, property-preserving finite element methods for scalar advection equations and their connection to Algebraic Flux Correction

In this paper, we continue our efforts to exploit optimization and control ideas as a common foundation for the development of property-preserving numerical methods. Here we focus on a class of scalar advection equations whose solutions have fixed mass in a given Eulerian region and constant bounds in any Lagrangian volume. Our approach separates discretization of the equations from the preservation of their solution properties by treating the latter as optimization constraints. This relieves the discretization process from having to comply with additional restrictions and makes stability and accuracy the sole considerations in its design. A property-preserving solution is then sought as a state that minimizes the distance to an optimally accurate but not property-preserving target solution computed by the scheme, subject to constraints enforcing discrete proxies of the desired properties. Furthermore, we consider two such formulations in which the optimization variables are given by the nodal solution values and suitably defined nodal fluxes, respectively. A key result of the paper reveals that a standard Algebraic Flux Correction (AFC) scheme is a modified version of the second formulation obtained by shrinking its feasible set to a hypercube. In conclusion, we present numerical studies illustrating the optimization-based formulations and comparing them with AFC

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Intermittent Frontogenesis in the Alboran Sea

Abstract We present a phenomenological description and dynamical analysis of the Alboran fronts using a realistic simulation at submesoscale resolution. The study is focused on east Alboran fronts emerging within relatively strong flows that separate from the Spanish coast into the basin interior. Despite modest lateral shifting associated with the position of the Alboran anticyclonic gyres and variations in intensity, these fronts present a similar structure and dynamical configuration as the climatological Almeria–Oran front. The statistical analysis of our solution shows that strained-induced frontogenesis is a recurrent submesoscale mechanism associated with these fronts, and the process is assessed in terms of the advective Lagrangian frontogenetic tendencies associated with buoyancy and velocity horizontal gradients. Intermittency in their strength and patterns is indicative of high variability in the occurrence of active frontogenesis in association with the secondary (overturning) circulation across the frontal gradient. As a result, we find many episodes with strong surface fronts that do not have much associated downwelling. Frontogenesis and the associated secondary circulation are further explored during two particular frontal events, both showing strong downwelling of (1) cm s −1 extending down into the pycnocline. A frontogenetic contribution of turbulent vertical momentum mixing to the secondary circulation is identified in the easternmost region during the cold season, when the dynamics are strongly influenced by the intrusion of the salty Northern Current. The background vertical velocity fields observed during the analyzed events indicate other currents in the submesoscale range, including tidal and topographic internal waves.

Capó, Esther↗
DOE OSTI2023

High-resolution (30-m) urban land cover projections for Los Angeles California Urban Area: 2010 to 2100 under SSP3 and SSP5 [Updated simulations based on population-driven urban intensity transitions]

These data (v3) are updated from previous versions (1 and 2) in that they include consider the effects of population on transitions in urban land intensity. This leads to more reasonable differences in urban land projections under variant SSPs. For the present dataset, both SSP3 and SSP5 are provided. These data represent simulations of future land use and land cover (LULCC) for Los Angeles urban area (U.S. Census Bureau defined area) as raster tiff images at a 30-m pixel resolution and at decadal time steps from 2010 to 2100. LULCC classes in this product follow the National Land Cover Dataset (NLCD) classification. NLCD 21-24 correspond to open developed, low developed, medium developed, and high developed urban land classes, respectively. Only urban land cover classes (NLCD class 21, 22, 23, and 24) are dynamic over time; however, all NLCD classes are included in the final product. Therefore, NLCD classes that do not convert to an urban class will be similar to year 2000. The products were developed using a hybridized statistical and cellular automata approach. Linear mixed models (LMMs) were used to estimate future urban land budgets based on 1-km urban land fraction projections from Gao and Pesaresi (2021), whereas separate generalized linear mixed models (GLMMs) were used to estimate shifts in urban land intensities based on retrospective shifts in NLCD urban class intensities over a 20- year period. Based on urban land allocations from the statistical models, a cellular-automata and downscaling routine was used to simulate dynamic urban land expansion at a 30-m resolution based on suitability criteria. Scenarios of future urban landcover change projections include variant solutions for the Shared Socioeconomic Pathway 5 (SSP5) and SSP 3 based on different population assumptions, different land use intensification assumptions, variable land zoning constraints, and iterative adjustments to correct for over allocation of urban expansion across decadal time periods from 2010 to 2100. This results in 320 raster products.

Land↗
DOE OSTI2025

Meteorological Variables and Energy Fluxes at the Pumphouse Site, Crested Butte, CO 2017-2019

This data contains output from the pumphouse eddy covariance tower that includes shortwave radiation, longwave radiation, net radiation, air temperature, relative humidity, as well as sensible, latent, and ground heat fluxes. Also included is calculated evapotranspiration from the latent heat flux and the latent heat of vaporization. All data are on a daily timestep and displayed in Mountain Time. The data has been processed, and Quality Assurance / Quality Control (QA/QC) was done, but any daily gaps in the data have not been filled in. This research was funded by the Department of Energy and performed as part of the Watershed Function Scientific Focus Area. This research aimed to constrain evapotranspiration in a high-elevation catchment.The dataset includes one comma-separated values (CSV) data file (EddyCovariance_MeteorlogicalVariables_CrestedButtePumphouse.csv). Additionally, three metadata CSV files are included: (1) location metadata file (locations.csv), which contains location metadata and coordinates; (2) a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and (3) a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Radiation asymmetry during shattered pellet and massive gas injection in DIII-D

Infrared thermography of the first wall in DIII-D is used to show the toroidal peaking of plasma radiation during mitigated disruptions with shattered pellet injection (SPI) and with massive gas injection (MGI). During MGI, the radiation peak location is shown to be due to the n = 1 magnetohydrodynamic (MHD) activity and continuously variable in toroidal phase based on externally applied error fields, consistent with previous experimental results. Furthermore, the measured toroidal peaking factor (TPF) is in agreement with the previous estimates based on radiometry, with a total TPF of 1.07 ± 0.05 when integrated over the entire duration of the disruption, and a value of 1.3 ± 0.1 during the thermal quench (TQ). For SPI, the location of the radiation peak is found to be determined predominantly by the particle source location, and thus can be varied on DIII-D by injecting from either of two toroidally separated injectors. 3D non-linear MHD simulations with the NIMROD code support this picture. The localized SPI particle source leads to higher peaking than for MGI, with a total TPF of 1.3 ± 0.1 over the full disruption and a TQ TPF of 1.9 +0.5/−0.3, a value also consistent with the NIMROD simulations. This TQ value is close to or potentially exceeding the allowable limit for the previously planned Be first wall in ITER, pointing to the importance of radiation asymmetries depending on the choice of first wall material.

Physics - Plasma physics↗
DOE OSTI2021

Selecting XFEL single-particle snapshots by geometric machine learning

A promising new route for structural biology is single-particle imaging with an X-ray Free-Electron Laser (XFEL). This method has the advantage that the samples do not require crystallization and can be examined at room temperature. However, high-resolution structures can only be obtained from a sufficiently large number of diffraction patterns of individual molecules, so-called single particles. Here, we present a method that allows for efficient identification of single particles in very large XFEL datasets, operates at low signal levels, and is tolerant to background. This method uses supervised Geometric Machine Learning (GML) to extract low-dimensional feature vectors from a training dataset, fuse test datasets into the feature space of training datasets, and separate the data into binary distributions of “single particles” and “non-single particles.” As a proof of principle, we tested simulated and experimental datasets of the Coliphage PR772 virus. We created a training dataset and classified three types of test datasets: First, a noise-free simulated test dataset, which gave near perfect separation. Second, simulated test datasets that were modified to reflect different levels of photon counts and background noise. These modified datasets were used to quantify the predictive limits of our approach. Third, an experimental dataset collected at the Stanford Linear Accelerator Center. The single-particle identification for this experimental dataset was compared with previously published results and it was found that GML covers a wide photon-count range, outperforming other single-particle identification methods. Moreover, a major advantage of GML is its ability to retrieve single particles in the presence of structural variability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Does the leaf economic spectrum hold within plant functional types? A Bayesian multivariate trait meta-analysis

The leaf economic spectrum is a widely-studied axis of plant trait variability that defines a trade-off between leaf longevity and productivity. While this has been investigated at the global scale, where it is robust, and at local scales, where deviations from it are common, it has received less attention at the intermediate scale of PFTs. We investigated whether global leaf economic relationships are also present within the scale of plant functional types (PFTs) commonly used by Earth System models, and the extent to which this global-PFT hierarchy can be used to constrain trait estimates. We developed a hierarchical multivariate Bayesian model that assumes separate means and covariance structures within and across PFTs and fit this model to seven leaf traits from the TRY database related to leaf longevity, morphology, biochemistry, and photosynthetic metabolism. Although patterns of trait covariation were generally consistent with the leaf economic spectrum, we found three approximate tiers to this consistency. Relationships among morphological and biochemical traits (SLA, N, P) were the most robust within and across PFTs, suggesting that covariation in these traits is driven by universal leaf construction trade-offs and stoichiometry. Relationships among metabolic traits (R_d, V_{c,max}, J_max) were slightly less consistent, reflecting in part their much sparser sampling (especially for high-latitude PFTs), but also pointing to more flexible plasticity in plant metabolistm. Finally, relationships involving leaf lifespan were the least consistent, indicating that leaf economic relationships related to leaf lifespan are dominated by across-PFT differences and that within-PFT variation in leaf lifespan is more complex and idiosyncratic. Across all traits, these covariance were an important source of information, as evidenced by the improved imputation accuracy and reduced predictive uncertainty in multivariate models compared to univariate models. Ultimately, our study reaffirms the value of studying not just individual traits but the multivariate trait space and the utility of hierarchical modeling for studying the scale dependence of trait relationships.

biodiversity, ecological modeling, ecology, leaf b↗
DOE OSTI2024

Transforming Drainage Research Data (USDA-NIFA Award No. 2015-68007-23193)

This dataset contains research data compiled by the “Managing Water for Increased Resiliency of Drained Agricultural Landscapes” project a.k.a. Transforming Drainage. This project was funded from 2015-2021 by the United States Department of Agriculture, National Institute of Food and Agriculture (USDA-NIFA, Award No. 2015-68007-23193). Data are also available from a separate web-accessible application (drainagedata.org). At drainagedata.org, users can visualize the data with customized tools, query based on specific sites and measurements of interest, and access site photographs, maps, summaries, and publications. Additional data or edits made following the publication of this data here at USDA NAL Ag Data Commons will be posted under the Versions tab on drainagedata.org. These data began in 1996 and include plot- and field-level measurements for 39 experiments across the Midwest and North Carolina. Practices studied include controlled drainage, drainage water recycling, and saturated buffers. In total, 219 variables are reported and span 207 site-years for tile drainage, 154 for nitrate-N load, 181 for water quality, 92 for water table, and 201 for crop yield.

Modeling↗
DOE OSTI2020

Analysis of Powered Air-Purifying Respirator (PAPR) Cartridge Performance Testing on Hanford Tanks SX-101 and SX-104 Volume 1

Washington River Protection Solutions (WRPS) conducted tests using two types of chemical cartridges for use in powered air-purifying respirators (PAPR) to determine the period of time that the cartridges would provide adequate performance for PAPRs used to protect workers when exposed to a mixture of Chemicals of Potential Concern (COPCs) from vapors exiting the headspaces of Hanford tanks SX-101 and SX-104. The Occupational Safety and Health Administration (OSHA) considers cartridge testing to be a valid approach for establishing cartridge change schedules. Testing is commonly applied in situations where mixtures of COPCs exist, and where other approaches, such as manufacturer recommendations and modeling, are less reliable. The tests were designed and conducted to assure measurement and/or control of the key variables OSHA identified as important to estimate the cartridge service life, including temperature, humidity, COPC concentration, breathing rate, and cartridge adsorption capacity. Testing was conducted from June 16-17, 2017, from headspace vapors from Hanford tank SX-101 and from June 23-24, 2017, from Hanford tank SX-104. Headspace vapors were fed to a respirator cartridge test stand developed by WRPS in collaboration with HiLine Engineering (Richland, Washington). Multipurpose high-efficiency PAPR cartridges, MSA-TL (TL1) (MSA Safety Inc., Pittsburgh, Pennsylvania) and 3M FR-57 (TL2) (3M Company, Maplewood, Minnesota) were assessed on separate days. Sample media (i.e., sorbent tubes) were used to collect samples of the vapor stream entering and exiting the respirator cartridge and were subsequently analyzed for COPC concentrations. Pacific Northwest National Laboratory was tasked with conducting an independent analysis of the analytical results and making recommendations based on the results for respiratory cartridge performance and service life. The key conclusions from the analysis are described below.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Competing Magnetic Interactions and Field-Induced Metamagnetic Transition in Highly Crystalline Phase-Tunable Iron Oxide Nanorods

The inherent existence of multi phases in iron oxide nanostructures highlights the significance of them being investigated deliberately to understand and possibly control the phases. Here, the effects of annealing at 250 °C with a variable duration on the bulk magnetic and structural properties of high aspect ratio biphase iron oxide nanorods with ferrimagnetic Fe3O4 and antiferromagnetic α-Fe2O3 are explored. Increasing annealing time under a free flow of oxygen enhanced the α-Fe2O3 volume fraction and improved the crystallinity of the Fe3O4 phase, identified in changes in the magnetization as a function of annealing time. A critical annealing time of approximately 3 h maximized the presence of both phases, as observed via an enhancement in the magnetization and an interfacial pinning effect. This is attributed to disordered spins separating the magnetically distinct phases which tend to align with the application of a magnetic field at high temperatures. The increased antiferromagnetic phase can be distinguished due to the field-induced metamagnetic transitions observed in structures annealed for more than 3 h and was especially prominent in the 9 h annealed sample. Our controlled study in determining the changes in volume fractions with annealing time will enable precise control over phase tunability in iron oxide nanorods, allowing custom-made phase volume fractions in different applications ranging from spintronics to biomedical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Optimal design of chemoepitaxial guideposts for the directed self-assembly of block copolymer systems using an inexact Newton algorithm

Directed self-assembly (DSA) of block copolymers (BCPs) is one of the most promising developments in the cost-effective production of nanoscale devices. The process makes use of the natural tendency for BCP melts to form nanoscale structures upon phase separation. The phase separation can be directed through the use of chemically patterned substrates to promote the formation of morphologies that are essential to the production of semiconductor devices. Moreover, the design of substrate pattern can be formulated as an optimization problem for which we seek optimal substrate designs that effectively produce given target morphologies. In this paper, we adopt a phase field model given by a nonlocal Cahn–Hilliard partial differential equation (PDE) based on the minimization of the Ohta–Kawasaki free energy, and present an efficient PDE-constrained optimization framework for the optimal design problem. The design variables are the locations of circular- or strip-shaped guiding posts that are used to model the substrate chemical pattern. To solve the ensuing optimization problem, we propose a variant of an inexact Newton conjugate gradient algorithm tailored to this problem. Additionally, we demonstrate the effectiveness of our computational strategy on numerical examples that span a range of target morphologies. Owing to our second-order optimizer and fast state solver, the numerical results demonstrate five orders of magnitude reduction in computational cost over previous work. The efficiency of our framework and the fast convergence of our optimization algorithm enable us to rapidly solve the optimal design problem in not only two, but also three spatial dimensions.

97 MATHEMATICS AND COMPUTING↗