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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Analyzing Residential Charging Demand for Light-Duty Electric Vehicles in Colorado: Preprint

The past decade has witnessed the rapid adoption of electric vehicles (EVs). The momentum is expected to continue with strong support from the government and industry. Rapid EV adoption brings significant charging demand to the power grid, causing additional stress and non-negligible risks to the already-aging power grid. To help power grid operators understand the impacts of EV home charging on the grid and identify risk factors, this study presents a data-driven residential charging demand analysis for light-duty vehicles. This study considers two real-world grid service regions in Colorado and merges multiple data sources and state-of-the-art tools that characterize EV adoption projections, vehicle travel patterns, seasonal variations, residential charging accessibility, ambient temperature impact, EV charging behaviors, grid utility customers, vehicle registration, and household-level EV charging demand distribution. We characterize potential residential charging demand in 2030 for two regions within the state of Colorado: Boulder and Aurora. We project that EVs will be 26% of the light-duty vehicle population in Boulder and 16% in Aurora. Charging demand is characterized for ten power grid feeders (five for each study region). Across the ten feeders, peak total EV charging powers during wintertime range from less than 1 MW to more than 4 MW.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Does Age, Residency, or Feeding Guild Coupled with a Drought Index Predict Avian Health during Fall Migration?

Birds are good indicators of environmental change and are often studied for responses to climate. Many studies focus on breeding birds, while fewer look at the migration period, which is a critical time for many birds. Birds are more susceptible to unusual climatic events during their migration due to the metabolic stress of long-distance movements. In the fall of 2020, an unusual cold weather event coupled with drought and wildfire smoke led to a large avian mortality event in New Mexico. Later analysis pointed to the mortality being largely due to starvation. This was the impetus for our research. We used 11 years of fall bird banding data from two locations, along with local drought indices, to determine what predicts avian health during the migration period. We used fat score data from over 15,000 individual birds to assess whether drought indices, age, diet, or residency influenced avian health using multiple logistic regression. We found that the probability of positive fat scores decreased as drought severity increased for younger, insectivorous, migratory birds. Insectivores had a higher probability of receiving a fat score greater than zero relative to local drought conditions, which is important, since many North American insectivores are in steep decline. Migratory birds showed a greater response than year-round residents, and older birds showed a lower but significant response compared to hatch-year birds. Our results suggest that migratory insectivores in the southwestern United States may be less resilient to drought-related climate change.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2022

Canadian and Alaskan Wildfire Smoke Particle Properties, Their Evolution and Controlling Factors, From Satellite Observations

The optical and chemical properties of biomass burning (BB) smoke particles greatly affect the impact that wildfires have on climate and air quality. Previous work has demonstrated some links between smoke properties and factors such as fuel type and meteorology. However, the factors controlling BB particle speciation at emission are not adequately understood nor are the factors driving particle aging during atmospheric transport. As such, modeling wildfire smoke impacts on climate and air quality remains challenging. The potential to provide robust, statistical characterizations of BB particles based on ecosystem type and ambient environmental conditions with remote sensing data is investigated here. Space-based Multi-angle Imaging SpectroRadiometer (MISR) observations, combined with the MISR Research Aerosol (RA) algorithm and the MISR Interactive Explorer (MINX) tool, are used to retrieve smoke plume aerosol optical depth (AOD) and to provide constraints on plume vertical extent; smoke age; and particle size, shape, light-absorption properties, and absorption spectral dependence. These tools are applied to numerous wildfire plumes in Canada and Alaska, across a range of conditions, to create a regional inventory of BB particle-type temporal and spatial distribution. We then statistically compare these results with satellite measurements of fire radiative power (FRP) and land cover characteristics, as well as short-term climate, meteorological, and drought information from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis and the North American Drought Monitor. We find statistically significant differences in the retrieved smoke properties based on land cover type, with fires in forests producing the thickest plumes containing the largest, brightest particles and fires in savannas and grasslands exhibiting the opposite. Additionally, the inferred dominant aging mechanisms and the timescales over which they occur vary systematically between land types. This work demonstrates the potential of remote sensing to constrain BB particle properties and the mechanisms governing their evolution over entire ecosystems. It also begins to realize this potential, as a means of improving regional and global climate and air quality modeling in a rapidly changing world.

Katherine T. Junghenn Noyes↗
NASA NTRS2010

High Resolution ECG for Evaluation of Heart Function During Exposure to Subacute Hypobaric Hypoxia

High altitude climbing presents a wide spectrum of health risks, including exposure to hypobaric hypoxia. Risks are also typically exacerbated by the difficulty in appropriately monitoring for early signs of organ dysfunction in remote areas. We investigated whether high resolution advanced ECG analysis might be helpful as a non-invasive and easy-to-use tool (e.g., instead of Doppler echocardiography) for evaluating early signs of heart overload in hypobaric hypoxia. Nine non-acclimatized healthy trained alpine rescuers (age 43.7 plus or minus 7.3 years) climbed in four days to the altitude of 4,200 m on Mount Ararat. Five-minute high-resolution 12-lead electrocardiograms (ECGs) were recorded (Cardiosoft) in each subject at rest in the supine position on different days but at the same time of day at four different altitudes: 400 m (reference altitude), 1,700 m, 3,200 m and 4,200 m. Changes in conventional and advanced resting ECG parameters, including in beat-to-beat QT and RR variability, waveform complexity, signal-averaged, high-frequency and spatial/spatiotemporal ECG was estimated by calculation of the regression coefficients in independent linear regression models. A p-value of less than 0.05 was adopted as statistically significant. As expected, the RR interval and its variability both decreased with increasing altitude, with trends k = -96 ms/1000 m with p = 0.000 and k = -9 ms/1000 m with p = 0.001, respectively. Significant changes were found in P-wave amplitude, which nearly doubled from the lowest to the highest altitude (k = 41.6 microvolt/1000 m with p = 0.000), and nearly significant changes in P-wave duration (k = 2.9 ms/1000 m with p = 0.059). Changes were less significant or non-significant in other studied parameters including those of waveform complexity, signal-averaged, high-frequency and spatial/spatiotemporal ECG. High resolution ECG analysis, particularly of the P wave, shows promise as a tool for monitoring early changes in heart function due to exposure to high altitude.

Zupet, Petra↗
DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler↗
DOE OSTI2024

A review of criticality dosimetry at the Y-12 National Security Complex and practical importance of dose accuracy in emergency response

A nuclear criticality results in the emission of both neutron and gamma radiation and can produce doses to personnel near the event that exceed 0.1 Gy (10 rad). The primary purpose of nuclear accident dosimetry is to rapidly identify affected personnel in need of prompt medical treatment and to reassure personnel who have been only minimally exposed. While accurate dosimetry is desired, it must be recognized that dose determinations made from whole-body dosimeters or simple triage methods are very rough estimates and contain significant uncertainties. Even when accounting for factors like varying neutron energy spectra, mean photon energies, body orientation within the radiation field, and transient effects on dosimeter response, etc., the end value is a dosimetric quantity defined for very specific radiological conditions and determined within a simple phantom usually at a single depth. Of more importance is the biological response to the radiation, which will vary by person and can be affected by the individual’s radiation sensitivity, age, gender, mass, and underlying health conditions. The overall biological, person-specific response to a given dose cannot be precisely determined except by patient symptom observation and individual biological dosimetry (e.g. chromosome analysis, lymphocyte ratios, etc.). This work describes and discusses the criticality accident dosimetry program at the Y-12 National Security Complex, a United States Department of Energy National Nuclear Security Administration facility. In conclusion, the primary goals of the Y-12 accident dosimetry program are, among others, the rapid identification of significantly exposed persons, prompt routing of exposed workers for medical evaluation and treatment, and the ultimate processing of dosimeters to assign doses to personnel.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Improving Thermal Stability of Perovskite Solar Cells by Suppressing Ion Migration Using Copolymer Grain Encapsulation

Thermal stability of organic–inorganic hybrid perovskites (OIHPs) remains as one of the critical challenges against the stable operation of perovskite solar cells (PSCs) in direct sunlight with elevated temperatures. Here, we show that the addition of a polystyrene-co-polyacrylonitrile (SAN) copolymer can significantly enhance thermal stability of OIHPs and improve the stability of the corresponding PSCs by suppressing the migration of organic cations in OHIP. The methylammonium lead iodide (MAPI) with SAN incorporated within the perovskite layer featured a superior thermal stability compared to pure MAPI without SAN, only displaying an average of 5–15% decrease in PCE even after continuous thermal aging for 24 h at 100 °C. The secondary ion mass spectrometry revealed that the thermal degradation of the pure MAPI was largely associated with MA+ out-migration. Conducting atomic force microscopy analysis further indicated that the incorporated SAN led to a suppression of ionic currents present at the grain boundaries of the perovskite film, which was understood by high immiscibility between SAN and MA+ components as confirmed by the experimentally estimated Flory–Huggins parameter between them. This study newly identifies a potential of using polymer grain encapsulation for enhancing thermal stability of OIHPs and their solar cell performance by suppressing the out-diffusion of cationic organic components.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Initial Radiation of Nuclear Power Plant Components (CRADA NFE-17-06892 Final Report)

As advanced reactor concepts are developed, instrumentation and control (I&C) cables and sensors will play a significant role in assuring their operation is well understood, and safety-related process information can be collected reliably over the course of their design life. As a first step to develop acceptance criteria and define the limits of currently available nuclear I&C cable and sensor technology, a collaboration between Oak Ridge National Laboratory and Analysis and Measurement Services (AMS) Corporation was initiated under the Gateway for Accelerated Innovation in Nuclear (GAIN) Program. This collaborative effort focused on providing technical information related to the combined thermal and radiation aging of nuclear power plant (NPP) cables, companion NPP cable insulation samples, and two prototype temperature and two pressure sensors. This work was carried out using the instrumented gamma irradiation system that is part of the High Flux Isotope Reactor Gamma Irradiation Facility (HFIR GIF). This system provided the opportunity for the condition of the prototype sensors to be tracked during the irradiation in order to determine their functional limits with greater granularity when compared to a simple irradiation insertion at the HFIRGIF. Experimental assemblies for sensor irradiation were successfully completed, and sensor irradiation to accumulated dose of 3000 kGy at a rate of approximately 6 kGy/hr was carried out. Two prototype temperature assemblies were continuously monitored during exposure to 3000 kGy and found to have no observable degradation from the irradiation. Two pressure sensors were first irradiated to 1000 kGy. At which point, one of the sensors was found to operate normally; however, a second sensor failed the operability test. The operable pressure sensor output was then continuously monitored from 1000 kGy to 3000 kGy. The sensor output exhibited steady trendable drift versus the accumulated radiation dose. At the conclusion of the irradiation, the four test sensors were released for laboratory calibration checks. The calibration check of the temperature sensors found no significant change after irradiation compared to baseline measurements before irradiation; however, both pressure sensors failed the post-test calibration checks and both sensors were not functioning properly. These results will help inform sensor manufacturers and I&C design engineers of potential limitations of these types of sensors for use in high radiation environments associated with the compact configuration of new Small Modular Reactors (SMRs) such as NuScale’s reactor power module. Irradiations on NPP cables and companion samples were not completed due to programmatic delays, however a path forward that was based on lessons learned from this project was defined to accommodate future, comparable instrumented gamma irradiations at the HFIR GIF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Mitigating Impact Through Community-Engaged Flood Modeling

Urban pluvial flooding poses a growing threat to the city of Baltimore, driven by heavy rainfall, increased impervious area, and aging infrastructure. Adapting to the risks posed by pluvial flooding is critical for building greater climate resiliency in Baltimore's Inner Harbor Watershed. This study addresses these challenges through community-informed decision analysis, which uses hydrologic modeling and optimization tools to identify robust flooding adaptation pathways. We will collaborate with community partners to identify key concerns and objectives regarding flooding. These concerns have been purposefully built in to a combined surface-subsurface dynamic flow simulation model. Model outputs are used to identify flooding locations within the Inner Harbor, and to test adaptation methods. Machine learning will be used search for solutions which meet diverse environmental, financial, and social goals, and solution performance will be examined under a wide range of potential future climatic conditions and integrated with an adaptive planning approach. This novel set of adaptation pathways will enhance the City's capacity to respond to evolving pluvial flood risk.

climate resilience↗
NASA NTRS2017

Space Weathering Rates in Lunar and Itokawa Samples

Space weathering alters the chemistry, microstructure, and spectral proper-ties of grains on the surfaces of airless bodies by two major processes: micrometeorite impacts and solar wind interactions. Investigating the nature of space weathering processes both in returned samples and in remote sensing observations provides information fundamental to understanding the evolution of airless body regoliths, improving our ability to determine the surface composition of asteroids, and linking meteorites to specific asteroidal parent bodies. Despite decades of research into space weathering processes and their effects, we still know very little about weathering rates. For example, what is the timescale to alter the reflectance spectrum of an ordinary chondrite meteorite to resemble the overall spectral shape and slope from an S-type asteroid? One approach to answering this question has been to determine ages of asteroid families by dynamical modeling and determine the spectral proper-ties of the daughter fragments. However, large differences exist between inferred space weathering rates and timescales derived from laboratory experiments, analysis of asteroid family spectra and the space weathering styles; estimated timescales range from 5000 years up to 108 years. Vernazza et al. concluded that solar wind interactions dominate asteroid space weathering on rapid timescales of 10(exp 4)-10(exp 6) years. Shestopalov et al. suggested that impact-gardening of regolith particles and asteroid resurfacing counteract the rapid progress of solar wind optical maturation of asteroid surfaces and proposed a space weathering timescale of 10(exp 5)-10(exp 6) years.

Keller, L. P.↗
NASA NTRSDate not supplied

Watching Without Seeing a Tool to Surveil Astronaut Health Outcomes While Maintaining Astronaut Medical Privacy

BACKGROUND The Privacy Act of 1974 regulates the use a nd disclosure of personally identifiable information by US Federal agencies. The Act applies to biographical, financial, a nd other identity-linked information, a s well a s personal health information (PHI). As such, the use of astronaut PHI is limited to authorized personnel for preapproved uses, with data reporting often limited to aggregated information about groups. These limitations on the use a nd reporting of astronaut PHI complicates surveillance efforts, wherein epidemiologists a t the National Aeronautics and Space Administration (NASA)monitor the incidence of targeted health conditions in the astronaut population, or to discover emerging trends of aging and disease. Stratification on one or more covariates –particularly time-period, sex, a nd mission participation –can lead to extremely small datasets such that the reporting of results is potentially attributable to individuals. An additional challenge is the small size of the astronaut population, both in terms of numbers of individuals a s well a s in terms of density of exposure time. Such small datasets yield volatile rate estimates that are difficult to interpret. To a id the epidemiological surveillance efforts, a surveillance tool is required that can (a) satisfy the need for rapid computation of condition-specific incidence and mortality rates; (b) improve the statistical estimates of these estimated rates; and (c) maintain astronaut privacy. Here we describe a nd demonstrate such a tool. METHODS We devised a system that models incidence a nd mortality rates rather than calculating them directly. This ha s the advantage of using all the available data to derive the estimates, lea ding to rates that a re not attributable to any one individual, a nd a re a s numerically stable a s they can be given the extremely limited data. The system models disease endpoints using a Poisson regression model with exposure density (measured in person-years) a s a n offset term. By doing so the model is estimating event counts per person-year, equivalent to modeling the rates directly. It uses a standard (pre-specified)set of covariates; the system does not engage in “model-building” as model parsimony is not the goa l. Instead, it is explicitly recognized that if a covariate is not statistically significant a nd not a confounder then it will likely have very little effect on the estimate of the incidence a nd mortality rates. Users are able to specify the disease endpoint of interest and the covariates over which they would like to stratify. The system then uses the resulting model to compute the estimated rates for the user-chosen configuration of variables as visualizes those either over an age range within a specified time-period, or over time for astronauts with a specified age range. RESULTS The first iteration of the tool computes incidence a nd mortality rates for cardiovascular conditions and cancers. Code ha s been developed to retrieve the appropriate data from the IMPALA analysis platform, compute the models for incidence a nd mortality, a nd then use those models to generate the corresponding rate curves. A companion graphical user interface allows the user to specify the curves and visualize the results. CONCLUSIONS It is important to note that the rapid surveillance tool described here is neither meant to be a definitive assessment of the incidence or mortality of any particular disease or condition in the astronaut population, nor is it meant to be used for research purposes. Rather, it is meant as an early indicator that in-depth investigation may be warranted. By automating a repetitive process and leveraging carefully curated astronaut health outcomes, the tool makes possible a rapid “first look” into known areas of concern, and, if used judiciously, may surface new areas of concern for long-term astronaut health. This work is supported in part by the Translational Research Institute for Space Health (TRISH) through NASA Cooperative Agreement NNX16AO69A.

R J Reynolds↗
DOE OSTI2024

Photovoltaic Cable Jackets: A Comparison of Representative Products Using Combined-Accelerated Stress Testing [Slides]

Photovoltaic (PV) cables facilitate the distribution of electricity collected from modules to the energy grid. Durable cabling enables continuous operation of PV installations, whereas cables with a lifetime less than the modules must be replaced - reducing electricity generation and adding to the operating expense. This study primarily focusses on the aging of the key cable types using the combined-accelerated stress testing (C-AST) protocol. Representative cables for utility, building, and control/auxiliary applications were examined. Cable jacket materials examined include: polyolefin, polyethylene, polyamide, poly(vinyl chloride), chlorinated polyethylene, thermoplastic elastomer, and ethylene propylene diene monomer rubber. Specimen characterizations applied include: optical microscopy, mechanical profilometry, instrumented indentation, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). A variety of performance and durability characteristics were observed, depending on the base material, polymer formulation, and jacket color. The results from C-AST are analyzed and discussed relative to a recent industry survey on electronic balance of system components in addition to a recent study where similar cables were aged using steady state ultraviolet weathering (International Electrotechnical Commission Technical Specification 62788-7-2). Recommendations are made for the screening, industry qualification, and service life prediction of PV cable jackets.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Microstructure and Mechanical Properties of Additively Manufactured Haynes 282: A Comparative Analysis between L-PBF and LP-DED Technologies

This study compares the microstructure and tensile properties of Haynes 282 fabricated using laser powder bed fusion and laser powder directed energy deposition. Both sets underwent stress-relieving, followed by hot isostatic pressing, and the standard double aging heat treatment. Tensile testing was conducted at room temperature on specimens fabricated with both technologies to evaluate and compare their tensile behaviors. Results show that the ultimate tensile and yield strengths of laser powder bed fused specimens were 18% and 57% higher, respectively than those of laser powder directed energy deposited ones, whereas the elongation to failure was similar in both. The difference in strengths is attributed to the differences in the size of ɣ' precipitates and grains, i.e., those in the LP-DED specimens being larger, whereas similar elongation to failure is attributed to the carbide debonding dominating the fracture mechanism in both batches.

Additive manufacturing↗
NASA NTRS2015

Mineralogical Analysis of the Oppia Quadrangle of Asteroid (4) Vesta: Evidence for Occurrence of Moderate-Reflectance Hydrated Minerals

Quadrangle Av-10 'Oppia' is one of five quadrangles that cover the equatorial region of asteroid (4) Vesta. This quadrangle is notable for the broad, spectrally distinct ejecta that extend south of the Oppia crater. These ejecta exhibit the steepest ('reddest') visible spectral slope observed across the asteroid and have distinct color properties as seen in multispectral composite images. Compared to previous works that focused on the composition and nature of unusual ('orange') ejecta found on Vesta, here we take into account a broader area that includes several features of interest, with an emphasis on mineralogy as inferred from data obtained by Dawn's Visible InfraRed mapping spectrometer (VIR). Our analysis shows that the older northern and northeastern part of Av-10 is dominated by howardite-like material, while the younger southwestern part, including Oppia and its ejecta blanket, has a markedly eucritic mineralogy. The association of the mineralogical information with the geologic and topographic contexts allows for the establishment of relationships between the age of the main formations observed in this quadrangle and their composition. A major point of interest in the Oppia quadrangle is the spectral signature of hydrous material seen at the local scale. This material can be mapped by using high-resolution VIR data, combined with multispectral image products from the Dawn Framing Camera (FC) so as to enable a clear correlation with specific geologic features. Hydrated mineral phases studied previously on Vesta generally correlate with low-albedo material delivered by carbonaceous asteroids. However, our analysis shows that the strongest OH signature in Av-10 is found in a unit west of Oppia, previously mapped as 'light mantle material' and showing moderate reflectance and a red visible slope. With the available data we cannot yet assess the presence of water in this material. However, we offer a possible explanation for its origin.

Asteroids↗
DOE OSTI2021

Combined effect of NaAlO2 and NaOH on the early age hydration of Portland cement with a high concentration of borate solution

The early age hydration of ordinary Portland cement in 5 M borate solution, with or without the addition of NaAlO{sub 2} and/or NaOH, was investigated. Hydration was measured using calorimetry, X-ray diffraction, thermogravimetric analysis, {sup 11}B and {sup 27}Al magic angle spinning NMR analysis, and scanning transmission electron microscopy. The purpose of this study was to reveal the mechanisms behind the retardation caused by a high concentration borate solution and the restoration of hydration through the combined addition of NaOH and NaAlO{sub 2}. Amorphous ulexite, which formed on the surface of the cement particles and prevented the further dissolution of anhydrous phases, was identified as the retardation product. The mechanism of the combined addition of NaAlO{sub 2} and NaOH in overcoming retardation was to transform amorphous ulexite into B-AFt and gowerite (CaB{sub 6}O{sub 10}·5H{sub 2}O). Formation of gowerite is favorable because of the much higher boron immobilization capacity in weight percentage, comparing to usual boron-containing phases reported previously.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Preprocessing Affords 3D Crystalline Poly(3-hexylthiophene) Structure

The aggregation and crystallization of poly(3-hexylthiophene- 2,5-diyl) (P3HT), a representative active layer material used for organic field-effect transistor (OFET) applications, are influenced by the solution pretreatment and deposition process. This study explores vibration-assisted convective deposition for the fabrication of OFETs in comparison to spin coating, blade coating, and convective deposition without vibration. The ultraviolet–visible spectroscopic analysis demonstrates that convective deposition, especially assisted with vibration, leads to a greater degree of intrachain interactions, longer conjugation length, and enhanced polymer backbone planarization. When the P3HT solution is preprocessed via sonication and aging, the P3HT films exhibit J-like aggregation, and (h11) peaks can be observed through grazing-incidence wide-angle X-ray scattering, suggesting an ordered 3D crystalline structure. OFETs based on such films exhibit high mobilities (up to 0.14 cm 2 V –1 s –1 ). The results point to the sensitivity of P3HT charge transport behavior to the intramolecular interactions and backbone planarity and further deepen our understanding of the relationship between processing, aggregates, molecular ordering, and resultant device properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

BLAST-Lite (Battery Lifetime Analysis and Simulation Tool - Lite) [SWR-22-69] Related to: BLAST aka: BLAST-Py

Battery Lifetime Analysis and Simulation Toolsuite (BLAST) provides a library of battery lifetime and degradation models for various commercial lithium-ion batteries from recent years. Degradation models are identified from publicly available lab-based aging data using NREL's battery life model identification toolkit. The battery life models predicted the expected lifetime of batteries used in mobile or stationary applications as functions of their temperature and use (state-of-charge, depth-of-discharge, and charge/discharge rates). Model implementation is in both Python and MATLAB programming languages. The MATLAB code also provides example applications (stationary storage and EV), climate data, and simple thermal management options. For more information on battery health diagnostics, prediction, and optimization, see NREL's Battery Lifespan webpage.

Smith, Kandler↗