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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Validation and Uncertainty Estimates for MODIS Collection 6 "Deep Blue" Aerosol Data

The "Deep Blue" aerosol optical depth (AOD) retrieval algorithm was introduced in Collection 5 of the Moderate Resolution Imaging Spectroradiometer (MODIS) product suite, and complemented the existing "Dark Target" land and ocean algorithms by retrieving AOD over bright arid land surfaces, such as deserts. The forthcoming Collection 6 of MODIS products will include a "second generation" Deep Blue algorithm, expanding coverage to all cloud-free and snow-free land surfaces. The Deep Blue dataset will also provide an estimate of the absolute uncertainty on AOD at 550 nm for each retrieval. This study describes the validation of Deep Blue Collection 6 AOD at 550 nm (Tau(sub M)) from MODIS Aqua against Aerosol Robotic Network (AERONET) data from 60 sites to quantify these uncertainties. The highest quality (denoted quality assurance flag value 3) data are shown to have an absolute uncertainty of approximately (0.086+0.56Tau(sub M))/AMF, where AMF is the geometric air mass factor. For a typical AMF of 2.8, this is approximately 0.03+0.20Tau(sub M), comparable in quality to other satellite AOD datasets. Regional variability of retrieval performance and comparisons against Collection 5 results are also discussed.

MODIS collection 6↗
NASA NTRS2024

VIIRS Version 2 Deep Blue Aerosol Products

NASA's Deep Blue aerosol project has developed global aerosol data records using consistent retrieval algorithms applied to various satellite sensors. The primary components of these data records are derived from the series of Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (SNPP) and the National Oceanic and Atmospheric Administration or NOAA-20+ satellites as well as the Moderate Resolution Imaging Spectroradiometer (MODIS), among others. These instruments provide over 23 years of measurements with similar radiometric characteristics for aerosol retrievals. The algorithms used for the initial Version 1 SNPP VIIRS data set were based on the MODIS Collection 6.1 Deep Blue algorithm over land and Satellite Ocean Aerosol Retrieval (SOAR) algorithm over water. For VIIRS Version 2 data reprocessing, major updates have been made to the algorithm suite, including better accounting for effects of surface pressure, improved determination of surface reflectance, and the inclusion of fine-mode aerosol optical models to better represent anthropogenic aerosols over land. Cross-calibration gain factors are derived for the NOAA-20 VIIRS measurements to be consistent with the SNPP VIIRS, which allows the use of a unified algorithm package for both instruments. Comparisons against AERONET observations indicate that the Version 2 AOD data from SNPP VIIRS are significantly better than the Version 1 counterpart over land and slightly degraded over water in exchange for better spatial coverage. The AOD data from SNPP and NOAA-20 VIIRS are comparable, indicating that cross-calibration enables the creation of consistent aerosol data records using the series of VIIRS sensors.

Deep Blue↗
NASA NTRS2015

Extending the Deep Blue aerosol record from SeaWiFS and MODIS to NPP-VIIRS

Deep Blue expands AOD coverage to deserts and other bright surfaces. Using multiple similar satellite sensors enables us to obtain a long data record. The Deep Blue family consists of three separate aerosol optical depth (AOD) retrieval algorithms: 1. Bright Land: Surface reflectance database, BRDF correction. AOD retrieved separately at each of 412, 470/490, (650) nm. SSA retrieved for heavy dust events. 2. Dark Land: Spectral/directional surface reflectance relationship. AOD retrieved separately at 470/490 and 650 nm. 3. Water: Surface BRDF including glint, foam, underlight. Multispectral inversion (Not present in MODISdataset) All report the AOD at 550 nm, and Ångström exponent (AE).

SeaWiFS and MODIS↗
DOE OSTI2025

Increasing the Stability of Deep Blue Phosphor‐Sensitized OLEDs Using the Polariton‐Enhanced Purcell Effect

Abstract The stability of efficient, deep blue organic light‐emitting diodes (OLEDs) remains a major challenge in the field of organic electronics. Poor device stability originates from the high probability for destructive non‐radiative triplet exciton annihilation events. Phosphor‐sensitized fluorescence (PSF) is proposed to achieve an efficient, deep blue color by energy transfer from phosphors to fluorophores. Recently, the polariton‐enhanced Purcell (PEP) effect is introduced to decrease the triplet radiative lifetime and density, resulting in an increase in blue phosphorescent OLED lifetime. Here, the PEP effect is introduced to enhance the stability of the PSF‐OLEDs. It is shown that the PEP effect increases all radiative decay rates of the phosphors and fluorophores, leading to a reduction in the triplet annihilation events. Using a Pt‐complex phosphor sensitizer and a so‐called multi‐resonance fluorescent emitter in a PEP cavity, a 3.1‐fold lifetime increase is observed at a current density ofJ= 10 mA cm −2 , reduced EQE roll‐off and deep blue color with Commission Internationale de l'Eclairage coordinates of (0.13, 0.09). The PEP effect maximally extends PSF‐OLED lifetimes in devices with the highest triplet‐to‐singlet energy transfer rates. Moreover, this work suggests that the benefits of PEPs apply to all triplet‐based OLEDs.

Chemistry↗
DOE OSTI2025

Deep-blue emitting 9,10-bis(perfluorobenzyl)anthracene

A new deep-blue emitting and highly fluorescent anthracene (ANTH) derivative containing perfluorobenzyl (Bn F ) groups, 9,10-ANTH(Bn F ) 2 , was synthesized in a single step reaction of ANTH or ANTH(Br) 2 with Bn F I, using either a high-temperature Cu-/Na 2 S 2 O 3 -promoted reaction or via a room-temperature photochemical reaction. Its structure was elucidated by NMR spectroscopy and single crystal X-ray diffractometry. The latter revealed no π–π interaction between neighboring ANTH cores. A combination of high photoluminescence quantum yield (PLQY) of 0.85 for 9,10-ANTH(Bn F ) 2 , its significantly improved photostability compared to ANTH and 9,10-ANTH derivatives, and a simple synthetic access makes it an attractive material as a deep-blue OLED emitter and an efficient fluorescent probe.

Chemistry↗
NASA NTRS2013

Enhanced Deep Blue Aerosol Retrieval Algorithm: The Second Generation

The aerosol products retrieved using the MODIS collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright-reflecting land surfaces, such as desert, semi-arid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and non- vegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of pre-calculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semi-arid regions to the entire land areas.

Deep Blue↗
NASA NTRS2015

Effect of MODIS Terra Radiometric Calibration Improvements on Collection 6 Deep Blue Aerosol Products: Validation and Terra/Aqua Consistency

The Deep Blue (DB) algorithm's primary data product is midvisible aerosol optical depth (AOD). DB applied to Moderate Resolution Imaging Spectroradiometer (MODIS) measurements provides a data record since early 2000 for MODIS Terra and mid-2002 for MODIS Aqua. In the previous data version (Collection 5, C5), DB production from Terra was halted in 2007 due to sensor degradation; the new Collection 6 (C6) has both improved science algorithms and sensor radiometric calibration. This includes additional calibration corrections developed by the Ocean Biology Processing Group to address MODIS Terra's gain, polarization sensitivity, and detector response versus scan angle, meaning DB can now be applied to the whole Terra record. Through validation with Aerosol Robotic Network (AERONET) data, it is shown that the C6 DB Terra AOD quality is stable throughout the mission to date. Compared to the C5 calibration, in recent years the RMS error compared to AERONET is smaller by approximately 0.04 over bright (e.g., desert) and approximately 0.01-0.02 over darker (e.g., vegetated) land surfaces, and the fraction of points in agreement with AERONET within expected retrieval uncertainty higher by approximately 10% and approximately 5%, respectively. Comparisons to the Aqua C6 time series reveal a high level of correspondence between the two MODIS DB data records, with a small positive (Terra-Aqua) average AOD offset <0.01. The analysis demonstrates both the efficacy of the new radiometric calibration efforts and that the C6 MODIS Terra DB AOD data remain stable (to better than 0.01 AOD) throughout the mission to date, suitable for quantitative scientific analyses.

Collection 6 Deep Blue↗
NASA NTRS2006

Deep Blue Retrievals of Asian Aerosol Properties During ACE-Asia

During the ACE-Asia field campaign, unprecedented amounts of aerosol property data in East Asia during springtime were collected from an array of aircraft, shipboard, and surface instruments. However, most of the observations were obtained in areas downwind of the source regions. In this paper, the newly developed satellite aerosol algorithm called "Deep Blue" was employed to characterize the properties of aerosols over source regions using radiance measurements from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS). Based upon the ngstr m exponent derived from the Deep Blue algorithm, it was demonstrated that this new algorithm is able to distinguish dust plumes from fine-mode pollution particles even in complex aerosol environments such as the one over Beijing. Furthermore, these results were validated by comparing them with observations from AERONET sites in China and Mongolia during spring 2001. These comparisons show that the values of satellite-retrieved aerosol optical thickness from Deep Blue are generally within 20%-30% of those measured by sunphotometers. The analyses also indicate that the roles of mineral dust and anthropogenic particles are comparable in contributing to the overall aerosol distributions during spring in northern China, while fine-mode particles are dominant over southern China. The spring season in East Asia consists of one of the most complex environments in terms of frequent cloudiness and wide ranges of aerosol loadings and types. This paper will discuss how the factors contributing to this complexity influence the resulting aerosol monthly averages from various satellite sensors and, thus, the synergy among satellite aerosol products.

Hsu, N. Christina↗
NASA NTRS2012

Global Long-Term SeaWiFS Deep Blue Aerosol Products available at NASA GES DISC

Long-term climate data records about aerosols are needed in order to improve understanding of air quality, radiative forcing, and for many other applications. The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) provides a global well-calibrated 13- year (1997-2010) record of top-of-atmosphere radiance, suitable for use in retrieval of atmospheric aerosol optical depth (AOD). Recently, global aerosol products derived from SeaWiFS with Deep Blue algorithm (SWDB) have become available for the entire mission, as part of the NASA Making Earth Science data records for Use in Research for Earth Science (MEaSUREs) program. The latest Deep Blue algorithm retrieves aerosol properties not only over bright desert surfaces, but also vegetated surfaces, oceans, and inland water bodies. Comparisons with AERONET observations have shown that the data are suitable for quantitative scientific use [1],[2]. The resolution of Level 2 pixels is 13.5x13.5 km2 at the center of the swath. Level 3 daily and monthly data are composed by using best quality level 2 pixels at resolution of both 0.5ox0.5o and 1.0ox1.0o. Focusing on the southwest Asia region, this presentation shows seasonal variations of AOD, and the result of comparisons of 5-years (2003- 2007) of AOD from SWDB (Version 3) and MODIS Aqua (Version 5.1) for Dark Target (MYD-DT) and Deep Blue (MYD-DB) algorithms.

Shen, Suhung↗
DOE OSTI2022

Narrowing the Phase Distribution of Quasi-2D Perovskites for Stable Deep-Blue Electroluminescence

Solution-processed quasi-2D perovskites contain multiple quantum wells with a broad width distribution. Inhomogeneity results in the charge funneling into the smallest bandgap components, which hinders deep-blue emission and accelerates Auger recombination. Here, a synthetic strategy applied to a range of quasi-2D perovskite systems is reported, that significantly narrows the quantum well dispersity. It is shown that the phase distribution in the perovskite film is significantly narrowed with controlled, simultaneous evaporation of solvent and antisolvent. Modulation of film formation kinetics of quasi-2D perovskite enables stable deep-blue electroluminescence with a peak emission wavelength of 466 nm and a narrow linewidth of 14 nm. Light emitting diodes using the perovskite film show a maximum luminance of 280 cd m –2 at an external quantum efficiency of 0.1%. This synthetic approach will serve in producing new materials widening the color gamut of next-generation displays.

36 MATERIALS SCIENCE↗
NASA NTRS2016

The "Deep Blue" Aerosol Project at NASA GSFC

Atmospheric aerosols such as mineral dust, wildfire smoke, sea spray, and volcanic ash are of interest for a variety of reasons including public health, climate change, hazard avoidance, and more. Deep Blue is a project which uses satellite observations of the Earth from sensors such as SeaWiFS, MODIS, and VIIRS to monitor the global aerosol burden. This talk will cover some basics about aerosols and the principles of aerosol remote sensing, as well as discussing specific results and future directions for the Deep Blue project.

Deep Blue↗
DOE OSTI2025

Dual interfacial H-bonding-enhanced deep-blue hybrid copper–iodide LEDs

Solution-processed light-emitting diodes based on non-toxic copper–iodide hybrids are a compelling solution for efficient and stable deep-blue lighting, owing to their tunability, high photoluminescence efficiency and environmental sustainability. Here we present a hybrid copper–iodide that shows near-unity photoluminescence quantum yield (99.6%) with an emission wavelength of 449 nm and colour coordinates (0.147, 0.087), alongside its emission mechanism and charge transport characteristics. Here, we use the thin film of this hybrid as the sole active emissive layer to fabricate deep-blue light-emitting diodes and subsequently enhance the device performance through a dual interfacial hydrogen-bond passivation strategy. This synergetic surface modification approach, integrating a hydrogen-bond-acceptor self-assembled monolayer with an ultrathin polymethyl methacrylate capping layer, effectively passivates both heterojunctions of the copper–iodide hybrid emissive layer and optimizes charge injections. We achieve a maximum external quantum efficiency of 12.57%, a maximum luminance of 3,970.30 cd m −2 with colour coordinates (0.147, 0.091) and an excellent operational stability (half-lifetime) of 204 hours under ambient conditions. We further showcase a large-area device of 4 cm 2 that maintains high efficiency. Our findings reveal the potential of copper–iodide-based hybrid materials for applications in solid-state lighting and display technologies, offering a versatile strategy for enhancing device performances.

14 SOLAR ENERGY↗
DOE OSTI2023

Control of Host-Matrix Morphology Enables Efficient Deep-Blue Organic Light-Emitting Devices

Mixing a sterically bulky, electron-transporting host material into a conventional single host–guest emissive layer is demonstrated to suppress phase separation of the host matrix while increasing the efficiency and operational lifetime of deep-blue phosphorescent organic light-emitting diodes (PHOLEDs) with chromaticity coordinates of (0.14, 0.15). Here, the bulky host enables homogenous mixing of the molecules comprising the emissive layer while suppressing single host aggregation; a significant loss channel of nonradiative recombination. By controlling the amorphous phase of the host-matrix morphology, the mixed-host device achieves a significant reduction in nonradiative exciton decay, resulting in 120 ± 6% increase in external quantum efficiency relative to an analogous, single-host device. In contrast to single host PHOLEDs where electrons are transported by the host and holes by the dopants, both charge carriers are conducted by the mixed host, reducing the probability of exciton annihilation, thereby doubling of the deep-blue PHOLED operational lifetime. These findings demonstrate that the host matrix morphology affects almost every aspect of PHOLED performance.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Toward Stable Deep-Blue Luminescent Colloidal Lead Halide Perovskite Nanoplatelets: Systematic Photostability Investigation

Colloidal lead halide perovskite nanocrystals and nanoplatelets have emerged as promising semiconductor nanomaterials because of their spectral tunability, facile processability, and bright emission with high color purity. In particular, strong quantum and dielectric confinement make atomically thin colloidal lead bromide perovskite nanoplatelets a favorable candidate for next-generation deep-blue-emitting (λ max = 437 nm) materials. However, poor photostability poses a critical challenge; colloidal nanoplatelets suffer from photobleaching or transformation into thicker, less-confined nanostructures with red-shifted emission upon UV irradiation. In this study, we synthesize deep-blue-emitting organic–inorganic hybrid perovskite nanoplatelets (formula: L 2 [ABX 3 ]BX 4 , L: butylammonium and octylammonium, A: methylammonium or formamidinium, B: lead, and X: bromide or iodide) with large lateral dimension (~1 μm) by ligand-assisted reprecipitation and systematically investigate the factors that affect the photostability of those nanoplatelets. We find that freshness of the prepared precursor solutions for ligand-assisted reprecipitation is critical to obtain better stability with high photoluminescence quantum yield of perovskite nanoplatelets. Photobleaching is found to result from intrinsic instability of the perovskite lattice against UV irradiation in nanoplatelets, whereas transformation into thicker nanostructures results from extrinsic factors—moisture, primarily. Furthermore, we observe that substitution of the organic cation from formamidinium to methylammonium and addition of excess alkylammonium bromide ligands significantly enhance both the ambient and photostability. Lastly, we demonstrate that the dropcast film of methylammonium lead bromide nanoplatelets with excess alkylammonium bromide ligands shows dramatically improved stability both under UV irradiation and under ambient conditions. Lastly, this study expands our understanding of the factors that affect perovskite nanoplatelet photostability and opens up new possibilities for the fabrication of stable perovskite nanoplatelet-based optoelectronic devices.

2D↗
NASA NTRS2014

Comparing MODIS C6 'Deep Blue' and 'Dark Target' Aerosol Data

The MODIS Collection 6 Atmospheres product suite includes refined versions of both 'Deep Blue' (DB) and 'Dark Target' (DT) aerosol algorithms, with the DB dataset now expanded to include coverage over vegetated land surfaces. This means that, over much of the global land surface, users will have both DB and DT data to choose from. A 'merged' dataset is also provided, primarily for visualization purposes, which takes retrievals from either or both algorithms based on regional and seasonal climatologies of normalized difference vegetation index (NDVI). This poster present some comparisons of these two C6 aerosol algorithms, focusing on AOD at 550 nm derived from MODIS Aqua measurements, with each other and with Aerosol Robotic Network (AERONET) data, with the intent to facilitate user decisions about the suitability of the two datasets for their desired applications.

MODIS Collection 6↗
NASA NTRS2019

VIIRS Deep Blue Aerosol Products Over Land: Extending the EOS Long‐Term Aerosol Data Records

A primary goal of the Deep Blue (DB) project is to create consistent long‐term aerosol data records, suitable for climate studies, using multiple satellite instruments. In order to continue Earth Observing System (EOS)‐era aerosol products into the Joint Polar Satellite System era, we have successfully ported the DB algorithm to process data from the Visible Infrared Imaging Radiometer Suite (VIIRS). Although the basic structure of the VIIRS algorithm is similar to that for the Moderate Resolution Imaging Spectroradiometer (MODIS), many enhancements have been made compared to the MODIS collection 6 (C6) version. Most have also been implemented in the latest MODIS Collection 6.1 (C6.1). For example, a new smoke mask was developed based on the spectral curvature of measured reflectance to distinguish biomass burning smoke from weakly absorbing urban/industrial aerosols. Consequently, a new aerosol‐type flag was added into the VIIRS DB data set. In addition, new dust models have been developed to account for the nonsphericity of mineral dust. As a result, a discontinuity in the retrieved aerosol optical depth (AOD) of Saharan dust plumes seen in MODIS C6 products near the boundary between North Africa and the Atlantic has been much reduced. We have also evaluated the VIIRS and MODIS Terra/Aqua C6.1 AOD against Aerosol Robotic Network data. VIIRS and MODIS retrievals show similar performance; around 80% of matchups agree with Aerosol Robotic Network within the expected error of ±(0.05 + 20)%, indicating that DB can provide consistent AOD through the historical EOS and present Joint Polar Satellite System eras.

aerosols↗
NASA NTRS2012

Recent Progress on Deep Blue Aerosol Algorithm as Applied TO MODIS, SEA WIFS, and VIIRS, and Their Intercomparisons with Ground Based and Other Satellite Measurements

The impact of natural and anthropogenic sources of aerosols has gained increasing attention from scientific communities in recent years. Indeed, tropospheric aerosols not only perturb radiative energy balance by interacting with solar and terrestrial radiation, but also by changing cloud properties and lifetime. Furthermore, these anthropogenic and natural air particles, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across oceans and continents resulting in important biogeochemical impacts on the ecosystem. With the launch of SeaWiFS in 1997, Terra/MODIS in 1999, and Aqua/MODIS in 2002, high quality comprehensive aerosol climatology is becoming feasible for the first time. As a result of these unprecedented data records, studies of the radiative and biogeochemical effects due to tropospheric aerosols are now possible. In this talk, we will demonstrate how this newly available SeaWiFS/MODIS aerosol climatology can provide an important piece of puzzles in reducing the uncertainty of estimated climatic forcing due to aerosols. We will start with the global distribution of aerosol loading and their variabilities over both land and ocean on short- and long-term temporal scales observed over the last decade. The recent progress made in Deep Blue aerosol algorithm on improving accuracy of these Sea WiFS / MODIS aerosol products in particular over land will be discussed. The impacts on quantifying physical and optical processes of aerosols over source regions of adding the Deep Blue products of aerosol properties over bright-reflecting surfaces into Sea WiFS / MODIS as well as VIIRS data suite will also be addressed. We will also show the intercomparison results of SeaWiFS/MODIS retrieved aerosol optical thickness with data from ground based AERONET sunphotometers over land and ocean as well as with other satellite measurements. The trends observed in global aerosol loadings of both natural and anthropogenic sources based upon more than a decade of combined MODIS/SeaWiFS data (1997-2011) will be discussed. We will also address the importance of various key issues such as differences in spatial-temporal sampling rates and observation time between different satellite measurements could potentially impact these intercomparisons results, especially for using the monthly mean data, and thus on estimates of long-term aerosol trends.

Hsu, N. Christina↗
NASA NTRS2017

Assimilation of MODIS Dark Target and Deep Blue Observations in the Dust Aerosol Component of NMMB-MONARCH version 1.0

A data assimilation capability has been built for the NMMB-MONARCH chemical weather prediction system, with a focus on mineral dust, a prominent type of aerosol. An ensemble-based Kalman filter technique (namely the local ensemble transform Kalman filter - LETKF) has been utilized to optimally combine model background and satellite retrievals. Our implementation of the ensemble is based on known uncertainties in the physical parametrizations of the dust emission scheme. Experiments showed that MODIS AOD retrievals using the Dark Target algorithm can help NMMB-MONARCH to better characterize atmospheric dust. This is particularly true for the analysis of the dust outflow in the Sahel region and over the African Atlantic coast. The assimilation of MODIS AOD retrievals based on the Deep Blue algorithm has a further positive impact in the analysis downwind from the strongest dust sources of the Sahara and in the Arabian Peninsula. An analysis-initialized forecast performs better (lower forecast error and higher correlation with observations) than a standard forecast, with the exception of underestimating dust in the long-range Atlantic transport and degradation of the temporal evolution of dust in some regions after day 1. Particularly relevant is the improved forecast over the Sahara throughout the forecast range thanks to the assimilation of Deep Blue retrievals over areas not easily covered by other observational datasets.The present study on mineral dust is a first step towards data assimilation with a complete aerosol prediction system that includes multiple aerosol species.

atmospheric dust↗