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At least 235 records · Page 13

Exploring Domain-Wall Pinning in Ferroelectrics via Automated High-Throughput Atomic Force Microscopy

Domain-wall dynamics in ferroelectric materials are strongly position-dependent, since each polar interface is locked into a unique local microstructure. This necessitates spatially resolved studies of wall pinning using scanning-probe microscopy techniques. The pinning centers and pre-existing domain walls are usually sparse within the image plane, precluding the use of dense hyperspectral imaging modes and requiring time-consuming human experimentation. Here, a large-area epitaxial PbTiO 3 film on cubic KTaO 3 was investigated to quantify the electric-field-driven dynamics of the polar–strain domain structures using ML-controlled automated piezoresponse force microscopy. Analysis of 1500 switching events reveals that domain-wall displacement depends not only on field parameters but also on the local ferroelectric–ferroelastic configuration. For example, twin boundaries in polydomains regions, like a 1 – /c+ ∥ a 2 – /c – , stay pinned up to a certain level of bias magnitude and change only marginally as the bias increases from 20 to 30 V, whereas single-variant boundaries, like the a 2 + /c + ∥ a 2 – /c – stack, are already activated at 20 V. These statistics on the possible ferroelectric and ferroelastic wall orientations, together with the automated high-throughput AFM workflow, can be distilled into a predictive map that links domain configurations to pulse parameters. Here, this microstructure-specific rule set forms the foundation for the design of ferroelectric memories.

automated scanning probe microscopy↗

Imaging local luminescence variations in CdSe 0.1 Te 0.9 thin films grown by the colossal grain growth process

Clear visualization and understanding of luminescence properties of grain interiors and grain boundaries in polycrystalline thin-film photovoltaic materials are crucial to achieving high-performance solar cells. Luminescence-based measurements, for example, reveal sub-bandgap energetic disorder or impurity-related radiative transitions in these materials, and when performed in the absolute scale, they can show the extent of voltage-limiting non-radiative recombination. Here we use a hyperspectral imaging technique to investigate inter- and intra-grain photoluminescence variations in polycrystalline CdSe 0.1 Te 0.9 films made by the colossal grain growth process. We observe that grain boundaries show higher luminescence than grain interiors for all energies below the bandgap energy. Multiple distinct sub-bandgap defect transitions are detected and determined to be related to donor-acceptor pair impurities. A comparison of the excitation-intensity-dependent photoluminescence at the grain boundaries with grain interiors suggests that carrier concentration is higher at grain boundaries. This finding is supported by photoemission electron microscopy imaging of the films, showing approximately 70 meV upward energy shift in the band structure at the grain boundaries. Finally, we investigate a dramatic thermal quenching behavior related to the donor-acceptor pairs luminescence over a temperature range and use a rate-equation model to attribute it to the sudden redirection of the radiative recombination channels to non-radiative channels with increasing temperature.

14 SOLAR ENERGY↗

Characterization of Semiconductor Materials Using AOTF Instruments

A non-invasive characterization of silicon-on-insulator (SOI) wafers using white light interference measured by an AOTF polarimetric hyperspectral imaging instrument will be presented an an illustration of the technology potential. Experiments provided high resolution thickness maps of both silicon and oxide layers with accuracy and observed optically active imperfections and distributions in the structure.

polarimetric hyperspectral imaging silicon oxide↗

Mine Discrimination Using Multispectral Imagery With Feedforward Neural Networks

Simulated mine detection was performed on a polarimetric hyperspectral imaging dataset collected by using an acousto-optic tunable filter camera. A feedforward artificial neural network was programmed to recognize predefined spectral "templates." The simulation results are provided along with the preprocessing steps and window sizes leading to mine detection without false alarms.

polarimetric↗

Monolithically-Fabricated Tunable Long-Wave Infrared Detectors Based on Dynamic Graphene Metasurfaces.

In this paper, the design, fabrication, and characterization of an actively tunable long-wave infrared detector, made possible through direct integration of a graphene-enabled metasurface with a conventional type-II superlattice infrared detector, are reported. This structure allows for post-fabrication tuning of the detector spectral response through voltage-induced modification of the carrier density within graphene and, therefore, its plasmonic response. These changes modify the transmittance through the metasurface, which is fabricated monolithically atop the detector, allowing for spectral control of light reaching the detector. Importantly, this structure provides a fabrication-controlled alignment of the metasurface filter to the detector pixel and is entirely solid-state. Using single pixel devices, relative changes in the spectral response exceeding 8% have been realized. These proof-of-concept devices present a path toward solid-state hyperspectral imaging with independent pixel-to-pixel spectral control through a voltage-actuated dynamic response.

47 OTHER INSTRUMENTATION↗

Multiple Spectral-Spatial Classification Approach for Hyperspectral Data

A .new multiple classifier approach for spectral-spatial classification of hyperspectral images is proposed. Several classifiers are used independently to classify an image. For every pixel, if all the classifiers have assigned this pixel to the same class, the pixel is kept as a marker, i.e., a seed of the spatial region, with the corresponding class label. We propose to use spectral-spatial classifiers at the preliminary step of the marker selection procedure, each of them combining the results of a pixel-wise classification and a segmentation map. Different segmentation methods based on dissimilar principles lead to different classification results. Furthermore, a minimum spanning forest is built, where each tree is rooted on a classification -driven marker and forms a region in the spectral -spatial classification: map. Experimental results are presented for two hyperspectral airborne images. The proposed method significantly improves classification accuracies, when compared to previously proposed classification techniques.

Tarabalka, Yuliya↗

Mineralogical, Elemental, and Tomographic Reconnaissance Investigation for CLPS (METRIC): A Payload Designed for Exploration of Terrestrial Planetary Bodies

Geological materials (indeed, all solid objects) are characterized by their crystal structure, elemental composition, and morphology. The Mineralogical, Elemental, and Tomographic Reconnaissance Investigation for CLPS (METRIC) instrument suite quantifies all three. These measurements address fundamental science questions (e.g., the origin and evolution of planetary bodies) and support the human exploration of space (e.g., the characterization of regolith for ISRU and the constraint of its geotechnical properties). METRIC comprises an X-ray Diffraction/X-ray Fluorescence instrument (XRD: mineral structure and XRF: elemental composition), an X-ray micro-Computed Tomography instrument (XCT: 3D internal micromorphology), and a hyperspectral imaging infrared spectrometer (IRS) to provide local/regional mineralogic context for these measurements. METRIC XRD/F draws heritage from the highly successful Mars Science Laboratory CheMin instrument. The METRIC XRD/F employs two separate sample cells, one optimized for XRD and one for XRF, resulting in more rapid XRD analysis (tens of minutes vs. tens of hours for CheMin) and an orders-of-magnitude improvement in XRF detection. XCT has not been deployed in space, so the METRIC XCT represents a new capability for solar system exploration. The XCT uses the same basic high-TRL components as METRIC XRD/F, decreasing its development cost for flight. The METRIC IRS is a derivative of the NASA Earth Science Technology Office funded Hyperspectral Thermal Imager instrument and utilizes the NASA Technology Transfer Program to incorporate a commercial-of-the-shelf infrared camera ruggedized for space by NASA Marshall Space Flight Center. The IRS spectral range (8–14 µm) and resolution (10.8 cm -1 ) are tailored to quantify mineralogy in rocks using their characteristic Reststrahlen bands and to characterize mineralogy of soils using the position of the Christensen Feature. The METRIC payload is currently designed for deployment to the Moon on a Commercial Lunar Payload Services (CLPS) mission, where the XRD/F and XCT would be located on a lander and the IRS would be on deployed on a companion rover to evaluate the mineralogical diversity of the landing site. A pneumatic drill designed by Honeybee Robotics would excavate regolith up to 50 cm below the lander and deliver multiple aliquots of regolith to the XRD/F and XCT. The METRIC payload could also be deployed on a rover. In this case, a sample handling system on a robotic arm could scoop regolith and/or drill rocks and deliver powder to the XRD/F and XCT located in the rover’s interior. Alternatively, METRIC instruments could be used singly or in combination on human space missions. The XRD/F and XCT could be used to characterize samples in a rover or in a science laboratory within a habitat. These data could help astronauts identify resource-enriched rocks and regolith and triage geologic samples to return samples of high interest for analysis in terrestrial laboratories. The IRS could be attached to a human-navigated rover to collect mineralogical data along a traverse and identify high-priority science samples.

E. B. Rampe↗

Deriving the Infrared Complex Refractive Indices of Organic Powders for Optical Modeling: Comparison of Methods

Identification of solids via infrared reflection spectroscopy requires a spectral library of all solids likely to be encountered. A confounding factor in populating such a spectral library is that the reflectance spectra of solids vary with their form, including particle size, film thickness, and substrate. To reduce the efforts of experimentally constructing such a library, an alternate strategy is to use the wavelength-dependent optical constants, n and k, of a solid to calculate a series of reflectance spectra corresponding to each scenario or morphology. Because most n/k measurements are best performed on mm-sized crystals, however, the challenge of determining the optical constants increases when a solid is only readily available as a powder, as is often the case. Some organic solids, such as caffeine, are both unavailable in large crystals and difficult to press into pellets. In this study, the infrared optical constants, or complex refractive indices, of caffeine were determined using three different methods: single-angle reflectance, infrared spectroscopic ellipsometry, and quantitative absorbance measurements of KBr pellets. The n and k values derived through each method were used to model the hyperspectral imaging reflectance spectrum of a caffeine film on a steel planchet. Over 1,110 – 870 cm-1, the single-angle reflectance-derived n and k had the best correlation with the experimental spectrum. These results suggest different organic solids may require different methods to determine the most accurate infrared complex refractive indices for synthetic spectral libraries.

FTIR, hyperspectral imaging, infrared, infrared (I↗

Intra-Grain Local Luminescence Properties of CdSe0.1Te0.9 Thin Films

We report on the local photoluminescence properties of grains and grain boundaries of CdSe 0.1 Te 0.9 thin film deposited by the colossal grain growth method using a wide-field hyperspectral imaging technique. We observed significant variations in the photoluminescence intensity of both individual grains and also that of grain boundaries. Multiple sub-bandgap defect peaks were captured in the luminescence spectra in the energy range 1.2 eV to 1.6 eV. The intensity and peak positions of these sub-gap emissions were slightly different among various grains and at the grain boundaries, revealing intra- and inter-grain variations in these polycrystalline thin films. A recently-developed density-of-states based photoluminescence model was extended to include multiple peaks and was fitted to the data. We observed that at a fixed temperature, the quasi-Fermi level splitting energy and a disordered energy parameter can be extracted locally by use of this model.

data models↗

One-shot gas detection with transformer paired neural networks in Mako collected longwave infrared hyperspectral imagery

To date, careful data treatment workflows and statistical detectors are used to perform hyperspectral image (HSI) detection of any gas contained in a spectral library, which is often expanded with physics models to incorporate different spectral characteristics. In general, surrounding evidence or known gas-release parameters are used to provide confidence in or confirm detection capability, respectively. This makes quantifying detection performance difficult as it is nearly impossible to develop an absolute ground truth for gas target pixel presence in collected HSI. Consequently, developing and comparing new detection methods, especially machine learning (ML)-based methods, is susceptible to subjectivity in derived detection map quality. Here, in this work, we demonstrate the first use of transformer-based paired neural networks (PNNs) for one-shot gas target detection for multiple gases while providing quantitative classification and detection metrics for their use on labeled data. Terabytes of training data are generated from a database of long-wave infrared HSI obtained from historical Mako sensor campaigns over Los Angeles. By incorporating labels, singular signature representations, and a model development pipeline, we can tune and select PNNs to detect multiple gas targets that are not seen in training on a quantitative basis. We additionally assess our test set detections using interpretability techniques widely employed with ML-based predictors, but less common with detection methods relying on learned latent spaces.

Hyperspectral imaging↗

Improved Gas Plume Identification Using Nearest Neighbor Methods for Background Estimation

Longwave infrared (LWIR) hyperspectral imaging (HSI) can be used for many tasks in remote sensing, including detecting and identifying effluent gases by LWIR sensors on airborne platforms. Identification is used after detection to increase confidence in weakly detected plumes, reduce false positives from detection, and distinguish between similar and confounding material signatures. Background estimation is an important step used to reveal the unique spectral characteristics of the detected gas, allowing the identification model to determine what the gas is specifically. The importance of proper background estimation increases when dealing with weak signals, large libraries of gases of interest, and uncommon or heterogeneous backgrounds. In this article, we propose two methods for background estimation: a novel k-nearest segments (KNS) algorithm and the standard k-nearest neighbors (KNN) algorithm. We test our methods and three existing background estimation methods for comparison against global background estimation to determine which performs best at estimating the true background radiance under a plume and for increasing identification confidence using a neural network classification model. We compare the different methods using 640 simulated weak plumes in an urban environment. For identification, our KNS algorithm improves median neural network identification confidence by 53.2%. For background radiance estimation, the KNN algorithm provides a median of 49 times less RMSE than global background estimation. Furthermore, KNN is the easiest method to tune for different plumes, making it an excellent “out of the box” background estimator.

47 OTHER INSTRUMENTATION↗

VIMS Observations of Titan During the First Two Close Flybys by the Cassini-Huygens Mission

The joint NASA-ESA-ASI Cassini-Huygens mission reached the saturnian system on July 1st 2004. It started the observations of Saturn s environment including its atmosphere, rings, and satellites (Phoebe, Iapetus and Titan). Titan, one of the primary scientific interests of the mission, is veiled by an ubiquitous thick haze. Its surface cannot be seen in the visible but as the haze effects decrease with increasing wavelength, there is signal in the infrared atmospheric windows if no clouds are present. Onboard the Cassini spacecraft, the VIMS instrument (Visual and Infrared Mapping Spectrometer) is expected to pierce the veil of the hazy moon and successfully image its surface in the infrared wavelengths, taking hyperspectral images in the range 0.4 to 5.2 micron. On 26 October (TA) and 13 December 2004 (TB), the Cassini-Huygens mission flew over Titan at an altitude lower than 1200 km at closest approach. VIMS acquired several tens of image cubes with spatial resolution ranging from a few tens of kilometers down to 1.5 kilometer per pixel, demonstrating its capability for studying Titan s geology.

Rodriquez, S.↗

PACE: How One NASA Mission Aligns With the United Nations Decade of Ocean Science for Sustainable Development (Ocean Shot #1)

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE; https://pace.gsfc.nasa.gov) mission, scheduled for launch in January 2024, will extend the continuous high-quality ocean color, atmospheric aerosol, and cloud data records begun by NASA in the late 1990s, building on the heritage of the Coastal Zone Color Scanner (CZCS), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS) (Figure 1). PACE’s global hyperspectral imaging radiometer design concept will enable new discoveries in Earth’s living ocean (Figure 2), such as the diversity of organisms fueling marine food webs and how aquatic ecosystems respond to environmental change. Its instrument payload (Figure 3) will also observe Earth’s atmosphere to study clouds, airborne aerosol particles, and the interactions between the two. Looking at the ocean, clouds, and aerosols together will improve our knowledge of the roles each plays in our evolving planet. Other applications of PACE science data records—from identifying the frequency, extent, and duration of aquatic harmful algal blooms to improving our understanding of air quality—will result in direct economic, recreational, and societal benefits. Ultimately, by extending and expanding NASA’s long record of global Earth satellite observations, the PACE mission will monitor our home planet in new and advanced ways in the coming decade.

Ocean color↗

Progress in InAs/InAsSb Superlattice Barrier Infrared Detectors

The InAs/InAsSb (Gallium-free) type-II strained-layer superlattice (T2SLS) has emerged in recent years as a viable infrared detector material. In particular, mid-wavelength InAs/InAsSb T2SLS focal plane array (FPA) based on the nBn detector architecture exhibits good operating characteristics at 160 K, demonstrating a considerably operating temperature advantage over InSb FPAs. In the long and very long cutoff wavelengths, InAs/InAsSb T2SLS detectors with n-type absorbers are limited in their attainable quantum efficiency (QE) due to shorter hole diffusion lengths and relatively modest absorption coefficients. We have explored long and very long wavelength InAs/InAsSb T2SLS complementary barrier infrared detectors (CBIRDs) that contain p-type absorber layers in order to take advantage of the longer electron diffusion length for QE enhancement. We also discuss recent development of the InAs/InAsSb T2SLS infrared detectors at the Jet Propulsion Laboratory for NASA Earth Science applications, including long-wavelength infrared FPAs for land imaging, and mid-wavelength infrared FPAs for CubeSat hyperspectral imaging.

Pagano, Thomas S.↗

Fast Active-Set Thresholding Method for Nonnegative Least Squares

Nonnegative Least Squares (NNLS) is a fundamental constrained optimization problem encountered in many applications such as image deblurring, signal processing, nonnegative matrix factorization, magnetic microscopy, and hyperspectral imaging. Active-set based methods are a common class of algorithms for solving NNLS which identify the optimal variable set of the NNLS solution. They do so by iteratively solving a series of unconstrained least squares problems, identifying which variables violate the nonnegativity constraints, and then swapping variables in/out of consideration until the optimal set of variables is found. Several variations improving upon this method exist in the literature. In this work, we propose an active-set swap heuristic which further improves upon existing active-set based methods for NNLS. Our optimizations are based upon adding multiple variables to the passive set within a threshold of the smallest gradient value and removing variables within a similar threshold of the closest boundary constraint. We leverage these optimizations to yield a Fast Active-Set Thresholding NNLS (FAST-NNLS) algorithm which significantly outperforms the existing state-of-the-art NNLS algorithms for a wide range of problems. Rigorous convergence guarantees are proven for the proposed method. We demonstrate the effectiveness of our proposed method on multiple synthetic datasets and two realworld text analysis applications. In doing so, we present the most comprehensive NNLS solver comparison in the literature to date.

Cobb, Benjamin [Georgia Institute of Technology]↗

Efficient Spectral Endmember Detection Onboard the EO-1 Spacecraft

Spaceflight and planetary exploration place severe constraints on the available bandwidth for downlinking large hyperspectral images. In addition, communications with spacecraft often occur intermittently, so mission-relevant hyperspectral data must wait for analysis on the ground before it can inform spacecraft activity planning. Onboard endmember detection can help alleviate these problems. It enables novelty detection and target identification for scheduling follow-up activities such as additional observation by narrow field of view instruments. Additionally, endmember analysis can facilitate data summary for downlink. This work describes a planned experiment of selective downlink by the EO-1 autonomous spacecraft. Here an efficient superpixel endmember detection algorithm keeps to the limited computational constraints of the flight processor. Tests suggest the procedure could enable significant improvements in downlink efficiency.

Endmember Detection↗

Fractal Characterization of Hyperspectral Imagery

Two Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral images selected from the Los Angeles area, one representing urban and the other, rural, were used to examine their spatial complexity across their entire spectrum of the remote sensing data. Using the ICAMS (Image Characterization And Modeling System) software, we computed the fractal dimension values via the isarithm and triangular prism methods for all 224 bands in the two AVIRIS scenes. The resultant fractal dimensions reflect changes in image complexity across the spectral range of the hyperspectral images. Both the isarithm and triangular prism methods detect unusually high D values on the spectral bands that fall within the atmospheric absorption and scattering zones where signature to noise ratios are low. Fractal dimensions for the urban area resulted in higher values than for the rural landscape, and the differences between the resulting D values are more distinct in the visible bands. The triangular prism method is sensitive to a few random speckles in the images, leading to a lower dimensionality. On the contrary, the isarithm method will ignore the speckles and focus on the major variation dominating the surface, thus resulting in a higher dimension. It is seen where the fractal curves plotted for the entire bandwidth range of the hyperspectral images could be used to distinguish landscape types as well as for screening noisy bands.

Qiu, Hon-Iie↗

Double-Diffusive Convection During Growth of Halides and Selenides

Heavy metal halides and selenides have unique properties which make them excellent materials for chemical, biological and radiological sensors. Recently it has been shown that selenohalides are even better materials than halides or selenides for gamma-ray detection. These materials also meet the strong needs of a wide band imaging technology to cover ultra-violet (UV), midwave infrared wavelength (MWIR) to very long wavelength infrared (VLWIR) region for hyperspectral imager components such as etalon filters and acousto-optic tunable filters (AO). In fact AOTF based imagers based on these materials have some superiority than imagers based on liquid crystals, FTIR, Fabry-Perot, grating, etalon, electro-optic modulation, piezoelectric and several other concepts. For example, broadband spectral and imagers have problems of processing large amount of information during real-time observation. Acousto-Optic Tunable Filter (AOTF) imagers are being developed to fill the need of reducing processing time of data, low cost operation and key to achieving the goal of covering long-wave infrared (LWIR). At the present time spectral imaging systems are based on the use of diffraction gratings are typically used in a pushbroom or whiskbroom mode. They are mostly used in systems and acquire large amounts of hyperspectral data that is processed off-line later. In contrast, acousto-optic tunable filter spectral imagers require very little image processing, providing new strategies for object recognition and tracking. They are ideally suited for tactical situations requiring immediate real-time image processing. But the performance of these imagers depends on the quality and homogeneity of acousto-optic materials. In addition for many systems requirements are so demanding that crystals up to sizes of 10 cm length are desired. We have studied several selenides and halide crystals for laser and AO imagers for MWIR and LWIR wavelength regions. We have grown and fabricated crystals of several materials such as mercurous chloride, mercurous bromide, mercurous iodide, lead chloride lead bromide, lead iodide, thallium arsenic selenide, gallium selenide, zince sulfide zinc selenide and several crystals into devices. We have used both Bridgman and physical vapor transport (PVT) crystal growth methods. In the past have examined PVT growth numerically for conditions where the boundary of the enclosure is subjected to a nonlinear thermal profile. Since past few months we have been working on binary and ternary materials such as selenoiodides, doped zinc sulfides and mercurous chloro bromide and mercurous bromoiodides. In the doped and ternary materials thermal and solutal convection play extremely important role during the growth. Very commonly striations and banding is observed. Our experiments have indicated that even in highly purified source materials, homogeneity in 1-g environment is very difficult. Some of our previous numerical studies have indicated that gravity level less than 10-4 (-g) helps in controlling the thermosolutal convection. We will discuss the ground based growth results of HgClxBr(1-x) and ZnSe growth results for the mm thick to large cm size crystals. These results will be compared with our microgravity experiments performed with this class of materials. For both HgCl-HgBr and ZnS-ZnSe the lattice parameters of the mixtures obey Vagard's law in the studied composition range. The study demonstrates that properties are very anisotropic with crystal orientation, and performance achievement requires extremely careful fabrication to utilize highest figure of merit. In addition, some parameters such as crystal growth fabrication, processing time, resolution, field of view and efficiency will be described based on novel solid solution materials. It was predicted that very similar to the pure compounds solid solutions also have very large anisotropy, and very precise oriented and homogeneous bulk and thin film crystals is required to achieve maximum performance of laser or imagers. Some of the parameters controlling the homogeneity such as thermos-solutal convection driven forces can be controlled in microgravity environments to utilize the benefits of these unique materials.

Singh, N. B.↗