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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 55 records · Page 3

Highly efficient bifacial single-junction perovskite solar cells

Bifacial photovoltaics (PV) harvest solar irradiance from both their front and rear surfaces, boosting energy conversion efficiency to maximize their electrical power production. For single-junction perovskite solar cells (PSCs), the performance of bifacial configurations is still far behind that of their state-of-the-art monofacial counterparts. Here, in this paper, we report on highly efficient, bifacial, single-junction PSCs based on the p-i-n (or inverted) architecture. We used optical and electrical modeling to design a transparent conducting rear electrode for bifacial PSCs to enable optimized efficiency under a variety of albedo illumination conditions. The bifaciality of the PSCs was about 91%–93%. Under concurrent bifacial measurement conditions, we obtained equivalent, stabilized bifacial power output densities of 26.9, 28.5, and 30.1 mW/cm 2 under albedos of 0.2, 0.3, and 0.5, respectively. We further showed that bifacial perovskite PV technology has the potential to outperform its monofacial counterparts with higher energy yields and lower levelized cost of energy (LCOE).

14 SOLAR ENERGY↗

4D-STEM of Beam-Sensitive Materials

We report that a scanning electron nanobeam diffraction, or 4D-STEM (four-dimensional scanning transmission electron microscopy), is a flexible and powerful approach to elucidate structure from "soft" materials that are challenging to image in the transmission electron microscope because their structure is easily damaged by the electron beam. In a 4D-STEM experiment, a converged electron beam is scanned across the sample, and a pixelated camera records a diffraction pattern at each scan position. This four-dimensional data set can be mined for various analyses, producing maps of local crystal orientation, structural distortions, crystallinity, or different structural classes. Holding the sample at cryogenic temperatures minimizes diffusion of radicals and the resulting damage and disorder caused by the electron beam. The total fluence of incident electrons can easily be controlled during 4D-STEM experiments by careful use of the beam blanker, steering of the localized electron dose, and by minimizing the fluence in the convergent beam thus minimizing beam damage. This technique can be applied to both organic and inorganic materials that are known to be beam-sensitive; they can be highly crystalline, semicrystalline, mixed phase, or amorphous. One common example is the case for many organic materials that have a π-π stacking of polymer chains or rings on the order of 3.4-4.2 Å separation. If these chains or rings are aligned in some regions, they will produce distinct diffraction spots (as would other crystalline spacings in this range), though they may be weak or diffuse for disordered or weakly scattering materials. We can reconstruct the orientation of the π-π stacking, the degree of π-π stacking in the sample, and the domain size of the aligned regions. This Account summarizes illumination conditions and experimental parameters for 4D-STEM experiments with the goal of producing images of structural features for materials that are beam-sensitive. We will discuss experimental parameters including sample cooling, probe size and shape, fluence, and cameras. 4D-STEM has been applied to a variety of materials, not only as an advanced technique for model systems, but as a technique for the beginning microscopist to answer materials science questions. It is noteworthy that the experimental data acquisition does not require an aberration-corrected TEM but can be produced on a variety of instruments with the right attention to experimental parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding and Controlling the Performance-Limiting Steps of Catalyst-Modified Semiconductors

Understanding and controlling factors that restrict the rates of fuel-forming reactions are essential to designing effective catalyst-modified semiconductors for applications in solar-to-fuel technologies. Herein, we describe GaAs semiconductors featuring a polymeric coating that contains cobaloxime-type catalysts for photoelectrochemically powering hydrogen production. The activities of these electrodes (limiting current densities >20 mA cm –2 under 1-sun illumination) enable identification of fundamental performance-limiting bottlenecks encountered at relatively high rates of fuel formation. Experiments conducted under varying bias potential, pH, illumination intensity, and scan rate reveal two distinct mechanisms of photoelectrochemical hydrogen production. At relatively low polarization and pH, the limiting photoactivity is independent of illumination conditions and is attributed to a mechanism involving reduction of substrate protons. At relatively high polarization or pH, the limiting photoactivity shows a linear response to increasing photon flux and is attributed to a mechanism involving reduction of substrate water. Furthermore, this work illustrates the complex interplay between transport of photons, electrons, and chemical substrates in photoelectrosynthetic reactions and highlights diagnostic tools for better understanding these processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Plasmon-Mediated Intramolecular Methyl Migration with Nanoscale Spatial Control

Plasmonic materials interact strongly with light to focus and enhance electromagnetic radiation down to nanoscale volumes. Due to this localized confinement, materials that support localized surface plasmon resonances are capable of driving energetically unfavorable chemical reactions. In certain cases, the plasmonic nanostructures are able to preferentially catalyze the formation of specific photoproducts, which offers an opportunity for the development of solar-driven chemical synthesis. Here, using plasmonic environments, we report inducing an intramolecular methyl migration reaction, forming 4-methylpyridine from N-methylpyridinium. Using both experimental and computational methods, we were able to confirm the identity of the N-methylpyridinium by making spectral comparisons against possible photoproducts. This reaction involves breaking a C–N bond and forming a new C–C bond, highlighting the ability of plasmonic materials to drive complex and selective reactions. Additionally, we observe that the product yield depends strongly on optical illumination conditions. This is likely due to steric hindrance in specific regions on the nanostructured plasmonic substrate, providing an optical handle for driving plasmonic catalysis with spatial specificity. Furthermore, this work adds yet another class of reactions accessible by surface plasmon excitation to the ever-growing library of plasmon-mediated chemical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polarization-Insensitive Medium-Switchable Holographic Metasurfaces

The adoption of metasurfaces has led to revolutionary advances in holography due to improved compactness, integrability, and performance. Switchable meta-holograms projecting different replay field images in a controllable manner are highly desirable. Still, existing technologies generally rely on the use of polarized light and additional optics to facilitate switching. Consequently, the potential benefits afforded through the use of metasurfaces are limited both by the system complexity and a fixed relationship between the optical input and output. In this manuscript, we demonstrate polarization-insensitive metasurfaces encoding arbitrary and independent holograms, which can be switched between by changing the refractive index of the infiltration medium while maintaining identical illumination conditions. Finally, by sidestepping the requirements for high-performance light sources, switching optics, or delicate alignment, this approach points toward ultracompact and cost-effective switchable meta-holograms for various practical applications, such as holographic image projection, eye-perceptible sensors, optical information storage, processing, and security.

36 MATERIALS SCIENCE↗

Serial femtosecond crystallography on in vivo-grown crystals drives elucidation of mosquitocidal Cyt1Aa bioactivation cascade

Cyt1Aa is the one of four crystalline protoxins produced by mosquitocidal bacterium Bacillus thuringiensis israelensis (Bti) that has been shown to delay the evolution of insect resistance in the field. Limiting our understanding of Bti efficacy and the path to improved toxicity and spectrum has been ignorance of how Cyt1Aa crystallizes in vivo and of its mechanism of toxicity. Here, we use serial femtosecond crystallography to determine the Cyt1Aa protoxin structure from sub-micron-sized crystals produced in Bti. Structures determined under various pH/redox conditions illuminate the role played by previously uncharacterized disulfide-bridge and domain-swapped interfaces from crystal formation in Bti to dissolution in the larval mosquito midgut. Biochemical, toxicological and biophysical methods enable the deconvolution of key steps in the Cyt1Aa bioactivation cascade. We additionally show that the size, shape, production yield, pH sensitivity and toxicity of Cyt1Aa crystals grown in Bti can be controlled by single atom substitution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Magnetically dependent photovoltages in permalloy films and gratings

Significant photoinduced voltages observed in permalloy structures consist of two contributions with different origins, which depend on illumination conditions, structure geometry and magnetic field in distinct ways. The first component is the plasmon drag effect voltage closely associated with plasmon propagation. The second contribution is magnetically dependent and can be related to photoinduced gradients in the sample temperature and spin polarization. Possible mechanisms of the effect are discussed

36 MATERIALS SCIENCE↗

Photoinduced phase separation in the lead halides is a polaronic effect

We present a perspective on recent observations of the photoinduced phase separation of halides in multi-component lead-halide perovskites. The spontaneous phase separation of an initial homogeneous solid solution under steady-state illumination conditions is found experimentally to be reversible, stochastic, weakly dependent on morphology, yet strongly dependent on composition and thermodynamic state. Regions enriched in a specific halide species that form upon phase separation are self-limiting in size, pinned to specific compositions, and grow in number in proportion to the steady-state carrier concentration until saturation. These empirical observations of robustness rule out explanations based on specific defect structures and point to the local modulation of an existing miscibility phase transition in the presence of excess charge carriers. A model for rationalizing existing observations based on the coupling between composition, strain, and charge density fluctuations through the formation of polarons is reviewed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Inverted metamorphic GaInAs solar cell grown by dynamic hydride vapor phase epitaxy

We present an inverted metamorphic rear heterojunction ~1.0 eV GaInAs solar cell deposited by dynamic hydride vapor phase epitaxy (D-HVPE) with high growth rate. This device uses a Ga 1-x In x P compositionally graded buffer (CGB) to bridge the lattice constant gap between the GaAs substrate and the Ga0.71In0.29As emitter layer. High-resolution x-ray diffraction and transmission electron microscopy confirm that the Ga 0.71 In 0.29 As emitter is grown lattice-matched to the in-plane lattice constant of the CGB with minimal generation of defects at the GaInAs/GaInP interface. The device contains a threading dislocation density of 2.3 × 10 6 cm -2 , a level that enables high-performance minority carrier devices and is comparable to previously demonstrated GaInP CGBs grown by D-HVPE. The device exhibits an open-circuit voltage of 0.589 V under a one-sun AM1.5G illumination condition and a bandgap-voltage offset of 0.407 V, indicating metamorphic epitaxial performance nearly equal to state-of-the-art devices. We analyze the dark current of the device and determine that reducing recombination in the depletion region, which can be achieved by reducing the threading dislocation density and optimizing the device doping density, will improve the device performance. Furthermore, the CGB and device layers, comprising ~8 µm of thickness, are grown in under 10 min, highlighting the ability of D-HVPE to produce high-quality metamorphic devices of all types with the potential for dramatically higher throughput compared to present technology.

14 SOLAR ENERGY↗

Optical contrast analysis of α -RuCl 3 nanoflakes on oxidized silicon wafers

α-RuCl 3 , a narrow-band Mott insulator with a large work function, offers intriguing potential as a quantum material or as a charge acceptor for electrical contacts in van der Waals devices. In this work, we perform a systematic study of the optical reflection contrast of α-RuCl 3 nanoflakes on oxidized silicon wafers and estimate the accuracy of this imaging technique to assess the crystal thickness. Via spectroscopic micro-ellipsometry measurements, we characterize the wavelength-dependent complex refractive index of α-RuCl 3 nanoflakes of varying thickness in the visible and near-infrared. Building on these results, we simulate the optical contrast of α-RuCl 3 nanoflakes with thicknesses below 100 nm on SiO 2 /Si substrates under different illumination conditions. We compare the simulated optical contrast with experimental values extracted from optical microscopy images and obtain good agreement. Finally, we show that optical contrast imaging allows us to retrieve the thickness of the RuCl 3 nanoflakes exfoliated on an oxidized silicon substrate with a mean deviation of –0.2 nm for thicknesses below 100 nm with a standard deviation of only 1 nm. Our results demonstrate that optical contrast can be used as a non-invasive, fast, and reliable technique to estimate the α-RuCl 3 thickness.

2D materials↗

Incident beam optics optimization for the single crystal neutron diffractometer Pioneer with a polarized beam option

Pioneer, a next-generation single-crystal neutron diffractometer, is under development for Oak Ridge National Laboratory’s Second Target Station. Designed to address a wide range of scientific questions, Pioneer will deliver homogeneous neutron beams with customizable size and divergence and provide a polarized beam option. This article introduces its incident beam optics, highlighting the optimization methodology and the simulated performance. Pioneer will utilize a modified elliptical-straight guide for neutron transport and deploy slit packages and insertable apertures to control beam size and divergence. The optimized guide geometry matches the optimal-and-full-sample-illumination condition, and the beam control system effectively filters out unwanted neutrons while preserving the desired ones. In addition, we have found that polygon-approximated guides provide satisfactory transport efficiency and beam homogeneity, eliminating the need for truly curved guides. Further, to enhance neutronics performance and reduce cost, the coatings of supermirror elements are individually optimized to the lowest half-integer m-values that are sufficient to deliver the desired neutrons. After evaluating polarizing V-cavities and 3 He spin filters over the default polarized wavelength band of 1.2–5.5 Å, we selected a translatable multichannel polarizing V-cavity as the incident beam polarizer. Strategically placed at a location where the beam divergence is low and a large in-guide gap has negligible impact on transport efficiency, the optimized V-cavity achieves an average P 2 T of ~35%.

47 OTHER INSTRUMENTATION↗

Topographic Correction of Optical Remote Sensing Images in Mountainous Areas: A systematic review

Rugged terrain distorts optical remote sensing observations and subsequently impacts land cover classification and biophysical and biochemical parameter retrieval over mountainous areas. Therefore, topographic correction (TC) is a prerequisite for many remote sensing applications. Although various TC methods have been explored over the past four decades to mitigate topographic effects, a systematic and global review of these studies is still lacking. Using a multicomponent bibliometric approach, we extracted bibliometric metadata from 426 publications identified by searching titles, keywords, and abstracts for research on “topographic correction” and “topographic effects” in Scopus and Web of Science (WoS) from 1980 to 2022. Here this systematic review revealed a rapid growth in the number of TC studies since the 1980s, primarily driven by the availability of decametric-resolution remote sensing observations and digital elevation models (DEMs). Most of the research has focused on relatively low-elevation regions, with increasing attention beyond American and European regions, particularly in China. The seasonal distribution of satellite acquisition for TC showed considerable imbalance, mainly concentrated in months with favorable solar illumination conditions (e.g., May to October). Important themes emerged from the keyword analysis, including satellite sensors, DEMs, TC methods, evaluation criteria, and applications.

58 GEOSCIENCES↗

Highly Efficient Bifacial Single Junction Perovskite Solar Cells

We report on efficient, single-junction bifacial perovskite solar cells (PSCs) that simultaneously exhibit high front-side-illumination power conversion efficiency (PCE) (over 22 %) and high bifaciality (over 91%), which represents a significant advancement for single junction bifacial PSC development. The bifacial PSCs exhibit substantial performance boost under concurrent front and rear illumination conditions. The stabilized power output goes up to 25.3 mW/cm 2 under albedos of 0.2, which is comparable to the state-of-the-art monofacial single-junction PSCs. Our work demonstrates the value and potential of bifacial single junction PSCs as an attractive direction for future scientific study and commercialization.

commercialization↗

Thermal Image Processing for Feature Extraction from Encapsulated Phase Change Materials

Encapsulated inorganic particles with high melting points (>300 °C) are desired as high-temperature Phase Change Materials (PCMs) for next-generation Latent Heat Thermal Energy Storage (LHTES) systems. One of the many challenges during the development of PCMs is to achieve a high throughput that in turn depends on accurately modeling the relation between process parameters and geometric & thermal properties of the PCMs particle. During the production of the PCMs, a high-speed infrared camera is used to acquire images of the encapsulated material under controlled illumination conditions. This research article focuses on the development of image processing techniques for both geometric and thermal feature extraction during the development of the PCMs. A user-friendly GUI has been designed in MATLAB and preliminary experimental results have demonstrated that the method is fast, accurate and reliable for a high throughput production. The extracted features will be used to develop Machine Learning (ML) models to predict the geometric and thermal properties of the PCM based on the process parameter settings. The ML model will accelerate the search for the optimized process settings to boost the throughput of the production.

25 ENERGY STORAGE↗

Grassmannian Diffusion Maps--Based Dimension Reduction and Classification for High-Dimensional Data

This work introduces the Grassmannian diffusion maps (GDMaps), a novel nonlinear dimensionality reduction technique that defines the affinity between points through their representation as low-dimensional subspaces corresponding to points on the Grassmann manifold. Here, the method is designed for applications, such as image recognition and data-based classification of constrained high-dimensional data where each data point itself is a high-dimensional object (i.e., a large matrix) that can be compactly represented in a lower-dimensional subspace. The GDMaps is composed of two stages. The first is a pointwise linear dimensionality reduction wherein each high-dimensional object is mapped onto the Grassmann manifold representing the low-dimensional subspace on which it resides. The second stage is a multipoint nonlinear kernel-based dimension reduction using diffusion maps to identify the subspace structure of the points on the Grassmann manifold. To this end, an appropriate Grassmannian kernel is used to construct the transition matrix of a random walk on a graph connecting points on the Grassmann manifold. Spectral analysis of the transition matrix yields low-dimensional Grassmannian diffusion coordinates embedding the data into a low-dimensional reproducing kernel Hilbert space. Further, a novel data classification/recognition technique is developed based on the construction of an overcomplete dictionary of reduced dimension whose atoms are given by the Grassmannian diffusion coordinates. Three examples are considered. First, a "toy" example shows that the GDMaps can identify an appropriate parametrization of structured points on the unit sphere. The second example demonstrates the ability of the GDMaps to revealing the intrinsic subspace structure of high-dimensional random field data. In the last ex- ample, a face recognition problem is solved considering face images subject to varying illumination conditions, changes in face expressions, and occurrence of occlusions. The technique presented high recognition rates (i.e., 95% in the best case) using a fraction of the data required by conventional methods.

42 ENGINEERING↗

COVID-19 Data Curation Effort: An Initial Analysis of the Data

During the COVID-19 pandemic of 2020, major case reporting outlets quickly coalesced around two or three primary vendors. Johns Hopkins University and The New York Times were among the more prominent, and all were of great value to the nation, particularly during the uncertain early stages of the pandemic. They primarily focused on three major attributes: number of new cases, deaths, and recovery. Recognizing that many states were reporting very detailed data sets (e.g., hospital beds) at a county level or finer, the ORNL Pandemic Modeling team embarked on a major data curation effort from March to June 2020 for the purpose of capturing this wealth of detailed data. The challenge of curating this data was daunting. The number of attributes reported by the states grew on almost on a weekly basis. States were routinely shifting their web tool strategies away from easily parsable HTML-based formatting to new Tableau and ArcGIS content. This growth in the sheer number of attributes, combined with the unpredictable shifts in data format, meant an aggressive and agile combination of automated scripting and manual scraping was required to capture new daily streams. Further, the team had to scale up staff and widen its approach for capture and storage. As a result, the team collected more than 11 million data points. Following the close of this data collection effort on June 30 th , 2020, the team embarked on a major effort to appraise what had been collected, including an inventory list, spatial completeness, temporal completeness, scale and geographic characteristics, and a determination. A report on this matter was submitted on September 15 th , 2020, titled “DOE COVID-19 Data Curation Effort: Overview of Data Collection Coverage”. Over 2000 unique attributes had been netted over a wide range of spatial scales, including state, county, zip codes, health regions, and census blocks. Over 11 million individual data points were collected across these attributes, and spatial coverage (in total) included all 50 states and multiple territories. What became apparent in the process is that in the absence of any data standards, many states reported a wide variety of unique attributes that were not always compatible with attributes reported in other states. As time continued, states began adding new attributes and offering finer grain detail in some older attributes. This meant that not all data streams existed for the entire time period; in fact, the number tended to increase dramatically towards the end. Often, states would begin an attribute series and then stop altogether. These highly variable and uncertain conditions illuminated the need for harmonization approaches that would reconcile and conflate changing attribute names and detail over time. For example, grouping racial data reported as either Black or African American, depending on the state, into a single harmonized attribute. These choices would make a within-state analysis possible during the time period and lead to potential between-state analytics later on. This was almost entirely a manual decision process, requiring some subjective decision-making at times, to prevent a fragmented, short-lived collection of time series fragments that would offer few insights into trends, patterns, and correlates. This report imports harmonized data for state and county into the World Spatio-Temporal Analytics and Mapping Project (WSTAMP). WSTAMP is a major space-time analysis and visualization tool developed at ORNL for the National Geospatial-Intelligence Agency specifically for this kind of exploratory analysis. WSTAMP offers a rich analytical and graphical environment consisting of a wide range of analytics. These include time series plots, statistical summaries, data mining techniques, trend and pattern detection, and hypothesis generation.

59 BASIC BIOLOGICAL SCIENCES↗

An Automated Method for Mapping Giant Kelp Canopy Dynamics from UAV

Satellite and aerial imagery have been used extensively for mapping the abundance and distribution of giant kelp ( Macrocystis pyrifera ) in southern California. There is now great potential for using unoccupied aerial vehicles (UAVs) to map kelp canopy at very high resolutions. However, tides and currents have been shown to affect the amount of floating kelp canopy on the water surface, and the impacts of these processes on remotely sensed kelp estimates in this region have not been fully quantified. UAVs were used to map fine-scale changes in canopy area due to tidal height and current speed at kelp forests off the coast of Palos Verdes, CA and Santa Barbara, CA. An automated method for detecting kelp canopy was developed that was 67% accurate using red-green-blue (RGB) UAV imagery and 93% accurate using multispectral UAV imagery across a range of weather, ocean, and illumination conditions. Increases in tidal height of 1 m reduced the amount of floating kelp canopy by 15% in Santa Barbara and by over 30% in Palos Verdes. The effect of current speed on visible kelp canopy was inconclusive, but there was a trend towards lower canopy area with increased current speed. Therefore, while tidal height and current speed can introduce significant variability to estimates of kelp abundance, the magnitude of this variability is site specific. Still, UAVs are a valuable tool for mapping of kelp canopy and can provide greater spatial resolution and temporal coverage than is possible from many satellite sensors. This data can provide insight into the patterns and drivers of high frequency fluctuations in kelp abundance.

54 ENVIRONMENTAL SCIENCES↗

Decision-Based Fusion for Vehicle Matching

In this work, a framework is proposed for decision fusion utilizing features extracted from vehicle images and their detected wheels. Siamese networks are exploited to extract key signatures from pairs of vehicle images. Our approach then examines the extent of reliance between signatures generated from vehicle images to robustly integrate different similarity scores and provide a more informed decision for vehicle matching. To that end, a dataset was collected that contains hundreds of thousands of side-view vehicle images under different illumination conditions and elevation angles. Experiments show that our approach could achieve better matching accuracy by taking into account the decisions made by a whole-vehicle or wheels-only matching network.

47 OTHER INSTRUMENTATION↗