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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Physical and behavioral adaptations to prevent overheating of the living wings of butterflies

The wings of Lepidoptera contain a matrix of living cells whose function requires appropriate temperatures. However, given their small thermal capacity, wings can overheat rapidly in the sun. Here we analyze butterfly wings across a wide range of simulated environmental conditions, and find that regions containing living cells are maintained at cooler temperatures. Diverse scale nanostructures and non-uniform cuticle thicknesses create a heterogeneous distribution of radiative cooling that selectively reduces the temperature of structures such as wing veins and androconial organs. These tissues are supplied by circulatory, neural and tracheal systems throughout the adult lifetime, indicating that the insect wing is a dynamic, living structure. Behavioral assays show that butterflies use wings to sense visible and infrared radiation, responding with specialized behaviors to prevent overheating of their wings. Our work highlights the physiological importance of wing temperature and how it is exquisitely regulated by structural and behavioral adaptations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

KAZR Hydrometeor and Insect Masks

The Ka-band ARM zenith pointing radar (aka, KAZR) is so sensitive that it detects cloud particles and individual insects. While detecting insects with Ka-band radar is beneficial and desirable to advance radar entomology, this sensitivity can be detrimental to radar meteorology because insects could be interpreted as clouds or precipitation. For example, misclassifying insects as clouds has been a problem for the ARM Active Remote Sensing of Clouds (ARSCL) Value Added Product since its inception (Clothiaux et al. 2000). Based on cloud particle and insect radar scattering properties, an algorithm was developed that identifies clouds, raindrops, ice particles, and insects in KAZR co- and cross-polarimeteric Doppler velocity spectra. The algorithm produces affirmative masks in the KAZR native time and height resolution indicating time-height locations of hydrometeors and insects. The hydrometeor mask contains binary information (e.g., yes/no hydrometeor presence), and the insect mask includes a proxy for insect activity that increases when more insects are detected in the Doppler velocity spectra. The algorithm was developed using KAZR medium sensitivity mode (MD) observations and was applied to two summer seasons of KAZR observations at the Southern Great Plains (SGP) Central Facility: May-October 2018 and 2019. In the future, this data set will be expanded to include other KAZR operating modes and observations from other ARM field sites. Details of the algorithm and data set can be found in: Williams, C.R., K.L. Johnson, S.E. Giangrande, J. C. Hardin, R. Oktem, and D. M. Romps, 2021: Identifying Insects, Clouds, and Precipitation using Vertically Pointing Polarimetric Radar Doppler Velocity Spectra. Atmospheric Measurement Techniques, submitted 6-Feb-2021. https://amt.copernicus.org/preprints/amt-2021-27/#discussion.For more information on the ARSCL VAP, see Clothiaux, E. E., T. P. Ackerman, G. G. Mace, K. P. Moran, R. T. Marchand, M. A. Miller, and B. E. Martner, 2000; J. Appl. Meteor., 39, 645-665.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Genomic Catalog of Stress Response Genes in Anaerobic Fungi for Applications in Bioproduction

Anaerobic fungi are a potential biotechnology platform to produce biomass-degrading enzymes. Unlike model fungi such as yeasts, stress responses that are relevant during bioprocessing have not yet been established for anaerobic fungi. In this work, we characterize both the heat shock and unfolded protein responses of four strains of anaerobic fungi ( Anaeromyces robustus, Caecomyces churrovis, Neocallimastix californiae , and Piromyces finnis ). The inositol-requiring 1 (Ire1) stress sensor, which typically initiates the fungal UPR, was conserved in all four genomes. However, these genomes also encode putative transmembrane kinases with catalytic domains that are similar to the metazoan stress-sensing enzyme PKR-like endoplasmic reticulum kinase (PERK), although whether they function in the UPR of anaerobic fungi remains unclear. Furthermore, we characterized the global transcriptional responses of Anaeromyces robustus and Neocallimastix californiae to a transient heat shock. Both fungi exhibited the hallmarks of ER stress, including upregulation of genes with functions in protein folding, ER-associated degradation, and intracellular protein trafficking. Relative to other fungi, the genomes of Neocallimastigomycetes contained the greatest gene percentage of HSP20 and HSP70 chaperones, which may serve to stabilize their asparagine-rich genomes. Taken together, these results delineate the unique stress response of anaerobic fungi, which is an important step toward their development as a biotechnology platform to produce enzymes and valuable biomolecules.

Swift, Candice L.↗
DOE OSTI2020

Structural Features of Zirconium-Based Metal–Organic Frameworks Affecting Radiolytic Stability

Metal–organic frameworks (MOFs) NU-1000 and UiO-66 are herein exposed to two different gamma irradiation doses and dose rates and analyzed to determine the structural features that affect their stability in these environments. MOFs have shown promise for the capture and sensing of off-gases at civilian nuclear energy reprocessing sites, nuclear waste repositories, and nuclear accident locations. However, little is understood about the structural features of MOFs that contribute to their stability levels under the ionizing radiation conditions present at such sites. This study is the first of its kind to explore the structural features of MOFs that contribute to their radiolytic stability. Both NU-1000 and UiO-66 are MOFs that contain Zr metal-centers with the same metal absorption cross section. However, the two MOFs exhibit different linker connectivities, linker aromaticities, node densities, node connectivities, and interligand separations. In this study, NU-1000 and UiO-66 were exposed to high (423.3 Gy/min, 23 min, and 37 s) and low (0.78 Gy/min, 4320 min) dose rates of 60 Co gamma irradiation. NU-1000 displayed insignificant radiation damage under both dose rates due to its high linker connectivity, low node density, and low node connectivity. However, low radiation dose rates caused considerable damage to UiO-66, a framework with lower aromaticity and smaller interligand separation. Finally, results suggest that chronic, low-radiation environments are more detrimental to Zr MOF stability than acute, high-radiation conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

U(VI) binding onto electrospun polymers functionalized with phosphonate surfactants

We previously observed that phosphonate functionalized electrospun nanofibers can uptake U(VI), making them promising materials for sensing and water treatment applications. Here, we investigate the optimal fabrication of these materials and their mechanism of U(VI) binding under the influence of environmentally relevant ions (e.g., Ca 2+ and CO 3 2- ). We found that U(VI) uptake was greatest on polyacrylonitrile (PAN) functionalized with longer-chain phosphonate surfactants (e.g., hexa- and octadecyl phosphonate; HDPA and ODPA, respectively), which were better retained in the nanofiber after surface segregation. Subsequent uptake experiments to better understand specific solid-liquid interfacial interactions were carried out using 5 mg of HDPA-functionalized PAN mats with 10 μM U at pH 6.8 in four systems with different combinations of solutions containing 5 mM calcium (Ca 2+ ) and 5 mM bicarbonate (HCO 3 -). U uptake was similar in control solutions containing no Ca 2+ and HCO 3 - (resulting in 19 ± 3% U uptake), and in those containing only 5 mM Ca2+ (resulting in 20 ± 3% U uptake). A decrease in U uptake (10 ± 4% U uptake) was observed in experiments with HCO 3 -, indicating that UO 2 -CO 3 complexes may increase uranium solubility. Results from shell-by-shell EXAFS fitting, aqueous extractions, and surface-enhanced Raman scattering (SERS) indicate that U is bound to phosphonate as a monodentate inner sphere surface complex to one of the hydroxyls in the phosphonate functional groups. New knowledge derived from this study on material fabrication and solid-liquid interfacial interactions will help to advance technologies for use in the in-situ detection and treatment of U in water.

42 ENGINEERING↗
DOE OSTI2023

Structural mechanism of intracellular autoregulation of zinc uptake in ZIP transporters

Abstract Zinc is an essential micronutrient that supports all living organisms through regulating numerous biological processes. However, the mechanism of uptake regulation by intracellular Zn 2+ status remains unclear. Here we report a cryo-electron microscopy structure of a ZIP-family transporter from Bordetella bronchiseptica at 3.05 Å resolution in an inward-facing, inhibited conformation. The transporter forms a homodimer, each protomer containing nine transmembrane helices and three metal ions. Two metal ions form a binuclear pore structure, and the third ion is located at an egress site facing the cytoplasm. The egress site is covered by a loop, and two histidine residues on the loop interact with the egress-site ion and regulate its release. Cell-based Zn 2+ uptake and cell growth viability assays reveal a negative regulation of Zn 2+ uptake through sensing intracellular Zn 2+ status using a built-in sensor. These structural and biochemical analyses provide mechanistic insight into the autoregulation of zinc uptake across membranes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Hyperspectral remote sensing-based plant community map for region around NGEE-Arctic intensive research watersheds at Seward Peninsula, Alaska, 2017-2019

Using airborne hyperspectral remote sensing data from NASA Airborne Visible-Infrared Imaging Spectrometer- Next Generation (AVIRIS-NG) platforms in a region near NGEE-Arctic intensive watersheds at Seward peninsula of Alaska, high resolution (5m) maps of plant community distribution were developed and included in this data collected. AVIRIS-NG data collected over 2017-2019 period were used to develop deep neural networks, trained using vegetation plot observations collected at NGEE-Arctic watersheds at Kougarok, Council and Teller. A hierarchical vegetation classification scheme consisting of six classes at Level I, and 16 classes at Level II contained in two .txt files were used to developed the plant community maps for the region. Two geospatial raster data files (.tif) at both thematic levels are shared in this data collection. Data files in this collection use Alaska Albers Equal Area projection. Readme files available in three formats (*.html, *.md, *.pdf) and one *.png visualization map.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Biodegradable surfactants and related compositions, methods and systems

Biodegradable surfactants are described, in which an amphiphilic heteroatom containing hydrocarbon optionally comprising at least one counterion (Z), and related compositions, methods and systems. Biodegradable surfactant described herein has an aHLB value in accordance with equation (1): aHLB=20*Gh/(Gh−Gt) (1) wherein Gh is the Group Number of a hydrophilic head portion of the biodegradable surfactant optionally comprising the at least one counterion (Z), and Gt is the Group Number of a hydrophobic tail portion of the biodegradable surfactant. A biodegradable surfactant in the sense of the disclosure can be tuned to a set hydrophilic-lipophilic balance (aHLB) by selectively modifying at least one tuning moiety of the biodegradable surfactants to provide tuned biodegradable surfactants having an increase or decrease in their adjusted hydrophilic-lipophilic balance (aHLB).

Lyman, Mathew Gerald↗
DOE OSTI2023

Optimization of the number and locations of the calibration stations needed to monitor soil moisture using distributed temperature sensing systems: A proof-of-concept study

The single-probe heat-pulse (SPHP) technique combined with the Fiber-optic Distributed Temperature Sensing (DTS) technology can offer novel high-resolution measurements of soil moisture (θ) over spatial scales ranging from several centimeters to several kilometers. However, the key limitation of this method is in obtaining the calibration relationship between θ and soil thermal conductivity (λ) across a specific field. In a previous study, a new methodology using a Gaussian processes model was presented to account for the spatial variability in the λ-θ relationship. The model aggregated θ measurements from soil moisture sensors scattered over the SPHP transect with the corresponding DTS λ measurements at their locations. In this study, a novel methodology is tested to optimize the number and locations of soil moisture sensors required to account for the spatial variability of the λ - θ relationship to achieve higher accuracy from the SPHP technique. The proposed methodology utilizes hierarchical clustering to analyze the information contained in the spatial structure of the SPHP measurements as the soil dries from a nearly-saturated condition. The proposed methodology was tested using data from a field in Oklahoma. Monte-Carlo simulation was performed to validate the performance of the proposed methodology. The predictions obtained from the proposed methodology resulted in θ measurements accuracy comparable to those obtained from the 10% best Monte-Carlo iterations of randomly assigned soil moisture locations. Further, this study demonstrates that the proposed methodology is more efficient than the traditional practice of randomly spreading calibration soil moisture sensors along the SPHP transect.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Total variation vs L1 regularization: a comparison of compressive sensing optimization methods for chemical detection

One of the fundamental assumptions of compressive sensing (CS) is that a signal can be reconstructed from a small number of samples by solving an optimization problem with the appropriate regularization term. Two standard regularization terms are the L1 norm and the total variation (TV) norm. We present a comparison of CS reconstruction results based on these two approaches in the context of chemical detection, and we demonstrate that optimization based on the L1 norm outperforms optimization based on the TV norm. Our comparison is driven by CS sampling, reconstruction, and chemical detection in two real-world datasets: the Physical Sciences Inc. Fabry-Perot interferometer sensor multispectral dataset and the Johns Hopkins Applied Physics Lab FTIR-based longwave infrared sensor hyperspectral dataset. Both datasets contain the release of a chemical simulant such as glacial acetic acid, triethyl phosphate, and sulfur hexafluoride. For chemical detection we use the adaptive coherence estimator (ACE) and bulk coherence, and we propose algorithmic ACE thresholds to define the presence or absence of a chemical of interest in both un-compressed data cubes and reconstructed data cubes. The un-compressed data cubes provide an approximate ground truth. We demonstrate that optimization based on either the L1 norm or TV norm results in successful chemical detection at a compression rate of 90%, but we show that L1 optimization is preferable. We present quantitative comparisons of chemical detection on reconstructions from the two methods, with an emphasis on the number of pixels with an ACE value above the threshold.

Hyperspectral imagery, L1-norm, total variation, A↗
DOE OSTI2025

Maps of growing season gross primary production and net ecosystem exchange for Council Road Mile Marker 71, Seward Peninsula, Alaska, [2017-2023]

This data archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025a). Murphy et al. (2025a) evaluated whether incorporating observed Arctic vegetation heterogeneity into ELM, the land model of the Department of Energy’s Energy Exascale Earth System Model (E3SM), improved simulations of tundra carbon cycling. The associated model archive can be found at Murphy et al. (2025b). The study focused on the spatial patterns and net landscape-level growing season productivity and carbon uptake. As part of this evaluation, observationally derived maps of average growing season (June–August) net ecosystem exchange (NEE) and gross primary production (GPP) were developed for the same domain. These maps, which form the dataset described here, integrate eddy covariance flux tower, remote sensing, and vegetation community data to provide spatially explicit benchmarks for model evaluation. The maps provide spatially explicit estimates of average growing season NEE and GPP across 13 tundra vegetation communities within the study domain. By combining flux tower observations with Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral imagery and drone-based normalized difference vegetation index (NDVI), these maps capture the heterogeneity of carbon fluxes associated with different Arctic vegetation types. While they represent average seasonal conditions rather than interannual variability, the maps provide a unique dataset for evaluating model performance, comparing vegetation community contributions to landscape-scale carbon cycling, and supporting regional analyses of Arctic carbon dynamics. This data archive contains 5 m resolution maps of vegetation communities, vegetation community average growing season GPP, and vegetation community average growing season NEE (three *.tif files), a User’s Guide (*pdf file), and Table 1 of the User’s Guide displaying vegetation community coverage and average growing season NEE and GPP values (*.csv file).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗
DOE OSTI2022

Metal-embedded optical fibers for monitoring pressure or corrosion at high temperatures

A fiber optic sensor and a related method of manufacture are provided. The fiber optic sensor includes an embedded optical fiber contained within a metal diaphragm assembly, where the terminal end of the optical fiber is positioned opposite a diaphragm. The method includes forming a metal-embedded optical fiber by ultrasonic additive manufacturing and securing the metal-embedded optical fiber to a housing having a diaphragm that is opposite of the terminal end of the optical fiber. The sensor can provide extremely accurate pressure measurement at high temperatures and in highly corrosive media. An optical fiber-based pressure sensing system is also provided.

Petrie, Christian M.↗
DOE OSTI2023

National Center for Airborne Laser Mapping (NCALM) LiDAR, Imagery, and DEM data from five NGEE Arctic Sites, Seward Peninsula, Alaska, August 2021

From August 8 through August 16 of 2021, airborne remote sensing data was collected by the National Center for Airborne Laser Mapping (NCALM) in collaboration with NGEE Arctic scientists. Data was collected around five NGEE Arctic study sites on the Seward Peninsula of Alaska: Teller mm 27, Teller mm 47, Kougarok mm 64, Kougarok mm 86, and Council mm 71. A Robinson R44 II helicopter with a RIEGL VQ-580 II airborne laser scanner was used to collect the LiDAR point cloud data for each study site. A Phase One iXM-RS100F camera was integrated with the Riegl sensor to collect RGB imagery. This data package contains LiDAR point clouds (.las), RGB imagery (tif), 1 m or 50 cm Digital Elevation Models (.tif) generated from the LiDAR data, and shapefiles of the .las tiling system for each site (.shp). Two supplemental documents are also included in the package: 1) a report describing data collection details, GNSS corrections, and processing steps and 2) a document describing the LiDAR Classification used (.pdf). This survey was conducted towards the end of the summer on the Seward Peninsula, and can be paired with data collected in April of 2022 during the snow-on campaign "National Center for Airborne Laser Mapping (NCALM) LiDAR and DEM data from two NGEE Arctic Sites, Seward Peninsula, Alaska, Winter 2022" (Singhania et.al, 2023) (NGA314). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Characterization of promoter elements of isoprene‐responsive genes and the ability of isoprene to bind START domain transcription factors

Abstract Isoprene has recently been proposed to be a signaling molecule that can enhance tolerance of both biotic and abiotic stress. Not all plants make isoprene, but all plants tested to date respond to isoprene. We hypothesized that isoprene interacts with existing signaling pathways rather than requiring novel mechanisms for its effect on plants. We analyzed the cis‐regulatory elements (CREs) in promoters of isoprene‐responsive genes and the corresponding transcription factors binding these promoter elements to obtain clues about the transcription factors and other proteins involved in isoprene signaling. Promoter regions of isoprene‐responsive genes were characterized using the Arabidopsis cis‐regulatory element database. CREs bind ARR1, Dof, DPBF, bHLH112, GATA factors, GT‐1, MYB, and WRKY transcription factors, and light‐responsive elements were overrepresented in promoters of isoprene‐responsive genes; CBF‐, HSF‐, WUS‐binding motifs were underrepresented. Transcription factors corresponding to CREs overrepresented in promoters of isoprene‐responsive genes were mainly those important for stress responses: drought‐, salt/osmotic‐, oxidative‐, herbivory/wounding and pathogen‐stress. More than half of the isoprene‐responsive genes contained at least one binding site for TFs of the class IV (homeodomain leucine zipper) HD‐ZIP family, such as GL2, ATML1, PDF2, HDG11, ATHB17. While the HD‐zipper‐loop‐zipper (ZLZ) domain binds to the L1 box of the promoter region, a special domain called the steroidogenic acute regulatory protein‐related lipid transfer, or START domain, can bind ligands such as fatty acids (e.g., linolenic and linoleic acid). We tested whether isoprene might bind in such a START domain. Molecular simulations and modeling to test interactions between isoprene and a class IV HD‐ZIP family START‐domain‐containing protein were carried out. Without membrane penetration by the HDG11 START domain, isoprene within the lipid bilayer was inaccessible to this domain, preventing protein interactions with membrane bound isoprene. The cross‐talk between isoprene‐mediated signaling and other growth regulator and stress signaling pathways, in terms of common CREs and transcription factors could enhance the stability of the isoprene emission trait when it evolves in a plant but so far it has not been possible to say what how isoprene is sensed to initiate signaling responses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Detection of a Space Capsule Entering Earth’s Atmosphere with Distributed Acoustic Sensing (DAS)

On 24 September 2023, the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer sample return capsule (SRC) entered Earth’s atmosphere after successfully collecting samples from an asteroid. The known trajectory and timing of this return provided a rare opportunity to strategically instrument sites to record geophysical signals produced by the capsule because it travelled at hypersonic speeds through the atmosphere. For this work, we deployed two distributed acoustic sensing (DAS) interrogators to sample over 12 km of surface-draped fiber-optic cables, as well as six collocated seismometer-infrasound sensor pairs, spread across two sites near Eureka, Nevada. This campaign-style rapid deployment is the first reported recording of an SRC re-entry with any distributed fiber-optic sensing technology. The DAS interrogators recorded an impulsive arrival with an extended coda which had features that were similar to recordings from both the seismometers and infrasound sensors. While the signal-to-noise ratio of the DAS data was lower than the seismic-infrasound data, the extremely dense spacing of fiber-optic sensors allowed for more phases to be clearly distinguished and the visualization of the continuous transformation of the wavefront as it impacted the ground. Unexpectedly, the DAS recordings contain less low-frequency content than is present in both the seismic and infrasound data. The deployment conditions strongly affected the recorded DAS data; in particular, we observed that fiber selection and placement exert strong controls on data quality.

58 GEOSCIENCES↗
DOE OSTI2021

Imposing equilibrium on experimental 3-D stress fields using Hodge decomposition and FFT-based optimization

Here, we present a methodology to impose micromechanical constraints, i.e. stress equilibrium at grain and sub-grain scale, to an arbitrary (non-equilibrated) voxelized stress field obtained, for example, by means of synchrotron X-ray diffraction techniques. The method consists in finding the equilibrated stress field closest (in L 2 -norm sense) to the measured non-equilibrated stress field, via the solution of an optimization problem. The extraction of the divergence-free (equilibrated) part of a general (non-equilibrated) field is performed using the Hodge decomposition of a symmetric matrix field, which is the generalization of the Helmholtz decomposition of a vector field into the sum of an irrotational field and a solenoidal field. The combination of: a) the Euler–Lagrange equations that solve the optimization problem, and b) the Hodge decomposition, gives a differential expression that contains the bi-harmonic operator and two times the curl operator acting on the experimental stress field. These high-order derivatives can be efficiently performed in Fourier space. The method is applied to filter the non-equilibrated parts of a synthetic piecewise constant stress fields with a known ground truth, and stress fields in Gum Metal, a beta-Ti-based alloy measured in-situ using Diffraction Contrast Tomography (DCT). In both cases, the largest corrections were obtained near grain boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Review of Existing Test Methods for Occupancy Sensors

One of the key new features of connected lighting systems (CLS) is their ability to collect data from various types of integral sensors and share that data with other lighting or building systems. Occupancy and vacancy sensors have been widely adopted as an energy-saving strategy in buildings, yet published test methods for reproducibly characterizing their performance remain few and limited in their sophistication. As a result, it has been difficult to predict the performance of such sensors in a specific application, and in practice, they frequently do not meet energy-savings expectations. Occupants at times remove or otherwise bypass occupancy sensors that hinder their work or otherwise do not perform as expected, thereby compromising the sensors’ potential to reduce energy consumption. Poor performance can result from multiple causes – ranging from fundamental limitations of the sensor technology, to misconfiguration, to poor placement in the room or space. Innovative occupancy sensors, some of them combining multiple sensing technologies (i.e., multimodal), have come on the market over the years, with claims of improved performance compared to their predecessors. However, in practice, their performance has neither differed enough from the performance of previous products to necessitate a test method that facilitated comparison between them, nor has it led to high deployment or high user satisfaction in human-occupied spaces with persistent presence. While the performance of both common and novel occupancy sensors has been the subject of many published research articles, the test methods that have been employed for them typically have been loosely described and have incorporated custom equipment or techniques that render them difficult to reproduce, or have been limited in their ability to fairly characterize devices that utilize varying sensor technology. The lack of a fully described, technology-agnostic test method that yields reproducible results across different implementations has been a barrier to the commercial success of new occupancy-sensor products, as users and specifiers who have been disappointed with previous products are often unwilling to take a chance with new ones. Motivated by a desire to fairly characterize new technologies that continue to enter the market and claim not only improved occupancy detection but, in some cases, additional capabilities (e.g., the ability to measure traffic or discern between different object types), this report presents the results of a literature review of recently published fully described test methods for characterizing occupancy-sensor performance, as well as research articles containing ad-hoc test methods. The review also identifies and consolidates test conditions for characterizing sensor performance in indoor spaces and identifies apparent test method gaps that need to be filled in order to evaluate emerging technologies and products. The identified test-method conditions are intended to enable the development of a future technology-agnostic test method that facilitates occupancy-sensor performance characterization more-accurately representing performance in buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Optical recognition of constructs using hyperspectral imaging and detection (ORCHID)

Abstract Challenges to deep sample imaging have necessitated the development of special techniques such as spatially offset optical spectroscopy to collect signals that have travelled through several layers of tissue. However, these techniques provide only spectral information in one dimension (i.e., depth). Here, we describe a general and practical method, referred to as Optical Recognition of Constructs Using Hyperspectral Imaging and Detection (ORCHID). The sensing strategy integrates (1) the spatial offset detection concept by computationally binning 2D optical data associated with digital offsets based on selected radial pixel distances from the excitation source; (2) hyperspectral imaging using tunable filter; and (3) digital image binding and collation. ORCHID is a versatile modality that is designed to collect optical signals deep inside samples across three spatial (X, Y, Z) as well as spectral dimensions. The ORCHID method is applicable to various optical techniques that exhibit narrow-band structures, from Raman scattering to quantum dot luminescence. Samples containing surface-enhanced Raman scattering (SERS)-active gold nanostar probes and quantum dots embedded in gel were used to show a proof of principle for the ORCHID concept. The resulting hyperspectral data cube is shown to spatially locate target emitting nanoparticle volumes and provide spectral information for in-depth 3D imaging.

47 OTHER INSTRUMENTATION↗