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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Synopsis of NREL's Automated Mobility District (AMD) Research Program and Associated Publications

An automated mobility district (AMD) envisions a system of integrated mobility options that serves major activity centers such as campuses, central business districts, and large medical facilities. The National Renewable Energy Laboratory (NREL) has been investigating the implementation prospects for fully automated passenger transport systems that are deployed to operate within dense urban settings. This document provides a synopsis of findings revealed over the last three phases of work, which have yielded insights into the creation and management of AMDs anticipated to use automated vehicle (AV) technology over the next decade. Phase I and Phase II tracked the deployment and lessons learned from 10 early-stage demonstrations of automated shuttle deployments, and their associated insights into the challenges for automated driving systems to achieve safe operations within district-scale deployments. Phase III began in-depth investigations of critical subsystem components, as automation, electrification, and on-demand service continue to converge within initial AMD operations. These directed studies focus on elements of electrification, curbfront/station management, the role of infrastructure sensing, and overall integration of AMD safety management in central, simultaneous coordination of multiple AMD fleets. Future research in AMDs includes systems engineering methodology (more frequently referred to as "digital twins") for planning, design, testing, and ongoing operation of AMDs; location (or co-location) of management functions; and human supervision and passenger communications for safety and security in unattended vehicles. The synopsis references the foundational research products (papers and presentations) that have been published through conference proceedings, journal articles, and NREL reports.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Parameterization of arctic hydrometeor physics using new precipitation measurement technologies: Final Report

Predictions of precipitation are highly sensitive to the accuracy of parameterized growth and sedimentation processes, especially in remote regions such as the Arctic where observations are scarce. The goal of this study was to combine measurements of meteorological conditions and retrievals from passive and active remote sensors to provide refined parameterizations of precipitation properties and processes with a particular focus on the Arctic. To accomplish the project goals, new instrumentation was used from the Oliktok Point Mobile Facility and the Utqiagvik (Barrow) North Slope of Alaska ARM site focusing in particular on Multi-Angle Snowflake Camera (MASC) data. The MASC is the first device able to automatically photograph precipitation particles in free-fall from multiple angles while simultaneously measuring their fall speed. The MASC installed at the ARM Oliktok Point and Utqiagvik facilities was used to examine the nature of Arctic precipitation, taking particular advantage of the unique suite of precipitation, meteorological, and remote sensing instrumentation that is available at the high latitude sites. Combined with radiometer data we were able to explore the relationship between precipitation particle characteristics and the clouds where the snow is created. Ground-based wind measurements provided detailed data on turbulence. Further theoretical work explored the physical mechanisms controlling precipitation size distributions, the physics determining hydrometeor fallspeed, and the existence of general solutions to the Navier-Stokes equations for falling particles. Outreach work introduced hydrometeor classification to classrooms across the United States.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Data Interfaces for Automated Vehicle Services - A Municipality Perspective

As Automated Vehicle (AV) services proliferate, data sharing between AV operators and municipal agents is assuming greater importance. Information on the dynamic nature of the road system such as incidents to avoid, weather hazards (such as flooding), construction and detours, as well as active safety concerns (e.g. - riots) is important for AV operators. Such information cannot be directly sensed from a vehicle's sensor array, but instead must be communicated in a timely and trustworthy channel. Municipalities are interested in pushing this information to AV operators to support emergency response efforts, reduce traffic in construction zones, and generally improve operation of the system. Similarly, information on vehicle safety such as disengagements, as well as critical information on the use of roadway system (trips, origin and destination patterns) are important performance factors for municipalities to understand utilization and plan for appropriate infrastructure. As mobility shifts to on-demand options, the need for safe and coordinated pick-up and drop-off zones will increase (potentially reducing parking needs). For all of these reasons, communication flows between AV operators and municipalities are becoming increasingly important. This paper investigates the functions, emerging practices and protocols for sharing of such critical data, and identifies gaps in and challenges in existing practices. Additionally, case studies are used to highlight the impacts of data sharing between AV operators and municipalities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Fully Automated Profile-based Calibration Strategy for Airborne and Terrestrial Mobile LiDAR Systems with Spinning Multi-beam Laser Units

LiDAR-based mobile mapping systems (MMS) are rapidly gaining popularity for a multitude of applications due to their ability to provide complete and accurate 3D point clouds for any and every scene of interest. However, an accurate calibration technique for such systems is needed in order to unleash their full potential. In this paper, we propose a fully automated profile-based strategy for the calibration of LiDAR-based MMS. The proposed technique is validated by comparing its accuracy against the expected point positioning accuracy for the point cloud based on the used sensors’ specifications. The proposed strategy was seen to reduce the misalignment between different tracks from approximately 2 to 3 m before calibration down to less than 2 cm after calibration for airborne as well as terrestrial mobile LiDAR mapping systems. In other words, the proposed calibration strategy can converge to correct estimates of mounting parameters, even in cases where the initial estimates are significantly different from the true values. Furthermore, the results from the proposed strategy are also verified by comparing them to those from an existing manually-assisted feature-based calibration strategy. The major contribution of the proposed strategy is its ability to conduct the calibration of airborne and wheel-based mobile systems without any requirement for specially designed targets or features in the surrounding environment. The above claims are validated using experimental results conducted for three different MMS – two airborne and one terrestrial – with one or more LiDAR unit.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Hyperspectral Infrared Observations of Arctic Snow, Sea Ice, and Non-Frozen Ocean from the RV Polarstern during the MOSAiC Expedition October 2019 to September 2020

This study highlights hyperspectral infrared observations from the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) collected as part of the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) deployment on the icebreaker RV Polarstern during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The ARM M-AERI directly measures the infrared radiance emission spectrum between 520 cm –1 and 3000 cm –1 (19.2–3.3 μm) at 0.5 cm –1 spectral resolution. These ship-based observations provide a valuable set of radiance data for the modeling of snow/ice infrared emission as well as validation data for the assessment of satellite soundings. Remote sensing using hyperspectral infrared observations provides valuable information on sea surface properties (skin temperature and infrared emissivity), near-surface air temperature, and temperature lapse rate in the lowest kilometer. Comparison of the M-AERI observations with those from the DOE ARM meteorological tower and downlooking infrared thermometer are generally in good agreement with some notable differences. Operational satellite soundings from the NOAA-20 satellite were also assessed using ARM radiosondes launched from the RV Polarstern and measurements of the infrared snow surface emission from the M-AERI showing reasonable agreement.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing

Abstract As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components. Here, we introduce low-power organic optoelectronic memristors with synergistic optical and mV-level electrical tunable operation for a dynamic “control-on-demand” architecture. Integrating signal sensing, featuring, and processing within the same memristors enables the realization of each in-sensor analogue reservoir computing module, and minimizes circuit integration complexity. The system achieves 97.15% fingerprint recognition accuracy while maintaining a minimal reservoir size and ultra-low energy consumption. Furthermore, we leverage wafer-scale solution techniques and flexible substrates for optimal memristor fabrication. By centralizing core functionalities on the same in-sensor platform, we propose a resilient and adaptable framework for energy-efficient and economical edge computing.

Optics↗
DOE OSTI2022

Harmonizing solar induced fluorescence across spatial scales, instruments, and extraction methods using proximal and airborne remote sensing: A multi-scale study in a soybean field

Solar-induced chlorophyll fluorescence (SIF) has been widely used to track vegetation photosynthesis at different scales ranging from in-situ measurements to satellite products. Airborne platforms sample SIF data at a spatial scale intermediate between in-situ and satellite, matching that of ground measurement (e.g. flux tower footprints and other field sampling), enabling us to explore causes of SIF variation and validate satellite-based SIF products. However, harmonizing SIF across sensors and platforms (correcting for systematic errors to yield a consistent, comparable SIF product) is challenging because SIF can be retrieved in different absorption windows, with different instruments and methods complicating the comparison between different observational levels (i.e., ground, airborne, satellites) and between sites equipped with different instruments with varying optical properties (spectral resolution and sampling intervals, spatial resolution). Additionally, the spatial and temporal variability of atmospheric properties can influence the retrieval of the weak SIF signal. Because of these complications, direct comparisons of airborne and ground SIF across scales are rarely attempted. Here, in this study, we combined airborne SIF data with simultaneous ‘ground truth’ data collected by stationary and mobile platforms in a soybean field in Nebraska, USA. In this effort, we tested several SIF extraction methods, including Fraunhofer Line Discrimination (FLD), improved Fraunhofer Line Discrimination (iFLD), Spectral Fitting Method (SFM), SpecFit, and a Singular Vector Decomposition (SVD) method. The SpecFit method was sensitive to the 715–740 nm water bands and removing the water bands in the fitting process yielded better agreement between the airborne and ground SIF spectra. Accurate estimation of the ground level downwelling irradiance obtained by ground measurements over a calibration target improved agreement between airborne and ground SIF retrievals at the O 2 A band, and allowed us to derive a SIF dataset with improved agreement across platforms and sampling scales. This experimental approach provided a method for generating comparable SIF signals across instruments, methods and platforms, which is critical to understanding the SIF-GPP relationship at different scales and to cross-validate the diversity of platforms used for satellite products calibration and validation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effectiveness of Deep Learning Trained on SynthCity Data for Urban Point-Cloud Classification

3D object recognition is one of the most popular areas of study in computer vision. Many of the more recent algorithms focus on indoor point clouds, classifying 3D geometric objects, and segmenting outdoor 3D scenes. One of the challenges of the classification pipeline is finding adequate and accurate training data. Hence, this article seeks to evaluate the accuracy of a synthetically generated data set called SynthCity, tested on two mobile laser-scan data sets. Varying levels of noise were applied to the training data to reflect varying levels of noise in different scanners. The chosen deep-learning algorithm was Kernel Point Convolution, a convolutional neural network that uses kernel points in Euclidean space for convolution weights.

Geology↗
DOE OSTI2024

Ambipolar Transport in Polycrystalline GeSn Transistors for Complementary Metal-Oxide-Semiconductor Applications

Group-IV alloy GeSn is a promising material for electronic and optoelectronic applications due to its compatibility with both Si substrates and established Si fabrication processes. This study focuses on polycrystalline GeSn (10% Sn), which offers a cost-effective, large-area, and versatile alternative to epitaxial GeSn. We demonstrate ambipolar transport behavior in polycrystalline GeSn thin film transistors, achieving electron and hole field-effect mobilities reaching up to 0.05 cm 2 /Vs and 2.05 cm 2 /Vs, respectively. Through temperature-dependent analysis, we elucidate the underlying mechanism of this phenomenon, which we attribute to quantum tunneling between the Schottky barrier contact and the channel, as well as potential barriers between the grain boundaries of this polycrystalline film, thereby advancing the understanding of polycrystalline GeSn's electrical properties. Furthermore, this work highlights the potential of ambipolar transport as a technique to employ towards the development of GeSn complementary metal-oxide-semiconductor field-effect transistors, promising to simplify and reduce the cost of GeSn manufacturing processes for edge computing and sensing applications.

42 ENGINEERING↗
DOE OSTI2024

Investigating the Influence of River Geomorphology on Human Presence Using Night Light Data: A Case Study in the Indus Basin

Human settlements have historically thrived near rivers due to enhanced navigation and trade, and the availability of water supply and resources. The use of night light data, representing economic activities, provides a novel approach to studying the interactions between human activity and rivers over time. Here, we use the Defense Meteorological Satellite Program (DMSP) stable night light data from 2000 to 2013 as a proxy for human presence and activities to quantify the statistical relationships between night light presence and intensity in the Indus Basin, Asia. We test how these data are affected by proximity to trunk channels and by channel type (single/multi-thread) in the study area. We find that night light presence is enhanced by 26% within a 0 to 5 km proximity range of the Indus River and its tributaries, relative to the basin as a whole. We interpret this to represent increased human presence and activity within this zone. However, the mean intensity is lower near the river and higher away from the river, signifying denser settlements, such as towns and cities, which are preferentially located away from the Indus and its tributaries. Moreover, the enhancement of lit pixels signifying human presence and activities is increased by 18% near single-thread sections of the Indus River, compared to segments of the Indus displaying multi-thread morphologies. We suggest that this is due to the enhanced stability of single-threaded channels, relative to mobile multi-threaded channel reaches. This study demonstrates how night lights are an important tool in studying the relationship between human presence and river dynamics in large catchments such as the Indus, and we suggest that these data will have an important role in assessing differential flood spatial and social vulnerability at a regional scale.

Environmental Sciences & Ecology↗
DOE OSTI2022

Technical Characterization and Benefit Evaluation of 5G-Enabled Grid Data Transport and Applications

This report summarizes the Year 1 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research Program. 5G is a breakthrough technology that enables a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for a clean energy economy and grid modernization. In collaboration with PNNL’s Advanced Wireless Communication team and Center for Advanced Technology Evaluation team, the project team has been evaluating the system performance of 5G testbeds in the PNNL 5G Innovation Studio, and has formulated a co-simulation test case of power system transmission, distribution, and communication (T&D&C) networks considering 5G technology and high penetration of distributed energy resources. The methodology developed in the 5G Energy FRAME project can be customized to fit different future grid scenarios to evaluate multiple (dynamic) configurations (computing, sensing, communication, environment) for different stakeholders. In summary, our main technical highlights in project Year 1 are as follows: 1) Technical characterization of 5G standalone architectures, 2) Formulation of co-simulation test case of T&D&C networks embedded with 5G, 3) Initial benefit evaluation of 5G communication platform for grid use cases, and 4) Additional extended discussions on edge computing, artificial intelligence and machine learning, and high-performance computing and cloud computing adoptions. In addition, a collection of system performance data is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

A Semiconducting Two‐Dimensional Polymer as an Organic Electrochemical Transistor Active Layer

Abstract Organic electrochemical transistors (OECTs) are devices with broad potential in bioelectronic sensing, circuits, and neuromorphic hardware. Their unique properties arise from the use of organic mixed ionic/electronic conductors (OMIECs) as the active channel. Typical OMIECs are linear polymers, where defined and controlled microstructure/morphology, and reliable characterization of transport and charging can be elusive. Semiconducting two‐dimensional polymers (2DPs) present a new avenue in OMIEC materials development, enabling electronic transport along with precise control of well‐defined channels ideal for ion transport/intercalation. To this end, a recently reported 2DP, TIIP, is synthesized and patterned at 10 µm resolution as the channel of a transistor. The TIIP films demonstrate textured microstructure and show semiconducting properties with accessible oxidation states. Operating in an aqueous electrolyte, the 2DP‐OECT exhibits a device‐scale hole mobility of 0.05 cm 2 V –1 s –1 and a µ C * figure of merit of 1.75 F cm –1 V –1 s –1 . 2DP OMIECs thus offer new synthetic degrees of freedom to control OECT performance and may enable additional opportunities such as ion selectivity or improved stability through reduced morphological modulation during device operation.

2D-polymer↗
DOE OSTI2024

Molecular shifts in dissolved organic matter along a burn severity continuum for common land cover types in the Pacific Northwest, USA

Increasing wildfire severity is of growing concern in the western United States, with consequences for the production, composition, and mobilization of dissolved organic matter (DOM) from terrestrial to aquatic systems. Our current understanding of wildfire impacted DOM (often termed pyrogenic DOM) composition is largely built from temperature-based studies that can be difficult to extrapolate to field conditions, which are often defined by ‘burn severity’, or the post-wildfire impact observed at a site. Thus, burn severity can encapsulate a broader range of fire and environmental conditions not exclusive to temperature. Biogeochemical studies that describe DOM along burn severity continuums remain limited but are needed to better link DOM composition with field conditions post-fire. Here, in this study, we addressed this need with an experimental open air burn simulation that generated chars from vegetation representative of major land cover types in the western United States. The chars were leached to simulate DOM mobilization potential. The DOM composition was characterized by ultra-high resolution mass spectrometry (HR-MS) and UV/VIS absorbance and fluorescence. Our results indicated that the shifts of DOM production and composition along a burn-severity gradient depends on the land cover type that was burned, with the degree of change dependent on the composition of the starting parent vegetation material. Fluorescence signatures indicated a strong convergence across land cover types to more aromatic DOM with increasing severity, while HR-MS indicated an increase in the production of aromatic nitrogen containing DOM with increasing severity. Results from this study enhance our ability to describe DOM composition in a framework that can be more directly related with field and remote-sensing based metrics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Revealing the Full Potential of Glycolated Mixed Ionic-Electronic Semiconductors – Symmetric Monomer Polymerization to Boost Electrochemical Transistor Performance

Organic electrochemical transistors (OECTs) enable the transduction of ionic signals into electronic outputs, positioning them as ideal candidates for next-generation sensing and (bio)signal processing applications. Recent years have witnessed the development of various OECT channel materials, affording insights into structural fine-tuning to achieve optimal performance and/or stability. However, homocouplings, commonly present in alternating conjugated polymers, have largely been overlooked. This study investigates the effect of homocoupling on OECT materials by employing two synthesis methods – standard Stille polymerization and an alternative symmetric approach – to create the p-type enhancement-mode benchmark polymer pgBTTT. The impact of homocoupling, and its absence, is studied by comparing the bulk properties of the two polymers and evaluating their respective OECT metrics. The new, homocoupling-free polymer exhibits a notably improved OECT performance ( μC *), mainly due to an average 3-fold increase in electronic mobility (μ).

defects↗
DOE OSTI2023

Particle Flux Measurements during TRACER (TRACER PFM) (Field Campaign Report)

The purpose of this campaign was to deploy an instrument payload collocated with a suite of in situ and remote-sensing aerosol instruments at the urban site at the La Porte, Texas Municipal Airport during the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Tracking Aerosol Convection Interactions Experiment (TRACER) in Houston, Texas. The payload was designed to characterize the physicochemical properties, mixing state, and size-resolved vertical fluxes of aerosols. Deployed aerosol instruments associated with the flux measurements included three condensation particle counters (CPCs) with different lower cutoff diameters ( D > 2.5 nm, D > 10 nm, and D > 40 nm), a single-particle soot photometer (SP2) measuring refractory black carbon, and a portable optical particle spectrometer (POPS) measuring the optical size distribution (~180 nm < D < ~5000 nm). A 10-m flux tower hosted a sonic anemometer (SONIC) for vertical velocity measurements. In addition, a humidified tandem differential mobility analyzer (HTDMA) was deployed to measure the growth factors and hygroscopicity parameter of 15-50 nm-sized particles in order to constrain the composition of compounds responsible for modal aerosol growth during new particle formation/growth events. Finally, a radial differential mobility analyzer (RDMA) was deployed to extend the size distribution measurement to 5 nm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Reinforced double-threaded slide-ring networks for accelerated hydrogel discovery and 3D printing

Traditionally, slide-ring gels are stretchable but soft as a result of an elasticity-stretchability trade-off. Herein, we introduce a new approach to breaking this trade-off and creating reinforced slide-ring networks with mobile crosslinkers. Our approach involves the construction of a polyethylene glycol double-threaded γ-cyclodextrin-based pro-slide-ring crosslinker that serves as a modular component for 3D printing and copolymerization. The resulting crystalline-domain-reinforced slide-ring hydrogels, or CrysDoS-gels, exhibit both high elasticity and high stretchability. The modular synthesis allows for high-throughput synthesis of CrysDoS-gels, generating a large amount of data for structure-property analysis. Here, by employing data science techniques, such as machine learning and linear regression, not only were we able to identify which chemical components influence the mechanical properties of CrysDoS-gels, but this analysis also aided in the discovery of better-performing CrysDoS-gels. Finally, we demonstrate the potential application of the newly discovered CrysDoS-gels as sensing devices by 3D printing them as stress sensors with high sensitivity and a broad detection range.

3D-printing↗
DOE OSTI2022

2021 Consequence Management Hotline Drill After Action Report

In March 2021, a functional area drill was held at the Remote Sensing Laboratory–Nellis that focused on using CBRNResponder and the Digital Field Monitoring (DFM) tablets for sample hotline operations and the new paper Sample Control Forms (SCFs) for sample collection. Participants included staff trained and billeted as sample control specialists and Consequence Management Response Team (CMRT) field monitoring personnel. Teams were able to successfully gather and transfer samples to the sample control hotline staff through the manual process, though there were several noted areas for improvement. In July and October 2021, two additional functional area drills were held at Sandia National Laboratories that focused on field sample collection and custody transfer at the sample control hotline for the Consequence Management (CM) Radiological Assistance Program (RAP) program. The overarching goal of the drills was to evaluate the current CM process for sample collection, sample drop off, and sample control using the CBRNResponder mobile and web-based applications. The July 2021 drill had an additional focus to have a subset of samples analyzed by the local analytical laboratory, Radiation Protection Sample Diagnostics (RPSD) laboratory, to evaluate the Laboratory Access portal on CBRNResponder. All three drills were able to accomplish their objectives however, there were several issues noted (Observations: 25 Urgent, 29 Important, and 22 Improvement Opportunities). The observations were prioritized according to their impact on the mission as well as categorized to align with the programmatic functional area required to address the issue. This report provides additional detail on each observation for skillset/program leads and software developers to consider for future improvement or mandatory efforts.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

Ka-Band ARM Zenith Radar (KAZR) Active Remote Sensing of Clouds (ARSCL) CloudSat Calibration (KAZRARSCL-CLOUDSAT) (Value-Added Product Report)

The Ka-band ARM Zenith Radar Active Remote Sensing of CLouds CloudSat-aligned (KAZRARSCL-CLOUDSAT) Value-Added Product (VAP) applies satellite-based reflectivity calibrations to KAZRARSCL data sets. The Atmospheric Radiation Measurement (ARM) user facility has primarily used radar subsystem calibration monitoring to track cloud radar reflectivity drift over time, since reliable external calibration sources or other absolute references (such as corner reflectors) have historically been unavailable or impracticable. A study by Kollias et al. (2019) examined cloud reflectivity profiles observed with a well-characterized spaceborne downward-pointing millimeter cloud radar, operating as part of NASA’s CloudSat satellite mission (Tanelli et al. 2008). The Kollias team derived monthly statistical reflectivity offsets between CloudSat and the various generations of ARM cloud radars (millimeter wavelength cloud radar [MMCR], W-Band ARM Cloud Radar [WACR[, and Ka-band ARM Zenith Radar [KAZR]) for many, but not all, months at most fixed and mobile ARM sites over the period 2007-2017. These offsets, when available, are applied to the existing KAZRARSCL VAP products using the KAZRARSCL-CLOUDSAT VAP.

54 ENVIRONMENTAL SCIENCES↗