Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Light Extraction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Exciton-Phonon Coupling and Carrier Relaxation in PbS Quantum Dots: The Case of Carboxylate Ligands

Some ligand-nanocrystal combinations exhibit rapid cooling of highly excited electronic states while other nanocrystal/shell combinations do not appear to have this effect. There remains a need to identify the distinguishing properties of ligand-nanocrystal interactions that avoid such rapid relaxation processes to guide the design of colloidal quantum dots (QDs) that take advantage of multiple exciton generation or hot-carrier extraction processes. Here, we use mid-infrared transient absorption spectroscopy to investigate the influence that carboxylate ligands with distinct excited state surface chemistries has on exciton-phonon coupling and hot exciton relaxation in PbS quantum dot (QD) films. Our findings reveal that despite significant differences in the excited state surface chemistry of oleate (OA) and iodide/mercaptopropionic acid (I-/MPA) ligands, PbS QD films passivated with both ligand types exhibit identical electronic relaxation rates and exciton-phonon coupling strengths within experimental precision. The data suggest that the inorganic lattice is the principal source of exciton-phonon coupling that influences hot exciton relaxation, rather than the vibronic modes of carboxylate ligands. The size-dependent nature of the exciton-phonon coupling strength is consistent with the localization of charge on the QD surfaces, which enhances the mixing of electronic and nuclear coordinates particularly when the electronic states are more quantum confined in smaller nanocrystals.

14 SOLAR ENERGY↗
NASA NTRS2013

The Antarctic Search for Meteorites: A Model for Deep Space Exploration

In an era of shrinking buying power and reduced flight opportunities, NASA must extract the greatest possible value from all sources of insight into the future of human space exploration. Antarctica is one such source. The history of Antarctic exploration has many political and technical parallels with the development of space, and Antarctica's remoteness and harsh climate make it an excellent proxy for space (e.g., [1,2]). Links between exploration of space and of the Antarctic date back to the International Geophysical Year of 1957-1958, which saw both the launch of Sputnik 1 and the establishment of a station at the South Pole. The Antarctic Search for Meteorites (ANSMET) is an annual expedition to the south polar plateau to collect meteorites. Although its intent is not to simulate a space mission, the handful of astronauts who have participated in ANSMET agree that it is very similar to a long-duration space flight. Independently, NASA and other space agencies have simulated deep space exploration missions in "analog" activities at remote field sites on Earth (e.g., [3]). These include NASA Extreme Environment Mission Operations (NEEMO) [4,5], Desert Research And Technology Studies (Desert RATS) [6,7], and the Pavilion Lake Research Project (PLRP or simply Pavilion Lake) [8]. This report focuses on NEEMO, Desert RATS, and PLRP because of the author's firsthand experience with them. Other noteworthy analogs, such as the arctic Haughton Mars Project and the European Space Agency's underground Cooperative Adventure for Valuing and Exercising human behavior and performance Skills (CAVES), are not treated here. NASA analogs often include fully staffed control centers, astronauts serving as crew, and realistic mission timelines lasting one to two weeks. Analogs have provided key insights into system architectures and operational concepts for the future human exploration of deep space. They have pioneered techniques for human communication with significant speed-of-light delays, for conducting spacewalks on natural objects with negligible surface gravity, and for empowering exploration crews to work with reduced dependence on a ground control center. They have field-tested dozens of emerging technologies including spacewalking tools and full-scale prototype vehicles and habitats. They have provided valuable experience for astronauts preparing for their first space flight, and for flown crewmembers who will take command roles on later flights. Some analogs, especially PLRP, have connected observers in the field with science teams in remotely located control centers to produce high-quality, publishable scientific results. The analogs have accomplished all of this at a tiny fraction of the cost of an actual space flight. This report treats ANSMET as space flight analog. The chapter following this introduction describes ANSMET in depth. The report then presents data on logistics and crew considerations that may be useful for developers of future human space exploration missions. It offers detailed comparisons between ANSMET and past, present, and future space flights on the Space Shuttle, the International Space Station (ISS), and a proposed Mars mission. Those comparisons are intended to complement the work of Eppler [2], who compares ANSMET to the Apollo moon flights. This report also compares ANSMET with the Desert RATS, NEEMO, and PLRP analogs. It then presents observations and makes recommendations related to ANSMET's value as a simulated space mission. The report ends with a short conclusion. The remainder of this introductory chapter provides background material to help readers interpret the rest of the report. It gives brief overviews of Space Shuttle and ISS missions along with information on a notional future human flight to Mars. It also presents the general features of three of NASA's space flight "analog" projects. With those points of reference in place, the chapter concludes with an overview of ANSMET.

Love, Stanley G.↗
DOE OSTI2026

Machine Learning Framework for Characterizing Processing–Structure Relationship in Block Copolymer Thin Films

The morphology of block copolymers (BCPs) critically influences material properties and applications. This work introduces a machine learning (ML)-enabled, high-throughput framework for analyzing grazing incidence small-angle X-ray scattering (GISAXS) data and atomic force microscopy (AFM) images to characterize BCP thin film morphology. A convolutional neural network was trained to classify AFM images by surface features, achieving 97% testing accuracy. Classified images were then analyzed to extract 2D grain size measurements from the samples in a high-throughput manner. ML models were trained to predict domain orientation based on processing parameters such as solvent ratio, additive type, and additive ratio. GISAXS-based properties were predicted with strong performances (R 2 > 0.75), while AFM-based property predictions were less accurate (R 2 < 0.60), likely due to the localized nature of AFM measurements compared to the bulk information captured by GISAXS. Beyond model performance, interpretability was addressed using SHapley Additive exPlanations (SHAP). SHAP analysis revealed that the additive ratio had the largest impact on morphological predictions, where additive provides the BCP chains with increased volume to rearrange into thermodynamically favorable morphologies. This interpretability helps validate model predictions and offers insight into parameter importance. Altogether, the presented framework combining high-throughput characterization and interpretable ML offers an approach to exploring and optimizing BCP thin film morphology across a broad processing landscape.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Eureka! Aerogel capture of meteoroids in space

Light gas gun studies have shown that 6 km/s solid mineral and glass test particles can be successively captured in 0.05 g cm(exp -3) aerogel without severe heating or fragmentation. In spite of this work, there has been uncertainty in the performance of aerogel for hypervelocity capture of real meteoroids. Natural impacts differ from simulations in that the particles are likely to be structurally weak and they typically impact at higher velocity that can be simulated in the laboratory. We are fortunate now to have had two successful capture experiments using aerogel exposed in space. These experiments provide fundamental data for the assessment of the value of silica aerogel for capture of hypervelocity meteoroids from spacecraft. The first experiment used 0.02 g cm(exp -3) aerogel flown on the lid of a Shuttle Get Away Special canister. During its 9 day exposure, the 0.165 m(exp 2) of aerogel in this Sample Return Experiment (SRE) captured two long 'carrot-shaped' tracks and one highly fractured bowl shaped 'crater'. The second collection was with 0.04 m(exp 2) of 0.05 g cm(exp -3) aerogel exposed on ESA's Eureca freeflying spacecraft that was exposed for 11 months before recovery by the Shuttle. The Eureca aerogel exposure consisted of four 10x10 cm module trays that were part of the TiCCE meteoroid collector built by the University of Kent at Canterbury. To date we have found ten 'carrot-shaped' tracks and two 'craters' on this experiment. The longest tracks in both exposures are over 2 mm long. Two of the TiCCE modules had a 0.1 micron Al film suspended a millimeter above the aerogel. On these modules several of the projectiles fragmented during passage through the film producing fields of carrot shaped tracks from the resulting miniature 'meteor' shower. Most of the tracks in these showers have observable particles at their ends. We have extracted one of the carrot track meteoroids and mounted it in epoxy for sectioning. So far the examination of these 14 impacts suggests that low density aerogel is a magic and highly effective media for intact capture of hypervelocity particles in space.

Brownlee, D. E.↗
NASA NTRSDate not supplied

Global 3D Data Visualization and Analysis Platform with Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera, Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

Maps↗
NASA NTRSDate not supplied

Global 3D Data Visualization and Analysis Platform With Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks [1]. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration [2]. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera [3], Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) [5] is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools [5, 7]. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool [8]. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers [5,6]. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

Maps↗
NASA NTRSDate not supplied

Quality Assurance of ISS LIS lightning Data

Optical lighting detection from space has been ongoing since 1995 from the Optical Transient detector (1995-2000), then later by the Lightning Imaging Sensors (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite (1997-2015) and the International Space Station (ISS) (ISS 2017-present). A rapid readout (2 ms) 128x128 pixel CCD (Charge-coupled Device) array detects optical transients from lightning (events) and transmits the observations to ground. Ground processing determines whether individual events are likely due to lightning or noise. Likely lightning events are then grouped into groups, flashes, and areas and their location on the earth are determined. The lightning data are saved in orbit files; each file containing the time, location, and intensity of the lightning events, groups, flashes, and areas detected during one orbit. Even after this processing anomalies may exist in some of the orbits. A manual quality assurance (QA) procedure is performed monthly to assess the data and omit orbits with obvious anomalies from the dataset. These files are not included in the final dataset that has undergone QA. The manual QA was developed during the OTD mission to identify artifacts that made it through ground processing algorithms. The manual QA process was continued for the TRMM and ISS LIS missions. Many anomalies have been identified and software updates now address many of them. However, some anomalies still occur in the processed datasets. The manual QA process examines the data for obvious issues in the lightning files that passed through the processing algorithms. These files are considered anomalous and are not included in the final QA dataset. Some issues that may cause an orbit to be considered anomalous include: obvious noise (excess events that make it through the processing), suspect geolocation, and excessive missing data packets. As an example, one way noise manifests is as “streaks” in lightning climatology plots. These streaks are especially apparent in low lightning rate regions (eg., over oceans). Since there is no method at present to extract these anomalies during processing, orbit files with significant anomalies are identified and removed from the final QA ISS LIS dataset. The final QA dataset can be obtained files from the Global Hydrometeorological Resource Center (GHRC). This presentation will provide examples of the various anomalies and examine how often the various anomalies occur and how much data is lost due to the omission of the anomalous orbits. Comparisons with OTD and TRMM LIS will also be examined.

ISS↗
DOE OSTI2025

Formation and optical properties of indium nanoparticle arrays for deep-UV plasmonics

We utilize a combined computational-experimental approach to examine the influence of indium nanoparticle (NP) array distributions on deep-ultraviolet (UV) plasmon resonances. For photon energies < 5.7 eV, analysis of ellipsometric spectra reveals an increase in silicon reflectance induced by indium NP arrays on silicon. For various energies in the range 5.7–7.0 eV, a decrease in reflectance is induced by the NP arrays. Similar trends in reflectance are predicted from finite-difference time-domain (FDTD) simulations using NP size distributions extracted from atomic-force micrographs as input. In addition, in the energy range of 7.4–9.2 eV, the FDTD simulations reveal reflectance minima, characteristic of localized surface plasmon resonances. Here, electron energy-loss spectroscopy collected from individual indium NPs reveals the presence of LSPR at ≈ 8 eV, further supporting the promise of indium NP arrays on silicon for deep-UV plasmonics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ultraselective sequestration of Li + and Mg 2+ from brines via a reusable polyoxoniobate-based ion sponge

Lithium (Li) and magnesium (Mg) are designated as critical mineral materials (CMM) due to their essential roles in clean energy technologies. However, extracting high-purity Li + from brine remains a formidable challenge owing to the presence of Mg 2+ , a physicochemical similar ion that often exists in excess. Here, we introduce a polyoxoniobate-based “Mg-PONb sponge” that enables ultraselective and rapid Li + /Mg 2+ separation across an exceptionally broad range of Mg/Li ratios (0.02 to 200.63). This framework achieves >99.9% Mg 2+ removal with negligible Li + loss in under 1 min, yielding Li + /Mg 2+ selectivity values exceeding 5000. The sponge demonstrates excellent recyclability, maintaining >99% Mg 2+ rejection and Li + permeability across five regeneration cycles without structural degradation. Mechanistic investigations reveal that selective Mg 2+ capture originates from strong coordination with terminal oxygens on the PONb cluster, driving rapid formation of porous Mg-PONb frameworks. This work presents a generalizable, scalable strategy for Li + /Mg 2+ separation and offers a sustainable path toward enhanced Li and Mg recovery from complex brine sources.

Chen, Linfeng [Lawrence Berkeley National Laborato↗
DOE OSTI2025

A model to assess Zircaloy’s mechanical property changes following a transient beyond critical heat flux

Maintaining the integrity of nuclear fuel rods is essential for ensuring public health and safety in nuclear power generation. During reactor operation, this integrity is confirmed by demonstrating compliance with established regulatory acceptance criteria. For moderate-frequency events, such as limiting transients and anticipated operational occurrences (AOOs), the current fuel integrity criterion is based on preventing boiling transition. This criterion assumes that prevention of boiling transition will prevent excessive cladding heating and, thus, fuel failure during normal operations. While conservative, this approach places significant constraints on core design, fuel cycle economics, and a plant’s ability to perform major power uprates, leading to suboptimal fuel utilization and inefficient carbon-free energy production. A more efficient approach could be achieved by revising the failure criterion to a material-specific limit rather than strictly preventing the boiling transition, since boiling transition per se is not a cause of fuel cladding failure. Here, as a result, a new licensing framework based on material properties, termed time-at-temperature (t@T), is needed. This approach would allow for brief periods of post–critical heat flux operation during an AOO without compromising safety. Implementing the t@T licensing strategy requires a robust technical foundation in material properties, which must be established through comprehensive data collection on both unirradiated and irradiated fuel and cladding materials. This foundation would enable the development of a safety basis that ensures safe operation while providing greater flexibility and efficiency for reactor operation. This paper documents a thorough review of the available data to establish a baseline knowledge that can inform the development of cladding mechanical models, as well as identify experimental data gaps that need to be addressed in future research. Machine learning and data informatics were utilized to extract the importance of parameters on the t@T parameter. Industry tools were used to perform baseline analyses to define the relevant transient conditions for data analysis. The subsequent review successfully identified applicable experimental data, as well as sufficient data to evaluate changes in cladding mechanical properties following an AOO transient. Rather than developing new models, this work coupled existing irradiation annealing and recrystallization models to calculate changes in hardness, yield stress, and ultimate tensile stress following an AOO event. The findings from this review were summarized to highlight the experimental data needs required to fill remaining gaps and support the development of future t@T licensing methodologies.

Cladding performance↗
DOE OSTI2023

Synthetic Calcium Carbonate Production by Carbon Dioxide (CO 2 ) Mineralization of Industrial Waste Brines

The global scale of CO 2 emission has crossed 36 B tons, and the United State represents 14% of the total emissions. In light of the high cost associated with current CO 2 capture processes ($60-to-150 per ton of CO 2 ), carbon capture and utilization (CCU), wherein CO 2 is converted to beneficial products, provides a pragmatic path to overcome the economic barrier for CO 2 emissions control. In particular, CO 2 mineralization offers an attractive route as it produces high-value mineral carbonates that sequester CO 2 in a stable form. For instance, fine precipitated calcium carbonate, a valuable product with unit price in the range of $230-280/t and a global market projected to reach 99 M tons in 2020, can be produced by capturing CO 2 within aqueous Ca 2+ solution. However, two critical challenges need to be overcome—(i) the need for costly processes such as electrolysis or addition of alkali hydroxides to maintain alkalinity during mineralization, and (ii) the geographic availability of Ca-rich solutions (or brines) which often renders efficient integration with power plants impractical. To simultaneously address these challenges, this project developed two novel routes to enable carbonate production based on efficient CO 2 mineralization. In one variation, the project developed a new alkaline carbonation process to capture CO 2 and produce calcite precipitates from coal ashes. Herein, coal ash is carbonated first in a sodium carbonate solution. The carbonation reaction produces sodium hydroxide and raises the solution pH. This high-pH hydroxide solution is then used for CO 2 capture, which converts the sodium hydroxide solution back to sodium carbonate to repeat the carbonation cycle. The carbonated ash residue is refined with a CO 2 pressure swing step to produce high-purity precipitated calcium carbonate. In another variation, Ca-rich produced water brine serves as the Ca-source to mineralize CO 2 . An H + /Na + ion-exchange cycle was designed to provision alkalinity during mineralization and regenerate the ion-exchange reagent in brines with high salinity. Ca-depleted brines can then be treated within a centralized water treatment facility. Both variations beneficially utilize reject streams—such as coal ashes and brines from oil and gas extraction or CO 2 storage operations—that are available at substantial quantities in the vicinity of coal power plants within the U.S. In addition to technology development, this project included techno-economic and life-cycle analysis to identify technically and economically appropriate solutions for power plants in different geographic locations. Taken together, the project provides a unique route to integrate CO 2 emissions control and waste handling/treatment for coal power plants, while producing a high-value product to offset the economic burden associated with waste management. The developed processes utilize post-desulfurization flue gas from coal-fired power plants as is. The CO 2 conversion reactions are performed in alkaline brines at ambient pressure from the flue gas, thereby minimizing the energy burden. By beneficiation of industrial waste streams with low energy input, the processes offers significant technical advantages in energy and CO 2 footprint over the current paradigm of precipitated calcium carbonate production, which involves calcination of limestone at processing temperatures in excess of 800 °C. Overall, this project developed viable CO 2 mineralization processes while strategically maximizing the economic benefit.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRSDate not supplied

Uncrewed Lunar Surface Operations and Support Activities

Sustained human presence on the surface of the Moon and future missions to Mars require increased independence from surface crews and Earth-based mission control to operate efficiently, safely, and reliably. The time for surface crews to perform tasks will be limited. Extravehicular activities by surface personnel are burdensome and time-consuming, even when a continuous human presence on the surface occurs. Identifying and balancing human/automation roles and tasks and infusing automation and autonomy practices early in a system’s lifecycle will be essential to achieve mission objectives. Among these objectives are attaining a sustained human presence, improving performance and mission effectiveness, reducing operations and maintenance (O&M) costs, and ensuring operations that are robust to communication delays. To achieve these objectives, an operational shift toward increased automation and autonomy with less reliance on humans is needed. Uncrewed lunar surface operations and support activities occur when surface crews are not present or are independent of surface crew timeline activities requiring no surface crew oversight or intervention. These uncrewed surface opportunities can also be planned to minimize crew workload that avoids routine maintenance and support tasks, thus maximizing crew exploration time. Uncrewed preparations such as staging and prepositioning equipment and materials before the crew arrives could improve crew task efficiency. Additional opportunities exist to conduct uncrewed science, exploration, and utilization. Uncrewed surface architecture functions can include science and exploration; habitation; launch and landing support; surface communication and navigation; surface power generation and distribution; human surface mobility; lifting, handling, manipulating; excavation, construction, and site preparation; logistics management; maintenance and repair; surface resource utilization; integrated site operations and shared support services (e.g., site scheduling/prioritization, dust mitigation/contamination control, and surface safety). Early robotic lunar surface campaigns will provide information on the availability of resources, such as oxygen and water, and demonstrate surface-based technologies. After the Artemis III human lunar return mission, a series of landers will deliver surface systems, cargo, supplies, science packages, spare parts, and commodities. A balance of crewed and uncrewed surface operations will enable a sustained lunar surface presence at the South Pole of the Moon at a site that will be known as the Artemis Base Camp (ABC). It is envisioned that base camp operations on and around the Moon will then help prepare for the mission durations and activities needed to support the first human mission to Mars. Before long-duration crew missions to the base camp can occur, the necessary surface infrastructure will be pre-deployed and verified operational. Surface assets will be teleoperated and remotely managed from Earth. Additionally, robotic and short-duration crewed missions to the ABC will ensure the site’s merit to achieve long-term science objectives, availability of usable resources, and that terrain, seasonal variations, and illumination conditions are acceptable. ABC will consist of different areas where specific functions and services are rendered, including: • Launch and Landing Area • Habitation Area • Power Production Area • Resource Areas Launch and Landing Area—The launch and landing area will support associated functions for the arrival and departure of vehicles, such as crewed landing and ascent and uncrewed cargo deliveries and offloading. It will evolve from an unimproved site at the beginning of the exploration campaign to a more sustainable landing and launch area that can support repeated arrivals and departures. Initial uncrewed Lunar Terrain Vehicle (LTV) surface operations may include emplacement of navigation beacons and communication equipment, real-time video and photography of landing/liftoff events, and element repositioning, such as portable utility power (PUP) (applicable for other landed assets at other areas). Site preparations, such as surface leveling, soil compaction, and berm/path construction, may be needed for a more sustainable launch and landing area capable of accommodating vehicles that are increasingly more reusable and reduce the effects of plume surface interactions and ejecta impacts on nearby surface assets. During the ABC missions, cargo and logistics will be delivered to the lunar surface via robotic cargo landers before the crew arrives. These shipments, which can arrive in pressurized logistics carriers, will deliver the logistics necessary to support a crewed mission and include items such as food, water, equipment spares, etc. Providing the capability to retrieve, offload, and transport the logistics closer to the ABC site before the arrival of the crew will increase the overall efficiency of crew operations once they arrive. In the sustained phase of exploration, other supporting services may be needed, such as lander propellant servicing, surface power services, commodity refreshes, and additional inspection, maintenance, and repair capabilities, to sustain a cadence of extended personnel stays and cargo arrivals and departures. Habitation Area—Uncrewed support to surface habitation could involve supporting activation and pre-entry operations of the habitat while the crew is in orbit at the Gateway outpost preparing for a surface landing. Surface Habitat (SH) uncrewed operations may include bringing the cabin environment to a habitable temperature and air mix and activating other critical crew support systems. Potential crop production uncrewed tasks in the SH could also include autonomous watering and tending. Additionally, when the crew departs, the SH enters dormancy for the long period of uncrewed operation. A logistical staging area could also be collocated near the SH. If so, staging operations for crew supplies, waste re-location, and recycling operations may be opportunities for uncrewed operations. Power Production Area—The Fission Surface Power (FSP) element and its supporting distribution equipment provide power to surface elements as needed across the ABC to supplement day-to-day operations and survive lunar nights. Uncrewed support of this power system includes any initial LTV-assisted deployments of cables and other distributed equipment, associated electrical connections, and system testing and activation operations. Robotically performing some inspections, maintenance, or repair tasks on the power distribution equipment could reduce the surface crew workload. Resource Area— Uncrewed resource prospecting, mapping, and characterizing possible resource sites is likely to be time-consuming and represents an opportunity for uncrewed operations between crewed missions. Uncrewed mobile equipment operations will be needed in the extreme environments of permanently shadowed locations where resource extractions occur. As In-Situ Resource Utilization (ISRU) pilot plant operations begin, uncrewed surface support activities with available mobile and portable assets (LTV, PUP, etc.) will better support these operations. Any produced commodities can be stored at a centralized storage location for future use. Also associated with these operations is the use of mobile robotic excavators for resource acquisition and robotic/autonomous regolith processing. The waste tailings generated during excavation and regolith processing would also need to be transported and deposited at a dedicated location. Surface assets will continue operating between crew visits to maintain surface capabilities, conduct lunar surface science, technology demonstrations, and public outreach opportunities. Additionally, certain sustaining tasks that would consume valuable crew time could be performed before crew arrival, or after their departure. This capability may offer more affordable options to construct, activate, test, and maintain a broad set of surface assets. Telerobotically operated human surface mobility systems, such as the LTV and Pressurized Rover (PR), can be utilized for various tasks. Surface environmental conditions pose a distinct challenge for all these activities. Surface illumination and localized shadows are one such factor. Night-survival operations could consist of thermal management, battery pre-charging, and load shedding. Some surface systems may hibernate through the night and then awake and continue nominal operations. Uncrewed mobile assets may use a more adaptive approach to optimize their power and operations; one method is to follow the sunlight. Night-survival operations may be initiated remotely by teleoperation, automated, or accomplished by supervised autonomous operation. The ability to pre-deploy and control remote assets in orbit or on Mars before the arrival of the mission crew is a key capability that can be simulated on the moon. The base camp provides a venue where these advanced operational concepts, technologies, and autonomous methods and techniques, including the incorporation of time delays to simulate Earth-Mars latency can be replicated to help buy down future Mars mission risks. This paper will examine the evolution of uncrewed lunar surface operations and support activities. It will also discuss the lunar surface environmental conditions (thermal, lighting, terrain, topography, communications) along with the challenges they pose on uncrewed surface operations, and the performance of these activities with limited to minimal human interaction and/or teleoperation. Since lunar missions include Mars mission analogs, such investigation provides the framework for future uncrewed Mars mission support.

Mark E Lewis↗
DOE OSTI2022

Multimodal sensor fusion framework for residential building occupancy detection

For several years now, smart building energy systems have been a research area of intensive activity. In light of the increasing need for sustainable buildings and energy systems, this trend motivates an increasing need for a solution to reduce carbon dioxide emissions and improve energy efficiency. This work proposes a high-performing and transferable occupancy detection framework that combines sensor data from different data modalities, including time series environmental data (temperature, humidity, and illuminance), image data, and acoustic energy data using ensemble method. To draw out the best prediction performance in each modality, the proposed framework was developed, including various models that were designed to learn the occupancy patterns reflected in the physical data streams. To tackle the time series environmental data, we designed two variants of an occupancy detection spatiotemporal pattern network (Occ-STPN) that performs both feature level and decision level fusion, respectively. We also propose a new metric; the fading memory mean square error (FMMSE), that provides a fair evaluation and penalization of delayed occupancy predictions. Multiple open-sourced datasets, including the Electricity Consumption and Occupancy and the University of California, Irvine's (UCI) building occupancy detection dataset, along with our own real data collected from six different houses, were used to validate the algorithms' performance. The experimental results presented herein break down the performance for each sensing modality, and a detailed analysis of the performance is also discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Revealing Local Structures through Machine-Learning-Fused Multimodal Spectroscopy

Atomistic structures of materials offer valuable insights into their functionality. Determining these structures remains a fundamental challenge in materials science, especially for systems with defects. While both experimental and computational methods exist, each has limitations in resolving nanoscale structures. Core-level spectroscopies, such as X-ray absorption (XAS) or electron energy-loss spectroscopies (EELS), have been used to determine the local bonding environment and structure of materials. Recently, machine learning (ML) methods have been applied to extract structural and bonding information from XAS/EELS data. However, frameworks relying solely on a single data stream, defined as characterization data derived from a single element using one technique, are often insufficient because multiple local environments can yield similar spectral features, making it challenging to differentiate between competing structural hypotheses. Here, in this work, we address this challenge by integrating multimodal ab initio simulations, experimental data acquisition, and ML techniques for structure characterization. Our goal is to determine local structures and properties using EELS and XAS data from multiple elements and edges. To showcase our approach, we use various lithium nickel manganese cobalt (NMC) oxide compounds which are used for lithium ion batteries, including those with oxygen vacancies and antisite defects, as the sample material system. We successfully inferred local element content, ranging from lithium to transition metals, with quantitative agreement with experimental data. Beyond local element inference, we find that ML model based on multimodal spectroscopic data is able to determine whether local defects such as oxygen vacancy and antisites are present, a task which is impossible for single mode spectra or other experimental techniques. Furthermore, our framework is able to provide physical interpretability, bridging spectroscopy with the local atomic and electronic structures.

battery↗
NASA NTRS2001

Composition of Hydrothermal Vent Microbial Communities as Revealed by Analyses of Signature Lipids, Stable Carbon Isotopes and Aquificales Cultures

Extremely thermophilic microbial communities associated with the siliceous vent walls and outflow channel of Octopus Spring, Yellowstone National Park, have been examined for lipid biomarkers and carbon isotopic signatures. These data were compared with that obtained from representatives of three Aquificales genera. Thermocrinis ruber. "Thermocrinis sp. HI", Hydrogenobacter thermophilus TK-6, Aquifex pyrophilus and Aquifex aeolicus all contained phospholipids composed not only of the usual ester-linked fatty acids, but also ether-linked alkyls. The fatty acids of all cultured organisms were dominated by a very distinct pattern of n-C-20:1 and cy-C-21 compounds. The alkyl glycerol ethers were present primarily as CIS() monoethers with the expection of the Aquifex spp. in which dialkyl glycerol ethers with a boarder carbon-number distribution were also present. These Aquificales biomarker lipids were the major constituents in the lipid extracts of the Octopus Spring microbial samples. Two natural samples, a microbial biofilm growing in association with deposition of amorphous silica on the vent walls at 92 C, and the well-known 'pink-streamers community' (PSC), siliceous filaments of a microbial consortia growing in the upper outflow channel at 87 C were analyzed. Both the biofilm and PSC samples contained mono and dialkyl glycerol ethers with a prevalence of C-18 and C-20 alkyls. Phospholipid fatty acids were comprised of both the characteristic Aquificales n-C-20:1 and cy-C-21, and in addition, a series of iso-branched fatty acids from i-C-15:0 to i-C-21:0, With i-C-17:0 dominant in the PSC and i-C-19:0 in the biofilm, suggesting the presence of two major bacterial groups. Bacteriohopanepolyols were absent and the minute quantities of archaeol detected showed that Archaea were only minor constituents. Carbon isotopic compositions of the PSC yielded information about community structure and likely physiology. Biomass was C-13-depleted (10.9%) relative to available CO2 from the source water inorganic carbon pool with lipids further depleted by 6.3% relative to biomass The C-20-21 Aquificales fatty acids of the PSC were somewhat heavier than the iso-branched fatty acids. The carbon isotopic signatures of lipid biomarkers were also explored using a pure culture, T ruber, previously isolated from the PSC. Cells grown on C02 with O2 and both H2 and thiosulfate as electron donors were only slightly depleted (3.3%) relative to the C-source while cells grown on formate with O2 showed a major discrimination (19.7%), possibly the result of a metabolic branch point involving the assimilation of C-formate to biomass and the dissimilation to CO2 associated with energy production. T. ruber lipids were slightly heavier than biomass (+1.3%) whether cells were grown using CO2 or formate. Fatty acids from CO2 grown T. ruber cells were a so slightly heavier (average +2.1%) than biomass. The relatively depleted PSC C-20-21 fatty acids suggest that any associated Thermocrinis biomass would also be similarly depleted and much too light to be explained by growth on CO2. The C-fractionations determined with the pure culture suggest that growth of Thermocrinis in the PSC is more likely to occur on formate, presumably generated by geothermal activity. This study points to the value of the analysis of the structural and isotopic composition of lipid blomarkers both in pure culture studies, and in establishing community structure and physiology, as a complement to genomic profiles of microbial diversity. This is especially so when the members of the microbial community are novel and difficult to cultivate in the laboratory.

Jahnke, Linda L.↗
NASA NTRS2000

Radar Reflectivity of the Martian Polar Regions

Radar experiments provide a unique method of probing the surfaces and subsurfaces of planetary bodies. Information on surface and subsurface structures and properties can be extracted from radar data. There is a well developed history of radar investigations of the planet Mars, beginning with the first reports of variations of scattering properties as a function of martian longitude in the mid-1960's. Because of the rapid rotation of Mars, the standard technique of delay-doppler mapping cannot be used as effectively as it is on Mercury and Venus, making it a more difficult radar target. Techniques have been developed to overcome this difficulty, including an inversion technique to combine many doppler-only (CW) experiments from different viewing geometries into a map of surface reflectivity, and new random long-code techniques. These techniques still suffer from ambiguities, however. A third technique which does not suffer from these ambiguities is the combination of the powerful Goldstone transmitter with the VLA as the receiving instrument to create a combined radar imaging instrument. We have used this combined radar instrument to image the surface of Mars in 3.5-cm radar reflectivity during the 1988, 1992/93, and 1999 oppositions. During the 1988 experiments, the residual south polar ice cap (RSPIC) was the brightest radar reflector on the planet - intrinsically brighter than even the Tharsis lava flows. This was quite an unexpected result. In contrast, during the 1992/93 experiments, the residual north polar ice cap (RNPIC) was not nearly so bright, and in fact showed no enhancement at all, This was puzzling, given the 1988 results for the RSPIC. We attributed the lack of a radar reflection enhancement to a combination of three effects: the geometry was different; the season was different; and the intrinsic scattering from the residual ice caps was different. The 1999 experiments provided a chance to test the relative importance of these three effects, since the RNPIC would be visible in a geometry very similar to the RSPIC in 1988, and the season would also be very similar. Preliminary reduction of the data taken in 1999 shows that the RNPIC did in fact show a radar reflectivity enhancement, but that it was still not as bright as the RSPIC in 1988. Details regarding the radar reflectivity of the residual ice caps, as well as the surrounding polar layered terrains (in light of our radar reflectivity data) will be discussed. Additional information is contained in the original extended abstract.

Butler, B. J.↗
DOE OSTI2022

The Use of Thermal Cameras for Pedestrian Detection

Visible-range camera sensors have been widely used for pedestrian detection. However, most of the methods, which employ visible-range color cameras, do not perform well under low-light and no-light conditions, e.g. during night time. Since the working principle of thermal camera sensors is mainly based on temperature and not light, they have been employed for person detection to overcome the drawbacks of visible-range sensors under these conditions. Every object gives off thermal energy, which is captured by a thermal camera sensor. When an object becomes hotter, it emits more thermal energy, and is therefore captured as much brighter or vice versa. Yet, compared to visible-range cameras, there are many additional challenges that need to be addressed when detecting pedestrians from thermal camera images. These challenges include bright hot objects close to humans, similar pixel values in an image due to weather conditions, or objects that block thermal cameras such as concrete or glass. Glass acts like a mirror for infrared radiation and reflects whatever is in front of the camera. Thus, novel methods are still required to accomplish pedestrian detection task from thermal camera images. To contribute to these efforts, we propose a new method and a modified object detection network incorporating saliency maps of thermal camera images. The features obtained from thermal images and their corresponding saliency maps are combined to obtain richer representations of pedestrian regions, and better detection performance. We perform extensive evaluations on five different datasets to compare the performance of the proposed approach with two baselines. Moreover, we evaluate and compare the transferability of these approaches by doing leave-one-out cross validation across different datasets. Furthermore, the results show that the proposed approach outperforms the baselines, and has better transferability properties across different thermal image datasets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

SAXS Assistant: Automated SAXS analysis for structural discovery in biologics and polymeric nanoparticles

Small-angle x-ray scattering (SAXS) is a powerful technique for assessing macromolecular structure. High-throughput SAXS is limited by the time-consuming and, at times, subjective nature of SAXS data interpretation. Here, we present SAXS Assistant, a Python-based script that streamlines SAXS data analysis to extract features for machine learning (ML) and key structural parameters, including the Guinier radius of gyration (R g ), pair distance distribution function (PDDF)-derived R g , maximum particle dimension (D max ), and Kratky plots. The script builds upon BioXTAS RAW and validates reliability via Guinier/PDDF R g agreement, an important indicator of well-measured data sets. For assistance in D max estimation, a multilayer perceptron regressor was trained with 1940 data files from the Small Angle Scattering Biological Data Bank. The model achieved a test set performance R 2 = 0.90 and mean absolute error = 11.7 Å. Training exclusively with experimental data translates analyses from researchers, including experts in the field, to the ML model, which helps assess D max estimations from PDDF. Gaussian mixture model clustering was implemented to classify profiles into structural classes based on entries in the Small Angle Scattering Biological Data Bank. Users may therefore assess the similarity between experimental samples and known biomolecular shapes within the mapped repository entries. This probabilistic clustering aids in quantifying information from Kratky and generating shape-descriptive features. SAXS Assistant accelerates SAXS data analysis through enforced quality control, ML-ready outputs, and flags for low-confidence results. In addition to providing the ability to analyze large data sets at high throughput, this tool is versatile and may serve researchers in both biological and synthetic polymer research fields.

36 MATERIALS SCIENCE↗