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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Portable fiber optic sensor for rare earth elements and other critical metals using photoluminescence methods

Rare earth elements and other metals are vital to a range of technologies that are used in the energy and defense sectors. However, monopolistic market conditions have caused significant concern over the stability of the critical metal supply chain, and this has spurred extensive efforts in many nations to produce these metals domestically, both from conventional sources such as mining and well as from unconventional sources such as coal and its utilization byproducts. Slow and expensive characterization methods pose a significant barrier for both metals prospecting and process monitoring. A promising solution to this challenge is the development of highly sensitive luminescent sensors for metals, which can offer low costs, portability, and sensitivity. Anionic zinc adeninate metal-organic frameworks (BioMOFs) are known to distinguishing and detect part-per-billion levels of terbium, europium, samarium, and dysprosium in water by sensitizing the narrow, element-specific emission bands from these lanthanides. Here, a BioMOF material is immobilized onto a large diameter, solarization-resistant fiber optic tip integrated with a portable, low-cost spectrometer for rare earth element sensing. Immobilizing the sensing material on fiber instead of dispersing the sensing material in solution offers several advantages: it facilitates solvent removal, which enhances luminescent signal from the sensitized lanthanides, and it also allows the BioMOF to be recycled for multiple uses. The sensing system was deployed on a simulated process stream and exhibited qualitative agreement with inductively-coupled plasma mass spectrometry for terbium and europium detection, highlighting the potential for the sensing system to be deployed for real-world applications. By using different sensing materials, the same portable sensor may be deployed to detect other energy relevant metals such as cobalt, providing a cost-effective and sensitive platform for critical metal characterization.

Crawford, Scott↗
DOE OSTI2023

Chapter Four—MSW characterization and preprocessing for biofuels and bioproducts

The organic fraction of MSW (OFMSW) has a high carbohydrate and lipid content, indicating its good potential as a feedstock for bioethanol and biodiesel production. However, variability in feedstock composition for MSW is a critical challenge for downstream conversion processes such as pyrolysis, gasification, incineration, and biotechnological conversion. MSW characterization is critical to inform and optimize the design of physical handling processes to minimize costs and environmental impacts, and improve the downstream conversion performance of MSW materials. Here, this book chapter focuses on current MSW characterization and preprocessing technologies and discusses the costs, benefits, and environmental impacts associated with MSW preprocessing. Also, the book chapter outlines the potential strategies to increase total revenue and mitigate negative environmental impacts for MSW recycling systems.

09 BIOMASS FUELS↗
DOE OSTI2022

Developing novel electrodes with ultralow catalyst loading for high-efficiency hydrogen production in proton exchange membrane electrolyzer cells

Hydrogen plays more crucial roles for decarbonizing the planets and meeting the climate challenges because of its high energy density and zero-emission. It can be produced with proton exchange membrane electrolyzer cells (PEMECs) driven by sustainable and renewable energy resources. Although PEMECs have a number of advantages, including high purity production, quick response, and the ability to operate at high pressure facilitating the gas delivering, their performance and cost greatly hinder their commercial-scale applications. To achieve high-efficiency and cost-reduced hydrogen production in PEMECs, we proposed thin engineered liquid/gas diffusion layers (LGDLs) and associated electrodes, i.e., catalyst-coated LGDLs (CCLGDLs), over conventional porous transport layers (PTLs) and catalyst-coated membranes (CCMs). The research approaches in this project are based on material synthesis, in-situ and ex-situ characterizations, component design and treatment, numerical modeling, and cost analysis. The thin and tunable LGDLs (TT-LGDLs) and CCLGDLs were successfully developed with great performance improvement as demonstrated in lab-scale, bench-scale, and system-scale electrolyzer tests. The electrode thickness was reduced from 370 µm to less than 100 µm with simplified fabrication processes. With the catalytically enhanced Ir-based catalyst coating, the as-developed CCLGDLs with a catalyst loading of 0.34 mg Ir /cm 2 achieved a cell performance of 1.77 V at 2 A cm -2 , exhibiting the catalyst mass activity enhanced by >20 times with significant catalyst saving over conventional catalyst cell design. In-situ PEMEC characterizations, including the current distribution mapping and high-speed and multiscale visualizations, were conducted for a deeper understanding of mass transport and electrochemical reactions within an electrolyzer with LGDLs and CCLGDLs. A 2D cell model was developed and validated for the enhanced performance on TT-LGDL through reducing ohmic losses due to nonuniform hydration and water transport. Further, the cost analysis results have shown a path to move beyond equivalency and surpass costs associated with the project baseline. In this project, the design and fabrication of TT-LGDLs and CCLGDLs will contribute to the performance enhancement, manufacturing simplification, and cost reduction for PEMECs and other energy conversion devices, thus shortening their pathways towards commercialization. This project also provides a good foundation for furthering the in-situ reaction interface research.

08 HYDROGEN↗
DOE OSTI2020

A cleanroom in a glovebox

The exploration of new materials, novel quantum phases, and devices requires ways to prepare cleaner samples with smaller feature sizes. Initially, this meant the use of a cleanroom that limits the amount and size of dust particles. However, many materials are highly sensitive to oxygen and water in the air. Furthermore, the ever-increasing demand for a quantum workforce, trained and able to use the equipment for creating and characterizing materials, calls for a dramatic reduction in the cost to create and operate such facilities. To this end, we present our cleanroom-in-a-glovebox, a system that allows for the fabrication and characterization of devices in an inert argon atmosphere. Additionally, we demonstrate the ability to perform a wide range of characterization as well as fabrication steps, without the need for a dedicated room, all in an argon environment. Finally, we discuss the custom-built antechamber attached to the back of the glovebox. This antechamber allows the glovebox to interface with ultra-high vacuum equipment such as molecular-beam epitaxy and scanning tunneling microscopy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2018

K-Means Cluster Study for Radiofrequency Propagation Characterization

The objective of this study is to design a simple method for mining radio frequency (RF) propagation data. The study explored the characteristics of a large dataset of propagation experiments conducted over the span of years and using several ground stations around the world. Furthermore, this study developed simple predictive models that can be used for link characterization and overall propagation behavior description, without the need for physical measurements on-site. It is understood that such statistical learning has several drawbacks in terms of accuracy and precision. K-means clustering was used to characterize the data set in a way never explored before in an attempt to create useful tools that reduce cost, time and risk. K-means clustering was used to characterize the data set. Cosine distance was used as a method to determine the optimal number for clustering each feature. Dependence and independence analysis was performed to explore intra and inter-sensitivity between the presented features, with respect to each other and time. Several predicative models were generated and evaluated with respect to a test set to assess a measure of prediction accuracy and precision. A simple method for data analysis was developed and tested as the basis for further studies and future refinement to produce optimal performing models.

Cognitive↗
DOE OSTI2020

Structural validation of a thermoplastic composite wind turbine blade with comparison to a thermoset composite blade

Reactive infusible thermoplastics have the potential to be advantageous for wind turbine blade composites because they are recyclable at end of life, can have reduced manufacturing costs, enable thermal joining and have similar, and in some cases better, structural properties than traditional thermoset epoxy composites. However, these materials are new to the wind industry and there is risk to investing in a material that has not been validated at a blade scale. Industry cannot adopt a new material such as this without large-scale validation and demonstration of system-level advantages in cost and/or performance. This paper presents structural characterization of a 13-m thermoplastic composite wind turbine blade compared to an identical geometry thermoset epoxy blade. In this work, the results of this comparison showed that the flatwise structural static performance and the fatigue performance of the two blades were similar, but the thermoplastic composite blade had increased damping compared to the epoxy blade, which may result in reduced operational loads.

17 WIND ENERGY↗
DOE OSTI2026

A ModEx Framework for Watershed Subsurface Investigation With Limited Geophysical Data Using Machine Learning and Hydrologic Modeling

Abstract Subsurface heterogeneity influences watershed hydrology strongly but remains difficult to characterize at catchment scales with sparse and costly field data. Geophysical surveys such as electromagnetic induction (EMI) provide local spatial subsurface images yet scaling them to watershed scales and converting EMI‐derived resistivity into hydraulic properties remains a challenge. We present a Model–Experiment (ModEx) framework that integrates limited EMI data with machine learning (ML) and hydrologic modeling to improve process representation and guide field investigations. Sparse EMI surveys were scaled to the catchment scale using a Random Forest model, and the resulting resistivity fields were combined with nearby borehole constraints to parameterize a hydrologic model. The EMI‐informed hydrological simulations improved predictions of streamflow sustained by subsurface flow and shallow saturation patterns. By combining EMI data and ML with hydrologic modeling, the ModEx framework guides future subsurface surveys, providing a transferable and efficient strategy for data–model integration across diverse watersheds. Plain Language Summary Mapping the underground network of soil and rock that controls water is essential for predicting floods and droughts, but seeing underground is difficult and expensive. We cannot drill everywhere, so scientists use geophysical tools to scan broad areas. There are two key challenges: these geophysical scans are often sparse across the whole watershed, and the geophysical data is hard to translate into water‐related properties. We used artificial intelligence to solve these problems. We taught a computer to find patterns linking the limited geophysical data to the land surface properties. This allowed it to fill in the gaps and create a complete, useful subsurface map for the entire watershed. This new map improves hydrologic simulations, leading to more accurate predictions of water movement in the watershed. It also helps scientists build better models with less data and generates a priority map showing where to measure next, making future investigations more efficient. Key Points Limited EMI scaled with ML improves catchment‐scale subsurface parameterization for hydrologic models The framework integrates hydrologic modeling with limited geophysical data to support subsurface investigation design ModEx framework offers a transferable data–model integration strategy that quantifies and reduces uncertainty guiding watershed studies

Chen, Hang↗
DOE OSTI2022

A portable fiber optic sensor for the luminescent sensing of cobalt ions using carbon dots

Cobalt is critical to energy-relevant technologies, and demand for cobalt will increase significantly with growing global adoption of renewables. However, supply chain stability is threatened by economic and geopolitical factors, incentivizing domestic cobalt production from alternative resources such as coal, coal utilization byproducts (e.g., ash, acid mine drainage) and electronic waste. Rapid, inexpensive, and portable characterization techniques are needed to reduce production costs associated with cobalt prospecting and process monitoring. Here, in this research, we develop a compact, portable fiber optic luminescent probe for cobalt using phosphorus and nitrogen co-doped carbon dots as the sensing material. The carbon dot emission overlaps well with the cobalt absorption band at ~510 nm, leading to a selective decrease in emission as a function of cobalt concentration. The system responds nearly instantly to the presence of cobalt, with detection limits of 0.7 and 3.5 ppm in water and pH 1.68 buffer, respectively, providing comparable performance to a commercial spectrometer at a significantly lower cost. Moreover, the sensor is selective for cobalt in the presence of 13 of the most common metal ions encountered in coal utilization byproducts and is responsive to cobalt when spiked into an acid mine drainage leachate sample, highlighting the sensor's potential for real-world deployment in challenging matrices. In addition, integrating the carbon dots with a filter paper substrate produced ‘test strip’ sensors that exhibited a selective and sensitive visual response to cobalt using a handheld UV lamp. Taken together, the sensing system represents a significant step forward in the development of low-cost practical sensors for high-value metals in complex streams.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Rotational transition, domain formation, dislocations, and defects in vortex systems with combined sixfold and twelvefold anisotropic interactions

We introduce a phenomenological model for a pairwise repulsive interaction potential of vortices in a type-II superconductor, consisting of superimposed sixfold and twelvefold anisotropies. Using numerical simulations we study how the vortex lattice configuration varies as the magnitudes of the two anisotropic interaction terms change. A triangular lattice appears for all values, and rotates through 30 ° as the ratio of the sixfold and twlevefold anisotropy amplitudes is varied, in agreement with experimental results. The transition causes the vortex lattice to split into domains that have rotated clockwise or counterclockwise, with grain boundaries that are “decorated” by dislocations consisting of fivefold and sevenfold coordinated vortices. We also find intradomain dislocations and defects, and characterize them in terms of their energy cost. We discuss how this model could be generalized to other particle-based systems with anisotropic interactions, such as colloids, and consider the limit of very large anisotropy where it is possible to create cluster crystal states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Metal Halide Perovskite Solar Module Encapsulation Using Polyolefin Elastomers: The Role of Morphology in Preventing Delamination

The development of perovskite solar cells (PSCs) has ushered in a new era of solar technology, characterized by its exceptional efficiency and cost-effective production. However, the soft and fragile nature of perovskites makes module encapsulation challenging. Polyolefin elastomers (POEs) have been reported to be promising encapsulants for perovskite modules. However, little research exists on identifying criteria among different types of POEs as encapsulants. Here, two POEs with different morphologies were compared as encapsulants. The first POE crystallizes during encapsulation (crystal content ∼40%), and the resulting shrinkage or warpage leads to delamination, causing minimodule failure. In contrast, perovskite minimodules encapsulated with a mostly amorphous POE exhibited better reliability and reproducibility. The best perovskite minimodules passed the thermal cycling test for 240 cycles between −40 and 85 °C and the damp heat test for 1419 h, according to the IEC 61215 standard. This study highlights the importance of the morphology of encapsulants in achieving high-quality encapsulation. Published by the American Physical Society 2024

14 SOLAR ENERGY↗
DOE OSTI2024

Cyber-Physical Simulation of the Cold Startup of Solid Oxide Fuel Cell – Gas Turbine (SOFC-GT) Hybrid Systems

This work introduces experimental studies for the cold startup process (CPS) of the SOFC-GT hybrid system using the cyber-physical simulation approach. The physical gas turbine is coupled with a cyber-physical SOFC stack, which is represented using the integration of a real time dynamic SOFC model with physical components (e.g., pressure chamber, natural gas burner, etc.). Different ramp rates of the turbine speed were tested out during the startup processes. Bypass valves were also used to manipulate the airflow during SOFC-GT hybrid system start-up process. Different ramp rates enable the rapid start-up of the turbine to avoid surge and stall, meanwhile enable acceptable warm rate of the fuel cell stack without damaging the cell material. CPS can enable dynamic characterizations of highly integrated systems at lower cost.

Zhou, Nana↗
DOE OSTI2024

Characterization Inform Sustainable Recovery of Critical Minerals from Fossil Energy Waste Feedstocks

Rare earth elements (REE) and other critical minerals (CM, e.g., Co, Ni, Li) have important uses in green energy and modern technologies, yet are vulnerable to potential supply chain disruptions. One potential domestic CM source is fossil energy wastes, such as acid mine drainage (AMD) and treatment solids (AMD solids), coal combustion ash, and Oil and Gas (O&G) drilling wastes (drill cuttings and produced waters). While they can contain lower CM concentrations then traditional ore, the quantity and fast availability as waste feedstock makes them a promising CM resource. To explore their promise, researchers at DOE’s National Energy Technology Laboratory (NETL) have collected and analyzed CM data for aforementioned fossil energy wastes, and utilized advanced geochemical characterization (e.g., synchrotron microprobe and sequential extraction) to identify the CM speciation and binding environments, and developed sustainable and targeted CM recovery. Successful examples include: (1) the discovery of easily mobile REE phases in Ca-rich coal combustion ash and developing a patented REE recovery process from Ca-rich Powder River Basin coal ash; (2) the successful identification of REE/Co/Ni/Zn hosting phases in acid mine drainage treatment solids (AMD solids) with diverse chemical composition (Al, Mn, or Fe-rich) informing the sequential recovery of different REE/CMs from AMD solids; (3) the recovery potential of Li and other CMs in O&G produced waters and drill cuttings. The innovations driven by characterization have the potential to offset the cost of waste management and wastewater treatments while reducing the cost and environmental footprint of CM extraction.

Stuckman, Mengling↗
DOE OSTI2026

Prairie State Generating Company Site: Storage Field Development Plan

This Storage Field Development plan presents the Storage Complex characterization results, construction, monitoring, operational plans, and costs associated with the proposed Prairie State Energy Campus - Carbon Capture and Storage (PSEC-CCS) project in Washington County, Illinois, near Marissa. The proposed storage complex, known as the St. Peter-Everton Storage Complex, comprises the St. Peter Sandstone and Everton sandstone reservoirs, with the Maquoketa Shale serving as the primary confining unit and the Knox Group as lower confining unit. The lowermost Underground Source of Drinking Water (USDW) identified for the site is the Pennsylvanian section.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1984

MIDAS - A microcomputer-based image display and analysis system with full Landsat frame processing capabilities

Image Display and Analysis Systems (MIDAS) developed at NASA/Ames for the analysis of Landsat MSS images is described. The MIDAS computer power and memory, graphics, resource-sharing, expansion and upgrade, environment and maintenance, and software/user-interface requirements are outlined; the implementation hardware (including 32-bit microprocessor, 512K error-correcting RAM, 70 or 140-Mbyte formatted disk drive, 512 x 512 x 24 color frame buffer, and local-area-network transceiver) and applications software (ELAS, CIE, and P-EDITOR) are characterized; and implementation problems, performance data, and costs are examined. Planned improvements in MIDAS hardware and design goals and areas of exploration for MIDAS software are discussed.

Hofman, L. B.↗
NASA NTRS1988

Delamination durability of composite materials for rotorcraft

Delamination is the most commonly observed failure mode in composite rotorcraft dynamic components. Although delamination may not cause immediate failure of the composite part, it often precipitates component repair or replacement, which inhibits fleet readiness, and results in increased life cycle costs. A fracture mechanics approach for analyzing, characterizing, and designing against delamination will be outlined. Examples of delamination problems will be illustrated where the strain energy release rate associated with delamination growth was found to be a useful generic parameter, independent of thickness, layup, and delamination source, for characterizing delamination failure. Several analysis techniques for calculating strain energy release rates for delamination from a variety of sources will be outlined. Current efforts to develop ASTM standard test methods for measuring interlaminar fracture toughness and developing delamination failure criteria will be reviewed. A technique for quantifying delamination durability due to cyclic loading will be presented. The use of this technique for predicting fatigue life of composite laminates and developing a fatigue design philosophy for composite structural components will be reviewed.

Obrien, T. Kevin↗
NASA NTRS1987

Gear systems for advanced turboprops

A new generation of transport aircraft will be powered by efficient, advanced turboprop propulsion systems. Systems that develop 5,000 to 15,000 horsepower have been studied. Reduction gearing for these advanced propulsion systems is discussed. Allison Gas Turbine Division's experience with the 5,000 horsepower reduction gearing for the T56 engine is reviewed and the impact of that experience on advanced gear systems is considered. The reliability needs for component design and development are also considered. Allison's experience and their research serve as a basis on which to characterize future gear systems that emphasize low cost and high reliability.

Wagner, Douglas A.↗
NASA NTRS2003

Micromechanics-Based Computational Simulation of Ceramic Matrix Composites

Advanced high-temperature Ceramic Matrix Composites (CMC) hold an enormous potential for use in aerospace propulsion system components and certain land-based applications. However, being relatively new materials, a reliable design properties database of sufficient fidelity does not yet exist. To characterize these materials solely by testing is cost and time prohibitive. Computational simulation then becomes very useful to limit the experimental effort and reduce the design cycle time, Authors have been involved for over a decade in developing micromechanics- based computational simulation techniques (computer codes) to simulate all aspects of CMC behavior including quantification of scatter that these materials exhibit. A brief summary/capability of these computer codes with typical examples along with their use in design/analysis of certain structural components is the subject matter of this presentation.

Murthy, Pappu L. N.↗
NASA NTRSDate not supplied

The Next Frontier for Remote Sensing of Freshwater HABS: Utilizing Imaging Spectroscopy Data to Identify Cyanobacteria Bloom Types

Cyanobacteria Harmful Algal Blooms (HABs) and their associated toxicity are a concern for inland waters. Due to the extensive spatial coverage and frequent data availability of satellite-based sensors, multi-spectral remote sensing tools have demonstrated utility for monitoring, understanding, and managing these blooms. The next frontier is utilizing high spectral resolution imaging spectroscopy data, such as from NASA’s upcoming PACE, GLIMR, and SBG missions planned for this decade, which allow for the development of more sophisticated cyanobacteria detection algorithms. We evaluate the performance of cyanobacteria genera differentiation algorithms using precursor datasets in support of these upcoming hyperspectral missions. In situ measurements of lake optical, biological, chemical, and physical properties are used to characterize cyanobacteria blooms in hypereutrophic Clear Lake, CA, USA, which supports large, diverse algal and cyanobacteria populations. Data collection occurred during 12 field events in 2021-2022 across all seasons. Three field events were conducted concurrently with hyperspectral data acquisitions from the DESIS sensor on the International Space Station. The results of this study will support the development of future tools utilizing satellite-based imaging spectroscopy data to identify the cyanobacteria genera present in a bloom, and thus the potential for cyanotoxin production. This outcome – the ability to quickly characterize a cyanobacteria bloom at a low cost – will have enormous benefits for public health.

remote sensing↗