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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Crystal Orientation and Defect Mapping in Electron-Beam-Sensitive Zeolites with Near-Axis Transmission Kikuchi Diffraction

Porous materials are vital in catalysis, energy conversion, and environmental remediation. Understanding structural heterogeneity in zeolites is key to linking synthesis, framework intergrowths, and catalytic performance, yet current methods for phase identification and spatial mapping lack sufficient resolution or throughput. We present a high-throughput approach using near-axis transmission Kikuchi diffraction in a scanning electron microscope, achieving high phase and spatial resolution for electron-beam-sensitive zeolites, including ZSM-5 and, for the first time, Zeolite A. Here, this method enables direct visualization of intergrowth features that critically affect catalytic and adsorption behavior, bridging the gap between ensemble-averaged X-ray diffraction and high-resolution but low-throughput transmission electron microscopy. Combining nanoscale mapping with statistical sampling is highly suited for machine-learning pipelines guiding new structure function understanding and could be extended to other beam-sensitive porous materials such as metal–organic or covalent–organic frameworks.

crystallography↗
DOE OSTI2022

Joint Planning of Electricity Transmission and Hydrogen Transportation Networks

The abundance and uneven distribution of renewable energy might cause congestion and curtailment in electric power systems. Transmission expansions can potentially alleviate transmission congestion and reduce renewable energy curtailment. On the other hand, with the substantial cost reduction of electrolyzer technology and the continuing rise of hydrogen demand, converting surplus renewable energy to hydrogen provides synergistic benefits to power and hydrogen systems, but consequently requires joint planning of the two systems. To this end, we propose a joint planning approach for power transmission and hydrogen transportation networks to coordinately optimize the investment and operation of power and hydrogen infrastructure. In our proposed model, detailed truck routing, pipeline, and hydrogen storage are formulated to quantify the flexibility of hydrogen transportation system. A robust joint planning approach is also proposed to address various uncertainties from renewable energy, electric load, and hydrogen demand. Furthermore, our numerical simulations show that the proposed joint planning model can save the total system cost, reduce renewable energy curtailment, and increase the utilization level of transmission lines.

08 HYDROGEN↗
DOE OSTI2021

Remote methane sensor for emissions from pipelines and compressor stations using chirped-laser dispersion spectroscopy

Leak rates of methane (CH 4 ) from the natural gas supply chain result in lost profit from unsold product, public safety and property concerns due to potential explosion hazards, and a potentially large source of economic damages from legal liabilities. Yet large measurement challenges exist in identifying and quantifying CH 4 leak rates along the vast number and type of components in the natural gas supply chain. This is particularly true of the “midstream” components involved in the gathering, processing, compression, transmission, and storage of natural gas. This project developed and deployed new advances in chirped laser dispersion spectroscopy (CLaDS) to detect methane leaks from pipelines, compressor stations, and other midstream infrastructure from a remote position (standoff detection). The system was deployed from a van to measure fugitive methane leaks from a local compressor station as a proof-of-concept. The technique was validated through mobile laboratory measurements with in-situ sensors as well as controlled releases of methane. The system also mapped a plume from a controlled release of methane by tracking a small unmanned aerial system (sUAS) that carried a corner cube retroreflector which reflected the beam back to the instrument. The drone-based system quantified a leak rate to within 30% of the actual rate and localized the emission location within 5 m of the actual release location at standoff distances of 25-45 m. This sUAS-reflector tracking approach has benefits for mapping leak locations remotely using small drones flying around a facility. Benefits of a commercial sensor with these capabilities include reductions of leaks for pipeline operators (more profit), earlier detection of leaks to avoid catastrophic explosion hazards for public health and to mitigate property damage, and reduced methane emissions to the atmosphere (improving air quality).

03 NATURAL GAS↗
DOE OSTI2021

Optimal Energy Scheduling and Sensitivity Analysis for Integrated Power-Water-Heat Systems

The conventionally independent power, water, and heating networks are becoming more tightly connected, which motivates their joint optimal energy scheduling to improve the overall efficiency of an integrated energy system. However, such a joint optimization is known as a challenging problem with complex network constraints and couplings of electric, hydraulic, and thermal models that are nonlinear and nonconvex. We formulate an optimal power-water-heat flow (OPWHF) problem and develop a computationally efficient heuristic to solve it. The proposed heuristic decomposes OPWHF into subproblems, which are iteratively solved via convex relaxation and convex-concave procedure. Simulation results validate that the proposed framework can improve operational flexibility and social welfare of the integrated system, wherein the water and heating networks respond as virtual energy storage to time-varying energy prices and solar photovoltaic generation. Moreover, we perform sensitivity analysis to compare two modes of heating network control: by flow rate and by temperature. Our results reveal that the latter is more effective for heating networks with a wider space of pipeline parameters.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

TuFF internal WRAP for Rapid Pipeline Repair (TuFF iWRAP)

The goal of “TuFF internal WRAP for Rapid Pipeline Repair” (TuFF iWRAP) program was to develop a novel material system and placement process to fabricate structural pipe within the existing deteriorated pipelines without disruption of gas delivery. The team (University of Delaware – Center for Composite Materials (UD-CCM) and Plitzie Inc.) addressed this challenge by developing a new material feedstock and pipe in pipe (PIP) repair strategy. This allows the potential for significant cost reduction and has minimum operational impact on gas customers. The new robotic based placement design allows discontinuous placement of pipe sections creating a stand-alone structural liner within the legacy pipeline without the need for pipe shutdown. Here, the material is supplied using a tethered material feeding system and is placed and UV cured with the internal Wound Rapid Automated Placement (iWRAP) system. This provides maximum placement efficiency capable of traversing 90 angle bends in 12-inch pipe and overall design customization to meet pipe repair requirements (e.g., variable wall thickness, bridging gaps, etc.). UV-curable fiber reinforced composite material has been optimized to meet structural performance and placement/cure times. Superior strength and fatigue life has been demonstrated by improving fiber-matrix adhesion using new fiber sizing for UV resins. Rapid cure approaches using new liner and resins have been evaluated with industry. The appropriate design of the section joints has been developed and tested. We estimate coating time to be ~100 hours per mile enabling typical pipe repair within 1 week.

03 NATURAL GAS↗
DOE OSTI2023

Robust design of semi-automated clustering models for 4D-STEM datasets

Materials discovery and design require characterizing material structures at the nanometer and sub-nanometer scale. Four-Dimensional Scanning Transmission Electron Microscopy (4D-STEM) resolves the crystal structure of materials, but many 4D-STEM data analysis pipelines are not suited for the identification of anomalous and unexpected structures. This work introduces improvements to the iterative Non-Negative Matrix Factorization (NMF) method by implementing consensus clustering for ensemble learning. We evaluate the performance of models during parameter tuning and find that consensus clustering improves performance in all cases and is able to recover specific grains missed by the best performing model in the ensemble. The methods introduced in this work can be applied broadly to materials characterization datasets to aid in the design of new materials.

Bruefach, Alexandra (ORCID:0000000209323477)↗
DOE OSTI2020

E-PiPEline: Quick to Market Emulated-PPE using Commonly Available Materials

The Center for Disease Control has recommended the public to wear cloth face coverings in public settings that reduce potential exposure to COVID-19 where other social distancing measures are difficult to maintain (e.g., grocery stores and pharmacies) especially in areas of significant community based transmission. These face coverings and other Emulated-Personal Protective Equipment (EPPE) can be made by using Commonly Available Materials (CAMs). As part of the Sandia COVID-19 LDRD effort (funded under the Materials Science Investment Area), the Sandia E-PiPEline task evaluated E-PPE design options for face coverings and face shields considering their effectiveness, durability, build difficulty, build cost, and comfort. Observations from this investigation are presented here to provide guidelines for home construction of E-PPE. This executive summary includes a brief roadmap of the analysis methodology, two one-page handouts geared to be distributed to the public at large (one for E-PPE face coverings and one for E-PPE face shields), and additional observations regarding the potential solutions for E-PPE face coverings and face shields included to further support the one-page handouts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Gap Analysis on the Impacts of Hydrogen Addition to the North American Natural Gas Infrastructure Polyethylene Pipelines

The existing natural gas pipeline system is being considered as a means to distribute blends of clean hydrogen and natural gas as one component of clean hydrogen’s role in enabling a future low-carbon energy system. With nearly three million miles of transmission and distribution lines in the United States, this national asset is uniquely situated as a transition strategy to assist in the decarbonization of the US economy. 1 This report reviews existing data on the effects of hydrogen on polyethylene (PE) natural gas pipeline materials and identifies gaps where additional investigation is required to fully assess deleterious impacts to the polyethylene pipes from exposure to hydrogen. This gap analysis will assist in determining the feasibility of blending hydrogen gas into existing natural gas pipelines.

08 HYDROGEN↗
DOE OSTI2021

On the Utility of Transmission Color Analysis i: Differentiating Super-Earths and Sub-Neptunes

The majority of exoplanets found to date have been discovered via the transit method, and transmission spectroscopy represents the primary method of studying these distant worlds. Currently, in-depth atmospheric characterization of transiting exoplanets entails the use of spectrographs on large telescopes, requiring significant observing time to study each planet. Previous studies have demonstrated trends for solar system worlds using color–color photometry of reflectance spectra, as well as trends within transmission spectra for hot Jupiters. Building on these concepts, we have investigated the use of transmission color photometric analysis for efficient, coarse categorization of exoplanets and for assessing the nature of these worlds, with a focus on resolving the bulk composition degeneracy to aid in discriminating super-Earths and sub-Neptunes. We present our methodology and first results, including spectrum models, model comparison frameworks, and wave band selection criteria. We present our results for different transmission “color” metrics, filter selection methods, and numbers of filters. Assuming noise-free spectra of isothermal atmospheres in chemical equilibrium, with our pipeline, we are able to constrain atmospheric mean molecular weight in order to distinguish between super-Earth and sub-Neptune atmospheres with >90% overall accuracy using specific low-resolution filter combinations, . We also found that increasing the number of filters does not substantially impact this performance. This method could allow for broad characterization of large numbers of planets much more efficiently than current methods permit, enabling population- and system-level studies. Additionally, data collected via this method could inform follow-up observing time by large telescopes for more detailed studies of worlds of interest.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Pipeline Monitoring Using Highly Sensitive Vibration Sensor Based on Fiber Ring Cavity Laser

A vibration fiber sensor based on a fiber ring cavity laser and an interferometer based single-mode-multimode-single-mode (SMS) fiber structure is proposed and experimentally demonstrated. The SMS fiber sensor is positioned within the laser cavity, where the ring laser lasing wavelength can be swept to an optimized wavelength using a simple fiber loop design. To obtain a better signal-to-noise ratio, the ring laser lasing wavelength is tuned to the maximum gain region biasing point of the SMS transmission spectrum. A wide range of vibration frequencies from 10 Hz to 400 kHz are experimentally demonstrated. In addition, the proposed highly sensitive vibration sensor system was deployed in a field-test scenario for pipeline acoustic emission monitoring. An SMS fiber sensor is mounted on an 18” diameter pipeline, and vibrations were induced at different locations using a piezoelectric transducer. The proposed method was shown to be capable of real-time pipeline vibration monitoring.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators

Atmospheric correction of airborne hyperspectral imaging spectroscopy (AHIS) to obtain high-quality surface reflectance is the prerequisite for remote sensing applications. Over the last decades, different atmospheric correction methods have been developed based on radiative transfer models (RTMs), however, the relative performances of different algorithms are unclear. Automated operational atmospheric correction methods to process large-volume AHIS data in a high-accurate and high-throughput manner are still lacking. Therefore, this study proposed an operational atmospheric correction pipeline for deriving surface reflectance from AHIS data. To ensure the accuracy and efficiency of the pipeline, we focused on three specific aspects: (1) selecting a suitable RTM for the development of atmospheric lookup tables (LUTs) by comparing the commercial MODerate resolution atmospheric TRANsmission (MODTRAN) and open-sourced Library for Radiative TRANsfer (LibRadTRAN) models, where the widely-used software, Atmospheric/Topographic Correction for Airborne Imagery (ATCOR), was used as benchmarks; (2) identifying key atmospheric correction parameters and determining suitable sources for parameter retrievals including AHIS, Moderate Resolution Imaging Spectroradiometer (MODIS), and AErosol RObotic NETwork (AERONET); and (3) testing the performance of using machine learning emulators to speed up the RTM-based atmospheric correction. Results indicate that (1) atmospheric correction based on MODTRAN LUTs can produce surface reflectance accurately with mean absolute errors < 0.05 and cosine similarities > 0.98 compared to field measurements, which is comparable to the software ATCOR and slightly outperforms the LibRadTRAN LUTs; (2) sobol global sensitivity analysis demonstrates that in the atmospheric correction, visibility and water vapor are two key parameters that can be accurately derived from AHIS in contrast to MODIS or AERONET data; and (3) Random Forest emulators can produce accurate estimations of surface reflectance with mean absolute errors < 0.03 and cosine similarities > 0.98 for higher processing efficiency and determine a suitable set of wavelengths for retrieving atmospheric visibility and water vapor. In conclusion, the proposed atmospheric correction pipeline also improved the four-stream radiative transfer theory for airborne applications by considering adjacent effects from airborne surrounding pixels and can also be applied for atmospheric correction of hyperspectral data from spaceborne missions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Multiscale simulation of integrated energy system and electricity market interactions

Accelerating the deep decarbonization of the world's electric grids requires the coordination of complex energy systems and infrastructures across timescales from seconds to decades. Here, we present a new multiscale simulation framework that integrates process- and grid-centric modeling paradigms to better design, operate, and control integrated energy systems (IESs), which combine multiple technologies, in wholesale energy markets. Traditionally, IESs are analyzed with a process-centric paradigm such as levelized cost of electricity (LCOE) or annualized net revenue, ignoring important interactions with electricity markets. This framework explicitly models the complex interactions between an IES's bidding, scheduling, and control decisions and the energy market's clearing and settlement processes, while incorporating operational uncertainties. Through two case studies, we show the importance of understanding and quantifying complex resource-grid interactions. In case study 1, we demonstrate that optimized bidding from one resource shifts the profit distribution for all energy systems in the market. This result suggests new and more flexible IES technologies can disrupt the economics of all market participants, possibly leading to accelerated retirements of less flexible resources. Interestingly, the optimized bidding has little impact on grid-level aggregate statistics, such as total generation costs and renewable penetration rate. While aggregate modeling strategies may remain valid under some IES adoption scenarios for analysis focused on regional outcomes, direct comparisons of IES technologies at specific locations without considering these interactions may lead to misleading or incorrect conclusions. In case study 2, we consider the design and flexible operation of IESs that hybridize conventional generators with energy storage. Through a sensitivity analysis, we find that as the size of the storage system increases, the total number of start-ups for coal- and natural gas-based IESs reduced by 25% and 33.6%, and the total thermal generator ramping (i.e., mileage) reduced by 86.5% and 62.5%, respectively. This shows the primary benefit of storage may not be reduced operational costs (which do not change significantly) but fewer start-ups and less ramping, which may greatly simplify the design, operation, and control of carbon capture systems. The new modeling and optimization capabilities from this work enable the coupling of rigorous, dynamic process models with grid-level production cost models to quantitatively identify the nuanced interdependencies across these vast timescales that must be addressed to realize clean, safe, and secure energy production. Moreover, the proposed general multiscale simulation framework is applicable to all IES technologies and can be easily extended to consider other energy carriers (e.g., hydrogen, ammonia) and energy infrastructures (e.g., natural gas pipelines).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Equitable Energy Transition Planning in Holyoke, Massachusetts: A Technical Analysis for Strategic Gas Decommissioning and Grid Resiliency

Buildings account for 30% of the emissions in Massachusetts and are the largest source of emissions in the United States, along with transportation. Pipeline-delivered methane gas is the dominant heating source in Massachusetts, representing 51% of heating in the state. The current gas network in Massachusetts and across many other US states is aging, a relic of the coal gas era, with thousands of miles of cast iron and unprotected steel pipes that are considered leak prone. Even newer plastic pipes are subject to degradation and in need of replacement, an upgrade that averages $2.8 million per mile of pipeline replacement across investor-owned utilities in Massachusetts.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Hydrogen carriers: Production, transmission, decomposition, and storage

Recognizing the potential role of liquid hydrogen carriers in overcoming the inherent limitations in transporting and storing gaseous and liquid hydrogen, a complete production and use scenario is postulated and analyzed for perspective one-way and two-way carriers. The carriers, methanol, ammonia and toluene/MCH (methylcyclohexane), are produced at commercially viable scales in a central location, transmitted by rail or pipelines for 2000 miles, and decomposed near city gates to generate fuel-cell quality hydrogen for distribution to refueling stations. In terms of the levelized cost of H 2 distributed to the stations, methanol is less expensive to produce (1.22 dollars per kg-H 2 ) than MCH (1.35 dollars per kg-H 2 ) or ammonia (2.20 dollars per kg-H 2 ). Levelized train transmission cost is smaller for methanol (0.63 dollars per kg-H 2 ) than ammonia (1.29 dollars per kg-H 2 ) or toluene/MCH system (2.07 dollars per kg-H 2 ). Levelized decomposition cost is smaller for ammonia (0.30-1.06 dollars per kg-H 2 ) than MCH (0.54-1.22 dollars per kg-H 2 ) or methanol (0.43-1.12 dollars per kg-H 2 ). Over the complete range of demand investigated, 10-350 tpd-H 2 , the levelized cost of H2 distributed to stations is aligned as methanol « ammonia ~ MCH. With pipelines at much larger scale, 6000 tpd-H 2 , the levelized cost decreases by ~1 dollar per kg-H 2 for ammonia and MCH and much less for methanol. Methanol is a particularly attractive low-risk carrier in the transition phase with lower than 50-tpd H 2 demand.

08 HYDROGEN↗
DOE OSTI2023

Spatiotemporal analysis of 3D human iPSC-derived neural networks using a 3D multi-electrode array

While there is a growing appreciation of three-dimensional (3D) neural tissues (i.e., hydrogel-based, organoids, and spheroids), shown to improve cellular health and network activity to mirror brain-like activity in vivo , functional assessment using current electrophysiology techniques (e.g., planar multi-electrode arrays or patch clamp) has been technically challenging and limited to surface measurements at the bottom or top of the 3D tissue. As next-generation MEAs, specifically 3D MEAs, are being developed to increase the spatial precision across all three dimensions (X, Y, Z), development of improved computational analytical tools to discern region-specific changes within the Z dimension of the 3D tissue is needed. In the present study, we introduce a novel computational analytical pipeline to analyze 3D neural network activity recorded from a “bottom-up” 3D MEA integrated with a 3D hydrogel-based tissue containing human iPSC-derived neurons and primary astrocytes. Over a period of ~6.5 weeks, we describe the development and maturation of 3D neural activity (i.e., features of spiking and bursting activity) within cross sections of the 3D tissue, based on the vertical position of the electrode on the 3D MEA probe, in addition to network activity (identified using synchrony analysis) within and between cross sections. Then, using the sequential addition of postsynaptic receptor antagonists, bicuculline (BIC), 2-amino-5-phosphonovaleric acid (AP-5), and 6-cyano-5-nitroquinoxaline-2,3-dione (CNQX), we demonstrate that networks within and between cross sections of the 3D hydrogel-based tissue show a preference for GABA and/or glutamate synaptic transmission, suggesting differences in the network composition throughout the neural tissue. The ability to monitor the functional dynamics of the entire 3D reconstructed neural tissue is a critical bottleneck; here we demonstrate a computational pipeline that can be implemented in studies to better interpret network activity within an engineered 3D neural tissue and have a better understanding of the modeled organ tissue.

3D culture↗
DOE OSTI2021

FLC Award: QED: Quantum Ensured Defense of the Smart Electric Grid

A reliable electric power supply is crucial for modern day life as well as national security, economic productivity, and life-and-death essentials. During the COVID pandemic, internet and cell communications became a “must-have” for government and business operations, education, and communicating COVID testing for vaccine information. Loss of electric power quickly leads to human health and national security emergencies. When a major winter storm hit Texas in mid-February 2021, the system was overwhelmed and over 4M people lost power. Although this crisis arose from an unprecedented weather event - not a cyberattack - it serves as a vivid illustration of the impact power disruption can have on our American way of life. The recent cyberattack on the Colonial Oil Pipeline also provides a stark reminder that infrastructure supporting our daily lives has vulnerabilities.

24 POWER TRANSMISSION AND DISTRIBUTION↗