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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Experimental and Theoretical Thermokinetic Analysis of the Na 3 VO 4 –CO 2 Reaction System under Different Physicochemical Conditions

Sodium vanadate (Na 3 VO 4 ) was synthesized, structural and microstructurally characterized as well as tested as possible carbon dioxide (CO 2 ) captor through thermodynamic calculations in addition to thermogravimetric dynamic and isothermal analyses. Ceramic structural characterization evidenced the formation of the Na 3 VO 4 crystal phase, while microstructural features evidenced dense agglomerates with a poor specific surface area, although synthesis temperature (600 °C) was not as high as that for other sodium ceramics. Na 3 VO 4 was investigated for the CO 2 capture process through dynamic and isothermal experiments, in the presence or absence of oxygen. All these experiments showed that Na 3 VO 4 possesses interesting CO 2 capture properties in a specific temperature range (520 and 600 °C). Isothermal products characterization allowed to elucidate the reaction pathway, implying the Na 4 V 2 O 7 formation, as possible reactive intermediate. In fact, reaction path evolution was supported with theoretical thermodynamic data. Moreover, the kinetic analysis, performed using the Avrami-Erofeev mathematical model and subsequent thermodynamic data obtention, probed the positive influence of the temperature, in both CO 2 superficial and bulk chemical sorption processes, while oxygen addition did not enhance the superficial process. Additionally, as it would be expected, kinetics were enhanced as a function of the CO 2 concentration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Analysis of Tar and Oil Derived from Pyrolysis and Copyrolysis of Waste Plastics and Biomass

Pyrolysis has been proposed as a potential technology for managing the growing volume of plastic waste generated worldwide. Co-pyrolysis of plastic waste with biomass is a promising technology for generating fuel and chemical products. However, this process generates tar as a waste product. The chemical properties of this tar have yet to be thoroughly analyzed. Further, this study presents the results of gas chromatography–mass spectrometry (GC–MS), Fourier-transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA) of oil and tar obtained from the pyrolysis of pure plastics including high-density polyethylene (HDPE), low-density polyethylene (LDPE), polyethylene (PE), polystyrene (PS), and plastic-biomass mixtures. GC–MS analysis revealed the presence of C 7 –C 37 carbon-containing hydrocarbons, which include alkanes and alkenes as the dominant products. FTIR data revealed the presence of various functional groups, including alcohols, aldehydes, ketones, and carboxylic acids, indicating the complexity of the pyrolysis and copyrolysis oil obtained from waste plastics and biomass. TGA data show that tar from all four plastics has a higher decomposition rate, suggesting the presence of heavier hydrocarbons compared with their corresponding oils. This research will be of interest to researchers looking to advance the study of plastic and biomass waste management.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Technoeconomic Analysis of Microwave-Assisted Dry Reforming Integrated with Chemical Looping for Production of Methanol

Methanol is a key component in producing formaldehyde, acetic acid, and methyl tert -butyl ether (MTBE) and supports a wide array of industries, including plastics, textiles, and automotive. It also plays a growing role in renewable energy solutions. However, the conventional production of methanol involves steam reforming of methane, which is very energy-intensive and produces significant quantities of the greenhouse gas carbon dioxide. In this research, a chemical looping scheme is combined with dry reforming of natural gas in a novel microwave reactor to produce an industrial quantity of methanol. A heat exchanger network is developed to substantially reduce hot and cold utility usage. The effect of the cost of purchasing carbon dioxide from an external source for dry reforming, the capital cost of the microwave reactor, and the cost of electricity on the net present value is analyzed. Technoeconomic comparison with the conventional industrial process that produces methanol via steam reforming of methane indicates that the chemical looping generates a significant positive net present value along with a substantial reduction in carbon dioxide emissions while producing methanol significantly below the U.S. Department of Energy’s goal of $800/ton.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Net Present Value Optimization of a Natural Gas Combined Cycle Plant with CO 2 Capture using a Water-Lean Solvent Considering Transient Electricity Price for Multiple Regions

Global CO 2 emissions are increasing at about a 1.5% rate per year. Fossil fuel-based plants are one of the main contributors to this rise. In the power generation industry, fossil fuel plants are dominant, and many plants are under development. In this study, a natural gas combined cycle (NGCC) power plant with postcombustion capture using a leading water-lean solvent is considered. For optimal design and operating schedule, large-scale dynamic optimization is undertaken for net present value (NPV) optimization. The first principle dynamic model of NGCC is developed, including a model of the highly efficient H-class gas turbines. For computational tractability of the dynamic optimization problem, a reduced-order model is developed by using the Hankel singular value decomposition. A waterlean solvent, N-(2-ethoxyethyl)-3-morpholinopropan-1-amine, is used for carbon capture. A model of the capture system is developed in Aspen Plus, which is used to develop a reduced-order model by using ALAMO, a machine learning software. In addition, a reduced model of the CO 2 compression system with a dehydration unit is also considered. The integrated system is used for NPV optimization by using the Python-based PYOMO platform. The PCC process is analyzed for three configurations-conventional packed bed, rotating packed bed (RPB), and a combination of RPB and direct contact cooler. The NPV optimization is performed for 14 regional markets by considering year-long clustered and continuous locational marginal price data with a 1 h interval. Optimization results show that the PCC can achieve 90% CO 2 capture with a positive NPV for six regions. Sensitivity studies conducted by using the PCC configurations indicate that the process is economically feasible for 9 regions out of 14 regional electricity markets with NPV values in the range of 33−540 $MM.

cabon capture↗
DOE OSTI2025

A Comparison of Electronic Structure Methods for Predicting the Hydrogenation Energies of Candidate Molecules for Hydrogen Storage

The development of novel energy materials and fuels is required to expand current available energy sources. Aiming to reach this goal, there is growing interest in using molecular hydrogen as an energy carrier due to its abundance and high energy density. Liquid organic hydrogen carriers (LOHCs) are a promising route to the large-scale storage and transport of hydrogen for use in the energy economy. The search for thermodynamically viable LOHC molecules for real world use has led to a set of constraints on the dehydrogenation enthalpy and the minimum gravimetric hydrogen capacity. These constraints allow one to formulate the search for an ideal LOHC candidate molecule as an optimization problem well suited to the strengths of machine learning and artificial intelligence computational approaches. A critical barrier to a large-scale, high-throughput screening of LOHC candidate molecules is the lack of reliable training data. Computational electronic structure methods including density functional theory, coupled cluster approximations, and diffusion Monte Carlo can be used to provide training data where experimental data are either unreliable or do not exist. In this work, we use these methods to calculate the dehydrogenation energies and enthalpies of candidate LOHC molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Cu–Ni Oxidation Mechanism Unveiled: A Machine Learning-Accelerated First-Principles and in Situ TEM Study

Here, the development of accurate methods for determining how alloy surfaces spontaneously restructure under reactive and corrosive environments is a key, long-standing, grand challenge in materials science. Using machine learning-accelerated density functional theory and rare-event methods, in conjunction with in situ environmental transmission electron microscopy (ETEM), we examine the interplay between surface reconstructions and preferential segregation tendencies of CuNi(100) surfaces under oxidation conditions. Our modeling approach predicts that oxygen-induced Ni segregation in CuNi alloys favors Cu(100)-O c(2 × 2) reconstruction and destabilizes the Cu(100)-O (2√2 × √2)R45° missing row reconstruction (MRR). In situ ETEM experiments validate these predictions and show Ni segregation followed by NiO nucleation and growth in regions without MRR, with secondary nucleation and growth of Cu 2 O in MRR regions. Our approach based on combining disparate computational components and in situ ETEM provides a holistic description of the oxidation mechanism in CuNi, which applies to other alloy systems.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Assessing the Accuracy of Property Model Predictions for Cost Optimization of Desalination Technologies

Accurate modeling of seawater thermophysical and thermodynamic properties is critical for optimizing desalination processes. This study compares three seawater property models, a Reaktoro multicomponent model, the thermophysical seawater properties library from the Massachusetts Institute of Technology, and a simplified sodium chloride model, in the context of levelized cost of water (LCOW) minimization for reverse osmosis (RO) and mechanical vapor compression systems. Process simulations and cost optimizations reveal that although all three models yield comparable LCOW and specific energy consumption (SEC) estimates under baseline conditions, deviations among their predictions increase with salinity. Relative differences in LCOW and SEC reach up to 6% and 8%, respectively. RO results show greater variability due to differences in osmotic pressure predictions, which affect pressure constraints at high recoveries. Computational performance varies substantially; specifically, Reaktoro simulations are up to 28 times slower than empirical models due to their detailed equilibrium calculations. These results suggest that empirical models offer acceptable accuracy for routine desalination process design, while Reaktoro provides advantages in scenarios requiring detailed speciation, such as scaling or pH adjustment studies. These findings underscore the importance of selecting appropriate property models based on the modeling objective of desalination applications and motivate future work integrating thermodynamic rigor with empirical efficiency.

Physical and chemical properties↗
DOE OSTI2025

How Did Westward Volcaniclastic Deposits Accumulate in the Deep Sea Following the January 2022 Eruption of Hunga Volcano?

Most volcanic eruptions on Earth take place below the ocean surface and remain largely unobserved. Reconstruction of past submerged eruptions has thus primarily been based on the study of seafloor deposits. Rarely before the 15 January 2022 eruption of Hunga volcano (Kingdom of Tonga) have we been able to categorically link deep-sea deposits to a specific volcanic source. This eruption was the largest in the modern satellite era, producing a 58-km-tall plume, a 20-m high tsunami, and a pressure wave that propagated around the world. The eruption induced the fastest submarine density currents ever measured, which destroyed submarine telecommunication cables and traveled at least 85 km to the west to the neighboring Lau Basin. Here we report findings from a series of remotely operated vehicle dives conducted 4 months after the eruption along the Eastern Lau Spreading Center-Valu Fa Ridge. Hunga-sourced volcaniclastic deposits 7–150 cm in thickness were found at nine sites, and collected. Study of the internal structure, grain size, componentry, glass chemistry, and microfossil assemblages of the cores show that these deposits are the distal portions of at least two ~100-km-runout submarine density currents. We identify distinct physical characteristics of entrained microfossils that demonstrate the dynamics and pathways of the density currents. Microfossil evidence suggests that even the distal parts of the currents were erosive, remobilizing microfossil-concentrated sediments across the Lau Basin. Remobilization by volcaniclastic submarine density currents may thus play a greater role in carbon transport into deep sea basins than previously thought.

58 GEOSCIENCES↗
DOE OSTI2025

Quantum graph learning and algorithms applied in quantum computer sciences and image classification

Graph and network theory play a fundamental role in quantum computer sciences, including quantum information and computation. Random graphs and complex network theory are pivotal in predicting novel quantum phenomena, where entangled links are represented by edges. Quantum algorithms have been developed to enhance solutions for various network problems, giving rise to quantum graph computing and quantum graph learning (QGL). Here, in this review, we explore graph theory and graph learning methods as powerful tools for quantum computers to generate efficient solutions to problems beyond the reach of classical systems. We delve into the development of quantum complex network theory and its applications in quantum computation, materials discovery, and research. We also discuss quantum machine learning (QML) methodologies for effective image classification using qubits, quantum gates, and quantum circuits. Additionally, the paper addresses the challenges of QGL and algorithms, emphasizing the steps needed to develop flexible QGL solvers. This review presents a comprehensive overview of the fields of QGL and QML, highlights recent advancements, and identifies opportunities for future research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Energy Communities IWG Site Review Tool

The Energy Communities IWG's new Site Review Tool is a resource for manufacturers and investors interested in developing or expanding clean energy supply chain projects in energy communities and nationwide. The interactive map provides access to publicly available information on brownfields, facilities, nearby infrastructure, and community attributes, including federal incentives. The site review tool empowers community leaders and developers to promote investment into communities and encourages users to learn and explore the diverse range of investment options. This tool can be useful for applicants to identify relevant information about their project that is requested in DOE grant and tax credit submissions, including 48C energy community status and whether a project is located in a disadvantaged community. More information on this tool can be found at: https://energycommunities.gov/iwg-site-review-tool/ Disclaimer: This mapping tool may not be relied upon by taxpayers to substantiate a tax return position or for determining whether certain penalties apply and will not be used by the IRS for examination purposes. The mapping tool does not reflect the application of the law to a specific taxpayer's situation, and the applicable Internal Revenue Code provisions ultimately control.

48C↗
DOE OSTI2024

Critical Minerals and Materials Matchmaker-CM3

This is the Critical Minerals and Materials Matchmaker (CM3) survey form. CM3 is an online information resource created to help connect users across the critical minerals and materials supply chain. The survey is designed to allow organizations to self-identify their critical minerals and materials-aligned activities and interests, and an interactive map that displays those on-going activities in a dynamic way. To include your critical minerals management activity or activities in CM3, please open and fill out the Critical Minerals and Materials Survey. If your organization has many ongoing or planned activities that would be onerous to enter in the form, or if your activities are difficult to geolocate (such as a transport network), please email the team at edxspatial@netl.doe.gov. This initiative is aligned with the approach of DOE’s H2 Matchmaker and Carbon Matchmaker. Read more information on H2 Matchmaker and Carbon Matchmaker. Below are some questions to help understand if you should fill out the CM3 survey: Does your company work with elements such as lithium, cobalt, copper, graphite, nickel, rare earth minerals, or platinum group metals? Does your organization have research and development activities related to critical materials or their supply chains? Does your company currently work in the critical minerals or materials supply chain? Do you have prospective work in critical minerals or materials in the next 5 years? Does your company mine, process, refine or distribute critical minerals or materials? Do you want to network with other facilities or organizations working in the same areas? Are you curious about the critical mineral and material activity in your surrounding area? Are you interested in aligning your potential needs across the supply chain to different geographic areas within the U.S? For more information, please see the CM3 website (https://www.energy.gov/fecm/articles/critical-minerals-materials-matchmaker-cm3) or email our team at edxspatial@netl.doe.gov.

CM3↗
DOE OSTI2025

Offshore Geologic Carbon Storage Inventory Dashboard

The Offshore Geologic Carbon Storage Inventory Dashboard is an interactive dashboard. The dashboard showcases the Offshore Geologic Carbon Storage (GCS) Inventory. It is intended to be used for research and comparison purposes, see full disclaimer and credits.

Carbon Sequestration↗
DOE OSTI2025

United States CMM Insights Dataset

Geo-data science applications for critical mineral analysis, development acceleration, economic impact assessment, and project efficiency. Coverage: 10 years (2014-2023), 3 geographic levels (county, state, tract), 45 features Data Categories: - census: 30 features (e.g., asian population percentage, black population percentage, citizen voting age population percentage) - ejscreen: 3 features (e.g., P_DSLPM, P_PM25, P_PWDIS) - energyexpenditure: 12 features (e.g., Housing adjustment factor, Income adjustment factor, Monthly electricity cost)

AS↗
DOE OSTI2025

National CMM Insights Platform

The National CMM Insights Platform is an interactive application. The tool showcases the U.S. National CMM Insights Dataset. It is intended to be used for research and comparison purposes, see full disclaimer and credits. Description: The National CMM Insights Platform is an interactive tool. The tool showcases the National CMM Insight Dataset. Application link: https://arcgis.netl.doe.gov/portal/apps/experiencebuilder/experience/?id=745ba8726d894a7f86c5d1859116c009 For additional information, please check out the StoryMap documentation: National CMM Insights Platform Guide The National CMM Insights Platform and Dataset provides access to aggregated publicly available information pertaining to census tracts, counties and states.

AS↗
DOE OSTI2026

Pore-Scale Study on the Positive Feedback Between Stress and Porosity Caused by Pressure Solution in Porous Media

Pressure solution is an important process in the evolution of sedimentary rocks, which provide storage space for most of our petroleum resources. It directly influences the generation, migration, and storage of petroleum fluids in subsurface sedimentary rocks. Here, in this paper, we develop a pore-scale, mechanochemical model to demonstrate a possible positive feedback between the local porosity and pore surface stress, in which a higher local porosity causes a higher local pore surface stress, thus enhancing pressure solution and consequently further increasing the local porosity. Pore surface stress represents stress on a solid grain adjacent to a pore. Specifically, the pore-scale, mechanochemical model directly simulates the stress distribution over solid and pore surfaces using a finite element model. The dissolution of solids at the solid-pore interfaces under a far-from-equilibrium condition is simulated using a first-order kinetics model that accounts for the local stress distribution. The updated pore geometry, caused by pore surface dissolution, is then used in the stress simulation in the next numerical iteration. Two types of porous media, the Oriskany sandstone and an artificial porous medium with spherical pores, were tested in the mechanochemical simulation. The positive stress-porosity feedback during pressure solution was observed in both samples. In addition, the model quantitatively illustrated the distribution of local mineral dissolution rates on all pore surfaces, as well as its relation to the effective mineral dissolution rate of the entire sample. Based on the comparison between the two porous media, the local mineral dissolution was regulated by pore space distribution, geometry, and coalescence during pressure solution. This work is the first that uses direct, pore-scale numerical simulation to demonstrate the positive stress-porosity feedback during pressure solution, which has the potential to advance the understanding of the mechanical-chemical (MC) coupling in many geological processes that are relevant to subsurface energy systems, such as the recovery of petroleum hydrocarbons and geothermal energy.

CT scanning↗
DOE OSTI2024

Rock Characterization for Subsurface Energy Applications

An overview of the Fossil Energy and Carbon Management mission for carbon management was given, along with information on the role the Research and Innovation Center plays in understanding aspect of research needed to accelerate geologic carbon storage nationwide.

Crandall, Dustin [NETL]↗