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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Accelerated CO2 Storage Optimization Using Multi-Resolution Fourier Neural Operator at the Illinois Basin Decatur Project (IBDP)

This paper presents a deep learning-based approach for optimizing CO2 injection in carbon capture and storage (CCS) operations. We developed a multi-resolution machine learning model to significantly reduce data generation costs. Utilizing this proxy model, we implemented a multi-objective genetic algorithm to optimize well control during the CO2 injection process. The proposed approach was applied to the Illinois Basin Decatur Project (IBDP), successfully optimizing the CO2 injection schedule based on three key objectives: maximizing the amount of CO2 stored, maximizing sweep efficiency, and minimizing pressure increase. The use of the proxy model accelerated the optimization workflow by two orders of magnitude, while the cost of data generation for the proxy model was reduced by 90% by utilizing a coarse-scale model.

accelerated CO2 storage optimization↗
DOE OSTI2024

MIBiG 4.0: advancing biosynthetic gene cluster curation through global collaboration

Specialized or secondary metabolites are small molecules of biological origin, often showing potent biological activities with applications in agriculture, engineering and medicine. Usually, the biosynthesis of these natural products is governed by sets of co-regulated and physically clustered genes known as biosynthetic gene clusters (BGCs). To share information about BGCs in a standardized and machine-readable way, the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard and repository was initiated in 2015. Since its conception, MIBiG has been regularly updated to expand data coverage and remain up to date with innovations in natural product research. Here, we describe MIBiG version 4.0, an extensive update to the data repository and the underlying data standard. In a massive community annotation effort, 267 contributors performed 8304 edits, creating 557 new entries and modifying 590 existing entries, resulting in a new total of 3059 curated entries in MIBiG. Particular attention was paid to ensuring high data quality, with automated data validation using a newly developed custom submission portal prototype, paired with a novel peer-reviewing model. MIBiG 4.0 also takes steps towards a rolling release model and a broader involvement of the scientific community. MIBiG 4.0 is accessible online at https://mibig.secondarymetabolites.org/.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

MRCI - Final Technical Report

The objective of the Midwest Regional Carbon Initiative (MRCI) project was to implement a collaborative Regional Initiative to accelerate the deployment of carbon capture, utilization, and storage (CCUS) in the Midwest-Northeastern and Mid-Atlantic areas of the United States. This area encompasses a 20-state region with much of the country’s carbon dioxide (CO2) emissions. The MRCI project is co-led by Battelle Memorial Institute (Battelle) in Columbus, Ohio, and the Illinois State Geological Survey (ISGS) in Champaign, Illinois, and benefitted from the experience these organizations have acquired over the past 10-plus years leading two Department of Energy (DOE) Regional Carbon Sequestration Partnerships (RCSPs): the Midwestern Regional Carbon Sequestration Partnership (MRCSP), led by Battelle, and the Midwest Geologic Sequestration Consortium (MGSC), led by the ISGS.

CCS↗
DOE OSTI2026

Carbon dioxide pipeline network transportation cost model: evaluating economic and geographic factors for efficient carbon capture, storage, and utilization

This study presents a comprehensive pipeline network modeling framework to estimate the CO 2 delivery cost for CO 2 utilization and geologic CO 2 storage across the United States. We developed a Python-based CO 2 pipeline transportation cost model leveraging Argonne National Laboratory’s pipeline engineering expertise and detailed natural gas transmission pipeline cost data across U.S. regions. Using existing road corridors as practical routing guides, the model designs pipeline networks that aggregate CO 2 from one or multiple sources and deliver it to selected destinations. It then minimizes the total transportation cost by optimizing pipeline diameters and incorporating booster pumps. A key contribution is the incorporation of up-to-date, region-specific cost factors with itemized components for materials, labor, miscellaneous construction expenses, and right-of-way acquisition. Results emphasize that regional variation and economies of scale associated with CO 2 pipeline costs are significant and should be explicitly accounted for in screening and planning studies. By combining realistic routing constraints with regionalized cost inputs, the model provides transparent design methodology and location-specific insights into source–destination delivery costs, including the effects of routing complexity along existing road networks. We demonstrate the model with two illustrative case studies – one for CO 2 storage and one for CO 2 utilization – in which the model designs pipeline networks spanning hundreds of miles across the states, collecting CO 2 from multiple sources and delivering it to designated endpoints while minimizing levelized cost of delivery via diameter and compression optimization. The model offers a practical, scalable approach for alternative design option screening and early-stage CO 2 transportation planning.

CCS↗
DOE OSTI2025

Life-cycle greenhouse gas emissions analysis of battery-grade lithium production in Finland

Various countries are undertaking initiatives to domestically produce battery-related critical materials. Within Finland, Keliber Technology Oy is developing capabilities for battery-grade lithium hydroxide monohydrate (LHM) production from spodumene ores. A detailed life-cycle assessment (LCA) of this pathway is conducted to determine its life-cycle GHG impacts using Argonne's R&D GREET (Research and Development Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model. The analysis shows life-cycle GHG emissions of similar to 9.2 kg CO 2-eq /kg LHM, dominated by contributions from three energy sources - diesel, natural gas, and electricity - and two material inputs - lime (CaO) and soda ash (Na 2 CO 3 ). Sensitivity analyses highlight the potential to reduce these impacts using low-carbon electricity, sequestration of process CO 2 emissions generated during CaO and Na 2 CO 3 production, and bio-based energy for LHM production (by similar to 15 % each). A comparative analysis shows lower impacts for Keliber's LHM than for existing LHM production from Australian spodumene ores processed in China (by similar to 40 %).

CCS↗
DOE OSTI2024

AutoCheck: Automatically Identifying Variables for Checkpointing by Data Dependency Analysis

Checkpoint/Restart (C/R) has been widely deployed in numerous HPC systems, Clouds, and industrial data centers, which are typically operated by system engineers. Nevertheless, there is no existing approach that helps system engineers without domain expertise and domain scientists without system fault tolerance knowledge identify those critical variables accounted for correct application execution restoration in a failure for C/R. To address this problem, we propose an analytical model and a tool (AutoCheck) that can automatically identify critical variables to checkpoint for C/R. AutoCheck relies on first, analytically tracking and optimizing data dependency between variables and other application execution state, and second, a set of heuristics that identify critical variables for checkpointing from the refined data dependency graph (DDG). AutoCheck allows programmers to pinpoint critical variables to checkpoint quickly within a few minutes. We evaluate AutoCheck on 13 representative HPC benchmarks, demonstrating that AutoCheck can efficiently identify correct critical variables to checkpoint.

HPC↗
DOE OSTI2024

Scrutinizing Variables for Checkpoint Using Automatic Differentiation

Checkpoint/Restart (C/R) saves the running state of the programs periodically, which consumes considerable time and system resources. We observe that not every piece of data is involved in the computation in typical HPC applications; such unused data should be excluded from checkpointing for better storage and compute efficiency. We propose a systematic approach that leverages automatic differentiation (AD) to scrutinize every element within variables (e.g., arrays) necessary for checkpointing. This allows us to identify critical and uncritical elements and eliminate uncritical elements from checkpointing. Specifically, we inspect every single element within a variable necessary for checkpointing with an AD tool to determine whether the element has an impact on the application output or not. We validate our approach with all benchmarks from the NPB suite. We visualize the distribution of critical and uncritical elements within a variable with respect to its binary impact (yes or no) on the application output.

Huang, Xin [Kobe University]↗
DOE OSTI2025

Data Readiness for AI: A 360-Degree Survey

Artificial Intelligence (AI) applications critically depend on data. Poor-quality data produces inaccurate and ineffective AI models that may lead to incorrect or unsafe use. Evaluation of data readiness is a crucial step in improving the quality and appropriateness of data usage for AI. R&D efforts have been spent on improving data quality. However, standardized metrics for evaluating data readiness for use in AI training are still evolving. In this study, we perform a comprehensive survey of metrics used to verify data readiness for AI training. This survey examines more than 140 papers published by ACM Digital Library, IEEE Xplore, journals such as Nature, Springer, and Science Direct, and online articles published by prominent AI experts. This survey aims to propose a taxonomy of data readiness for AI (DRAI) metrics for structured and unstructured datasets. We anticipate that this taxonomy will lead to new standards for DRAI metrics that would be used for enhancing the quality, accuracy, and fairness of AI training and inference.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Advanced Infrastructure Integrity Modeling (AIIM) Onshore Pipeline Database

The Advanced Infrastructure Integrity Modeling (AIIM) Onshore Pipeline Database is an interoperable spatial resource containing critical environmental, operational, and reported stressors tied to publicly available oil and gas pipeline locations across the contiguous U.S. and Alaska. This database contains two layers: 1. Pipeline point locations (‘pipeline_points’) – More than 500,000 points (at every kilometer along pipelines, and end points) to which more than 350 stress-related variables have been appended. 2. Merged pipelines (‘merged_pipelines’) – The original, publicly available pipeline data (see table below) merged together into one feature class.

Carbon Transport↗
DOE OSTI2025

WELLS Interactive Application

The Wellbore Exploration and Location Logistic System (WELLS) Interactive Application is an interactive tool to enable easy exploration and visualization of the living national wellbore database (WELLS Database (https://edx.netl.doe.gov/dataset/wells_database)). The tool and underlying database were created and are maintained by the National Energy Technology Laboratory (NETL), providing visualization of the more than six million public wellbore records from more than 65 authoritative state, federal, and tribal resources. The WELLS Interactive Application serves up wellbore data from oil, gas, underground injection, research, geothermal, geotechnical, groundwater, and other types of wells in a single, standardized, unified system. In addition to the surface location of these wells, the underlying database combines select key attributes for features such as well age, depth, and operating status. The system also provides users with references back to the original sources used in this unified platform. The underlying data can be accessed through the WELLS Database: https://edx.netl.doe.gov/dataset/wells_database Additional Information: The WELLS Interactive Application (formerly titled CO2-Locate) enables visualization and access to the public wellbore records through an intuitive web-based mapping tool. The WELLS Interactive Application was designed to help users visualize, query, analyze, and download wellbore records. Public wellbore points are included as a layer in the Map page, called Public Wells. Additionally, a multivariate hexagon grid summarizing well density from proprietary well data, called Well Density, is included to identify data gaps between the public and proprietary well data. Filtering functionalities in the tool allow these two layers to be spatially filtered by state, county, or basin as well as by status, type, true vertical depth, and spud year. The WELLS Interactive Application also contains a Near Me tool can be used to search and explore wellbore data within a user-defined distance of a specified location on the map, which can also be downloaded. The Query tool allows users to query the selected or filtered wells in the Public Wells layer and export the data. For additional information on these tool functionalities, see the help documentation on the About page of the tool. Notes for Consideration: The Well Density layer provided in this application is derived from proprietary wellbore data, the records of which do not always contain values for key features (status, type, true vertical depth, or spud year). Therefore, data might not be available when layers are queried for all filter combinations. Additionally, visualizing layers and applying filters may take additional time to load (i.e., draw on the map) due to the large size of the data.

ccs↗
DOE OSTI2024

EV SALaD 2023 Demonstration: Best Practices and Mitigations for Protecting EVSE Infrastructure

The Electric Vehicle Secure Architecture Laboratory Demonstration (EV SALaD) program is a demonstration of cybersecurity best practices for high-power electric vehicle (EV) charging infrastructure led by Idaho National Laboratory (INL), in collaboration with other DOE National Laboratories participating in the EVs at Scale Consortium.a Sandia National Laboratories (SNL) and Pacific Northwest National Laboratory (PNNL) participated in the first 2-year (FY22-23) demonstration cycle for EV SALaD. This report documents the FY23 demonstration, the second in a series of demonstrations and collaborations in deploying and operating cybersecure EV charging infrastructure. It includes a summary of improvements from the FY22 demonstration, technical analysis of the FY23 demonstration, how the research demonstrates cyber-physical and cybersecurity best practices for high-power EV charging infrastructure, and related impacts to national and energy security. For EV SALaD, the FY22 demonstration focused on the detection, ranking, and prioritization of anomalous events for high-power EV charging. The FY23 demonstration additionally included the demonstration of cybersecurity best practices, which included protection and mitigation solutions to prevent, respond, and recover from anomalous events. During the demonstrations, the multi-lab EV SALaD team conducted a Test Effect Payload (TEP)b evaluation on extreme fast charger (XFC) hardware equipped with Cerberus, a detection and response solution, to demonstrate anomaly detection and mitigation cybersecurity best practices against cyber-enabled events.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Upscaling Methods Applied to a Fine-Scale Reservoir Model

This study was conducted as part of the Southwest Regional Partnership on Carbon Sequestration (SWP) project to evaluate how upscaling fine-scale simulation models to coarse-scale simulation models impacted the results. The focus was on the Farnsworth Unit (FWU) and its Morrow' B' Sandstone reservoir, specifically the west half of the field. Due to data limitations and the geologic characteristics of the surrounding area, the upscaling was limited to the west half of the FWU rather than a broader basinscale model. The primary aim was to explore how upscaling impacts numerical simulation models, particularly regarding CO 2 -enhanced oil recovery (EOR) and storage capacity predictions. Upscaling was necessary to reduce computational demands when transitioning from high-resolution geological models to coarser grids, as large-scale simulations with finer grids can be computationally prohibitive. This study expands on previous work by the SWP to understand how additional upscaling, applied to already fine-scale numerical simulation models, affects reservoir performance simulations (Ampomah, Balch, & Grigg, 2015). This is key to understanding how loss of resolution can affect coarsescale model results that may be used for large sensitivity analyses, uncertainty quantifications, and training data for machine learning applications.

02 PETROLEUM↗
DOE OSTI2025

MRCI Subtask 2.2: Precambrian Basement Structure, Faulting, and Stress Final Technical Summary Report

Subtask 2.2 was largely focused on compiling information about the Precambrian basement rock that underlies the MRCI region. Understanding the nature and extent of the basement rock is important in order to mitigate certain risks associated with CO2 injection. For example, this information will provide a resource for defining areas where a storage reservoir is in direct contact with the Precambrian or indirectly via a fault. Also, an understanding of the stress field in addition to fault orientations will help determine which faults may be subject to reactivation under increased pore pressures.

Battelle,CCS,CCUS,Carbon storage,MRCI,Midwest Regi↗
DOE OSTI2025

MRCI Task 5: Promoting Regional Technology Transfer Final Summary Report

The goal of the MRCI Task 5 – Promoting Regional Technology Transfer is to leverage existing and new relationships with critical CCUS stakeholders (national and international stakeholders include state geological surveys, universities, industrial partners and advisors, energy production and utilization companies, and NGOs) within the regional initiative and globally and become a key resource for CCUS information, acceptance, and development. Work completed under Task 5 is categorized through four actions: • Promote acceleration of CCUS deployment by providing general support for commercialization and technology transfer • Compile and communicate information from previous tasks to interested stakeholders • Engage with federal and state governments, industry consortia and NGOs • Engage with global institutions

CCUS,Midwest,Midwest Regional Carbon Initiative,Mi↗
DOE OSTI2026

Transformational Sorbent System for Post-Combustion Carbon Capture (Final Report)

As part of this DOE Contract (Transformational Sorbent System for Post-Combustion Carbon Capture, DE-FE0031734),TDA Research Inc. developed a transformational sorbent system for post combustion CO 2 capture process that captures more than 95% of CO 2 emissions from a coal fired power plant, recovering CO 2 at 95% purity with a cost of CO 2 capture significantly lower than with amine-based system (~$30 per tonne (MT) of CO 2 captured). TDA’s transformational sorbent system uses a novel, highly stable, high-capacity metal organic framework (MOF) based CO 2 sorbent in a new vacuum/concentration swing adsorption (VCSA) process that allows us to use high efficiency vacuum pumps with a low auxiliary load. A pulverized coal fired power plant equipped with TDA’s transformational sorbent system for post combustion CO 2 capture is expected to efficiently produce electricity with a low Cost of Electricity (COE) and capture greater than 95% of the CO 2 from the power plant exhaust.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Optimizing Alabama’s CO 2 Storage in Shelby County (Project OASIS) Milestone 6.0: Evaluation of Class VI Readiness

Introduction. Project OASIS is approximately 30 miles southeast of Birmingham, Alabama, and approximately 5 miles north-northwest of Alabama Power Company's Plant Gaston. Geologically, the Project area is in the Alabama fold and thrust belt province. This work builds on the initiatives of the Southeast Regional Carbon Utilization and Storage Acceleration Partnership (SECARB-USA, DE-FE0031830) that identified nearly 500 million metric tonnes of CO 2 emitted on an annual basis that is not collocated with prospective storage geology (the Coastal Plain of the Southeastern US in this context). This observation suggests costly investments in connective infrastructure (e.g., pipelines) or exploratory well drilling campaigns to identify CO 2 storage opportunities in under explored areas. While not traditionally thought of for saline storage, these studies suggest that storage prospects in the Valley and Ridge Province occur in relatively flat lying structural panels between thrust faults. For the Project OASIS region, available geologic studies related to hydrocarbon exploration suggest that Cambro-Ordovician carbonates and Cambrian clastic units offer multiple potential storage intervals, and that regional confining systems are present, such as the tectonically thickened Floyd-Parkwood Shale. The Project OASIS surface property is owned by a timber and land stewardship company, The Westervelt Company, Inc., who worked with the Project Team to select and prepare adequate sites for geologic assessment. The purpose of drilling the Westover Stratigraphic Test Well #2 was to collect geologic data to model the feasibility of commercial scale CO 2 injection and storage in an under explored region. This initiative benefits the regions emitters as the data generated from this study can inform their own internal decision making. The field program included geological and geophysical evaluations, reservoir engineering analyses, and risk assessments. This report evaluates existing data, as well as a variety of modeling scenarios to evaluate project readiness. Importantly, the impact of this study is not limited to Alabama as there are numerous large emitters throughout Appalachia, in similar geologic settings, contemplating their decarbonization options.

20 FOSSIL-FUELED POWER PLANTS↗