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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 361 records · Page 20

Tunable Rapid Uptake Amino Polymer Aerogels for Direct Air Capture of Carbon Dioxide (Final Scientific/Technical Report)

The Palo Alto Research Center (PARC) developed a novel CO 2 adsorbent material, and in collaboration with Lawrence Livermore National Laboratory (LLNL), demonstrated its state-of-the-art performance for direct air capture. The target application for this technology is in direct air carbon capture and storage (DACCS), for which the adsorbent material provides the critical function of binding CO 2 from ambient air. At the beginning of the project, the technology concept and application were established, representing technology readiness level (TRL) 2. The hypothesis was that a microporous polymer comprising a high density of primary amines would make an exceptional adsorbent for direct air capture, and the goal of the project was to prove that hypothesis and advance the technology to TRL 3. To accomplish this, we approached the challenge from the perspective of materials synthesis optimization with the narrow focus of achieving the target material properties. This approach was successful, and we now have a synthetic procedure that results in a novel adsorbent material with the target material properties. The chemical name for the novel adsorbent material is poly(vinylamine-co-divinylbenzene) (PVAm-DVB).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

All-digital Sensor System for Distributed Downhole Pressure Monitoring in Unconventional Fields

This project developed and validated (through field tests) a new low-cost all-digital pressure sensing technology for in situ distributed downhole pressure monitoring in unconventional oil and gas (UOG) fields. The all-digital sensing technology uses a built-in non-electric analog-to-digital converter (ADC) to transform the pressure information into a combination of binary (ON/OFF) states. As such, the system does not need downhole electronics for signal conditioning and telemetry. The all-digital sensors can be remotely logged over a long distance, and many sensors can be multiplexed for distributed sensing. Based on a review of unconventional wells in the Lower 48 states, the specification of the sensor is to measure pressure up to 69 MPa (10,000 psi) and temperature up to 250°C. A sensor with a helical bourdon sensing element and a digital signal decoder of 50 mm diameter and 109 mm length was constructed. The helical bourdon sensing element was made of 304L stainless steel and filled with motor oil. The digital converter was made up of 8 digital reading pads constructed of high-temperature epoxy with conductive inserts made of stainless steel. The sensor had a linear response to pressure with an accuracy of 0.14 MPa (20 psi). To withstand the high pressure, the sensor was enclosed in a stainless-steel pressure housing with a wall thickness of 5.5 mm, a diameter of 73 mm, and a length of 724 mm. In the laboratory tests, the sensor exhibited no temperature-related effects on the results. The sensor did not show drift over a 14-day test period at elevated pressure. A field test was conducted where the sensor was deployed in a test wellbore at the Quest drilling test facility to a depth of 0 feet over three weeks. The sensor was attached to the production rods, along with a downhole reference sensor of PPS27 type, which is a permanent downhole monitoring system. During the testing phase, the test well annular blow-out preventer was closed, and the well was pressurized at the surface to 11 MPa (1600 psi). The sensor read the elevated bottom hole pressure of 1500 psi. A multiplexing unit was created for the sensor to deploy multiple sensors on one data transmission line in a distributed approach. The multiplexing unit was tested in a simulated environment of 3048 m (10,000 ft) with five sensors distributed. The sensors were pressurized at different intervals. The multiplexed sensors recorded the correct pressure, and the multiplexing did not interfere with the readings. The proposed concept of an all-digital pressure sensor for harsh downhole environments was designed, manufactured, and tested in the laboratory and tested at the field to a up to 69 MPa and 250°C. This technology has high-temperature tolerance and has potential in downhole areas outside oil and gas, such as carbon capture and storage (CCS) and geothermal wells. The sensor concept has been proven in this project, but to create a commercially viable product, manufacturing a sensor with a smaller diameter needs to be performed.

02 PETROLEUM↗

SimCCS 3.0 User GUIDE

Carbon Capture and Storage (CCS) is an important technology aimed at reducing CO 2 emissions and contributing to the mitigation strategies of climate change. The process involves three main steps: CO 2 capture, transport, and storage. Specifically, CO 2 is captured from industrial facilities, such as coal-fired power plants and natural gas processing plants. It is then transported through infrastructure networks, such as pipelines, rails, and ships, and injected into underground geological formations, such as depleted oil and gas reservoirs or deep saline aquifers, for permanent storage. The entire CCS value chain encompasses multiple components, including CO 2 sources, transport networks, and storage sites. The proper design of CCS transport infrastructure is an essential step for the deployment of CCS technology. However, the design is not a trivial process, as it presents many challenges and requires consideration of numerous economic, social, and environmental factors.

42 ENGINEERING↗

A Geodatabase Designed to Inform and Support Safe CO2 Transport-Route Planning

The National Energy Technology Laboratory developed the Carbon Capture and Storage (CCS) Pipeline Route Planning Database to inform safe and sustainable CO2 transport planning in support of decarbonization efforts. This comprehensive Esri Geodatabase contains over 90 GBs of data and 60+ spatial layers representing key considerations including natural hazards, infrastructure, energy, and social justice. Leveraging ArcGIS Pro, nationwide raster, and vector datasets containing millions of features were processed to be easily digestible for users and complex modeling software.

Romeo, Lucy↗

Community Sentiment Analysis with Focus on CCS

This research assesses community sentiment towards Carbon Capture and Storage (CCS) as depicted in digital media, focusing on themes such as emissions, transport, and storage. Utilizing the VADER sentiment analysis model, the study analyzed titles and descriptions from online news articles to capture immediate impressions and sentiments. Results indicate a predominantly positive sentiment towards CCS, with significant regional variations. States like Alabama and Texas exhibit high positive sentiment, likely due to economic ties to the energy industry, while states like Delaware and Utah show negative sentiment, potentially driven by environmental concerns. The significance of this study lies in its potential to inform policy and communication strategies for CCS implementation. Understanding public sentiment is crucial for the success of CCS projects as it helps to identify and address community concerns. Media influence plays a significant role in shaping public opinion, and this study highlights the need for effective communication strategies to promote the benefits of CCS while addressing any misconceptions. By providing insights into regional differences in sentiment, this research supports the development of tailored interventions that can enhance public acceptance and support for CCS initiatives, ultimately contributing to the success of efforts to mitigate climate change through reduced greenhouse gas emissions.

White, Casey↗

ML-Based Rock Properties and Seismic Volume Enhancement

This project aims to improve field-scale Carbon Capture and Storage (CCS) assessments by enhancing petrophysical and geophysical log predictions through machine learning and neural networks. In our work during EY23, we applied Conditional Variational Autoencoders (CVAEs) to predict compressional velocity (Vp) and assess CO2 saturation levels in geological formations at the Illinois Basin Decatur Project (IBDP). In another task, we improved full-waveform inversion (FWI) methods with machine-learning approaches using lithological constraints. Full-waveform inversion (FWI) of seismic data estimates the elastic properties of subsurface rocks with high spatial resolution.

Nathanail, Athanasios↗

ML-based Dimension Reduction Strategies

Deep learning (DL)--based surrogate models have achieved success in various applications in carbon capture and storage (CCS). However, the model training on high-dimensional spaces is computationally expensive and impractical for large-scale and complex geological models, because the models usually contain hundreds of thousands to millions of grid cells, each with a set of parameters. Furthermore, the high cost of generating training data with sufficient variation is another limitation of model training on high-dimensional spaces, which may result in overfitting and reduce the model efficiency and prediction performance. We proposed the workflow incorporating dimension reduction methods and deep learning models, which aim to extract the latent variables of input parameters and output state variables, and then build the mapping function at the latent spaces. The proposed workflow can significantly reduce the computational complexity in solving both forward and inverse problems compared to models trained on high-dimensional spaces. Dimensionality reduction models showed great potential in workflows for fast reservoir simulation, history matching, prior model generation, visualization, and more, ultimately enhancing DL model performance in related SMART Work Packages.

Hosseini, Seyyed↗

Cost and Performance Baseline for Fossil Energy Plants – Volume 1: Bituminous Coal and Natural Gas to Electricity: May 2025

This presentation at EPRI's annual Generation Sector Meeting during the Advanced Generation and Carbon Capture and Storage session provides an overview of the recently published Cost and Performance Baseline for Fossil Energy Plants – Volume 1: Bituminous Coal and Natural Gas to Electricity dated May 2025. It further connects viewers with the recently released tool/dashboard, an interactive tool that allows users to manipulate six key study parameters simultaneously for each case and visualize the impact on three metrics: 1) levelized cost of electricity (LCOE), 2) cost of CO2 captured (CCC), and 3) cost of CO2 avoided (CCA).

baseline study↗

CO2 Streams Captured From Industrial Processes and Corrosion of Steel Pipelines

Based on the knowledge accumulated in the last decade related to Carbon Capture and Storage (CCS) processes and the identified gaps in knowledge, our study identifies and quantifies the key issues that impact the corrosion of materials, specifically relating to the integrity of structures for the CO2 transport pipelines and provides a better understanding of the materials’ compatibility with CO2 steams with impurities. This will help to understand the corrosion risks associated with CO2 transport and injection and leverage existing infrastructure or rebuild new pipeline networks to transport CO2 with impurities for EOR or geological storage.

CO2 corrosion↗

Summary of Carbon Dioxide Pipeline Systems and Incident Data in North America

Pipelines are historically seen as the primary transportation mode for carbon dioxide (CO 2 ) streams in the context of carbon capture and storage (CCS) and oil and gas industries. Pipeline transmission of CO 2 over longer distances is regarded as most efficient and economical when the CO 2 is in the dense phase, i.e., in liquid or supercritical regime, due to transporting CO 2 in dense phase that allows for a smaller-diameter pipeline to move a given flow, which optimizes project cost.

42 ENGINEERING↗

Performance and Cost Potential for Direct-Fired Supercritical CO2 Natural Gas Power Plants

Direct-fired supercritical CO2 (sCO2) power cycles are being explored as an attractive alternative to natural gas combined cycle (NGCC) plants with carbon capture and storage (CCS). Therefore, understanding their performance and cost potential is important for the commercialization of the technology. This study presents the techno-economic optimization results of natural gas-fired, utility-scale power plants based on the direct sCO2 power cycle, which are lacking in public literature. To identify the optimum plant configuration, the study considered multiple cases with varying levels of thermal integration with the plant air separation unit (ASU). Several design variables for each power cycle configuration were identified and optimized to minimize the levelized cost of electricity (LCOE) for each case. The optimization design variables include the sCO2 cooler outlet temperatures, recuperator approach temperatures, and pressure drops. High fidelity models for recuperators, coolers, and turbines were developed and used to capture the impact of design variables on plant efficiency and capital costs. The optimization was conducted using a combination of manual sensitivity analyses and automated derivative-free optimization algorithms available under NETL’s Framework for Optimization and Quantification of Uncertainty and Sensitivity platform. The optimized direct sCO2 power plants offered similar or slightly higher plant efficiencies than the reference NGCC plants based on the F-class gas turbine with CCS. The LCOE of the optimized direct sCO2 plants is 13 to 17% higher than the reference NGCC plants with CCS due to high capital costs associated with the ASU and sCO2 power block, though there is significant room for improvement due to the high uncertainty in component capital costs for these new plants. Recuperators make up over 50% of the sCO2 power block costs. Consequently, any research and development efforts to reduce the recuperator capital costs will benefit the technology’s commercialization. The study also presents preliminary results showing the impact of co-firing landfill gas and natural gas on plant efficiency, LCOE, and CO2 emissions.

Pidaparti, Sandeep↗

Performance and Cost Potential for Direct-Fired Supercritical CO2 Natural Gas Power Plants

Direct-fired supercritical CO2 (sCO2) power cycles are being explored as an attractive alternative to natural gas combined cycle (NGCC) plants with carbon capture and storage (CCS). Therefore, understanding their performance and cost potential is important for the commercialization of the technology. This study presents the techno-economic optimization results of natural gas-fired, utility-scale power plants based on the direct sCO2 power cycle, which are lacking in public literature. To identify the optimum plant configuration, the study considered multiple cases with varying levels of thermal integration with the plant air separation unit (ASU). Several design variables for each power cycle configuration were identified and optimized to minimize the levelized cost of electricity (LCOE) for each case. The optimization design variables include the sCO2 cooler outlet temperatures, recuperator approach temperatures, and pressure drops. High fidelity models for recuperators, coolers, and turbines were developed and used to capture the impact of design variables on plant efficiency and capital costs. The optimization was conducted using a combination of manual sensitivity analyses and automated derivative-free optimization algorithms available under NETL’s Framework for Optimization and Quantification of Uncertainty and Sensitivity platform. The optimized direct sCO2 power plants offered similar or slightly higher plant efficiencies than the reference NGCC plants based on the F-class gas turbine with CCS. The LCOE of the optimized direct sCO2 plants is 13 to 17% higher than the reference NGCC plants with CCS due to high capital costs associated with the ASU and sCO2 power block, though there is significant room for improvement due to the high uncertainty in component capital costs for these new plants. Recuperators make up over 50% of the sCO2 power block costs. Consequently, any research and development efforts to reduce the recuperator capital costs will benefit the technology’s commercialization. The study also presents preliminary results showing the impact of co-firing landfill gas and natural gas on plant efficiency, LCOE, and CO2 emissions.

Pidaparti, Sandeep↗

Decarbonization of the power sector with CCS: Case study in two regions in the U.S. and lessons for Latin America

This work consists of estimates of potential changes in the total systems cost (TSC) of two RTOs of the United States (U.S.), MISO-N and SPP RTO West, under the traditional decarbonization pathway of replacement of fossil-power plants with variable renewable energy (VRE) and the less traditional pathway of retrofitting fossil fuel units with carbon capture and storage (CCS). Although the power mixes of MISO-N and SPP RTO West are particular to these regions, results can apply to other regions, including Latin American countries that are planning to decarbonize their power sectors. This case study serves to highlight lessons on differences in technology costs between these two pathways, as well as the cost associated with decarbonization rates close to 100%.

Pena-Cabra, Ivonne A.↗

Decarbonization of the power sector with CCS: Case study in two regions in the U.S. and lessons for Latin America

This paper estimates potential changes in the total systems cost (TSC) of two RTOs of the United States (U.S.), MISO-N and SPP RTO West, under the traditional decarbonization pathway of replacement of fossil-power plants with variable renewable energy (VRE) and the less traditional pathway of retrofitting fossil fuel units with carbon capture and storage (CCS). Although the power mixes of MISO-N and SPP RTO West are particular to those regions, the results can apply to other regions, including Latin American countries that are planning to decarbonize their power sectors. This case study serves to highlight lessons on the difference of technology costs between these two pathways, as well as the cost associated with decarbonization rates close to 100%.

Pena-Cabra, Ivonne A.↗