Search NASA⌕ Search

SEARCH · Search NASA

Results for “industrial capture”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Scale-up Testing of Advanced Polaris Membrane in CO2 Capture Technology

This final technical report describes work conducted by Membrane Technology and Research, Inc. (MTR) for the U.S. Department of Energy (DOE), National Energy Technology Lab (NETL) on the scale-up and testing of advanced Polaris™ membrane CO2 capture technology at the Technology Centre Mongstad (TCM) under award number DE-FE0031591. The work was performed from August 1, 2018 through January 31, 2023. The overall goal of this project was to design, build and operate an advanced Polaris membrane CO2 capture system at TCM. MTR was assisted in this project by Trimeric Corporation (Trimeric), an engineering design services company, the Carbon Capture Simulation for Industry Impact (CCSI2), a partnership among national laboratories, industry, and academic institutions, and the Technology Centre Mongstad (TCM), who provided the host site for the slipstream field test. This report details the work conducted to scale-up MTR’s second-generation (Gen-2) Polaris membrane and advanced planar membrane modules to a final form factor optimized for commercial use; validate their performance in an engineering-scale field test at TCM; and to show the potential of the MTR process to meet DOE CO2 capture targets from large source point emitters. Work for this project included membrane optimization and scale-up, advanced planar module design and fabrication, design and fabrication of an engineering-scale field test membrane skid, operation of the field test skid processing Residue Fluid Catalytic Cracker (RFCC) industrial flue gas at TCM, and a detailed techno-economic analysis (TEA) of the MTR membrane post-combustion process for CO2 capture. This project validated recent membrane technology advancements at the engineering-scale, moves the MTR advanced post-combustion capture technology to TRL-6, and mitigates risk in future Large Pilot or Demonstration scale-up activities.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Application of Sequential Design of Experiments (SDoE) to Large Pilot-Scale Solvent-Based CO2 Capture Process at Technology Centre Mongstad (TCM)

The United States Department of Energy’s Carbon Capture Simulation for Industry Impact (CCSI2) program has developed a framework for sequential design of experiments (SDoE) that aims to maximize knowledge gained from budget- and schedule-limited pilot scale testing. SDoE was applied to the planning and execution of campaigns for testing CO2 capture systems at pilot-scale in order to optimally allocate resources available for the testing. In this methodology, a stochastic process model is developed by quantifying the parametric uncertainty in submodels of interest; for a solvent-based CO2 capture system, these may include physical properties and equipment performance submodels (e.g., mass transfer, interfacial area). This uncertainty is propagated through the full process model, over variable operating conditions, for estimating the resulting uncertainty in key model outputs (e.g., percentage of CO2 capture, solvent regeneration energy requirement). In developing a data collection plan, the predicted output uncertainty is incorporated into an algorithm that seeks simultaneously to select process operating conditions for which the predicted uncertainty is relatively high and to ensure that the entire space of operation is well represented. This test plan is then used to guide operation of the pilot plant at varying steady-state conditions, with resulting process data incorporated into the existing model using Bayesian inference to refine parameter distributions. The updated stochastic model, with reduced parametric uncertainty from data collected, is then used to guide additional data collection, thus the sequential nature of the experimental design. The SDoE process was implemented at the pilot test unit (12 MWe in scale) at Norway’s Technology Centre Mongstad (TCM) in a summer 2018 test campaign with aqueous monoethanolamine (MEA). During the test campaign, the varied operating conditions included the flowrates of circulated solvent, flue gas, and reboiler steam and the CO2 concentration in the flue gas. The process data were used to update probability distributions of mass transfer and interfacial area parameters of a stochastic process model developed by the CCSI2 team. Two iterations of the SDoE process were executed, resulting in the uncertainty in model predicted CO2 capture percentage decreasing by an average of 58.0 ± 4.7% over the full input space of interest. This work demonstrates the potential of the SDoE process for model refinement through reduction in process model parametric uncertainty, and ultimately risk in scale-up, in CO2 capture technology performance.

carbon capture↗
DOE OSTI2026

A Review on Direct Air Capture of Carbon Dioxide: Sorbent Materials, Process Engineering, Industrial Scale-Up, and Future Perspectives

The relentless accumulation of anthropogenic greenhouse gases has driven atmospheric carbon dioxide concentrations to approximately 426 ppm, necessitating the aggressive deployment of negative-emission technologies to achieve net zero by 2050. Direct air capture (DAC) offers a scalable, location-independent approach to atmospheric carbon removal; however, it is fundamentally constrained by the significant thermodynamic barriers associated with capturing CO 2 from ultradilute ambient conditions, requiring minimum thermodynamic energy inputs substantially higher than those for postcombustion point sources. This comprehensive review critically examines the technological landscape of DAC, focusing on the interdependent triad of sorbent material design, contactor engineering, and regeneration thermodynamics. We evaluate the fundamental boundaries of adsorption, emphasizing that an optimal adsorption enthalpy and isosteric heat of adsorption must balance the high CO 2 uptake capacity with the energetic penalties of sorbent regeneration. A systematic, comparative analysis of state-of-the-art sorbents is presented, encompassing mesoporous silicas, zeolites, carbon-based materials (CBMs), metal−organic frameworks (MOFs), porous organic polymers (POPs), and polymeric membranes. Special attention is devoted to surface functionalization strategies, particularly amine grafting and impregnation, which transition capture mechanisms from physisorption to chemisorption to enhance selectivity under ambient moisture and low partial pressures. Furthermore, we assess the operational merits of various reactor configurations, including gas−solid, gas−liquid, and membrane contactors, alongside regeneration cycles such as temperature, vacuum, pressure, and moisture swing adsorption. Finally, the review bridges fundamental materials science with industrial application by chronicling the scale-up milestones of pioneering entities and providing a strategic roadmap for advancing DAC technology readiness levels toward global deployment.

Adsorption↗
DOE OSTI2024

Highly Permeable Rubbery Thin Film Composite Membranes for CO2 Capture from Steel Mills

This presentation will report the rational design and fabrication of NETL’s highly permeable non-aging thin film composite (TFC) membranes for CO2 capture from various industrial point sources. This talk will also cover the design, computational fluid dynamic simulation, 3D printing, and permeation testing of plate-and-frame membrane modules for an upcoming field demonstration at U. S. Steel’s Edgar Thomson Plant in Braddock, PA. The field test will demonstrate membrane-based CO2 capture from a blast furnace for decarbonization of steel manufacturing for the first time in the U.S. A mobile gas permeation test unit is currently under design and construction for the field test, which is scheduled to take place in 2025.

Zhu, Lingxiang↗
DOE OSTI2020

A single-component water-lean post-combustion CO 2 capture solvent with exceptionally low operational heat and total costs of capture – comprehensive experimental and theoretical evaluation

A comprehensive evaluation of a recently developed water-lean amine-based solvent, namely N-(2-ethoxyethyl)-3-morpholinopropan-1-amine (2-EEMPA), has been performed to analyze its post-combustion CO 2 capture performance. This evaluation comprises (1) fundamental characterization of the solvent–CO 2 interaction using vapor–liquid equilibria, kinetics and viscosity measurements; (2) process characterization of the CO 2 capture performance as measured in a laboratory scale continuous flow system and via Aspen Plus® simulation using a flue gas simulant; as well as (3) a full techno economic analysis of the capture process at industrial scale with corresponding projections of critical metrics. This paper summarizes the many parts of this comprehensive evaluation and shows how the various parts come together to empower validated conclusions about its process performance. Notably, it is projected that this solvent can operate at a regeneration heat rate of 2.0 GJ per tonne CO 2 for post-combustion capture, and at a total cost of capture of $50.6/tonne CO 2 . Overall, with further process optimization significant reductions in the capture cost are predicted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Integrated Approach to CO 2 Capture and Conversion to Cyclic Carbonates under Solvent- and Additive-Free Conditions Utilizing the CO 2 Capture Solvent EEMPA

An integrated CO 2 capture and conversion to materials (IC 3 M) implementation utilizing a CO 2 capture solvent is an efficient approach to reduce the amount of CO 2 in the atmosphere while producing value-added chemicals. In this work, we demonstrate that the advanced water-lean CO 2 capture solvent, N-(2-Ethoxyethyl)-3-morpholinopropan-1-amine (EEMPA), can catalyze the cycloaddition reaction between CO 2 and propylene oxide to produce the value-added chemical propylene carbonate in an IC 3 M fashion. When excess propylene oxide is used relative to EEMPA, yields as high as 75% with 85% selectivity toward propylene carbonate can be achieved under solvent-free conditions without the need of additives/cocatalysts. The reaction temperature (120 °C) is comparable to that used in the thermal regeneration of the capture solvent under industrial conditions. Formation of an undesired amino alcohol side product was observed, but it may be reversible or avoidable with continued research despite the unsuccessful initial attempts. Finally, we show that this can be applied to other epoxides for the production of various cyclic carbonates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Membrane Development for CO2 Capture from Steel Manufacturing

The U.S. government is targeting a net-zero carbon-emission economy by 2050, offering an exciting opportunity for membrane-based CO2 capture from various industrial point sources. Given that industrial flue gas has low CO2 partial pressures and high volumetric flow rates, high-permeance membranes are needed to make membrane technology economically viable for large-scale deployment. Thin film composite (TFC) membranes are necessary for this implementation because they can provide high permeance by forming a thin selective layer on top of a porous support. This presentation will report the rational design and fabrication of NETL’s highly permeable non-aging TFCs achieved by: synthesizing a high-performance rubbery selective material; developing a high-porosity membrane support; optimizing coating methods to assemble the two materials into scalable membranes; and scaling up membrane supports and TFCs via a roll-to-roll process. The novel rubbery selective material shows mixed-gas CO2 permeability of 930 Barrer and CO2/N2 selectivity of 44, exceeding the 2008 Robeson upper bound. The resulting TFCs yield remarkably high CO2 permeance of 4,500 GPU and CO2/N2 selectivity of 34 at 23ºC. Moreover, the TFCs exhibit not only excellent performance stability (or non-aging behavior) for 1,000 hours in the lab, but also maintain their separation properties in a 700-hour field test at the U.S. DOE’s National Carbon Capture Center using real humid flue gas.

Tran, Thien↗
DOE OSTI2021

Synthetic Methanol/Fischer–Tropsch Fuel Production Capacity, Cost, and Carbon Intensity Utilizing CO 2 from Industrial and Power Plants in the United States

Captured CO 2 is a potential feedstock to produce fuel/chemicals using renewable electricity as the energy source. In this study, we explored resource availability and synergies by region in the United States and conducted cost and environmental analysis to identify unique opportunities in each region to inform possible regional and national actions for carbon capture and utilization development. This study estimated production cost of synthetic methanol and Fischer–Tropsch (FT) fuels by using CO 2 captured from the waste streams emitted from six industrial [ethanol, ammonia, natural gas (NG) processing, hydrogen, cement, and iron/steel production plants] and two power generation (coal and NG) processes across the United States. The results showed that a total of 1594 million metric ton per year of waste CO 2 can be captured and converted into 85 and 319 billion gallons of FT fuels and methanol, respectively. FT fuels can potentially substitute for 36% of the total petroleum fuels used in the transportation sector in 2018. Technoeconomic analysis shows that the minimum selling prices for synthetic FT fuels and methanol are 1.8–2.8 times the price of petroleum fuel/chemicals, but the total CO 2 reduction potential is 935–1777 MMT/year.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

High-Throughput Screening and Accurate Prediction of Ionic Liquid Viscosities Using Interpretable Machine Learning

Ionic liquids (ILs) are a novel group of green solvents with great promise for various industrial applications, including carbon capture and lignocellulosic biomass deconstruction. However, the use of ILs at the industrial scale remains challenging due to their high viscosities at ambient temperatures. To develop ILs with lower viscosities, a systematic study of their quantitative structure–property relationship (QSPR) is desirable. Here, we developed four machine learning (ML) models to predict viscosity at various temperature and pressure ranges, trained over a wide range of ILs consisting of various cationic and anionic families. ML methods including two-factor polynomial regression (two-factor PR), support vector regression (SVR), feed-forward neural networks (FFNN), and categorical boosting (CATBoost) were developed based on features that have proven useful in previous ML studies: COSMO-RS (conductor-like screening model for real solvents)-derived surface screening charge densities (sigma profiles). FFNN and CATBoost were the most accurate in predicting IL viscosities with lower average absolute relative deviation and higher R2 values on the test set. Tanimoto similarity scores were calculated to characterize the chemical space and structural similarity of the investigated ions. Furthermore, SHapley Additive exPlanation (SHAP) analysis was employed to interpret the ML results. Temperature, the polar area of ILs, and the nonpolar regions of ions are key features that influence the viscosity predictions. Importantly, the IL viscosity prediction here is the most accurate reported to date.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Extensive Attention Mechanisms in Graph Neural Networks for Materials Discovery

We present our research where attention mechanism is extensively applied to various aspects of graph neural net- works for predicting materials properties. As a result, surrogate models can not only replace costly simulations for materials screening but also formulate hypotheses and insights to guide further design exploration. We predict formation energy of the Materials Project and gas adsorption of crystalline adsorbents, and demonstrate the superior performance of our graph neural networks. Moreover, attention reveals important substructures that the machine learning models deem important for a material to achieve desired target properties. Our model is based solely on standard structural input files containing atomistic descriptions of the adsorbent material candidates. We construct novel methodological extensions to match the prediction accuracy of state-of-the-art models some of which were built with hundreds of features at much higher computational cost. We show that sophisticated neural networks can obviate the need for elaborate feature engineering. Our approach can be more broadly applied to optimize gas capture processes at industrial scale.

Cong, Guojing↗
DOE OSTI2024

Streamlining heterologous expression of top carbonic anhydrases in Escherichia coli : bioinformatic and experimental approaches

Carbonic anhydrase (CA) enzymes facilitate the reversible hydration of CO 2 to bicarbonate ions and protons. Identifying efficient and robust CAs and expressing them in model host cells, such as Escherichia coli, enables more efficient engineering of these enzymes for industrial CO 2 capture. However, expression of CAs in E. coli is challenging due to the possible formation of insoluble protein aggregates, or inclusion bodies. This makes the production of soluble and active CA protein a prerequisite for downstream applications. In this study, we streamlined the process of CA expression by selecting seven top CA candidates and used two bioinformatic tools to predict their solubility for expression in E. coli. The prediction results place these enzymes in two categories: low and high solubility. Our expression of high solubility score CAs (namely CA5-SspCA, CA6-SazCAtrunc, CA7-PabCA and CA8-PhoCA) led to significantly higher protein yields (5 to 75 mg purified protein per liter) in flask cultures, indicating a strong correlation between the solubility prediction score and protein expression yields. Furthermore, phylogenetic tree analysis demonstrated CA class-specific clustering patterns for protein solubility and production yields. Unexpectedly, we also found that the unique N-terminal, 11-amino acid segment found after the signal sequence (not present in its homologs), was essential for CA6-SazCA activity. Overall, this work demonstrated that protein solubility prediction, phylogenetic tree analysis, and experimental validation are potent tools for identifying top CA candidates and then producing soluble, active forms of these enzymes in E. coli. The comprehensive approaches we report here should be extendable to the expression of other heterogeneous proteins in E. coli.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Abstract for CRADA among National Energy Technology Laboratory, Research Triangle Institute, Lawrence Livermore National Laboratory, and Los Alamos National Laboratory (AGMT-0921)

Through the Carbon Capture Simulation for Industry Impact (CCSI 2 ) project, the National Energy Technology Laboratory (NETL), Lawrence Livermore National Laboratory (LLNL), and Los Alamos National Laboratory (LANL) (herein collectively “the CCSI 2 team”) will collaborate through a CRADA with the Research Triangle Institute (RTI). This collaboration will develop a modeling framework of RTI’s Non-Aqueous Solvent (NAS) process using physical and thermodynamic data and models previously developed by RTI. RTI will provide existing models and data on its NAS system to inform the model construction effort by the CCSI 2 team.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Highly Permeable Rubbery Thin Film Composite Membranes for CO2 Capture from Steel Mills

For presentation at the 2024 AIChE Annual Meeting, San Diego, CA, October 27-31, 2024. High-permeance and CO2-selective membranes are needed to make membrane technology economically viable for large-scale deployment of carbon capture from various industrial point sources such as steel mills. Thin film composite (TFC) membranes are necessary for this practical implementation because they can provide high permeance by forming a thin selective layer on top of a porous support layer. This presentation reports the rational design and fabrication of National Energy Technology Laboratory’s highly permeable non-aging TFC membranes achieved by: (1) synthesizing a high-performance rubbery selective material; (2) developing a high-porosity membrane support; (3) optimizing coating methods to assemble the two materials into scalable membranes; and (4) scaling up membrane supports and TFCs via a roll-to-roll process. This talk will also cover the design, computational fluid dynamic simulation, 3D printing, construction, and permeation testing of plate-and-frame membrane modules for an upcoming field demonstration at U. S. Steel’s Edgar Thomson Plant in Braddock, PA.

Zhu, Lingxiang↗
DOE OSTI2022

Probing Electrolyte Influence on CO 2 Reduction in Aprotic Solvents

Selective CO 2 capture and electrochemical conversion are important tools in the fight against climate change. Industrially, CO 2 is captured using a variety of aprotic solvents due to their high CO 2 solubility. However, most research efforts on electrochemical CO 2 conversion use aqueous media and are plagued by competing hydrogen evolution reaction (HER) from water breakdown. Fortunately, aprotic solvents can circumvent HER, making it important to develop strategies that enable integrated CO 2 capture and conversion. However, the influence of ion solvation and solvent selection within nonaqueous electrolytes for efficient and selective CO 2 reduction is unclear. In this work, we show that the bulk solvation behavior within the nonaqueous electrolyte can control the CO2 reduction reaction and product distribution occurring at the catalyst-electrolyte interface. We study different tetrabutylammonium (TBA) salts in two electrolyte systems with glyme ethers (e.g., 1,2 dimethoxyethane or DME) and dimethyl sulfoxide (DMSO) as a low and high dielectric constant medium, respectively. Using spectroscopic tools, we quantify the fraction of ion pairs that forms within the electrolyte. Also, we show how ion pair formation is prevalent in DME and is dependent on the anion type. More importantly, we show that as ion pair formation decreases within the electrolyte, CO 2 current densities increase, and a higher CO Faradaic efficiency is observed at low overpotentials. Meanwhile, in an electrolyte medium where the ion pair fraction does not change with the anion type (such as in DMSO), a smaller influence of solvation is observed on CO 2 current densities and product distribution. By directly coupling bulk solvation to interfacial reactions and product distribution, we showcase the importance and utility of controlling the reaction microenvironment in tuning the electrocatalytic reaction pathways. Insights gained from this work will enable novel electrolyte designs for efficient and selective CO 2 conversion to desired fuels and chemicals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Field Programmable Gate Array Data Capture for Control Systems

Some Industrial Control Systems (ICS) networks are based on protocols such as Serial and Industrial Ethernet. These protocols currently have no existing cybersecurity monitoring tools, leaving a large gap in the cyber defense of critical infrastructure. In order to analyze such ICS traffic, it is first necessary to implement methods of capturing the ICS data. Whereas traditional methods of analyzing data would use microprocessors, the nature of high-speed analog data can be difficult to implement on such a versatile processor, as they are rather inefficient for doing a single task. Whereas Field Programmable Gate Arrays (FPGAs) provide an adequate tool in analyzing high speed data, as despite the lack of program versatility, Programmable Logic can implement a solution with minimal clock cycles, allowing time for each new packet of data to be captured before a new data sample is taken.

42 ENGINEERING↗