Mixed;#8208;Metal MOF;#8208;74 Templated Catalysts for Efficient Carbon Dioxide Capture and Methanat
Explore the source record for details and available documents.
SEARCH · Search NASA
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.
Explore the source record for details and available documents.
The mission of this project was to provide a preliminary feasibility assessment of powering different marine carbon dioxide removal (mCDR), marine carbon capture, and marine carbon sequestration strategies with marine energy. In this report, carbon capture refers to methods that can separate or capture carbon dioxide (CO 2 ) from the air or ocean; carbon sequestration refers to methods that store CO 2 obtained by capture methods out of the atmosphere for long periods of time; and carbon dioxide removal (CDR) refers to methods that do both. The project found that mCDR powered by marine energy and offshore wind energy available in the United States could meet global CDR scales needed by 2040 and 2050 to limit warming to 1.5 degrees C by 2100. Note that this preliminary estimate assumes that it is possible to harvest all the marine and offshore wind resources available in the United States with existing technology options, and it does not account for the power needed for monitoring these methods, as these power needs are not yet well defined and require further research. Additionally, these CDR scales will still require emissions reductions.
Integrated Carbon Capture and Conversion of CO 2 into materials (IC3M) is an attractive solution to meet the global energy demand, reduce our dependence on fossil fuels and lower CO 2 emissions. In this work, using a water-lean post combustion capture solvent, (N-(2-ethoxyethyl)-3-morpholinopropan-1-amine) (2-EEMPA), >90% conversion of captured CO2 to hydrocarbons, mostly methane, is achieved in the presence of a heterogenous Ru catalysts under relatively mild reaction conditions (170 °C and <15 bar H 2 pressure). The catalytic performance was better in 2-EEMPA than aqueous 5M monoethanol amine (MEA). Operando NMR study showed in-situ formation of N-formamide intermediate, which underwent further hydrogenation to form methane and other higher hydrocarbons. The technoeconomic analyses (TEA) showed that the proposed integrated process can potentially improve the thermal efficiency by 5% and reduce the total capital investment and minimum synthetic natural gas (SNG) selling price by 32% and 12% respectively compared to conventional Sabatier process, highlighting the energetic and economic benefits of integrated capture and conversion. Methane derived from CO 2 and renewable H 2 source is an attractive fuel, and it has a great potential as a renewable hydrogen carrier as an environmentally responsible carbon capture and utilization approach.
Direct air capture (DAC) of carbon dioxide is one approach among many proposed that is capable of offsetting hard-to-avoid emissions. In previous work, we developed the alkalinity concentration swing (ACS) method, which is driven through concentrating an alkaline solution that has been loaded with atmospheric CO 2 by desalination technologies, such as reverse osmosis or capacitive deionization. Though the ACS is promising in terms of energy usage and implementation, its absorption rate and water requirements are infeasible for a large-scale DAC process. Here, we propose an improvement on the ACS, the bicarbonate-enriched alkalinity concentration swing (BE-ACS), which selects bicarbonate ions from a stream of aqueous alkaline solution that has absorbed atmospheric CO 2 . The bicarbonate-rich stream is then concentrated, which greatly increases its CO 2 partial pressure, and then CO 2 is extracted from solution. We experimentally investigate the use of pressure-driven nanofiltration (NF) membrane-based separation to select bicarbonate ions over carbonate ions. We screen commercial membranes and select one high-performance membrane for detailed studies, quantifying its bicarbonate-carbonate selectivity factor and bicarbonate-passage factor. Feed pH, the combined concentration of aqueous CO 2 , bicarbonate, and carbonate species (or dissolved inorganic carbon), alkalinity, and permeation flux are systematically varied to study NF separation properties. We find that the selectivity factor, which exceeds 30 times in certain regimes, increases with higher feed pH and higher alkalinity. Lastly, the performance metrics of the selected NF membrane are input into a theoretical BE-ACS cycle analysis, and the required energy input and cycle capacity output are evaluated. Ideal cycle energy is found to be as low as around 250 kJ/mol, with opportunities identified for further decreases through process engineering and forward osmosis energy recovery.
Carbon capture can mitigate point-source carbon dioxide (CO 2 ) emissions, but hurdles remain that impede the widespread adoption of amine-based technologies. Capturing CO 2 at temperatures closer to those of many industrial exhaust streams (>200°C) is of interest, although metal oxide absorbents that operate at these temperatures typically exhibit sluggish CO 2 absorption kinetics and instability to cycling. Here, in this study, we report a porous metal–organic framework featuring terminal zinc hydride sites that reversibly bind CO 2 at temperatures above 200°C—conditions that are unprecedented for intrinsically porous materials. Gas adsorption, structural, spectroscopic, and computational analyses elucidate the rapid, reversible nature of this transformation. Extended cycling and breakthrough analyses reveal that the material is capable of deep carbon capture at low CO 2 concentrations and high temperatures relevant to postcombustion capture.
Abstract Carbon capture, utilization and storage is a key yet cost-intensive technology for the fight against climate change. Single-component water-lean solvents have emerged as promising materials for post-combustion CO 2 capture, but little is known regarding their mechanism of action. Here we present a combined experimental and modelling study of single-component water-lean solvents, and we find that CO 2 capture is accompanied by the self-assembly of reverse-micelle-like tetrameric clusters in solution. This spontaneous aggregation leads to stepwise cooperative capture phenomena with highly contrasting mechanistic and thermodynamic features. The emergence of well-defined supramolecular architectures displaying a hydrogen-bonded internal core, reminiscent of enzymatic active sites, enables the formation of CO 2 -containing molecular species such as carbamic acid, carbamic anhydride and alkoxy carbamic anhydrides. This system extends the scope of adducts and mechanisms observed during carbon capture. It opens the way to materials with a higher CO 2 storage capacity and provides a means for carbamates to potentially act as initiators for future oligomerization or polymerization of CO 2 .
The sustainability potential of carbon capture, concentration, and utilization technologies motivates accelerated discovery of carbon dioxide sorbents, for which we present a high throughput screening instrument.
Reactive carbon dioxide capture (RCC) is a process where carbon dioxide (CO 2 ) is captured from a mixed gas stream (such as air) and converted to products without first performing a separation step to concentrate the CO 2 . Here, in this work, zeolite dual-functional materials (ZFMs) are introduced and evaluated for simulated RCC. The studied ZFMs feature high surface area, crystalline, microporous zeolite faujasite (FAU) as the support. Sodium oxide (“Na 2 O”) is impregnated as an effective capture agent capable of scavenging low concentration CO 2 (1,000 ppm). Exchanged and impregnated sodium on FAU chemisorbs CO 2 as carbonates and bicarbonates but does not promote the conversion of sorbed CO 2 to products when heated in hydrogen. The addition of Ru promotes the formation of formates, while the addition of Pt generates carbonyl surface species when heated in hydrogen. The active metal then promotes extremely high selectivity for CO 2 hydrogenation to either methane on Ru catalyst (~150 °C) or carbon monoxide on Pt catalyst (~200 °C) when heated in reducing atmospheres.
Our group recently developed dual-function materials (DFMs) and reactive carbon capture (RCC) processes for the selective production of methanol (MeOH) or CO, offering two novel and unique pathways for MeOH production. This study conducted a comparative techno-economic analysis (TEA) of the two RCC pathways from exhaust CO 2 : 1) a “Direct RCC-to-MeOH” pathway and 2) an “Indirect RCC-to-CO” pathway followed by MeOH synthesis. The “Direct RCC-to-MeOH” pathway produced a lower levelized cost of MeOH (LCOM) at $\$$0.78/kg, compared to $\$$0.84/kg for the “Indirect RCC-to-CO” pathway. The key difference is the need to recompress the syngas from RCC before MeOH synthesis in “Indirect RCC-to-CO.” Nonetheless, with reduced catalyst costs and hydrogen requirements for “RCC-to-CO,” this pathway merits further study to produce syngas rather than MeOH. Both pathways are comparable in LCOM to baseline e-MeOH production from CO 2 hydrogenation ($\$$0.72/kg) while having lower carbon intensities (0.45 and 0.51 kg-CO 2 e/kg vs 0.54 kg-CO 2 e/kg).
Direct air capture of carbon dioxide is a viable option for the mitigation of CO 2 emissions and their impact on global climate change. Conventional processes for carbon capture from ambient air require 230 to 800 kJ thermal per mole of CO 2 , which accounts for most of the total cost of capture. Here, we demonstrate electrochemical direct air capture using neutral red as a redox-active material in an aqueous solution enabled by the inclusion of nicotinamide as a hydrotropic solubilizing agent. The electrochemical system demonstrates a high electron utilization of 0.71 in a continuous flow cell with an estimated minimum work of 35 kJ e per mole of CO 2 from 15% CO 2 . Further exploration using ambient air (410 ppm CO 2 in the presence of 20% oxygen) as a feed gas shows electron utilization of 0.38 in a continuous flow cell to provide an estimated minimum work of 65 kJ e per mole of CO 2 .
A chemical processing system for removing carbon dioxide from a gas mixture using a multicomponent amine-based scrubbing solution includes a spectroscopic evaluation system with a liquid contact probe for spectroscopic investigation, an energy source connected with the liquid contact probe to provide the spectroscopic stimulation energy to the probe, a spectrometer connected with the liquid contact probe to detect the spectroscopic response energy to the probe and to output spectral data corresponding to the spectroscopic response energy, and a machine learning spectral data analyzer connected to the spectrometer for evaluation of the spectral data to determine a concentration value for each of water, amine component and captured carbon dioxide in the scrubbing solution, the machine learning spectral data analyzer being trained for each such component over a corresponding trained concentration range, and optionally over a trained temperature range to provide a temperature-compensated concentration value.
Carbon dioxide (CO 2 ) emissions from fossil fuel combustion are a significant source of greenhouse gas, contributing in a major way to global warming and climate change. Carbon dioxide capture and sequestration is gaining much attention as a potential method for controlling these greenhouse gas emissions. Among the environmentally friendly solvents, deep eutectic solvents (DESs) have demonstrated the potential capability for carbon capture. To establish a theoretical framework for DES activity, thermodynamics modeling and solubility predictions are significant factors to anticipate and understand the system behavior. Here, in this study, we combine the COSMO-RS model with machine learning techniques to predict the solubility of CO 2 in various deep eutectic solvents. A comprehensive data set was established comprising 1973 CO 2 solubility data points in 132 different DESs at a variety of temperatures, pressures, and DES molar ratios. This data set was then utilized for the further verification and development of the COSMO-RS model. The CO 2 solubility (ln(x CO 2 )) in DESs calculated with the COSMO-RS model differs significantly from the experiment with an average absolute relative deviation (AARD) of 23.4%. A multilinear regression model was developed using the COSMO-RS predicted solubility and a temperature-pressure dependent parameter, which improved the AARD to 12%. Finally, a machine learning model using COSMO-RS-derived features was developed based on an artificial neural network algorithm. The results are in excellent agreement with the experimental CO 2 solubilities, with an AARD of only 2.72%. The ML model will be a potentially useful tool for the design and selection of DESs for CO 2 capture and utilization.
This NETL report provides a comprehensive techno-economic analysis of current, state-of-the-art, fossil-based ammonia production processes, explicitly utilizing natural gas as the feedstock. The study thoroughly investigates three distinct configurations: conventional Steam Methane Reforming (SMR) without carbon capture, SMR integrated with carbon capture and storage (CCS), and Autothermal Reforming (ATR) also with CCS. The analysis incorporates detailed equipment cost accounting as part of its methodology. The primary objective is to meticulously evaluate the cost and performance of these established and emerging technological pathways, considering factors such as capital expenditures, operational costs, and energy consumption. While the report acknowledges and quantifies environmental impacts, its central focus remains on the economic and technical feasibility of each process design employing these current technologies. The analysis provides a direct comparison of the Levelized Cost of Ammonia (LCOA) for each pathway, revealing how the integration of CCS within these state-of-the-art systems impacts the overall production cost. The ATR+CCS configuration, representing an advanced approach, emerged with a slightly more favorable LCOA compared to SMR+CCS. This benefit was attributed to its inherent process efficiencies, high carbon capture rates, and economy of scale advantages. The report details the energy consumption profiles for each case, including metrics like net energy consumption and thermal efficiency, which are critical for assessing the performance of these contemporary industrial processes. Sensitivity analyses further explore how variables such as natural gas price, capital costs, and capacity factors influence the LCOA across all scenarios, offering critical insights into the economic robustness and scalability of these current ammonia production technologies.
Carbon capture and sequestration (CCS) from industrial point sources and direct air capture are necessary to combat global climate change. A particular challenge faced by amine-based sorbents—the current leading technology—is poor stability towards O 2 . Here, we demonstrate that CO 2 chemisorption in γ-cylodextrin-based metal-organic frameworks (CD-MOFs) occurs via HCO 3 – formation at nucleophilic OH – sites within the framework pores, rather than via previously proposed pathways. Here, the new framework KHCO 3 CD-MOF possesses rapid and high-capacity CO 2 uptake, good thermal, oxidative, and cycling stabilities, and selective CO 2 capture under mixed gas conditions. Because of its low cost and performance under realistic conditions, KHCO 3 CD-MOF is a promising new platform for CCS. More broadly, our work demonstrates that the encapsulation of reactive OH – sites within a porous framework represents a potentially general strategy for the design of oxidation-resistant adsorbents for CO 2 capture.
Direct air capture (DAC) systems often consist of packing material wetted by a capture fluid that reacts with CO 2 in the airstream. The efficiency of the contactor is determined by a complex relationship of fluid dynamics, heat and mass transfer, contactor geometry, and chemical properties. The efficiency of the contactor must be balanced with other factors, primarily pressure drop through the system. Triply periodic minimal surfaces (TPMS) are a class of differential surfaces that have been explored in multiple engineering applications and have been shown to exhibit excellent performance when used in heat exchangers. Their tortuous path provides a high surface-to-volume ratio and favorable trade-off between contact area and pressure drop. In this work, a gyroid-type TPMS contactor was evaluated using computational fluid dynamics for a variety of geometric parameters to explore the potential benefit of TPMS shapes for DAC applications. A thin-film model was employed to model the flow and distribution of the capture solvent, allowing efficient simulations of TPMS structures at scale by eliminating the need for a computationally intensive interface capturing method. A liquid-gas mass transfer model was implemented in the commercial software STAR-CCM+ and used to predict the CO 2 capture efficiency and study the trade-off between capture performance and pressure drop through analysis of capture rates, mass transfer coefficients, and other relevant variables. TPMS contactors with a variety of geometric parameters and two capture solvent options were investigated to determine the effect of design choices on the operational performance of DAC systems. In conclusion, results showed that while contactor geometry is the dominant factor in efficiency and pressure drop, the physiochemical properties of the solvent are an important secondary influence on the contactor performance.
Abstract Carbon capture and sequestration (CCS) from industrial point sources and direct air capture are necessary to combat global climate change. A particular challenge faced by amine‐based sorbents—the current leading technology—is poor stability towards O 2 . Here, we demonstrate that CO 2 chemisorption in γ‐cylodextrin‐based metal–organic frameworks (CD‐MOFs) occurs via HCO 3 − formation at nucleophilic OH − sites within the framework pores, rather than via previously proposed pathways. The new framework KHCO 3 CD‐MOF possesses rapid and high‐capacity CO 2 uptake, good thermal, oxidative, and cycling stabilities, and selective CO 2 capture under mixed gas conditions. Because of its low cost and performance under realistic conditions, KHCO 3 CD‐MOF is a promising new platform for CCS. More broadly, our work demonstrates that the encapsulation of reactive OH − sites within a porous framework represents a potentially general strategy for the design of oxidation‐resistant adsorbents for CO 2 capture.
Carbon Collect Inc., along with Arizona State University, the Electric Power Research Institute (EPRI), PM Group, and Trimeric Corporation, completed an initial design of a commercial-scale, passive direct air capture (DAC) system termed “carbon trees” that will capture, separate, and store at least 100,000 tonnes/year of carbon dioxide (CO2) from air (net basis). Passive DAC is unique among DAC technologies in that passive air delivery by wind avoids the energy penalty of forced convection. Carbon Collect Inc.’s sorbent-agnostic approach offers the flexibility to choose sorbents for a wide range of climates. A combination of steam, low-grade heat, and vacuum releases the CO2 from the sorbent, which is extracted from the chamber and purified and compressed for geological storage. A commercial carbon tree forest combines the output of several thousand trees for compression and purification with high heat and energy integration. The project team prepared an initial engineering design package for each of three geographically diverse host sites throughout the United States to better understand the effect of local/regional ambient conditions on DAC system performance and project costs. A techno-economic analysis, life cycle analysis, business case analysis, and an environmental, health, and safety risks assessment were also completed for each of the three geographically diverse host sites.
Overview The Capacity Expansion Regional Feasibility (CERF) model is an open-source geospatial python package that provides new power plant locations at a 1km resolution. The model ingests U.S. state or regional-scale electricity system capacity expansion plans, such as those produced by the Global Change Analysis Model (GCAM-USA), and identifies feasible, site-specific locations for individual new power plants (renewable and non-renewable). CERF combines high-resolution geospatial suitability analyses with an economic algorithm that selects individual plant siting locations based on grid interconnection costs and the locational marginal value of new generation. The model incorporates a wide range of dynamic constraints and opportunities, such as protected lands, population density, existing infrastructure, and water availability. This dataset provides CERF power plant siting results for IM3 Phase 2 simulations across eight different scenarios for the Western US through 2055. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States (see, https://tgw-data.msdlive.org/). These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 CERF siting results in this dataset correspond to capacity expansion plans in the GCAM-USA IM3 Phase 2 simulation data and are available for each of the above scenarios. Data Details Temporal Range: 2015-2055 in 5-year timesteps. Note that 2015 is the experiment base year and 2020 and beyond represent model simulation years. Spatial Range: Plant locations are provided for the eleven states in the Western US including Arizona, California, Colorado, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, and Wyoming. Spatial Resolution: 1 km-squared, provided in x and y coordinates Geospatial Projection: Albers Equal Area Conic (ESRI:102003) File Type: csv The dataset contains subdirectories for each of the eight scenarios described in the overview. Each scenario folder contains two subfolders with the following information: 1. Power Plant Data This directory contains a single .csv file of power plant locations for both pre-existing (non-CERF sited plants in operation in 2015) and new (CERF-sited) power plants across the temporal range along with additional CERF model output parameters for CERF-sited plants. Plant with a siting year earlier than 2020 correspond to facilities that are operational leading into the first timestep CERF simulation. For a more detailed description of CERF model output parameters, see the CERF model documentation. Note that the cerf_plant_id parameter is unique within each scenario file but not across scenario files. Parameter Descriptions scenario - Name of scenario cerf_plant_id - Unique siting identifier cerf_sited - If True, indicates that plant was sited by CERF model. If False, indicates pre-existing facility region_name - Name of region (state) tech_id - Technology ID tech_name - Full generation technology name inclusive of cooling type (if applicable) and additional characteristics tech_simple - Simplified generation technology type unit_size_mw - Power plant unit size (MW) xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) index - Index position in the flattend 2D array buffer_in_km - Exclusion buffer around site (km) sited_year - Year of siting retirement_year - Year of retirement lmp_zone - Locational marginal price (LMP) zone ID locational_marginal_price_usd_per_mwh - Locational marginal price ($/MWh) generation_mwh_per_year - Generation output (MWh/yr) operating_cost_usd_per_year - Cost of plant operations ($/yr) net_operational_value - Net operational value based on LMP and and operating costs ($/yr) interconnection_cost - Cost of interconnection for transmission & gas pipeline (if applicable) net_locational_cost -- Difference of interconnection cost and operating value ($/yr) capacity_factor_fraction - Capacity factor (fraction) carbon_capture_rate_fraction - Carbon capture rate (fraction) fuel_co2_content_tons_per_btu - Fuel CO2 content (tons/Btu) fuel_price_usd_per_mmbtu - Fuel price ($/MMBtu) fuel_price_esc_rate_fraction - Fuel price escalation rate (fraction) heat_rate_btu_per_kWh - Heat rate (Btu/kWh) lifetime_yrs - Technology lifetime for annuity (years) operational_life_yrs - Operational lifetime for retirement (years) variable_om_usd_per_mwh - Variable operation and maintenance costs of yearly capacity use ($/MWh) variable_om_esc_rate_fraction - Variable operation and maintenance costs escalation rate (fraction) carbon_tax_usd_per_ton - Carbon tax ($/ton) carbon_tax_esc_rate_fraction - Carbon tax escalation rate (fraction) 2. Storage Data This directory contains information on new and pre-existing energy storage facilities operational in each timestep along with various storage operational parameters. The 2015 timestep provides pre-existing energy storage data and corresponds with facilities that are operational leading into the first model simulation timestep. Note that coordinates in the storage files correspond to the interconnection point on the grid (substation location), not individual energy storage locations. Energy storage is added in a cumulative process at each given interconnection point. That is, each individual file provides the total operational storage capacity interconnected to the specified substation for the given timestep, inclusive of previously installed storage at that location and new storage installed in that timestep at that location. Parameters scenario - Name of scenario timestep - Simulation timestep name - Unique storage identifier s_typ - Type of energy storage technology (battery or pumped storage hydro) s_node - Node ID of interconnecting substation xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) charge_rate - Maximum charge rate (power capacity) of storage system (MW) discharge_rate - Maximum discharge rate (power capacity) of storage system (MW) duration - Duration of storage system (hours) max_SoC - Allowed maximum state of charge (energy capacity) of storage system (MWh) min_SoC -Allowed minimum state of charge (energy capacity) of storage system (MWh) charge_eff - Efficiency of charge (fraction between 0 and 1) discharge_eff - Efficiency of discharge (fraction between 0 and 1) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.