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All sources NASA NTRS DOE OSTI

NASA NTRS2001

Low-Pressure Long-Term Xenon Storage for Electric Propulsion

This Phase 2 effort demonstrated an alternative Xe storage and regulation system using activated carbon (AC) as a secondary storage media (ACSFR). This regulator system is nonmechanical, simple, inexpensive, and lighter. The ACSFR system isolates the thruster from the compressed gas tank, and allows independent multiple setpoint thruster operation. The flow using an ACSFR can also be throttled by applying increments in electrical power. Primary storage of Xe by AC is not superior to compressed gas storage with regard to weight, but AC storage can provide volume reduction, lower pressures in space, and potentially in situ Xe purification. With partial fill designs, a primary AC storage vessel for Xe could also eliminate problems with two-phase storage and regulate pressure. AC could also be utilized in long-term large quantity storage of Xe serving as a compact capture site for boil-off. Several Xe delivery ACSFR protocols between 2 and 45 sccm, and 15 min to 7 hr, were tested with an average flow variance of 1.2 percent, average power requirements of 5 W, and repeatability s of about 0.4 percent. Power requirements are affected by ACSFR bed sizing and flow rate/ duration design points, and these flow variances can be reduced by optimizing PID controller parameters.

Back, Dwight D.↗

DOE OSTI2025

Learning to Simulate Aerosol Dynamics with Graph Neural Networks

Aerosol effects on climate, weather, and air quality depend on characteristics of individual particles, which are tremendously diverse and change in time. Particle-resolved models are the only models able to capture this diversity in particle physiochemical properties, and these models are computationally expensive. As a strategy for accelerating particle-resolved microphysics models, we introduce Graph-based Learning of Aerosol Dynamics (GLAD) and use this model to train a surrogate of the particle-resolved model PartMC-MOSAIC. GLAD implements a Graph Network-based Simulator (GNS), a machine learning framework that has been used to simulate particle-based fluid dynamics models. In GLAD, each particle is represented as a node in a graph, and the evolution of the particle population over time is simulated through learned message passing. Here, we demonstrate our GNS approach on a simple aerosol system that includes condensation of sulfuric acid onto particles composed of sulfate, black carbon, organic carbon, and water. A graph with particles as nodes is constructed, and a graph neural network (GNN) is then trained using the model output from PartMC-MOSAIC. The trained GNN can then be used for simulating and predicting aerosol dynamics over time. Results demonstrate the framework's ability to accurately learn chemical dynamics and generalize across different scenarios, achieving efficient training and prediction times. We evaluate the performance across four scenarios, highlighting the framework's robustness and adaptability in modeling aerosol microphysics and chemistry.

aerosol chemistry dynamics↗

DOE OSTI2021

MODELING AND TESTING OF A NOVEL ULTRA-LOW TEMPERATURE SCO2 OPPOSING PISTON EXPANDER

The Flameless Pressurized Oxy-Combustion (FPO) cycle, a novel flexible fuel technology, is being developed into a large pilot. This effort seeks to complete the preliminary engineering and planning of a 25 MWth Pilot Plant that will demonstrate the technology for scale-up to a commercial unit. The technology, pioneered by ITEA at the 5 MWth scale, must be brought to a higher technology readiness level (TRL) to be viable at the commercial scale. The 25 MWth pilot cycle was optimized for cost and technology development and demonstration. Preliminary drawings, layouts, and plans were defined. Process flow diagrams were used to describe the pilot configuration in greater detail. A heat and mass balance with stream data was created. A master equipment list specified the operating conditions for major pieces of equipment within the pilot using this heat and mass balance. The 25 MWth FPO pilot is assessed for environmental performance. A test campaign is developed to assess the type of test and number of hours required for pilot demonstration. The environmental performance is compared against projected performance at the commercial scale. This project builds upon extensive evaluation of the techno-economic performance of the FPO technology already performed by ITEA. This includes system improvements, such as the addition of a turbo-expander to the flue gas stream. Some of the performance-enhancing components are not as well defined as others. The primary goal of this effort was to bring all of the core cycle components to the same level of design maturity. A techno-economic assessment (TEA) evaluated the FPO technology at the commercial scale in comparison to the NETL baseline cases. The reference plants were used in combination with proprietary equipment estimates to build a plant capital cost and cost of electricity evaluation. FPO performed better than the sub-bituminous post-combustion capture cases. Further preliminary estimates of improvements to the FPO cycle show even further gains when compared to conventional carbon capture methods.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2021

DEVELOPMENT OF A 25 MWTH FLAMELESS PRESSURIZED OXY-COMBUSTION PILOT

20 FOSSIL-FUELED POWER PLANTS↗

NASA NTRS2014

Amine Swingbed Payload Testing on ISS

One of NASA Johnson Space Center's test articles of the amine-based carbon dioxide (CO2) and water vapor sorbent system known as the CO2 And Moisture Removal Amine Swing-bed, or CAMRAS, was incorporated into a payload on the International Space Station (ISS). The intent of the payload is to demonstrate the spacecraft-environment viability of the core atmosphere revitalization technology baselined for the new Orion vehicle. In addition to the air blower, vacuum connection, and controls needed to run the CAMRAS, the payload incorporates a suite of sensors for scientific data gathering, a water save function, and an air save function. The water save function minimizes the atmospheric water vapor reaching the CAMRAS unit, thereby reducing ISS water losses that are otherwise acceptable, and even desirable, in the Orion environment. The air save function captures about half of the ullage air that would normally be vented overboard every time the cabin air-adsorbing and space vacuum-desorbing CAMRAS beds swap functions. The JSC team conducted 1000 hours of on-orbit Amine Swingbed Payload testing in 2013 and early 2014. This paper presents the basics of the payload's design and history, as well as a summary of the test results, including comparisons with prelaunch testing.

Button, Amy B.↗

DOE OSTI2022

Climatic clustering and longitudinal analysis with impacts on food, bioenergy, and pandemics

Predicted growth in world population will put unparalleled stress on the need for sustainable energy and global food production, as well as increase the likelihood of future pandemics. In this work, we identify high-resolution environmental zones in the context of a changing climate and predict longitudinal processes relevant to these challenges. We do this using exhaustive vector comparison methods that measure the climatic similarity between all locations on earth at high geospatial resolution relative to global-scale analyses. The results are captured as networks, in which edges between geolocations are defined if their historical climate similarities exceed a threshold. We apply Markov clustering and our novel Correlation of Correlations method to the resulting climatic networks, which provides unprecedented agglomerative and longitudinal views of climatic relationships across the globe. The methods performed here resulted in the fastest (9.37x10 18 operations/sec) and one of the largest (168.7x10 21 operations) scientific computations ever performed, with more than 100 quadrillion edges considered for a single climatic network. Our climatic analysis reveals areas of the world experiencing rapid environmental changes, which can have important implications for global carbon fluxes and zoonotic spillover events. Correlation and network analyses of this kind are widely applicable across computational and predictive biology domains, including systems biology, ecology, carbon cycles, biogeochemistry, and zoonosis research.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2000

Continuous Processing With Mars Gases

Current Martian missions call for the production of oxygen for breathing, and fuel and oxygen for propulsion to be produced from atmospheric carbon dioxide (CO2). Adsorption and freezing are the two methods considered for capturing CO2 from the atmosphere. However, the nitrogen (N2) and argon (Ar), which make up less than 5 percent of the atmosphere, cause difficulties with both of these processes by blocking the CO2. This results in the capture process rapidly changing from a pressure driven process to a diffusion controlled process. To increase the CO2 capture rates, some type of mechanical pump is usually proposed to remove the N2 and Ar. The N2 and Ar are useful and have been proposed for blanketing and pressurizing fuel tanks and as buffer gas for breathing air for manned missions. Separation of the Martian gases with the required purity can be accomplished with a combination of membranes. These membrane systems do not require a high feed pressure and provide suitable separation. Therefore, by use of the appropriate membrane combination with the Martian atmosphere supplied by a compressor a continuous Supply Of CO2 for fuel and oxygen production can be supplied. This phase of our program has focused on the selection of the membrane system. Since permeation data for membranes did not exist for Martian atmospheric pressures and temperatures, this information had to be compiled. The general trend as the temperature was lowered was for the membranes to become more selective. In addition, the relative permeation rates between the three gases changed with temperature. The end result was to provide design parameters that could be used to separate CO2 from N2 and Ar. This paper will present the membrane data, provide the design requirements for a compressor, and compare the results with adsorption and freezer methods.

Parrish, Clyde↗

NASA NTRS2001

Continuous Processing with Mars Gases

Current Martian missions call for the production of oxygen for breathing, and fuel and oxygen for propulsion to be produced from atmospheric carbon dioxide (CO2). Adsorption and freezing are the two methods considered for capturing CO, from the atmosphere. However, the nitrogen (N2) and argon (Ar), which make up less than 5 percent of the atmosphere, cause difficulties with both of these processes by blocking the CO2, This results in the capture process rapidly changing from a pressure driven process to a diffusion controlled process. To increase the CO, capture rates, some type of mechanical pump is usually proposed to remove the N2 and Ar. The N2 and Ar are useful and have been proposed for blanketing and pressurizing fuel tanks and as buffer gas for breathing air for manned missions. Separation of the Martian gases with the required purity can be accomplished with a combination of membranes. These membrane systems do not require a high feed pressure and provide suitable separation. Therefore, by use of the appropriate membrane combination with the Martian atmosphere supplied by a compressor a continuous supply of CO2 for fuel and oxygen production can be supplied. This phase of our program has focused on the selection of the membrane system. Since permeation data for membranes did not exist for Martian atmospheric pressures and temperatures, this information had to be compiled. The general trend as the temperature was lowered was for the membranes to become more selective. In addition, the relative permeation rates between the three gases changed with temperature. The end result was to provide design parameters that could be used to separate CO2 from N2 and Ar. This paper will present the membrane data, provide the design requirements for a compressor, and compare the results with adsorption and freezer methods.

Parrish, Clyde↗

NASA NTRS2014

Amine Swingbed Payload Testing on ISS

One of NASA/Johnson Space Center's test articles of the amine-based carbon dioxide (CO2) and water vapor sorbent system known as the CO2 And Moisture Removal Amine Swing-bed, or CAMRAS, was incorporated into a payload on the International Space Station (ISS). The intent of the payload is to demonstrate the spacecraft-environment viability of the core atmosphere revitalization technology baselined for the new Orion vehicle. In addition to the air blower, vacuum connection, and controls needed to run the CAMRAS itself, the payload incorporates a suite of sensors for scientific data gathering, a water save function, and an air save function. The water save function minimizes the atmospheric water vapor reaching the CAMRAS unit, thereby reducing ISS water losses that are otherwise acceptable, and even desirable, in the Orion environment. The air save function captures about half of the ullage air that would normally be vented overboard every time the cabin air-adsorbing and space vacuum-desorbing CAMRAS beds swap functions. The JSC team conducted 1000 hours of on-orbit Amine Swingbed Payload testing in 2013. This paper presents the basics of the payload's design and history, as well as a summary of the test results, including comparisons with prelaunch testing.

Button, Amy↗

DOE OSTI2020

Characterization of organic aerosol across the global remote troposphere: a comparison of ATom measurements and global chemistry models

The spatial distribution and properties of submicron organic aerosol (OA) are among the key sources of uncertainty in our understanding of aerosol effects on climate. Uncertainties are particularly large over remote regions of the free troposphere and Southern Ocean, where very few data have been available and where OA predictions from AeroCom Phase II global models span 2 to 3 orders of magnitude, greatly exceeding the model spread over source regions. The (nearly) pole-to-pole vertical distribution of non-refractory aerosols was measured with an aerosol mass spectrometer onboard the NASA DC-8 aircraft as part of the Atmospheric Tomography (ATom) mission during the Northern Hemisphere summer (August 2016) and winter (February 2017). This study presents the first extensive characterization of OA mass concentrations and their level of oxidation in the remote atmosphere. OA and sulfate are the major contributors by mass to submicron aerosols in the remote troposphere, together with sea salt in the marine boundary layer. Sulfate was dominant in the lower stratosphere. OA concentrations have a strong seasonal and zonal variability, with the highest levels measured in the lower troposphere in the summer and over the regions influenced by biomass burning from Africa (up to 10 µg sm -3 ). Lower concentrations (~0.1–0.3 µg sm -3 ) are observed in the northern middle and high latitudes and very low concentrations (<0.1 µg sm -3 ) in the southern middle and high latitudes. The ATom dataset is used to evaluate predictions of eight current global chemistry models that implement a variety of commonly used representations of OA sources and chemistry, as well as of the AeroCom-II ensemble. The current model ensemble captures the average vertical and spatial distribution of measured OA concentrations, and the spread of the individual models remains within a factor of 5. These results are significantly improved over the AeroCom-II model ensemble, which shows large overestimations over these regions. However, some of the improved agreement with observations occurs for the wrong reasons, as models have the tendency to greatly overestimate the primary OA fraction and underestimate the secondary fraction. Measured OA in the remote free troposphere is highly oxygenated, with organic aerosol to organic carbon (OA/OC) ratios of ~2.2–2.8, and is 30 %–60 % more oxygenated than in current models, which can lead to significant errors in OA concentrations. The model–measurement comparisons presented here support the concept of a more dynamic OA system as proposed by Hodzic et al. (2016), with enhanced removal of primary OA and a stronger production of secondary OA in global models needed to provide better agreement with observations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2019

High Velocity Impact Performance of a Dual Layer Thermal Protection System for the Mars Sample Return Earth Entry Vehicle

The Mars Sample Return (MSR) Earth Entry Vehicle (EEV) is currently planned on being released from its Micro-Meteorite/Orbital Debri (MM/OD) shielding housing about two days before the Earth entry phase. This leaves the EEV exposed to incoming MM/OD impacts, potentially damaging the heat shield and compromising its Entry, Decent, and Landing (EDL) integrity. Currently, two materials are proposed to comprise the MSR-EEV heat shield, a dual layer material Heat-shield for Extreme Entry Environment Technology (HEEET) and Phenolic Impregnated Carbon Ablator (PICA). PICA has been well characterized for OD class impacts, ~7km/s high mass impacts, from previous testing done in the Orion program, but hasn't under-gone extensive MM impact testing. HEEET is a rela-tively new material with minimal prior testing in re-gards to High Velocity Impacts (HVI). In order to in-form selectability of a material, it is crucial to under-stand the material performance when faced with an HVI, directly affecting mission success probability.The current measure of a Thermal Protection Sys-tem's (TPS) performance against an HVI is evaluating a thermally sized material against its derived Balistic Limit Equation (BLE). A BLE is generated empirically from multiple shots of HVI testing, and is used as a first order method in evaluating TPS's performance against the expected MM/OD environment. This method has proved useful for previous uniform densi-ty TPS materials, but has never been validated against a dual layer recession material such as HEEET. Testing in the MSR program for FY19 has a re-quirement to assess the effects of a dual layer TPS by testing various thicknesses of HEEET's Recession Layer, seen in Figure 1. From this data, BLE's will be derived for the individual thickness ratio samples, as well as the material as a whole to evaluate if a heritage form of the BLE can capture the complex physics associated with a dual layer system. Crater morpholo-gy will also be assessed with post-test Non-Destructive Evaluation (NDE) methods such as CT scanning to visualize if a BLE can well predict the associated pene-tration depths, since a BLE assumes full disinigration of the impacting particle and is generally only used to size a spherical crater ? disregarding any shrapenel effects from a high density impactor.To inform this analysis, expected MM environ-ments from the Meteoroid Engineering Model (MEM) and analytical equations for mass flux of incoming MM were evaluated against the notional MSR-EEV trajectory [1]. Using those dispersions, a monte-carlo was run to determine the most probable particle pa-rameters, as well as the riskiest in terms of full bondline penetration. From these probabilities, a test matrix was designed to test against bounding cases for the various parameters of the BLE: projectile density, projectile mass, projectile velocity, and the impact angle.This presentation will discuss the performance of the dual layer TPS material HEEET against a wide range of impact kinetic energies and densitites, as well as the comparison of HEEET to PICA in terms of MM/OD performance and selectability criteria.

Libben, B. J.↗

DOE OSTI2021

Techno-Economic Impact Assessments of Energy Efficiency Improvements in the Industrial Combustion Systems

Industrial energy efficiency assessments not only provide benefits to manufacturers but also generate significant economic and environmental benefits to localities, states, and the nation through indirect and induced benefits. Quantifying these benefits requires a systematic economic framework for capturing these interactions. This article employs methodologies for improving the energy efficiency of small- and medium-sized industry through their combustion systems. Combustion systems offer large opportunities to enhance energy efficiency through adopting advanced technologies and better-informed operations. The case studies presented illuminate the potential savings and impacts from implementing energy-efficient combustion recommendations and the importance of energy audits and energy efficiency in the fight against climate change. This study describes and quantifies the cascading economic and environmental impacts of implementing the industrial energy efficiency recommendations offered by an energy auditing program by participating facilities over a 10-year period. Results showed that it is expected that a total of $185 M would be saved in energy costs, and 2.3 million metric tons of carbon dioxide emissions would be avoided annually, and about 972 jobs could be created in the studied region if all the combustion recommendations would be implemented. Furthermore, the broader view afforded by the proposed study can be used to support better energy-efficient practices in manufacturing facilities, communities, and states.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Photochemically-Driven CO 2 Release Using a Metastable-State Photoacid for Energy Efficient Direct Air Capture

One of the grand challenges underlying current direct air capture (DAC) technologies relates to the intensive energy cost for sorbent regeneration and CO 2 release, making the massive scale (GtCO 2 /year) deployment required to have a positive impact on climate change economically unfeasible. This challenge underscores the critical need to develop new DAC processes with substantially reduced regeneration energies. Here, in this work, we report a photochemically-driven approach for CO 2 release by exploiting the unique properties of an indazole metastable-state photoacid (mPAH). Our measurements on simulated and amino acid-based DAC systems revealed the potential of mPAH to be used for CO 2 release cycles by regulating pH changes and associated isomers driven by light. Upon irradiating with moderate intensity light, a ≈55 % and ≈68 % to ≈78 % conversion of total inorganic carbon to CO 2 was found for the simulated and amino acid-based DAC systems, respectively. Our results confirm the feasibility of on-demand CO 2 release under ambient conditions using light instead of heat, thereby providing an energy efficient pathway for the regeneration of DAC sorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

The Implications of Global Change for the Co-Evolution of Argentina's Integrated Energy-Water-Land Systems

This study seeks to understand how Argentina’s energy, water, and land (EWL) systems will co-evolve under a representative array of human and earth system influences, including socioeconomic change, climate change, and climate policy. To capture Argentina’s sub-national EWL dynamics in the context of global change, we couple the Global Change Analysis Model with a suite of consistent, gridded sectoral downscaling models to explore multiple stakeholder-engaged scenarios. Across scenarios, Argentina has the economic opportunity to use its vast land resources to satisfy growing domestic and international demand for crops, such as oil (e.g., soy) and biomass. The human (rather than earth) system produces the most dominant changes in mid-century EWL resource use. A Reference scenario characterized by modest socioeconomic growth projects a 40% increase in Argentina’s agricultural production by 2050 (relative to 2020) by using 50,000 km 2 of additional cropland and 40% more water. A Climate Policy scenario designed to achieve net-zero carbon emissions globally shortly after mid-century projects that Argentina could use 100,000 km 2 of additional land (and 65% more water) to grow biomass and other crops. The burden of navigating these national opportunities and challenges could fall disproportionately on a subset of Argentina’s river basins. The Colorado and Negro basins could experience moderate-to-severe water scarcity as they simultaneously navigate substantial irrigated crop demand growth and climate-induced declines in natural water availability. Argentina serves as a generalizable testbed to demonstrate that multi-scale EWL planning challenges can be identified and managed more effectively via integrated analysis of coupled human-earth systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

Vegetation responses to air dryness amplify future land surface warming

Temperature exerts a first-order control on vegetation photosynthesis and transpiration. Yet most studies investigating temperature impacts on plants rely on near-surface air temperature, rather than canopy temperature—the temperature plants actually experience. Because canopy temperature directly regulates ecosystem function, it provides a more accurate measure of vegetation–climate interactions. Combining Earth System Model (ESM) simulations and satellite observations in a dual emergent constraint, here we show that canopy temperature is projected to increase substantially more than air temperature (~0.11-degrees more or a 16% increase in their difference) over the 21st century. The ESM ensemble median fails to capture these stronger increases in the majority of vegetated regions. We find that the largest projected increases in the difference between canopy and air temperature are predicted to occur in regions where elevating moisture stress—particularly rising vapor pressure deficit—increasingly constrains vegetation growth and transpiration. This implies that future warming will impose stronger constraints on plant function than currently estimated. Relying on air temperature alone will therefore lead to systematic underestimation of temperature effects on photosynthesis, vegetation growth, and the land carbon sink. Accurate representation of canopy temperature in ESMs is thus essential to improve projections of ecosystem responses and feedbacks to climate change.

Green, Julia K↗

DOE OSTI2025

Host Design for Carbon Capture and Regeneration in Porous Liquids

The demand for efficient gas capture technologies drives the exploration of porous liquids (PLs) as alternatives to traditional amine mixtures, which incur high operational costs due to energy-intensive regeneration processes. This research investigates the use of porous organic cages (POCs) within PLs to enhance gas capture and separation capabilities. We demonstrate that the flexibility of POCs under isostatic pressure facilitates the expulsion of captured gas molecules, enabling low-energy regeneration and the creation of an isostatic pressure testing capability for PLs. Additionally, a new CC3-OH POC derivative with scrambled hydroxides exhibits a twofold increase in CO 2 adsorption capacity, attributed to enhanced interactions between hydroxide linkers and CO 2 . Furthermore, we explore the stability of azobenzene-containing organic cages formed via imine and amine bonds, revealing that the flexible amine bond allows for more efficient E-Z isomerization. Our findings highlight the transformative potential of PLs and azobenzene-derived systems in gas separation technologies, paving the way for innovative low-energy regeneration pathways.

36 MATERIALS SCIENCE↗

DOE OSTI2024

DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology

Abstract. Vegetation phenology plays a key role in controlling the seasonality of ecosystem processes that modulate carbon, water and energy fluxes between the biosphere and atmosphere. Accurate modelling of vegetation phenology in the interplay of Earth's surface and the atmosphere is thus crucial to understand how the coupled system will respond to and shape climatic changes. Phenology is controlled by meteorological conditions at different timescales: on the one hand, changes in key meteorological variables (temperature, water, radiation) can have immediate effects on the vegetation development; on the other hand, phenological changes can be driven by past environmental conditions, known as memory effects. However, the processes governing meteorological memory effects on phenology are not completely understood, resulting in their limited performance of vegetation phenology represented in land surface models. A deep learning model, specifically a long short-term memory network (LSTM), has the potential to capture and model the meteorological memory effects on vegetation phenology. Here, we apply the LSTM to model the vegetation phenology using meteorological drivers and high-temporal-resolution canopy greenness observations through digital repeat photography by the PhenoCam network. We compare a multiple linear regression model, a no-memory-effect LSTM model and a full-memory-effect LSTM model to predict the whole seasonal greenness trajectory and the corresponding phenological transition dates across 50 sites and 317 site years during 2009–2018, covering deciduous broadleaf forests, evergreen needleleaf forests and grasslands. Results show that the deep learning model outperforms the multiple linear regression model, and the full-memory-effect LSTM model performs better than the no-memory-effect model for all three plant function types (median R2 of 0.878, 0.957 and 0.955 for broadleaf forests, evergreen needleleaf forests and grasslands). We also find that the full-memory-effect LSTM model is capable of predicting the seasonal dynamic variations of canopy greenness and reproducing trends in shifting phenological transition dates. We also performed a sensitivity analysis of the full-memory-effect LSTM model to assess its plausibility, revealing its coherence with established knowledge of vegetation phenology sensitivity to meteorological conditions, particularly changes in temperature. Our study highlights that (1) multi-variate meteorological memory effects play a crucial role in vegetation phenology, and (2) deep learning opens up new avenues for improving the representation of vegetation phenological processes in land surface models via a hybrid modelling approach.

Geology↗

DOE OSTI2022

Efficient carbon capture using sub-textured polymer packing surfaces via 3D printing

Gas absorption is a common unit operation whose performance deeply relies on the gas liquid contact behavior. In this work, we report a solid polymeric surface feature containing microscale striation to improve the solid-liquid and gas-liquid contact and facilitate mass transfer. As a proof of concept, the surface feature is adopted for CO 2 capture absorber packing via 3D printing. Besides traditional embossing texture, an additional laminar striation is applied to the packing surface as a sub-texture. The packing shows notable CO 2 mass transfer increase without interfering with other key operating characteristics including pressure drop and liquid holdup. The improvement is based on the synergy of favorable wettability, thin liquid film and increased liquid mixing from rougher surface. In the demonstration test, the packing height could decrease by 33% using the advanced packing with same CO 2 removal, leading to a significant decrease in equipment size and capital expense for commercial CO 2 capture systems.

3D printing↗