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At least 847 records · Page 47

Impact of Interposer Microstructure on Ionic Transport in Liquid-Phase Bicarbonate Electrolysis

The electrochemical reduction of CO 2 (CO 2 RR) is a potentially scalable approach for converting captured carbon dioxide into value-added products. Conventional gas-phase electrolysis systems can suffer from carbonate crossover, which limits the efficiency of the system. Liquid-phase (bi)carbonate electrolysis using bipolar membrane electrode assemblies (BPMMEA) has emerged as a promising alternative. The interposer layer, a porous mass-transport material between the BPM and the catalyst, is an essential component of the MEA, as it allows evolved CO 2 to reach the catalyst surface for reaction. In the absence of this layer, evolved CO 2 generated by the pH swing process at the BPM can be converted back into (bi)carbonate (CO 2 recapture) due to the high bulk pH. Thus, clear design guidelines are needed to maximize CO 2 conversion, minimize CO 2 recapture in the catholyte, and improve energy efficiency. Here, the transport properties of the interposer are systematically characterized by X-ray tomography and symmetric-cell impedance spectroscopy to quantify porosity, tortuosity, and the resulting MacMullin number. We then examine the correlation between these material properties and the electrolyzer performance. We focus on characterizing two commercial porous membrane filters, mixed cellulose ester (MCE) and poly(ether sulfone) (PES).

CO2 electrolysis↗

Theory and Simulation of Metal–Insulator–Semiconductor (MIS) Photoelectrodes

A metal–insulator–semiconductor (MIS) structure is an attractive photoelectrode-catalyst architecture for promoting photoelectrochemical reactions, such as the formation of H 2 by proton reduction. The metal catalyzes the generation of H 2 using electrons generated by photon absorption and charge separation in the semiconductor. The insulator layer between the metal and the semiconductor protects the latter element from photo-corrosion and, also, significantly impacts the photovoltage at the metal surface. Understanding how the insulator layer determines the photovoltage and what properties lead to high photovoltages is critical to the development of MIS structures for solar-to-chemical energy conversion. Herein, we present a continuum model for charge-carrier transport from the semiconductor to the metal with an emphasis on mechanisms of charge transport across the insulator. The polarization curves and photovoltages predicted by this model for a Pt/HfO 2 /p-Si MIS structure at different HfO 2 thicknesses agree well with experimentally measured data. The simulations reveal how insulator properties (i.e., thickness and band structure) affect band bending near the semiconductor/insulator interface and how tuning them can lead to operation closer to the maximally attainable photovoltage, the flat-band potential. This phenomenon is understood by considering the change in tunneling resistance with insulator properties. The model shows that the best MIS performance is attained with highly symmetric semiconductor/insulator band offsets (e.g., BeO, MgO, SiO 2 , HfO 2 , or ZrO 2 deposited on Si) and a low to moderate insulator thickness (e.g., between 0.8 and 1.5 nm). Beyond 1.5 nm, the density of filled interfacial trap sites is high and significantly limits the photovoltage and the solar-to-chemical conversion rate. These conclusions are true for photocathodes and photoanodes. This understanding provides critical insight into the phenomena enhancing and limiting photoelectrode performance and how this phenomenon is influenced by insulator properties. The study gives guidance toward the development of next-generation insulators for MIS structures that achieve high performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sulfate Promotes Compact CaCO 3 Formation and Protects Portland Cement from Supercritical CO 2 Attack

Supercritical (sc) CO 2 in geologic carbon sequestration (GCS) can chemically and mechanically deteriorate wellbore cement, raising concerns for long-term operations. In contrast to the conventional view of “sulfate attack” on cement, we found that adding 0.15 M sulfate to the acidic brine can significantly reduce the impact of scCO 2 attack on Portland cement, resulting in stronger cement than that found in a sulfate-free system. Scanning electron microscopy revealed a decreased total attack depth in reacted cement in the presence of sulfate. With a newly defined minimum porosity term in reactive transport modeling, our model suggests that sulfate caused CaCO 3 to fill more nanopore spaces in the cement. Small angle X-ray scattering experiments also showed that sulfate can decrease the pore sizes of the carbonate layer. The results suggest that the interactions between sulfate and cement can generate a less porous CaCO 3 layer, which better resists acidic brine. Using this mechanism as a proof-of-concept, we tested the incorporation of sodium sulfate into Portland cement and synthesized new cement composites that show stronger resistance against scCO 2 attacks. Finally, these newly discovered interfacial interactions between CaCO 3 and sulfate provide new insights into engineering mechanically strong and green materials for safer GCS.

54 ENVIRONMENTAL SCIENCES↗

Pore-Scale Transport Effects in Electrochemical CO 2 Reduction on Gold via Coupled Microkinetic-Transport Modeling

A pore-resolved modeling framework is developed to quantify how pore-scale transport affects the intrinsic microkinetics of CO 2 -to-CO on Au. A DFT-informed microkinetic model is coupled self-consistently to a Generalized-Modified Poisson–Nernst–Planck (GMPNP) transport description in a single, electrolyte-filled cylindrical pore, allowing local concentrations and potential to feed back into site-specific reaction rates. FIB-SEM is used to determine pore sizes within realistic electrode materials. Across pore diameters, d p = 10–6000 nm, the surface-averaged CO 2 reduction rate is systematically reduced relative to the ideal microkinetic baseline where mass transport is not accounted for; the effectiveness factor 𝜂 𝑠,CO 2 , which quantifies this ratio, decreases rapidly at more negative potentials and is about 1% near −1.0 V vs SHE due to reactant depletion. Spatial maps reveal pore-bulk alkalization that emerges at higher cathodic bias, with a small, near-wall pH dip due to electrostatic repulsion of hydroxide at the cathode interface. For a fixed aspect ratio L p /d p , narrower pores exhibit larger 𝜂 𝑠,CO 2 by shortening diffusion paths, whereas variations in the aspect ratio L p /d p play a secondary role. A dimensionless analysis (surface/bulk Damköhler numbers) delineates operating regimes. In conclusion, this work offers a concept for incorporating microkinetic models into homogenized porous-electrode models through effectiveness factors and pore-size distribution.

Au-catalyst↗

A robust deep learning workflow to predict multiphase flow behavior during geological C O 2 sequestration injection and Post-Injection periods

Simulation of multiphase flow in porous media is essential to manage the geologic CO 2 sequestration (GCS) process, and physics-based simulation approaches usually take prohibitively high computational cost due to the nonlinearity of the coupled physics. This paper contributes to the development and evaluation of a deep learning workflow that accurately and efficiently predicts the temporal-spatial evolution of pressure and CO 2 plumes during injection and post-injection periods of GCS operations. Based on a Fourier Neural Operator, the deep learning workflow takes input variables or features including rock properties, well operational controls and time steps, and predicts the state variables of pressure and CO 2 saturation. To further improve the predictive fidelity, separate deep learning models are trained for CO 2 injection and post-injection periods due to the difference in primary driving force of fluid flow and transport during these two phases. We also explore different combinations of features to predict the state variables. We use a realistic example of CO 2 injection and storage in a 3D heterogeneous saline aquifer, and apply the deep learning workflow that is trained from physics-based simulation data and emulate the physics process. Through this numerical experiment, we demonstrate that using two separate deep learning models to distinguish post-injection from injection period generates the most accurate prediction of pressure, and a single deep learning model of the whole GCS process including the cumulative injection volume of CO 2 as a deep learning feature, leads to the most accurate prediction of CO 2 saturation. For the post-injection period, it is key to use cumulative CO 2 injection volume to inform the deep learning models about the total carbon storage when predicting either pressure or saturation. The deep learning workflow not only provides high predictive fidelity across temporal and spatial scales, but also offers a speedup of 250 times compared to full physics reservoir simulation, and thus will be a significant predictive tool for engineers to manage the long-term process of GCS.

58 GEOSCIENCES↗

Two-stage membrane-based process utilizing highly CO 2 -selective membranes for cost and energy efficient carbon capture from coal flue gas: A process simulation study

Membrane technology for CO 2 capture has become an attractive strategy due to its cost and energy efficiency and low materials costs. In the past decade, membrane-based process designs for post-combustion power plant CO 2 capture have been developed, utilizing existing highly CO 2 -permeable membranes with relatively low CO 2 /N 2 selectivity (<50), and have obtained reasonably economic carbon capture. However, few membrane-based process designs were proposed for moderate to highly CO 2 -selective membranes (CO 2 /N 2 selectivity of 50–300, and >300, respectively), which have vastly emerged in recent years, such as various facilitated transport membranes (FTMs). Herein, we proposed a two-stage membrane-base process design targeting economic carbon capture from coal-fired flue gas. This process design features the utilization of highly CO 2 -selective membranes for one-stage CO 2 enrichment to 95% dry-base purity in the first stage and recycle of the remaining CO 2 by a highly CO 2 -permeable membrane in the second stage, in order to achieve economic CO 2 capture with 90% capture rate and >95% CO 2 product purity. Through an integration-iteration membrane model and the Aspen Plus process simulation, a sensitivity study of operating pressures (feed and permeate pressures) and membrane properties (CO 2 permeance and CO 2 /N 2 selectivity) was conducted. Critical CO 2 /N 2 selectivity of 300–400 was found for the highly CO 2 -selctive membranes to meet the demand for cost and energy efficient results. The lowest possible membrane area of 4.8 × 10 5 m 2 and fractional energy of 19.3% were obtained, which is comparable to or even more attractive than reported membrane-based process designs. Here, this work provides a new membrane process design option for highly CO 2 -selective membranes and gives insights on the influence of membrane performance and operation condition.

42 ENGINEERING↗

Exploring the Role of Inorganic and Organic Interfaces on CO 2 and CH 4 Partitioning: Case Study of Silica, Illite, Calcite, and Kerogen Nanopores on Gas Adsorption and Nanoscale Transport Behaviors

The adsorption, partitioning, and diffusion of CO 2 and CH 4 in organic–inorganic pores composed of kerogen with silica, illite, or calcite are studied using density functional theory and classical molecular dynamics simulations. The adsorption and partitioning behavior of CO 2 and CH 4 molecules is found to be a function of chemistry of the solid interface, pore size, and surface area. CO 2 molecules are preferentially adsorbed compared to CH 4 molecules on silica, illite, calcite, and kerogen surfaces due to significant contributions of electrostatic interactions with the atoms of the associated surfaces. CO 2 and CH 4 molecules display higher adsorption energy on calcite and silica compared to those on illite and kerogen because of enhanced interactions with the positively charged calcium ions on the calcite surface and the hydroxyl group (-OH) on the silica surface. Enhanced internal nanopores and the availability of adsorption active sites in illite and kerogen matrices aid in higher partitioning of the gas molecules into these pores. CO 2 has a significant influence on the clustering and swelling of kerogen fragments compared to CH 4 . Higher CO 2 adsorption on inorganic and kerogen surfaces results in lower overall self-diffusivities compared to CH 4 . This study illustrates surface and pore size controls on the adsorption, partitioning, and self-diffusivities of CO 2 and CH 4 at conditions relevant for subsurface energy applications. The chemistry of the surfaces along with the availability of internal pores and active adsorption sites influences the adsorption behavior of gases. Our results suggest that CO 2 stored in depleted gas reservoirs may preferentially inhabit nanoconfined pores.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polymer Layer-Accelerated CO 2 Absorption in Aqueous Amino Acid Solutions

Direct air capture (DAC) of CO 2 via solvent-based absorption is considered a promising negative-emission technology. However, the low concentration of CO 2 in the air and slow transport into the solvent make DAC notoriously challenging to implement without costly investments. In this study, we explore the fundamental role that the bulk and surface properties of CO 2 -permeable polymer membranes play in enhancing the efficiency of the solution sorption process in passive DAC of CO 2 . This work leverages various spectroscopic and computational studies to demonstrate that a hybrid system, comprising a reusable CO 2 -permeable polymer layer placed atop an aqueous amino acid (AA) solution, can outperform a pure aqueous AA system by 2-fold. Here we show how the enhanced solubility of CO 2 in the polymer layer can improve the transport of CO 2 into the aqueous phase, while the chemistry of the polymer can control the interfacial barrier for CO 2 permeation and the interfacial concentration of reactive AAs. The derived knowledge of the material properties achieved here can aid in the design of DAC systems with improved performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sub-Nanometer Nanoclusters of Copper Atop Single-Atom Copper Moieties toward Electrochemical CO 2 Hydrogenation to Methane

The electrochemical CO 2 reduction (eCO 2 R) offers a compelling route for converting CO 2 into value-added fuels and chemicals. Among CO 2 -derived products, methane (CH 4 ) occupies a distinct position, serving both as a key intermediate for emerging cascade electro-oxidation to oxygenates and as a strategically important extraterrestrial fuel that can be generated in situ from off-planet CO 2 resources. Although Cu-based catalysts capable of selectively producing CH 4 have been reported, they seldom sustain high selectivity at practically relevant current densities. Here, we created a single-step co-pyrolysis strategy toward generating and anchoring Cu sub-nanometer clusters (Cu SNC ) atop Cu-N x single-atom (SA) motifs embedded within N-doped carbon (NC), with controllable nanostructures through tuning of the synthesis parameters. Complementary spectroscopic analyses and density functional theory (DFT) calculations help reveal a structure−activity correlation that could guide the catalyst design. The Cu SNC @NC sample synthesized at 550 °C pyrolysis temperature (best described and modeled as Cu 3 -CuN 4 domains) represents the most effective combination of cluster size, metal-nitrogen coordination, and adsorption energetics needed to selectively promote CH 4 generation versus other eCO 2 R products. Incorporating pulsed electrolysis and hydrophobicity-modulated transport tuning at the triple-phase boundary (TPB) further enhanced CH 4 production achieving a partial CH 4 current density of ∼321 mA cm −2 , 53% Faradaic efficiency (FECH 4 ), and less than 4% combined FE for other eCO 2 R products, simplifying downstream CH 4 purification or upgrading. This work establishes generalizable principles for controlling Cu cluster atomicity and metal−nitrogen coordination, both of which are recognized determinants of CH 4 -efficient eCO 2 R.

CH4 production↗

Assessing reservoir performance for geologic carbon sequestration in offshore saline reservoirs

Carbon capture and storage (CCS) is a technological strategy to reduce CO 2 emissions from hydrocarbon-based energy production and non-energy industrial emitters, like fertilizer and cement production. To expand the geographic opportunities for CCS, offshore geologic settings are increasingly considered for saline CO 2 storage, particularly where legacy oil and gas infrastructure may be repurposed for CO 2 transport and injection. In this context, the Gulf of Mexico (GoM), United States (U.S.), may offer tremendous opportunity for CCS because the surrounding states are among the largest CO 2 producers in the U.S. and there has been extensive oil and gas development over the last half century. Nevertheless, there remains significant uncertainty in how GoM reservoir/seal systems will respond to industrial-scale CO 2 injections, particularly in the context of meso-scale (1–10s of meters) permeability variations that are difficult to identify prior to injection. Such permeability variations can have significant impacts on CO 2 migration and fluid pressure propagation, both of which govern the overall effectiveness of the CCS project. This research uses ensemble simulation methods to quantify the influence of spatially variable and a priori unknown permeability fields on CO 2 plume development and fluid pressure propagation when CO 2 is injected at 1 MMt per year for ten years. Results show a number of characteristic patterns that reveal the substantial influence of both near- and far-field permeability on reservoir performance. By focusing on basin characteristics that are common among offshore basins worldwide, results from this study suggest that offshore CCS may be a feasible carbon management strategy in regions where offshore basins are proximal to industrial CO 2 sources.

42 ENGINEERING↗

SPRUCE Sphagnum Growth and Photosynthesis Responses to Shading Treatments, 2021

This dataset reports growth, water content, nitrogen concentration, and photosynthesis of Sphagnum grown under shade cloth of different density in replicated plots adjacent to the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental study plots located in the S1-Bog. Data are reported for May to October 2021. Investigations were instigated from questions arising in the SPRUCE experiment where the Sphagnum-shrub-spruce/larch ecosystem is exposed to air and peat warming in combination with elevated atmospheric CO2. SPRUCE is located at the 8.1-ha S1 Bog forest site in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). Thirty plots (35 × 35 cm) were established in May, 2021, in three blocks on unused large plots on the S-1 bog. Data are reported for growth of Sphagnum angustifolium/fallax and S. divinum growing in plastic columns within the shade plots. Growth is reported as dry mass of new tissue measured when the columns were harvested in October 2021. Additional measurements in the final harvest datasetinclude Sphagnum water content, new stem length, mass per unit length, and nitrogen content. Stem extension was measured periodically during the summer and reported in a separate datasetas stem length. Photosynthesis of Sphagnum angustifolium/fallax samples from hollows under low and high shade was measured in the laboratory. Responses of sphagnum to shading are important for understanding the future of peatland systems under the encroachment of shrubs and other woody plant species. This dataset contains three data files in comma-separated values (.csv) format. Additional metadata are provided: three data dictionaries and a file-level metadata file in comma-separated values (.csv) format and a user guide in PDF (*.pdf) format.

carbon dioxide flux↗

Experimental Characterization of Hydrocarbons and Nitrogen Oxides Production in a Heavy-Duty Diesel–Natural Gas Reactivity-Controlled Compression Ignition Engine

Reactivity-Controlled Compression Ignition (RCCI) combustion is considered one of the most promising Low-Temperature Combustion (LTC) concepts aimed at reducing greenhouse gases for the transportation and power generation sectors. Due to the spontaneous combustion of a lean, nearly homogeneous mixture of air and low-reactivity fuel (LRF), ignited through the direct injection of a small quantity of high-reactivity fuel (HRF), RCCI (dual-fuel) shows higher efficiency and lower pollutants compared to conventional diesel combustion (CDC) if run at very advanced injection timing. Even though a HRF is used, the use of advanced injection timing leads to high ignition delays, compared to CDC, and generates high cycle-to-cycle variability, limited operating range, and high pressure rise rates at high loads. This work presents an experimental analysis performed on a heavy-duty single-cylinder compression ignited engine in dual-fuel diesel–natural gas mode. The objective of the present work is to investigate and highlight the correlations between combustion behavior and pollutant emissions, especially unburned hydrocarbons (HC) and oxides of nitrogen (NOx). Based on the analysis of crank-resolved pollutants measurements performed through fast FID and fast NOx systems under different engine operating conditions, two correlations were found demonstrating a good accordance between pollutant production and combustion behavior: Net Cyclic Hydrocarbon emission—cyclic IMEP variations (R 2 = 0.86), and Cyclic NOx—maximum value of the Rate of Heat Released (R 2 = 0.82).

33 ADVANCED PROPULSION SYSTEMS↗

Unraveling membrane electrode assembly design for electrochemical conversion of carbon dioxide to formate/formic acid

This work presents a one-dimensional continuum modeling approach to investigate various cell architectures used for electrochemical conversion of CO 2 to formate/formic acid. Ion transport is simulated by a system of generalized modified Poisson–Nernst–Planck (GMPNP) equations that reflect the reactive transport phenomena including steric effects as the electrolyte solutions become concentrated. In the cathode catalyst layer, ionic current contributions from both the supporting electrolyte and solid-state ionomer are considered. Voltage and CO 2 utilization breakdowns are utilized to deconvolute the impacts of the cell architecture. The origins of (bi)carbonate formation in the cathode are explored, as the subsequent decrease in CO 2 availability is a key reason for low faradaic efficiencies to formate/formic acid. In addition, the role of a supporting electrolyte (KOH) is investigated to understand its tradeoffs: while the K + ions can improve both conductivity and electrochemically active surface area in the cathode, the presence of OH − ions raises the pH and leads to deleterious formation of (bi)carbonates. To this end, we also present parametric studies on the concentration and flow rate of supplied KOH to the cell, to establish a path towards eliminating the need for a supporting electrolyte.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of Rock Wettability and Mineralization on CO 2 Storage Efficiency in Basalt Reservoirs

Basalt formations have emerged as highly promising targets for geological CO 2 storage due to their abundance of reactive silicate minerals that can rapidly convert dissolved CO 2 into stable carbonate minerals. The efficiency of CO 2 trapping in basalts, however, depends not only on their geochemical reactivity but also on reservoir wettability, which governs how CO 2 partitions among structural, residual, solubility, and mineral trapping mechanisms. However, wettability and mineral kinetics have largely been examined separately, wettability for plume migration and kinetics in terms of mineralization, leaving their coupled impact unquantified. Here, we systematically integrate th ese processes in a reservoir-scale reactive transport model to quantify the impact of three distinct wettability conditions (water-wet, mixed-wet, and CO 2 -wet) on plume migration, mineral precipitation, pore-scale blockage, and long-term immobilization. Results show that under ideal conditions (no mineralization), water-wet systems exhibited plume aspect ratios up to 28% higher than CO 2 -wet systems and promoted at least 60% greater residual trapping. When mineralization was incorporated, mineral trapping accounted for 57%, 53%, and 46% of the total immobilized CO 2 in water-wet, mixed-wet, and CO 2 -wet systems, respectively. Dissolved CO 2 contributed 43-46%, while residual trapping remained below 5%, and mobile CO 2 was substantially reduced due to mineralization, demonstrating that as the system becomes more water-wet, CO 2 is more effectively converted into stable carbonate minerals, although extensive mineral precipitation may lead to pore clogging. A global Sobol-Morris sensitivity analysis further reveals that the kinetic parameters of reactive minerals are the most influential factor, followed by wettability, while salinity has only a minor influence. Furthermore, these findings highlight that wettability is not merely a flow property but a fundamental control on CO 2 mineralization in basalts, with direct implications for site selection for storage projects.

Basalts↗

An integrated experimental–modeling approach to identify key processes for carbon mineralization in fractured mafic and ultramafic rocks

Abstract Controlling atmospheric warming requires immediate reduction of carbon dioxide (CO2) emissions, as well as the active removal and sequestration of CO2 from current point sources. One promising proposed strategy to reduce atmospheric CO2 levels is geologic carbon sequestration (GCS), where CO2 is injected into the subsurface and reacts with the formation to precipitate carbonate minerals. Rapid mineralization has recently been reported for field tests in mafic and ultramafic rocks. However, unlike saline aquifers and depleted oil and gas reservoirs historically considered for GCS, these formations can have extremely low porosities and permeabilities, limiting storage volumes and reactive mineral surfaces to the preexisting fracture network. As a result, coupling between geochemical interactions and the fracture network evolution is a critical component of long-term, sustainable carbon storage. In this paper, we summarize recent advances in integrating experimental and modeling approaches to determine the first-order processes for carbon mineralization in a fractured mafic/ultramafic rock system. We observe the critical role of fracture aperture, flow, and surface characteristics in controlling the quantity, identity, and morphology of secondary precipitates and present where the influence of these factors can be reflected in newly developed thermo-hydro-mechanical–chemical models. Our findings provide a roadmap for future work on carbon mineralization, as we present the most important system components and key challenges that we are overcoming to enable GCS in mafic and ultramafic rocks.

58 GEOSCIENCES↗

Seawater Acidification and Bubble Plume Dispersion from Accidental Subsea CO 2 Pipeline Rupture: A Multiphase CFD Study

If a CO 2 reservoir or transmission pipeline were to leak, both the surrounding ecology and maritime traffic safety could be put at risk. To better understand and prepare for this risk, multiphase Computational Fluid Dynamics (CFD) models were built in ANSYS Fluent to capture the behavior of a leak once it enters the water. A 3D Eulerian–Eulerian model was used for validation, while a simplified 2D model was applied to simulate conditions at a 50-m depth. The models integrate bubble dynamics, gas holdup, CO 2 dissolution, dissolved species transport, and seawater acidification into a unified CFD framework. Mass transfer was calculated using the Hughmark correlation, and local seawater temperature and salinity were factored in to determine dissociation behavior and the relevant Henry’s Law constant. To confirm the 3D model’s accuracy, results were checked against two experimental datasets: the QICS field study and the Hauser Tank experiments. The team also modeled a hypothetical release scenario at the High Island 10L site and compared the results with earlier published work. The results show that at a depth of 50 m, the surrounding water column can completely absorb a CO 2 release at a rate of 35 kg/s, since the gas dissolves into the seawater as it rises toward the surface. Beyond confirming this mitigation capacity, the simulations shed light on how a leak would actually unfold in the environment, including the shape and movement of the rising bubble plume, how much CO 2 dissolves along the way, and the resulting shifts in seawater pH and pCO 2 . Together, this provides a practical framework for assessing how CO 2 leaks could affect marine environments in the Gulf of Mexico.

54 ENVIRONMENTAL SCIENCES↗

Catalytic Oxygen Reduction for Deep O 2 Removal from CO 2 Streams

Streams of CO 2 from various capture processes may contain several impurities of which O 2 is often overlooked as a problematic impurity. Because of its reactivity, the National Energy Technology Laboratory has recommended a stringent limit, less than 10 ppm, for the O 2 level in treated CO 2 products for safe transport, storage, and utilization. Here, in this study, a variety of catalytic oxygen reduction approaches using commercial automotive exhaust emission catalysts are evaluated for O 2 removal from CO 2 streams using different reducing agents, including H 2 , CO, CH 3 OH, and CH 4 . When the amount of reductant added into the feed is carefully controlled, H 2 , CO, or CH 3 OH can effectively remove O 2 from 1.5% to below 10 ppm with a single-reactor design (>99.93% removal efficiency), while simultaneously meeting the impurity limits for other species. With CH 4 as a reductant, it is challenging to simultaneously meet the the O 2 and CO specifications in a single-reactor design because CH 4 also reacts with CO 2 to produce high levels of CO in the stream (at several hundred ppm). A dual-reactor design is developed to enable the use of CH 4 , a readily available and low-cost reductant, for the purification of CO 2 streams to meet the specifications for O 2 and other impurities.

CO2 purification↗

Combined Experimental and Modeling Study of the Interactions of Acid Gas with Common Spacecraft Surfaces for Fire Safety Applications

A fire in a spacecraft poses detrimental consequences and risks mission success in addition to crew safety. This is compounded during long-duration missions when the crew has limited options to recover from a fire. A common spacecraft fire concern is the smoldering of wire insulation, typically made from Polyvinyl chloride (PVC) or Polytetrafluoroethylene (PTFE). This creates acid gases such as Hydrogen Chloride (HCl), Hydrogen Fluoride (HF) and Hydrogen Cyanide (HCN). These poisonous gases are hazardous to the crew. They also interact with common surfaces within the spacecraft more than dominant combustion products such as CO2 and H2O. This makes them more difficult to track for potential fire detection techniques, or for postfire clean-up. It is imperative to be able to understand and predict the fate of these poisonous species in a microgravity environment in order to design a safe vehicle. HCl interacts with a number of materials inside a spacecraft. Primary among these materials is aluminum, which is abundantly used due to its strong and light weight nature. Aluminum has a natural oxide layer that protects it from corrosion but is typically treated to enhance this oxide layer. Among these treatments is a chromate conversion coating (CCC), which provides a thin enough protective oxide layer to still conduct electricity, and a traditional anodized material that has a thicker oxide layer that does not conduct electricity. Nomex is another common material found inside a spacecraft. It is a flame-resistant woven polymer that is related to nylon. This commercially available material is used for cargo storage bags and as a fire barrier. Physics-based models were developed to predict the uptake of HCl by these materials. The ultimate objective of these models is to predict the fate of HCl within the spacecraft so that sensors can be placed in meaningful locations in future missions based on the model predictions. To support these modeling efforts, experiments were performed in a cast acrylic test cell that measured the difference between the inlet and outlet concentration of HCl after inserting a sample rod of the test material. Different uptake capacities were realized for each type of sample tested. A computational fluid dynamics model (CFD) model of the reactor was then constructed that used a one-step global reaction rate with calibratable reaction (or kinetic) constants. These constants were calibrated to match the HCl uptake on the CCC aluminum samples, and the same kinetic constants were then tested for the stock and anodized aluminum samples. Model predictions matched the experimental data for the stock aluminum, and to a much lesser extent, the anodized aluminum. The model was additionally validated at different flow rates, sample surface areas, and inlet concentrations, and showed good agreement for all stock and CCC samples. The model did not accurately predict the HCl uptake in the anodized samples compared to the other two types of aluminum. Adjusting the kinetic constants and transport properties did little to improve the prediction. X-Ray Photoelectron Spectroscopy (XPS) was used to determine that the oxide layer thickness of anodized aluminum is approximately 5,000 nm, compared to 250 nm for CCC and 50 nm for stock. XPS also revealed presence of chlorine further down in the aluminum oxide layer in anodized samples than CCC and stock samples after the samples were saturated with HCl, indicating that accounting for diffusion of HCl into the oxide layer is important for accurate prediction of HCl uptake onto anodized aluminum. Consequently, a multi-scale model was developed and tested. First, a single pore inside the anodized aluminum oxide layer was modeled and is referred to as the pore-scale model. In this model, HCl diffused through the pore and reacted with the aluminum oxide pore wall to create aluminum chloride. The sample was then saturated when the mass transfer resistance through the growing aluminum chloride layer became too large for the HCl to reach the aluminum oxide wall and continue the reaction. This pore-scale model was coupled to the reactor-scale model using a concentration-dependent diffusion coefficient, resulting in much more accurate predictions (approximately half the sum square error of the aforementioned reactor-scale model that produced good agreement for stock and CCC) for a variety of operating conditions. The amount of water vapor or relative humidity (RH) in the flow during a reactor experiment was determined to influence HCl uptake. Experiments were performed to understand the interaction of gaseous HCl with aluminum surfaces in the presence of water vapor. The results show that increasing levels of RH increased the capacity of aluminum to adsorb HCl but decreased the capacity of Nomex to uptake HCl. A series of tests were performed on individual aluminum samples after they had been saturated with a fixed concentration of HCl in dry air conditions with the goal of determining how their HCl uptake capacity changes after various treatments with water relative to the original saturation tests. HCl-saturated aluminum samples subjected to a second dry air flow at the same HCl concentration as the original test had an uptake of 23.5% of the original sample with no treatment in between. Saturated aluminum samples subjected to an air flow with a RH of 90% in between tests had an uptake of 35.6% of the original. Saturated aluminum samples submerged in distilled water for 12 hours in between tests had an uptake of 82.2% of the original sample. Previously saturated aluminum tested with HCl and a 50% RH air flow resulted in similar uptake characteristics in multiple repeated tests. The experiments show the profound effect water vapor has on HCl uptake onto aluminum surfaces. In the samples subjected to water vapor or liquid water, capillary condensation and capillary diffusion alters the transport of HCl significantly. A model was proposed that developed a relationship between RH and the coefficient of HCl diffusion in aluminum chloride. This produced an “S-shaped” curve with diffusion coefficient as a function of RH, with 45% RH represented as the point where the diffusion coefficient is halfway between no water saturation and 100% water saturation in the aluminum chloride product layer. No difference in uptake characteristics for the experiment or model were realized between 50% and 62% RH. The results from the large-scale microgravity experiment, Saffire, are discussed as they pertain to the fate of HCl throughout a spacecraft. HCl was released, both as a standalone event, and in concurrence with the burning of a structured cloth. These events only produced a small response in the far field HCl sensor, while a PMMA burn that did not produce HCl had a significantly greater response. A ground-based large-scale facility was constructed to flow acid gas at the scale and configuration realized in the Saffire experiments. A CFD model of this duct was constructed to test kinetic parameters developed in this work at a larger scale and different geometric configuration and to predict the results of the large-scale facility. The models developed in this work were used to interpret the results of the microgravity tests and lead the discussion on what further experiments and models are needed in order to predict the fate of acid gas in a spacecraft environment. To summarize, the major contributions of this work are as follows: the capacity to uptake HCl, with and without the presence of water vapor, was measured for a variety of real spacecraft surfaces. Several different models (single reactor-scale, multiscale, spacecraft-scale) were developed and with the aid of modeling, the rate of uptake for those surfaces was also predicted and validated. The kinetic parameters determined from the small-scale reactor experiments and models were used to predict large-scale and microgravity tests. Conclusions from this research will be used in the design of spacecraft vehicles and large-scale microgravity fire safety experiments. The models built by this work will aid designers in sensor placement and could be used to predict acid gas transport from fires in partial gravity, as would be seen in Lunar and Martian habitats.

fire safety↗