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At least 217 records · Page 12

Electrocatalysis in CO 2 -Binding Organic Liquids with an Iron Porphyrin

Direct electrochemical upgrading of CO 2 in capture media is an attractive approach to carbon capture that can bypass the energy requirement for the thermal release of pure CO 2 . Here we investigate the electrocatalytic activity of iron(tetraphenylporphyrin) in the presence of organic solvents that convert into ionic liquids upon exposure to CO 2 . Four different solvent systems were tested, all of which capture CO 2 in the form of an alkyl carbonate (or carbamate) anion and an acidic ammonium cation. The electrocatalytic selectivity exhibited a strong dependence on the acidity of the capture medium, with the most basic solvent affording a high selectivity for production of CO instead of H 2 . Experimental and computational studies support a canonical mechanism in which the catalyst reacts with free CO 2 in solution, as opposed to a reaction with the alkyl carbonate that is present in high concentration. Kinetic analysis indicates that the rate-limiting step is changed from C–O protonolysis in traditional solvents to the binding of CO 2 in the capture media. Quantitative 13 C– 13 C EXSY revealed that the dissociation of the alkyl carbonate into free, solvated CO 2 is very rapid (~15 s –1 ) compared to the interconversion of HCO 3 – /CO 2 in aqueous solution. These results underscore the need to understand the mechanism and kinetics for both the release of captured CO 2 and its electrocatalytic conversion.

Carbon Dioxide↗

Lanthanide binding peptide surfactants at air–aqueous interfaces for interfacial separation of rare earth elements

Rare earth elements (REEs) are critical materials to modern technologies. They are obtained by selective separation from mining feedstocks consisting of mixtures of their trivalent cation. We are developing an all-aqueous, bioinspired, interfacial separation using peptides as amphiphilic molecular extractants. Lanthanide binding tags (LBTs) are amphiphilic peptide sequences based on the EF-hand metal binding loops of calcium-binding proteins which complex selectively REEs. We study LBTs optimized for coordination to Tb 3+ using luminescence spectroscopy, surface tensiometry, X-ray reflectivity, and X-ray fluorescence near total reflection, and find that these LBTs capture Tb 3+ in bulk and adsorb the complex to the interface. Molecular dynamics show that the binding pocket remains intact upon adsorption. We find that, if the net negative charge on the peptide results in a negatively charged complex, excess cations are recruited to the interface by nonselective Coulombic interactions that compromise selective REE capture. If, however, the net negative charge on the peptide is −3, resulting in a neutral complex, a 1:1 surface ratio of cation to peptide is achieved. Surface adsorption of the neutral peptide complexes from an equimolar mixture of Tb 3+ and La 3+ demonstrates a switchable platform dictated by bulk and interfacial effects. The adsorption layer becomes enriched in the favored Tb 3+ when the bulk peptide is saturated, but selective to La 3+ for undersaturation due to a higher surface activity of the La 3+ complex.

Ortuno Macias, Luis E. (ORCID:0000000284342192)↗

Radioiodine sorbent selection criteria

Methods for preventing radioiodine from entering the environment are needed in processes related to nuclear energy and medical isotope production. The development and performance of many different types of sorbents to capture iodine have been reported on for decades; however, there is yet to be a concise overview on the important parameters that should be considered when selecting a material for chemically capturing radioiodine. This paper summarizes several criteria that should be considered when selecting candidate sorbents for implementation into real-world systems. The list of selection criteria discussed are 1) optimal capture performance, 2) kinetics of adsorption, 3) performance under relevant process conditions, 4) properties of the substrate that supports the getter, and 5) environmental stability and disposition pathways for iodine-loaded materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enhancing CO 2 Transport Across a PEEK‐Ionene Membrane and Water‐Lean Solvent Interface

Abstract Efficient direct air capture (DAC) of CO 2 will require strategies to deal with the relatively low concentration in the atmosphere. One such strategy is to employ the combination of a CO 2 ‐selective membrane coupled with a CO 2 capture solvent acting as a draw solution. Here, the interactions between a leading water‐lean carbon‐capture solvent, a polyether ether ketone (PEEK)‐ionene membrane, CO 2 , and combinations were probed using advanced NMR techniques coupled with advanced simulations. We identify the speciation and dynamics of the solvent, membrane, and CO 2 , presenting spectroscopic evidence of CO 2 diffusion through benzylic regions within the PEEK‐ionene membrane, not spaces in the ionic lattice as expected. Our results demonstrate that water‐lean capture solvents provide a thermodynamic and kinetic funnel to draw CO 2 from the air through the membrane and into the bulk solvent, thus enhancing the performance of the membrane. The reaction between the carbon‐capture solvent and CO 2 produces carbamic acid, disrupting interactions between the imidazolium (Im + ) cations and the bistriflimide anions within the PEEK‐ionene membrane, thereby creating structural changes through which CO 2 can diffuse more readily. Consequently, this restructuring results in CO 2 diffusion at the interface that is faster than CO 2 diffusion in the bulk carbon‐capture solvent.

Walter, Eric D.↗

Accurate prediction of carbon dioxide capture by deep eutectic solvents using quantum chemistry and a neural network

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.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Numerical Simulation and Experimental Comparison of System Analysis Module 1D Mixing Model for Cold Shock Transients in the Gallium Thermal-Hydraulic Mixing Facility

Abstract Liquid metals are being investigated as coolants in many advanced reactor designs because of their high thermal conductivity and effectiveness at high temperatures. However, they often pose challenges to reactor operation and safety because of the complex thermal mixing and stratification in the plenum of pool-type reactor designs. The advanced system analysis code System Analysis Module (SAM) currently under development at Argonne National Laboratory aims to develop and implement thermal mixing models to accurately capture these complex thermal fluid behaviors. In this study, the SAM thermal mixing model was compared against experimental data from the Gallium Thermal-Hydraulic Experiment facility, a scaled liquid metal test facility that uses gallium as a surrogate fluid to investigate the stratification and thermal mixing of low-Prandtl-number fluids in the upper plenum of a liquid metal-cooled reactor. Two cold shock transient cases were used: one with stable stratified flow (Ri = 32) and one with stronger thermal mixing (Ri = 0.5). The resultant temperatures were then compared with the experimental temperatures over the entire plenum to assess the ability of the mixing models to capture the thermal behavior and to better correspond mixing parameters to various flow scenarios. Generally, the zero-dimensional mixing model was more capable of capturing the bulk temperature of the component modeled assuming that an accurate mass flow rate was provided, but it was inherently unable to capture thermal gradients in space. The one-dimensional mixing model was capable of capturing that the thermal gradients provided accurate selection of the mixing coefficients. Further, the temperature at the outlet junction was compared over time for each of the mixing models with the recorded experimental temperature. The implemented mixing models demonstrated the ability to effectively capture the overall thermal behavior for stronger mixing scenarios but struggled with more stably stratified flows. It was found that a system analysis code's covering of the entire range of different operating conditions still remains a challenging task, and it is suggested that further model and closure improvements are necessary to accurately capture complex thermal mixing and stratification phenomena.

stratification↗

Data-driven simultaneous process optimization and adsorbent selection for vacuum pressure swing adsorption

Technologies for post-combustion carbon capture are essential for the reduction of greenhouse gas emissions to the atmosphere. However, they are still associated with high costs and energy consumption. Intensified processes for carbon capture have the potential to overcome these challenges due to their higher efficiency, lower capital cost, and increased operational flexibility. Here, this work investigates simultaneous optimization of process conditions and adsorbent selection for a modular Vacuum Pressure-Swing Adsorption system designed for CO 2 capture. Both surrogate-based Nonlinear Programming and Mixed-Integer Nonlinear Programming approaches are applied and compared in terms of computational efficiency and solution accuracy. Moreover, process performance results are examined by applying several data analytics techniques to gain insights into the material-process correlations. Data-driven classifiers and neural networks can accurately predict whether a material is likely to satisfy purity, recovery, and energy constraints when operated at optimal process conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cost of Capturing CO 2 from Industrial Sources

The objective of this study is to provide an estimate of the cost to capture carbon dioxide (CO 2 ) from select industrial processes (ammonia, ethylene oxide, ethanol, natural gas processing, coal-to-liquids, gas-to-liquids, refinery hydrogen, cement, iron/steel, and pulp/paper). Each of the ten processes were chosen for analysis due to either the high purity of the CO 2 emission source (99–100 mole percent CO 2 ) or the large quantity of CO 2 potentially available. For each industrial process considered, available plant information, such as existing average plant size, projected new development plant size, or existing plant operations data was used to develop a reference plant for this study.

20 FOSSIL-FUELED POWER PLANTS↗

PowerModel-AI: A First On-the-Fly Machine-Learning Predictor for AC Power Flow Solutions

The real-time creation of machine-learning models via active or on-the-fly learning has attracted considerable interest across various scientific and engineering disciplines. These algorithms enable machines to build models autonomously while remaining operational. Through a series of query strategies, the machine can evaluate whether newly encountered data fall outside the scope of the existing training set. In this study, we introduce PowerModel-AI, an end-to-end machine learning software designed to accurately predict AC power flow solutions. We present detailed justifications for our model design choices and demonstrate that selecting the right input features effectively captures load flow decoupling inherent in power flow equations. Our approach incorporates on-the-fly learning, where power flow calculations are initiated only when the machine detects a need to improve the dataset in regions where the model’s suboptimal performance is based on specific criteria. Otherwise, the existing model is used for power flow predictions. This study includes analyses of five Texas A&M synthetic power grid cases, encompassing the 14-, 30-, 37-, 200-, and 500-bus systems. The training and test datasets were generated using PowerModels.jl, an open-source power flow solver/optimizer developed at Los Alamos National Laboratory, NM, USA.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Guideline requirements for serviceable spacecraft grasping/berthing/docking interfaces based on simulations and flight experience

The described efforts support a NASA Space Assembly and Servicing Working Group activity to draft guideline interface standards. The general requirements are to provide a simple, reliable, and durable system. Interface requirements developed include lateral position offset, axial and lateral velocities, and angular misalignment. A survey of concepts and simulation studies of spacecraft docking, existing docking/end effector performance criteria, and space proven, qualified docking data was conducted and evaluated, in order to provide recommended mechanical interface guidelines and interface tolerances for manual and autonomous capture operations. The criterion for the selection of the guidelines was maximum capability to handle malfunctions. Originally the guidelines for a zero velocity docking were considered to be covered within the grasping/berthing definition. It is acknowledged that perhaps a separate category needs to be established for this operation. The draft standard was delivered to the AIAA for review, revision, and issuance as the first U.S. national standard guideline on interfaces. The intent is to develop the guidelines into an International Standards Organization standard.

Thompson, Allen B.↗

Reducing neural network training time with parallel processing

Obtaining optimal solutions for engineering design problems is often expensive because the process typically requires numerous iterations involving analysis and optimization programs. Previous research has shown that a near optimum solution can be obtained in less time by simulating a slow, expensive analysis with a fast, inexpensive neural network. A new approach has been developed to further reduce this time. This approach decomposes a large neural network into many smaller neural networks that can be trained in parallel. Guidelines are developed to avoid some of the pitfalls when training smaller neural networks in parallel. These guidelines allow the engineer: to determine the number of nodes on the hidden layer of the smaller neural networks; to choose the initial training weights; and to select a network configuration that will capture the interactions among the smaller neural networks. This paper presents results describing how these guidelines are developed.

Rogers, James L., Jr.↗

Large Eddy/Reynolds-Averaged Navier-Stokes Simulations of CUBRC Base Heating Experiments

ven with great advances in computational techniques and computing power during recent decades, the modeling of unsteady separated flows, such as those encountered in the wake of a re-entry vehicle, continues to be one of the most challenging problems in CFD. Of most interest to the aerothermodynamics community is accurately predicting transient heating loads on the base of a blunt body, which would result in reduced uncertainties and safety margins when designing a re-entry vehicle. However, the prediction of heat transfer can vary widely depending on the turbulence model employed. Therefore, selecting a turbulence model which realistically captures as much of the flow physics as possible will result in improved results. Reynolds Averaged Navier Stokes (RANS) models have become increasingly popular due to their good performance with attached flows, and the relatively quick turnaround time to obtain results. However, RANS methods cannot accurately simulate unsteady separated wake flows, and running direct numerical simulation (DNS) on such complex flows is currently too computationally expensive. Large Eddy Simulation (LES) techniques allow for the computation of the large eddies, which contain most of the Reynolds stress, while modeling the smaller (subgrid) eddies. This results in models which are more computationally expensive than RANS methods, but not as prohibitive as DNS. By complimenting an LES approach with a RANS model, a hybrid LES/RANS method resolves the larger turbulent scales away from surfaces with LES, and switches to a RANS model inside boundary layers. As pointed out by Bertin et al., this type of hybrid approach has shown a lot of promise for predicting turbulent flows, but work is needed to verify that these models work well in hypersonic flows. The very limited amounts of flight and experimental data available presents an additional challenge for researchers. Recently, a joint study by NASA and CUBRC has focused on collecting heat transfer data on the backshell of a scaled model of the Orion Multi-Purpose Crew Vehicle (MPCV). Heat augmentation effects due to the presence of cavities and RCS jet firings were also investigated. The high quality data produced by this effort presents a new set of data which can be used to assess the performance of CFD methods. In this work, a hybrid LES/RANS model developed at North Carolina State University (NCSU) is used to simulate several runs from these experiments, and evaluate the performance of high fidelity methods as compared to more typical RANS models. .

Salazar, Giovanni↗

Advances in Molten Oxide Electrolysis for the Production of Oxygen and Metals from Lunar Regolith

As part of an In-Situ Resource Utilization infrastructure to sustain long term-human presence on the lunar surface, the production of oxygen and metals by electrolysis of lunar regolith has been the subject of major scrutiny. There is a reasonably large body of literature characterizing the candidate solvent electrolytes, including ionic liquids, molten salts, fluxed oxides, and pure molten regolith itself. In the light of this information and in consideration of available electrolytic technologies, the authors have determined that direct molten oxide electrolysis at temperatures of approx 1600 C is the most promising avenue for further development. Results from ongoing studies as well as those of previous workers will be presented. Topics include materials selection and testing, electrode stability, gas capture and analysis, and cell operation during feeding and tapping.

Sadoway, Donald R.↗

Coherence Analysis of the Space Launch System using Unsteady Pressure Sensitive Paint

Transonic buffet during atmospheric ascent is a major source of unsteady loading on launch vehicles that, in the past, has led to structural failures. Thus, determining accurate buffet forcing functions (BFFs) to properly predict the vehicle response to buffet is of vital importance in launch vehicle design. The state of the art for obtaining the BFFs relies on wind-tunnel tests where the fluctuating pressures are measured by pressure transducers (PTs) at sparse locations on a rigid, geometrically-scaled buffet model. To compute the BFFs, the outer mold line (OML) of the vehicle is mapped onto contiguous panels centered at the location of the PTs and the measured fluctuating pressures are integrated over the panels’ areas. To mitigate conservatism due to the assumption that the measured buffet pressures act in phase across each panel, coherence factors are applied, effectively reducing the integration areas and, therefore, the buffet forces. For coherence factors to provide the proper level of BFF attenuation, accurate knowledge of the spatial and temporal correlation of the buffet pressures is paramount. Unfortunately, even with hundreds of unsteady pressure transducers instrumenting the models, compromises must be made on the spatial resolution of the PTs. Typically, the PT layout aims at resolving the pressure correlation along the longitudinal axis of the vehicle, assuming that coherent structures propagate mostly in the longitudinal direction. As a result, the distribution of azimuthal/cross-stream correlation is not well known and its impact on the estimated BFFs is often neglected. To fill this and other knowledge gaps, extremely high spatial-resolution uPSP data were collected for three different production-design configurations of the Space Launch System in the NASA Ames Research Center Unitary Plan Wind Tunnel 11-Foot Transonic Wind Tunnel. Specifically, two cargo configurations, the Block 1 and Block 1B, and one crew configuration, the Block 1B crew, were surveyed at resolutions ranging from 600,000 to over 1 million uPSP measurement locations. To shed light on the temporal and spectral behavior of are presented. Several OML regions and flow features of interest are investigated, from theexpansion/shock on the Orion Multi-Purpose Crew Vehicle, to the terminal shock environment on the core stage, and the Strouhal shedding behind the boosters forward attach. The sensitivity of these environments to the vehicle attitude is examined. Furthermore, for selected panels,coherence factors that accurately capture the azimuthal coherence distribution of the buffetpressures are derived and their impact on the estimated BFFs is discussed. Finally, distributions of the local convection velocity and cross spectrum phase are presented.

buffet↗

Regenerative adsorbents of modified amines on solid supports

The invention relates to regenerative, solid sorbents for adsorbing carbon dioxide from a gas mixture, including air, with the sorbent including a modified polyamine and a solid support. The modified polyamine is the reaction product of an amine and an epoxide. The sorbent provides structural integrity, as well as high selectivity and increased capacity for efficiently capturing carbon dioxide from gas mixtures, including the air. The sorbent is regenerative, and can be used through multiple cycles of adsorption-desorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Regenerative adsorbents of modified amines on solid supports

The invention relates to regenerative, solid sorbents for adsorbing carbon dioxide from a gas mixture, including air, with the sorbent including a modified polyamine and a solid support. The modified polyamine is the reaction product of an amine and an epoxide. The sorbent provides structural integrity, as well as high selectivity and increased capacity for efficiently capturing carbon dioxide from gas mixtures, including the air. The sorbent is regenerative, and can be used through multiple cycles of adsorption-desorption.

Goeppert, Alain↗

Cooperative and bifunctional Ga-Ca-Cr 2 O 3 @CaO structured monoliths as versatile platform for reactive capture of CO 2 and its subsequent conversion to ethylene

Cooperative and bifunctional materials (BFMs) that integrate adsorbents and catalysts offer a promising strategy for the reactive capture of CO 2 to produce valuable fuels and chemicals. In this study, we developed structured BFMs via 3D printing that combine CaO as an adsorbent with Ga–Ca–Cr 2 O 3 metal oxides as the catalyst for the reactive capture of CO 2 and its subsequent conversion to C 2 H 4 via the oxidative dehydrogenation of C 2 H 6 (CO 2 -ODHE). Three different Ga–Ca compositions were used to modify the catalyst surface characteristics and enhance C 2 H 4 selectivity. In these formulations, Ga ions stabilize the oxygen lattice of the BFM, while Ca ions interact strongly with Cr to form CaCrO 4 , thereby altering the oxygen species and enhancing the material’s basic properties. Under adsorption–reaction conditions at 600–650 °C, the optimal BFM achieved an excellent C 2 H 4 selectivity of 96.4 %, attributed to a balanced redox process and improved basicity that facilitate efficient C 2 H 6 conversion and rapid desorption of C 2 H 4 without excessive oxidation. Overall, this work provides new insights into the formulation of BFMs monoliths and highlights the critical role of catalytic surface modification in enhancing C 2 H 4 selectivity in the CO 2 -ODHE reactive capture process.

C2H4 production↗

Large-Scale Commercial Carbon Capture Retrofit of the San Juan Generating Station

Enchant Energy, L.L.C. (Enchant) was selected to conduct a Front-End Engineering Design study (FEED) for the addition of a full-scale carbon capture system to remove carbon dioxide from the flue gas emissions of the two coal-fired generating units (total of 847 MW net) at San Juan Generating Station (SJGS), using Mitsubishi Heavy Industries Americas (MHIA) KM CDR Process™. Sargent & Lundy LLC (S&L) was selected as the primary technical lead, and along with various other organizations, were able to support Enchant’s completion of the following FEED tasks: Task 1 – Project Management & Planning; Task 2 – FEED Study; Task 3 - Final FEED Study Package. The FEED study period was between October 15, 2019 to September 30, 2022.

01 COAL, LIGNITE, AND PEAT↗