Diamine-appended metal-organic frameworks exhibiting step-shaped CO2 adsorption are exceptional candidates for energy-efficient carbon capture. However, there are few studies examining their performance in real-world capture scenarios, in part due to the challenge inherent in modeling their CO2 uptake behavior. Here, we develop a dual-site Sips model to fit experimental CO2 adsorption data for dmpn-Mg2(dobpdc) (dmpn = 2,2-dimethyl-1,3-diaminopropane; dobpdc 4-= 4,4′-dioxidobiphenyl-3,3′-dicarboxylate) and develop a linear driving force model for the adsorption kinetics based on available experimental data. These models are used to develop a dynamic, fixed bed, non-isothermal contactor model using shaped particles of the material, which is validated with experimental breakthrough data. We also examine the effects of the high heat of adsorption of the material on CO2 uptake performance and find that heat removal is essential to maximize capture performance. We finally investigate "basic" (no bed cooling during adsorption) and "modified" (bed cooling during adsorption) temperature swing adsorption (TSA) processes using dmpn-Mg2(dobpdc) and their process economics are compared to a state-of-the-art monoethanolamine (MEA) capture system, with and without heat recovery. In the absence of heat recovery, the adsorbent systems are more costly than established technology. However, with 85% heat recovery, both adsorbent-based TSA processes are projected to cost less than the MEA system. This work highlights that thermal management is vital for implementation of dmpn-Mg2(dobpdc) as a viable CO2 capture technology. Investigation of other contactor technologies that can provide unique ways to manage system heat represent promising future areas of study.

A detailed model of a capsule containing sodium carbonate solution is developed here to study the microencapsulated carbon capture solvents (MECS). A rigorous vapor−liquid equilibrium model is developed for the Na 2 CO 3 −CO 2 −H 2 O system, where liquid-phase nonideality is modeled by the electrolyte nonrandom two-liquid model. The data from the experiments conducted at the Lawrence Livermore National Laboratory is used to obtain a maximum likelihood estimate of the initial solvent concentration inside the capsules and the parameters for the capsule model. A nonisothermal, dynamic model of a fixed bed contactor filled with these capsules is then developed. In addition to direct steam injection, indirect heating using an embedded heat exchanger is modeled for desorption. Finally, the model is used to simulate temperature swing absorption and desorption cycles. The results of these studies indicate that there is an optimal residence time or superficial flue gas velocity to minimize the bed volume. However, the total energy requirement for desorption monotonically decreases with increased residence time as the proportion of the sensible heat to the total regeneration heat keeps decreasing. Furthermore, heat recovery from the bed is crucial to keep energy penalty for regeneration low. A techno-economic analysis is conducted, and the equivalent annual operating cost (EAOC) is analyzed for two different reactor materials (concrete and carbon-steel) and compared with a system using a conventional monoethanolamine (MEA) solvent. The minimum EAOC for the MECS fixed bed configuration is approximately 1.8−2.7 times higher than the EAOC for an MEA system with a similar amount of heat recovery (85%). The impact of ±50% uncertainty in the capital cost estimate is also evaluated, and the minimum EAOC is 1.5 times higher than the MEA technology for 85% heat recovery. These results using microencapsulated sodium carbonate solution are a starting point that sets an upper limit on the cost of the MECS carbon-capture system. Improvements to the MECS capsules (e.g., using a higher carbonate concentration and lowering the shell mass transfer resistance) and also exploring other contactor technologies are expected to decrease the system cost and make it more competitive.

Due to the recent boom in shale gas production, aromatics production using direct nonoxidative methane dehydroaromatization (DHA) is being investigated extensively. However, due to rapid coke formation, catalysts in the nonoxidative methane DHA reactors get deactivated, which is one of the critical issues for the commercial success of the methane DHA process. In this paper, a model for catalyst deactivation is developed. Rate models for other DHA reactions are developed by considering the decrease in the catalyst activity with time. Due to the very fast coke formation rate on the fresh catalyst, there is coke formation immediately upon the introduction of the feed. Therefore, an algorithm is developed for estimation of the initial state of the reactor and the kinetic parameters by coupling an iterative direct substitution approach with an optimization approach. Transient experimental data from an in-house reactor are first reconciled and then used for developing the kinetic model including the coke formation model. Using the rate model, a dynamic, heterogeneous, multiscale reactor model with embedded heating is developed. The model couples the catalyst pellet level model with a reactor level model. Impacts of temperature, L/D ratio, and scheduling of reactors on variability in conversion and yield with time are studied.

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Rigorous rate-based models were developed for post-combustion CO 2 capture using chilled aqueous ammonia. Optimal estimation of mass-transfer and kinetic model parameters is undertaken by a simultaneous regression approach using wetted wall column and pilot plant data. In addition to the weighted leastsquares estimate, two robust estimation approaches using Hampel's redescending M-estimator and logistic estimator are used for parameter estimation. A fully Bayesian approach is used for quantifying the uncertainty of the selected parameters. A model of a novel membrane-assisted chilled ammonia process was developed for reducing the energy penalty in the NH 3 abatement section where a reverse osmosis membrane is used to aid in the separation of ammonia from the wash water. The study shows that the membrane can considerably lower the reboiler, cooler, and condenser duties in the NH 3 abatement section, but with higher water removal, there is a steeper rise in the required membrane area. Bayesian inference is observed to result in considerable reduction in prediction uncertainty of key performance variables.