465824 Design and Optimization of Integrated Carbon Capture and Conversion with Natural Gas to Produce Syngas
Specifically, we combine a CO2-selective zeolite  and a dry-reforming catalyst in a sequential configuration to capture and store CO2 from dilute flue gas, and convert it to syngas using renewables. A special instance of this is when both the zeolite and catalyst are packed inside a single column in a layered configuration. The process is dynamic and operates in a cyclic manner, where each cycle consists of at least two steps. In the first step, the zeolite section separates and intermittently stores CO2 from flue gas at ambient temperature. In the second step, the zeolite section automatically supplies CO2 and methane toward the catalyst section for conversion, due to desorption triggered by solar heating and/or the introduction of methane-rich feed. The high temperature for conversion is partially achieved by using concentrated solar energy. The simultaneous desorption and conversion of CO2 completely eliminates a separate regeneration step, which is typically the most energy-intensive operation in current capture technologies.
The integration of CO2 adsorption, intermittent storage, desorption using reactor feed, and conversion with methane is largely controlled by the trade-offs between these competing phenomena. Hence, a predictive model of the overall process has been difficult to create – largely because of the time-dependent, distributed and cyclic nature of the process and the complex interaction between the adsorption and conversion sections. In this work, we use a nonlinear, algebraic and partial differential equation (NAPDE)-based model that captures the equilibrium, transport and kinetic behavior of the gases for the dynamic adsorption, desorption and conversion operations. The optimization of the NAPDE model is also challenging. To this end, we have recently developed and applied a data-driven platform for the simulation-based optimization of complex process models, which treats the NAPDE-based model as a black-box system and use it to generate the required data for optimization. We optimize the process for different feed conditions and syngas specifications (H2:CO ratio). Once optimized, the integrated technology shows significant promise for reducing the cost of CO2 capture by eliminating the need for a material regeneration step, and reducing the cost of CO2 conversion by storing solar energy as chemical energy while mitigating GHG emission.
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