5-hydroxymethyl furfural (HMF) is a platform chemical, which can be derived from lignocellulosic biomass, and used for production of liquid fuels and polymers. We demonstrate a process for production of...
An
integrated, modular, and multifunctional process is conceptually
designed, simulated, and optimized for direct utilization of CO2 from dilute flue gas to produce high-quality syngas, a precursor
for many value-added chemicals and liquid transportation fuels. The
process is intensified to simultaneously capture and convert CO2 using methane, natural gas, or excess fuel gas from the same
plant, or using nearby unconventional methane from biogas or landfill
gas. It is an integrated adsorption-purge-reaction system where CO2 is first adsorbed and then desorbed using methane-rich feed
leading to a mixture suitable for dry-reforming. The merging of concentration-based
CO2 desorption with the reactor feed premixing step eliminates
the need for pressure or temperature swings and significantly reduces
the energy penalty and cost of CO2 capture and utilization.
The process is simulated at different conditions using a high-fidelity
process model to elucidate the effects of key decision variables as
well as the trade-offs and interactions between the capture and reforming
sections. The technology is flexible to handle different feedstock
compositions, and is amenable to both centralized and distributed
production of syngas. A constrained grey-box optimization method is
employed to achieve a maximum of 99.7% net overall CO2 utilization
considering auxiliary emissions at a total cost ranging from $110–130
per ton of syngas. As much as 14.6% of the total CO2 input
to the process comes “directly” from flue gas without
additional cost for CO2 capture while maintaining about
91% overall CO2 utilization. The technology is also computationally
found to be robust in terms of CO2 utilization and cost
for different natural gas feeds with CO2 contamination
as high as 60%. This can be attributed to the novel process intensification
concept and the gray-box constrained optimization method presented
in this work.
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