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    Optimizing network pathways of CO2 conversion processes

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    Date
    2021-03-01
    Author
    Saad, Dimitri M.
    Bilbeisi, Rana A.
    Alnouri, Sabla Y.
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    Abstract
    Carbon capture and utilization (CCU) has gained great attraction as an alternative route of producing carbon-based chemicals, which also mitigates atmospheric CO2. This paper develops a numerical optimization model that utilizes experimental data pertaining to the CO2 hydrogenation reaction (catalyst type, conversion, selectivity, and space velocity) to guide engineers to pick the optimal industrial scale CCU process. Four carbon conversion pathways that produce value-added chemicals are assessed: conversion into methanol, methane, carbon monoxide, and dimethyl ether. This techno-economic analysis is founded on elaborate sizing methods and process design principles of heat exchangers, compressors, reactors, and separators. Based on the collected data reported in the literature, the state-of-the-art model incorporates and assesses feed and catalyst costing, plant sizing and costing, and revenues from the produced commodity chemicals at market price. A thorough optimization analysis is conducted to determine the optimal conversion pathway subject to corresponding constraints. The objective of this problem targets cost minimization with respect to various production constraints. The results of the model show that the optimal CCU path is associated with the CO2-to-MeOH/DME reactions, with the model almost strictly allocating the available CO2 mass at the different production rates to processes generating these products. This result is due to the processes' high reaction selectivity, which has been at the forefront of research in CO2 hydrogenation, in addition to the relatively high market price of both these products. Such results reinforce the promise of George Olah's Methanol Economy. The optimization model thus presents a novel basis for a comprehensive and quantitative multi-variable CCU plant assessment, utilizing optimized carbon conversion reaction data.
    URI
    https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85100028840&origin=inward
    DOI/handle
    http://dx.doi.org/10.1016/j.jcou.2020.101433
    http://hdl.handle.net/10576/53857
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    • GPC Research [‎501‎ items ]

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