On the use of molecular-based thermodynamic models to assess the performance of solvents for CO2 capture processes: monoethanolamine solutions.
On the use of molecular-based thermodynamic models to assess the performance of solvents for CO2 capture processes: monoethanolamine solutions.
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DOI：
10.1039/c6fd00041j
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发表时间：
2016-10
影响因子：
3.4
通讯作者：
C. Brand;E. Graham;J. Rodriguez;A. Galindo;G. Jackson;C. Adjiman
中科院分区：
文献类型：
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作者：
C. Brand;E. Graham;J. Rodriguez;A. Galindo;G. Jackson;C. Adjiman
预测模型在设计用于捕获发电厂排放的二氧化碳（CO2）的燃烧后过程中起着重要作用。提出了一种基于速率的吸收剂模型，以研究使用含水单乙醇胺（MEA）作为溶剂的CO2反应性捕获，集成了基于预测分子的状态方程：SAFT-VR SW（统计关联流体理论-可变范围，方阱）。一个独特的物理方法是通过模拟的过程中固有的化学平衡。与更常用的化学方法相比，这消除了明确考虑反应产物的需要，并大大减少了模拟吸收器所需的实验数据量。吸收剂模型的预测能力进行了分析，从10个试点工厂运行的配置文件，考虑两种情况：（i）没有中试工厂的数据被用于模型开发;（ii）只有一组有限的中试工厂的数据被使用。在第一种情况下，清洁气体中CO2的质量分数在除一种情况外的所有情况下都被低估，这表明使用这种预测方法可以获得溶剂的最佳情况性能。在第二种情况下，基于来自单个中试装置运行的数据来估计单个参数，以校正反应性溶剂中CO2扩散率的急剧变化。这个参数被发现是可转移的广泛的操作条件。灵敏度分析，然后进行，和液体粘度和扩散率被发现是关键属性的组成分布的预测。温度和组成分布对对应于热产生或耗散的主要来源的热力学性质敏感。拟议的建模框架可用作溶剂的早期评估，以帮助缩小搜索空间，并可帮助确定实验和更详细建模的目标溶剂。
Predictive models play an important role in the design of post-combustion processes for the capture of carbon dioxide (CO2) emitted from power plants. A rate-based absorber model is presented to investigate the reactive capture of CO2 using aqueous monoethanolamine (MEA) as a solvent, integrating a predictive molecular-based equation of state: SAFT-VR SW (Statistical Associating Fluid Theory-Variable Range, Square Well). A distinctive physical approach is adopted to model the chemical equilibria inherent in the process. This eliminates the need to consider reaction products explicitly and greatly reduces the amount of experimental data required to model the absorber compared to the more commonly employed chemical approaches. The predictive capabilities of the absorber model are analyzed for profiles from 10 pilot plant runs by considering two scenarios: (i) no pilot-plant data are used in the model development; (ii) only a limited set of pilot-plant data are used. Within the first scenario, the mass fraction of CO2 in the clean gas is underestimated in all but one of the cases, indicating that a best-case performance of the solvent can be obtained with this predictive approach. Within the second scenario a single parameter is estimated based on data from a single pilot plant run to correct for the dramatic changes in the diffusivity of CO2 in the reactive solvent. This parameter is found to be transferable for a broad range of operating conditions. A sensitivity analysis is then conducted, and the liquid viscosity and diffusivity are found to be key properties for the prediction of the composition profiles. The temperature and composition profiles are sensitive to thermodynamic properties that correspond to major sources of heat generation or dissipation. The proposed modelling framework can be used as an early assessment of solvents to aid in narrowing the search space, and can help in determining target solvents for experiments and more detailed modelling.