胺洗滌是一種廣泛被認可的從煙氣中捕獲CO2的技術，它在實現2050年淨零碳排放目標方面扮演著關鍵角色。然而，以往對吸收劑和工藝的評估主要是獨立進行的，並未考慮它們之間的協同效應。為了解決這個限制，需要一種綜合性的方法，能夠同時評估溶劑和工藝。
本研究旨在在過程模擬器中開發一個通用溶劑模型，以整合新型溶劑和工藝篩選。該模型基於Aspen Plus®中實施的電解質非隨機二液（e-NRTL）活度係數模型。模型參數通過拟合一系列不同鹼度的胺的實驗數據（𝑝𝐾𝑎和CO2溶解度）來確定。通過使用這個通用溶劑模型，可以基於胺的pKa和分子結構來預測特定胺與CO2反應性。
此外，本研究通過模擬使用開發的模型的CO2吸收器，展示了通用溶劑模型的實際應用。這項工作的成果有潛力促進同時開發溶劑和工藝，用於CO2捕獲，從而為實現淨零碳排放做出貢獻。總體來說，這項研究滿足了在開發胺基CO2捕獲技術中綜合方法的需求，使得更高效和有效的碳中和解決方案成為可能。

Amine scrubbing is a widely recognized technology for capturing CO2 from flue gas and plays a crucial role in achieving the goal of net-zero carbon emissions by 2050. However, previous evaluations of absorbents and processes have mostly been conducted independently, without considering their synergistic effects. To address this limitation, there is a need for a comprehensive approach that can evaluate both the solvent and the process simultaneously.
This work focuses on developing a generic solvent model within a process simulator to integrate novel solvent and process screening. The model is based on the Electrolyte Nonrandom Two-Liquid (e-NRTL) activity coefficient model, implemented in Aspen Plus®. The model parameters are determined by fitting experimental data on 𝑝𝐾𝑎 and CO2 solubility for a range of amines with varying basicity. By utilizing this generic solvent model, the reactivity of a specific amine with CO2 can be predicted based on its 𝑝𝐾𝑎 and molecular structure.
Furthermore, this study showcases the practical application of the generic solvent model by simulating a CO2 absorber using the developed model. The outcomes of this work have the potential to facilitate the simultaneous development of both solvents and processes for CO2 capture, thus contributing to the realization of net-zero carbon emissions. Overall, this research addresses the need for an integrated approach in the development of amine-based CO2 capture technologies, enabling more efficient and effective solutions for achieving carbon neutrality.

Abstract i
摘要 ii
Contents iii
List of Figures v
List of Tables viii
Chapter1 Introduction 1
1.1 Background 1
1.2 Literature review 2
1.3 Motivation 4
1.4 Thermodynamic modeling 6
Chapter2 Modeling methods 7
2.1 Amine selection 7
2.2 Aqueous phase chemical equilibrium 11
2.3 Parameter settings 13
2.4 𝑝𝐾𝑎 fitting process 15
2.5 CO2 solubility fitting process 16
2.6 Calculation of solvent accessible surface area 17
2.7 Prediction of ΔGcarb 18
2.8 Data regression 19
Chapter3 Results and discussions 20
3.1 Overall 𝑝𝐾𝑎 fitting results 20
3.2 Overall CO2 solubility fitting results 31
3.3 Carbamate stability 50
3.4 The results of correlating experimental ΔGcarb , 𝑝𝐾𝑎 and SASA 53
3.5 ΔGcarb prediction 60
3.6 CO2 capacity comparison of isothermal and adiabatic absorber 60
Chapter4 Conclusions 73
Chapter5 Reference 74

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