研究生: |
蔡皓融 Tsai, Hao-Rong |
---|---|
論文名稱: |
自適應力匹配法開發的力場研究:模擬超臨界二氧化碳的結構和傳輸性質 Simulating the Structural and Transport Properties of Supercritical CO2: an Force Field Study Developed by the Adaptive Force Matching Method |
指導教授: |
蔡明剛
Tsai, Ming-Kang |
學位類別: |
碩士 Master |
系所名稱: |
化學系 Department of Chemistry |
論文出版年: | 2019 |
畢業學年度: | 107 |
語文別: | 中文 |
論文頁數: | 58 |
中文關鍵詞: | 超臨界二氧化碳 、分子力場 、自適應力匹配法 、第一原理 |
英文關鍵詞: | Supercritical Carbon Dioxide, Adaptive Force Matching |
DOI URL: | http://doi.org/10.6345/NTNU201900296 |
論文種類: | 學術論文 |
相關次數: | 點閱:152 下載:0 |
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隨著世界各國的工業發展,二氧化碳被廣泛地排放至我們的大氣中。重新利用二氧化碳是維持地球上生活環境的關鍵課題之一。二氧化碳也是在生物、化學或地球科學領域中的重要流體,特別是超臨界二氧化碳(sCO2)已經應用於許多工業合成的應用中,有良好的選擇性來提取有價值的產物。因此了解sCO2的傳輸和結構性質可以幫助科學家提高工業上sCO2的使用效率。
從2005年到現在,已經發表了許多組的CO2力場參數,這些參數可用於分子動力學模擬(MD)對sCO2進行理論建模。但可惜的是,它們都沒有辦法在模擬中完全呈現sCO2的物理或化學性質。因此為了想要能描述在超臨界情況下的CO2與其他溶質的交互作用,在新的力場參數開發中仍然面臨了許多的挑戰。
自適應力匹配法(AFMM),可以用ab initio 級別所計算出的力,來擬合MD的力場參數,目前已經被證明可以有效地對超臨界流體的力場進行改善。在這項工作中,我們將會利用透過AFMM而獲得的新CO2力場參數,並使用MD模擬計算CO2的自擴散係數、徑向分佈函數和痕量擴散,最後將與文獻結果和實驗數據進行比較分析,來驗證新力場參數表現sCO2傳輸和物理性質的能力。
Due to the industrial evolution, carbon dioxide is a widely emitted to our atmosphere. Re-utilizing CO2 becomes an important and critical issue for maintain a sustainable living environment on earth. CO2 is also an important fluid in biological, chemical, or geochemical processes. In particular, supercritical carbon dioxide (sCO2) has been applied in numerous industrial synthesis applications for selectively extracting valuable product. Understanding the transport and structural properties of sCO2 can help the scientists improve the efficiency of the industrial extraction processes.
Since 2005, there are several theoretical modeling studies in sCO2 using molecular dynamics simulations (MD). Although there are multiple sets of CO2 force field parameters reported in the literature, none of them can fully present the physical properties of sCO2 in simulation. It still poses the challenge in force field parameter development for describing the sCO2–solute interactions under the supercritical CO2 condition.
Adaptive force matching method (AFMM), fitting the force fields from ab initio MD, has been proven to parametrize force fields effectively for supercritical liquid. In this work, we present the new parameters obtained by AFMM and using MD simulation to calculate the self-diffusion coefficient, radial distribution functions and trace-diffusion then compare with literature results and experiment data to advance the force field parameters for sCO2.
1. Brunner, G., Applications of Supercritical Fluids. 2010; Vol. 1, p 321-342.
2. De Melo, M. M. R.; Domingues, R. M. A.; Silvestre, A. J. D., et al., Extraction and purification of triterpenoids using supercritical fluids: From lab to exploitation. Mini-Rev. Org. Chem. 2014, 11 (3), 362-381.
3. De Melo, M. M. R.; Silvestre, A. J. D.; Silva, C. M., Supercritical fluid extraction of vegetable matrices: Applications, trends and future perspectives of a convincing green technology. J. Supercrit. Fluid. 2014, 92, 115-176.
4. DeSimone, J.; Guan, Z.; Elsbernd, C. J. S., Synthesis of fluoropolymers in supercritical carbon dioxide. Science. 1992, 257 (5072), 945-947.
5. Kim, S. W.; Ahn, J. P., Polycrystalline nanowires of gadolinium-doped ceria via random alignment mediated by supercritical carbon dioxide. Sci. Rep.-U.K. 2013, 3, 1606.
6. Long, J.-J.; Xu, H.-M.; Cui, C.-L., et al., A novel plant for fabric rope dyeing in supercritical carbon dioxide and its cleaner production. J. Clean. Prod. 2014, 65, 574-582.
7. Zhang, X.; Chang, D.; Liu, J., et al., Conducting polymer aerogels from supercritical CO2 drying PEDOT-PSS hydrogels. J. Mater. Chem. 2010, 20 (24), 5080-5085.
8. Anderson, K. E.; Mielke, S. L.; Siepmann, J. I., et al., Bond angle distributions of carbon dioxide in the gas, supercritical, and solid phases. J. Phys. Chem. A 2009, 113 (10), 2053-2059.
9. Saharay, M.; Balasubramanian, S., Enhanced Molecular Multipole Moments and Solvent Structure in Supercritical Carbon Dioxide. ChemPhysChem 2004, 5 (9), 1442-1445.
10. Mehr, C.; Biswal, R.; Collins, J., et al., Supercritical carbon dioxide extraction of caffeine from Guarana. J. Supercrit. Fluid. 1996, 9 (3), 185-191.
11. Peker, H.; Srinivasan, M.; Smith, J., et al., Caffeine extraction rates from coffee beans with supercritical carbon dioxide. AIChE J. 1992, 38 (5), 761-770.
12. Zhong, H.; Lai, S.; Wang, J., et al., Molecular Dynamics Simulation of Transport and Structural Properties of CO2 Using Different Molecular Models. J. Chem. Eng. Data. 2015, 60 (8), 2188-2196.
13. Murthy, C.; O'Shea, S.; McDonald, I.; Electrostatic interactions in molecular crystals: lattice dynamics of solid nitrogen and carbon dioxide. Mol. Phys. 1983, 50 (3), 531-541.
14. Murthy, C.; Singer, K.; McDonald, I. R.; Interaction site models for carbon dioxide. Mol. Phys. 1981, 44 (1), 135-143.
15. Harris, J. G.; Yung, K. H.; Carbon dioxide's liquid-vapor coexistence curve and critical properties as predicted by a simple molecular model. J. Phys. Chem. 1995, 99 (31), 12021-12024.
16. Potoff, J. J.; Siepmann, J. I. J. A. j., Vapor–liquid equilibria of mixtures containing alkanes, carbon dioxide, and nitrogen. AIChE J. 2001, 47 (7), 1676-1682.
17. Nieto-Draghi, C.; de Bruin, T.; Pérez-Pellitero, J., et al., Thermodynamic and transport properties of carbon dioxide from molecular simulation. J. Chem. Phys. 2007, 126 (6), 064509.
18. Akin-Ojo, O.; Song, Y.; Wang, F., Developing ab initio quality force fields from condensed phase quantum-mechanics/molecular-mechanics calculations through the adaptive force matching method. J. Chem. Phys. 2008, 129 (6), 064108.
19. Huang, I. S.; Tsai, M.-K., Interplay between Polarizability and Hydrogen Bond Network of Water: Reparametrizing the Flexible Single-Point-Charge Water Model by the Nonlinear Adaptive Force Matching Approach. J. Phys. Chem. A 2018, 122 (19), 4654-4662.
20. Vaz, R. V.; Gomes, J. R. B.; Silva, C. M., Molecular dynamics simulation of diffusion coefficients and structural properties of ketones in supercritical CO2 at infinite dilution. J. Supercrit. Fluid. 2016, 107, 630-638.
21. Koch, W.; Holthausen, M. C.; Holthausen, M. C., A chemist's guide to density functional theory. Wiley Online Library: 2001; Vol. 2.
22. Frisch, M. J.; Trucks, G. W.; Schlegel, H. B., et al. Gaussian 16 Rev. B.01, Wallingford, CT, 2016.
23. Zhao, Y.; Truhlar, D. G.; The M06 suite of density functionals for main group thermochemistry, thermochemical kinetics, noncovalent interactions, excited states, and transition elements: two new functionals and systematic testing of four M06-class functionals and 12 other functionals. Theor. Chem. Acc. 2008, 120 (1-3), 215-241.
24. Chai, J.-D.; Head-Gordon, M. J. P. C. C. P., Long-range corrected hybrid density functionals with damped atom–atom dispersion corrections. Phys. Chem. Chem. Phys. 2008, 10 (44), 6615-6620.
25. Thiel, W.; QM/MM methodology: Fundamentals, scope, and limitations. 2009; Vol. 42, p 203-214.
26. Chung, L. W.; Sameera, W. M. C.; Ramozzi, R., et al., The ONIOM Method and Its Applications. Chem. Rev. 2015, 115 (12), 5678-5796.
27. Plimpton, S. J. J. o. c. p., Fast parallel algorithms for short-range molecular dynamics. J. Comput. Phys. 1995, 117 (1), 1-19.
28. Jorgensen, W.; Tirado-Rives, J.; The OPLS Potential Functions for Protins. Energy Minimizations for Crystals of Cyclic Peptides and Crambin. J. Am. Chem. Soc. 1988, 110, 1666-1671.
29. Jorgensen, W. L.; Maxwell, D. S.; Tirado-Rives, J. J. J. o. t. A. C. S., Development and testing of the OPLS all-atom force field on conformational energetics and properties of organic liquids. J. Am. Chem. Soc. 1996, 118 (45), 11225-11236.
30. Kaminski, G. A.; Friesner, R. A.; Tirado-Rives, J., et al., Evaluation and Reparametrization of the OPLS-AA Force Field for Proteins via Comparison with Accurate Quantum Chemical Calculations on Peptides. J. Phys. Chem. B 2001, 105 (28), 6474-6487.
31. Rizzo, R. C.; Jorgensen, W. L., OPLS All-Atom Model for Amines: Resolution of the Amine Hydration Problem. J. Am. Chem. Soc. 1999, 121 (20), 4827-4836.
32. Watkins, E. K.; Jorgensen, W. L., Perfluoroalkanes: Conformational Analysis and Liquid-State Properties from ab Initio and Monte Carlo Calculations. J. Phys. Chem. A 2001, 105 (16), 4118-4125.
33. Zhu, C.; Byrd, R. H.; Lu, P., et al., Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization. ACM T. Math. Software 1997, 23 (4), 550-560.
34. Lemmon, E. J.; Thermophysical Properties of Fluid Systems, NIST chemistry WebBook, NIST standard reference database number 69. 2005.
35. Groß, T.; Buchhauser, J.; Lüdemann, H.-D. J. T. J. o. c. p., Self-diffusion in fluid carbon dioxide at high pressures. J. Chem. Phys. 1998, 109 (11), 4518-4522.
36. Funazukuri, T., Measurements of Binary Diffusion Coefficients of 20 Organic Compounds in CO2 at 313 and 16 MPa. J. Chem. Eng. Jan. 1996, 29 (1), 191-192.