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UNIVERSITY of CALIFORNIA RIVERSIDE Density Functional UNIVERSITY OF CALIFORNIA RIVERSIDE Density Functional Theory for High-Throughput Screening of Chemicals and Materials A Dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Chemical and Environmental Engineering by Jia Fu June 2015 Dissertation Committee: Dr. Jianzhong Wu, Chairperson Dr. David Kisailus Dr. Chia-En Chang Copyright by Jia Fu 2015 The Dissertation of Jia Fu is approved: Committee Chairperson University of California, Riverside Acknowledgements I feel grateful to many people for their great support over the years. First and foremost, I would like to thank my supervisor Prof. Jianzhong Wu for his superb and insightful guidance. Learned from him, I start to know how to think as a theoretician, to solve problems in an elegant way and to enjoy the beauty of statistical mechanics. His strong enthusiasm motivate me and shows an excellent example on how to be a successful chemical engineer and professor. I sincerely appreciate my PhD committee, Prof. David Kisailus, Prof. Chia-en A. Chang for their great advice and help in my qualifying exam and final defense. I also wish to express my special thanks to Prof. De-en Jiang, Prof. Shuangliang Zhao, Dr. Zhehui Jin, Dr. Ke Wang, Dr. Yu Liu and Dr. Jehoon Kim for their valuable support during my PhD studying. Also all the good friends that I have made in Riverside for their encouragement throughout this special period. What’s more, I greatly appreciate the endless support and patience of my parents during this long journey, who support and encourage me more than anyone else to pursue an academic career. iv In this dissertation, some parts are the reprint of the materials appeared in Journal of Physical Chemistry Letter (Volume 4, Issue 21, Page 3687-3691, October 2013), Journal Computer-Aided Molecular Design (Volume 28, Issue 3, Page 299-304, March 2014), Chemical Engineering Science (Volume 126, Page 370-382, April 2015), Langmuir (Volume 29, Issue 42, Page 12997-13002, 2013), Journal of Physical Chemistry C (Volume 119, Issue 10, Page 5374-5385, 2015), Journal of Colloid and Interface Science (Volume 438, Page 191-195, January 2015). This work is financially sponsored by the US Department of Energy (DOE) (DE-FG02-06ER46296 and DE-AC02-05CH11231), the National Science Foundation (NSF-CBET-0852353, NSF-CBET-1404046). This work utilizes supercomputer from the National Energy Research Scientific Computing Center (NERSC). v ABSTRACT OF THE DISSERTATION Density Functional Theory for High-Throughput Screening of Chemicals and Materials by Jia Fu Doctor of Philosophy Graduate Program in Chemical and Environmental Engineering University of California, Riverside, June 2015 Professor Jianzhong Wu, Chairperson Multiscale modelling is an essential part in chemical engineering field, recently with the developments in physical and computer sciences, computer modelling plays a more and more important role in quantitative predictions of chemical reactions and thermodynamic data, covering broad applications to problems of practical concern. Whereas classical simulations and quantum density functional theory methods have become routine tools for engineering applications, the power of classical density functional theory has not been widely recognized, which has already shown great success in many model systems. Considering its efficiency and accuracy, it’s necessary to establish a systematic way to utilize this method applied in realistic applications. During this PhD research, I mainly focus on developing classical density functional theory for large-scale screening of chemicals and materials, especially for organic compounds solvation free energy and gas storage and transport properties in nanoporous materials. vi For the hydration free energy calculation part, we try to build a reliable multiscale procedure to predict the water solvation free energies of organic compounds at ambient conditions, by combination of quantum mechanics, statistical mechanics and molecular mechanics force fields. Using the experimental data of hydration free energies as the benchmark, we show that the new method, taking the explicit solvent molecules into consideration, shows a comparable accuracy as full atomistic molecular simulations, but over one magnitude faster calculation speed. We also find that the theoretical results are sensitive to the input generation methods, i.e. selection of quantum-mechanical methods for determining atomic charges and solute configurations, the assignment of the van der Waals parameters and the solvent models. In generally speaking, HF/6- 31G/Vac/OPLS/ChelpG gives the best prediction, in particular those less hydrophilic ones, the overall average unsiged error is 1.35 kcal/mol compared to 700 common organic molecular hydration free energy database, close to the experimental measurement chemical accuracy limit 1 kcal/mol. On the other hand, we have investigated the four representative versions of non- local density functionals as efficient methods to predict gas adsorption in both simple slit pore model system and a large library of real metal-organic frameworks (MOFs) under a broad range of temperatures and pressures, compared with grand canonical Monte Carlo simulation data. Overall all the four methods are reasonably accurate in comparison with the simulation results, but our results show for each specific gas and interested condition, there is a best candidate: for DOE’s hydrogen storage target condition, it’s FMSA, while for ARPA-E’s methane storage target condition, it’s MFA. Besides, combing with entropy vii scaling method, we can also predict the gas self-diffusion coefficient in the same one time calculation with an average calculating time 30 seconds, far beyond the classical molecular simulation ways. From a computational perspective, the classical density functional theory is shown as a versatile and promising tool for large-scale screening of thousands of chemicals and nanostructured materials with a modern desktop computer. viii Table of Contents Title Page Copyright Page Approval Page Acknowledgements ............................................................................................................ iv Abstract of the dissertation ............................................................................................... vi Chapter 1. Introduction .......................................................................................................1 1.1 Background ..............................................................................................................1 1.1.1 Quantum Mechanics .........................................................................................1 I. Wavefunction Methods..................................................................................1 II. Quantum Density Functional Theory ...........................................................2 1.1.2 Classical Simulation Methods ..........................................................................6 I. Molecular Mechanic Force Fields .................................................................6 II. Molecular Dynamics ..................................................................................10 III. Monte Carlo Method .................................................................................11 1.1.4 Hydration Free Energy ..................................................................................13 1.1.3 Gas Adsorption in Nanoporous Materials .....................................................16 1. 2 Dissertation organization .......................................................................................18 Chapter 2. Basic Concepts of Classical Density Functional Theory .................................29 2. 1 Density Profile ........................................................................................................29 2. 2 Density Functional Theory .....................................................................................31 ix 2. 3 Intrinsic Helmholtz Free Energy ............................................................................32 2. 4 Euler-Lagrange Equation .......................................................................................33 2. 5 Excess Helmholtz Free Energy ..............................................................................33 Chapter 3. Computer-Aided Materials Design .................................................................40 3.1 Density functional methods for fast screening of metal-organic frameworks for hydrogen storage ...........................................................................................................40 3.2 Extension of excess-entropy scaling for the self-diffusivity of confined gases ......69 3.3 Classical Density Functional Theory for Systematic Predictions of Thermodynamic and Kinetic Data for CH4 Adsorption in Metal-Organic Frameworks ..........................90 3.4 Seeking Metal-Organic Frameworks (MOFs) for Methane Storage in Natural Gas Vehicles .......................................................................................................................129 3.5 Nitrogen-Doped Porous Aromatic Frameworks for Enhanced CO2 Adsorption ..155 Chapter 4. Fast Screening Method for Predicting Hydration Free Energy .....................194 4.1 High-throughput prediction of the hydration free energies of small molecules from a classical density functional theory ..............................................................................194 4.2
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