New and Traditional Density Functional Theory Methods for Unveiling Mechanisms of Green Chemistry Processes

Green chemistry develops processes and products that reduce the use of substances that are harmful for humans and the environment.Computational chemistry can advance green chemistry research by offering tools to model and predict chemical behavior and by facilitating the design of eco-friendly processes and materials.Density functional theory (DFT) is one of the most widely used computational tools in green chemistry that is vital for explaining and predicting reaction pathways, designing catalysts, and assessing environmental impact, all of which advance sustainability in chemical research.The first part of this thesis (Chapter 2) investigates the mechanism of reversible CO 2 capture -a promising green chemistry technology -by a cyclodextrin-based metal-organic framework called CD-MOF-2, which is synthesized from environmentally benign ingredients.By analysing results of DFT modeling and available experimental data, this study describes the nature and structural characteristics of diverse alcohol adsorption sites in CD-MOF-2, capable of binding CO 2 in the irreversible, reversible, and weak regimes.It explains the role of hydrogen bonding environments in modulating CO 2 binding strength at these sites.These findings provides insights into designing solid materials for CO 2 capture or detection by linking acid-base proton equilibrium and hydrogen bonding to CO 2 binding efficiency.The second part of the thesis presents a new DFT method for describing excited electronic states, modeling of which is essential for green chemistry research in photochemistry, photovoltaics, and photocatalysts.Many inaccuracies of time-dependent (TD) DFT, which is most often used to model excited states, arise from its non-variational nature.On the other hand, recently developed variational time-independent DFT must deal with the problem of excited states collapsing onto the ground state during their optimization.We present a computational method that solves the collapse problem while keeping theory simple and computations efficient.This is done in two steps.The first chapter of the development part of the thesis (Chapter 3) presents a method to avoid collapse of molecular orbitals within a single electronic state during the self-consistent field (SCF) optimization.This method, called variable-metric SCF, is applied to describe the electronic ground state.The main idea of the method is to allow nonorthogonal molecular orbitals and then penalize linearly dependent orbitals with a term that is added to the DFT energy functional.Variable-metric SCF method allows to use molecular orbital coefficients as independent variables in a direct, unconstrained minimization.It is shown that variable-metric SCF equations are simple and can be solved efficiently even with a basic preconditioned conjugate gradient algorithm for various molecular and solid-state systems, including challenging narrow gap systems and singlet diradicals.The second chapter of the development part (Chapter 4) extends variable-metric SCF to multiple electronic states by adding a new term that penalizes overlapping states, not just overlapping molecular orbitals.The resulting variable-metric time-independent DFT method treats both ground and excited states variationally and equally, improving the accuracy of modeling charge-transfer and two-electron excited states of various molecules compared to TDDFT.The variational nature of variable-metric time-independent DFT also allows to greatly simplify the evaluation of atomic forces, which will lead to more efficient non-adiabatic molecular dynamics simulations of green photochemical and photocatalytic processes.Going through the PhD path has been a truly life-changing experience for me, and this milestone would not have been possible to reach without the support and guidance I received from many people.First and foremost, I am deeply grateful and want to extend my heartfelt thanks to my supervisor, Dr. Rustam Z. Khaliullin, for his constant

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