<p>In this thesis, we present novel computational methods and frameworks to address the challenges associated with the determination of free energy profiles for condensed-phase chemical reactions using combined quantum mechanical and molecular mechanical (QM/MM) approaches. We focus on overcoming issues related to force matching, molecular polarizability, and convergence of free energy profiles. First, we introduce a method called Reaction Path-Force Matching in Collective Variables (RP-FM-CV) that efficiently carries out ab initio QM/MM free energy simulations through mean force fitting. This method provides accurate and robust simulations of solution-phase chemical reactions by significantly reducing deviations on the collective variables forces, thereby bringing simulated free energy profiles closer to experimental and benchmark AI/MM results. Second, we explore the role of pairwise repulsive correcting potentials in generating converged free energy profiles for chemical reactions using QM/MM simulations. We develop a free energy correcting model that sheds light on the behavior of repulsive pairwise potentials with large force deviations in collective variables. Our findings contribute to a deeper understanding of force matching models, paving the way for more accurate predictions of free energy profiles in chemical reactions. Next, we address the underpolarization problem in semiempirical (SE) molecular orbital methods by introducing a hybrid framework called doubly polarized QM/MM (dp-QM/MM). This framework improves the response property of SE/MM methods through high-level molecular polarizability fitting using machine learning (ML)-derived corrective polarizabilities, referred to as chaperone polarizabilities. We demonstrate the effectiveness of the dp-QM/MM method in simulating the Menshutkin reaction in water, showing that ML chaperones significantly reduce the error in solute molecular polarizability, bringing simulated free energy profiles closer to experimental results. In summary, this thesis presents a series of novel methods and frameworks that improve the accuracy and reliability of free energy profile estimations in condensed-phase chemical reactions using QM/MM simulations. By addressing the challenges of force matching, molecular polarizability, and convergence, these advancements have the potential to impact various fields, including computational chemistry, materials science, and drug design.</p>

Indiana University-Purdue University Indianapolis (IUPUI) / In this thesis, we present novel computational methods and frameworks to address the challenges associated with the determination of free energy profiles for condensed-phase chemical reactions using combined quantum mechanical and molecular mechanical (QM/MM) approaches. We focus on overcoming issues related to force matching, molecular polarizability, and convergence of free energy profiles. First, we introduce a method called Reaction Path-Force Matching in Collective Variables (RP-FM-CV) that efficiently carries out ab initio QM/MM free energy simulations through mean force fitting. This method provides accurate and robust simulations of solution-phase chemical reactions by significantly reducing deviations on the collective variables forces, thereby bringing simulated free energy profiles closer to experimental and benchmark AI/MM results. Second, we explore the role of pairwise repulsive correcting potentials in generating converged free energy profiles for chemical reactions using QM/MM simulations. We develop a free energy correcting model that sheds light on the behavior of repulsive pairwise potentials with large force deviations in collective variables. Our findings contribute to a deeper understanding of force matching models, paving the way for more accurate predictions of free energy profiles in chemical reactions. Next, we address the underpolarization problem in semiempirical (SE) molecular orbital methods by introducing a hybrid framework called doubly polarized QM/MM (dp-QM/MM). This framework improves the response property of SE/MM methods through high-level molecular polarizability fitting using machine learning (ML)-derived corrective polarizabilities, referred to as chaperone polarizabilities. We demonstrate the effectiveness of the dp-QM/MM method in simulating the Menshutkin reaction in water, showing that ML chaperones significantly reduce the error in solute molecular polarizability, bringing simulated free energy profiles closer to experimental results. In summary, this thesis presents a series of novel methods and frameworks that improve the accuracy and reliability of free energy profile estimations in condensed-phase chemical reactions using QM/MM simulations. By addressing the challenges of force matching, molecular polarizability, and convergence, these advancements have the potential to impact various fields, including computational chemistry, materials science, and drug design.

In this work the electronic and magnetic structure of the crystals Sr2FeMoO6, Fe0.5Cu0.5Cr2S4, LuFe2O4 and the molecules FeStar, Mo72Fe30, W72Fe30 are investigated by means of X-ray spectroscopic techniques. These advanced materials exhibit very interesting properties like magnetoresistance or multiferroic behaviour. In case of the molecules they also could be used as spin model systems. A long standing issue concerning the investigation of these materials are contradicting results found for the magnetic and electronic state of the iron (Fe) ions present in these compounds. Therefore this work focuses on the Fe state of these materials in order to elucidate reasons for these problems. Thereby the experimental results are compared to multiplet simulations.

Thin metallic films with magnetic properties like magnetite are an interesting material in current technological applications. In the presented work the iron oxide films are grown by molecular beam epitaxy on MgO(001) substrates at temperatures between room temperature and 600K. The film and surface structure are investigated by x-ray reflectometry (XRR), x-ray diffraction (XRD) and low energy electron diffraction (LEED). The chemical properties are investigated by x-ray photoelectron spectroscopy (XPS). Furthermore, charge transfer multiplet (CTM) calculations are performed as a means to gain additional information from photoemission spectra. It is shown that only for temperatures higher than 500K the oxide film forms a spinel structure. A previously unobserved (2x1) surface reconstruction in two orthogonal domains is found for various preparation conditions. The application of CTMs results in good quantitative and qualitative agreement to other methods for the determination of the film stoichiometry. In addition CTMs can well describe the segregation of Mg atoms into the oxide film either during film growth or during film annealing. It is found that initially Mg substitutes Fe on all possible lattice sites, only for prolonged treatment at high temperature do Mg atoms favour the octahedral lattice sites of divalent Fe.