Metal Organic Materials (MOM) are composed of transition metal ions as connectors and organic ligands as linkers. MOMs have been found to have high porosity, catalytic, and optical properties. Here we study the gas adsorption, color change, and non-linear optical properties of MOMs. These properties can be predicted using theoretical methods, and the results may provide experimentalists with guidance for rational design and engineering of novel MOMs. The theory levels used include semi-empirical quantum mechanical calculations with the PM7 Hamiltonian and, Density Functional Theory (DFT) to predict the geometry and electronic structure of the ground state, and Time Dependent DFT (TD-DFT) to predict the excited states and the optical properties. The molecular absorption capacity of aldoxime coordinated Zn(II) based MOMs (previously measured experimentally) is predicted by using PM7 Theory level. The 3D structures were optimized with and without host molecules inside the pores. The absorption capacity of these crystals was predicted to be 8H2 or 3N2 per unit cell. When going beyond this limit, the structural integrity of the bulk material becomes fractured and microcrystals are observed both experimentally and theoretically. The linear absorption properties of Co(II) based complexes are known to change color when the coordination number is altered. In order to understand the mechanism of this color change TD-DFT methods are employed. The chromic behavior of the Co(II) based complexes studied was confirmed to be due to a chain in coordination number that resulted in lower metal to ligand distances. These distances destabilize the occupied metal d orbitals, and as a consequence of this, the metal to ligand transition energy is lowered enough to allow the crystals to absorb light at longer wavelengths. Covalent organic frameworks (COFs) present an extension of MOM principles to the main group elements. The synthesis of ordered COFs is possible by using predesigned structures andcarefully selecting the building blocks and their conditions for assembly. The crystals formed by these systems often possess non-linear optical (NLO) properties. Second Harmonic Generation (SHG) is one of the most used optical processes. Currently, there is a great demand for materials with NLO optical properties to be used for optoelectronic, imaging, sensing, among other applications. DFT calculations can predict the second order hyperpolarizability ?2 and tensor components necessary to estimate NLO. These calculations for the ?2 were done with the use of the Berry's finite field approach. An efficient material with high ?2 was designed and the resulting material was predicted to be nearly fivefold higher than the urea standard. Two-photon absorption (2PA) is another NLO effect. Unlike SHG, it is not limited to acentric material and can be used development of in vivo bio-imaging agents for the brain. Pt(II) complexes with porphyrin derivatives are theoretically studied for that purpose. The mechanism of 2PA enhancement was identified. For the most efficient porphyrin, the large 2PA cross-section was found to be caused by a HOMO-LUMO+2 transition. This transition is strongly coupled to 1PA allowed Q-band HOMO-LUMO states by large transition dipoles. Alkyl carboxyl substituents delocalize the LUMO+2 orbital due to their strong ?-acceptor effect, enhancing transition dipoles and lowering the 2PA transition to the desirable wavelengths range. The mechanism 2PA cross-section enhancement of aminoxime and aldoxime ligands upon metal addition of is studied with TD-DFT methods. This mechanism of enhancement is found to be caused by the polarization of the ligand orbitals by the metal cation. After polarization an increase in ligand to ligand transition dipole moment. This enhancement of dipole moment is related to the increase in 2PA cross-sections.

<p>Bridging the accuracy of ab initio (AI) QM/MM with the efficiency of semi-empirical<br> (SE) QM/MM methods has long been a goal in computational chemistry. This dissertation<br> presents four ∆-Machine learning schemes aimed at achieving this objective. Firstly, the in-<br> corporation of negative force observations into the Gaussian process regression (GPR) model,<br> resulting in GPR with derivative observations, demonstrates the remarkable capability to<br> attain high-quality potential energy surfaces, accurate Cartesian force descriptions, and reli-<br> able free energy profiles using a training set of just 80 points. Secondly, the adaptation of the<br> sparse streaming GPR algorithm showcases the potential of memory retention from previous<br> phasespace, enabling energy-only models to converge using simple descriptors while faith-<br> fully reproducing high-quality potential energy surfaces and accurate free energy profiles.<br> Thirdly, the utilization of GPR with atomic environmental vectors as input features proves<br> effective in enhancing both potential energy surface and free energy description. Further-<br> more, incorporating derivative information on solute atoms further improves the accuracy<br> of force predictions on molecular mechanical (MM) atoms, addressing discrepancies arising<br> from QM/MM interaction energies between the target and base levels of theory. Finally, a<br> comprehensive comparison of three distinct GPR schemes, namely GAP, GPR with an aver-<br> age kernel, and GPR with a system-specific sum kernel, is conducted to evaluate the impact<br> of permutational invariance and atomistic learning on the model’s quality. Additionally, this<br> dissertation introduces the adaptation of the GAP method to be compatible with the sparse<br> variational Gaussian processes scheme and the streaming sparse GPR scheme, enhancing<br> their efficiency and applicability. Through these four ∆-Machine learning schemes, this dis-<br> sertation makes significant contributions to the field of computational chemistry, advancing<br> the quest for accurate potential energy surfaces, reliable force descriptions, and informative<br> free energy profiles in QM/MM simulations.<br> </p>

A molecule can crystallise in more than one crystal structure, a common phenomenon in organic compounds known as polymorphism. Different polymorphic forms may have significantly different physical properties, and a reliable prediction would be beneficial to the pharmaceutical industry. However, crystal structure prediction (CSP) based on the knowledge of the chemical structure had long been considered impossible. Previous failures of some CSP attempts led to speculation that the thermodynamic calculations in CSP methodologies failed to predict the kinetically favoured structures. Similarly, regarding the stabilities of co-crystals relative to their pure components, the results from lattice energy calculations and full CSP studies were inconclusive. In this thesis, these problems are addressed using the state-of-the-art CSP methodology implemented in the GRACE software. Firstly, it is shown that the low-energy predicted structures of four organic molecules, which have previously been considered difficult for CSP, correspond to their experimental structures. The possible outcomes of crystallisation can be reliably predicted by sufficiently accurate thermodynamic calculations. Then, the polymorphism of 5- chloroaspirin is investigated theoretically. The order of polymorph stability is predicted correctly and the isostructural relationships between a number of predicted structures and the experimental structures of other aspirin derivatives are established. Regarding the stabilities of co-crystals, 99 out of 102 co-crystals and salts of nicotinamide, isonicotinamide and picolinamide reported in the Cambridge Structural Database (CSD) are found to be more stable than their corresponding co-formers. Finally, full CSP studies of two co-crystal systems are conducted to explain why the co-crystals are not easily obtained experimentally. / University of Bradford

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Understanding the “incomprehensible” world of materials is the biggest challenge to the materials science community. To access the properties of the materials and to utilize them for positive changes in the world are of great interest. Often scientists use approximate theories to get legitimate answers to the problems. Density functional theory (DFT) has emerged as one of the successful and powerful predictive methods in this regard. The accuracy of DFT relies on the approximate form of the exchange-correlation (EXC) functional. The most complicated form of this functional can be as accurate as more complicated and computationally robust method like Quantum Monte Carlo (QMC), Random Phase Approximation (RPA). Two newest meta-GGAs, SCAN and SCAN+rVV10 are among those functionals. Instantaneous charge fluctuation between any two objects gives rise to the van der Waals (vdW) interactions (often termed as dispersion interactions). It is a purely correlation effect of the interacting electrons and thus non-local in nature. Despite its small magnitude it plays a very important role in many systems such as weakly bound rare-gas dimers, molecular crystals, and molecule-surface interaction. The traditional semi-local functionals can not describe the non-local of vdW interactions; only short- and intermediate-range of the vdW are accounted for in these functionals. In this thesis we investigate the effect of the weak vdW interactions in surface properties, rare-gas dimers and how it can be captured seamlessly within the semi-local density functional approximation. We have used summed-up vdW series within the spherical-shell approximation to develop a new vdW correction to the meta-GGA-MS2 functional. This method has been utilized to calculate binding energy and equilibrium binding distance of different homo- and hetero- dimers and we found that this method systematically improves the MGGA-MS2 results with a very good agreement with the experimental data. The binding energy curves are plotted using this MGGA-MS2, MGGA-MS2-vdW and two other popular vdW-corrected functionals PBE-D2, vdW-DF2. From these plots it is clear that our summed-up vdW series captures the long-range part of the binding energy curve via C6, C8, and, C10 coefficients. The clean metallic surface properties such as surface energy, work functions are important and often play a crucial role in many catalytic reactions. The weak dispersion interactions present between the surfaces has significant effect on these properties. We used LDA, PBE, PBSEsol, SCAN and SCAN+rVV10 to compute the clean metallic surface properties. The SCAN+rVV10 seamlessly captures different ranges of the vdW interactions at the surface and predicts very accurate values of surface energy (σ), and work function (Φ) and interlayer relaxations (δ%). Our conclusion is adding non-local vdW correction to a good semilocal density functional such as SCAN is necessary in order to predict the weak attractive vdW forces at the metallic surface. The SCAN+rVV10 has also been employed to study the hydrogen evolution reaction (HER) on 1T-MoS2. We have chosen as a descriptor differential Gibbs free energy (ΔGH to understand the underlying mechanism of this catalytic reaction. Density functional theory calculations agree with the experimental findings. In the case of layered materials like 1TMoS2, vdW interactions play an important role in hydrogen binding, that SCAN+rVV10 calculation was able to describe precisely. We have also used SCAN and SCAN+rVV10 functionals to understand bonding of CO on (111) metal surfaces, where many approximations to DFT fail to predict correct adsorption site and adsorption energy. In this case SCAN and SCAN+rVV10 do not show systematic improvements compared to LDA or PBE, rather, both SCAN and SCAN+rVV10 overbind CO more compared to PBE but less compared to the LDA. This overbinding of CO is associated with the incorrect charge transfer from metal to molecule and presumably comes from the density-driven self-interaction error of the functionals. In this thesis we assessed different semi-local functionals to inivestigate molecule surface systems of π-conjugated molecules (thiophene, pyridine) adsorbed on Cu(111), Cu(110), Cu(100) surfaces. We find the binding mechanism of these molecules on the metallic surface is mediated by short and intermediate range vdW interactions. Calculated values of binding energies and adsorbed geometries imply that this kind of adsorption falls in the weak chemisorption regime. Structural phase transitions due to applied pressure are very important in materials science. However, pressure induced structural phase transition in early lanthanide elements such as Ce are considered as abnormal first order phase transition. The Ce α-to-γ isostructural phase transition is one of them. The volume collapse and change of magnetic properties associated with this transition are mediated by the localized f -electron. Semi-local density functionals like LDA, GGA delocalize this f -electron due to the inherent self-interaction error (SIE) of these functionals. We have tested the SCAN functional for this particular problem, and, it was found that the spin-orbit coupling calculations with SCAN not only predicts the correct magnetic ordering of the two phases, but also gives a correct minima for the high-pressure α-Ce phase and a shoulder for the low-pressure γ-Ce phase. / Physics

Water is of essential importance for life on earth, yet the physics concerning its various anomalous properties has not been fully illuminated. This thesis is dedicated to the understanding of liquid water from aspects of microscopic structures, dynamics, electronic structures, X-ray absorption spectra, and proton transfer mechanism. This thesis use the computational simulation techniques including density functional theory (DFT), ab initio molecular dynamics (AIMD), and theoretical models for X-ray absorption spectra (XAS) to investigate the dynamics and electronic structures of liquid water system. The topics investigated in this thesis include a comprehensive evaluation on the simulation of liquid water using the newly developed SCAN meta-GGA functional, a systematic modeling of the liquid-water XAS using advanced ab initio approaches, and an explanation for a long-puzzling question that why hydronium diffuses faster than hydroxide in liquid water. Overall, significant contributions have been made to the understanding of liquid water and ionic solutions in the microscopic level through the aid of ab initio computational modeling. / Physics

It remains a major challenge in biophysics to understand the conformational dynamics of biomolecules. As powerful tools, molecular dynamics (MD) simulations have become increasingly important in studying the full atomic details of conformational dynamics of biomolecules. In addition, many statistical models have been developed to give insight into the big datasets from MD simulations. In this work, I first describe three statistical models used to analyze MD simulation data: Lifson-Roig Helix-Coil theory, Bayesian inference models, and Markov state models. Then I present the applications of each model in analyzing MD simulations and revealing insight into the conformational dynamics of biomolecules. These statistical models allow us to bridge microscopic and macroscopic mechanisms of biological processes and connect simulations with experiments. / Chemistry

In this thesis, we have employed two computational methods, molecular dynamics (MD) and hybrid quantum mechanics/molecular mechanics (QM/MM) MD simulations with umbrella sampling (US), to gain insights into the molecular mechanism governing the molecular recognition and reactivity in several protein-ligand complexes. Three systems involving protein-ligand interactions are examined in this dissertation utilizing well-established computational methodologies and mathematical modeling. The three proteins studied here are acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (PIN1). These enzymes are known to interact with a variety of ligands. AChE dysfunction caused by organophosphorus (OP) chemicals is a severe hazard since AChE is a critical enzyme in neurotransmission. Oximes are chemical compounds that can reactivate inhibited AChE; hence in the development of better oximes, it is critical to understand the mechanism through which OPs block AChE. We have described the covalent inhibition mechanism between AChE and the OP insecticide phorate oxon and its more potent metabolites and established their free energy profiles using QM/MM MD-US for the first time. Our results suggest a concerted mechanism and provide insights into the challenges in reactivating phorate oxon inhibited AChE. Reactivating BChE is another therapeutic approach to detoxifying circulating OP molecules before reaching the target AChE. We explored the covalent modification of BChE with phorate oxon and its metabolites using hybrid quantum mechanics/molecular mechanics (QM/MM) umbrella sampling simulations (PM6/ff14SB) for the inhibition process. Our results reveal that the mechanism is distinct between the inhibitors. The PM6 methodology is a good predictor of these compounds' potency, which may efficiently help study OPs like phorate oxon with larger leaving groups. Finally, we investigated the interactions between Peptidyl-prolyl isomerase (PPIase), which consists of a peptidyl isomerase (PPIase) domain flexibly tethered to a smaller Trp-Trp (WW) protein-binding domain, and chimeric peptides based on the human histone H1.4 sequence (KATGAApTPKKSAKW), as well as the effects on inter-domain dynamics. Using explicit solvent MD simulations, simulated annealing, and native contact analysis, our modeling sugget that the residues in the N-terminal immediate to the pSer/Thr Pro site connect the PPIase and WW domains via a series of hydrogen bonds and native contacts.

<p dir="ltr">Hypergolic propellants contain a fuel and an oxidizer that ignite on contact without the need for an external ignition source. Hydrazines are often used as the fuel, despite health and environmental safely concerns. Monomethylhydrazine (MMH) is a commonly used fuel in conjunction with dinitrogen tetroxide as the oxidizer for in-space maneuvering, although the mechanisms for the reactions of these two compounds are not fully understood. Based on the spontaneous generation of product ions in liquid phase experiments, quantum chemical calculations using the SMD model of implicit solvation were used to probe proposed reaction mechanisms. The reactions of hydrazine and MMH with the nitrosonium cation and the nitronium cation, which included the formation of the corresponding fuel radical cation, were explored. The reactions of hydrazines with the nitronium cation in model solvents were found to be highly exergonic, by as much as 70 kcal mol^-1. Further reactions of the MMH radical cation were also explored, including the formation of tetrazanes. Developing a complete mechanism to explain the formation of the most abundant product ions can further the understanding of hypergolicity and aid in the development of safer fuels.</p><p dir="ltr">The ASTM D2425 method was originally developed in 1965 and updated in 2019 for analyzing aviation fuels. However, a method using two dimensional gas chromatography coupled to a flame ionization detector (GCxGC/FID) was previously developed at Purdue University for the analysis of aviation fuels, including those derived from traditional sources and those derived from sustainable feedstocks. The established ASTM D2425 method was compared to the GCxGC/FID method for the analysis of Jet A-1, a sustainable aviation fuel, and a model compound mixture. The peak areas of eleven compound classes were compared across the three different samples by using a Pearson coefficient to determine skewness, an Anderson-Darling test for normality, Levene’s test and F-test for equal variances (depending on the normality of the data), and a 2-sample t-test. The results of these statistical analyses were somewhat vague and further studies should be done to fully compare the ASTM D2425 method with the GCxGC/FID method.</p>

The research conducted focused on the oxidative intermediates of antioxidants known as Myricetin, Quercetin, and 4-Methylesutin by calculating the reaction mechanism. During this research, computational quantum chemistry on selected parts for the 3 antioxidants previously mentioned were performed to find the most stable intermediate to act as a spin trap. The hypothesis is that the intermediates found can act as spin traps which will allow longer preservation of a free radical to be identified using Electron Paramagnetic Resonance (EPR) spectroscopy. This may be because the buildup of excess free radicals in a system leads them to cause damage down to the DNA and other deleterious processes to cellular levels in those areas which leads to disease. However, current artificial spin traps in use are somewhat ineffective due to being toxic at higher levels of concentration under solubility. The goal of this research is to use the naturally occurring antioxidants Myricetin, Quercetin, and 4-Methylesutin as the trap, which will provide a more efficient detection method. This research has generated greater insight into the oxidative reaction mechanism of antioxidants.