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APPLICATION OF THE THEORY OF ATOMS IN MOLECULES TO THE BORANES AND CARBORANESLegare, Daniel A. 11 1900 (has links)
The theory of Atoms in Molecules is applied to a series of borane molecules. A study of the topological features of the charge density, p(r), yields a quantum mechanical definition of atoms, bonds, and the average properties of atoms within a molecule. Other topological features of the boranes studied include rings and cages, formed by bond paths in p which link the atoms. These bond paths which form rings are bent inward in order to maximize the binding in these electron-deficient molecules. An important result of this analysis is the unambiguous assignment of the connectivity of the boranes.
The theory of atoms and molecules allows one to quantum mechanically partition molecules into atomic basins, and calculations of average values for electron count and energies of individual atoms are performed by integration over these basins. Comparisons of atomic properties are performed to determine the transferability of atomic properties across the series.
The Laplacian of p, V2p, yields information about sites of electrophilic and nucleophilic attack in molecules. These sites are found to correspond to the positions of critical points in V2p, which are localized to specific atoms in the molecule. The boranes and carboranes are ranked according to their susceptibility to electrophilic and nucleophilic attack, and such reactions with boranes are predicted to be regiospecific. / Thesis / Master of Science (MSc)
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Ab initio studies of the static and dynamic properties of phases of Hâ‚‚O iceJenkins, Samantha January 1999 (has links)
No description available.
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Local Quantum ChemistryBohorquez, Hugo J. 18 February 2011 (has links)
The single-particle momentum is studied as a tool for the visualization of the electronic regions in atoms and molecules. The limiting values of this function correctly obey two fundamental theorems: Kato's cusp condition and the Hoffmann-Ostenhof and Hoffmann-Ostenhof exponential decay. The local momentum also depicts the electron shell structure in atoms as given by its local maxima and inflection points. The integration of the electron density in a shell gives electron populations that are in agreement with the ones expected from the periodic table of the elements. The shell structure obtained is in agreement with higher level of theory computations. The average of the local kinetic energy associated with the local momentum is the Weizsäcker kinetic energy. It is shown that this quantity provides an estimate of steric interactions in molecules.
The single-particle momentum is a practical tool for the exploration of new stabilizing interactions for all kinds of molecular systems. It provides a three-dimensional representation of the molecular structure and depicts the polarizability regions, a feature not available with other continuous analyses.
A general definition of the radius of an atom in terms of its ionization energy is found. A relationship between these two fundamental properties is derived from the radial distribution function and the local momentum for the valence electrons. Strong correlations with well-known atomic radii suggest that this is a universally valid definition of the atomic radius.
The stability of peptides in the alpha-helix conformation upon replacement of the central amino acid is studied. These systems were optimized with a continuous solvent model and a recently developed DFT functional with empirical terms accounting for dispersion interactions. Both, the dispersion terms and the solvent model are directly related to the polarizability of the involved atoms. A new formula for an ab initio computation of the polarizability is introduced and tested for the amino acids.
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A multipolar polarisable force field method from quantum chemical topology and machine learningMills, Matthew January 2012 (has links)
Force field methods are used to investigate the properties of a wide variety of chemical systems on a routine basis. The expression for the electrostatic energy typically does not take into account the anisotropic nature of the atomic electron distribution or the dependence of that distribution on the system geometry. This has been suggested as a cause of the failure of force field methods to reliably predict the behaviour of chemical systems. A method for incorporation of anisotropy and polarisation is described in this work. Anisotropy is modelled by the inclusion of multipole moments centred at atoms whose values are determined by application of the methods of Quantum Chemical Topology. Polarisation, the dependence of the electron distribution on system geometry, is modelled by training machine learning models to predict atomic multipole moments from knowledge of the nuclear positions of a system. The resulting electrostatic method can be implemented for any chemical system. An application to progressively more complex systems is reported, including small organic molecules and larger molecules of biological importance. The accuracy of the method is rigorously assessed by comparison of its predictions to exact interaction energy values. A procedure for generating transferable atomic multipole moment models is defined and tested. The electrostatic method can be combined with the empirical expressions used in force field calculations to describe total system energies by fitting parameters against ab initio conformational energies. Derivatives of the energy are given and the resulting multipolar polarisable force field can be used to perform geometry optimisation calculations. Future applications to conformational searching and problems requiring dynamic descriptions of a system are feasible.
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Plasmonic atoms and molecules for imaging and sensingChen, Tianhong 13 February 2016 (has links)
Nanoscale structures play a fundamental role in diverse scientific areas, including biology and information technology. It is necessary to develop methods that can observe nanoscale structures and dynamic processes that involve them. Colloidal plasmonic nanoparticles (plasmonic “atoms”) and their clusters (plasmonic “molecules”) are nanoscale objects with remarkable optical properties that provide new opportunities for sensing and imaging on the relevant length and time scales.
Many biology questions require optically monitoring of the dynamic behavior of biological systems on single molecule level. In contrast to the commonly used fluorescent probes which have the problem of bleaching, blinking and relatively weak signals, plasmonic probes display superb brightness, persistency and photostability, thus enable long observation time and high temporal and spacial resolutions. When plasmonic atoms are clustered together, their resonances redshift while the intensities increase as a result of plasmon coupling. These optical responses are dependent on the interparticle gaps and the overall geometry, which makes plasmonic molecules capable of detecting biomolecule clustering and measuring nanometer scale distance fluctuations. In this dissertation, individual plasmonic atoms are firstly evaluated as imaging probe and their interactions with lipid membrane are tested on a newly developed on-chip black lipid membrane system. Subsequently, plasmonic dimers (plasmon rulers) prepared through DNA-programmed self-assembly are monitored to detect the mechanical properties of single biopolymers. Measurement of the spring constant of short (tens of nucleotides or base pairs) DNAs is demonstrated through plasmon coupling microscopy.
Colloidal plasmonic atoms of various materials, sizes and shapes scatter vivid colors in the full-visible range. Assembling them into plasmonic molecules provides additional degrees of freedom for color manipulation. More importantly, the electric field in the gaps of plasmonic molecules can be enhanced by several orders of magnitude, which is highly desirable in single molecule sensing applications. In this dissertation, the fundamentals of plasmonic coupling are investigated through one-dimensional gold nanosphere chains. Using the directed self-assembly approach, multichromatic color-switchable plasmonic nanopixels composed of plasmonic atoms and molecules of various materials, sizes, shapes and geometries are integrated in one image with nanometer precision, which facilitates the encoding of complex spectral features with high relevance in security tagging and high density optical data storage. / 2017-01-01T00:00:00Z
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Variational Information-Theoretic Atoms-in-MoleculesHeidar-Zadeh, Farnaz 11 1900 (has links)
It is common to use the electron density to partition a molecular system into atomic regions. The necessity for such a partitioning scheme is rooted in the unquestionable role of atoms in chemistry. Nevertheless, atomic properties are not well- defined concepts within the domain of quantum mechanics, as they are not observable. This has resulted in a proliferation of different approaches to retrieve the concept of atoms in molecules (AIM) within the domain of quantum mechanics and in silico experiments based on various flavors of model theories.
One of the most popular families of models is the Hirshfeld, or stockholder, partitioning methods. Hirshfeld methods do not produce sharp atomic boundaries, but instead distribute the molecular electron density at each point between all the nuclear centers constituting the molecule. The various flavors of the Hirshfeld scheme differ mainly in how the atomic shares are computed from a reference promolecular density and how the reference promolecular density is defined.
We first establish the pervasiveness of the Hirshfeld portioning by extending its information-theoretic framework. This characterizes the family of f-divergence measures as necessary and sufficient for deriving Hirshfeld scheme. Then, we developed a variational version of Hirshfeld partitioning method, called Additive Variational Hirshfeld (AVH). The key idea is finding the promolecular density, expanded as a linear combination of charged and neutral spherically-averaged isolated atomic densities in their ground and/or excited states, that resembles the molecular density as much as possible. Using Kullback-Liebler divergence measure, this automatically guarantees that each atom and proatom have the same number of electrons, and that the partitioning is size consistent. The robustness of this method is confirmed by testing it on various datasets. Considering the mathematical properties and our numerical results, we believe that AVH has the potential to supplant other Hirshfeld partitioning schemes in future. / Thesis / Doctor of Philosophy (PhD)
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Computational study of anion-anion intermolecular interactions between I3-ions in the gas phase, solution and solid stateGroenewald, Ferdinand George 12 1900 (has links)
Thesis (MSc)--Stellenbosch University, 2012. / Please refer to full text for abstract.
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High Resolution X-ray Diffraction Analysis of CB1 Receptor Antagonists as a Means to Explore Binding AffinityFournet, Steven P. 20 December 2013 (has links)
Abstract
Charge density studies have been conducted on ten CB1 cannabinoid receptor antagonists via high resolution x-ray crystallography. Bond critical point values and various other properties derived from these studies including the electrostatic potential were analyzed in correlation to the affinity of each compound with the CB1 receptor. Correlation/anti-correlation was found between several properties and Ki. The data was also interpreted by principal component analysis with three principal components accounting for 85% of the data variation. Data mining was limit due to the low sample count and the requirements set for the inclusion of correlated/anti-correlated variables left fewer variables to analyze. The model presented is left for future interpretation.
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From X-ray diffraction data annealing to comprehensive charge density analysisHey, Jakob 01 July 2013 (has links)
No description available.
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The prediction of mutagenicity and pKa for pharmaceutically relevant compounds using 'quantum chemical topology' descriptorsHarding, Alexander January 2011 (has links)
Quantum Chemical Topology (QCT) descriptors, calculated from ab initio wave functions, have been utilised to model pKa and mutagenicity for data sets of pharmaceutically relevant compounds. The pKa of a compound is a pivotal property in both life science and chemistry since the propensity of a compound to donate or accept a proton is fundamental to understanding chemical and biological processes. The prediction of mutagenicity, specifically as determined by the Ames test, is important to aid medicinal chemists select compounds avoiding this potential pitfall in drug design. Carbocyclic and heterocyclic aromatic amines were chosen because this compounds class is synthetically very useful but also prone to positive outcomes in the battery of genotoxicity assays.The importance of pKa and genotoxic characteristics cannot be overestimated in drug design, where the multivariate optimisations of properties that influence the Absorption-Distribution-Metabolism-Excretion-Toxicity (ADMET) profiles now features very early on in the drug discovery process.Models were constructed using carboxylic acids in conjunction with the Quantum Topological Molecular Similarity (QTMS) method. The models produced Root Mean Square Error of Prediction (RMSEP) values of less than 0.5 pKa units and compared favourably to other pKa prediction methods. The ortho-substituted benzoic acids had the largest RMSEP which was significantly improved by splitting the compounds into high-correlation subsets. For these subsets, single-term equations containing one ab initio bond length were able to accurately predict pKa. The pKa prediction equations were extended to phenols and anilines.Quantitative Structure Activity Relationship (QSAR) models of acceptable quality were built based on literature data to predict the mutagenic potency (LogMP) of carbo- and heterocyclic aromatic amines using QTMS. However, these models failed to predict Ames test values for compounds screened at GSK. Contradictory internal and external data for several compounds motivated us to determine the fidelity of the Ames test for this compound class. The systematic investigation involved recrystallisation to purify compounds, analytical methods to measure the purity and finally comparative Ames testing. Unexpectedly, the Ames test results were very reproducible when 14 representative repurified molecules were tested as the freebase and the hydrochloride salt in two different solvents (water and DMSO). This work formed the basis for the analysis of Ames data at GSK and a systematic Ames testing programme for aromatic amines. So far, an unprecedentedly large list of 400 compounds has been made available to guide medicinal chemists. We constructed a model for the subset of 100 meta-/para-substituted anilines that could predict 70% of the Ames classifications. The experimental values of several of the model outliers appeared questionable after closer inspection and three of these have been retested so far. The retests lead to the reclassification of two of them and thereby to improved model accuracy of 78%. This demonstrates the power of the iterative process of model building, critical analysis of experimental data, retesting outliers and rebuilding the model.
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