Benzo[c]thiophene chromophores linked to cationic Fe and Ru derivatives for NLO materials: synthesis characterization and quadratic hyperpolarizabilities

5-Monocyclopentadienyliron(II)/ruthenium(II) complexes of the general formula [M(5-C5H5)(PP)(L1)][PF6] {M = Fe, PP = dppe; M = Ru, PP = dppe or 2PPh3; L1 = 5-[3-(thiophen-2-yl)benzo[c]thiophenyl]thiophene-2-carbonitrile} have been synthesized and studied to evaluate their molecular quadratic hyperpolarizabilities. The compounds were fully characterized by NMR, FTIR and UV/Vis spectroscopy and their electrochemical behaviour studied by cyclic voltammetry. Quadratic hyperpolarizabilities () were determined by hyper-Rayleigh scattering measurements at a fundamental wavelength of 1500 nm. Density functional theory calculations were employed to rationalize the second-order non-linear optical properties of these complexes.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

A fluorescente bicyclic Calix[4] Arene-Oxacyclophane with planar chirality: Resolution, chiroptical, properties, and absolute configuration.

A new inherently chiral calix[4]arene ICC 1 has been disclosed. The dissymmetry of 1 is generated from a chirality plane in the quinol moiety of a 1,3-bridged bicyclic calix[4]arene. ICC 1 has been resolved by enantioselective HPLC, and the chiroptical properties of both isolated antipodes (pS)-1 and (pR)-1 confirm their enantiomeric nature. The absolute configuration of the (pS)-1/(pR)-1 enantiomeric pair was established through time-dependent density functional theory (TDDFT) calculations of electronic circular dichroism (CD) spectra. (C) 2014 Elsevier Ltd. All rights reserved.

Mono(Eta(5)-cyclopentadienyl)metal(II) complexes with thienyl acetylide chromophores: synthesis, electrochemical studies, and first hyperpolarizabilities

A series of mono(eta(5)-cyclopentadienyl)metal-(II) complexes with nitro-substituted thienyl acetylide ligands of general formula [M(eta(5)-C5H5)(L)(C C{C4H2S}(n)NO2)] (M = Fe, L = kappa(2)-DPPE, n = 1,2; M = Ru, L = kappa(2)-DPPE, 2 PPh3, n = 1, 2; M = Ni, L = PPh3, n = 1, 2) has been synthesized and fully characterized by NMR, FT-IR, and UV-Vis spectroscopy. The electrochemical behavior of the complexes was explored by cyclic voltammetry. Quadratic hyperpolarizabilities (beta) of the complexes have been determined by hyper-Rayleigh scattering (HRS) measurements at 1500 nm. The effect of donor abilities of different organometallic fragments on the quadratic hyperpolarizabilities was studied and correlated with spectroscopic and electrochemical data. Density functional theory (DFT) and time-dependent DFT (TDDFT) calculations were employed to get a better understanding of the second-order nonlinear optical properties in these complexes. In this series, the complexity of the push pull systems is revealed; even so, several trends in the second-order hyperpolarizability can still be recognized. In particular, the overall data seem to indicate that the existence of other electronic transitions in addition to the main MLCT clearly controls the effectiveness of the organometallic donor ability on the second-order NLO properties of these push pull systems.

Synthesis of organometallic Ruthenium(II) complexes with strong activity against several human canceer cell lines

A new family of "RuCp" (Cp=eta(5)-C5H5) derivatives with bidentate N,O and N,N'-heteroaromatic ligands revealed outstanding cytotoxic properties against several human cell lines namely, A2780, A2780CisR, HT29, MCF7, MDAMB231, and PD. IC50 values were much lower than those found for cisplatin. Crystal structure of compound 4 was determined by X-ray diffraction studies. Density functional theory (DFT) calculations performed for compound 1 showed electronic flow from the ruthenium center to the coordinated bidentate ligand, in agreement with the electrochemical studies and the existence of a metal-to-ligand charge-transfer (MLCT) band evidenced by spectroscopic data.

The key role of coligands in novel ruthenium(II)-cyclopentadienyl bipyridine derivatives: Ranging from non-cytotoxic to highly cytotoxic compounds

A new family of eight ruthenium(II)-cyclopentadienyl bipyridine derivatives, bearing nitrogen, sulfur, phosphorous and carbonyl sigma bonded coligands, has been synthesized. Compounds bearing nitrogen bonded coligands were found to be unstable in aqueous solution, while the others presented appropriate stabilities for the biologic assays and pursued for determination of IC50 values in ovarian (A2780) and breast (MCF7 and MDAMB231) human cancer cell lines. These studies were also carried out for the [5: HSA] and [6: HSA] adducts (HSA = human serum albumin) and a better performance was found for the first case. Spectroscopic, electrochemical studies by cyclic voltammetry and density functional theory calculations allowed us to get some understanding on the electronic flow directions within the molecules and to find a possible clue concerning the structural features of coligands that can activate bipyridyl ligands toward an increased cytotoxic effect. X-ray structure analysis of compound [Ru(eta(5)-C5H5)(bipy)(PPh3)][PF6] (7; bipy = bipyridine) showed crystallization on C2/c space group with two enantiomers of the [Ru(eta(5)-C5H5)(bipy)(PPh3)](+) cation complex in the racemic crystal packing. (C) 2015 Elsevier Inc All rights reserved.

Temperature-induced structural transitions in self-assembling magnetic nanocolloids

With the help of a unique combination of density functional theory and computer simulations, we discover two possible scenarios, depending on concentration, for the hierarchical self-assembly of magnetic nanoparticles on cooling. We show that typically considered low temperature clusters, i.e. defect-free chains and rings, merge into more complex branched structures through only three types of defects: four-way X junctions, three-way Y junctions and two-way Z junctions. Our accurate calculations reveal the predominance of weakly magnetically responsive rings cross-linked by X defects at the lowest temperatures. We thus provide a strategy to fine-tune magnetic and thermodynamic responses of magnetic nanocolloids to be used in medical and microfluidics applications.

The key role of coligands in novel ruthenium(II)-cyclopentadienyl bipyridine derivatives: ranging from non-cytotoxic to highly cytotoxic compounds

A new family of eight ruthenium(II)-cyclopentadienyl bipyridine derivatives, bearing nitrogen, sulfur, phosphorous and carbonyl sigma bonded coligands, has been synthesized. Compounds bearing nitrogen bonded coligands were found to be unstable in aqueous solution, while the others presented appropriate stabilities for the biologic assays and pursued for determination of IC50 values in ovarian (A2780) and breast (MCF7 and MDAMB231) human cancer cell lines. These studies were also carried out for the [5: HSA] and [6: HSA] adducts (HSA=human serum albumin) and a better performance was found for the first case. Spectroscopic, electrochemical studies by cyclic voltammetry and density functional theory calculations allowed us to get some understanding on the electronic flow directions within the molecules and to find a possible clue concerning the structural features of coligands that can activate bipyridyl ligands toward an increased cytotoxic effect. X-ray structure analysis of compound [Ru(η(5)-C5H5)(bipy)(PPh3)][PF6] (7; bipy=bipyridine) showed crystallization on C2/c space group with two enantiomers of the [Ru(η(5)-C5H5)(bipy)(PPh3)](+) cation complex in the racemic crystal packing.

A chemical Hamiltonian approach study of the basis set superposition error changes on electron densities and one- and two-center energy components

A comparision of the local effects of the basis set superposition error (BSSE) on the electron densities and energy components of three representative H-bonded complexes was carried out. The electron densities were obtained with Hartee-Fock and density functional theory versions of the chemical Hamiltonian approach (CHA) methodology. It was shown that the effects of the BSSE were common for all complexes studied. The electron density difference maps and the chemical energy component analysis (CECA) analysis confirmed that the local effects of the BSSE were different when diffuse functions were present in the calculations

Docking to heme proteins.

In silico screening has become a valuable tool in drug design, but some drug targets represent real challenges for docking algorithms. This is especially true for metalloproteins, whose interactions with ligands are difficult to parametrize. Our docking algorithm, EADock, is based on the CHARMM force field, which assures a physically sound scoring function and a good transferability to a wide range of systems, but also exhibits difficulties in case of some metalloproteins. Here, we consider the therapeutically important case of heme proteins featuring an iron core at the active site. Using a standard docking protocol, where the iron-ligand interaction is underestimated, we obtained a success rate of 28% for a test set of 50 heme-containing complexes with iron-ligand contact. By introducing Morse-like metal binding potentials (MMBP), which are fitted to reproduce density functional theory calculations, we are able to increase the success rate to 62%. The remaining failures are mainly due to specific ligand-water interactions in the X-ray structures. Testing of the MMBP on a second data set of non iron binders (14 cases) demonstrates that they do not introduce a spurious bias towards metal binding, which suggests that they may reliably be used also for cross-docking studies.

Structure and energetics of mixed 4He-3He drops

Using a finite-range density functional, we have investigated the energetics and structural features of mixed helium clusters. The possibility of doping the cluster with a molecule of sulfur hexafluoride is also considered. It is seen that the repulsion introduced by the impurity strongly modifies the properties of the smallest drops. Although only a qualitative comparison is possible, the gross features displayed by our calculations are in agreement with recent experimental findings.

Spin and density longitudinal response of quantum dots in the time-dependent local-spin-density approximation

The longitudinal dipole response of a quantum dot has been calculated in the far-infrared regime using local-spin-density-functional theory. We have studied the coupling between the collective spin and density modes as a function of the magnetic field. We have found that the spin dipole mode and single-particle excitations have a sizable overlap, and that the magnetoplasmon modes can be excited by the dipole spin operator if the dot is spin polarized. The frequency of the dipole spin edge mode presents an oscillation which is clearly filling factor (v) related. We have found that the spin dipole mode is especially soft for even-n values. Results for selected numbers of electrons and confining potentials are discussed.

Wave-vector dependence of spin and density multipole excitations in quantum dots

We have employed time-dependent local-spin density-functional theory to analyze the multipole spin and charge density excitations in GaAs-AlxGa1-xAs quantum dots. The on-plane transferred momentum degree of freedom has been taken into account, and the wave-vector dependence of the excitations is discussed. In agreement with previous experiments, we have found that the energies of these modes do not depend on the transferred wave vector, although their intensities do. Comparison with a recent resonant Raman scattering experiment [C. Schüller et al., Phys. Rev. Lett. 80, 2673 (1998)] is made. This allows us to identify the angular momentum of several of the observed modes as well as to reproduce their energies

Density modes in spherical 4He shells

We compute the density-fluctuation spectrum of spherical 4HeN shells adsorbed on the outer surface of Cn fullerenes. The excitation spectrum is obtained within the random-phase approximation, with particle-hole elementary excitations and effective interaction extracted from a density-functional description of the shell structure. The presence of one or two solid helium layers adjacent to the adsorbing fullerene is phenomenologically accounted for. We illustrate our results for a selection of numbers of adsorbed atoms on C20, C60, and C120. The hydrodynamical model that has proven successful to describe helium excitations in the bulk and in restricted geometries permits to perform a rather exhaustive analysis of various fluid spherical systems, namely, spheres, cavities, free bubbles, and bound shells of variable size.