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Formation of Hybrid Electronic States in FePc Chains Mediated by the Au(110) Surface
Maria Grazia Betti, Pierluigi Gargiani, Carlo Mariani, Stefano Turchini, Nicola Zema, Sara Fortuna, Arrigo Calzolari, Stefano Fabris, 2012, original scientific article

Abstract: Iron–phthalocyanine (FePc) molecules deposited on the Au(110) surface self-organize in ordered chains driven by the reconstructed Au channels. The interaction process induces a rehybridization of the electronic states localized on the central metal atom, breaking the 4-fold symmetry of the molecular orbitals of the FePc molecules. The molecular adsorption is controlled by a symmetry-determined mixing between the electronic states of the Fe metal center and of the Au substrate, as deduced by photoemission and absorption spectroscopy exploiting light polarization. DFT calculations rationalize this mixing of the Fe and Au states on the basis of symmetry arguments. The calculated electronic structure reproduces the main experimental spectral features, which are associated to a distorted molecular structure displaying a trigonal bipyramidal geometry of the ligands around the metal center.
Keywords: phthalocyanine, Au(110), gold, surface, DFT, density functional theory, calculation, simulation
Published in RUNG: 13.10.2016; Views: 4793; Downloads: 0
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16.
Molecule-Driven Substrate Reconstruction in the Two-Dimensional Self-Organization of Fe-Phthalocyanines on Au(110)
Sara Fortuna, Pierluigi Gargiani, Maria Grazia Betti, Carlo Mariani, Arrigo Calzolari, Silvio Modesti, Stefano Fabris, 2012, original scientific article

Abstract: The structural patterns formed by molecular self-assembly at surfaces are usually controlled by the relative strengths of the intermolecular and molecule–substrate interactions. An additional steering effect is present when the substrate can easily reconstruct upon molecular adsorption, which therefore drives a self-templating effect on the metal support. This is here demonstrated for the model case of Fe-phthalocyanine molecules adsorbed on the Au(110) surface. Scanning tunneling microscopy shows that molecular adsorption promotes a local (1 × 5) surface reconstruction, which drives the assembly of molecular chains along the [11̅0] direction. The order and periodicity of the molecular assemblies are determined with low energy electron diffraction patterns. Density functional theory calculations reveal the energetic origins of the molecule-driven substrate reconstruction. Since the function of molecular overlayers at surfaces is strongly correlated to their structure, these results have implications in the design of new metal/molecular interfaces.
Keywords: self-assembly, phthalocyanine, Au(110), DFT, density functional theory, simulation, surface, recontruction
Published in RUNG: 11.10.2016; Views: 4581; Downloads: 0
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17.
Polymer Vesicles with a Colloidal Armor of Nanoparticles
Rong Chen, Daniel J. G. Pearce, Sara Fortuna, David L. Cheung, Stefan A. F. Bon, 2011, original scientific article

Abstract: The fabrication of polymer vesicles with a colloidal armor made from a variety of nanoparticles is demonstrated. In addition, it is shown that the armored supracolloidal structure can be postmodified through film-formation of soft polymer latex particles on the surface of the polymersome, hereby effectively wrapping the polymersome in a plastic bag, as well as through formation of a hydrogel by disintegrating an assembled polymer latex made from poly(ethyl acrylate-co-methacrylic acid) upon increasing the pH. Furthermore, ordering and packing patterns are briefly addressed with the aid of Monte Carlo simulations, including patterns observed when polymersomes are exposed to a binary mixture of colloids of different size.
Keywords: Pickering emultion, self-assemblt, Monte Carlo, simulation, nanoparticle, packing, pattern garnd canonical, colloids
Published in RUNG: 11.10.2016; Views: 4698; Downloads: 0
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18.
Agent based modelling for the 2D molecular self-organization of realistic molecules
Sara Fortuna, Alessandro Troisi, 2010, original scientific article

Abstract: We extend our previously developed agent-based (AB) algorithm to the study of the self-assembly of a fully atomistic model of experimental interest. We study the 2D self-assembly of a rigid organic molecule (1,4-benzene-dicarboxylic acid or TPA), comparing the AB results with Monte Carlo (MC) and MC simulated annealing, a technique traditionally used to solve the global minimization problem. The AB algorithm gives a lower energy configuration in the same simulation time than both of the MC simulation techniques. We also show how the AB algorithm can be used as a part of the protocol to calculate the phase diagram with less computational effort than standard techniques.
Keywords: self-assembly, self-organisation, 1, 4-benzene-dicarboxylic acid, TPA, agent based, Monte Carlo, simulation, phase diagram
Published in RUNG: 11.10.2016; Views: 4760; Downloads: 0
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19.
Hexagonal lattice model of the patterns formed by hydrogen-bonded molecules on the surface
Sara Fortuna, David L. Cheung, Alessandro Troisi, 2010, original scientific article

Abstract: We model the two-dimensional self-assembly of planar molecules capable of complementary interactions (like hydrogen bonding) as a set of hexagonal tiles on a hexagonal lattice. We use Monte Carlo simulations to study the phase diagrams of three model systems. The phases are characterized using a variety of order parameters, and they are studied as a function of the strength of the complementary interaction energy. This simplified model is proven to be capable of reproducing the phases encountered in real systems, unifying within the same framework most of the structures encountered experimentally.
Keywords: self-assembly, self-organisation, Monte Carlo, simulation, lattice model, dicarboxilic acid, hexagonal lattice
Published in RUNG: 10.10.2016; Views: 4756; Downloads: 0
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20.
An artificial intelligence approach for modeling molecular self-assembly: Agent Based simulations of rigid molecules
Sara Fortuna, Alessandro Troisi, 2009, original scientific article

Abstract: Agent-based simulations are rule-based models traditionally used for the simulations of complex systems. In this paper, an algorithm based on the concept of agent-based simulations is developed to predict the lowest energy packing of a set of identical rigid molecules. The agents are identified with rigid portions of the system under investigation, and they evolve following a set of rules designed to drive the system toward the lowest energy minimum. The algorithm is compared with a conventional Metropolis Monte Carlo algorithm, and it is applied on a large set of representative models of molecules. For all the systems studied, the agent-based method consistently finds a significantly lower energy minima than the Monte Carlo algorithm because the system evolution includes elements of adaptation (new configurations induce new types of moves) and learning (past successful choices are repeated).
Keywords: Self-assembly, self-organisation, agent based, Monte Carlo, rigid molecules, simulation
Published in RUNG: 10.10.2016; Views: 4741; Downloads: 0
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