155 research outputs found

    Adsorption of Alkanes on the Platinum Surface: Density Functional Theory compared to the Random Phase Approximation

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    Die Dichtefunktionaltheorie (DFT) einschließlich Dispersionkorrekturen (+D) wird mit der Random-Phase-Approximation (RPA) für die Adsorption von Alkanen auf der Pt(111)-Oberfläche verglichen. RPA wird zuerst im Hinblick auf relevante technische Parameter evaluiert und für die Methanadsorption an der Pt(111)-Oberfläche getestet. Im Vergleich zum Perdew-Burke-Ernzerhof-Funktional (PBE) mit Tkatchenkos Many-Body-Dispersionskorrektur (PBE+MBD) liefert RPA gute Ergebnisse. Auch reproduziert RPA experimentelle Adsorptionsenergien bei verschiedenen, physikalisch sinnvollen Beladungsstufen der Pt(111) Oberfläche mit Alkanmolekülen. Für Platin in der hexagonal dichtesten Kugelpackung sagt RPA richtigerweise die Methanadsorption an der hollow-tripod-Stelle voraus, während mit PBE+MBD die Adsorption an einer anderen Stelle bevorzugt wäre. Dies geht aus Schwingungsspektren hervor. Da periodisches RPA sehr rechenaufwändig ist, wird ein QM:QM Hybridansatz (QM=Quantenmechanik) angewendet, wobei periodisches PBE(+D) mithilfe von RPA Rechnungen an Clustern korrigiert wird (RPA:PBE(+D)). In einem Test verschiedener Dispersionskorrekturen schneiden RPA:PBE und RPA:PBE+MBD am besten ab. Diese Arbeit ist wegbereitend für die Anwendung des QM:QM Hybridansatzes zur Beschreibung der Adsorptionsprozesse an Metalloberflächen ‒ bei hoher Genauigkeit und deutlich verringertem Rechenaufwand. Auch Kresses low-scaling RPA Algorithmus wird getestet. Dieser Algorithmus ermöglicht, große Systeme, wie z.B. die Methan-, Ethan-, Propan- und n-Butanadsorption an Pt(111), zu untersuchen. Der Vergleich mit experimentellen Daten zeigt, dass mit RPA stets die beste Übereinstimmung erreicht wird. Dabei wird eine deutliche Verbesserung gegenüber allen untersuchten Dichte-Funktionalen erzielt. Obwohl Bindungen mit RPA etwas zu schwach vorhergesagt werden, ist es die derzeit beste Methode zur Untersuchung der Adsorption an Metalloberflächen und damit der Benchmark für diese Systeme.Density Functional Theory (DFT) including dispersion (+D) is compared against the Random Phase Approximation (RPA) for the adsorption of alkanes on the Pt(111) surface. RPA is first benchmarked with respect to technical parameters and tested for methane adsorption on Pt(111). It is found to perform well relative to the Perdew–Burke–Ernzerhof (PBE) functional augmented with the many-body dispersion scheme of Tkatchenko (PBE+MBD). It also compares well relative to experimentally derived adsorption energies at physically relevant coverages. RPA correctly assigns the adsorption of methane to the hcp (hexagonal close packed) hollow tripod site, matching vibrational spectra, whereas PBE+MBD found another site. Given the high cost of periodic RPA, a high-level: low-level QM:QM (QM = quantum mechanics) hybrid approach is applied using RPA (RPA:PBE(+D)), which has also been tested with several dispersion corrections, with RPA:PBE and RPA:PBE+MBD performing best. This extends the QM:QM hybrid approach to the study of adsorption on metal surfaces, resulting in high accuracy at significantly reduced cost. Finally we test the performance of the low-scaling RPA algorithm of Kresse and co-workers. This algorithm enables the study of larger systems and is applied to the first four n-alkanes (C1-C4) on the Pt(111) surface. Comparison against experiment indicates that RPA offers the best agreement, consistently better than any studied density functional. RPA underbinds slightly but is still found to be the best method for studying adsorption on metal surfaces and is the current benchmark for such systems

    GAMMA: Eine Software für den automatischen Aufbau von Makromolekülen

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    Die Vielfalt möglicher makromolekularer Strukturen gepaart mit den explorativen Fähigkeiten computergestützter Generierung chemischer (Makro-)Molekülstrukturen bietet großes Forschungspotential. Die Eigenschaften solcher Strukturen, darunter häufig Hohlräume, in die kleine Moleküle passen, führen z. B. zu Anwendungen in Wirt-Gast-Strukturen. Das Hauptthema der vorliegenden Arbeit war die Entwicklung eines neuen Computerprogrammes, das, ausgehend von (kleinen) molekularen Bausteinen, makromolekulare Strukturen erstellt. Nach Vorgabe eines Templatgraphen werden molekulare Bausteine so miteinander verknüpft, dass ein Makromolekül entsteht. Dieses kann anschließend um polare funktionelle Gruppen erweitert werden, die das elektrische Feld des Makromoleküls gezielt verändern, um beispielsweise eine katalytische Wirkung zu entfalten

    Prediction of partition coefficients for systems of micelles using DFT

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    [eng] A compound’s solvent−water partition coefficient (log P) measures the equilibrium ratio of the compound’s concentrations in a two-phase system: as two solvents in contact or a system of micelles in an aqueous solution. In this thesis, the partition coefficient of three groups of small compounds (alcohol, ether, and hydrocarbons) in 10 different solvents (benzene, cyclohexane, hexane, n-Octane, toluene, carbon tetrachloride, heptane, trichloroethane, and octanol) was computed used DFT and B3LYP method with 6.31G(d), 6.311+G** and 6.311++G** basis sets. It is obtained that the partition coefficient of alcohol solutes in various solvents using the 6.31G(d) basis set indicates a satisfactory correlation with experimental values. The correlation between the experimental value and the partition coefficient of ether solutes in different solvents using the 6.311++G** basis set shows high agreement. The experimental data displayed a high correlation with the partition coefficient computed for hydrocarbon compounds in various solvents using all three basis sets: 6.31G(d), 6.311+G**, and 6.311++G**. In addition, we have studied the correlation of the experimental partition coefficients in Sodium Dodecyl Sulfate (SDS), Hexadecyltrimethylammonium bromide (HTAB), Sodium cholate (SC), and Lithium perfluoro octane sulfonate (LPFOS) micelles with ab initio calculated partition coefficients in 15 different organic solvents. Specifically, the partition coefficients of a series of 63 molecules in an aqueous system of SDS, SC, HTAB, and LPFOS micelles are correlated with the partition coefficient in heptane/water, cyclohexane/water, n-dodecane/water, pyridine/water, acetic acid/water, octanol/water, acetone/water, 1-propanol/water, 2-propanol/water, methanol/water, formic acid/water, diethyl sulfide/water, decan-1-ol/water, 1-2 ethane diol/water and dimethyl sulfoxide/water systems. All calculations were performed using the Gaussian 16 Quantum Chemistry package. Molecular structures were generated in the more extended conformation using Avogadro, and geometries of all molecules were optimized using Density Functional Theory (DFT) B3LYP and MO6-2X with 6-31++G** basis set by the continuum solvation model based on density (SMD). The obtained results show that calculated partition coefficients in the alcohol/water mixture give the best correlation to predict the experimental partition coefficients in SDS, SC, and LPFOS micelles. With respect to HTAB micelle systems, a new selection of molecules is created, excluding those containing N atoms and Urea atom groups. Interestingly, the partition coefficient of these chosen molecules exhibits a strong correlation with the experimental partition coefficient. Finally, the partition coefficient of flexible molecules was studied by the same protocol for two solvent combinations, octanol/water and cyclohexane/water. The calculated values were compared with the experimental partition coefficients. The average partition coefficient in octanol solvent exhibited a high correlation with the experimental data. However, for the 16 compounds in the cyclohexane solvent, their partition coefficients do not exhibit significant agreement with the experimental partition coefficients.[cat] S'ha desenvolupat una metodologia computacional per calcular el coeficient de partició de diferents tipus de molècules en sistemes micel·lars. En primer lloc, s'ha calculat el coeficient de partició de tres grups de compostos (alcohol, èter i hidrocarburs) utilitzant el mètode DFT amb el funcional B3LYP. S'han obtingut correlacions satisfactòries amb els valors experimentals. En aquesta tesi s'ha desenvolupat un procediment per calcular els coeficients de partició experimentals en micel·les de dodecilsulfat de sodi (SDS), bromur d'hexadeciltrimetilamoni (HTAB), colat de sodi (SC) i perfluorooctanosulfonat de liti (LPFOS). Específicament, els coeficients de partició d'una sèrie de 63 molècules en un sistema aquós de micel·les de SDS, SC, HTAB i LPFOS es correlacionen amb el coeficient de partició en deu barreges aquoses. Els resultats obtinguts mostren que els coeficients de partició calculats a la barreja alcohol/aigua donen la millor correlació per predir els coeficients de partició experimentals en micel·les SDS, SC i LPFOS. Pel que fa als sistemes micelars HTAB, es crea una nova selecció de molècules, excloent-ne aquelles que contenen àtoms de N aromàtics i grups d'urea. És interessant notar que el coeficient de partició d'aquestes molècules triades mostra una forta correlació amb el coeficient de partició experimental. Finalment, es va estudiar el coeficient de partició de molècules flexibles mitjançant el mateix protocol per a dues combinacions de dissolvents, octanol/aigua i ciclohexà/aigua. Els valors calculats es van comparar amb els coeficients de partició experimentals. El coeficient de partició mitjana en dissolvent octanol va mostrar una alta correlació amb les dades experimentals. Tot i això, per als 16 compostos en el dissolvent ciclohexà, els seus coeficients de partició no mostren una concordança significativa amb els coeficients de partició experimental

    Models, Simulations, and the Reduction of Complexity

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    Modern science is a model-building activity. But how are models contructed? How are they related to theories and data? How do they explain complex scientific phenomena, and which role do computer simulations play? To address these questions which are highly relevant to scientists as well as to philosophers of science, 8 leading natural, engineering and social scientists reflect upon their modeling work, and 8 philosophers provide a commentary

    Using iron to catch a ride - synthetic siderophores as molecular 'Trojan Horses' to visualize and treat MDR bacterial pathogens

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    The rise in multidrug-resistant, bacterial infections, together with a shallow industrial discovery pipeline, urgently calls for novel diagnostic and therapeutic strategies. Bacterial cells, particularly Gram-negative pathogens with their double-layered cell wall, closely resemble a fortress that restricts the accumulation of small molecules. However, microbial transporters ensure a sufficient nutrient supply during infection of a host organism and act as gateways into the pathogen, e.g. for ferric iron, which plays a crucial role in microbial metabolism and growth. Siderophores, small bacterial molecule chelators, sequester Fe3+ from host proteins and are transported by bacterial, TonB-dependent transporters (TBDTs). Like a molecular “Trojan Horse”, synthetic siderophore mimics can hijack the siderophore transport system and actively translocate diagnostic or therapeutic payloads over the impervious bacterial membrane and accumulate at their site of action. This thesis expanded and evaluated the potential of synthetic and natural siderophores for the visualization and antibiotic therapy of MDR bacteria in cellular and in vivo. The structure of the DOTAM triscatecholate siderophore was adapted for an application as a bacteria-specific, gallium-68 labeled PET tracer for the detection of bacterial infections in vivo. Two tracers showed good in vitro, radiochemical and pharmacokinetic properties in vivo and selectively accumulated at the site of infection vs. a site of sterile inflammation. Similarly, chemiluminescent dioxetanes were attached to siderophores to yield a panel of siderophore dioxetane probes that detected Gram-positive and Gram-negative bacterial pathogens. The best compound exhibited superior stability in bacterial supernatant, detected low bacterial counts and even intracellular bacteria in infected lung epithelial cells. In an attempt to enhance the accumulation in Gram-negative bacteria and thus restore the activity of antibiotics used only against Gram-positive bacteria (e.g. lipopeptides, ansamycins, macrolides), chelators were conjugated via covalent and cleavable linker systems, to yield potent drug conjugates. Studies on siderophore receptor mutants of E. coli and P. aeruginosa, including transcriptomic and proteomic investigations, contributed information on the involved siderophore transporters as well as on the mechanistic response upon siderophore and conjugate addition. Peptide siderophore conjugates that target the TonB-dependent transport of ferric chelates in Pseudomonas successfully inhibited bacterial growth. This proof-of-concept established TonB as a novel target in antimicrobial therapy. The design, synthesis and biological evaluation of novel diagnostic and therapeutic siderophore conjugates represents an important milestone towards a clinical usage of this approach against MDR ESKAPE bacteria

    The development of electron deficient materials for organic electronics applications

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    This thesis reports on the development of electron deficient (n-type) small molecule and polymer semiconductors. Firstly, the synthesis of a new electron deficient 4,5,6-trifluoro-2,1,3-benzothiadiazole (TFBT) end group is presented. Coupling of TFBT to an electron rich indacenodithiophene (IDT) core, through direct arylation conditions, affords a TFBT IDT material which performs as a poorly ambipolar semiconductor in organic field effect transistor (OFET) devices. A range of related TFBT-based materials with expanded IDT or cyclopentadithiophene (CDT) cores were prepared and characterised. A six-fold nucleophilic aromatic substitution reaction with cyanide was developed and applied to all fluorinated materials. This one step modification resulted in the formation of 2,1,3-benzothiadiazole-4,5,6-tricarbonitrile (TCNBT) end group. This modification dramatically changed structural, optoelectronic and semiconducting properties compared to their fluorinated counterparts. This highlights the importance of strong π-acceptors, like cyano groups, in influencing electron accepting properties, compared to inductively withdrawing fluorine atoms. TCNBT-based semiconductors were utilised in a range of applications such as organic field effect transistors (OFETs) and organic photodetectors (OPDs), demonstrating good stability and high electron mobility. The strong electron accepting properties of the TCNBT end group resulted in low band gap materials that strongly absorb in the NIR range and were utilised to afford semi transparent electronic devices. A range of electron deficient donor-acceptor (D-A) type polymers were also synthesised, based on benzothiadiazole, functionalised with a mixture of cyano, nitro and fluoro groups. This study highlights the importance of molecular engineering and how small structural modifications have a great impact on the nature of the resulting semiconductor. More specifically, the effect of fluorine atoms and their influence on backbone planarity is shown to affect charge transport properties. On the other hand, cyano groups cause backbone twisting that is not easily overcome in the solid state and in turn disrupts charge transport in the polymer backbone. When applied to OFET and organic photovoltaic (OPV) devices, these polymers performed differently to the small molecules presented in this thesis, with fully cyanated polymers showing lower electron mobilities compared to the ones containing fluorine atoms. This demonstrates that the impact of cyano groups have a different effect in polymeric compared to small molecule systems.Open Acces

    Exploration of Chemical Space: Formal, chemical and historical aspects

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    Starting from the observation that substances and reactions are the central entities of chemistry, I have structured chemical knowledge into a formal space called a directed hypergraph, which arises when substances are connected by their reactions. I call this hypernet chemical space. In this thesis, I explore different levels of description of this space: its evolution over time, its curvature, and categorical models of its compositionality. The vast majority of the chemical literature focuses on investigations of particular aspects of some substances or reactions, which have been systematically recorded in comprehensive databases such as Reaxys for the last 200 years. While complexity science has made important advances in physics, biology, economics, and many other fields, it has somewhat neglected chemistry. In this work, I propose to take a global view of chemistry and to combine complexity science tools, modern data analysis techniques, and geometric and compositional theories to explore chemical space. This provides a novel view of chemistry, its history, and its current status. We argue that a large directed hypergraph, that is, a model of directed relations between sets, underlies chemical space and that a systematic study of this structure is a major challenge for chemistry. Using the Reaxys database as a proxy for chemical space, we search for large-scale changes in a directed hypergraph model of chemical knowledge and present a data-driven approach to navigate through its history and evolution. These investigations focus on the mechanistic features by which this space has been expanding: the role of synthesis and extraction in the production of new substances, patterns in the selection of starting materials, and the frequency with which reactions reach new regions of chemical space. Large-scale patterns that emerged in the last two centuries of chemical history are detected, in particular, in the growth of chemical knowledge, the use of reagents, and the synthesis of products, which reveal both conservatism and sharp transitions in the exploration of the space. Furthermore, since chemical similarity of substances arises from affinity patterns in chemical reactions, we quantify the impact of changes in the diversity of the space on the formulation of the system of chemical elements. In addition, we develop formal tools to probe the local geometry of the resulting directed hypergraph and introduce the Forman-Ricci curvature for directed and undirected hypergraphs. This notion of curvature is characterized by applying it to social and chemical networks with higher order interactions, and then used for the investigation of the structure and dynamics of chemical space. The network model of chemistry is strongly motivated by the observation that the compositional nature of chemical reactions must be captured in order to build a model of chemical reasoning. A step forward towards categorical chemistry, that is, a formalization of all the flavors of compositionality in chemistry, is taken by the construction of a categorical model of directed hypergraphs. We lifted the structure from a lineale (a poset version of a symmetric monoidal closed category) to a category of Petri nets, whose wiring is a bipartite directed graph equivalent to a directed hypergraph. The resulting construction, based on the Dialectica categories introduced by Valeria De Paiva, is a symmetric monoidal closed category with finite products and coproducts, which provides a formal way of composing smaller networks into larger in such a way that the algebraic properties of the components are preserved in the resulting network. Several sets of labels, often used in empirical data modeling, can be given the structure of a lineale, including: stoichiometric coefficients in chemical reaction networks, reaction rates, inhibitor arcs, Boolean interactions, unknown or incomplete data, and probabilities. Therefore, a wide range of empirical data types for chemical substances and reactions can be included in our model
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