964 resultados para Coarse-grained potential


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In part 1 of this article, cleavage initiation in the intercritically reheated coarse-grained heat affected zone (IC CG HAZ) of high-strength low-alloy (HSLA) steels was determined to occur between two closely spaced blocky MA particles. Blunt notch, crack tip opening displacement (CTOD), and precracked Charpy testing were used in this investigation to determine the failure criteria required for cleavage initiation to occur by this mechanism in the IC CG HAZ. It was found that the attainment of a critical level of strain was required in addition to a critical level of stress. This does not occur in the case of high strain rate testing, for example, during precracked Charpy testing. A different cleavage initiation mechanism is then found to operate. The precise fracture criteria and microstructural requirements (described in part I of this article) result in competition between potential cleavage initiation mechanisms in the IC CG HAZ.

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Composition and orientation effects on the final recrystallization texture of three coarse-grained Nb-containing AISI 430 ferritic stainless steels (FSSs) were investigated. Hot-bands of steels containing distinct amounts of niobium, carbon and nitrogen were annealed at 1250 degrees C for 2h to promote grain growth. In particular, the amounts of Nb in solid solution vary from one grade to another. For purposes of comparison, the texture evolution of a hot-band sheet annealed at 1030 degrees C for 1 min (finer grain structure) was also investigated. Subsequently, the four sheets were cold rolled up to 80% reduction and then annealed at 800 degrees C for 15 min. Texture was determined using X-ray diffraction and electron backscatter diffraction (EBSD). Noticeable differences regarding the final recrystallization texture and microstructure were observed in the four investigated grades. Results suggest that distinct nucleation mechanisms take place within these large grains leading to the development of different final recrystallization textures. (c) 2011 Elsevier B.V. All rights reserved.

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Named entity recognizers are unable to distinguish if a term is a general concept as "scientist" or an individual as "Einstein". In this paper we explore the possibility to reach this goal combining two basic approaches: (i) Super Sense Tagging (SST) and (ii) YAGO. Thanks to these two powerful tools we could automatically create a corpus set in order to train the SuperSense Tagger. The general F1 is over 76% and the model is publicly available.

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It is now well accepted that cellular responses to materials in a biological medium reflect greatly the adsorbed biomolecular layer, rather than the material itself. Here, we study by molecular dynamics simulations the competitive protein adsorption on a surface (Vroman effect), i.e. the non-monotonic behavior of the amount of protein adsorbed on a surface in contact with plasma as functions of contact time and plasma concentration. We find a complex behavior, with regimes during which small and large proteins are not necessarily competing between them, but are both competing with others in solution ("cooperative" adsorption). We show how the Vroman effect can be understood, controlled and inverted.

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It is now well accepted that cellular responses to materials in a biological medium reflect greatly the adsorbed biomolecular layer, rather than the material itself. Here, we study by molecular dynamics simulations the competitive protein adsorption on a surface (Vroman effect), i.e. the non-monotonic behavior of the amount of protein adsorbed on a surface in contact with plasma as functions of contact time and plasma concentration. We find a complex behavior, with regimes during which small and large proteins are not necessarily competing between them, but are both competing with others in solution ("cooperative" adsorption). We show how the Vroman effect can be understood, controlled and inverted.

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A 1µs Molecular Dynamic simulation was performed with a realistic model system of Sodium Dodecyl Sulfate (SDS) micelles in aqueous solution, comprising of 360 DS-, 360 Na+ and 90000 water particles. After 300 ns three different micellar shapes and sizes 41, 68 and 95 monomers, were observed. The process led to stabilization in the total number of SDS clusters and an increase in the micellar radius to 2.23 nm, in agreement with experimental results. An important conclusion, is be aware that simulations employed in one aggregate, should be considered as a constraint. Size and shape distribution must be analyzed.

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Tempestitos grossos constituem camadas delgadas de conglomerado gradando a arenito, com estratificação cruzada seguida de laminação ondulada truncante a simétrica e de drape/flaser de siltito/folhelho. Cinco exemplos extraídos do Permiano da bacia do Paraná ilustram esse tipo de depósito: três deles são de rochas siliciclásticas, contendo bioclastos de bivalves e vertebrados (Formação Rio Bonito-Membro Triunfo e Formação Palermo), enquanto os outros dois são de rochas carbonática e fosfática (respectivamente, formações Teresina e Corumbataí do Grupo Passa Dois). O componente tracional da base do tempestito grosso apresenta-se como arenite quartzoso/lítico ou grainstone oolítico com cimento calcífero preenchendo poros (casos das formações Palermo e Teresina). em sua maioria, os tempestitos grossos constituem pavimentos transgressivos intercalados em folhelhos ou tempestitos finos (arenitos muito finos a folhelhos com estratificação ondulada truncante-hummocky). em outro caso, extraído de subsuperfície, o pavimento transgressivo ocorre na base de uma sucessão progradante de barra de plataforma. O tempestito grosso da Formação Teresina constitui um evento transgressivo sobreposto a depósitos de barra de plataforma.

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A number of studies have demonstrated that simple elastic network models can reproduce experimental B-factors, providing insights into the structure-function properties of proteins. Here, we report a study on how to improve an elastic network model and explore its performance by predicting the experimental B-factors. Elastic network models are built on the experimental C coordinates, and they only take the pairs of C atoms within a given cutoff distance r(c) into account. These models describe the interactions by elastic springs with the same force constant. We have developed a method based on numerical simulations with a simple coarse-grained force field, to attribute weights to these spring constants. This method considers the time that two C atoms remain connected in the network during partial unfolding, establishing a means of measuring the strength of each link. We examined two different coarse-grained force fields and explored the computation of these weights by unfolding the native structures. Proteins 2014; 82:119-129. (c) 2013 Wiley Periodicals, Inc.

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In dieser Arbeit wird ein vergröbertes (engl. coarse-grained, CG) Simulationsmodell für Peptide in wässriger Lösung entwickelt. In einem CG Verfahren reduziert man die Anzahl der Freiheitsgrade des Systems, so dass manrngrössere Systeme auf längeren Zeitskalen untersuchen kann. Die Wechselwirkungspotentiale des CG Modells sind so aufgebaut, dass die Peptid Konformationen eines höher aufgelösten (atomistischen) Modells reproduziert werden.rnIn dieser Arbeit wird der Einfluss unterschiedlicher bindender Wechsel-rnwirkungspotentiale in der CG Simulation untersucht, insbesondere daraufhin,rnin wie weit das Konformationsgleichgewicht der atomistischen Simulation reproduziert werden kann. Im CG Verfahren verliert man per Konstruktionrnmikroskopische strukturelle Details des Peptids, zum Beispiel, Korrelationen zwischen Freiheitsgraden entlang der Peptidkette. In der Dissertationrnwird gezeigt, dass diese “verlorenen” Eigenschaften in einem Rückabbildungsverfahren wiederhergestellt werden können, in dem die atomistischen Freiheitsgrade wieder in die CG-Strukturen eingefügt werden. Dies gelingt, solange die Konformationen des CG Modells grundsätzlich gut mit der atomistischen Ebene übereinstimmen. Die erwähnten Korrelationen spielen einerngrosse Rolle bei der Bildung von Sekundärstrukturen und sind somit vonrnentscheidender Bedeutung für ein realistisches Ensemble von Peptidkonformationen. Es wird gezeigt, dass für eine gute Übereinstimmung zwischen CG und atomistischen Kettenkonformationen spezielle bindende Wechselwirkungen wie zum Beispiel 1-5 Bindungs- und 1,3,5-Winkelpotentiale erforderlich sind. Die intramolekularen Parameter (d.h. Bindungen, Winkel, Torsionen), die für kurze Oligopeptide parametrisiert wurden, sind übertragbarrnauf längere Peptidsequenzen. Allerdings können diese gebundenen Wechselwirkungen nur in Kombination mit solchen nichtbindenden Wechselwirkungspotentialen kombiniert werden, die bei der Parametrisierung verwendet werden, sind also zum Beispiel nicht ohne weiteres mit einem andere Wasser-Modell kombinierbar. Da die Energielandschaft in CG-Simulationen glatter ist als im atomistischen Modell, gibt es eine Beschleunigung in der Dynamik. Diese Beschleunigung ist unterschiedlich für verschiedene dynamische Prozesse, zum Beispiel für verschiedene Arten von Bewegungen (Rotation und Translation). Dies ist ein wichtiger Aspekt bei der Untersuchung der Kinetik von Strukturbildungsprozessen, zum Beispiel Peptid Aggregation.rn