Topology and Dynamics in Complex Networks: The Role of Edge Reciprocity

A key issue in complex systems regards the relationship between topology and dynamics. In this work, we use a recently introduced network property known as steering coefficient as a means to approach this issue with respect to different directed complex network systems under varying dynamics. Theoretical and real-world networks are considered, and the influences of reciprocity and average degree on the steering coefficient are quantified. A number of interesting results are reported that can assist the design of complex systems exhibiting larger or smaller relationships between topology and dynamics

Irreversible time-dependent rheological behavior of cement slurries : constitutive model and experiments

Over the last few decades, much focus has been given to investigating the reversible rheological behavior of thixotropic materials, but the description of the rheology of materials undergoing an irreversible process is still challenging. In this work, the time-dependent rheological behavior of a cement slurry is investigated. Different rheometric experiments are performed to evaluate the structure breakdown under shear, cement gelation, and curing process. A recently proposed thixotropic elasto-viscoplastic model [de Souza Mendes, Soft Matter 7, 2471-2483 (2011)] is modified to account for irreversible effects, which can be either of a chemical or physical nature, making the current model capable of describing reversible and irreversible processes with a single structure parameter. The parameters of the model are estimated from constant shear rate tests and from the flow curve of the fresh cement slurry. The model predictions are compared to step-down and step-up in stress experiments, and the results show that the model successfully describes experimental data obtained. Interesting phenomena are observed and discussed, including (i) thixotropic behavior during the dormant period, (ii) shear banding, (iii) irreversible changes in cement slurry rheology after the hydration reactions accelerate, and (iv) the existence of a characteristic time for the transition from a thixotropic-yield-stress material to a solid during curing. The predictive capability of the new model includes bifurcation, shear banding, stress overshoots, effects of chemical reactions, and irreversible shear degradation. It is argued that the ideas employed in the present work can be used to incorporate irreversible effects into other thixotropic models, giving rise to the possibility of describing the transient rheological behavior of complex materials in an unprecedented fashion. (c) 2019 The Society of Rheology

Pitfalls of the Martini Model

R.A. thanks The Netherlands Organisation for Scientific Research NWO (Graduate Programme Advanced Materials, No. 022.005.006) for financial support. S.T. thanks the European Commission for financial support via a Marie Skłodowska-Curie Actions Individual Fellowship (MicroMod-PSII, grant agreement 748895).The computational and conceptual simplifications realized by coarse-grain (CG) models make them a ubiquitous tool in the current computational modeling landscape. Building block based CG models, such as the Martini model, possess the key advantage of allowing for a broad range of applications without the need to reparametrize the force field each time. However, there are certain inherent limitations to this approach, which we investigate in detail in this work. We first study the consequences of the absence of specific cross Lennard-Jones parameters between different particle sizes. We show that this lack may lead to artificially high free energy barriers in dimerization profiles. We then look at the effect of deviating too far from the standard bonded parameters, both in terms of solute partitioning behavior and solvent properties. Moreover, we show that too weak bonded force constants entail the risk of artificially inducing clustering, which has to be taken into account when designing elastic network models for proteins. These results have implications for the current use of the Martini CG model and provide clear directions for the reparametrization of the Martini model. Moreover, our findings are generally relevant for the parametrization of any other building block based force field.publishersversionpublishe

Martini coarse-grained models of imidazolium-based ionic liquids:from nanostructural organization to liquid-liquid extraction

Ionic liquids (ILs) are remarkable green solvents, which find applications in many areas of nano- and biotechnology including extraction and purification of value-added compounds or fine chemicals. These liquid salts possess versatile solvation properties that can be tuned by modifications in the cation or anion structure. So far, in contrast to the great success of theoretical and computational methodologies applied to other fields, only a few IL models have been able to bring insights towards the rational design of such solvents. In this work, we develop coarse-grained (CG) models for imidazolium-based ILs using a new version of the Martini force field. The model is able to reproduce the main structural properties of pure ILs, including spatial heterogeneity and global densities over a wide range of temperatures. More importantly, given the high intermolecular compatibility of the Martini force field, this new IL CG model opens the possibility of large-scale simulations of liquid-liquid extraction experiments. As examples, we show two applications, namely the extraction of aromatic molecules from a petroleum oil model and the extraction of omega-3 polyunsaturated fatty acids from a fish oil model. In semi-quantitative agreement with the experiments, we show how the extraction capacity and selectivity of the IL could be affected by the cation chain length or addition of co-solvents

Modelling structural properties of cyanine dye nanotubes at coarse-grained level

Self-assembly is a ubiquitous process spanning from biomolecular aggregates to nanomaterials. Even though the resulting aggregates can be studied through experimental techniques, the dynamic pathways of the process and the molecular details of the final structures are not necessarily easy to resolve. Consequently, rational design of self-assembling aggregates and their properties remains extremely challenging. At the same time, modelling the self-assembly with computational methods is not trivial, because its spatio-temporal scales are usually beyond the limits of all-atom based simulations. The use of coarse-grained (CG) models can alleviate this limitation, but usually suffers from the lack of optimised parameters for the molecular constituents. In this work, we describe the procedure of parametrizing a CG Martini model for a cyanine dye (C8S3) that self-assembles into hollow double-walled nanotubes. First, we optimised the model based on quantum mechanics calculations and all-atom reference simulations, in combination with available experimental data. Then, we conducted random self-assembly simulations, and the performance of our model was tested on preformed assemblies. Our simulations provide information on the time-dependent local arrangement of this cyanine dye, when aggregates are being formed. Furthermore, we provide guidelines for designing and optimising parameters for similar self-assembling nanomaterials

Capturing Choline–Aromatics Cation−π Interactions in the MARTINI Force Field

Cation-πinteractions play an important role in biomolecular recognition, including interactions between membrane phosphatidylcholine lipids and aromatic amino acids of peripheral proteins. While molecular mechanics coarse grain (CG) force fields are particularly well suited to simulate membrane proteins in general, they are not parameterized to explicitly reproduce cation-πinteractions. We here propose a modification of the polarizable MARTINI coarse grain (CG) model enabling it to model membrane binding events of peripheral proteins whose aromatic amino acid interactions with choline headgroups are crucial for their membrane binding. For this purpose, we first collected and curated a dataset of eight peripheral proteins from different families. We find that the MARTINI CG model expectedly underestimates aromatics-choline interactions and is unable to reproduce membrane binding of the peripheral proteins in our dataset. Adjustments of the relevant interactions in the polarizable MARTINI force field yield significant improvements in the observed binding events. The orientation of each membrane-bound protein is comparable to reference data from all-atom simulations and experimental binding data. We also use negative controls to ensure that choline-aromatics interactions are not overestimated. We finally check that membrane properties, transmembrane proteins, and membrane translocation potential of mean force (PMF) of aromatic amino acid side-chain analogues are not affected by the new parameter set. This new version "MARTINI 2.3P" is a significant improvement over its predecessors and is suitable for modeling membrane proteins including peripheral membrane binding of peptides and proteins

Martini 3 Coarse-Grained Force Field:Small Molecules

The recent re-parametrization of the Martini coarse-grained force field, Martini 3, improved the accuracy of the model in predicting molecular packing and interactions in molecular dynamics simulations. Here, we describe how small molecules can be accurately parametrized within the Martini 3 framework and present a database of validated small molecule models. We pay particular attention to the description of aliphatic and aromatic ring-like structures, which are ubiquitous in small molecules such as solvents and drugs or in building blocks constituting macromolecules such as proteins and synthetic polymers. In Martini 3, ring-like structures are described by models that use higher resolution coarse-grained particles (small and tiny particles). As such, the present database constitutes one of the cornerstones of the calibration of the new Martini 3 small and tiny particle sizes. The models show excellent partitioning behavior and solvent properties. Miscibility trends between different bulk phases are also captured, completing the set of thermodynamic properties considered during the parametrization. We also show how the new bead sizes allow for a good representation of molecular volume, which translates into better structural properties such as stacking distances. We further present design strategies to build Martini 3 models for small molecules of increased complexity

Structural, morphological, and magnetic characterizations of (FexMn1-x)2O3 nanocrystals: A comprehensive stoichiometric determination

Iron manganese trioxide (FexMn1-x)2O3 nanocrystals were synthesized by the sol-gel method. The 80 K Mossbauer spectrum was well-fitted using two doublets representing the 8b and 24d crystallographic sites of the (FexMn1-x)2O3 phase and two weak extra sextets which were attributed to crystalline and amorphous hematite. Our findings showed formation of a bixbyite primary phase. The Raman spectrum exhibits six Raman active modes, typical of (Fe,Mn)2O3, and two extra Raman modes associated with the secondary hematite phase. X-ray photoelectron spectroscopy analysis confirmed the presence of oxygen vacancy onto the (FexMn1-x)2O3 particle surface, with varying oxidation states. X-band magnetic resonance data revealed a single broad resonance line in the whole temperature range (3.8 K - 300 K). The temperature dependence of both resonance field and resonance linewidth shows a remarkable change in the range of 40 - 50 K, herein credited to surface spin glass behavior. The model picture used assumes (FexMn1-x)2O3 nanoparticles with a core-shell structure. Results indicate that below about 50 K the spin system of shell reveals a paramagnetic to spin glass-like transition upon cooling, with a critical temperature estimated at 43 K. In the higher temperature range, the superparamagnetic hematite (secondary) phase contributes remarkably to the temperature dependence of the resonance linewidth. Zero-field-cooled (ZFC) and fieldcooled (FC) data show strong irreversibility and a peak in the ZFC curve at 33 K, attributed to a paramagnetic-ferrimagnetic transition of the main phase. Hysteresis curve at 5 K shows a low coercive field of 4 kOe, with the magnetization not reaching saturation at 70 kOe, suggesting the occurrence of a ferrimagnetic core with a magnetic disorder at surface, characteristic of core-shell spin-glass-like behavior

Multiscale modeling of molecular structure and optical properties of complex supramolecular aggregates

Supramolecular aggregates of synthetic dye molecules offer great perspectives to prepare biomimetic functional materials for light-harvesting and energy transport. The design is complicated by the fact that structure-property relationships are hard to establish, because the molecular packing results from a delicate balance of interactions and the excitonic properties that dictate the optics and excited state dynamics, in turn sensitively depend on this packing. Here we show how an iterative multiscale approach combining molecular dynamics and quantum mechanical exciton modeling can be used to obtain accurate insight into the packing of thousands of cyanine dye molecules in a complex double-walled tubular aggregate in close interaction with its solvent environment. Our approach allows us to answer open questions not only on the structure of these prototypical aggregates, but also about their molecular-scale structural and energetic heterogeneity, as well as on the microscopic origin of their photophysical properties. This opens the route to accurate predictions of energy transport and other functional properties

Composição química e atividade inibidora de acetilcolinesterase de óleos voláteis de Myrceugenia myrcioides(Cambess.) O. Berg and Eugenia riedeliana O. Berg, Myrtaceae

The chemical composition of volatile oils from two Myrtaceae species, Myrceugenia myrcioidesand Eugenia riedeliana, both native from the Brazilian Atlantic Rain Forest, was analyzed by GC-MS. Acetylcholinesterase inhibitory activity was colorimetrically evaluated for these oils. For M. myrcioides, monoterpene hydrocarbons represented the major class in the volatile oil, with α-pinene as the most abundant component and a weak inhibitory activity was observed, whilst for E. riedeliana sesquiterpenes were found in higher amounts, being valerianol the major compound, and this oil presented a strong acetylcholinesterase inhibition.A composição química dos óleos voláteis de duas espécies de Myrtaceae, Myrceugenia myrcioidese Eugenia riedeliana, ambas nativas da Mata Atlântica, foi analisada por CG-EM. A atividade inibidora de acetilcolinesterase foi determinada colorimetricamente para estes óleos. Em M. myrcioides, hidrocarbonetos monoterpênicos representaram a classe majoritária de compostos presentes no óleo volátil, sendo α-pineno o componente mais abundante e a atividade inibidora de acetilcolinesterase foi baixa, enquanto para E. riedelianaos sesquiterpenos foram observados em maiores concentrações, sendo o valerianol o componente majoritário, e este óleo apresentou uma forte atividade inibidora da enzima.BIOTA/FAPESPCNPqCoordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES