Rough Set Model based on Uncertain Measure

Abstract Probabilistic rough set model based on probability measure is a new rough set model to deal with uncertain information systems. Uncertain measure is a generalization of probability measure. Based on the fundamental knowledge of rough set model and uncertain measure, a rough set model based on uncertain measure is established. Furthermore, by comparative study of the lower approximation and upper approximation, it is true that the rough set model based on uncertain measure is an extension of the probabilistic rough set model

Mechanical and Electrical Ageing Effects on the Long-Term Stretching of Silicone Dielectric Elastomers with Soft Fillers:Long-Term Stretching of Silicone Dielectric Elastomers

Dielectric elastomer materials for actuators need to be soft and stretchable while possessing high dielectric permittivity. Soft silicone elastomers can be obtained through the use of silicone oils, while enhanced permittivity can be obtained through the use of dipolar groups on the polymer backbone. Such elastomers are prepared by adding soft fillers to a strong and relatively stiff elastomer, Elastosil LR3043/50. The long-term stability of the materials is tested by straining the elastomers 60% statically for up to 3 months. The results show that soft fillers significantly influence the long-term stability of silicone elastomers, with electrical breakdown strength being the most influenced. Especially high concentrations of silicone oils should be avoided for long-term mechanical stability

Octa-n-butyl-1κ2 C,2κ2 C,3κ2,4κ2 C-bis­(μ-2,3-dibromo­propionato)-1:2κ2 O:O′,3:4κ2 O:O′-bis­(2,3-dibromo­propionato)-1κO,3κO-di-μ3-oxido-1:2:4κ3 O:O:O,2:3:4κ3 O:O:O-tetra­tin(IV)

In the centrosymmetric tetra­nuclear title complex, [Sn4(C4H9)8(C3H3Br2O2)4O2], one of the two independent Sn atoms is five-coordinated by one O atom of the carboxyl­ate anion, two bridging O atoms and two n-butyl groups in a C2SnO3 distorted trigonal bipyramidal geometry. The other Sn atom also has a distorted trigonal bipyramidal geometry, being coordinated by two O atoms of two carboxyl­ate anions, one bridging O atom and two butyl groups. An inter­esting feature of the crystal structure is the short Sn⋯O [2.756 (4) Å] and O⋯O [2.608 (3) Å] inter­actions. The –BrCH2—CHBr– segments of the two carboxyl­ate anions are disordered over two positions [site occupancies of 0.60 (1)/0.40 (1) and 0.53 (2)/0.47 (2)]. Weak non-directional C—H⋯O inter­actions lead to the formation of infinte chains along the a axis; other weak inter­molecular C—H⋯π inter­actions are also present

[3-(Dimethyl­amino)benzoato]triphenyl­tin(IV)

In the title compound, [Sn(C6H5)3(C9H10NO2)], the Sn atom is coordinated by three phenyl groups and a carboxyl­ate anion in a distorted tetra­hedral geometry. An intra­molecular C—H⋯O inter­action forms an S(7) ring motif. The dihedral angles between the benzoate group and the other three phenyl rings are 76.94 (8), 66.82 (8) and 42.34 (9)°. The crystal structure is further stabilized by inter­molecular C—H⋯π inter­actions

A cloud platform for automating and sharing analysis of raw simulation data from high throughput polymer molecular dynamics simulations

Open material databases storing hundreds of thousands of material structures and their corresponding properties have become the cornerstone of modern computational materials science. Yet, the raw outputs of the simulations, such as the trajectories from molecular dynamics simulations and charge densities from density functional theory calculations, are generally not shared due to their huge size. In this work, we describe a cloud-based platform to facilitate the sharing of raw data and enable the fast post-processing in the cloud to extract new properties defined by the user. As an initial demonstration, our database currently includes 6286 molecular dynamics trajectories for amorphous polymer electrolytes and 5.7 terabytes of data. We create a public analysis library at https://github.com/TRI-AMDD/htp_md to extract multiple properties from the raw data, using both expert designed functions and machine learning models. The analysis is run automatically with computation in the cloud, and results then populate a database that can be accessed publicly. Our platform encourages users to contribute both new trajectory data and analysis functions via public interfaces. Newly analyzed properties will be incorporated into the database. Finally, we create a front-end user interface at https://www.htpmd.matr.io for browsing and visualization of our data. We envision the platform to be a new way of sharing raw data and new insights for the computational materials science community.Comment: 21 pages, 7 figure

Simple networks on complex cellular automata: From de Bruijn diagrams to jump-graphs

We overview networks which characterise dynamics in cellular automata. These networks are derived from one-dimensional cellular automaton rules and global states of the automaton evolution: de Bruijn diagrams, subsystem diagrams, basins of attraction, and jump-graphs. These networks are used to understand properties of spatially-extended dynamical systems: emergence of non-trivial patterns, self-organisation, reversibility and chaos. Particular attention is paid to networks determined by travelling self-localisations, or gliders.Comment: 25 pages, 14 figure

Synthesis of anthraquinone based electroactive polymers: A critical review

Conducting polymers or synthetic monomers have revolutionized the world and are at the heart of scientific research having a scope of vast diverse applications in many technological fields. The conducting and redox polymers have been investigated as energy storage systems because of their better sustainability, ease of synthesis, and environmental compatibility. Owing to the conducting properties of quinones, they gain too much importance among the researchers. Keeping in view the importance and sustainability of conducting polymers, for the first time, this study compiles a detailed overview of synthetic approaches followed by investigations on electrochemical properties and future directions. This study critically examines the synthetic process of simple monomers, substituted monomers, and polymers of anthraquinone (AQ) under the classification of low- and high-molecular-weight AQ–based derivatives, their working principles, and their electrochemical applications, which enable us to explore their novel possible application in automotive, solar cell devices, aircraft aileron, and biomedical equipment. Irrefutably, we confirm that high-molecular-weight polymeric AQ compounds are best in comparison with low-molecular-weight AQ monomers because they have pre-eminent properties over monomeric systems. Because of the significant properties of AQ, polymeric systems are high demanding and have emerged as a hot topic among the researchers these days. In the current scenario, this study is of immense importance because it identifies and discusses the right and sustainable combination and paves the way to utilize these novel materials in different technologies