81 resultados para Ferroelectric ordering


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Three long chain cationic surfactants were intercalated into Ca-montmorillonite through ion exchangeand the obtained organoclays were characterized by X-ray diffraction (XRD), high resolution thermo-gravimetric analysis (TG) and Raman spectroscopy. The intercalation of surfactants not only changes thesurface properties of clay from hydrophilic to hydrophobic but also greatly increases the basal spacing ofthe interlayers based on XRD analysis. The thermal stability of organoclays intercalated with three sur-factants (TTAB, DTAB and CTAB) and the different arrangements of the surfactant molecules intercalatedinto Ca-montmorillonite were determined by TG-DTG analysis. A Raman spectroscopic study on the Ca-montmorillonite modified by three surfactants prepared at different concentrations provided the detailedconformational ordering of different intercalated long-chain surfactants under different conditions. Thewavenumber of the antisymmetric stretching mode is more sensitive than that of the symmetric stretch-ing mode to the mobility of the tail of the amine chain. At room temperature, the conformational orderingis more easily affected by the packing density in the lateral model. With the increase of the temperature,the positions of both the antisymmetric and symmetric stretching bands shift to higher wavenumbers,which indicates a decrease of conformational ordering. This study offers new insights into the struc-ture and properties of Ca-montmorillonite modified with different long chain surfactants. Moreover, theexperimental results confirm the potential applications of organic Ca-montmorillonites for the removalof organic impurities from aqueous media.

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Piezoelectric composites comprising an active phase of ferroelectric ceramic and a polymer matrix have recently attracted numerous sensory applications. However, it remains a major challenge to further improve their electromechanical response for advanced applications such as precision control and monitoring systems. We hereby investigated the incorporation of graphene platelets (GnPs) and multi-walled carbon nanotubes (MWNTs), each with various weight fractions, into PZT (lead zirconate titanate)/epoxy composites to produce three-phase nanocomposites. The nanocomposite films show markedly improved piezoelectric coefficients and electromechanical responses (50%) besides an enhancement of ~200% in stiffness. Carbon nanomaterials strengthened the impact of electric field on the PZT particles by appropriately raising the electrical conductivity of epoxy. GnPs have been proved far more promising in improving the poling behavior and dynamic response than MWNTs. The superior dynamic sensitivity of GnP-reinforced composite may be caused by GnPs’ high load transfer efficiency arising from their two-dimensional geometry and good compatibility with the matrix. Reduced acoustic impedance mismatch resulted from the improved thermal conductance may also contribute to the higher sensitivity of GnP-reinforced composite. This research pointed out the potential of employing GnPs to develop highly sensitive piezoelectric composites for sensing applications.

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Chambersite is a manganese borate mineral with formula: MnB7O13Cl and occurs as colorless crystals in the monoclinic pyramidal crystal system. Raman bands at 902, 920, 942 and 963 cm-1 are assigned to the BO stretching vibration of the B7O13 units. Raman bands at 1027, 1045, 1056, 1075 and 1091 cm-1 are attributed to the BCl in-plane bending modes. The intense infrared band at 866 cm-1 is assigned to the trigonal borate stretching modes. The Raman band at 660 cm-1 together with bands at 597, 642 679, 705 and 721 cm-1 are assigned to the trigonal and tetrahedral borate bending modes. The molecular structure of a natural chambersite has been assessed using vibrational spectroscopy.

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By using information collected from numerous American Economic Review publications from the last 100 years, Torgler and Piatti examine the top publishing institutions to determine their most renowned AER papers based on citation success. Areas of interest include how often an individual can publish in the AER, how equally successful citations are distributed and who the top AER publishing authors are. The book explores what the level of cooperation is among authors and what drives systems such as the alphabetical name ordering. Torgler and Piatti critically examine the individual characteristics of AER authors, editors, editorial board members and referees and even tackle more intricate details such as the frequency of female publications in the AER. The authors observe and analyse the relationship between academic age and publication performance to see if there is any pattern on these factors and citation success. The book then goes on to analyse data concerning awards, and whether awards can increase the probability of publishing in the AER at a later stage

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The multianion mineral gartrellite PbCu(Fe3+,Cu)(AsO4)2(OH,H2O)2 has been studied by a combination of Raman and infrared spectroscopy. The molecular structure of gartrellite is assessed. Gartrellite is one of the tsumcorite mineral group based upon arsenate and/or sulphate anions. Crystal symmetry is either triclinic in the case of an ordered occupation of two cationic sites, triclinic due to ordering of the H bonds in the case of species with two water molecules per formula unit, or monoclinic in the other cases. Characteristic Raman spectra of the mineral gartrellite enable the assignment of the bands to specific vibrational modes. These spectra are related to the structure of gartrellite. The position of the hydroxyl and water stretching vibrations are related to the strength of the hydrogen bond formed between the OH unit and the AsO3/4 anion.

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Due to the demand for better and deeper analysis in sports, organizations (both professional teams and broadcasters) are looking to use spatiotemporal data in the form of player tracking information to obtain an advantage over their competitors. However, due to the large volume of data, its unstructured nature, and lack of associated team activity labels (e.g. strategic/tactical), effective and efficient strategies to deal with such data have yet to be deployed. A bottleneck restricting such solutions is the lack of a suitable representation (i.e. ordering of players) which is immune to the potentially infinite number of possible permutations of player orderings, in addition to the high dimensionality of temporal signal (e.g. a game of soccer last for 90 mins). Leveraging a recent method which utilizes a "role-representation", as well as a feature reduction strategy that uses a spatiotemporal bilinear basis model to form a compact spatiotemporal representation. Using this representation, we find the most likely formation patterns of a team associated with match events across nearly 14 hours of continuous player and ball tracking data in soccer. Additionally, we show that we can accurately segment a match into distinct game phases and detect highlights. (i.e. shots, corners, free-kicks, etc) completely automatically using a decision-tree formulation.

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Railway crew scheduling problem is the process of allocating train services to the crew duties based on the published train timetable while satisfying operational and contractual requirements. The problem is restricted by many constraints and it belongs to the class of NP-hard. In this paper, we develop a mathematical model for railway crew scheduling with the aim of minimising the number of crew duties by reducing idle transition times. Duties are generated by arranging scheduled trips over a set of duties and sequentially ordering the set of trips within each of duties. The optimisation model includes the time period of relief opportunities within which a train crew can be relieved at any relief point. Existing models and algorithms usually only consider relieving a crew at the beginning of the interval of relief opportunities which may be impractical. This model involves a large number of decision variables and constraints, and therefore a hybrid constructive heuristic with the simulated annealing search algorithm is applied to yield an optimal or near-optimal schedule. The performance of the proposed algorithms is evaluated by applying computational experiments on randomly generated test instances. The results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time for large-sized problems.

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This essay is a critique of the discourse concerned with a so coiled Crisis of Representation. It examines the role of representational media (text and drawing) in the formation of the notion of an architectural ‘work’ and argues that there is no necessary privilege to any ordering of modes of representation rather particular orderings uncover specific agendas.

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In the current market, extensive software development is taking place and the software industry is thriving. Major software giants have stated source code theft as a major threat to revenues. By inserting an identity-establishing watermark in the source code, a company can prove it's ownership over the source code. In this paper, we propose a watermarking scheme for C/C++ source codes by exploiting the language restrictions. If a function calls another function, the latter needs to be defined in the code before the former, unless one uses function pre-declarations. We embed the watermark in the code by imposing an ordering on the mutually independent functions by introducing bogus dependency. Removal of dependency by the attacker to erase the watermark requires extensive manual intervention thereby making the attack infeasible. The scheme is also secure against subtractive and additive attacks. Using our watermarking scheme, an n-bit watermark can be embedded in a program having n independent functions. The scheme is implemented on several sample codes and performance changes are analyzed.

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Recently, a new approach for structuring acyclic process models has been introduced. The algorithm is based on a transformation between the Refined Process Structure Tree (RPST) of a control flow graph and the Modular Decomposition Tree (MDT) of ordering relations. In this paper, an extension of the algorithm is presented that allows to partially structure process models in the case when a process model cannot be structured completely. We distinguish four different types of unstructuredness of process models and show that only two are possible in practice. For one of these two types of unstructuredness an algorithm is proposed that returns the maximally structured representation of a process model.

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Process models specify behavioral aspects by describing ordering constraints between tasks which must be accomplished to achieve envisioned goals. Tasks usually exchange information by means of data objects, i.e., by writing information to and reading information from data objects. A data object can be characterized by its states and allowed state transitions. In this paper, we propose a notion which checks conformance of a process model with respect to data objects that its tasks access. This new notion can be used to tell whether in every execution of a process model each time a task needs to access a data object in a particular state, it is ensured that the data object is in the expected state or can reach the expected state and, hence, the process model can achieve its goals.

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Real world business process models may consist of hundreds of elements and have sophisticated structure. Although there are tasks where such models are valuable and appreciated, in general complexity has a negative influence on model comprehension and analysis. Thus, means for managing the complexity of process models are needed. One approach is abstraction of business process models-creation of a process model which preserves the main features of the initial elaborate process model, but leaves out insignificant details. In this paper we study the structural aspects of process model abstraction and introduce an abstraction approach based on process structure trees (PST). The developed approach assures that the abstracted process model preserves the ordering constraints of the initial model. It surpasses pattern-based process model abstraction approaches, allowing to handle graph-structured process models of arbitrary structure. We also provide an evaluation of the proposed approach.

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Businesses document their operational processes as process models. The common practice is to represent process models as directed graphs. The nodes of a process graph represent activities and directed edges constitute activity ordering constraints. A flexible process graph modeling approach proposes to generalize process graph structure to a hypergraph. Obtained process structure aims at formalization of ad-hoc process control flow. In this paper we discuss aspects relevant to concurrent execution of process activities in a collaborative manner organized as a flexible process graph. We provide a real world flexible process scenario to illustrate the approach.

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The results of the combined experimental and numerical study suggest that nonequilibrium plasma-driven self-organization leads to better size and positional uniformity of nickel nanodot arrays on a Si(100) surface compared with neutral gas-based processes under similar conditions. This phenomenon is explained by introducing the absorption zone patterns, whose areas relative to the small nanodot sizes become larger when the surface is charged. Our results suggest that strongly nonequilibrium and higher-complexity plasma systems can be used to improve ordering and size uniformity in nanodot arrays of various materials, a common and seemingly irresolvable problem in self-organized systems of small nanoparticles. © 2008 American Institute of Physics.

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Self-assembly of size-uniform and spatially ordered quantum dot (QD) arrays is one of the major challenges in the development of the new generation of semiconducting nanoelectronic and photonic devices. Assembly of Ge QD (in the ∼5-20 nm size range) arrays from randomly generated position and size-nonuniform nanodot patterns on plasma-exposed Si (100) surfaces is studied using hybrid multiscale numerical simulations. It is shown, by properly manipulating the incoming ion/neutral flux from the plasma and the surface temperature, the uniformity of the nanodot size within the array can be improved by 34%-53%, with the best improvement achieved at low surface temperatures and high external incoming fluxes, which are intrinsic to plasma-aided processes. Using a plasma-based process also leads to an improvement (∼22% at 700 K surface temperature and 0.1 MLs incoming flux from the plasma) of the spatial order of a randomly sampled nanodot ensemble, which self-organizes to position the dots equidistantly to their neighbors within the array. Remarkable improvements in QD ordering and size uniformity can be achieved at high growth rates (a few nms) and a surface temperature as low as 600 K, which broadens the range of suitable substrates to temperature-sensitive ultrathin nanofilms and polymers. The results of this study are generic, can also be applied to nonplasma-based techniques, and as such contributes to the development of deterministic strategies of nanoassembly of self-ordered arrays of size-uniform QDs, in the size range where nanodot ordering cannot be achieved by presently available pattern delineation techniques.