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Ye X.,University of Pennsylvania | Chen J.,University of Pennsylvania | Engel M.,University of Michigan | Millan J.A.,University of Michigan | And 8 more authors.
Nature Chemistry | Year: 2013

Progress in nanocrystal synthesis and self-assembly enables the formation of highly ordered superlattices. Recent studies focused on spherical particles with tunable attraction and polyhedral particles with anisotropic shape, and excluded volume repulsion, but the effects of shape on particle interaction are only starting to be exploited. Here we present a joint experimental- computational multiscale investigation of a class of highly faceted planar lanthanide fluoride nanocrystals (nanoplates, nanoplatelets). The nanoplates self-assemble into long-range ordered tilings at the liquid-air interface formed by a hexane wetting layer. Using Monte Carlo simulation, we demonstrate that their assembly can be understood from maximization of packing density only in a first approximation. Explaining the full phase behaviour requires an understanding of nanoplate-edge interactions, which originate from the atomic structure, as confirmed by density functional theory calculations. Despite the apparent simplicity in particle geometry, the combination of shape-induced entropic and edge-specific energetic effects directs the formation and stabilization of unconventional long-range ordered assemblies not attainable otherwise. © 2013 Macmillan Publishers Limited. Source


Mohaghegh S.D.,Intelligent Solutions Inc. | Mohaghegh S.D.,West Virginia University
Journal of Natural Gas Science and Engineering | Year: 2011

In this paper a new class of reservoir models that are developed based on the pattern recognition technologies collectively known as Artificial Intelligence and Data Mining (AI&DM) is introduced. The workflows developed based on this new class of reservoir simulation and modeling tools break new ground in modeling fluid flow through porous media by providing a completely new and different angle on reservoir simulation and modeling. The philosophy behind this modeling approach and its major commonalities and differences with numerical and analytical models are explored and two different categories of such models are explained. Details of this technology are presented using examples of most recent applications to several prolific reservoirs in the Middle East and in the Gulf of Mexico.AI-based Reservoir Models can be developed for green or brown fields. Since these models are developed based on spatio-temporal databases that are specifically developed for this purpose, they require the existence of a basic numerical reservoir simulator for the green fields while can be developed entirely based on historical data for brown fields. The run-time of AI-based Reservoir Models that provide complete field responses is measured in seconds rather than hours and days (even for a multi-million grid block reservoir). Therefore, providing means for fast track reservoir analysis and AI-assisted history matching are intrinsic characteristics of these models. AI-based Reservoir Models can, in some cases, completely substitute numerical reservoir simulation models, work side by side but completely independent or be integrated with them in order to increase their productivity.Advantages associated with AI-based Reservoir Models are short development time, low development cost, fast track analysis and practical capability to quantify the uncertainties associated with the static model. AI-based Reservoir Model includes a novel design tool for comprehensive analysis of the full field and design of field development strategies to meet operational targets. They have open data requirement architecture that can accommodate a wide variety of data from pressure tests to seismic. © 2011 Elsevier B.V. Source


Patent
University of Pennsylvania and Intelligent Solutions Inc. | Date: 2011-10-03

Monodisperse particles having: a single pure crystalline phase of a rare earth-containing lattice, a uniform three-dimensional size, and a uniform polyhedral morphology are disclosed. Due to their uniform size and shape, the monodisperse particles self assemble into superlattices. The particles may be luminescent particles such as down-converting phosphor particles and up-converting phosphors. The monodisperse particles of the invention have a rare earth-containing lattice which in one embodiment may be an yttrium-containing lattice or in another may be a lanthanide-containing lattice. The monodisperse particles may have different optical properties based on their composition, their size, and/or their morphology (or shape). Also disclosed is a combination of at least two types of monodisperse particles, where each type is a plurality of monodisperse particles having a single pure crystalline phase of a rare earth-containing lattice, a uniform three-dimensional size, and a uniform polyhedral morphology; and where the types of monodisperse particles differ from one another by composition, by size, or by morphology. In a preferred embodiment, the types of monodisperse particles have the same composition but different morphologies. Methods of making and methods of using the monodisperse particles are disclosed.


Patent
Intelligent Solutions Inc. | Date: 2014-07-28

This invention relates to a transparent or translucent transaction card having a base comprising a core of substantially transparent or translucent material with a plurality of coats, including optically recognizable ink comprising one or more infrared blocking dyes and other nanoparticles, such as rare earth nanophosphors and other metal nanoparticles, and/or optically recognizable film comprising nanoparticles, such as rare earth nanophosphors, and other metal oxide and/or non-oxide complexes, and methods for their preparation.


Patent
Intelligent Solutions Inc. | Date: 2015-10-23

This invention relates to a transparent or translucent transaction card having a base comprising a core of substantially transparent or translucent material with a plurality of coats, including optically recognizable ink comprising one or more infrared blocking dyes and other nanoparticles, such as rare earth nanophosphors and other metal nanoparticles, and/or optically recognizable film comprising nanoparticles, such as rare earth nanophosphors, and other metal oxide and/or non-oxide complexes, and methods for their preparation.

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