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Materials simulation

Car and Parrinello [202] proposed a teclmique for efficiently solving the Scluodinger equation which has had an enonuous impact on materials simulation (for reviews, see [203. 204. 205. 206]). The technique is an ab initio one, i.e., free of empirical parameters, and is based on the use of a quantum mechanical orthononual... [Pg.2275]

Brenner D W, O A Shendreova and D A Areshkin 1998. Quantum-Based Analytic Interatomic Force and Materials Simulation. In Lipkowitz K B and D B Boyd (Editors). Reviews in Computationc Chemistry Volume 12. New York, VCH Publishers, pp. 207-239. [Pg.265]

Ground red sandstone Meteorite material Simulated Mars soil... [Pg.305]

Phys. Cond. Matter, 14, 2745 (2002). The SIESTA Method for Ab Initio Order-N Materials Simulation. [Pg.247]

Donald W. Brenner, Olga A. Shenderova, and Denis A. Areshkin, Quantum-Based Analytic Interatomic Forces and Materials Simulation. [Pg.445]

A complete review of spectroscopic methods applied to the analysis of alkyl-modified surfaces with a comprehensive list of spectroscopic indicators of alkyl chain conformational order is provided elsewhere [9] this review will focus on the application of spectroscopic and other relevant experimental techniques for the characterization of shape-selective chromatographic materials. On the whole, it has been observed experimentally that any increase in alkyl stationary-phase conformational order promotes an increase in selectivity for shape-constrained solutes in RPLC separations [9], As a complement to the wealth of spectroscopic and chromatographic data, the use of molecular simulation techniques to visualize and characterize alkyl-modified surfaces may also provide new insights into molecular-level features that control shape selectivity. A review of progress in the field of chromatographic material simulations will also be discussed. [Pg.261]

Frauenherm, T.. Seifert, G., Elstner, M., Hajnal, Z., Jungnickel. G.. Porezag. D.. Suhai. S.. and Scholz. R. 2000. A Self-consistent Charge Density-functional Based Tight-binding Method for Predictive Materials Simulations in Physics, Chemistry and Biology , Phys. Stat. Sol. B. 217. 41. [Pg.301]

We have used both the commercial crude and stripped materials without further purification in tests of relative antioxidant effectiveness because they effectively simulate two different food exposures of phosphatide. The crude material simulates a typical emulsified oil (35% triglyceride), as in a baking shortening, while the stripped powder in microdispersion (3-5% triglyceride) is an approximate membrane model (25). [Pg.54]

Mixer material Simulation study only Polymers such as PMMA and PDMS may be suitable Mixing channel width, depth, length 300 pm, 500 pm, 5 mm... [Pg.217]

The main purpose of quantum-chemical modeling in materials simulation is to obtain necessary input data for the subsequent calculations of thermodynamic and kinetic parameters required for the next steps of multiscale techniques. Quantum-chemical calculations can also be used to predict various physical and chemical properties of the material in hand (the growing film in our case). Under quantum-chemical, we mean here both molecular and solid-state techniques, which are now implemented in numerous computer codes (such as Gaussian [25], GAMESS [26], or NWCHEM [27] for molecular applications and VASP [28], CASTEP [29], or ABINIT [30] for solid-state applications). [Pg.470]

Hietaniemi et al. [76] used a prerelease version of FDS4 to model lire spread on several materials in several different configurations and compared the calculated results with experimental data. This is one of the most comprehensive (in terms of the number of materials and the number of different configurations simulated) large-scale flame spread modeling studies conducted to date. The materials simulated include spruce timber (SBI, room/corner, and 6 m cavity), medium density fiber board (SBI and room/corner), PVC wall carpet on gypsum board (SBI, room/corner), upholstered furniture (furniture calorimeter and ISO room), and polyethylene-sheathed cables in 6 m cavity. [Pg.573]

In contrast to the use of large Sf ratios, where attention is focussed on the wall of the tube, Wood and Wise [62, 63] have used short tubes to determine j for the material simulating the end plate. They investigated the recombination efficiency of several metals for H atoms. In the later study [63], their terminal probe was in the form of a heated spiral filament of the metal under investigation. The decrease in energy necessary to maintain the filament at constant temperature was measured and assumed to be proportional to the atom concentration at the cross-section occupied by the filament. The method is preferable to the use of thermocouple probes, whose change in temperature might affect the atom decay profiles. Wood and Wise attribute differences in their results obtained... [Pg.204]

Materials Studio is a software environment that brings together the world s most advanced materials simulation and informatics technology. It is a product of Accelrys Inc. [Pg.28]

Soler JM, Artacho E, Gale JD, Garcia A, Junquera J, Ordejon P, Sanchez-Portal D (2002) The SIESTA Method for ab initio Order-N Materials Simulation, J Phys Condens Matter 14 2745-2779... [Pg.561]

In a separate study overall migration from several plastic films was compared with and without a sticky label attached to film. The overall migration limit was exceeded for selected material/simulant combinations. The author concluded that it could be anticipated, that a certain, possibly very significant, migration of substances from the label to the foodstuff could take place in real packaging also . [Pg.327]

Frauenheim T, Seifert G, Elstner M, Hajnal Z, Jungnickel G, Porezag D, Suhai S, Scholz R (2000) A self-consistent charge density-functional based tight-binding method for predictive materials simulations in physics, chemistry, and biology (2000) Physica Status Solid B 217 41-62 Espan ol P (1998) Fluid particle model. Phys Rev E 57 2930-2948... [Pg.214]

Photo 58 This boom and skimmer are undergoing tests in the Oil and Hazardous Materials Simulated Environmental Test Tank (OHMSETT) facility in Leonardo, New Jersey. Such testing is important to determine the parameters of equipment as well as to improve their design. (Environment Canada)... [Pg.96]

The incorporation of lossy and frequency-dependent materials in the production of modern devices, such as patch antennas, waveguides, or integrated circuits, has become a topic of intensive studies due to several attractive properties. Toward this direction, Yee s algorithm has already received the suitable modifications to cope with lossy [1-4] and dispersive configurations [5-19]. Given the competence of higher order schemes in material simulation, a possible... [Pg.121]

COMBINING SCATTERED WAVES IN ORDER TO OBTAIN AN IMAGE OF THE DIFFRACTING MATERIAL (SIMULATING AN X-RAY LENS)... [Pg.16]

Ken Jordan received his Ph.D. in physical chemistry in 1974 under the direction of Bob Silbey at MIT. He then joined the Department of Engineering and Applied Science, Yale University, as a J.W. Gibbs Instructor, being promoted to Assistant Professor in 1976. In 1978 Professor Jordan moved to the Chemistry Department at the University of Pittsburgh where he is now Professor and Director of the Center for Molecular and Materials Simulations. His interest in the application of computers to chemical problems stems from his graduate student days. Professor Jordan s recent research has focused on the properties of hydrogen-bonded clusters, modeling chemical reactions on surfaces, electron-induced chemistry and the development of new methods for Monte Carlo simulations. [Pg.1241]

Botanieal Gardens, transplanted material, simulated acid rain... [Pg.301]


See other pages where Materials simulation is mentioned: [Pg.175]    [Pg.123]    [Pg.538]    [Pg.221]    [Pg.24]    [Pg.28]    [Pg.335]    [Pg.92]    [Pg.210]    [Pg.636]    [Pg.254]    [Pg.397]    [Pg.1088]    [Pg.258]    [Pg.472]    [Pg.472]    [Pg.303]    [Pg.143]    [Pg.504]    [Pg.139]   
See also in sourсe #XX -- [ Pg.207 , Pg.210 ]

See also in sourсe #XX -- [ Pg.151 ]




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Analytic Potentials and Materials Simulation

Computer simulation in materials science

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First-Principle Simulation in Materials Science

Functional Properties of Phase Change Materials from Atomistic Simulations

Material balances simulation

Material-point-method simulation

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Quantum-Based Analytic Interatomic Forces and Materials Simulation

Simulation in Materials Science

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