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Applications of Crystal Structure Prediction

Crystal structure prediction methods do not aim to replace experimental studies but are a complementary technique to experimental investigations. The roles that CSP can play in such investigations can fall into three categories to characterize an existing material, usually as an aid to crystal structure determination from [Pg.105]

FIGURE 5.5 Distributions of calculated differences in (a) lattice energy and (b) lattice vibrational entropy between parrs of known polymorphs of organic molecules. Source Nyman and Day [91], http //pubs.rsc.org/en/content/articlehtml/2015/ce/c5ce00045a. Used under CC-BY 3.0 http //creativecommons.Org/licenses/by/3.0/. [Pg.106]


Abstract Methods, evolutionary and systematic search approaches, and applications of crystal structure prediction of closest-packed and framework materials are reviewed. Strategies include developing better cost functions, used to assess the quality of the candidate structures that are generated, and ways to reduce the set of candidate structures to be assessed. The crystallographic coordinates for new materials, available only as a powder sample, are often intractable from diffraction data alone. In recent years, steady progress has been made in the ability to solve previously unknown crystal structures of such compounds, the generation of known structures (inferring more confidence in such approaches) and the prediction of hypothetical yet-to-be-synthesised structures. [Pg.95]

Finding applications of crystal structures by employing the polarization potential through the ionic constituents which eventually drives the intensity of chemical bond, thus the type of bonding and the allied properties, toward predicting the manifested (observed) features. [Pg.486]

R. J. Wawak, J. Pillardy, A. Liwo, K. D. Gibson, and H. A. Scheraga, Diffusion equation and distance scaling methods of global optimization Applications to crystal structure prediction. J. Phys. Chem. A 102(17), 2904-2918 (1998). [Pg.453]

The lattice energy based on the Born model of a crystal is still frequently used in simulations [14]. Applications include defect formation and migration in ionic solids [44,45],phase transitions [46,47] and, in particular, crystal structure prediction whether in a systematic way [38] or from a SA or GA approach [ 1,48]. For modelling closest-packed ionic structures with interatomic force fields, typically only the total lattice energy (per unit cell) created by the two body potential,... [Pg.107]

C.M. Freeman, Inorganic Crystal-Structure Prediction Using Simplified Potentials and Experimental Unit Cells - Application to the Polymorphs of Titanium-Dioxide. J. Mater. Chem., 1993, 3, 531-535. [Pg.460]

The applications we now discuss relate to the modelling and prediction of crystal structures, to the development of atomistic models for amorphous materials, to the modelling of surfaces of inorganic solids, to the simulation of the dynamical and defect properties of solids and to the explicit calculation of the electronic structure of crystals. They will foreshadow the much more detailed accounts that follow in later chapters. [Pg.8]


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Applications structure

Crystal prediction

Crystal structure prediction

Crystal structure prediction applications

Crystal structures, predicted

Crystallization predictions

Predicting structures

Prediction of structure

Structured-prediction

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