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Direct transformation of cubic diamond to hexagonal diamond (2002)

He, Hongliang ; Sekine, T. ; Kobayashi, T.

Woodbury, NY : American Institute of Physics (AIP)

Applied Physics Letters 81 (2002), S. 610-612

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ISSN: 1077-3118

Source: AIP Digital Archive

Topics: Physics

Notes: For a long time, hexagonal diamond has been formed only by static and shock wave compression of well-crystallized graphites. Here, we demonstrate that cubic diamond loses its structure stability and transforms to hexagonal diamond in massive. This transformation has been completed in nanoseconds under a shock wave compression of cubic diamond, in which the shock pressure and temperature are only tens of giga pascal and hundreds of kelvin, thermodynamically being within the stability of cubic diamond. The formation of hexagonal diamond is interpreted as a direct transition (solid to solid) of cubic diamond by a kinetic mechanism due to the shear stress and enhanced temperature induced by the rapid shock wave compression. © 2002 American Institute of Physics.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1063/1.1495078

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Sensory Modeling of Coffee with a Fuzzy Neural Network (2002)

Tominaga, O. ; Ito, F. ; Hanai, T. ; [et al.]

Oxford, UK : Blackwell Publishing Ltd

Journal of food science 67 (2002), S. 0

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ISSN: 1750-3841

Source: Blackwell Publishing Journal Backfiles 1879-2005

Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Process Engineering, Biotechnology, Nutrition Technology

Notes: : Models were constructed to predict sensory evaluation scores from the blending ratio of coffee beans. Twenty-two blended coffees were prepared from 3 representative beans and were evaluated with respect to 10 sensory attributes by 5 coffee cup-tasters and by models constructed using the response surface method (RSM), multiple regression analysis (MRA), and a fuzzy neural network (FNN). The RSM and MRA models showed good correlations for some sensory attributes, but lacked sufficient overall accuracy. The FNN model exhibited high correlations for all attributes, clearly demonstrated the relationships between blending ratio and flavor characteristics, and was accurate enough for practical use. FNN, thus, constitutes a powerful tool for accelerating product development.