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Binary Gaseous, Liquid, near-Critical, and Supercritical Fluid Systems of Nonelectrolytes : Landolt-Bornstein: Numerical Data and Functional Relationships in Science and Technology - New Series - C. J. Wormald

Binary Gaseous, Liquid, near-Critical, and Supercritical Fluid Systems of Nonelectrolytes

By: C. J. Wormald, K. Sosnkowska-Kehiaian, J.-P. E. Grolier, J.-C. Fontaine, H.V. Kehiaian

Multi-Item Pack | 1 December 2004

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This subvolume contains selected data on heats of mixing and solution of binary gaseous, liquid, near-critical, and supercritical fluid systems of nonelectrolytes, including aqueous-organic systems, in broad ranges of temperature, pressure, and composition. All the data are extracted from the original literature published from 1957 to 2005. The names of the authors, the titles of the publications, and the exact references are given. Estimated uncertainties are reported. The printed volume presents tables for 314 representative systems. The CD-ROM displays all these data, as well as 134 additional data files, in PDF format and in fully documented computer readable standard electronic files (SELF and ELDATA)t. Moreover, the ELBT-program includes a comprehensive bibliographical database on heats of mixing and solution measurements published in the period 1853-2005 for 10867 two- to six-component systems consisting of organic or inorganic electrolytes and nonelectrolytes, ionic liquids, alloys, fused salts, polymers and other materials. The ELBT-program allows the fast search of data according to property type, chemical system (substances, mixtures, and solutions), author(s), source and year of publication. The software on the CD-ROM allows the correlation of the numerical data with several equations and the display of the original data and of the correlated data in tabular and graphical form. In order to facilitate the storage, exchange and use of the data, the ELBT-program of this volume allows importation of the information of SELF and ELDATA files, as well as of the files containing the results of correlations into Spreadsheet ML documents.

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