Materials Science: Data Sources

The data, encapsulated in 914 tables and 1025 illustrations, have been selected and extracted primarily from the extensive high-quality data collection Landolt-Börnstein and also from other systematic data sources and recent publications of physical and technical property data.

This 2nd Edition has been updated with over 40 new interactive tables which include new tables covering 503 Heat Capacity and Thermal Conductivity, 3,133 Reaction Thermodynamics and Equilibrium Constants, 854 Density and Compressibility, 13,332 Vaporization and Vapor Pressure, 185 Thermal Expansion, 377 Transport and Flow, and 1902 Electrical Properties data. Each table is fully interactive and searchable by keyword and numeric property value. The thermodynamic tables feature an Equation Plotter that graphically represents the temperature correlation relationships and allows for easy calculation and plotting of the properties. This important, interactive Knovel reference contains tables of physical, solvent, and thermodynamic properties. The physical property tables alone include over 21,000 inorganic and organic compounds, and pure substances. The solvent property tables have data for 385 common solvents, and the thermodynamic property tables have data for over 15,000 compounds. Additionally, several tables make use of the interactive Equation Plotter to plot thermodynamic properties as a function of temperature. Source of the Data: This information was collected from publicly available Internet sources and from non-copyrighted publications. Knovel's internal engineering and science editors reviewed the data. If there were differences between values for the same compound and/or the same property, the values were either averaged or a range was created. Final product testing emphasizes data integrity to sources and consistency with data models and leverages the skill sets of our team resources. Automated programmatic validation processes are performed to compare source against final published data. Errors are trapped and corrected to ensure fidelity to the source data.

designed to help materials scientists calculate macroscopic properties from images of real or simulated microstructures. It reads an image, assigns material properties to features in the image, and conducts virtual experiments to determine the macroscopic properties of the microstructure.