Extracting information from the molten salt database

Molten salt technology is a catchall phrase that includes some very diverse technologies; electrochemistry, heat transfer, chemical oxidation/reduction baths, and nuclear reactors. All of these technologies are linked by the general characteristics of molten salts that can function as solvents, have good heat-transfer characteristics, function like a fluid, can attain very high temperatures, can conduct electricity, and also may have chemical catalytic properties. The Janz molten salt database is the most comprehensive compilation of property data about molten salts available today and is widely used for both fundamental and applied purposes. Databases are traditionally viewed as “static” documents that are used in a “search and retrieval” mode. These static data can be transformed by informatics and data mining tools into a dynamic dataset for analysis of the properties of the, materials and for making predictions. While this approch has been successful in the chemical and biochemical sciences in searching for and establishing structure-property relationships, it is not widely used in the materials science community. Because the design of the original molten salt database was not oriented toward this informatics goal, it was essential to evaluate this dataset in terms of data mining standards. Two techniques were used—a projection (principal components analysis (PCA)) and a predictive method (partial least squares (PLS))—in conjunction with fundamental knowledge acquired from the long-term practice of molten salt chemistry. This article is based on a presentation made in the symposium entitled “Fourth International Alloy Conference,” which occurred in Kos, Greece, from June 26 to July 1, 2005, and was Sponsored by Engineering Conferences International (ECI) and co-sponsored by Lawrence Livermore National Laboratory and Naval Research Laboratory, United Kingdom.