SmartMetals: a new method for metal identification based on fuzzy logic

Abstract

This paper presents a method of searching, identifying and cross-referencing metal alloys based on their chemical composition and/or mechanical properties, typically obtained by analysis and tests. The method uses a general pattern similar to the approach of a human expert, and relies on a classification of metals based on metallurgical expertise and fuzzy logic for identifying metals and comparing their chemical and mechanical properties. The algorithm has been tested and deployed in real applications for fast metal identification and finding of unknown equivalents, by the leading companies in the field. The same principles can also be used in other domains for similar problems, such as organic and inorganic materials identification and generic drugs comparison.

Selecting Doping Elements by Data Mining for Advanced Magnets

“…As is known, data analysis and machine learning can be used to discover rules that exist in data. , Recently, it has been successfully demonstrated in catalysts and shape memory alloys that new advanced materials can be developed by machine learning even based on “small data sets” . However, for the Sm-Co systems, although some fundamental features were collected in the known databases such as Total Materia, PAULING FILE, NOMAD, and Materials Project, the data available for materials design aimed at a certain magnetic property are very limited.…”