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ERIC Number: EJ951455
Record Type: Journal
Publication Date: 2011-Nov
Pages: 4
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0021-9584
EISSN: N/A
Periodic Table of the Elements in the Perspective of Artificial Neural Networks
Lemes, Mauricio R.; Dal Pino, Arnaldo
Journal of Chemical Education, v88 n11 p1511-1514 Nov 2011
Although several chemical elements were not known by end of the 19th century, Mendeleev came up with an astonishing achievement, the periodic table of elements. He was not only able to predict the existence of (then) new elements, but also to provide accurate estimates of their chemical and physical properties. This is a profound example of the human intelligence. Here, we try to shed some light on the following question: Can an artificial intelligence system yield a classification of the elements that resembles, in some sense, the periodic table? To achieve our goal, we have used a self-organized map (SOM) with information available at Mendeleev's time. Our results show that similar elements tend to form individual clusters. Thus, although SOM generates clusters of halogens, alkaline metals, and transition metals that show a similarity with the periodic table of elements, the SOM did not achieve the sophistication that Mendeleev achieved. (Contains 5 tables and 3 figures.)
Division of Chemical Education, Inc and ACS Publications Division of the American Chemical Society. 1155 Sixteenth Street NW, Washington, DC 20036. Tel: 800-227-5558; Tel: 202-872-4600; e-mail: eic@jce.acs.org; Web site: http://pubs.acs.org/jchemeduc
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A