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Journal of Failure Analysis and Prevention

, Volume 7, Issue 4, pp 229–238 | Cite as

Traditional Metallurgy, Nanotechnologies, and Structural Materials: A Sorby Award Lecture

  • M. R. LouthanJr.
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Abstract

Traditional metallurgical processes are among the many “old fashion” practices that use nanoparticles to control the behavior of materials. Many of these practices were developed long before microscopy could resolve nanoscale features, yet the practitioners learned to manipulate and control microstructural elements that they could neither see nor identify. Furthermore, these early practitioners used that control to modify microstructures and develop desired material properties. Centuries old colored glass, ancient high-strength steels and medieval organ pipes derived many of their desirable features through control of nanoparticles in their microstructures. Henry Sorby was among the first to recognize that the properties of rocks, minerals, metals, and organic materials were controlled by microstructure. However, Mr. Sorby was accused of the folly of trying to study mountains with a fsmicroscope. Although he could not resolve nanoscale microstructural features, Mr. Sorby’s observations revolutionized the study of materials. The importance of nanoscale microstructural elements should be emphasized, however, because the present foundation for structural materials was built by manipulating those features. That foundation currently supports several multibillion dollar industries but is not generally considered when the nanomaterials revolution is discussed. This lecture demonstrates that using nanotechnologies to control the behavior of metallic materials is almost as old as the practice of metallurgy and that many of the emergent nanomaterials technologists are walking along pathways previously paved by traditional metallurgists.

Keywords

Theoretical Strength Microstructural Defect National Nanotechnology Initiative Columbium Nanoscale Feature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© ASM International 2007

Authors and Affiliations

  1. 1.Materials Technology SectionSavannah River National LaboratoryAikenUSA

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