Associate Professor
Dept. Mechanical Engineering & Materials Science
University of Pittsburgh
Pittsburgh
PA
15261
United States
PH:
+1 (412) 6249735
Fax:
+1 (412) 6248069
Email:
[email protected]
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Background
Dr Nettleship’s teaching interests include materials processing and mechanical
properties. He teaches introductory materials science and engineering as well
as higher level undergraduate courses in ceramics, materials processing and
mechanical properties of materials. He is particularly interested in the undergraduate
laboratory experience and its role in teaching fundamental concepts and tools.
At the graduate level he teaches ceramics processing and mechanical behavior
of ceramic materials.
Dr. Nettleship has two main areas of research. The first is the processing
of macroporous ceramics for biomedical and environmental applications. The second,
termed “Microstructure Mining”, involves creating and using microstructural
information to support decision making for processing high reliability materials.
This is described below.
Dr. Nettleship’s research interests are rooted in the concept of “microstructure
mining” which he has developed over the last decade. Until now materials
research has tended to focus on new materials, often emphasizing underlying
mechanisms and new physical understanding. While this results in an appreciation
of the “ideal microstructure”, it often fails to provide information
on the microstructural phenomena that control reliability, a topic that is of
primary concern to those interested in manufacturing. Microstructure mining
has been developed as a response to this circumstance. It is an interdisciplinary
approach which considers material structures to be complex systems and combines
new methods in quantitative microstructural analysis and materials informatics
to address problems in processing for high reliability. In this method, digitized
microstructural images are processed and assembled into databases that can be
searched using existing database mining methods. The resulting correlations
can be used for: (i) empirical process modeling, (ii) exploring new physical
understanding of materials processing and (iii) developing and testing of phenomenological
models of microstructure evolution.