Many scientists and administrators contend that instrument development is not compatible with the operation of American universities. The period for promotion to tenure might be too short for young scientists embarking on a difficult instrument development program, and a project might require more time than a graduate student’s education. But these problems can be overcome, as demonstrated by laboratories in Europe and Japan and by different departments (such as high-energy physics, astrophysics, or biology) within the American university system.
The potential for development of new instrumentation is particularly great at present. For instance, materials processing equipment could combine computer control of such technologies as MBE, plasma deposition, and particle beam lithography. Synergistic combinations of emerging technologies could give birth to new and exciting instruments.
Recent advances in theoretical understanding and computational ability are changing the nature of materials science and engineering. Two complementary forces are driving these changes. The first is the unprecedented speed, capacity, and accessibility of computers. Problems in mathematics, data analysis, and communication that seemed untouchable just a few years ago can now be solved quickly and reliably with modern computational systems. The second is the growing complexity of materials research. The latter change has occurred in large part because instruments are now available to make highly detailed and quantitative measurements and because the computational ability exists to deal with the resulting wealth of data. Underlying all of these developments are advances in the theoretical understanding of materials properties and the mathematical ability to devise accurate numerical simulations.
Analysis and modeling find application in each of the four elements of materials science and engineering. For instance, in performance research, advances in analysis and modeling have made it possible to develop quantitative methods for solving some of the major problems in the field. In particular, accurate codes may become available to enable reliable predictions of the lifetimes of structural materials in service. Such observations also apply to the application of analysis and modeling in synthesis and processing and in characterization of the structures, compositions, and properties of materials. An example of computer analysis of copolymer systems is shown in Plate 4.
Analysis and modeling in materials research traditionally have been divided into roughly three different areas of activity. The most fundamental models—those used primarily by condensed-matter physicists and quantum chemists—deal with microscopic length scales, where the atomic structure of materials plays an explicit role. Much of the most sophisticated analysis is carried out at intermediate length scales, where continuum models are appropriate. Fi-