Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-23T23:03:03.018Z Has data issue: false hasContentIssue false
  • English
  • Français

Handshaking Your Way to the Top: Simulation at the Nanoscale

Published online by Cambridge University Press:  01 January 2022

Eric Winsberg
Get access Rights & Permissions [Opens in a new window]

Abstract

Should philosophers of science be paying attention to developments in “nanoscience”? Undoubtedly, it is too early to tell for sure. The goal of this paper is to take a preliminary look. In particular, I look at the use of computational models in the study of nano-sized solid-state materials. What I find is that there are features of these models that appear on their face to be at odds with some basic philosophical intuitions about the relationships between different theories and between theories and their models. My conclusion is that developments in nanoscience are not an unlikely place for novel insights in the philosophy of science to emerge.

Type
Simulation, Instrumentation, and Representation at the Nanoscale
Information
Philosophy of Science , Volume 73 , Issue 5: Proceedings of the 2004 Biennial Meeting of The Philosophy of Science Association. Part II: Symposia Papers. Edited by Miriam Solomon , December 2006 , pp. 582 - 594
Copyright
Copyright © The Philosophy of Science Association

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

‡

I thank the many attendees at PSA 2004 and at a presentation at the University of Bielefeld for helpful comments.

References

Abraham, F., Broughton, J., Bernstein, N., and Kaxiras, E. (1998), “Spanning the Length Scales in Dynamic Simulation,” Computers in Physics 12 (6): 538–546..CrossRefGoogle Scholar
Batterman, R. (2002), The Devil in the Details: Asymptotic Reasoning in Explanation, Reduction, and Emergence. New York: Oxford University Press.Google Scholar
Broughton, J., Abraham, F., Bernstein, N., and Kaxiras, E. (1999), “Concurrent Coupling of Length Scales: Methodology and Application,” Physical Review B 60 (4): 2391–2403..CrossRefGoogle Scholar
Chelikowski, J., and Ratner, M. (2001), “Nanoscience, Nanotechnology, and Modeling,” Computing in Science and Engineering 3 (4): 40–41..CrossRefGoogle Scholar
Frisch, M. (2004), “Inconsistency in Classical Electrodynamics,” Philosophy of Science 71 (4): 525–549..CrossRefGoogle Scholar
Laymon, R. (1985), “Idealization and the Testing of Theories by Experimentation,” in Achinstein, P. and Hannaway, O. (eds.), Observation, Experiment and Hypothesis in Modern Physical Science. Cambridge: MIT Press, 147–173.Google Scholar
Nakano, A., et al. (2001), “Multiscale Simulation of Nano-systems,” Computing in Science and Engineering 3 (4): 56–66..CrossRefGoogle Scholar
Rudd, R. E., and Broughton, J. Q. (2000), “Concurrent Coupling of Length Scales in Solid State Systems,” Physica Status Solidi B 217:251–291.3.0.CO;2-A>CrossRefGoogle Scholar
Stillinger, F. H., and Weber, T. A. (1985), “Computer Simulation of Local Order in Condensed Phases of Silicon,” Physical Review B 31:5262–5271.CrossRefGoogle ScholarPubMed
Winsberg, E. (2006), “Models of Success vs. the Success of Models: Reliability without Truth,” Synthese 152:1–19.CrossRefGoogle Scholar