The impact of subcontinuum gas conduction on topography measurement sensitivity using heated atomic force microscope cantilevers

Nathan D. Masters, Wenjing Ye, William P. King

Research output: Contribution to journalArticlepeer-review

Abstract

Nanometer-scale topographical imaging using heated atomic force microscope (AFM) cantilevers, referred to here as thermal sensing AFM (TSAFM), is a promising technology for high resolution topographical imaging of nanostructured surfaces. Heated AFM cantilevers were developed for high-density data storage, where the heated cantilever tip can form and detect 20 nm indents made in a thermoplastic polymer. The scan height of the cantilever heater platform is typically near 500 nm, but could be made much smaller to improve reading sensitivity. Under atmospheric conditions the continuum models used in previous studies to model the gas phase heat transfer are invalid for the smallest operating heights. The present study uses a molecular model of subcontinuum heat transfer coupled with a finite difference simulation to predict the behavior of a TSAFM system. A direct simulation Monte Carlo model and a kinetic theory based macromodel are separately developed and used to model subcontinuum gas conduction. For the working gas (argon) the simple macromodel is found to be accurate and is used to predict cantilever operation. This systems-level modeling approach for TSAFM operation can aid data interpretation and seeks to improve microcantilever design.

Original languageEnglish (US)
Article number100615
JournalPhysics of fluids
Volume17
Issue number10
DOIs
StatePublished - 2005
Externally publishedYes

Keywords

  • Argon
  • Atomic force microscopy
  • Finite difference methods
  • Heat conduction
  • Kinetic theory
  • Monte Carlo methods
  • Nanostructured materials
  • Sensitivity
  • Surface topography measurement

ASJC Scopus subject areas

  • Computational Mechanics
  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering
  • Fluid Flow and Transfer Processes

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