Combination of atomic force microscopy and principal component analysis as a general method for direct recognition of functional and structural domains in nanonocomposite materials

Bruno Torre*, Manuele Bicego, Marco Cristiani, Vittorio Murino, Alberto Diaspro, Roberto Cingolani

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

In this work, we report a simple method to direct identify nanometer sized textures in composite materials by means of AFM spectroscopy, aiming at recognizing structured region to be further investigated. It consists in acquiring a set of dynamic data organized in spectroscopy maps and subsequently extracting most valuable information by means of the principal component analysis (PCA) method. This algorithm projects the information of D spectroscopy curves, each containing P data, acquired at each point of an LxC grid into a subset of LxC maps without any assumption on the sample structure, filtering out redundancies and noise. As a consequence, a huge amount of 3D data is condensed into few 2D maps, easy to be examined. Results of this algorithm allow to find and locate regions of interest within the map, allowing a further reduction of data series to be extensively analyzed or modeled. In this work, we explain the main features of the method and show its application on a nanocomposite sample. Microsc. Res. Tech. 73:973-981, 2010.

Original languageEnglish (US)
Pages (from-to)973-981
Number of pages9
JournalMicroscopy Research and Technique
Volume73
Issue number10
DOIs
StatePublished - Oct 1 2010

Keywords

  • Dimensionality reduction
  • Dynamic spectroscopy
  • Functional materials
  • Functional recognition
  • Microscopy
  • Nanotechnology
  • Principal component analysis

ASJC Scopus subject areas

  • Anatomy
  • Histology
  • Instrumentation
  • Medical Laboratory Technology

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