Discrimination of nano-objects via cluster analysis techniques applied to time-resolved thermo-acoustic microscopy

Claudio Giannetti, Francesco Banfi, Gabriele Ferrini, Andrea Ronchi, Marco Gandolfi, Andrea Sterzi, Ali Belarouci, Natalia Del Fatti

Research output: Contribution to journalArticlepeer-review

Abstract

Time-effective, unsupervised clustering techniques are exploited to discriminate nanometric metal disks patterned on a dielectric substrate. The discrimination relies on cluster analysis applied to time-resolved optical traces obtained from thermo-acoustic microscopy based on asynchronous optical sampling. The analysis aims to recognize similarities among nanopatterned disks and to cluster them accordingly. Each cluster is characterized by a fingerprint time-resolved trace, synthesizing the common features of the thermo-acoustics response of the composing elements. The protocol is robust and widely applicable, not relying on any specific knowledge of the physical mechanisms involved. The present route constitutes an alternative diagnostic tool for on-chip non-destructive testing of individual nano-objects.
Original languageEnglish
Pages (from-to)N/A-N/A
JournalUltrasonics
Volume114
DOIs
Publication statusPublished - 2021

Keywords

  • Cluster-analysis
  • Microscopy
  • Nanometrology
  • Non-destructive testing
  • Photoacoustics
  • Photothermics
  • Single metal nano-object

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