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Published on: October 20, 2020
Discrimination of nano-objects via cluster analysis techniques applied to time-resolved thermo-acoustic microscopy
Andrea Ronchi1, Andrea Sterzi2, Marco Gandolfi3
1Department of Physics and Astronomy, KU Leuven, Celestijnenlaan 200D, 3001 Leuven, Belgium; Interdisciplinary Laboratories for Advanced Materials Physics (I-LAMP), Università Cattolica del Sacro Cuore, I-25121 Brescia, Italy; Dipartimento di Matematica e Fisica, Università Cattolica del Sacro Cuore, I-25121 Brescia, Italy.
Unsupervised clustering effectively sorts nanometric metal disks using thermo-acoustic microscopy. This method identifies distinct nanopatterns for non-destructive testing without needing prior physical knowledge.
Area of Science:
- Materials Science
- Nanotechnology
- Optics
Background:
- Characterizing nanometric structures is crucial for advanced materials and devices.
- Thermo-acoustic microscopy offers a pathway for probing nanoscale properties.
Purpose of the Study:
- To develop a time-effective, unsupervised method for discriminating nanometric metal disks.
- To establish a robust protocol for analyzing thermo-acoustic responses of nanopatterned elements.
Main Methods:
- Utilizing unsupervised clustering techniques for data analysis.
- Applying cluster analysis to time-resolved optical traces from thermo-acoustic microscopy with asynchronous optical sampling.
- Developing fingerprint time-resolved traces to characterize clusters.
Main Results:
- Successful discrimination of nanometric metal disks based on their thermo-acoustic response.
- Identification of distinct clusters, each represented by a characteristic fingerprint trace.
- Demonstration of a protocol robust to variations in physical mechanisms.
Conclusions:
- Unsupervised clustering provides an effective approach for analyzing nanoscale material responses.
- The developed protocol serves as an alternative diagnostic tool for on-chip, non-destructive testing of nano-objects.
- This method offers broad applicability without requiring specific physical mechanism knowledge.
