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Related Experiment Video

Updated: Jul 19, 2025

Precision Milling of Carbon Nanotube Forests Using Low Pressure Scanning Electron Microscopy
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Reimagining Carbon Nanomaterial Analysis: Empowering Transfer Learning and Machine Vision in Scanning Electron

Siddharth Gupta1,2, Sunayana Gupta1, Arushi Gupta3

  • 1Ira A Fulton School of Engineering, Computer Science and Engineering, Arizona State University, Tempe, AZ 85281, USA.

Materials (Basel, Switzerland)
|August 12, 2023
PubMed
Summary

We developed a new method using AI and electron microscopy to identify nanoscale carbon materials like Q-carbon and nanodiamonds. This technique efficiently discovers and classifies diverse carbon allotropes, even when they are sparsely distributed.

Keywords:
Q-carbonRaman spectroscopygraphenelaser irradiationnon-equilibriumscanning electron microscopy

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Area of Science:

  • Materials Science
  • Nanotechnology
  • Artificial Intelligence

Background:

  • Identifying diverse nanoscale carbon allotropes is challenging due to sparse distribution.
  • Standard laser irradiation methods produce varied carbon polymorphs unpredictably.

Purpose of the Study:

  • To propose a novel technique for identifying and analyzing diverse nanoscale carbon allotropes.
  • To enable efficient discovery and classification of sparsely located carbon polymorphs.

Main Methods:

  • Precisely controlling quenching rates of undercooled molten carbon via laser irradiation.
  • Applying transfer-learning with convolutional neural networks and computer vision to scanning electron micrographs.
  • Achieving allotrope discovery even with sparse spatial presence.

Main Results:

  • Successfully formed microdiamonds, nanodiamonds, and Q-carbon films through controlled laser irradiation.
  • Achieved 92% accuracy for Q-carbon identification.
  • Reached 94% accuracy in distinguishing Q-carbon from nanodiamonds.

Conclusions:

  • The developed technique enables efficient identification and characterization of nanoscale carbon structures.
  • Automated tools for Q-materials and carbon polymorph identification are provided.
  • Opens new avenues for exploring these materials in various applications.