Seeking regularity from irregularity: unveiling the synthesis–nanomorphology relationships of heterogeneous nanomaterials using unsupervised machine learning

Abstract

Shape fingerprint functions and unsupervised machine learning are used to classify and analyze nanomaterial morphologies from 2D and 3D TEM data.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jan 01, 2022
Source ID
10.1039/d2nr03712b

Entities

People

  • Ahyoung Kim
  • Erik Luijten
  • Hyosung An
  • Lehan Yao
  • Qian Chen
  • Shan Zhou

Organizations

  • Chonnam National University
  • Northwestern University
  • United States Department of Energy
  • University of Illinois Urbana–Champaign

Tags

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Nanocomposite Materials Science
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks