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Title: New method of automated statistical analysis of polymer-stabilized metal nanoparticles in electron microscopy images

Abstract

The efficiency of the synthesis and application of metal/nonmetal particles several nanometers in size, prepared in solutions and stabilized with polymers, can be increased by applying a reliable statistical analysis and determining particle-size distributions for different systems. A new method for processing electron microscopy images of nanoparticles ≤10 nm in size and the program Analyzer of Nanoparticles designed for rapid recognition and measurements are presented. The program combines two approaches: threshold image processing for particle recognition and fitting the model of the particles with neighborhood background to the real experimental images.

Authors:
;  [1]
  1. Russian Academy of Sciences, Shubnikov Institute of Crystallography, Federal Scientific Research Centre “Crystallography and Photonics,” (Russian Federation)
Publication Date:
OSTI Identifier:
22758336
Resource Type:
Journal Article
Journal Name:
Crystallography Reports
Additional Journal Information:
Journal Volume: 62; Journal Issue: 5; Other Information: Copyright (c) 2017 Pleiades Publishing, Inc.; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 1063-7745
Country of Publication:
United States
Language:
English
Subject:
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY; EFFICIENCY; ELECTRON MICROSCOPY; IMAGE PROCESSING; IMAGES; NANOPARTICLES; NONMETALS; PARTICLE SIZE; POLYMERS; STATISTICAL MODELS; SYNTHESIS

Citation Formats

Shvedchenko, D. O., E-mail: dmitrymephi@gmail.com, and Suvorova, E. I. New method of automated statistical analysis of polymer-stabilized metal nanoparticles in electron microscopy images. United States: N. p., 2017. Web. doi:10.1134/S1063774517050200.
Shvedchenko, D. O., E-mail: dmitrymephi@gmail.com, & Suvorova, E. I. New method of automated statistical analysis of polymer-stabilized metal nanoparticles in electron microscopy images. United States. doi:10.1134/S1063774517050200.
Shvedchenko, D. O., E-mail: dmitrymephi@gmail.com, and Suvorova, E. I. Fri . "New method of automated statistical analysis of polymer-stabilized metal nanoparticles in electron microscopy images". United States. doi:10.1134/S1063774517050200.
@article{osti_22758336,
title = {New method of automated statistical analysis of polymer-stabilized metal nanoparticles in electron microscopy images},
author = {Shvedchenko, D. O., E-mail: dmitrymephi@gmail.com and Suvorova, E. I.},
abstractNote = {The efficiency of the synthesis and application of metal/nonmetal particles several nanometers in size, prepared in solutions and stabilized with polymers, can be increased by applying a reliable statistical analysis and determining particle-size distributions for different systems. A new method for processing electron microscopy images of nanoparticles ≤10 nm in size and the program Analyzer of Nanoparticles designed for rapid recognition and measurements are presented. The program combines two approaches: threshold image processing for particle recognition and fitting the model of the particles with neighborhood background to the real experimental images.},
doi = {10.1134/S1063774517050200},
journal = {Crystallography Reports},
issn = {1063-7745},
number = 5,
volume = 62,
place = {United States},
year = {2017},
month = {9}
}