Quantitative Analysis of Nanorod Aggregation and Morphology from Scanning Electron Micrographs Using SEMseg.


Journal

The journal of physical chemistry. A
ISSN: 1520-5215
Titre abrégé: J Phys Chem A
Pays: United States
ID NLM: 9890903

Informations de publication

Date de publication:
25 Jun 2020
Historique:
pubmed: 29 5 2020
medline: 29 5 2020
entrez: 29 5 2020
Statut: ppublish

Résumé

General methods to achieve better physical insight about nanoparticle aggregation and assembly are needed because of the potential role of aggregation in a wide range of materials, environmental, and biological outcomes. Scanning electron microscopy (SEM) is fast and affordable compared to transmission electron microscopy, but SEM micrographs lack contrast and resolution due to lower beam energy, topographic contrast, edge effects, and charging. We present a new segmentation algorithm called SEMseg that is robust to the challenges inherent in SEM micrograph analysis and demonstrate its utility for analyzing gold (Au) nanorod aggregates. SEMseg not only supports nanoparticle size analysis for dispersed nanoparticles, but also discriminates between nanoparticles within an aggregate. We compare our algorithm to those incorporated into the commonly used software ImageJ and demonstrate improved segmentation of aggregate structures. New physical insight about aggregation is demonstrated by the introduction of an order parameter describing side-by-side structure in nanoparticle aggregates. We also present the segmentation and fitting algorithms included in SEMseg within a user-friendly graphical user interface. The resulting code is provided with an open-source interface to provide quantitative image processing tools for researchers to characterize both dispersed nanoparticles and nanoparticle assemblies in SEM micrographs with high throughput.

Identifiants

pubmed: 32463671
doi: 10.1021/acs.jpca.0c03190
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

5262-5270

Auteurs

Rashad Baiyasi (R)

Department of Electrical and Computer Engineering, Rice University, MS 366, Houston, Texas 77005, United States.

Miranda J Gallagher (MJ)

Department of Chemistry, Rice University, MS 60, Houston, Texas 77005, United States.

Lauren A McCarthy (LA)

Department of Chemistry, Rice University, MS 60, Houston, Texas 77005, United States.

Emily K Searles (EK)

Department of Chemistry, Rice University, MS 60, Houston, Texas 77005, United States.

Qingfeng Zhang (Q)

Department of Chemistry, Rice University, MS 60, Houston, Texas 77005, United States.
Smalley-Curl Institute, Rice University, Houston, Texas 77005, United States.

Stephan Link (S)

Department of Electrical and Computer Engineering, Rice University, MS 366, Houston, Texas 77005, United States.
Department of Chemistry, Rice University, MS 60, Houston, Texas 77005, United States.
Smalley-Curl Institute, Rice University, Houston, Texas 77005, United States.

Christy F Landes (CF)

Department of Electrical and Computer Engineering, Rice University, MS 366, Houston, Texas 77005, United States.
Department of Chemistry, Rice University, MS 60, Houston, Texas 77005, United States.
Smalley-Curl Institute, Rice University, Houston, Texas 77005, United States.
Department of Chemical and Biomolecular Engineering, Rice University, Houston, Texas 77005, United States.

Classifications MeSH