Directional Statistics of Preferential Orientations of Two Shapes in Their Aggregate and Its Application to Nanoparticle Aggregation



Sikaroudi, Ali Esmaieeli, Welch, David A, Woehl, Taylor J, Faller, Roland, Evans, James E, Browning, Nigel D and Park, Chiwoo ORCID: 0000-0002-2463-8901
(2018) Directional Statistics of Preferential Orientations of Two Shapes in Their Aggregate and Its Application to Nanoparticle Aggregation. Technometrics, 60 (3). pp. 332-344.

[thumbnail of ParketalTechnometricssubmitted.pdf] Text
ParketalTechnometricssubmitted.pdf - Author Accepted Manuscript

Download (1MB)

Abstract

Nanoscientists have long conjectured that adjacent nanoparticles aggregate with one another in certain preferential directions during a chemical synthesis of nanoparticles, which is referred to the oriented attachment. For the study of the oriented attachment, the microscopy and nanoscience communities have used dynamic electron microscopy for direct observations of nanoparticle aggregation and have been so far relying on manual and qualitative analysis of the observations. We propose a statistical approach for studying the oriented attachment quantitatively with multiple aggregation examples in imagery observations. We abstract an aggregation by an event of two primary geometric objects merging into a secondary geometric object. We use a point set representation to describe the geometric features of the primary objects and the secondary object, and formulated the alignment of two point sets to one point set to estimate the orientation angles of the primary objects in the secondary object. The estimated angles are used as data to estimate the probability distribution of the orientation angles and test important hypotheses statistically. The proposed approach was applied for our motivating example, which demonstrated that nanoparticles of certain geometries have indeed preferential orientations in their aggregates.

Item Type: Article
Additional Information: peerreview_statement: The publishing and review policy for this title is described in its Aims & Scope. aims_and_scope_url: http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=utch20
Uncontrolled Keywords: 49 Mathematical Sciences, 4905 Statistics, Nanotechnology, Bioengineering
Depositing User: Symplectic Admin
Date Deposited: 12 Dec 2018 09:59
Last Modified: 21 Jun 2024 08:49
DOI: 10.1080/00401706.2017.1366949
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3029869