Location and Dispersion Analysis

Chiwoo Park () and Yu Ding ()
Additional contact information
Chiwoo Park: Florida State University
Yu Ding: Industrial & Systems Engineering

Chapter Chapter 5 in Data Science for Nano Image Analysis, 2021, pp 109-144 from Springer

Abstract: Abstract Material scientists have discovered that certain properties of a composite, for instance, the strength, conductivity or transparency, can be remarkably enhanced by blending nanoparticles into the host materials. The resulting improvement in material properties is believed to depend, to a large degree, on how uniformly nanoparticles are mixed into the host materials. This calls for data science methods to quantify the homogeneity of nanoparticles mixing state, also referred to the location and dispersion analysis of nanoparticles in a host material. This chapter covers two methods of quantifying the mixing state: the count-based approaches such as the quadrat method and the distance-based approaches such as Ripley’s K function. Aware that the real materials are 3D while the current nano images are mostly 2D, the last section of the chapter is dedicated to the discussion on the 2D-to-3D inference. We want to note that the importance of material mixing applies not only to nanoparticle-embedded materials but also to other types of material mixing involving a host and additive or reinforcing agents, endowing the methods discussed in this chapter with broader impacts beyond nanomaterials.

Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-030-72822-9_5

Ordering information: This item can be ordered from
http://www.springer.com/9783030728229

DOI: 10.1007/978-3-030-72822-9_5

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().