Diffusion-based clustering analysis of coherent X-Ray scattering patterns of self-assembled nanoparticles

Hao Huang, Shinjae Yoo, Konstantine Kaznatcheev, Kevin G. Yager, Fang Lu, Dantong Yu, Oleg Gang, Andrei Fluerasu, Hong Qin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Coherent X-ray scattering is an emerging technique for measuring structure at the nanoscale. Data management and analysis is becoming a bottleneck in this technique. We present an unsupervised method which can sort and cluster the scattering snapshots, uncovering patterns inherent in the data. Our algorithm operates without resorting to templates, specific noise models, or user-directed learning. We test our methods using scattering images of two-dimensional nanoparticle assemblies. The experimental results show the effectiveness of our algorithm on real world scientific data.

Original languageEnglish (US)
Title of host publicationProceedings of the 29th Annual ACM Symposium on Applied Computing, SAC 2014
PublisherAssociation for Computing Machinery
Pages85-90
Number of pages6
ISBN (Print)9781450324694
DOIs
StatePublished - Jan 1 2014
Externally publishedYes
Event29th Annual ACM Symposium on Applied Computing, SAC 2014 - Gyeongju, Korea, Republic of
Duration: Mar 24 2014Mar 28 2014

Publication series

NameProceedings of the ACM Symposium on Applied Computing

Other

Other29th Annual ACM Symposium on Applied Computing, SAC 2014
CountryKorea, Republic of
CityGyeongju
Period3/24/143/28/14

All Science Journal Classification (ASJC) codes

  • Software

Keywords

  • AHK
  • EMD
  • Nanoparticle Assemblies

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