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

Ali Esmaieeli SikaroudiJPMorgan Chase, Jacksonville, FL

David A. WelchSuffolk County Community College, Selden, NY

Taylor J. WoehlDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD

Roland FallerDepartment of Chemical Engineering, University of California at Davis, Davis, CA

James E. EvansEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA

Nigel D. BrowningFundamental Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA

Chiwoo ParkDepartment of Industrial and Manufacturing Engineering, Florida State University, Tallahassee, FLCorrespondence[email protected]

http://orcid.org/0000-0002-2463-8901

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Tin Lok James Ng & Kwok-Kun Kwong. (2022) Universal approximation on the hypersphere. Communications in Statistics - Theory and Methods 51:24, pages 8694-8704.
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Riccardo Scimone, Tommaso Taormina, Bianca Maria Colosimo, Marco Grasso, Alessandra Menafoglio & Piercesare Secchi. (2022) Statistical Modeling and Monitoring of Geometrical Deviations in Complex Shapes With Application to Additive Manufacturing. Technometrics 64:4, pages 437-456.
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Articles from other publishers (3)

Chiwoo Park & Yu DingChiwoo Park & Yu Ding. 2021. Data Science for Nano Image Analysis. Data Science for Nano Image Analysis 75 108 .

Chiwoo Park & Yu DingChiwoo Park & Yu Ding. 2021. Data Science for Nano Image Analysis. Data Science for Nano Image Analysis 277 321 .

Chiwoo Park & Yu Ding. (2019) Automating material image analysis for material discovery. MRS Communications 9:2, pages 545-555.
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Directional Statistics of Preferential Orientations of Two Shapes in Their Aggregate and Its Application to Nanoparticle Aggregation

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

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