Machine learning for analyzing atomic force microscopy (AFM) images generated from polymer blends

Paruchuri, Aanish [Master of Science in Data Science Program, University of Delaware, Newark, DE 19713, USA]; Wang, Yunfei [School of Polymer Science and Engineering, University of Southern Mississippi, 118 College Drive, #5050, Hattiesburg, MS 39406, USA] (ORCID:0000000175555308); Gu, Xiaodan [School of Polymer Science and Engineering, University of Southern Mississippi, 118 College Drive, #5050, Hattiesburg, MS 39406, USA] (ORCID:0000000211233673); Jayaraman, Arthi [Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy St, Newark, DE 19713, USA, Department of Materials Science and Engineering, University of Delaware, Newark, DE 19713, USA, Data Science Institute, University of Delaware, Newark, DE, 19713, USA] (ORCID:0000000252954581)

doi:10.1039/d4dd00215f

DOE OSTI · 2475705

Machine learning for analyzing atomic force microscopy (AFM) images generated from polymer blends

Paruchuri, Aanish [Master of Science in Data Science Program, University of Delaware, Newark, DE 19713, USA]·Wang, Yunfei [School of Polymer Science and Engineering, University of Southern Mississippi, 118 College Drive, #5050, Hattiesburg, MS 39406, USA] (ORCID:0000000175555308)·Gu, Xiaodan [School of Polymer Science and Engineering, University of Southern Mississippi, 118 College Drive, #5050, Hattiesburg, MS 39406, USA] (ORCID:0000000211233673)·Jayaraman, Arthi [Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy St, Newark, DE 19713, USA, Department of Materials Science and Engineering, University of Delaware, Newark, DE 19713, USA, Data Science Institute, University of Delaware, Newark, DE, 19713, USA] (ORCID:0000000252954581)

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Abstract

In this paper, we present a new machine learning (ML) workflow with unsupervised learning techniques to identify domains within atomic force microscopy (AFM) images obtained from polymer films.

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Paruchuri, Aanish [Master of Science in Data Science Program, University of Delaware, Newark, DE 19713, USA], Wang, Yunfei [School of Polymer Science and Engineering, University of Southern Mississippi, 118 College Drive, #5050, Hattiesburg, MS 39406, USA] (ORCID:0000000175555308), Gu, Xiaodan [School of Polymer Science and Engineering, University of Southern Mississippi, 118 College Drive, #5050, Hattiesburg, MS 39406, USA] (ORCID:0000000211233673), Jayaraman, Arthi [Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy St, Newark, DE 19713, USA, Department of Materials Science and Engineering, University of Delaware, Newark, DE 19713, USA, Data Science Institute, University of Delaware, Newark, DE, 19713, USA] (ORCID:0000000252954581). 2024-12-04. Machine learning for analyzing atomic force microscopy (AFM) images generated from polymer blends. https://doi.org/10.1039/d4dd00215f

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