@inproceedings{e2d201903b344a2a94459896f92ccc27,
title = "Nano-scale Defect Analysis Through K-Means Clustering of CuInSe2 Solar Cells with Ag and K Incorporation",
abstract = "Nano-X-ray fluorescence microscopy is used to correlate elemental inhomogeneity to device performance measured through X-ray beam induced current (XBIC). Unsupervised machine learning techniques can be useful in the processing and correlation of XRF/XBIC data. A case study using CuInSe2 solar cells treated with Ag-alloying and KF-post- deposition treatment (PDT) is presented. The implementation of K-means clustering is studied for its ability to identify statistically meaningful results from XRF/XBIC data. The procedure described may be applied to datasets of a similar nature.",
keywords = "CIS, K-means, X-ray beam induced current, X-ray fluorescence, clustering, machine learning",
author = "Tara Nietzold and Michael Stuckelberger and Trumann Walker and Nicholas Valdes and West, {Bradley M.} and Barry Lai and Shafarman, {William N.} and Bertoni, {Mariana I.}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 46th IEEE Photovoltaic Specialists Conference, PVSC 2019 ; Conference date: 16-06-2019 Through 21-06-2019",
year = "2019",
month = jun,
doi = "10.1109/PVSC40753.2019.8980709",
language = "English (US)",
series = "Conference Record of the IEEE Photovoltaic Specialists Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2164--2166",
booktitle = "2019 IEEE 46th Photovoltaic Specialists Conference, PVSC 2019",
}