A database of elemental compositions of architectural float glass samples measured by LA-ICP-MS

• Published in: Data in brief Vol. 30; p. 105449
• Main Authors: Park, Soyoung, Carriquiry, Alicia, Horkley, L. Kenneth, Peate, David W.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Inc 01-06-2020; Elsevier
• Subjects: Chemical compositions; Chemistry; Float glass analysis; Forensic analysis; LA-ICP-MS; Statistics; Trace evidence; Trace evidence; LA-ICP-MS; Forensic analysis; Float glass analysis; Statistics; Chemical compositions
• ISSN: 2352-3409; 2352-3409
• DOI: 10.1016/j.dib.2020.105449

We measured the elemental chemical composition of architectural float glass fragments using inductively coupled mass spectrometry with a laser ablation add-in. Measurements of 18 elemental concentrations were obtained from each fragment at each measurement occasion. These data can be used for statistical analysis with the purpose of evaluating forensic trace evidence. The data collection and measurement process in this database were carefully designed by the authors to enable understanding similarities and differences in elemental composition within a fragment, between fragments within a pane, between panes produced by the same manufacturer, and between manufacturers, to help in forensic glass evaluation. We received 48 panes that were produced on consecutive days, from two glass manufacturers in the U.S. Half of each pane was broken into small fragments and 24 fragments were randomly sampled from each half pane. To compute well-conditioned estimates of high-dimensional covariance matrices at all levels, we replicated measurements on each fragment; for three of the 24 fragments from a pane, we obtained 20 replicate measurements, and for the other 21 fragments, we made five replicate measurements. Analytical procedures to carry out the measurements followed the protocols recommended for forensic float glass samples by ENFSI [1] and the ASTM [2]. The database described in this article is related to two published research articles, “Learning algorithms to evaluate forensic glass evidence” by Park and Carriquiry (2019) [3] and “Evaluation and comparison of methods for forensic glass source conclusions” by Park and Tyner (2019) [4].