COMBIgor: Data-Analysis Package for Combinatorial Materials Science

Combinatorial experiments involve synthesis of sample libraries with lateral composition gradients requiring spatially resolved characterization of structure and properties. Because of the maturation of combinatorial methods and their successful application in many fields, the modern combinatorial l...

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Veröffentlicht in:ACS combinatorial science 2019-07, Vol.21 (7), p.537-547
Hauptverfasser: Talley, Kevin R, Bauers, Sage R, Melamed, Celeste L, Papac, Meagan C, Heinselman, Karen N, Khan, Imran, Roberts, Dennice M, Jacobson, Valerie, Mis, Allison, Brennecka, Geoff L, Perkins, John D, Zakutayev, Andriy
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container_end_page 547
container_issue 7
container_start_page 537
container_title ACS combinatorial science
container_volume 21
creator Talley, Kevin R
Bauers, Sage R
Melamed, Celeste L
Papac, Meagan C
Heinselman, Karen N
Khan, Imran
Roberts, Dennice M
Jacobson, Valerie
Mis, Allison
Brennecka, Geoff L
Perkins, John D
Zakutayev, Andriy
description Combinatorial experiments involve synthesis of sample libraries with lateral composition gradients requiring spatially resolved characterization of structure and properties. Because of the maturation of combinatorial methods and their successful application in many fields, the modern combinatorial laboratory produces diverse and complex data sets requiring advanced analysis and visualization techniques. In order to utilize these large data sets to uncover new knowledge, the combinatorial scientist must engage in data science. For data science tasks, most laboratories adopt common-purpose data management and visualization software. However, processing and cross-correlating data from various measurement tools is no small task for such generic programs. Here we describe COMBIgor, a purpose-built open-source software package written in the commercial Igor Pro environment and designed to offer a systematic approach to loading, storing, processing, and visualizing combinatorial data. It includes (1) methods for loading and storing data sets from combinatorial libraries, (2) routines for streamlined data processing, and (3) data-analysis and -visualization features to construct figures. Most importantly, COMBIgor is designed to be easily customized by a laboratory, group, or individual in order to integrate additional instruments and data-processing algorithms. Utilizing the capabilities of COMBIgor can significantly reduce the burden of data management on the combinatorial scientist.
doi_str_mv 10.1021/acscombsci.9b00077
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subjects COMBIgor
combinatorial data
data management
MATHEMATICS AND COMPUTING
title COMBIgor: Data-Analysis Package for Combinatorial Materials Science
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