COMBIgor: Data-Analysis Package for Combinatorial Materials Science

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 A.

doi:10.1021/acscombsci.9b00077

Title: COMBIgor: Data-Analysis Package for Combinatorial Materials Science

Journal Article · Thu May 23 00:00:00 EDT 2019 · ACS Combinatorial Science

DOI:https://doi.org/10.1021/acscombsci.9b00077· OSTI ID:1524326

^[1]; Bauers, Sage R. ^[2];

^[1];

^[1]; Heinselman, Karen N. ^[2]; Khan, Imran ^[2]; Roberts, Dennice M. ^[3]; Jacobson, Valerie ^[1]; Mis, Allison ^[1]; Brennecka, Geoff L. ^[4]; Perkins, John D. ^[2];

^[2]

National Renewable Energy Lab. (NREL), Golden, CO (United States); Colorado School of Mines, Golden, CO (United States)
National Renewable Energy Lab. (NREL), Golden, CO (United States)
National Renewable Energy Lab. (NREL), Golden, CO (United States); Univ. of Colorado, Boulder, CO (United States)
Colorado School of Mines, Golden, CO (United States)

Combinatorial experiments involve synthesis of sample libraries with lateral composition gradients requiring spatially-resolved characterization of structure and properties. Here, due to 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, designed to offer a systematic approach to loading, storing, processing, and visualizing combinatorial data sets. 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.

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Research Organization:: Energy Frontier Research Centers (EFRC) (United States). Center for Next Generation of Materials by Design: Incorporating Metastability (CNGMD); National Renewable Energy Lab. (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: AC36-08GO28308

OSTI ID:: 1524326

Report Number(s):: NREL/JA-5K00-73859

Journal Information:: ACS Combinatorial Science, Vol. 21, Issue 7; ISSN 2156-8952

Publisher:: American Chemical Society (ACS)Copyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 43 works

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Ternary nitride semiconductors in the rocksalt crystal structure Bauers, Sage R.; Holder, Aaron; Sun, Wenhao Proceedings of the National Academy of Sciences, Vol. 116, Issue 30 https://doi.org/10.1073/pnas.1904926116	journal	July 2019
Templated Growth of Metastable Polymorphs on Amorphous Substrates with Seed Layers Han, Yanbing; Trottier, Ryan; Siol, Sebastian Physical Review Applied, Vol. 13, Issue 1 https://doi.org/10.1103/physrevapplied.13.014012	journal	January 2020
Wurtzite materials in alloys of rock salt compounds Han, Yanbing; Millican, Samantha L.; Liu, Jun Journal of Materials Research, Vol. 35, Issue 8 https://doi.org/10.1557/jmr.2019.402	journal	January 2020

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