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Comparative dataset of experimental and computational attributes of UV/vis absorption spectra.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Beard, Edward J 
Vázquez-Mayagoitia, Álvaro 
Vishwanath, Venkatram 
Cole, Jacqueline M 

Abstract

The ability to auto-generate databases of optical properties holds great prospects in data-driven materials discovery for optoelectronic applications. We present a cognate set of experimental and computational data that describes key features of optical absorption spectra. This includes an auto-generated database of 18,309 records of experimentally determined UV/vis absorption maxima, λmax, and associated extinction coefficients, ϵ, where present. This database was produced using the text-mining toolkit, ChemDataExtractor, on 402,034 scientific documents. High-throughput electronic-structure calculations using fast (simplified Tamm-Dancoff approach) and traditional (time-dependent) density functional theory were executed to predict λmax and oscillation strengths, f (related to ϵ) for a subset of validated compounds. Paired quantities of these computational and experimental data show strong correlations in λmax, f and ϵ, laying the path for reliable in silico calculations of additional optical properties. The total dataset of 8,488 unique compounds and a subset of 5,380 compounds with experimental and computational data, are available in MongoDB, CSV and JSON formats. These can be queried using Python, R, Java, and MATLAB, for data-driven optoelectronic materials discovery.

Description

Keywords

34 Chemical Sciences, 3407 Theoretical and Computational Chemistry, Networking and Information Technology R&D (NITRD)

Journal Title

Sci Data

Conference Name

Journal ISSN

2052-4463
2052-4463

Volume Title

6

Publisher

Springer Science and Business Media LLC