A database of refractive indices and dielectric constants auto-generated using ChemDataExtractor.

Area of Science:

• Materials Science
• Computational Chemistry
• Optics

Background:

• Data-driven approaches are crucial for advancing optical materials discovery.
• Extracting optical properties from scientific literature is challenging and time-consuming.
• Existing databases may not cover the breadth of optical properties found in recent research.

Purpose of the Study:

• To create a comprehensive, auto-generated database of optical properties.
• To facilitate data-driven research in optical materials science.
• To provide public access to a large repository of refractive indices and dielectric constants.

Main Methods:

• Utilized ChemDataExtractor, a natural language processing tool, for automated data extraction.
• Processed a corpus of 388,461 scientific papers.
• Compiled a database containing 49,076 refractive index and 60,804 dielectric constant records for 11,054 unique chemicals.

Main Results:

• Successfully generated the first auto-extracted database of optical properties from a large scientific literature corpus.
• The database covers linear optical properties reported over the last 30 years.
• A web interface has been developed for easy database access and searching.

Conclusions:

• The auto-generated optical property database significantly accelerates the search for material properties.
• This resource empowers data-driven design and prediction of new optical materials.
• Public availability of this database promotes further research and innovation in optical materials.