AI4Green: An Open-Source ELN for Green and Sustainable Chemistry

Area of Science:

• Organic Chemistry
• Green Chemistry
• Computational Chemistry

Background:

• Traditional laboratory notebooks lack robust data management and collaboration features.
• Integrating sustainability metrics into daily research workflows is challenging.
• There is a need for accessible tools to promote environmentally conscious chemical practices.

Purpose of the Study:

• To present AI4Green, a novel web-based Electronic Laboratory Notebook (ELN).
• To integrate green and sustainability metrics into organic chemistry research.
• To provide a platform for secure data archival, collaboration, and automated sustainability assessments.

Main Methods:

• Development of a web-based application with core ELN functionalities.
• Integration of automated green metric calculations and hazard color-coding.
• Linking to a PubChem-derived database for automatic reaction information collation.

Main Results:

• AI4Green offers secure reaction storage and team sharing capabilities.
• The system automatically calculates green metrics and highlights potential hazards.
• The application facilitates the development of auxiliary sustainability tools, such as a Solvent Guide.

Conclusions:

• AI4Green effectively promotes green and sustainable chemistry in organic synthesis.
• The ELN enhances research collaboration and data management.
• Future work will focus on providing "intelligent" sustainability suggestions based on captured reaction data.