Journal:AI4Green: An open-source ELN for green and sustainable chemistry

Abstract

This paper presents the free and open-source, web-based electronic laboratory notebook (ELN) AI4Green, which combines features such as data archiving, collaboration tools, and green and sustainability metrics for organic chemistry. AI4Green offers the core functionality of an ELN, namely, the ability to store reactions securely and share them among different members of a research team. As users plan their reactions and record them in the ELN, green and sustainable chemistry is encouraged by automatically calculating green metrics and color-coding hazards, solvents, and reaction conditions. The interface links a database constructed from data extracted from PubChem, enabling the automatic collation of information for reactions. The application’s design facilitates the development of auxiliary sustainability applications, such as our Solvent Guide. As more reaction data are captured, subsequent work will focus on providing “intelligent” sustainability suggestions to the user.

Keywords: electronic laboratory notebook, ELN, green and sustainable chemistry, open-source, data sharing

Introduction

For researchers to communicate their findings between their team and the wider scientific community, data must be shared and stored. Paper-based laboratory notebooks are traditionally used to record experiments, and little has changed over the last few decades, despite the ubiquity of digital technology. Over the past 20 years, electronic laboratory notebooks (ELNs) have become more prevalent as the benefits of digitization are realized. [1] Despite this, there remains a significant barrier to the uptake of ELNs, especially in the academic community. [2] In 2017, a survey at a BioSistemika webinar revealed that only 7% of respondents used an ELN in their daily laboratory routine. [2] Another survey from the same study showed that the main barriers were the cost associated with implementing an ELN and the system’s usability.

Recently, in a comprehensive comparison of commercial and open-source ELNs, it was discovered that the majority of the 96 currently active ELNs are commercial. [3] It was also noted that open-source codebases have the advantage that users could more directly contribute to the development of new features and have more control over the underlying software. However, there is more onus on the institution to install, host, and maintain the infrastructure. Chemotion is an open-source ELN designed for synthetic chemistry with a growing user base and a strong focus on data sharing and integrity [4,5], but not a particular emphasis on green and sustainable chemistry. Another open-source solution is eLabFTW, an ELN suitable for storing data from various scientific disciplines. [6]

Research data management is fundamental to scientific research. [7] Transitioning from paper-based laboratory notebooks to ELNs is crucial for adhering to data standards when reporting and publishing studies. [8] ELNs are also vital in making data FAIR (findable, accessible, interoperable, and reusable). [9] ELNs allow data sharing among colleagues and institutions, while also facilitating public access. [10] Open science [11,12] can also be enabled using ELNs, where data is curated using a standard data format, expediting data searches and preparation for machine learning (ML), where large data sets are often required to train insightful models. Recent examples of such databases include the Open Reaction Database [13] and the Chemotion Repository. [14]

Sustainability and reducing waste are vital considerations in laboratory-based projects. "Sustainable" refers to both the environmental and socio-economic impacts of a process. [15] Making processes more sustainable is not just a requirement of government regulations. There are also the benefits of cost reductions, improved worker health and safety, and the reduction of impact on the environment. [16,17] Current software tools for green and sustainable chemistry have recently been reviewed. [18] ELNs also offer the opportunity for collecting data that can be used to monitor sustainability targets (such as the reduction of hazardous solvents) and share knowledge among colleagues. [19]

In this work, we present AI4Green, designed to fulfill the core functionality of an ELN for synthetic organic chemistry in academic and industry settings, while also encouraging green and sustainable chemistry. The software automatically presents the hazards and sustainability of an inputted reaction by calculating sustainability metrics and a color-coded assessment of solvents and reaction conditions. While the web application is open-source, the software is provided in a manner that has a low barrier to installation and hosting, has a user-friendly interface, and is easily customizable. As the number of users grows, the captured reaction data will be subsequently leveraged using ML to provide “intelligent” suggestions to users on improving their reactions’ sustainability.

Notes

This presentation is faithful to the original, with only a few minor changes to presentation. Grammar was cleaned up for smoother reading. In some cases important information was missing from the references, and that information was added.