ArticleMolecules (Basel, Switzerland)2020
SUSSOL-Using Artificial Intelligence for Greener Solvent Selection and Substitution.
Article in Molecules (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
9 citing papers in PubMed.
- Deep Eutectic Solvent-Assisted Synergistic Technologies for the Extraction of Natural Bioactive Compounds: Enhancement Mechanisms, Application Advances, and Challenges.Foods (Basel, Switzerland) · 2026Review
- The Promise and Pitfalls of Artificial Intelligence in the Evaluation of Synthetic "Greenness".ChemSusChem · 2025Article
- Interactive Knowledge-Based Kernel PCA for Solvent Selection.ACS sustainable chemistry & engineering · 2025Article
- Solvent-free synthesis of bio-basedRSC advances · 2025Article
- Application of Biobased Solvents in Asymmetric Catalysis.Molecules (Basel, Switzerland) · 2022Review
- MLSolvA: solvation free energy prediction from pairwise atomistic interactions by machine learning.Journal of cheminformatics · 2021Article
- The green solvent: a critical perspective.Clean technologies and environmental policy · 2021Review
- Editorial for the "Green Chemistry" Section in the Journal Molecules: Focus on Solvents.Molecules (Basel, Switzerland) · 2020Article
- Collagen/PCL Nanofibers Electrospun in Green Solvent by DOE Assisted Process. An Insight into Collagen Contribution.Materials (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Solvents come in many shapes and types. Looking for solvents for a specific application can be hard, and looking for green alternatives for currently used nonbenign solvents can be even harder. We describe a new methodology for solvent selection and substitution, by applying Artificial Intelligence (AI) software to cluster a database of solvents based on their physical properties. The solvents are processed by a neural network, the Self-organizing Map of Kohonen, which results in a 2D map of clusters. The resulting clusters are validated both chemically and statistically and are presented in user-friendly visualizations by the SUSSOL (Sustainable Solvents Selection and Substitution Software) software. The software helps the user in exploring the solvent space and in generating and evaluating a list of possible alternatives for a specific solvent. The alternatives are ranked based on their safety, health, and environment scores. Cases are discussed to demonstrate the possibilities of our approach and to show that it can help in the search for more sustainable and greener solvents. The SUSSOL software makes intuitive sense and in most case studies, the software confirms the findings in literature, thus providing a sound platform for selecting the most sustainable solvent candidate.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.