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In recent years, Machine Learning (ML) and Artificial Intelligence (AI) have become vital tools in advancing chemical processes and material design, particularly in developing green solvents. These technologies support sustainable development by reducing dependence on chemicals that are harmful to the environment and enhancing industrial efficiency. Solvents are essential in green chemistry, but most conventional solvents are non-renewable, toxic, or flammable. With the global solvent market reaching around 20 million tons annually, selecting sustainable solvents that align with green chemistry principles is crucial to reduce the impact and danger of chemical solvents on the environment. This review examines recent AI research trends in green chemistry and green solvents, analyzing data from the Scopus database over the past five years. Key bibliometric indicators, such as publication volume, leading authors, highly cited documents, major affiliations, and keyword distributions, were evaluated. Co-occurrence network graphs were generated using VOSviewer and CiteSpace to visualize research trends. The findings highlight the growing role of ML and AI in accelerating the discovery and optimization of green solvents, driving innovation, and reducing the environmental impact of chemical industries. This research underscores the potential of AI and ML to promote sustainable practices and advance green chemistry.

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Green Alternative Solvents and Artificial Intelligence: For a Greener and more Sustainable Future

  • 会议论文

  • 发表日期：

    2026年

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  • Raya Doraid Mohammed,
  • Alaa Qasim Hayder,
  • Noor Mahmood Sultan,
  • Rawya Z. Al-Khayat,
  • Karam. S. Sharif,
  • Abd Al-Bar Al-Farha,
  • Ali Q. Saeed

摘要

In recent years, Machine Learning (ML) and Artificial Intelligence (AI) have become vital tools in advancing chemical processes and material design, particularly in developing green solvents. These technologies support sustainable development by reducing dependence on chemicals that are harmful to the environment and enhancing industrial efficiency. Solvents are essential in green chemistry, but most conventional solvents are non-renewable, toxic, or flammable. With the global solvent market reaching around 20 million tons annually, selecting sustainable solvents that align with green chemistry principles is crucial to reduce the impact and danger of chemical solvents on the environment. This review examines recent AI research trends in green chemistry and green solvents, analyzing data from the Scopus database over the past five years. Key bibliometric indicators, such as publication volume, leading authors, highly cited documents, major affiliations, and keyword distributions, were evaluated. Co-occurrence network graphs were generated using VOSviewer and CiteSpace to visualize research trends. The findings highlight the growing role of ML and AI in accelerating the discovery and optimization of green solvents, driving innovation, and reducing the environmental impact of chemical industries. This research underscores the potential of AI and ML to promote sustainable practices and advance green chemistry.