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Polymers

Artificial Intelligence Guided Search for Chalcogenide Hybrid Materials Reveals Promising Comonomers

Strategic Insights

— 1 min read

A recent breakthrough in artificial intelligence has led to the discovery of promising comonomers for chalcogenide hybrid inorganic/organic polymers (CHIPs). Researchers from the University of Arizona, funded by the National Science Foundation, Air Force Research Laboratory, and the University of Arizona College of Science, have developed a gradient-boosted tree model that identifies high-performing CHIPs materials. The study, published in the journal Chemistry of Materials, demonstrates the potential of CHIPs to revolutionize infrared (IR) optics and create sustainable and recyclable devices.

Key Takeaways:

  • The researchers developed a gradient-boosted tree model that determines which comonomers merit further consideration as high-performing CHIPs materials.
  • The model was trained on previously calculated IR absorption data and applied to a larger set of 960,966 molecules from the GDB data set, validating the predictions for both highly transparent molecules and a set of 1000 randomly selected molecules.
  • The study found 2942 possible comonomers predicted to have better optical properties than the state-of-the-art comonomer stillene.
  • The research concluded that a set of target comonomers was identified that have potential for improving the optical properties of CHIPs materials.
  • The study highlights the potential of artificial intelligence in guiding the search for new materials and improving their performance.
  • The research was funded by the National Science Foundation, Air Force Research Laboratory, and the University of Arizona College of Science.
  • The study's authors include Thomas A. R. Purcell, Maliheh Shaban Tameh, and Veaceslav Coropceanu.

Statistics:

  • 960,966 molecules from the GDB data set were used to train and validate the model.
  • 2942 possible comonomers were predicted to have better optical properties than stillene.
  • The research identified a set of target comonomers to improve the optical properties of CHIPs materials.
  • The study was published in the journal Chemistry of Materials.
  • The research was funded by three organizations: National Science Foundation, Air Force Research Laboratory, and the University of Arizona College of Science.

Sources:

  • Artificial Intelligence Guided Search for Chalcogenide Hybrid Inorganic/organic Polymers Comonomers. Chemistry of Materials, 2025.
  • NewsRx. New Artificial Intelligence Findings from University of Arizona Discussed (Artificial Intelligence Guided Search for Chalcogenide Hybrid Inorganic/organic Polymers Comonomers). Journal of Engineering. October 20, 2025; p 1678.
  • University of Arizona. Artificial Intelligence Guided Search for Chalcogenide Hybrid Inorganic/organic Polymers Comonomers.

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