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Utilizing Similarity Measures to Map Chemical Reactivity.

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This study introduces a new chemically agnostic method for real-time reactivity monitoring using spectroscopy. This approach enables autonomous chemical synthesis by analyzing spectral data without prior mechanistic knowledge.

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Area of Science:

  • Chemical Synthesis
  • Spectroscopy
  • Chemical Kinetics

Background:

  • Autonomous chemical synthesis requires real-time reactivity assessment.
  • Current methods rely on predefined models or intuition, limiting adaptability.
  • A generalizable, data-driven approach is needed.

Purpose of the Study:

  • To develop a chemically agnostic method for quantifying reactivity dynamics.
  • To enable real-time monitoring of chemical reactions using in-situ spectroscopic data.
  • To advance autonomous chemical synthesis platforms.

Main Methods:

  • Utilized similarity metrics applied to the full informational content of in-situ spectroscopic data (NMR, UV/Vis, IR, EPR).
  • Quantified spectral similarity trajectories to track reaction progress and kinetics.
  • Demonstrated the approach across diverse reaction classes without reaction-specific tuning.

Main Results:

  • Spectral similarity trajectories reliably indicated reaction progress and detected kinetic features like autocatalysis.
  • Successfully resolved complex behaviors including chemical oscillations (e.g., Belousov Zhabotinsky reaction).
  • Enabled end-point detection and kinetic profiling, exemplified by lophine formation kinetics.

Conclusions:

  • Established a generalizable framework for real-time, data-driven reactivity monitoring.
  • This method is a critical step toward autonomous synthesis guided by multidimensional spectroscopic feedback.
  • The chemically agnostic approach enhances adaptability and broad applicability in chemical research.