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High-Throughput Screening for Ultrafast Photochemical Reaction Discovery
Matthew Bain1, José L Godínez Castellanos1, Stephen E Bradforth1
1Department of Chemistry, University of Southern California, Los Angeles, California 90089-0482, United States.
The Journal of Physical Chemistry Letters
|October 27, 2023
Summary
High-repetition-rate lasers enable ultrafast spectroscopy for machine learning in photochemical synthesis design. This transient absorption spectrometer rapidly characterizes photoreactions, aiding excited-state process studies.
Area of Science:
- Photochemistry
- Spectroscopy
- Machine Learning
Background:
- Ultrafast spectroscopy traditionally probes model photochemical systems.
- High-repetition-rate lasers offer potential for routine analysis and machine learning integration.
Purpose of the Study:
- To develop a transient absorption spectrometer for rapid photoreaction characterization.
- To utilize machine learning in photochemical synthesis design.
- To investigate conformational effects on excited-state processes in pyrimidine nucleosides.
Main Methods:
- Integration of line scan cameras and micro-electro-mechanical grating modulators.
- Sample delivery using high-pressure liquid chromatography pumps.
- Initiation of photoreactions with ultrashort ultraviolet pulses.
Main Results:
- Demonstration of a transient absorption spectrometer capable of characterizing photoreactions in minutes.
- Rapid screening of pyrimidine nucleosides.
- Exploration of conformational modification effects on excited-state dynamics.
Conclusions:
- High-repetition-rate laser-based ultrafast spectroscopy can be a routine analysis technique.
- This approach facilitates machine learning model training for photochemical synthesis design.
- Rapid screening enables detailed studies of excited-state processes and molecular modifications.
