Quantitative Criterion for AIEgens

28 October 2020, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

We defined two novel descriptors to demonstrate the flexibility
of both chemical and electronic structures of organic
fluorescence compounds upon excitation. Classification
algorithms were introduced to predict the aggregationinduced
emission behavior from the chemical structures
based on the new descriptors. A dataset was built to train
the classifier, which is optimized to 87.3% accuracy finally.

Keywords

supervised learning
aggregation-induced emission

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