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Machine Learning Analysis for Photo-Induced Phenomena of 1-Methyl-3-(N-(1,8- Naphthalimidyl)ethyl)imidazolium Salts

20 November 2020, Version 1
Working Paper
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

1-Methyl-3-(N-(1,8-naphthalimidyl)ethyl)imidazolium (MNEI) salts show various photochemical phenomena depending on the guest anion. We used machine learning techniques to extract decisive factors that dominate the fate of MNEI salts after UV irradiation and prepared a decision tree diagram to deduce their photochemical phenomena before experiments.

Keywords

anion sensor
decision tree
density functional theory

Supplementary materials

Title
Description
Actions
Title
MNEI SI
Description
Actions

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Version History

Nov 20, 2020 Version 1

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The content is available under CC BY NC ND 4.0 [opens in a new tab]

DOI

10.26434/chemrxiv.13259726.v1
D O I: 10.26434/chemrxiv.13259726.v1 [opens in a new tab]

Author’s competing interest statement

There are no conflicts of interest to declare.

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