Dataset for "Photophysics of HBI-based Probes: An Interpretable Machine Learning and DFT-Integrated Framework for Data-Driven Discovery of Structure–Property Relationships"

Name: Dataset for "Photophysics of HBI-based Probes: An Interpretable Machine Learning and DFT-Integrated Framework for Data-Driven Discovery of Structure–Property Relationships"
Creator: shuai zhang
Published: 2026-05-08T06:47:17.174Z
Keywords: Quantum Chemistry Composite Methods

zhang, shuai; liu, yide; liu, xing; wang, chunlei; yang, shouning; Yang, Huayan

doi:10.17632/d9gr727tdp.1

Dataset for "Photophysics of HBI-based Probes: An Interpretable Machine Learning and DFT-Integrated Framework for Data-Driven Discovery of Structure–Property Relationships"

Published: 8 May 2026| Version 1 | DOI: 10.17632/d9gr727tdp.1

Contributors:

shuai zhang, yide liu, xing liu, chunlei wang, shouning yang, Huayan Yang

Description

In this dataset, the files contains the set of code and data necessary to replicate the results in the article "Photophysics of HBI-based Probes: An Interpretable Machine Learning and DFT-Integrated Framework for Data-Driven Discovery of Structure–Property Relationships" .

Dataset for "Photophysics of HBI-based Probes: An Interpretable Machine Learning and DFT-Integrated Framework for Data-Driven Discovery of Structure–Property Relationships"

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