Chemical feature-based machine learning model for predicting photophysical properties of BODIPY compounds: density functional theory and quantitative structure–property relationship modeling

Related articles

1. Integrated 2D- and 3D-QSAR Modeling Reveals Structural Determinants Governing the Bioactivity of Triazine Derivatives Against COPD

   This article has 3 authors:

   1. Ajay Singh
   2. Sushil K. Kashaw
   3. Ajay Kumar Verma

2. Data-Driven Process–Structure–Property Framework for the Design, Understanding, and Prediction of Sustainable Polymers

   This article has 7 authors:

   1. Yoshifumi Amamoto
   2. Hiroteru Kikutake
   3. Ken Kojio
   4. Atsushi Takahara
   5. Kei Hirose
   6. Maiya Hori
   7. Kei Terayama

3. Machine learning interatomic potential for the structural properties iron oxides

   This article has 11 authors:

   1. Alberto Torres
   2. Alan Barros de Oliveira
   3. Mathus dos Santos Barbosa
   4. Leonardo Villegas Lelovsky
   5. Valdirene Resende
   6. Flávio Dutra
   7. Felipe Pimenta
   8. Fabricio Parreira
   9. Amaury de Mello Souza
   10. Matheus Josué Souza Matos
   11. Alexandre Reily Rocha