Learning Chemical Intuition: From Molecular Models to Neural Networks

Chemical Education

Authors

  • Magdalena Lederbauer Department of Chemistry and Applied Biosciences, ETH Zurich, Vladimir-Prelog- Weg 1, CH-8093 Zurich, Switzerland.

DOI:

https://doi.org/10.2533/chimia.2025.174

Keywords:

Digital chemistry, Machine learning, Predictive chemistry

Abstract

This article examines how both chemists and neural networks learn to predict chemical reactivity through different yet complementary frameworks, exploring how to effectively combine human chemical intuition with machine learning.

CHIMIA Vol. 79 No. 3 (2025): Innovation through Chemical Biology

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Published

2025-03-26

Issue

Vol. 79 No. 3 (2025): Innovation through Chemical Biology

Section

Columns, Conference Reports

Categories

License

Copyright (c) 2025 Swiss Chemical Society

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
M. Lederbauer, Chimia 2025, 79, 174, DOI: 10.2533/chimia.2025.174.