The accurate prediction of molecular spectra is essential for substance discovery and structure identification, but conventional quantum chemistry methods are computationally expensive. Now, DetaNet achieves the accuracy of quantum chemistry while improving the efficiency of prediction of organic molecular spectra.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$32.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Rent or buy this article
Prices vary by article type
from$1.95
to$39.95
Prices may be subject to local taxes which are calculated during checkout
References
Abolhasani, M. & Kumacheva, E. Nat. Synth. 2, 483–492 (2023).
Delgado-Licona, F. & Abolhasani, M. Adv. Intell. Syst. 5, 2200331 (2023).
Seifrid, M. et al. Acc. Chem. Res. 55, 2454–2466 (2022).
Balan, V. et al. Materials 12, 2884 (2019).
Dreimann, J. M. et al. ACS Catal. 9, 4308–4319 (2019).
Zou, Z. et al. Nat. Comput. Sci. https://doi.org/10.1038/s43588-023-00550-y (2023).
Han, R., Ketkaew, R. & Luber, S. J. Phys. Chem. A 126, 801–812 (2022).
McGill, C., Forsuelo, M., Guan, Y. & Green, W. H. J. Chem. Inf. Model. 61, 2594–2609 (2021).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The author declares no competing interests.
Rights and permissions
About this article
Cite this article
Tetsassi Feugmo, C.G. Accurately predicting molecular spectra with deep learning. Nat Comput Sci 3, 918–919 (2023). https://doi.org/10.1038/s43588-023-00553-9
Published:
Version of record:
Issue date:
DOI: https://doi.org/10.1038/s43588-023-00553-9
