Open AccessMachine Learning: Deep Learning Spectroscopy: Neural Networks for Molecular Excitation Spectra (Adv. Sci. 9/2019)
Author(s) -
Ghosh Kunal,
Stuke Annika,
Todorović Milica,
Jørgensen Peter Bjørn,
Schmidt Mikkel N.,
Vehtari Aki,
Rinke Patrick
Publication year - 2019
Publication title -
advanced science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.388
H-Index - 100
ISSN - 2198-3844
DOI - 10.1002/advs.201970053
Subject(s) - spectroscopy , artificial neural network , deep learning , computer science , artificial intelligence , molecular spectroscopy , deep neural networks , spectral line , physics , quantum mechanics , astronomy
With artificial intelligence (AI), we learn the relationship between molecular structure and properties. In article number 1801367 , Patrick Rinke and co‐workers build a deep learning AI spectroscopist that can make predictions for molecular spectra instantly and at no further cost for the end user. AI spectroscopy will greatly accelerate the way in which science is done and aid materials discovery and design.