Identification and localization of rotational spectra using recurrent neural networks
Patent
·
OSTI ID:1987181
A method of identifying molecular parameters in a complex mixture may include receiving a set of combined transition frequencies and analyzing the set of combined transition frequencies using a first trained artificial neural network to generate a plurality of separated transition frequency sets. Each of the plurality of separated frequency sets may be analyzed using a second trained artificial neural network to generate a respective set of estimated spectral parameters. The method may include identifying a set of molecular parameters corresponding to the set of separated transition frequencies.
- Research Organization:
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC02-06CH11357
- Assignee:
- UChicago Argonne, LLC (Chicago, IL)
- Patent Number(s):
- 11,594,304
- Application Number:
- 16/146,970
- OSTI ID:
- 1987181
- Country of Publication:
- United States
- Language:
- English
Automated assignment of rotational spectra using artificial neural networks
|
journal | September 2018 |
Artificial intelligence characterizes rotational spectroscopy
|
journal | September 2018 |
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