The database of spectroscopic constants of diatomic molecules (DSCDM): A dynamic and user-friendly interface for molecular physics and spectroscopy

Yueqian Wang; Daniel Julian; Mahmoud A.E. Ibrahim; Connor Chin; Saketh Bhattiprolu; Ethan Franco; Jesús Pérez-Ríos

doi:10.1016/j.jms.2023.111848

The database of spectroscopic constants of diatomic molecules (DSCDM): A dynamic and user-friendly interface for molecular physics and spectroscopy

Yueqian Wang
, Daniel Julian
, Mahmoud A.E. Ibrahim
, Connor Chin
, Saketh Bhattiprolu
, Ethan Franco
, Jesús Pérez-Ríos

Physics and Astronomy

Stony Brook University

Stony Brook University

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

We present the database of spectroscopic constants of diatomic molecules (DSCDM), a website dedicated to the spectroscopic constants of ground and excited states of diatomics (https://dscdm.physics.stonybrook.edu). The database can be improved based on community feedback: the community as contributors may upload new data. Additionally, it counts on an Application Programming Interface (API) for molecular spectroscopy data retrieval to make the search process more efficient. On the other hand, the website presents a machine learning predictor of spectroscopic constants based on atomic properties and a new plotting tool to study the statistical distribution of spectroscopic constants.

Original language	English
Article number	111848
Journal	Journal of Molecular Spectroscopy
Volume	398
DOIs	https://doi.org/10.1016/j.jms.2023.111848
State	Published - Nov 1 2023

Keywords

Diatomic molecules
Machine learning
Spectroscopic constants

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10.1016/j.jms.2023.111848

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title = "The database of spectroscopic constants of diatomic molecules (DSCDM): A dynamic and user-friendly interface for molecular physics and spectroscopy",

abstract = "We present the database of spectroscopic constants of diatomic molecules (DSCDM), a website dedicated to the spectroscopic constants of ground and excited states of diatomics (https://dscdm.physics.stonybrook.edu). The database can be improved based on community feedback: the community as contributors may upload new data. Additionally, it counts on an Application Programming Interface (API) for molecular spectroscopy data retrieval to make the search process more efficient. On the other hand, the website presents a machine learning predictor of spectroscopic constants based on atomic properties and a new plotting tool to study the statistical distribution of spectroscopic constants.",

keywords = "Diatomic molecules, Machine learning, Spectroscopic constants",

author = "Yueqian Wang and Daniel Julian and Ibrahim, \{Mahmoud A.E.\} and Connor Chin and Saketh Bhattiprolu and Ethan Franco and Jes{\'u}s P{\'e}rez-R{\'i}os",

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doi = "10.1016/j.jms.2023.111848",

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T1 - The database of spectroscopic constants of diatomic molecules (DSCDM)

T2 - A dynamic and user-friendly interface for molecular physics and spectroscopy

AU - Wang, Yueqian

AU - Julian, Daniel

AU - Ibrahim, Mahmoud A.E.

AU - Chin, Connor

AU - Bhattiprolu, Saketh

AU - Franco, Ethan

AU - Pérez-Ríos, Jesús

PY - 2023/11/1

Y1 - 2023/11/1

N2 - We present the database of spectroscopic constants of diatomic molecules (DSCDM), a website dedicated to the spectroscopic constants of ground and excited states of diatomics (https://dscdm.physics.stonybrook.edu). The database can be improved based on community feedback: the community as contributors may upload new data. Additionally, it counts on an Application Programming Interface (API) for molecular spectroscopy data retrieval to make the search process more efficient. On the other hand, the website presents a machine learning predictor of spectroscopic constants based on atomic properties and a new plotting tool to study the statistical distribution of spectroscopic constants.

AB - We present the database of spectroscopic constants of diatomic molecules (DSCDM), a website dedicated to the spectroscopic constants of ground and excited states of diatomics (https://dscdm.physics.stonybrook.edu). The database can be improved based on community feedback: the community as contributors may upload new data. Additionally, it counts on an Application Programming Interface (API) for molecular spectroscopy data retrieval to make the search process more efficient. On the other hand, the website presents a machine learning predictor of spectroscopic constants based on atomic properties and a new plotting tool to study the statistical distribution of spectroscopic constants.

KW - Diatomic molecules

KW - Machine learning

KW - Spectroscopic constants

UR - https://www.scopus.com/pages/publications/85175628927

U2 - 10.1016/j.jms.2023.111848

DO - 10.1016/j.jms.2023.111848

M3 - Article

SN - 0022-2852

VL - 398

JO - Journal of Molecular Spectroscopy

JF - Journal of Molecular Spectroscopy

M1 - 111848

ER -

The database of spectroscopic constants of diatomic molecules (DSCDM): A dynamic and user-friendly interface for molecular physics and spectroscopy

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