2026-09-19T12:19:34Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1578202024-12-12T03:38:23Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
McGuire, Brett
Cheung, Jasmine So Yee
Massachusetts Institute of Technology. Department of Chemistry
2024-12-11T15:04:24Z
2024-12-11T15:04:24Z
2024-02
2024-12-09T18:07:52.094Z
https://hdl.handle.net/1721.1/157820
https://orcid.org/0000-0002-5864-8438
The Species-agnostic Automated Gas Analyzer (SAAGA) project aims to automate the detection and characterization of chemical compounds in a complex chemical mixture in the gas phase through experimental rotational spectroscopy and
computational tools. A database of spectroscopic data serves as the foundation of the automation pipeline for assigning
spectral lines to species. While there are existing databases available for use, we developed our custom database, named
SAAGAdb, and an application programming interface (API) to access the database to fulfill the needs of SAAGA.
SAAGAdb is designed to store structured, high quality spectroscopic data of all species not limited to astrochemically
relevant ones, enabling convenient data manipulation, integration into future automation pipelines, deployment, and
maintenance. We implemented software development best practices, including software development life cycle, continuous
integration/continuous delivery, and version control, to develop a PostgreSQL database with a Python API built on Django
with RDKit integration. The product passed all unit tests and was successfully seeded with data. With the flexibility
provided by the Django framework as well as detailed documentation of the software, SAAGAdb and its API can be easily improved and expanded in the future to suit the needs of the SAAGA project.
S.M.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright retained by author(s)
https://rightsstatements.org/page/InC-EDU/1.0/
Database and Application Programming Interface Development for Rotational Spectroscopy
Thesis
application/pdf
Master
Master of Science in Chemistry
Publication
unknown
unknown
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<Abstract>The Species-agnostic Automated Gas Analyzer (SAAGA) project aims to automate the detection and characterization of chemical compounds in a complex chemical mixture in the gas phase through experimental rotational spectroscopy and
computational tools. A database of spectroscopic data serves as the foundation of the automation pipeline for assigning
spectral lines to species. While there are existing databases available for use, we developed our custom database, named
SAAGAdb, and an application programming interface (API) to access the database to fulfill the needs of SAAGA.
SAAGAdb is designed to store structured, high quality spectroscopic data of all species not limited to astrochemically
relevant ones, enabling convenient data manipulation, integration into future automation pipelines, deployment, and
maintenance. We implemented software development best practices, including software development life cycle, continuous
integration/continuous delivery, and version control, to develop a PostgreSQL database with a Python API built on Django
with RDKit integration. The product passed all unit tests and was successfully seeded with data. With the flexibility
provided by the Django framework as well as detailed documentation of the software, SAAGAdb and its API can be easily improved and expanded in the future to suit the needs of the SAAGA project.</Abstract>
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