Overview of complex organic molecule observations in protostellar systems
P. Nazari
TL;DR
This review addresses how complex organic molecules (COMs) form and vary in protostellar systems by synthesizing extensive gas-phase surveys from ALMA/SMA/NOEMA and ice-phase measurements enabled by JWST. It highlights that ice chemistry plays a crucial role in COM formation, with many gas–ice ratios showing agreement and a general abundance of icy COMs relative to methanol, though notable scatter exists due to physical structures like disks and shocks. The analysis reveals that N-bearing COMs tend to correlate with luminosity and temperature more strongly than O-bearing species, implying different formation pathways and desorption histories, while some molecules show clear chemical links and others reflect local environmental conditions. The review emphasizes the need for high-angular-resolution, large-sample gas–ice studies and predicts that upcoming surveys COMPASS and NASCENT-stars, together with continued JWST observations, will significantly advance understanding of chemical versus physical drivers in protostellar COM chemistry and its connection to cometary and planetary material.
Abstract
Complex organic molecules (COMs) have been detected abundantly at various stages of star formation, particularly in the warm protostellar phase. The progress in gas-phase measurements has been accelerated by the advent of the Atacama Large Millimeter/submillimeter Array and in ice measurements by the James Webb Space Telescope. Particularly, the community has moved from single-source studies of COMs to statistical analyses because of these powerful instruments. In this article, I review surveys that consider COMs in the gas and ice. The two takeaways from this review include; 1. Gas-phase abundance ratios for some COMs show a small difference across many objects and the ice abundance ratios show similar or higher values to the gas, both pointing to the importance of ice chemistry in COM formation, 2. Some COM ratios show larger differences across many objects which could be due to either chemical or physical effects, thus both factors need to be considered when interpreting the data.
