\dssp The asymptotic giant branch ( AGB ) phase is the penultimate stage of evolution for low- and intermediate-mass stars .
Nucleosynthesis products transported from the helium-fusing shell to the outer , cooler regions form gas molecules and dust grains whose chemistry depends on whether oxygen or carbon is more abundant on the surface .
Radiation pressure causes the oxygen- or carbon-rich dust to flow outward , dragging the gas along .
Such outflows inject a significant amount of material into the interstellar medium ( ISM ) , seeding new star formation .
AGB mass loss is thus a crucial component of galactic chemical evolution .
The Large Magellanic Cloud ( LMC ) is an excellent site for AGB studies .
Over 40,000 AGB candidates have been identified using photometric data from the Spitzer Space Telescope Surveying The Agents of a Galaxy ’ s Evolution ( SAGE ) mid-infrared ( MIR ) survey , including about 35,000 oxygen-rich , 7000 carbon-rich and 1400 “ extreme ” sources .
For the first time , SAGE photometry reveals two distinct populations of O–rich sources in the LMC : a faint population that gradually evolves into C–rich stars and a bright , massive population that circumvents this evolution , remaining O–rich .

This work aims to quantify the mass-loss return from AGB stars to the LMC , a rough estimate for which is derived from the amount of MIR dust emission in excess of that from starlight .
I show that this excess flux is a good proxy for the mass-loss rate , and I calculate the total AGB injection rate to be ( 5.9-13 ) x 10 ^ { -3 } M _ { \odot } yr ^ { -1 } .
A more accurate determination requires detailed dust radiative transfer ( RT ) modeling .
For this purpose , I present a grid of C–rich AGB models generated by the RT code 2DUST , spanning a range of effective temperatures , gravities , dust shell radii and optical depths as well as a baseline set of dust properties obtained by modeling a carbon star , data for which was acquired as part of the spectroscopic follow-up to SAGE .
AGB stars are the best laboratories for dust studies , and the development of a model grid will reinforce future research in this field .

Advisor : Margaret Meixner .