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COMPUTATIONAL MODELING OF AMORPHOUS SILICON NITRIDE AS OPTICAL COATINGS FOR FUTURE GRAVITATIONAL-WAVE DETECTORS**

Abstract

The sensitivity of current gravitational-wave (GW) observatories, such as Advanced LIGO, is limited in their most sensitive frequency band (around 100 Hz) by Brownian thermal noise originating from the mirror coatings. To enhance the sensitivity of current and future detectors, coatings made from materials with reduced thermal noise are essential. Research stemming from a more advanced GW observatory would provide invaluable data for testing major astrophysical theories. One of the promising candidates for such coatings is amorphous silicon nitride (SiNₓ), particularly for cryogenic detectors. A detailed understanding of the origins of SiNₓ coatings' mechanical loss and optical absorption, in terms of their atomic and electronic structure, could be useful in guiding experimentalists toward optimal GW coating design. However, such understanding is currently lacking. My work in this project aims to fill this knowledge gap. To do so, I generate atomic models of SiNₓ by using state-of-the art Molecular Dynamics (MD) simulations with varying values of x. It has been empirically observed that Nitrogen-to-Silicon ratio, denoted to x, is critically important parameter scientists can tune to influence coating behavior. I then use quantum calculations, specifically Density Functional Theory (DFT), to compute electronic structure based on the resulting atomic structure. Using this data, we predict key properties like bond angles, geometric defects, optical band gap, and defect states. By varying x above and below the stoichiometric level (x=1.33), I will predict its effects on mechanical loss, optical absorption, and refractive index—the key performance metrics for high-performance GW detector coatings.

Acknowledgements

KSU Dept. of Science and Mathematics

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