Predictive method to assess chalcogenide glass properties: bonding, density and the impact on glass properties

Abstract

This paper evaluates composition and property measurements for 267 chalcogenide glass compositions developed by researchers over the past several decades for potential use in infrared optical applications. It addresses the role and impact of chemical bonding as it relates to the physical properties for this class of materials, by applying a novel strategy to predict density, based on a new theory which assigns molecular bonding type and type contribution. This theory challenges decades of beliefs by pioneers in the field. The authors validated the models using a wealth of supportive measured density data from literature. The predictive algorithms developed in this paper are intended to aid the infrared optical engineer’s understanding of the physics and properties of bulk glass components, planar thin films and fibers for imaging and sensing devices.