journal article·2019-05Open access

Analysis of viscosity data in As2Se3, Se and Se95Te5 chalcogenide melts using the pressure assisted melt filling technique

Jaroslav Barták, Petr Koštál, Diego Valdés, Jiří Málek, Torsten Wieduwilt, Jens Kobelke, Markus A. Schmidt

Abstract

The pressure-assisted melt filling technique (PAMFT) is promising approach for integrating new materials such as glasses or semiconductor into fiber, while only a small amount of starting material (<0.1 mg) is actually required for the implementation of such hybrid optical fibers of length of several centimeters. PAMFT has also the capability to provide viscosity data of glass-forming melts determined during the filling process. The main advantage of this technique – the demand of only small amounts of material (<0.1 mg) is accompanied by the fact that the molten material is encapsulated inside a silica capillary under high pressure. Therefore, PAMFT represents a promising method for measuring highly volatile and corrosive materials, such as chalcogenides. Here we present a detailed analysis on applying PAMFT for viscosity measurement of chosen chalcogenide systems with respect to experimental conditions (applied pressure and capillary diameter) and physical materials properties (surface tension and contact angle towards silica glass). For our study, we chose two well-known chalcogenide materials (Se and As 2Se 3 ) as representatives of non-wetting and wetting liquids towards silica glass. The melt viscosities were measured in the range of 0.01–25 Pa·s showing that PAMFT is a suitable method for the determination of viscosity of chalcogenide melts providing reliable data even if in the situation the influence of surface tension and contact angle is neglected. We also present new viscosity data on Se 95Te 5 chalcogenide melt obtained using PAMFT.
Source: expertdata · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Phase-change materials and chalcogenides · Material Dynamics and Properties · Glass properties and applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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