ZwickRoell high-temperature testing machines open up new ranges of application for fem

The Research Institute for Precious Metals and Metal Chemistry (fem) provides the development and production, processing and metallurgical testing and characterization of metallic materials for the jewellery, watch, dental and electrical industries. These include alloys and composites whose structures and microstructures are investigated with regard to their mechanical, thermal and functional properties. Particular attention is paid to the relationships between the production, processing and mechanical loading of materials and alloys in practical use.
1x1 Maytec furnace extensometer

The two materials testing machines were installed at the end of 2015. Key factors in the Institute’s decision to acquire the testing machines from ZwickRoell were high extensometer accuracy, precise control and the ability to define test sequences freely. The RetroLine is equipped with a temperature chamber, allowing to perform tests in a temperature range from -70°C to +200°C. In particular, strain-controlled test sequences (e.g. stress relaxation tests at temperatures up to 250°C) are conducted with the ZwickRoell testing systems in the fem laboratory.

The Z100 AllroundLine testing machine includes a high-temperature furnace and extensometer and is used for tests in air at elevated temperatures up to 1,250°C (e.g. high-temperature tensile strength test, creep strength test, determination of high-temperature shape memory properties). Materials tested include precious metal alloys, copper materials for electrical applications, samples produced by additive manufacturing processes or by investment casting.

makroXtens for tests at room temperature

Material data of numerous tensile and creep relaxation tests of CuNiSi alloys have been determined between room temperature and 200°C. Such data are the basis for the modelling and simulation of stress relaxation phenomena that occur during application in electric contacts. This model enables an accurate prediction of the component behavior in service.

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