Title data
Schubert, Franz ; Gollner, Michael ; Kita, Jaroslaw ; Linseis, Florian ; Moos, Ralf:
Optimization of a sensor for a Tian-Calvet calorimeter with LTCC-based
sensor discs.
In: Journal of Sensors and Sensor Systems.
Vol. 5
(2016)
Issue 2
.
- pp. 381-388.
ISSN 2194-878X
DOI: https://doi.org/10.5194/jsss-5-381-2016
Project information
Project title: |
Project's official title Project's id No information MST-1304-0003//BAY182/002 |
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Project financing: |
Bayerisches Staatsministerium für Wirtschaft, Infrastruktur, Verkehr und Technologie |
Abstract in another language
In this work, it is shown how a finite element method (FEM) model of a Tian–Calvet calorimeter is used to find improvements in the sensor design to increase the sensitivity of the calorimeter. By changing the layout of the basic part of the sensor, which is a low temperature co-fired ceramics (LTCC) based sensor disc, an improvement by a factor of 3 was achieved. The model was validated and the sensors were calibrated with a set of measurements that were later used to determine the melting enthalpies and melting temperatures of indium and tin samples. Melting temperatures showed a maximum deviation of 0.2 K while the enthalpy was measured with a precision better than 1 % for most samples. The values for tin deviate by less than 2 % from literature data.
Further data
Item Type: | Article in a journal |
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Refereed: | Yes |
Institutions of the University: | Faculties > Faculty of Engineering Science Faculties > Faculty of Engineering Science > Chair Functional Materials > Chair Functional Materials - Univ.-Prof. Dr.-Ing. Ralf Moos Profile Fields > Advanced Fields > Advanced Materials Research Institutions > Research Centres > Bayreuth Center for Material Science and Engineering - BayMAT Faculties Faculties > Faculty of Engineering Science > Chair Functional Materials Profile Fields Profile Fields > Advanced Fields Research Institutions Research Institutions > Research Centres |
Result of work at the UBT: | Yes |
DDC Subjects: | 600 Technology, medicine, applied sciences > 620 Engineering |
Date Deposited: | 14 Nov 2016 08:02 |
Last Modified: | 14 Nov 2016 08:02 |
URI: | https://eref.uni-bayreuth.de/id/eprint/35112 |