On model fitting methods for modeling polymer cure kinetics in microelectronics assembly applications
Tilford, T., Morris, J.E., Ferenets, M., Rajaguru, P.R. ORCID: 0000-0002-6041-0517, Pavuluri, S.K., Desmulliez, M.P.Y. and Bailey, C. ORCID: 0000-0002-9438-3879 (2010) On model fitting methods for modeling polymer cure kinetics in microelectronics assembly applications. In: Electronics System Integration Technology Conference, ESTC 2010 - Proceedings. IEEE Computer Society, Piscataway, USA, pp. 1-6. ISBN 9781424485536 (Print), 9781424485543 (Online) (doi:https://doi.org/10.1109/ESTC.2010.5642820)
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Abstract
This work assesses the accuracy of specific numerical models in predicting the cure kinetics of a commercially available isotropic conductive adhesive material. A series of Differential Scanning Calorimetry (DSC) analyses have been performed on the materials to determine fundamental cure data. Cure models have been fitted to these experimental data using both the traditional and Particle Swarm Optimization (PSO) fitting methods. The traditional model fitting approach indicates a significant variation in the activation energy during the cure process. The particle swarm optimization fitting method is able to provide coefficient sets for all cure models assessed. Results obtained with these models are in relatively good agreement with experimental data.
Item Type: | Conference Proceedings |
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Title of Proceedings: | Electronics System Integration Technology Conference, ESTC 2010 - Proceedings |
Additional Information: | This paper forms part of the Published Proceedings from 3rd Electronics System Integration Technology Conference, ESTC 2010 September 13, 2010 - September 16, 2010 Berlin, Germany |
Uncontrolled Keywords: | cure kinetics, cure data, particle swarm optimization |
Subjects: | Q Science > QA Mathematics T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Pre-2014 Departments: | School of Computing & Mathematical Sciences School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis School of Computing & Mathematical Sciences > Department of Computer Systems Technology School of Computing & Mathematical Sciences > Department of Mathematical Sciences |
Related URLs: | |
Last Modified: | 13 Mar 2019 11:32 |
URI: | http://gala.gre.ac.uk/id/eprint/4298 |
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