Skip navigation

On model fitting methods for modeling polymer cure kinetics in microelectronics assembly applications

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)

[img] PDF
10_35.pdf - Published Version
Restricted to Repository staff only

Download (402kB)

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
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
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/4298

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics