On the application of variable frequency microwave technology for processing of individual surface mount components

Dual-section variable frequency microwave systems enable rapid, controllable heating of materials within an individual surface mount component in a chip-on=board assembly. The ability to process devices individually allows components with disparate processing requirements to be mounted on the same assembly. The temperature profile induced by the microwave system can be specifically tailored to the needs of the component, allowing optimisation and degree of cure whilst minimising thermomechanical stresses. This paper presents a review of dual-section microwave technology and its application to curing of thermosetting polymer materials in microelectronics applications. Curing processes using both conventional and microwave technologies are assessed and compared. Results indicate that dual-section microwave systems are able to cure individual surface mount packages in a significantly shorter time, at the expense of an increase in thermomechanical stresses and a greater variation in degree of cure.

Application of particle swarm optimisation to evaluation of polymer cure kinetics models

A particle swarm optimisation approach is used to determine the accuracy and experimental relevance of six disparate cure kinetics models. The cure processes of two commercially available thermosetting polymer materials utilised in microelectronics manufacturing applications have been studied using a differential scanning calorimetry system. Numerical models have been fitted to the experimental data using a particle swarm optimisation algorithm which enables the ultimate accuracy of each of the models to be determined. The particle swarm optimisation approach to model fitting proves to be relatively rapid and effective in determining the optimal coefficient set for the cure kinetics models. Results indicate that the singlestep autocatalytic model is able to represent the curing process more accurately than more complex model, with ultimate accuracy likely to be limited by inaccuracies in the processing of the experimental data.