Role of bonding time and temperature on the physical properties of coupled anisotropic conductive–nonconductive adhesive film for flip chip on glass technology

Using thermosetting epoxy based conductive adhesive films for the flip chip interconnect possess a great deal of attractions to the electronics manufacturing industries due to the ever increasing demands for miniaturized electronic products. Adhesive manufacturers have taken many attempts over the last decade to produce a number of types of adhesives and the coupled anisotropic conductive-nonconductive adhesive film is one of them. The successful formation of the flip chip interconnection using this particular type of adhesive depends on, among factors, how the physical properties of the adhesive changes during the bonding process. Experimental measurements of the temperature in the adhesive have revealed that the temperature becomes very close to the required maximum bonding temperature within the first 1s of the bonding time. The higher the bonding temperature the faster the ramp up of temperature is. A dynamic mechanical analysis (DMA) has been carried out to investigate the nature of the changes of the physical properties of the coupled anisotropic conductive-nonconductive adhesive film for a range of bonding parameters. Adhesive samples that are pre-cured at 170, 190 and 210°C for 3, 5 and 10s have been analyzed using a DMA instrument. The results have revealed that the glass transition temperature of this type of adhesive increases with the increase in the bonding time for the bonding temperatures that have been used in this work. For the curing time of 3 and 5s, the maximum glass transition temperature increases with the increase in the bonding temperature, but for the curing time of 10s the maximum glass transition temperature has been observed in the sample which is cured at 190°C. Based on these results it has been concluded that the optimal bonding temperature and time for this kind of adhesive are 190°C and 10s, respectively.

Uncertainty analysis to minimise risk in designing micro-electronics manufacturing processes

A design methodology based on numerical modelling, integrated with optimisation techniques and statistical methods, to aid the process control of micro and nano-electronics based manufacturing processes is presented in this paper. The design methodology is demonstrated for a micro-machining process called Focused Ion Beam (FIB). This process has been modelled to help understand how a pre-defined geometry of micro- and nano- structures can be achieved using this technology. The process performance is characterised on the basis of developed Reduced Order Models (ROM) and are generated using results from a mathematical model of the Focused Ion Beam and Design of Experiment (DoE) methods. Two ion beam sources, Argon and Gallium ions, have been used to compare and quantify the process variable uncertainties that can be observed during the milling process. The evaluations of the process performance takes into account the uncertainties and variations of the process variables and are used to identify their impact on the reliability and quality of the fabricated structure. An optimisation based design task is to identify the optimal process conditions, by varying the process variables, so that certain quality objectives and requirements are achieved and imposed constraints are satisfied. The software tools used and developed to demonstrate the design methodology are also presented.

Optimisation methodology for risk mitigation in advanced micro-system electronics manufacturing

This paper presents a design methodology based on numerical modelling, integrated with optimisation techniques and statistical methods, to aid the development of new advanced technologies in the area of micro and nano systems. The design methodology is demonstrated for a micro-machining process called Focused Ion Beam (FIB). This process has been modelled to provide knowledge of how a pre-defined geometry can be achieved through this direct milling. The geometry characterisation is obtained using a Reduced Order Models (ROM), generated from the results of a mathematical model of the Focused Ion Beam, and Design of Experiment (DoE) methods. In this work, the focus is on the design flow methodology which includes an approach on how to include process parameter uncertainties into the process optimisation modelling framework. A discussion on the impact of the process parameters, and their variations, on the quality and performance of the fabricated structure is also presented. The design task is to identify the optimal process conditions, by altering the process parameters, so that certain reliability and confidence of the application is achieved and the imposed constraints are satisfied. The software tools used and developed to demonstrate the design methodology are also presented.