Multiphysics modelling for electronics design

The future of many companies will depend to a large extent on their ability to initiate techniques that bring schedules, performance, tests, support, production, life-cycle-costs, reliability prediction and quality control into the earliest stages of the product creation process. Important questions for an engineer who is responsible for the quality of electronic parts such as printed circuit boards (PCBs) during design, production, assembly and after-sales support are: What is the impact of temperature? What is the impact of this temperature on the stress produced in the components? What is the electromagnetic compatibility (EMC) associated with such a design? At present, thermal, stress and EMC calculations are undertaken using different software tools that each require model build and meshing. This leads to a large investment in time, and hence cost, to undertake each of these simulations. This paper discusses the progression towards a fully integrated software environment, based on a common data model and user interface, having the capability to predict temperature, stress and EMC fields in a coupled manner. Such a modelling environment used early within the design stage of an electronic product will provide engineers with fast solutions to questions regarding thermal, stress and EMC issues. The paper concentrates on recent developments in creating such an integrated modeling environment with preliminary results from the analyses conducted. Further research into the thermal and stress related aspects of the paper is being conducted under a nationally funded project, while their application in reliability prediction will be addressed in a new European project called PROFIT.

Case base adaptation using solution-space metrics

In this paper we propose a generalisation of the k-nearest neighbour (k-NN) retrieval method based on an error function using distance metrics in the solution and problem space. It is an interpolative method which is proposed to be effective for sparse case bases. The method applies equally to nominal, continuous and mixed domains, and does not depend upon an embedding n-dimensional space. In continuous Euclidean problem domains, the method is shown to be a generalisation of the Shepard's Interpolation method. We term the retrieval algorithm the Generalised Shepard Nearest Neighbour (GSNN) method. A novel aspect of GSNN is that it provides a general method for interpolation over nominal solution domains. The performance of the retrieval method is examined with reference to the Iris classification problem,and to a simulated sparse nominal value test problem. The introducion of a solution-space metric is shown to out-perform conventional nearest neighbours methods on sparse case bases.

Computational modeling techniques for reliability of electronic components on printed circuit boards

This paper describes modeling technology and its use in providing data governing the assembly and subsequent reliability of electronic chip components on printed circuit boards (PCBs). Products, such as mobile phones, camcorders, intelligent displays, etc., are changing at a tremendous rate where newer technologies are being applied to satisfy the demands for smaller products with increased functionality. At ever decreasing dimensions, and increasing number of input/output connections, the design of these components, in terms of dimensions and materials used, is playing a key role in determining the reliability of the final assembly. Multiphysics modeling techniques are being adopted to predict a range of interacting physics-based phenomena associated with the manufacturing process. For example, heat transfer, solidification, marangoni fluid flow, void movement, and thermal-stress. The modeling techniques used are based on finite volume methods that are conservative and take advantage of being able to represent the physical domain using an unstructured mesh. These techniques are also used to provide data on thermal induced fatigue which is then mapped into product lifetime predictions.

Correlation of solder paste rheology with computational simulations of the stencil printing process

Soldering technologies continue to evolve to meet the demands of the continuous miniaturisation of electronic products, particularly in the area of solder paste formulations used in the reflow soldering of surface mount devices. Stencil printing continues to be a leading process used for the deposition of solder paste onto printed circuit boards (PCBs) in the volume production of electronic assemblies, despite problems in achieving a consistent print quality at an ultra-fine pitch. In order to eliminate these defects a good understanding of the processes involved in printing is important. Computational simulations may complement experimental print trials and paste characterisation studies, and provide an extra dimension to the understanding of the process. The characteristics and flow properties of solder pastes depend primarily on their chemical and physical composition and good material property data is essential for meaningful results to be obtained by computational simulation.This paper describes paste characterisation and computational simulation studies that have been undertaken through the collaboration of the School of Aeronautical, Mechanical and Manufacturing Engineering at Salford University and the Centre for Numerical Modelling and Process Analysis at the University of Greenwich. The rheological profile of two different paste formulations (lead and lead-free) for sub 100 micron flip-chip devices are tested and applied to computational simulations of their flow behaviour during the printing process.

Polychlorinated Biphenyl DDT And Dieldrin Residues In Grey Seal (Halichoerus-Grypus) Males Females And Mother-Foetus Pairs Sampled At The Farne Islands England During The Breeding-Season

PCB, DDT, DDE, dieldrin and total non-polar organohalogen residues have been determined in the blubber-lipid of grey seals (Halichoerus grypus) sampled during the 1972 breeding season (November) at the Farne Islands off the north eastern coast of England. PCBs were analysed by gas-liquid chromatography linked to a chlorine- and carbon-selective microwave plasma detector and total organohalogen residues were determined by microcoulometry. Total organohalogen residues were negatively correlated with blubber thickness and positively correlated with age in males (aged 1 to 24 y) and females (aged 5 to 38 y). However, the correlation of blubber-lipid residue with age in males depended upon the inclusion of immature (aged < 6 y) animals, and in females reflected only a small residue increment. The mean blubber organohalogen concentration of the males was significantly greater than that of the females. PCB and DDT group residue concentrations were significantly correlated. PCB, DDT, DDE and dieldrin were detected in the liver of mother/foetus pairs demonstrating transplacental movement of these residues. The possibility of the condition of the seals at breeding time influencing residue levels and of these residues influencing the health of the population is discussed.

Iron organic speciation determination in rainwater using cathodic stripping voltammetry

A sensitive method using Competitive Ligand Exchange-Adsorptive Cathodic Stripping Voltammetry (CLE-ACSV) has been developed to determine for the first time iron (Fe) organic speciation in rainwater over the typical natural range of pH. We have adapted techniques previously developed in other natural waters to rainwater samples, using the competing ligand 1-nitroso-2-naphthol (NN). The blank was equal to 0.17 ± 0.05 nM (n = 14) and the detection limit (DL) for labile Fe was 0.15 nM which is 10–70 times lower than that of previously published methods. The conditional stability constant for NN under rainwater conditions was calibrated over the pH range 5.52–6.20 through competition with ethylenediaminetetraacetic acid (EDTA). The calculated value of the logarithm of β′Fe3+3(NN)β′Fe3+(NN)3 increased linearly with increasing pH according to log β′Fe3+3(NN)=2.4±0.6×pH+11.9±3.5log β′Fe3+(NN)3=2.4±0.6×pH+11.9±3.5 (salinity = 2.9, T = 20 °C). The validation of the method was carried out using desferrioxamine mesylate B (DFOB) as a natural model ligand for Fe. Adequate detection windows were defined to detect this class of ligands in rainwater with 40 μM of NN from pH 5.52 to 6.20. The concentration of Fe-complexing natural ligands was determined for the first time in three unfiltered and one filtered rainwater samples. Organic Fe-complexing ligand concentrations varied from 104.2 ± 4.1 nM equivalent of Fe(III) to 336.2 ± 19.0 nM equivalent of Fe(III) and the logarithm of the conditional stability constants, with respect to Fe3+, varied from 21.1 ± 0.2 to 22.8 ± 0.3. This method will provide important data for improving our understanding of the role of wet deposition in the biogeochemical cycling of iron.