Surface Insulation Resistance Degradation and Electrochemical Migration on Printed Circuit Boards

Widespread adoption of lead-free materials and processing for printed circuit board (PCB) assembly has raised reliability concerns regarding surface insulation resistance (SIR) degradation and electrochemical migration (ECM). As PCB conductor spacings decrease, electronic products become more susceptible to these failures mechanisms, especially in the presence of surface contamination and flux residues which might remain after no-clean processing. Moreover, the probability of failure due to SIR degradation and ECM is affected by the interaction between physical factors (such as temperature, relative humidity, electric field) and chemical factors (such as solder alloy, substrate material, no-clean processing). Current industry standards for assessing SIR reliability are designed to serve as short-term qualification tests, typically lasting 72 to 168 hours, and do not provide a prediction of reliability in long-term applications. The risk of electrochemical migration with lead-free assemblies has not been adequately investigated. Furthermore, the mechanism of electrochemical migration is not completely understood. For example, the role of path formation has not been discussed in previous studies. Another issue is that there are very few studies on development of rapid assessment methodologies for characterizing materials such as solder flux with respect to their potential for promoting ECM. In this dissertation, the following research accomplishments are described: 1). Long-term temp-humidity-bias (THB) testing over 8,000 hours assessing the reliability of printed circuit boards processed with a variety of lead-free solder pastes, solder pad finishes, and substrates. 2). Identification of silver migration from Sn3.5Ag and Sn3.0Ag0.5Cu lead-free solder, which is a completely new finding compared with previous research. 3). Established the role of path formation as a step in the ECM process, and provided clarification of the sequence of individual steps in the mechanism of ECM: path formation, electrodeposition, ion transport, electrodeposition, and filament formation. 4). Developed appropriate accelerated testing conditions for assessing the no-clean processed PCBs' susceptibility to ECM: a). Conductor spacings in test structures should be reduced in order to reflect the trend of higher density electronics and the effect of path formation, independent of electric field, on the time-to-failure. b). THB testing temperatures should be modified according to the material present on the PCB, since testing at 85oC can cause the evaporation of weak organic acids (WOAs) in the flux residues, leading one to underestimate the risk of ECM. 5). Correlated temp-humidity-bias testing with ion chromatography analysis and potentiostat measurement to develop an efficient and effective assessment methodology to characterize the effect of no-clean processing on ECM.

Modeling the Effects of Habitat Fragmentation on the Movements of the Mongolian Gazelle in the Eastern Mongolian Steppe

The Mongolian gazelle, Procapra gutturosa, resides in the immense and dynamic ecosystem of the Eastern Mongolian Steppe. The Mongolian Steppe ecosystem dynamics, including vegetation availability, change rapidly and dramatically due to unpredictable precipitation patterns. The Mongolian gazelle has adapted to this unpredictable vegetation availability by making long range nomadic movements. However, predicting these movements is challenging and requires a complex model. An accurate model of gazelle movements is needed, as rampant habitat fragmentation due to human development projects - which inhibit gazelles from obtaining essential resources - increasingly threaten this nomadic species. We created a novel model using an Individual-based Neural Network Genetic Algorithm (ING) to predict how habitat fragmentation affects animal movement, using the Mongolian Steppe as a model ecosystem. We used Global Positioning System (GPS) collar data from real gazelles to “train” our model to emulate characteristic patterns of Mongolian gazelle movement behavior. These patterns are: preferred vegetation resources (NDVI), displacement over certain time lags, and proximity to human areas. With this trained model, we then explored how potential scenarios of habitat fragmentation may affect gazelle movement. This model can be used to predict how fragmentation of the Mongolian Steppe may affect the Mongolian gazelle. In addition, this model is novel in that it can be applied to other ecological scenarios, since we designed it in modules that are easily interchanged.