<p>Electromigration in thin films is a well known failure mode for scaled microelectronics. While our understanding of electromigration physics has improved immensely in the last few decades, there are still some gaps in literature. In particular, the influence of interfaces on the mass transport rate is not well understood. Through reliability studies conducted on passivated metals films, marked improvement in electromigration lifetimes was observed. Specifically, some choices of materials for passivation appear to perform better than others. Qualitatively this improvement in electromigration performance is attributed to surface adhesion. However, a theoretical connection is largely missing in the literature. Lane et al. through in-situ electromigration experiments and separate interfacial debond experiments on sandwich specimens showed that a correlation exists between the void growth rate and the debond energy. However, a fundamental understanding of the relation between the two is missing. In this study we explore the connection between interfacial adhesion and void growth in a current driven system. Several experiments with varying test conditions are carried out on Blech-like test structures with different capping layers. The influence of these capping layers is captured through direct void growth measurements. Comparison of activation energy associated with electromigration was made against existing literature. It was found to be consistent with values reported for surface/interface dominated diffusion mechanisms. Further, an extension is proposed to the phase growth relations derived in existing literature to include the effect of surface adhesion. Interfacial adhesion energy ratios are extracted from the electromigration experiments for two of the test structures (Cu-Ta and Cu-SiNx) tested in this study. This ratio is compared to values reported in literature for the two interfaces and they show good agreement with experimental data.<br></p>

Methods are presented to acquire data from analytical ultracentrifugation experiments by computer using the absorption optical scanning system of the Beckman Model-E ultracentrifuge. A computer program was written which analyzes sedimentation velocity experiments by the van Holde - Weischet method and by the second moment method. The van Holde - Weischet method allows a high resolution analysis of sedimentation velocity data by eliminating the effects of diffusion on the shape of the moving boundary to provide sedimentation coefficients for a heterogeneous composition of a sample. The second moment method obtains the sedimentation coefficient by calculating the second moment point, by which the sedimentation coefficient is defined. Since it is impractical to manually analyze sedimentation velocity data by this method, these computer programs make an important analysis method available to the researcher. Using this computer program, it is now possible to analyze data to a higher resolution and accuracy than manual analysis of stripchart recordings would permit. Moreover, the time required for the analysis is greatly reduced. Data from sedimentation equilibrium experiments are analyzed by x² minimization. Further, a program was written for the acquisition of data to measure diffusion coefficients from quasi elastic light scattering experiments with a Langley Ford correlator. The analysis of autocorrelation spectra from light scattering experiments is performed by the Levenberg - Marquardt method, which allows fitting of data to nonlinear models. The model used allows the analysis of multicomponent systems by fitting to a sum of exponentials and a baseline. Traditional analysis of autocorrelation data by hand was limited to least squares fitting of the data to a linear model of one component without an optimized baseline, often an unrealistic approximation of the system. Analysis of autocorrelation data by nonlinear curve fitting increases both the accuracy and amount of data that can be analyzed. The development of the PPOL-1 208-n series of plasmids and of the miniplasmid pMX is described. These plasmids were designed to allow studies of in vitro transcription and chromatin structure after reconstitution with histones. The plasmids themselves were analyzed by sedimentation and diffusion studies using the computer programs. Sedimentation data is presented which suggests a new method for rapid estimation of S₀ (the sedimentation coefficient at zero concentration) for molecules which show a concentration dependency of the sedimentation coefficient. This is accomplished by linearly extrapolating van Holde Weischet distributions to zero concentration. Manual analysis of sedimentation velocity experiments to determine nonideality contributions required several experiments, computer analysis can provide this information in a single experiment due to the increased resolution of the method. Diffusion data for this plasmid DNA is used to demonstrate the feasibility of the multicomponent analysis presented here. Also, sedimentation measurements were carried out on reconstituted chromatin and on the effects of ethidium bromide on reconstituted chromatin. The programs were used to demonstrate significant changes in chromatin structure upon ethidium bromide binding. These changes involved the reduction of S of reconstituted plasmids upon addition of ethidium bromide as well as a reduction of heterogeneity of the sample. The data indicates the possibility of a forced exchange of nucleosomes between plasmids, as well as conformational changes in the chromatin structure. / Graduation date: 1993

The model-free analysis of NMR relaxation data, which is widely used for the study of protein dynamics, consists of the separation of the Brownian rotational diffusion from internal motions relative to the diffusion frame and the description of these internal motions by amplitude and timescale. Through parametric restriction and the addition of the Rex parameter a number of model-free models can be constructed. The model-free problem is often solved by initially estimating the diffusion tensor. The model-free models are then optimised and the best model is selected. Finally, the global model of all diffusion and model-free parameters is optimised. These steps are repeated until convergence. This thesis will investigate all aspects of the model-free data analysis chain. (For complete abstract open document)