We have studied the corrosion of phosphorus-doped polySi when contacted to a gold metallization layer and exposed to various hydrofluoric acid (HF) based chemistries, including mixtures with HCl, C<sub>2</sub>H<sub>6</sub>O, H<sub>2</sub>O, NH<sub>4</sub>F, Triton-X-100, as well as vapor-based HF. Here, we utilize optical-, electron-, and atomic-force-microscopy, optical interferometry, as well as instrumented indentation ("nanoindentation") to characterize test and reference specimens exposed to the various HF solutions. These measurements provide information concerning the appearance, roughness, physical dimensions, hardness, elastic modulus, and reverse phase transformation activity of the various polysilicon specimens. In general, some of the chemistries produced time-dependent darkening or "staining" visibly seen on free surfaces, roughening and attack at grain boundaries, nano-scale pitting of the free surfaces, decrease in thickness, decrease in hardness and mechanical modulus, and diminished elbow and reverse excursion activity for those silicon specimens electrically connected to metal. Change in performance is attributed to the formation of a galvanic cell during the HF immersion, and the corresponding damage driven by an anodic current. The results here can be used to explain previous work, which focused on the change in performance of designated MEMS diagnostic structures.
Testing using n-detection test sets, in which a fault is detected by n (n > 1) input patterns, is being increasingly advocated to increase defect coverage. However, the data volume for an n-detection test set is often too large, resulting in high testing time and tester memory requirements. Test set selection is necessary to ensure that the most effective patterns are chosen from large test sets in a high-volume production testing environment. Test selection is also useful in a time-constrained wafer-sort environment. The authors use a probabilistic fault model and the theory of output deviations for test set selection - the metric of output deviation is used to rank candidate test patterns without resorting to fault grading. To demonstrate the quality of the selected patterns, experimental results were presented for resistive bridging faults and non-feedback zero-resistance bridging faults in the ISCAS benchmark circuits. Our results show that for the same test length, patterns selected on the basis of output deviations are more effective than patterns selected using several other methods
