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Assessment of XRF Technique as a Method to Measure Percent Ag in SnAg Solders for Flip Chip Applications
Keywords: Silver Composition SnAg, X-Ray Fluorescence XRF, Flip Chip
Pb-free SnAg solder has become the industry standard for fabricating flip chip interconnects. One area of interest for manufacturability of Pb-free solders is the ability to measure the %Ag composition and its variation within wafer to wafer, chip to chip, and C4 to C4. In addition, pre-solder %Ag distribution on the laminate is of interest since it contributes about 1/3 of the total flip chip volume. It is the composition of this system one needs to know in order to determine electromigration performance. There are various ways to measure solder composition, in particular the %Ag. These are divided into two categories which are invasive or non invasive referring to if solder must be removed from the wafer in order to conduct the measurement. There are a variety of invasive methods including Atomic Absorption (AA), Differential Scanning Calorimetry (DSC), Inductively Coupled Plasma (ICP) and Electron Probe Micro-Analyzer (EPMA) used with cross sections. Non-invasive methods are limited, making the development of the non-invasive X-Ray Fluorescence (XRF) technique an important step in data collection of coating thickness and composition. There are many factors which can affect the accuracy of the measurements. These include bump geometry, composition, UBM stack, bump spatial density, underlying chip wiring, tool vibration and tool parameters, such as collimator size, power levels, scan time , etc. This paper will address the implementation issues in utilizing XRF for Pb-free solder SnAg systems. The paper will describe: (1) Experimental bumping variables, (2) XRF configuration, calibration, optimized measuring methodology and the importance of having known standards with the same dimensions of the bumps being measured (3) Measuring accuracy and correlation with ICP and DSC, (4) Ag distribution study in the die and wafer level, (5) Noise factors, and (6) Current XRF technique uses and future applications
Chia-Hsin Shih, Jennifer Schuler,
STATSChipPAC, IBM
Hopewell Junction, NY
USA


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