研究目的
Investigating the effects of copper migration on the reliability of through-silicon via (TSV) structures, including detection, control, and monitoring of copper migration, and its impact on time-dependent dielectric breakdown (TDDB) lifetime.
研究成果
The study demonstrated non-destructive detection of Cu migration in TSV structures and its impact on TDDB lifetime. The Poole-Frenkel conduction mechanism was identified as dominant after degradation. The √E model provided the best prediction for TDDB lifetime. The oxidation state of Cu ions was found to change over time, influencing TDDB performance.
研究不足
The study focuses on Ti as a barrier material, and other barrier materials like TiN or TaN are not considered. The oxidation state of Cu ions changes over time, affecting TDDB lifetime, which complicates the analysis.
1：Experimental Design and Method Selection:
Non-destructive electrical characterization was performed to detect copper migration in TSV structures after various stressing conditions. Physical failure analysis was used to verify the presence of migrated copper.
2：Sample Selection and Data Sources:
A single Cu TSV blind via structure with Ti barrier and silicon dioxide (SiO2) dielectric liner on p-type Si substrate was analyzed.
3：List of Experimental Equipment and Materials:
Keithley 4200-SCS Parameter Analyzer, Cascade Microtec PM8PS probe station, optical ellipsometer, transmission electron microscopy (TEM), energy-dispersive x-ray spectroscopy (EDX), and X-ray photoelectron spectroscopy (XPS).
4：Experimental Procedures and Operational Workflow:
Samples were subjected to heat treatment at 400 °C for 30 min in nitrogen ambient to degrade the barrier. Electrical characterization was performed by plotting capacitance-voltage (C-V) and current density-electric field (J-E) curves. TDDB evaluation was conducted with positive and negative bias applied to the Cu via.
5：Data Analysis Methods:
The Poole-Frenkel conduction mechanism was fitted with experimental data. TDDB lifetime was fitted experimentally to the √E model.
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