journal article·2021-02

Fusion bonding of copper and silicon at -70 °C by electrochemistry

Po-Yen Chien, Lin Cheng, Cheng-Ying Liu, Jhong-En Li, Benjamin Tien-Hsi Lee

Acta Materialia· Volume 204
Publisher page

Abstract

Abstract Wafer bonding processing typically employs thermal energy to fuse two surfaces by stimulating atomic interdiffusion at high temperatures. However, we found that the fusion bonding of copper and silicon can occur at an extremely low temperature in cryo-electrochemical processing cooled by dry-ice (-20 °C) or even by liquid nitrogen (-70 °C). The results demonstrate that electrical energy can replace the thermal energy that must be used in semiconductor processes. The bonding phenomenon reproducibly occurred, and even the copper surface was not favorable for spontaneous bonding. Notably, the bonding strength of Cu/Si was very high. Even after forcibly inserting a razor at the bonding interface, a copper layer was split from the Cu host substrate to enable a transfer onto silicon. The secondary-ion mass spectrometry (SIMS) analysis revealed that the bonding was caused by nanoscale interdiffusion between surface copper and silicon atoms. We propose a possible mechanism where holes are driven into the bonding interface of Cu/Si under bias, positively charge the Cu atoms and form cations (i.e., surface activation). The electric field continuously drives Cu cations to bond with the dangling bonds on the mating silicon to form Si-Cu bonds. The Cu cations that arrive later can pass over the bonding interface and quickly diffuse into the silicon interstitials. This study of fusion bonding at -70 °C by electrochemistry-assisted interdiffusion instead of thermal energy has profound implications for wafer bonding processes and applications.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: 3D IC and TSV technologies · Electronic Packaging and Soldering Technologies · Electrostatic Discharge in Electronics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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