Cu–Cu Grain Intermixing Quantification for Hybrid Bonding Applications
- 1Lam Research Corporation, 11155 SW Leveton Drive, Tualatin, OR 97062, USA
Abstract
Cu–Cu hybrid bonding at reduced thermal budgets depends critically on reliable grain intermixing across the bonding interface. Yet interfacial evolution is still predominantly assessed qualitatively, precluding objective comparison across copper microstructures and process conditions. Here, we introduce Bond IQ, an automated image-based metrology framework that converts registered cross-sectional FIB-SEM datasets into physically interpretable descriptors using classical computer-vision methods. We apply the framework to five blanket chip-level pairings spanning three engineered copper microstructures: coarse-grain (CG), fine-grain locked (FG-L), and fine-grain thermally dynamic (FG-TD) Cu, thermocompression bonded at 210 °C for 2 h. Three coupled but distinct metrics are extracted: Bridged Interface Fraction (BIF), Interface Void Loading (IVL), and normalized Grain Penetration Depth (GPD). The symmetric CG/CG interface exhibited the weakest evolution, combining high IVL (5.4 nm) with low BIF (6.1%) and low GPD (0.20). By contrast, CG/FG-TD achieved the highest BIF (54.5%) at low IVL (0.6 nm), signifying broad but comparatively shallow bridging, whereas CG/FG-L reached the highest GPD (0.89) at moderate BIF (32.7%), indicating localized yet deeper directional grain advancement. Among symmetric fine-grained interfaces, FG-L/FG-L displayed the lowest IVL (0.5 nm), underscoring the role of fine-grain stability in void suppression. Collectively, these results demonstrate that interface bridging, void elimination, and penetration depth are governed by distinct but interrelated contributions of grain-size contrast and microstructural stability. By reducing subjective interfacial assessment to quantitative, mechanistically interpretable descriptors, Bond IQ offers a scalable route to screen copper microstructures and bonding conditions, and it can be extended to other metal–metal interfaces where microstructural evolution governs low-temperature bonding reliability.
Related
- Hybrid Grain-Core/Grain Boundary Proton Conductivity in Nanocrystalline La2Ce2O7 Thin Films at 298 - 453K
- Biodegradable Foam Synthesized from Lignin-Rich Brewer’s Spent Grain Waste with Potential Use as a Sustainable Alternative for Packaging Applications
- Selective Upcycling of Waste PET into Di(2-ethylhexyl) Terephthalate via a Hybrid Organometallic Catalytic Strategy for PVC Plasticizer Applications
- Lightweight Mechanical Performance of Hybrid Al 2 O 3 /TiO 2 Nano-Reinforced Jute Fiber Biocomposites with Polyester and Epoxy Matrices for Potential Automotive Exterior Applications
- Review of Silicon-Based Nanomaterials Fabricated via Laser Microstructuring, Electrochemical Etching, and Hybrid Microstructures: Exploring Functional Integration and Future Applications
BibTeX
@article{kumar2026cucu,
title = {{Cu–Cu Grain Intermixing Quantification for Hybrid Bonding Applications}},
author = {Ankit Kumar and Jeyavel Velmurugan and Jae Shin and Roshni Ramakrishnan and Bryan Buckalew},
journal = {Nanomaterials},
year = {2026},
month = nov,
doi = {10.3390/nano16211424},
url = {https://www.mdpi.com/2079-4991/16/21/1424},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Cu–Cu Grain Intermixing Quantification for Hybrid Bonding Applications
AU - Ankit Kumar
AU - Jeyavel Velmurugan
AU - Jae Shin
AU - Roshni Ramakrishnan
AU - Bryan Buckalew
PY - 2026
DA - 2026/11/05
JO - Nanomaterials
DO - 10.3390/nano16211424
UR - https://www.mdpi.com/2079-4991/16/21/1424
AB - Cu–Cu hybrid bonding at reduced thermal budgets depends critically on reliable grain intermixing across the bonding interface. Yet interfacial evolution is still predominantly assessed qualitatively, precluding objective comparison across copper microstructures and process conditions. Here, we introduce Bond IQ, an automated image-based metrology framework that converts registered cross-sectional FIB-SEM datasets into physically interpretable descriptors using classical computer-vision methods. We apply the framework to five blanket chip-level pairings spanning three engineered copper microstructures: coarse-grain (CG), fine-grain locked (FG-L), and fine-grain thermally dynamic (FG-TD) Cu, thermocompression bonded at 210 °C for 2 h. Three coupled but distinct metrics are extracted: Bridged Interface Fraction (BIF), Interface Void Loading (IVL), and normalized Grain Penetration Depth (GPD). The symmetric CG/CG interface exhibited the weakest evolution, combining high IVL (5.4 nm) with low BIF (6.1%) and low GPD (0.20). By contrast, CG/FG-TD achieved the highest BIF (54.5%) at low IVL (0.6 nm), signifying broad but comparatively shallow bridging, whereas CG/FG-L reached the highest GPD (0.89) at moderate BIF (32.7%), indicating localized yet deeper directional grain advancement. Among symmetric fine-grained interfaces, FG-L/FG-L displayed the lowest IVL (0.5 nm), underscoring the role of fine-grain stability in void suppression. Collectively, these results demonstrate that interface bridging, void elimination, and penetration depth are governed by distinct but interrelated contributions of grain-size contrast and microstructural stability. By reducing subjective interfacial assessment to quantitative, mechanistically interpretable descriptors, Bond IQ offers a scalable route to screen copper microstructures and bonding conditions, and it can be extended to other metal–metal interfaces where microstructural evolution governs low-temperature bonding reliability.
SN - 2079-4991
ER -