Characterization and Metrology Development of a Copper Plating Bath for Hybrid Bonding Interconnect

Heterogeneous integration of wafer-level packaging enables more I/O counts on smaller footprints with shrinking feature sizes and pitch sizes. From C4 bump, C2 bump, and micropillar with tin/silver cap, the interconnect technology evolved into the most advanced copper-to-copper direct hybrid bonding without solder cap for high density 2.5D and 3D packaging [1]. The advantages of hybrid bonding over traditional flip-chip soldering are obvious. It enables ultra-fine pitch and small contact sizes, facilitating high I/O counts (Figures 1). This is critical for future semiconductor packaging, where devices require a larger number of connections to meet performance demands. In addition, unlike flip-chip soldering, copper to copper bonding eliminates the need for underfill, reducing parasitic capacitance, resistance, and inductance, as well as thermal resistance. New technology allows the reduced thickness of the bonded connections, nearly eliminating up to 30-micron thickness of solder balls in flip-chip technology, making possible more compact semiconductor packages. Hybrid bonding technology looks very promising for advanced packaging, but it also presents numerous challenges that require solutions for future development. Achieving a flat and clean dielectric surface through Chemical Mechanical Polishing (CMP) optimization is critical. Other aspect is the development of dielectric materials that can withstand lower annealing temperatures to minimize the potential for wafer distortion and warpage during the bonding process. Optimization of electrochemical deposition (ECD) process using acidic copper solutions can also reduce annealing time and lower annealing temperatures improving overall bonding process efficiency. Obviously, the surface condition and grain structure of electrodeposited copper plays a crucial role in the performance for direct hybrid bonding [2]. The size and distribution of the individual ““grains”” (crystal regions with a consistent orientation) within the electroplated copper layer can be influenced by plating conditions like current density and electrolyte composition. Any copper plating bath typically includes inorganic components and organic additives. Organic additives in copper plating baths affect the crystalline structure of the deposited copper layer, primarily by influencing the nucleation and growth of crystals, leading to smaller grain sizes, smoother surfaces, and a more refined texture. Additives can control the microstructure of the copper deposit by selectively adsorbing onto the growing crystal faces, inhibiting certain growth directions, and promoting others. Inorganic components also play an important role: copper salt provides a source of metal and acid concentration defines the bath conductivity. Chloride ions combine with suppressor additive forming a complex that slows down plating in selective areas. Analytical methods that are both accurate and reproducible are extremely important to monitor and maintain good performance of plating baths. To develop analytical methods, the interactions among organic additives of a commercial copper acid chemistry were investigated. The additives include a suppressor (polarizer), an accelerator (depolarizer), and a leveler (leveling agent) which acts as a secondary suppressor. The responses of organic components were examined under different electrochemical and hydrodynamic conditions, and the results suggest the suppressor, accelerator and leveler exhibit strong polarizing, moderate depolarizing, and relatively strong secondary suppressing effects, respectively. The polarization strength of the leveler additive is higher comparing to other plating processes used in semiconductor manufacturing (Figure 2). Optimized electrochemical analytical techniques were developed for the commercial chemistry and the analyses were performed with simple and automated fluidics that include a single electrochemical cell and accurate temperature control. Test were performed using robotized online analyzer. The analysis performance was evaluated in terms of accuracy against its expected concentration and repeatability, which is summarized and compared in Table 1.