Water that is used in microelectronics should contain no particles. Fine filters are widely used to improve wet etch equipment performance. The filter is expected to reduce the number of particles in the water.
The number of particles is defined by measuring the number of defects on a wafer.
Two experiments were conducted:
The main question is - why do fine filters unexpectedly result in an increased number of defects?
What is the model of failure?
What is the solution?
This project investigates how to increase the copper removal rate during Chemical Mechanical Planarization (CMP). Functional modeling revealed that increasing H₂O₂ alone is ineffective beyond an optimum level because rapid oxidation creates a thick, passivating Cu₂O/CuO layer that must be mechanically removed. The winning direction is to balance faster oxidation with stronger mechanical removal by optimizing pad speed, abrasive concentration, pressure, conditioning, and slurry transport.
Wet cleaning is widely used in microchip manufacturing. Single wafer equipment is working as follows. A wafer rotates, and chemistry is poured from a movable nozzle. Water rinsing is performed at the end of the process. Loading of a new batch of the chemistry resulted in excursion - a strongly increased amount of defects was observed on the wafer after the processing. The project is dedicated to the failure analysis and creation of innovative solutions.
Semiconductor devices are becoming more complex and expensive. But what exactly are we paying for when we buy a computer, cellphone, or any device containing a microchip? It’s not for radically new functions—the core components remain the same: transistors and interconnections. According to Moore’s law, transistors are getting smaller, with more interconnection layers added, making the manufacturing process longer and more costly. In reality, we’re paying for the inability of engineers to efficiently solve engineering challenges. This project leverages System Functional Modeling (SFM) to analyze the IC interconnection layer and Process Functional Modeling (PFM) to evaluate its manufacturing process. These analyses aim to deepen our understanding of both the device and the production process, generating innovative solutions for cost reduction and improved efficiency.